pdfVolume 8 Issue 4 CONTENTS

Differences between Western and East Central European Patterns of Remarriage and Their Consequences for Children Living in Stepfamilies

Gabriella Erdélyi
Research Centre for the Humanities
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In the preindustrial period, children were significantly more likely to lose a parent before they reached adulthood for a number of reasons, including disease, childbed mortality, famines and wars. To secure the upbringing of surviving children (or even simply the birth of children) and to ensure economic survival, many widowed parents sought to rebuild broken families by remarrying. As a result, it was not uncommon for people to live as members of stepfamilies, either as stepchildren with halfsiblings and/or stepsiblings or as stepparents. Until divorce became largely a civil institution in the so-called West and, in the twentieth century, began to become more economically feasible and socially acceptable, stepfamilies came into being primarily because of death and not divorce. Thus, it follows that stepfamily experiences before these changes differed for children in some key aspects, while there were also important similarities on the basis of which meaningful comparisons can be made. Two articles in this thematic issue deal, however, with the history of the institution of divorce and the blended families which came up in the wake of the breakup of a marriage, since divorce in East Central Europe was, if not common, certainly not an exceptional practice, neither in Jewish nor in Protestant communities.

Burgeoning historical interest in stepfamilies began among scholars in the United States,1 where the ratio of children and adults living in stepfamilies to children and adults living in traditional families is the highest in the modern West,2 and the growing sociological and psychological secondary literature has been attempting to address this phenomenon. Stepfamilies in Europe 1400–1800, a collection of essays edited by Lyndan Warner, was perhaps the first major step in the comparative study of premodern stepfamilies.3 One of the strengths of the collection is that it reconsiders some of the findings of the extensive studies concerning remarriage patterns and examines the frequency and structures of stepfamilies which came into existence as a consequence of remarriage (such as the higher presence of stepmothers compared to stepfathers). Moreover, by analyzing a wide range of written and visual sources with a sharp eye on stepfamilies, it also constructs a cultural-historical narrative of relationships within the stepfamily, thus shedding light, for example, on the supportive and caring roles played by stepparents and step-kin and encouraging us to discard the fairytale figure and plot woven around the image of the wicked stepmother.

Our research group, which has enjoyed the funding and support of the Hungarian Academy of Sciences,4 aims to follow both lines of this research agenda, shifting the emphasis, however, from northwestern Europe and the Mediterranean, the main focus of Warner’s volume, to East Central Europe (Hungary, Romania, Russia, the Czech Republic, Slovakia, Croatia, and Poland). Moreover, as we rely on quantitative approaches, we offer more insight into the stepfamily dynamics of non-elite groups, and the ethnic and religious diversity of the region allows us to draw meaningful distinctions and comparisons within the region. Our fundamental intention in this thematic issue is to provide a clear overview of this work in progress, presenting demographic, legal, and social-historical approaches to the study of the history of the stepfamily in a variety of social, ethnic, and religious settings. The introduction below, however, focuses on the preliminary findings of our research concerning one theme, the gendered patterns of remarriage in East Central Europe and some of the consequences of these patterns for the caregiving and rearing of children in stepfamilies.

A fair amount of knowledge has been accumulated with regard to the remarriage patterns in northwestern and southern Europe (the “West”) and Asia (the “East”).5 One finding which had become common knowledge in the secondary literature is simply that, between 1500 and 1900, men remarried more frequently as well as more rapidly than women after the loss of a spouse, both in the West and the East. Even when they were already middle-aged or older, they often sought and found new wives, and the likelihood that they would remarry declined less over the course of the eighteenth and nineteenth centuries than it did among women.6 Our preliminary findings concerning East Central Europe, however, only partly correspond to this pattern of remarriage. Some divergences from the familiar model seem to have emerged. Analyses of a variety of cases and data sets done according to divergent methodologies seem to suggest that both widowers and widows, but especially widows, were more likely to remarry (less content with staying alone) than in the West.7 How can we account for this difference? What factors made it more likely that a widow would find a new spouse?

In order to answer this question, it may well help to take into consideration the fact that the intention to remarry was very much influenced by the number and ages of children a widow or widower had.8 Widowed fathers often remarried within a matter of weeks or months if they had infants who were still suckling,9 and the community itself seems, for this reason, to have been less concerned with whether or not they waited for the usual year of mourning to pass. Thus, parents with small children constituted a significant share of the people who remarried (alongside widows and widowers who had not had any children from their first marriages and thus still sought an heir or heirs). For a widowed parent with small children, remarriage served as an attempt to replace the lost parent, something children who had already reached adulthood would have needed much less. This was a salient pattern both in the East and the West (including East Central Europe), and it merits noting that in both parts of the world, widowed men with small children had less difficulty finding a new spouse (and stepmother for their children) than women with small children.10

We also identified at least one other significant difference between the patterns prevailing in the West and the patterns in East Central Europe: new marriages which were “uneven” from the perspective of age were less common than they were in the West, and this was true in areas with very different economic and social circumstances. It was the case, for instance, among the German-speaking burghers of Buda and Óbuda in the eighteenth century and in the Transylvanian city of Kolozsvár (today Cluj) and Transylvanian Székely villages in the nineteenth century.11 A widower in East Central Europe was more likely than a widower in the West to marry a widow instead of a maiden (in the West, only 20 percent of widowers who remarried married a widow, while this figure was 45.3 percent in Transylvania).12 In other words, beyond the familiar scenarios of a childless widower taking a second wife who was significantly younger and of a significantly lower social status in the hope of having an heir or a younger apprentice marrying a master’s widow in part to gain a claim to her workshop and guild membership, such uneven marriages were not a customary practice. How might one explain this difference? Given the higher mortality rates, were there simply more widows and widowers on the marriage market? Was there greater communal anxiety about single men and women? Was living in a marriage a more important factor from the perspective of social prestige and male/female honor?

The above differences, including the significantly greater frequency of marriages among widows and widowers in comparison to the situation in the West, suggests that a widow in East Central Europe had more value on the marriage market and was more interested in remarrying. One explanation for this difference may well lie in the different marital property regimes and the inheritance practices in the two parts of Europe. Clearly, one element which would have left a widow more eager to remarry is the simple fact that, in East Central Europe, she did not lose control over her properties. The mixed property regime which applied to most marriages in Hungary (there were both shared properties and individually owned properties) gave a widow more independence and more rights than regimes under which a husband acquired full control of his wife’s properties and, indeed, was the only legal entity in a marriage (one extreme but illuminating example of this was the legal doctrine of coverture, which remained part of common law in England throughout most of the nineteenth century).13 Furthermore, both in rural peasant communities and in urban communities, girls’ and women’s claims to inheritance were equal to those of men.14 It was therefore not uncommon for a widow to inherit her husband’s estates (meaning in this case plots of land worked by serfs) and to continue to manage these estates. Widows who belonged to the urban burgher class inherited half of any properties or wealth that they acquired with their husbands, and again, it was not uncommon for a widow to continue to manage these properties (including shops and businesses), at least for a time. Together with a woman’s individual properties (meaning what she had inherited from her mother and father), this wealth acquired in the course of a marriage meant that a widow seeking to remarry was often considerably wealthier than unmarried women who were seeking spouses and therefore had at least this advantage on the marriage market. In places where women were unable, legally, to inherit properties from their husbands (for instance Italy and England) and were given back only what they had brought to the marriage in dowry,15 they did not have the advantage of a financially favorable situation in the competition with unmarried women for spouses on the marriage market. This may well explain, at least partly, why a widower in these regions was more likely than a widower in East Central Europe to choose an unmarried woman as his bride. Thus, in Hungary, whether they belonged to the peasantry or the urban burgher community, widows were both more appealing as potential mates than widows in the West and they were also more likely to consider remarrying, as remarriage did not threaten their financial independence.

Furthermore, over the course of the eighteenth and nineteenth centuries, married women in the West lost rights to own properties independently, a tendency which the ethos of motherhood and the home may have been used to conceal. In contrast, no similar trends have been identified in Hungary.16 As a consequence, at least in part, of these factors, widows were less likely to remain single, including widows with young children.

How did these differences between the remarriage patterns in the West and patterns in East Central Europe affect the experiences of children? What influence did the stronger inclination among widowed parents in East Central Europe to remarry have on their lives, or the fact that many of the stepmothers in these new marriages were not young women who had been unmarried before they came into the broken families, but rather were themselves mothers with small children from an earlier marriage? Demographers tend to examine how deaths and remarriages of mothers and fathers affect their children’s likelihood of surviving, marrying, and moving out of the parental home.17 While they tend to agree that a mother’s death posed the single greatest threat to her children’s changes of survival,18 this simple picture becomes more complex when one takes into consideration the effects of the arrival into a family of a stepmother.19 The beneficial influence of a stepmother on the mortality rates of children in Sweden and China in the eighteenth and nineteenth centuries, for instance, are clear, though in some regions, such as Quebec (within New France), mortality rates among children living with a stepmother were the same as mortality rates among children whose fathers did not remarry. Indeed, in the case of one German community in the eighteenth century, the arrival of a stepmother actually increased mortality among children from the previous marriage, especially girls.20 However, Péter Őri’s analysis of child mortality in the market town of Zsámbék (in Hungary, near Budapest), which had a Catholic and German-speaking peasant and craftsmen population, pinpoints instead primarily boys on whom their father’s remarriage to a widowed woman had negative effects, especially if she brought her own children to the household.21

The question of the effects of stepfathers on stepchildren has not been given as much attention in the secondary literature. In the course of our comparative study of the questions of remarriage and stepfamilies in East Central Europe, we came across particularly interesting findings in eighteenth-century Western Bohemia. The authors Velková and Tureček narrowed the focus of their study to the fates of children five years old or younger, and they discovered that the death of the father was a particularly grave threat to the children because, when the mother was compelled to play the father’s role, this meant that she was less able to play the traditional role of a mother as caregiver. When children were between the ages of two and five, stepmothers and stepfathers essentially could replace biological parents. In other words, what was important was not a biological (“blood”) relationship, but rather the fulfillment of the role of parent as caregiver and provider.22 The articles in this thematic issue offer considerable evidence in support of this conclusion in a variety of situations.

An examination of remarriage patterns in the Romanian principalities (Moldavia and Wallachia) in the eighteenth century also calls attention to the figure of the stepfather. In practice, it was uncommon, both among the lower classes and among the social elites (the boyars) to take guardianship of children away from their mothers or to take children out from under their mothers’ care. Almost without exception, children remained with their mothers, both in cases of divorce and in cases of widowhood and even if the mother remarried. As a result, instead of the high frequency of stepmothers, as was the case in the West, stepfathers became more typical figures of family life. This practice (children remaining with their mothers instead of becoming parts of their fathers’ households, even when their mothers remarried and in spite of the fact that the society was patrilineal, both in its attitudes towards lineage and in its inheritance customs) was utterly extraordinary and contrasted starkly with practices in other parts of Europe, where the children of mothers who remarried had varying fates, but very often did not remain in their mothers’ households.23 The relationship between mother and child seems to have been particularly tight and strong, even if the control of the father’s family over children grew in parallel with the children’s inheritance. Is it possible that one factor which played a significant role in this difference was that divorce was not simply possible in the Orthodox Church, but was a relatively common practice?

And in contrast with a widow, who could reclaim her dowry and was entitled to a dower, a divorced woman often lost even her dowry and was under more economic pressure to remarry. Was this too perhaps a factor? A reading of the Church litigation records reveals cases in which the difference between law, according to which a remarried mother could not be the guardian of the children from her earlier marriage, and common practice was stark (in other words, remarried women often remained the guardians of their children in practice). Or was the bond between mother and children influenced by the distinctive aspects of female property rights and their devolution in the Romanian principalities? Was it also a factor that, in the Romanian principalities, a woman’s dowry, which she received as part of her paternal patrimony, formed part of her children’s inheritance, and thus the dowry was not given back to her family of birth even if she remarried? Remarriage, thus, did not pose any threat to the financial interests and wellbeing of the children, unlike (for instance) in the case of the Florentine aristocracy, where a woman who remarried reclaimed ownership of her dowry (more precisely, it became the property of her father and brothers) and for this reason was labeled a cruel mother by her children.24

To return to the perspective of demographers: why did children in the aforementioned eighteenth-century German community whose widowed fathers remarried end up at a disadvantage when compared to children whose widowed fathers did not remarry? Was this a consequence of neglect, abuse, undernourishment, or competition with halfsiblings and/or stepsiblings? Willführ and Gagnon, who adopted an evolutionary approach to their interpretation of the sources, suggest that in all likelihood the explanation lies not in the abuse or neglect suffered by children because of a stepmother’s indifference or hostility, but rather in the father’s and stepmother’s lack of parenting skills.25 This is an interesting hypothesis, and it is particularly thought-provoking if one takes into consideration the distinctive feature of remarriage patterns in Hungary, namely that a marriage between a widow and a widower was much more common as in the West. Given their experiences in their first marriages, widowed mothers who remarried may well have had better skills in caregiving and childrearing than new wives who had not been married or raised children before. It is not immediately obvious, of course, that fathers who were seeking to remarry necessarily took into consideration a prospective wife’s talents or experience as a caregiver for children. It is also worth considering the extent to which the relationships between husband and wife, which as noted earlier were more balanced from the perspective of age than in the West, affected relationships between stepparents and stepchildren. In our search for insights into the individual considerations of parents and experiences of children in these situations, we are compelled to rely on ego-documents. A text left by an anonymous Jewish memoirist from seventeenth-century Bohemia offers an example of one such ego-document. The author remembers his stepmother as having been very young and thus having lacked parenting skills. His stepmother, he writes, was “still a young child who did not know how to bring us up in cleanliness, as is necessary with little boys, nor could she properly care for us when we were sick.”26 The stepmother, according to her stepson, was not evil or abusive, but simply ignorant and unskilled, as she was young and lacked experience as a parent.

The research by Péter Őri, another member of our research group, throws some light on the other side of the coin. His study of child mortality suggests that widows with children of their own from a previous marriage tended to favor their children over the children brought to a second (or later) marriage by their new husbands. The arrival of a stepmother who brought older stepchildren into the household and the new family put the sons of her new husband at risk first and foremost. In the competition for resources and care, the father’s children, and in particular his sons, were at a disadvantage.27

In the period between adolescence and marriage, when childrearing became for the most part the responsibility of the father, the situation of children changed, or at least so the findings of our research group suggest. We used quantitative analyses of data from Church records of births, marriages, and deaths to identify patterns in family formation (family reconstitution) and study the fates of stepchildren. In a manner which, to my knowledge, is pioneering in the secondary literature, they examined the question of whether, in the communities on which they focused, sons and daughters from a previous marriage were at a disadvantage (as one would expect on the basis of collective fears, the law, and stereotypes) in comparison with children of a new marriage when it came to their chances for success in adulthood (including career, marriage, and social status).

On the basis of data concerning stepchildren belonging to the community of German-speaking Lutherans in the city of Pressburg (Pozsony in Hungary, today Bratislava, Slovakia), a community numbering roughly 5,000 people, it was unusual to draw distinctions between the stepchildren and children of remarried parents in the division of family wealth and resources. Boys were given instruction and taught a trade before they married, and stepdaughters were just as likely as daughters of the new marriage to find husbands whose social status matched theirs. Children inherited the social status of their biological parents, which meant that there could be differences in status between halfsiblings, and there were significant differences between the opportunities afforded to sons and the opportunities afforded to daughters, but this was the case among siblings as well, not just stepsiblings. In other words, these differences in opportunity were determined by gender, not by whether a given child was from a first or second marriage.28

The study of another community also suggested that the figure of the neglected or abused stepchild was an exception more than a rule (fairytales notwithstanding). In the 50 stepfamilies in a Transdanubian market town (Csetnek, Štítnik in Slovakia today) in the middle of the eighteenth century, halfsiblings (stepchildren and children) had the same life expectancy and the same chances of marrying.29 These findings may seem to contradict the image one has from the writings of stepchildren memoirists, who seem to have feared that when their widowed parent remarried, this would lead to their marginalization in the family.30 Should we perhaps consider the image of the stepmother as the embodiment of cruelty at least in part (perhaps in large part) a figure woven of the fears of children from first marriages? Further research is needed in order to determine the chances halfsiblings in other communities had (beyond the Slovak-speaking Catholic peasants and German-speaking Lutheran burghers), including life expectancy, career, marriage, etc.

It is worth summarizing here the initial findings of our work, which this thematic issue presents in greater detail in the individual articles. In East Central Europe, widowed spouses seem to have been somewhat more inclined (even in later periods of life) to remarry than in the West.31 Thus, single-parent families, especially with small children, were rarer in comparison with reconstituted families. Children in these stepfamilies may have been given better care and thus had better chances of survival presumably in no small part because in a marriage between a widow and a widower, which was more common than in the West, both parents were likely already to have had experience raising and providing care for children. Whatever disadvantages may have been caused by rivalries between the children brought into the new unions and their younger halfsiblings, they were offset by an attitude towards parenting according to which the parents were as responsible for raising and providing for stepchildren as they were for rearing their biological children. One of the goals of the research our group continues to pursue is to arrive at a more nuanced understanding of stepfamily formation and relationships within stepfamilies within a regionally and socially comparative framework, taking into consideration such aspects as marital property regimes, inheritance practices, kinship structures, and the cultural and religious meanings and values of kinship ties.

 

 

1 Lisa Wilson, Stepfamilies in early America (Chapel Hill: The University of North Carolina Press, 2014).

2 Rose Kreider, Daphne Lofquist, “Adopted Children and Stepchildren: 2010. Population Characteristics,” US Census Bureau (2014) April, 20–572. https://www.census.gov/library/publications/2014/demo/p20-572.html.

3 Lyndan Warner, ed., Stepfamilies in Europe, 1400–1800 (Abingdon and New York: Routledge, 2018).

4 The project entitled Integrating Families: Stepfamilies and Children in the Past, carried out by HAS Momentum Family History Research Group. http://www.families.hu/en/

5 On the extensive historiography of remarriage pattern in pre-modern Europe, see Warner, Stepfamilies, 266–67. On Japan: Satomi Kurosu, “Remarriage in a Stem Family System in Early Modern Japan,” Continuity and Change 22, no. 3 (2007): 429–58. Comparatively: Satomi Kurosu, Christer Lundh, and Marco Breschi, “Remarriage, Gender, and Rural Households: A Comparative Analysis of Widows and Widowers in Europe and Asia,” in Similarity in Difference: Marriage in Europe and Asia, 1700–1900, edited by Lundh Christer and Kurosu Satomi (Cambridge, Massachusetts, London: The MIT Press, 2014), 169–208.

6 Antoinette Fauve-Chamoux, “Revisiting the decline in remarriage in early modern Europe: the case of Rheims in France,” The History of the Family 15 (2010): 283–97.

7 On the rural context (Szekély Land, today in Romania), see Sándor Lakatos, “Házasságkötés, megözvegyülés és újraházasodás a Homoródok vidékén 1830–1939 között,” forthcoming in Özvegystratégiák és árvasorsok Magyarországon, 1550–1940, edited by Gabriella Erdélyi, Budapest 2020. Lakatos examined 2,600 marriages. In comparison with averages in the West of 10–15 percent, 21 percent of marriages involved a widow (18,3 percent) or/and a widower (16,2 percent) or a divorced man or woman. For similar results see Levente Pakot, “Megözvegyülés és újraházasodás székelyföldi rurális közösségekben, 1840–1930,” Demográfia 52 (2009): 55–88, 62–63. On urban communities, see Árpád Tóth, “Mostohasors? Mozaikcsaládokban felnőtt gyermekek érvényesülési lehetőségei a pozsonyi evangélikus közösségben, 1740–1850,” forthcoming ibid. Edina Tünde Gál, “A kolera szegényei: Árvák és özvegyek az 1873-as kolozsvári kolerajárvány után,” Ibid. Cf. Swedish remarriage patterns: Martin Dribe, Christer Lundh, “Social Norms and Human Agency: Marriage in Nineteenth Century Sweden,” in Similarity in Difference, 233.

8 Gál, “A kolera szegényei.”

9 It would be worth studying the demographics of remarriage from the perspective of breastfeeding customs. Alice Velková and Petr Tureček have taken a step in this direction: Alice Velková, Petr Tureček, “Influence of parental death on child mortality and the phenomenon of the stepfamily in western Bohemia in 1708–1834.” Forthcoming in Journal of Family History, thematic issue on stepfamilies.

10 Lundh, Kurosu, Breschi, “Remarriage, Gender,” 205. Tóth however in the same article “Mostohasors” has found that in Pressburg (Slovakia) widowed women with children remarried more often than men.

11 Eleonóra Géra, “Városi és kamarai árvák a 18. századi Budán,” forthcoming in Özvegystratégiák, Katalin Simon, “Remarriage Patterns and Stepfamily Formation in a German-speaking Market-Town in Eighteenth-Century Hungary,” in present issue of the Hungarian Historical Review; Lakatos, “Házasságkötés,” 62; Gál, “A kolera szegényei.”

12 Pakot, “Megözvegyülés,” 62. Michel Oris, Emiko Ochiai, “Family Crisis in the Context of Different Family Systems: Frameworks and Evidence,” in R. Derosas, M. Oris, eds., When Dad Died: individuals and families coping with distress in past societies (Bern: Peter Lang, 2002), 17–80. In Sweden in the nineteenth century, marriages between widows and widowers accounted for only 10 percent of the total number of remarriages. Dribe, Lundh, “Social Norms,” 235.

13 Sándor Nagy, Engesztelhetetlen gyűlölet: Válás Budapesten, 1850–1914 (Budapest, 2018), 320. On the Russain marital property regime, which was very similar to the Hungarian regime, see Barbara Alpern Engel, Breaking the Ties That Bound: The Politics of Marital Strife in Late Imperial Russia (Ithaca: Cornell University Press, 2011); Amy Louise Erickson, Women and Property in Early Modern England (London–New York: Routledge, 1993).

14 The inheritance model among the nobility, in contrast, was patrilineal. Girls were entitled to one-fourth of the patrimony, which they usually received in personal assets and money as a dowry when they married. It became theirs again if their husbands died, and this complemented the dower which they received from their husbands’ estates.

15 Jutta Sperling, “The Economics and Politics of Marriage,” in Ashgate Research Companion to Women and Gender in Early Modern Europe, ed. Couchmann Jane, Poska Allyson (Routledge, 2016), 214–30, 214.

16 Cavallo-Warner, “Introduction,” in Sandra Cavallo, Lyndan Warner, eds., Widowhood in Medieval and Early Modern Europe, (Harlow: Routledge, 1999), 13. Nagy, “Engesztelhetetlen gyűlölet,” 317–30.

17 See for example on the timing of marriage of stepchildren: Levente Pakot, “Nemek és nemzedékek: Demográfiai reprodukció a 19–20. századi Székelyföldön,” in Központi Statisztikai Hivatal Népességtdományi Intézetének Kutatási Jelentései 95 (Budapest, 2013), 83.

18 E. Beekink, F. van Poppel, A. C. Liefbroer, “Surviving the Loss of the Parent in a Nineteenth-century Duch Provincial Town,” Journal of Social History, 32 (1999): 641–69; R. Sear, R. Mace, “Who keeps children alive? A review of the effects of kin on child survival,” Evolution and Human Behavior 29 (2008):1–18.

19 S. Åckerman, U. Högberg, T. Andersson, “Survival of orphans in 19th century Sweden: The importance of remarriages.” Acta Paediatrica 85 (1996): 981–85; C. Campbell, J. Z. Lee, “When husbands and parents die: Widowhood and orphanhood in late Imperial Liaoning, 1789–1909,” in R. Derosas, M. Oris, When Dad died, 301–22.

20 Kai P. Willführ, Alain Gagnon, “Are Stepparents Always Evil? Parental Death, Remarriage, and Child Survival in Demographically Saturated Krummhörn (1720–1859) and Expanding Québec (1670–1750),” Biodemography and Social Biology 59, no. 2 (2013): 191–211.

21 Péter Őri, “Life courses in 18–19th century Hungary: the impact of the parents’ widowhood and remarriage on their children’s survival, Zsámbék, 1720–1850.” Forthcoming in Journal of Family History, thematic issue on stepfamilies.

22 Velková, Tureček, “Influence of parental death.”

23 See for example Sylvie Perrier, “Stepfamily relationships in multigenerational households: The case of Toulouse, France in the eighteenth century,” in Stepfamilies in Europe 1400–1800, ed. by Lyndan Warner (Abingdon: Routledge, 2018), 187–203. On the gender assymetry of parent-child relations after remarriage (in other words, in stepfamilies) and the possiblities of inclusive stepfamilies (i.e. remarried mothers living together with their children from their first marriages even though they could not be their guardians), see also Warner’s conlusions in the same volume, 248–52.

24 Giulia Calvi, “‘Cruel’ and ‘nurturing’ mothers: The construction of motherhood in Tuscany (1500–1800),” L’Homme 17, no. 1 (2013): 75–92.

25 Kai Willführ, Alain Gagnon, “Are Stepmothers Evil or Simply Unskilled? Infant Death Clustering in Recomposed Families,” Biodemography and Social Biology 58, no. 2 (2012): 149–61.

26 Tali Berner, “Constructions of Childhood in Early Modern Jewish Ego-Documents,” Journal of Family History 39 (2014): 101–13, 107.

27 Őri, “Life courses.”

28 Tóth, “Mostohasors?”

29 Baros-Gyimóthy Eszter, “Édesek és mostohák: Gyermeksorsok a csetneki katolikus egyházközség csonka- és mozaikcsaládjaiban, 1735–1807,” in forthcoming Özvegystratégiák.

30 Stephen Collins, “British Stepfamily Relationships, 1500–1800,” Journal of Family History 16, no. 4 (1991): 331–44.

31 On this point and only on this point, our findings correspond to Hajnal’s model of first marriages in Eastern Europe. In Eastern Europe, marriage was simply far more common. In the West, there were more people who remained unmarried. See Kurosu, Lundh, “Remarriage,” 204. Kurosu and Lundh see no correlation between marriage patterns as defined by John Hajnal and remarriage patterns.

Volume 8 Issue 2 CONTENTS

pdfDebates Concerning the Regulation of Border Rivers in the Late Middle Ages: The Case of the Mura River*

Bence Péterfi
Research Centre for the Humanities, Hungarian Academy of Sciences
peterfi.bence
@btk.mta.hu

It has been well known for ages that atypical elements of a border line, such as ditches, large trees etc., may have served as points for orientation. Literate societies, however, have had the privilege of conserving the knowledge not only by oral tradition but also by various kinds of written word. In the following, I present an especially well-documented conflict between Styrian and Hungarian families regarding the riverbed of the River Mura, which was the border of the two polities for some 20 kilometers. The debate emerged in the beginning of the sixteenth century and lasted until 1546. The Mura-question was one of the most permanent ones in the political discourse of the first third of the sixteenth century. Although we can grasp hardly any of it, the conflict involved a fear on the part of the estates of both countries that they might lose lands. First, my goal is to show the dynamics of such phenomena as an archetype of border conflicts in a nutshell. Second, I seek to identify the main reason why the conflict was so protracted and explain how eventually the issue was addressed in order to put an end to the conflict in 1546.

Keywords: Austria, Styria, Hungary, River Mur(a), river regulation, border disputes

In March 1573, the Styrian estates informed Archduke Charles II of Austria (1564–1590) that the Hungarians again had diverted the Mura River and, in doing so, had wronged the German lands. This happened despite the fact that, until then, regulation was prohibited by a strict agreement (“bis letzlich ein starkher vertrag aufgericht, dardurch die Hungarn von sollichn ihrem fürnemen abstehen müesten”).1 Within a short period of time, the Styrian estates informed the Lower Austrian Chamber of the archival research they had carried out at the request of the estates, and, though they had found some of the documents concerning the problem, they had not found the 1546 treaty.2 Some months later, Emperor Maximilian II of the Holy Roman Empire (1564–1576) himself (in part at the request of his brother, Archduke Charles II) ordered the Lower Austrian Chamber, then half a month later – this time as king of Hungary – the Hungarian Chamber, to retrieve the agreement concluded between the Kingdom of Hungary and the Duchy of Styria from their registry books.3 The archduke also contacted the Lower Austrian Chamber, from which he eventually got a copy of the treaty.4 The copy that today is held in the archive of the Styrian estates may have been produced from this version.5

What importance does this treaty have, and what was the investigation for? According to the sources, it put an end to a border conflict of different intensity which lasted a good forty years, and it had an impact which proved unusually strong, even if not put in print,6 as its strength and memory only started to fade about a generation after its conclusion. This, in the circumstances of the period, was an extraordinarily long period of time. In this article, I will sketch out in short the stages that led to the conclusion of the treaty. During the negotiations, which lasted almost two decades, the Styrian and Hungarian estates followed different and, with respect to the issue to be discussed here, in many ways contradictory legal traditions, but one may ask whether this was of any real relevance, as the success may have depended on something else. How could the parties approximate their stands to a point which generated peace for such a long time?

Permeability and Malleability of Borders

While unlike in the case of the Early Middle Ages7 there can be no doubt that each geographical/political entity had well defined borders, it would still not be appropriate to project our present ideas and preconceptions onto the Late Middle Ages. In the context of the late medieval period, one can hardly speak of state power in the modern sense, so Peter Moraw’s statement that border and border could significantly differ and the abilities of the landlords to enforce their interests could carry weight can be confirmed.8 This in many cases could hold for state borders, as these borders were also estate borders, and their keeping count – that being land or riverine border – could not differ.9 “The border of the Kingdom of Hungary is well known both for Germans and Hungarians,” wrote nobleman Ferenc Batthányi (or Batthyány) around 1529.10 On the other hand, for a given polity, conflicts that crossed borders, were obvious matters of prestige. However, because of the immature form of concluding a case, enforcing one’s interest went uneasily, therefore again, recalling Moraw’s statement cited above, much could depend on the aptitude and influence of the claimant and the other side when it came to putting an end to a dispute or conflict. The number of similar conflicts in the sources is countless, as well as the attempts to resolve them, the diversity of which starts to become clear beginning in the 1530s in the Hungarian source material.11

“Previously, people had walked straight across the boundary; aristocrats, men of letters and merchants crossed it quite naturally. The frontière only existed for soldiers and princes, and only then in time of war,” as Lucien Febvre writes in one of his essays.12 The apropos of the petition of Ferenc Battyányi, quoted above, comes from the nature of crossing the (state) borders on a daily basis: a conflict and then a lawsuit arose with the Polheim family, landowners with holdings on the other side of the River Lafnitz,13 which was the border between the Kingdom of Hungary and Styria. The Polheims therefore counted as inhabitants of the Empire. The stake was how and how much seigniorial duty the subjects of the Polheims should pay after their possessions in the estate of Battyányi which was settled by an agreement between the two families in 1546. The conflict unfolded despite the fact that in the previous century the same problem has been regulated a number of times (1429, 1440, 1452). Apart from extorting better conditions, two things can be seen behind the questioning of lordship: first, the tithe of Hungarian plots of the Styrian peasants was collected by their Styrian lords who paid it to the bishop of Győr. Second, one cannot contest that the Styrian tenants had cultivated the lands on the other side of the Lafnitz collectively since before anyone could remember, and because of the routine, these lands on the Hungarian side had been counted as part of the lands on the Styrian side of the border.14 The case in itself is extraordinary, but the problem is not, as the Austrian–Styrian burghers had vineyards in Western Hungary for centuries.15 Moreover, the mostly German speaking people who lived in the border area were in had close ties to one another, so one cannot be surprised by the appearance of some legal customs of the Empire, such as the legally binding private charters in Western Hungary.16

Some of the estate complexes in Western Hungary that got into the hands (a smaller part as pledge, the majority by arms) of Emperor Frederick III (1440–1493) or his younger brother, Archduke Albert VI of Austria (1458–1463) during the years of the civil war and weak royal power in the 1440s and 1450s in Hungary further increased the degree of interlocking and “disturbed” the perception of the border. Most of these areas remained under the authority of the Habsburgs until 1647. In some cases, they were considered part of the Archduchy of Austria, and not without any reason, since beginning in the 1530s, they were under the financial control of the Lower Austrian Chamber. Despite this, in most cases they still were considered parts of the Kingdom of Hungary. The way they were acquired, however, has been rewritten in collective memory, according to which the peace treaty of Bratislava in 1491, which put an end to the war between the Habsburgs and the Jagiellonians (who finally took the Hungarian throne in the autumn of 1490), had an important role. This treaty handled the estates that ended up under Habsburg control in all manner of ways the same way. In fact, only two of them were achieved by pledging, most of them were taken by arms unlike how the well-known narrative in the Austrian, and Hungarian scholarship goes about the 1463 contract between Emperor Frederick III and Matthias Corvinus (pledging Western Hungary for Holy Crown of Hungary held by the Emperor that time).17

Based on what has been said so far, the case of Sinnersdorf on the Styrian–Hungarian border becomes clearer. The village originally belonged to the estate complex of Bernstein in Western Hungary, which the Habsburgs acquired in the 1440s. Sinnersdorf was donated in 1499 by King Maximilian I (1493–1519) to his influential Styrian councilor, Georg von Rottal. It was then attached it to his Styrian estate complex, Thalberg. While by the mid-seventeenth century in lay matters, the settlement, otherwise in almost every direction bordered by the Hungarian Pinkafeld, became an organic part of Styria (for instance, it paid taxes to Styria), in ecclesiastic matters it still belonged under the jurisdiction of the parish of Pinkafeld, which means it was part of the bishopric of Győr. Similar problems occurred in the case of Zillingdorf and Lichtenwörth along the River Lajta, as well as in the case of four villages of the estate of Scharfeneck (Mannersdorf, Sommerein, Au, and Hof). While in the middle of the fifteenth century, the six settlements practically were torn from the Hungarian crown, in an ecclesiastic sense they still belonged to the authority of the bishop of Győr. This is how the peculiar situation arose in which the villages of the bishop of Wiener Neustadt, Zillingdorf, and Lichtenwörth, which the bishopric owned as a landlord, continued to pay the tithe to the bishop of Győr.18 This also indicates that the borders of dioceses could be more permanent than state borders.

Finally, two examples of permeability are worth mention: Hornstein, which until the mid-seventeenth century as one of the aforementioned estates in Western Hungary was under Habsburg authority, was joined to Seiberdorf on the Austrian side of the River Lajta during the fifteenth century by Ulrich von Grafeneck, and the latter became the center of the dual estate complex. The reason for this may have been the little income of the small estate complex of Hornstein and the ruined state of the castle of Hornstein.19 The Counts of Montfort administered the estate complex of Rohrau together with their Rohrau estate in the Archduchy of Austria and other lands in Hungary,20 even if their acquisition in Hungary (1419, 1435) took place only many years after their acquisition in Austria (1404). The Hungarian parts were also acknowledged by the representatives of the vendor, Count George III of Monfort, and the buyer, Leonhard von Harrach, in front of the chapter of Bratislava when, in December 1524 (i.e. significantly later), for the sake of safety, had transcribed with the chancellery of King Louis II of Hungary.21 In both cases, practical reasons and more effective farming were in the background of joining the parts of different origin, yet the border remained unchanged.

“Variations on a Theme”

Being a neighbor went with the presence of conflicts, which the parties first tried to negotiate between themselves. However, when they were unsuccessful, the parties may have had trust in the royal-imperial court(s) so that the ruler(s) would appoint some kind of committee to evaluate the causes of the disagreement. Of most border disputes one can only have a fragmented view, as in the majority of cases neither the first nor the last step in the course of the events can be known, and moreover, what is generally missing is the different opinions of the two parties. From the 1510s on the sources become more abundant. Nevertheless, the complaints of the Austrian party are much better known than those of the Hungarians because of the ways in which the sources were preserved and stored. Most of the similar documents can be found in the Österreichisches Staatsarchiv and the Austrian provincial archives (Graz, Sankt Pölten).22

The Styrian–Hungarian border was fixed along rivers in a number of its sections: for forty kilometers it ran along the abovementioned Lafnitz, for a few kilometers the Feistritz Stream, one of the tributaries of the Lafnitz, formed the border, and then, further to the south, the Mura River was the border for ca. 22–23 kilometers, followed by the River Dráva for approximately the same length, and then almost at its full length, for 90 kilometers, a tributary of the River Sava, the Sutla. Moreover, the Dráva and the Mura in the border sections are old rivers; they have numerous branches, and they are scattered with islands. This means that major floods that could change the flood plain even more than once a year always remained a source of conflicts for the people who lived by the river and worked to harness it.23

Moreover, at least in theory, in such cases, the legal stance of the two parties, here the Austrian or Styrian and the Hungarian, may have been different. According to the Roman legal tradition, which by the Late Middle Ages was used throughout the Holy Roman Empire, as a supplement in a case of riverbed changes, borders did not change. Hungarian practice, however, was the opposite (the borders moved with the river beds), although in the customary law collection of István Verbőci (or Werbőczy) compiled in 1514 a different opinion based on the Roman tradition also appeared. In the sixteenth century, however, this view was still not accepted generally.24

The abovementioned short section of the Mura was split between Vas and Zala Counties, and the county border reached the river somewhere opposite the Styrian Veržej (Wernsee). The Mura River was referred to as a border river between the “German” territories (i.e. Styria) and Hungary in 1331 for the first time,25 however it probably is not an overstatement to suggest that the border, if it did not along the Mura, was not far from it from the thirteenth century onwards,26 as a source from 1249 tells of the Germans earlier (sometime in the 1230s) having dammed up the Mura River, which flooded the lands of many villages.27 In the Late Middle Ages, the estate complex of Grad (Vas County) and that of Lendava (Zala County) ran along the bank of the Mura River. Both gave names to important aristocratic families, the Szécsi (or Széchy) family of Grad (Felsőlendva) and the Bánfi (or Bánffy) family of Lendava (Alsólendva), respectively. In the border conflicts along the Mura in the Late Middle Ages, these two families played the most important role, especially the count of Vas County, Tamás Szécsi (1501–1526),28 his son, István, and to some extent Antal, Jakab, and Zsigmond Bánfi, as well as their tenants and noble retinue, who sometimes were ready to act without the knowledge of their lords. On the Styrian side of River Mura we could find the Pernegg family with a seat in Negova (Negau) as well as the Schweinpecks with a residence in Ljutomer (Luttenberg).29

An agreement survived from 1504 concluded with the mediation of imperial councilor Georg von Weißenegg and Kaspar von Khuenburg, Styrian provincial lieutenant (Verweser), between Bartolomäus von Pernegg of Styria, and Tamás Szécsi of Hungary. The complaints connected to the agreement had already been appealed to the provincial administration.30 Both parties were aggrieved and felt they had been caused damage, as becomes clear from the text of the agreement. According to the Styrian nobleman, the subjects of Szécsi, who owned vineyards in the slopes next to his village called Turjanci (Siebeneichen), kept him out of grape juice, in answer to which he took the harvest of the past eight years and brought it to the castle of Negova. As Szécsi did not bring up any arguments in defense of his tenants, they agreed that the confiscated goods would remain with Pernegg, but in the near future, the vineyard owners would present their documents, and all the affairs connected to the sale and purchase could only happen with the consent of the Styrian nobleman. Finally, the tenants of Szécsi in the coming three years (probably as a reduction of the confiscation) did not have to pay seigniorial dues. The other case is probably difficult to dissociate from what happened at the vineyards, but one cannot be certain which one was first (or whether it was just part of the daily back-and-forth squabbles). The Hungarian aristocrat did not deny anything: he had the course of the Mura River diverted by a dam, as a consequence of which part of Turjanci owned by Pernegg was destroyed. While the Styrian nobleman argued that the diverted river should be returned to its original bed, this either would have been very costly or not possible at all. For this, and because Szécsi had a good relationship with the brother of Bartolomäus, Stefan, he offered personal assistance for the son of Stefan, and as a redemption, keeping in mind the suggestions of the uncle and his friends, he offered to cover the costs of the education of his nephew and legal guardian until his adulthood as if he were his own son. This, as Szécsi cynically argued, would have been more useful for the youngster than a village with 50 tenants (ihm sein hilff und freündschafft lieber und nutzer sein soll, dann ain dorff, darinnen fuefzig bauren haußlich sitzen).31

Be that as it may, we learn from the distance of two decades that in 1511, at the call of the steward of the Styrian provincial estates (Vizedom), a building master set out with laborers to modify the course of the Mura River to the benefit of the Styrian side. However, the building master was arrested by Szécsi and was kept in custody until his death. Szécsi had the existing dam strengthened and three ditches cut, allegedly in order to detach a major piece of land from the territory of Styria. As a result of the work, three villages were flooded by the river.32

But not only can the blackmailing potential be seen in the attempts to divert the river: the earlier riverbed modifications probably had to be repeated from time to time, since the Mura River could not be kept in the its bed and in its current course without securing the banks.33 As the most important viewpoint was the protection of their own lands, the Hungarians obviously erected the dams and deepened the ditches so that the water would spare the left bank, i.e. their bank. This, of course, went with the right (Styrian) bank being increasingly endangered by the destruction of the water, to which the locals and landowners gave voice. In addition to protecting the settlements themselves, the flood plains may also have been used for fishing or animal herding, and they may have provided favorable places for watermills. All of these factors may have been important to local communities. Thus, modification of water systems could even be done for such purposes (maintenance, improvement etc.).34

The changes in the course of the Mura River may have been closely tied with the different endeavors of the neighbors, too. Most of them are complaint letters which one has to read with some precaution, as they usually only represent the viewpoint of one of the parties, in this case usually that of the Styrians.35 Beginning in the 1520s, the names of Tamás Szécsi and his neighbor Jakab Bánfi occur again and again in the documents, probably for different reasons, but they both took aim at the same settlement along the Mura; in 1520 they raided Veržej.36 The Styrian party appears as a perpetrator only exceptionally because of the nature of the source material. For instance, in 1519 one of the men of Jakab Bánfi was murdered at the fair of Radkersburg,37 or when, in December 1522, the retinue of the Hungarian nobleman raided Styria, because allegedly one of their tenants was being kept in custody.38 A letter written by a Styrian nobleman named Hans von Schweinpeck from December 1522 tells of his continuous conflicts with the Szécsis (Zetschy krieg): eighty of his cattle were said to have been drawn away by the servants of the Hungarian aristocrat. Schweinpeck answered violence with violence, and he also had captives taken.39 In another undated letter which certainly was written at the time, Schweinpeck notes similarly unfortunate circumstances, telling of his relation with the Bánfis in a number of cases and reiterating the claims he had made in his previous letter.40 The conflict with the Szécsis was still an issue in 1523.41

Negotiation Attempts in the 1520s and 1530s

There is no clear answer as to why it was possible not only to bring the two parties to a table to negotiate, but also to spur them to come to an agreement in 1504. It is similarly unclear why there was no similar thing after the above conflicts. Moreover, in the course of 1523–1524, the Austrian–Hungarian commission members met at least once in Sopron, although the issues there strictly concerned the regional conflicts that crossed the border of the Austrian Archduchy and the Kingdom of Hungary.42 This regional division of border conflicts was not be new, as a similar system existed already in the fourteenth century.43

The Styrian party apparently turned to King Louis II of Hungary through Archduke Ferdinand of Austria in vain. The royal orders sent to Tamás Szécsi and/or Zsigmond Bánfi in roughly the same period in (1524–1525) to destroy the newly built dams were proven to be pointless,44 just as when the provincial procurator (Verweser) sent them in response to pressure from the Styrian estates to, for instance, Szécsi.45 (Allegedly, in 1524, the Szécsis made the members of the committee who were sent to the bank of the Mura leave at the point of the sword.46) One of the complaints of the Styrian estates from 1533 directly addressed the fact that when Tamás Szécsi had diverted the Mura River, he had gone against the treaty concluded between Emperor Frederick III and King Vladislas II of Hungary (the treaty of Bratislava of 1491), as his acts were in sharp contradiction with the peace reached in the treaty.47 Probably in the middle of March 1528 or in May 152948 at a commission meeting on the border conflicts held in Sopron, Wilhelm von Pernegg sent an envoy who claimed that the promises Szécsi made in the agreement of 1504, namely on his education, had not been kept.49

Even though, Tamás Szécsi died probably in late spring or early summer in 1526,50 this did not change anything with regard to the conflicts concerning the Mura River. Instead of his name, the name of his son, István Szécsi, appears in the legal documents, and in the late 1520s and 1530, documents again testify to the dam building activities of the Szécsis and the Bánfis. (Although it is not always clear from the complaints whether these were renewals of older dams or entirely new dams.) After 1526, the Hungarian estates did not invest major energy into solving this. In the shadow of the threat of the Ottoman Empire and the conflict between King Ferdinand I and his rival, John Szapolyai (who was also elected as king of Hungary) that quickly escalated into a civil war this problem did not seem so significant. This was further complicated in the Hungarian Chamber by a lack of financial and personal assets for the above reasons. It was not unique that the councilors ordered to the different negotiations did not receive any money or only received money with difficulties.51 In the summer of 1531, news spread that the supporters of the John Szapolyai again diverted the Mura, as they wanted to extend the Hungarian authority towards Styria and in the meantime guard the bank of the river with firearms. It was to be feared that the conflict would end in violence.52 Meanwhile (at the end of July 1531), the Styrian estates brought in a person who had great respect among the Hungarian elite. This is how their choice fell on one of the key figures in the war against the Ottomans, Hans Katzianer, whose presence they hoped would lead to changes to their advantage in the Styrian issues.53 For King Ferdinand I, the utilization54 of joint commissions was in focus, which had been written down in the 1491 treaty of Bratislava.55 However, this must have been rather a theoretical consideration. Finally, Katzianer is unlikely to have attended the commission’s meeting called for on August 24, 1531 at Radkersburg. He was not the only person who missed the meeting. To the surprise of the Styrian estates, so did the Hungarians, and Hans Ungnad complained to King Ferdinand I that the Hungarians gave no explanation for not having attended, even after four days.56 One of the most influential Hungarian noblemen in the court of King Ferdinand I, Elek Thurzó, reasoned for the overburdening of the Hungarian councilors in a letter dated to the beginning of September 1531, in which he also asked for the postponement of the commission meeting. 57 But similar queries had also been shared with the king by the Hungarian councilors six weeks earlier, as by then he must have known that the diet was set for September 8 to Bratislava.58

What was discussed there may not have had a major impact on the conflicts, as two years later, on July 25, 1533, a joint commission meeting was held, again at Radkersburg. Three long complaints were written against the late Tamás Szécsi and his son István, and one concerned the abuses of the retinue of Antal Bánfi,59 but they did not have any visible impact. Only the Styrian appointees traveled to the Styrian town, and similarly to what had happened two years before, no one from the Hungarians appeared.60 After the death of István Szécsi in spring 1535,61 the abovementioned Elek Thurzó,62 the new landlord63 of estate complex of Grad, the foster father of István Szécsi and second husband of Magdolna Székely of Kövend/Ormož (Friedau) (i.e. widow of Tamás Szécsi), was named liable for the abuses in the past and the present. In July 1537, he made a complaint fairly similar to those the Styrian estates had written before, as they did not attend the joint commission meeting called for March 11, 1537. The Styrians, protected by armed men, were said to have diverted the water of the Mura River into a ditch by which his plow lands and forests were detached from the estate complex. After that, the men of Thurzó entrenched the ditch, and the Styrians destroyed it.64 The results of the joint commission meeting held good half a year later (called first for September 1537, then for mid-October, and finally for the end of November, for the last time probably to Radkersburg65) are unknown, and neither do the sources give any details concerning the allegedly futile meeting held at the end of March 1538 at Murska Sobota (Muraszombat).66 As for the negotiations held at Petanjci by the Mura River in October 1539, it is the one and only occasion when we are aware of the dynamics of the discussion between the parties. The arguments were not based on classical legal principles but solely on highly technical aspects of water management as well as damages caused by the Mura River. In the end, the parties managed to settle all the points, but for some reason their decisions were never implemented.67 A letter sent by King Ferdinand I from January 1540 makes it clear that Thurzó was somewhat resentful of the newly initiated “armistice” (though actually we do not know how many times it was initiated), as he definitely wanted to have his dam on the Mura River, which was under construction at the time, completed.68 For this, a new meeting was set to February 25, 1540,69 and even if, of course, there were complaints in the first half of the 1540s (in the majority of the cases about Hungarians, most importantly the Bánfis70), the number of complaints dropped significantly. It is also telling that there is no further information on joint commission meetings. The death of Elek Thurzó on January 25, 1543, who as noted above stood in for the male line of the Szécsi family, probably had a major role in this.71

The Agreement of 1546

A private diary of the Hungarian diet of 1546 gives a good summary of the basic problem in this case, as well as the general functioning of the border commissions: all the involved parties tried to favor themselves.72 Therefore, the king decided to take the questions to a special committee consisting of Czechs and Moravians,73 which the Hungarians also acknowledged. (The tasks of the delegated judges included not only the Mura case, but also possibly other litigations, e.g. on the Dráva River.)74 The decision concerning the course of the Mura River was made two days before the arrival of the king to the Hungarian diet in Bratislava,75 on February 4 in Vienna.

What conclusion did the Czech and Moravian appointees arrive at? The narrative elements, which with some exaggeration were repeated for decades, were presented: the Styrians complained that the Hungarian nobles had modified the course of the Mura River by building ditches and/or dams, which had caused damages to the landlords on the right bank, and moreover relocated animals and people of the Styrians. The Hungarian Bánfis either denied these accusations or reasoned that their actions had been a counterstrike to compensate for damages they had suffered. The appointees decided that, as the three dams built by the Bánfis were rather new and they indeed had caused damages to the Styrian neighbors, they had to be eliminated, including the piles put down four weeks before the agreement. Regarding the future, they also advised the “opposite neighbors” along the river to negotiate and determine where the banks should be strengthened. And if that had been done, dams should be built on both sides out of earth and not sand in a width of four Viennese fathoms (7.584 meters76). However, the regulation of the smaller branches of the river (in the form of dams or ditches) would have been everyone’s individual task. The appointees declared that the riverbed should be kept in its present form, and the parties should cease causing losses to each other.77

The claims against the Szécsis were more complicated than those against the Bánfis, as Tamás Szécsi has been dead for twenty years and his son István had been dead for eleven years. After the death of the second husband, Elek Thurzó, Magdolna Székely (who was marrying for a third time) and her daughter, Margit Szécsi, would have been the people to have to face consequences because of the acts of the late male members of the family. It was enlightening to read, after the long lists of complaints, that the biggest abuse of the Styrian party was caused by Tamás Szécsi back then when he had caused damages to the village of Turjanci with a newly built dam. The husband of Margit Szécsi, Niklas Graf zu Salm (the Younger), however, successfully persuaded the commissioners that the living members of the family could not be punished for the crimes of their forefathers, so all related claims were disregarded. The regulations on the main and the smaller branches of the river were the same as in the case of the agreement of the Bánfis and the Styrian estates. The violator of the agreement had to pay 50 marks within three months.78 It seems that the agreement paid off even in the short term, and in 1549, the Styrians actually wrote that by then they did not have any border disputes with the Hungarians, except for the complaint concerning the Zrinski/Zrínyi family and the Styrian town of Ljutomer.79

Conclusions

King Ferdinand I probably wanted to accelerate the decision so that he could show progress for the Hungarian estates in at least some questions at the 1546 diet of Bratislava, which the estates took with satisfaction. From the point of view of the estates, who took all the measures to guard over the border of the country, especially in the period of the Ottoman conquests, the ruler made an apt decision. He could say, that with a simple technique, choosing members for a committee who were entirely independent and came from another country ruled by him, he managed to do away with conflicts which had lasted for at least two and a half decades. The seemingly moderate committee decisions managed to address the complaints raised in the letters, and even if the Styrian and Hungarian territories followed different legal principles, the decisions of the committee in the present situation can be considered a generous resolution. This may have had major significance for the parties, who were probably fed up with the lasting conflicts.

It is also clear, if one can believe the complaints made in the letters of the Styrian estates and other rather sporadic evidence, that strong men like Tamás Szécsi could even deny royal orders. Elek Thurzó, who was even more important and influential, may have also used his political connections to settle his own issues, though there are fewer concrete signs of this in the sources.

Obviously, even before the sixteenth century, a frequently changing geographical boundary such as the Mura River was inevitably a source of sharp conflicts. However, these conflicts usually broke out because of changes in private landownership rather than changes in state borders This is well reflected in the 1504 and 1546 treaties as well as in the files of the failed negotiations of 1539 held at Petanjci. It may have been totally clear to people at the time that the course of the Mura River could not be preserved without human intervention, neither on the short term nor on the long term. Even if from time to time one could find a solution either because of the death of someone involved or, in a more lucky case, with some kind of compromise concerning the problem of the changing flow of either the Mura or other rivers, the damages going back to the different, not necessarily ill-intentioned water management systems were hard to address simply. The Mura River along the Hungarian–Styrian border splits into numerous branches, and the riverbed changed constantly. Year by year, the dam and ditch system had to be modified. It was precisely this border situation that increasingly triggered the people to take action. This is why in the eighteenth century on a number of occasions (1717–1718, 1753–1755, and 1793) bilateral commissions were set up to negotiate not only the riverine but also the land borders. The sources on the abovementioned conflicts were partly preserved thanks to these negotiations, as the historical documents had an important role in defining the new borders. The parallel running of the border and the crooked course of the Mura were separated during the long negotiations in the 1750s, which is how the almost straight running Linea Theresiana80 came into existence in 1755 as the new Styrian–Hungarian borderline. From then on, the changing of the bed of the Mura River was merely a hydrological issue.

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1* This study was prepared with the support of the NKFIH PD 124903 grant. I am indebted to Renáta Skorka and Szabolcs Varga for their useful comments on the preliminary version of my article. The author is a member of the Research Centre for the Humanities, Hungarian Academy of Sciences “Lendület” Medieval Hungarian Economic History Research Group (LP2015-4/2015) as well as of the project “Commercial Sources in the Service of Hungarian Medieval Economy” (NKFIH KH 130473).

March 9, 1573, Graz, the Styrian Estates to Archduke Charles II. StLA Laa. A, Antiquum I, Karton 7, Heft 30, [no pagination].

2 March 12, 1573, Graz, the Styrian Estates to the Lower Austrian Chamber. StLA Laa. A., Antiquum I, Karton 7, Heft 30, [no pagination].

3 October 19, 1573, Vienna, Emperor Maximilian II to the Lower Austrian Chamber, November 5, 1573, Vienna, King Maximilian I to the Hungarian Chamber, ÖStA AVA FHKA AHK HFU, rote Nummer 25, Konv. Oktober 1573, fol. 66r–67v. Cf. ÖStA AVA FHKA AHK HFÖ Geschäftsbücher 306 (Protokoll Registratur, 1573), fol. 414v, 439v.

4 ÖStA AVA FHKA AHK HFÖ Geschäftsbücher 304 (Protokoll Expedit, 1573), fol. 499r.

5 February 4, 1546, Vienna, StLA Laa. A., Antiquum XIII, Schachtel 236, [no pagination].

6 For (international) agreements and the impact of their printed versions, see e.g. Péterfi, “… nach vermungen,” 193–99, especially 199, note 33.

7 Rutz, Die Beschreibung, 75–104.

8 “Das Problem der Grenze wird noch dadurch kompliziert, daß man gerade im späten Mittelalter häufig nicht von einer einheitlichen »staatlichen« Gewalt sprechen kann, daß vielmehr einzelne Anteile von verschiedenen Herren wahrgenommen wurden. So konnte es Grenzlinien unterschiedlichen Verlaufs und unterschiedlichen Gewichts geben.” Moraw, Von offener Verfassung, 43.

9 Cf. Auer, “Die Jagdgebiete,” 188–89. On the relationship of estate complexes and polities in the Middle Ages: Rutz, Die Beschreibung, 58–75. Rutz, Die Beschreibung, 105–82 gives a general overview of the ways to define borders and their concrete forms of demarcation.

10 “Mÿnd nemethnek s mÿnd magyarnak nÿlwan wagÿon az Magiarorzagh hattara…” MNL OL P 1313, Senioratus, Lad. 4/1, no. 8/b/1.

11 For the conditions before the fourteenth century, see Krones, Landesfürst, 62–74; Wertner, “A stájer Treun;” Kos, “K postanku;” Kring, “A magyar államhatár;” Posch, “Siedlungsgeschichte;” Gruszeczki, “Die Stubenberger,” 116–17; Pirchegger, Landesfürst, 215–16. For the fourteenth century, see Groß, “Zur Geschichte,” and the study of Renáta Skorka in the present issue of the journal. For the fifteenth and sixteenth centuries, see Házi, “Határszéli;” Legler, “Grenzlandstreitigkeiten.”

12 Febvre, “Frontière,” 214. For a general overview on the topic of borders, see also Constable, “Frontiers.”

13 Ca. 1529: “Flavius (!) enim nomine Lapunch utriusque partis terminos tam regni Hungarię quam etiam Germanis (!) dirimit…” MNL OL P 1313, Senioratus, Lad. 4/1, no. 6/b. See also the study of Renáta Skorka in the present issue of the journal.

14 Prickler, “Typen und Problemen,” 2–6; Prickler, “Zwei mittelalterliche Grenzverträge.”

15 Prickler, “Zur Geschichte;” Prickler, “Adalékok;” Prickler, “Typen und Problemen,” 17–19; Prickler, “Weingartenbesitz.”

16 Cf. Lakatos, “Kismarton város,” 287, and legally binding private charter is preserved from 1434, also with the seal of the town of Eisenstadt. (I acknowledge the information provided by Bálint Lakatos.)

17 Csermelyi, “A határon innen.” For the pledged estate complexes, see Bariska, A Szent Koronáért.

18 Prickler, “Typen und Problemen,” 10–12.

19 Mohl, “Szarvkő,” 629–30; Der Verwaltungsbezirk Eisenstadt, vol. 2/1, 72; Haller-Reiffenstein, “Ulrich von Grafeneck,” 149.

20 “Slos unnd herschafft Roraw im lannd Osterreich unnder Prugkh an der Leytta gelegen sambt allen unnd yeden sein zuegehorungen und gerechtigkhaiten in bemeltenn lannd Osterreich unnd in Hungern dartzue gehorig…” ÖStA AVA FA Harrach U 1524 IX 30. “Totale castrum suum Roraw appellatum intra terminos ducatus Austrie prope civitatem Prwkh vocatum adiacens simulcum cunctis oppidis, villis, possessionibus portionibusque et quibuslibet iuribus possessionariis ad ipsum castrum Roraw spectantibus, illis etiam bonis et iuribus possessionariis incerta sui parte intra limites predicti regni nostri Hungariae adiacentibus…” ÖStA AVA FA Harrach U 1525 IX 7.

21 ÖStA AVA FA Harrach U 1524 XII 15 (copy from the eighteenth century: MNL OL DL 24 024, pp. 6–9), 1525 IX 7. Cf. Burmeister, “Graf Georg,” 14.

22 Cf. Házi, “Határszéli;” Legler, “Grenzlandstreitigkeiten.”

23 On another section of the River Dráva with the same patterns, see Viczián, and Zatykó, “Geomorphology.”

24 Degré, Magyar halászati jog, 137–40. Recently with the same opinion: Tringli, “A magyar szokásjog,” 262. Cf. Wesener, Einflüsse. See also the article by András Vadas in the present issue.

25 Anjou-kori oklevéltár, 15. 118 no. 208. (I am indebted to Renáta Skorka for the data.)

26 The southern border of Petanjci terra in 1234 was the River Mura, which the author of the document, unlike in the case of its western section, did not mention as a border: “A meridie eciam participat metam cum Mura et ab occidente tenet metas cum Theutonicis.” Urkundenbuch des Burgenlandes, 161, no. 215.

27 Urkundenbuch des Burgenlandes, 224, no. 322. (I am indebted to Renáta Skorka for the data.)

28 Megyék, 331–32. In 1516, for certain reasons Tamás Szécsi was decorated with a barony by Emperor Maximilian I. December 9, 1516, Haguenau (Hagenau), MNL OL DL 101 816.

29 For the historical topography of Lower Styria/Untersteiermark (i.e. the lands situated south of the River Dráva, nowadays belonging mainly to Slovenia), see Pirchegger, Die Untersteiermark.

30 Cf. sine dato [between 1502–1504, according to Roland Schäffer’s dating], sine loco, ÖStA HHStA Maximiliana, Karton 38, Konv. “s. d. I/1–4,” I/2, fol. 33v.

31 December 10, 1504, sine loco, MNL OL DL 104 143. Further copies: StLA Laa. A., Antiquum I, Karton 7, Heft 30, [no pagination], MNL OL P 396, Lad. Scs, Fasc. B, no. 3.

32 Steinwenter, “Materialien,” 108–9, no. XXVI.

33 Cf. sine loco, sine dato [1539]: “Mura fluvius sine munitione riparum in alveo et cursu suo conservari non potest.” MNL OL N 80, Lad. RR, Fasc. U, no. 6, fol. 92r.

34 For the River Danube, see Andrásfalvy, A Duna mente; Andrásfalvy, “Die traditionelle Bewirtschaftung.” More recently Ferenczi, “Water Management.”

35 Most of these in forms of excerpts were published in: Steinwentner, “Materialien,” in which he also provides a short summary of the problem (ibid., 92–99). On the same problem, based on the documents of Styrian provincial diets (in this term, similarly to Steinwentner): Burkert, “Ferdinand I,” 112–18.

36 Damage list: MNL OL DF 276 047 (originally as ÖStA HHStA UA AA, Fasc. 1, Konv. D, fol. 30r–42v).

37 May 6, 1519, Innsbruck, MNL OL DF 290 345, p. 181.

38 MNL OL DF 276 016–018. (originally as ÖStA HHStA UA AA, Fasc. 1, Konv. C, fol. 12r–15v). Cf. StLA Meiller-Akten, X-a (Landeshauptmannschaft, 1523–1526), no. 1–4, no. 6.

39 MNL OL DF 276 016. Cf. MNL OL DF 276017.

40 MNL OL DF 276 089 (originally as ÖStA HHStA UA AA, Fasc. 1, Konv. D, fol. 158r–159v).

41 MNL OL DF 276 037 (originally as ÖStA HHStA UA AA, Fasc. 1, Konv. D, fol. 18r–19v).

42 Házi, “Határszéli viszályaink,” 63–70; Gruszecki, “Cuspinian,” 75–78; Legler, “Grenzlandstreitigkeiten,” 74–85.

43 See the article of Renáta Skorka in the recent volume.

44 August 9, 1524, Buda, MNL OL DL 39 346 (originally as SI AS 1063, 1227), December 6, 1525, Buda, StLA Meiller-Akten XIII-nn, no. 3 (fol. 55r–56v, German version), no. 13 (fol. 87r–v, Latin version). For a full edition and Slovenian translation of the royal mandate of 1524: Zelko, Zgodovina, 65–66.

45 July 9, 1524, Graz, StLA Meiller-Akten XIII-nn, no. 3 (fol. 54r–v, German version), no. 13 (fol. 86r–v, Latin version).

46 Steinwenter, “Materialien,” 109, no. XXVI.

47 Ibid., 108, no. XXVI.

48 The date of the Sopron meeting of 1528 and 1529 (Oculi Sunday and Jubilate Sunday respectively) is preserved by MNL OL P 1313, Senioratus, Lad. 4/1, no. 3/b. Cf. Házi, “Határszéli viszályaink,” 71; Gruszecki, “Cuspinian,” 79. See also two undated invitations to the Sopron summit of 1528: StLA Laa. A., Antiquum I, Karton 5, Heft 20, [no pagination].

49 StLA Meiller-Akten XIII-nn, no. 12.

50 Reiszig, “A Felsőlendvai,” 71.

51 E.g. Steinwenter, “Materialien,” 99, no. I.

52 Steinwenter, “Materialien,” 100, no. III; I. Ferdinánd, 240, no. LIV. Cf. Steinwenter, “Materialien,” 99–100, no. II.

53 Steinwenter, “Materialien,” 101, no. V.

54 Cf. Ausgewählte Urkunden, 427–28 (§6), 435–36 (§29, §31), 438 (§38).

55 Steinwenter, “Materialien,” 100, no. III; I. Ferdinánd, 247, no. 21.

56 Steinwenter, “Materialien,” 102–3, no. VIII. On Hungarians being absent from the meeting, see: ibid., 103–4, no. X.

57 Steinwenter, “Materialien,” 102, no. VII; I. Ferdinánd, 265–68, no. 73.

58 Ibid., 101, no. IV; I. Ferdinánd, 262, no. 72.

59 Ibid., 108–12, no. XXV–XXVIII.

60 Ibid., 112, no. XXX.

61 He must have died some time before May 14, 1535: Reiszig, “A Felsőlendvai,” 72.

62 Steinwenter, “Materialien,” 115–16, no. XXXV.

63 Cf. 28 April, 1535, Vienna, ÖStA HHStA UA AA, Fasc. 26, Konv. D, fol. 26r–v.

64 Steinwenter, “Materialien,” 116–17, no. XXXVI. Cf. ibid., 117–18, no. XXXVII–XXXIX.

65 Steinwenter, “Materialien,” 118–20, no. XL–XLVII.

66 Hrvatski saborski spisi, 192, no. 116. (I am indebted to Szabolcs Varga for drawing my attention to this document.) Steinwenter, “Materialien,” 122, no. LI–LIII, 127, no. LXIV.

67 MNL OL N 80, Lad. RR, Fasc. U, no. 6–7. Copies from the 18th century: ibid., no. 5. StLA Laa. A., Antiquum I, Karton 7, Heft 30, [no pagination]. Cf. Steinwenter, “Materialien,” 127–31, no. LXIV–LXIX.

68 Steinwenter, “Materialien,” 130, no. LXXI.

69 Ibid., 131–32, no. LXII–LXXIV.

70 Ibid., 132–35, no. LXXV–LXXX. Cf. October 6, 1545, Český Brod, ÖStA HHStA UA AA, Fasc. 54, Konv. B, fol. 74r–v.

71 Ludiková, Mikó, and Pálffy, “A lőcsei Szent Jakab-templom,” 345.

72 “Quod quamdiu rex Hungariae esset, semper variae dissensiones inter eos fuissent et saepius commissarios constituisset, sed semper Hungari commissarii favebant Hungaris, Germani vero Germanis.” Paulinyi, “Az első magyar,” 228.

73 Their earliest mention in the documents of the Styrian provincial estates: Steinwenter, “Materialien,” no. LXXXI. They have yet to be identified. The diary of the 1546 diet mentioned only one person by name (Paulinyi, “Az első magyar,” 228): “castellanum videlicet supremum Pragensem marschalkum Wolfgangem Schlyk,” but this may be (partially) wrong information, as Wolfgang Kraiger von Kraigk the Elder (Krajíř z Krajku in its Czech form) stood at the head of the castellany of Prague. At this point, neither Schlick, nor Kraiger can be associated with the 1546 royal commission that was meant to settle the Styrian–Hungarian border dispute.

74 Sine dato, sine loco, ÖStA HHStA UA AA, Fasc. 54, Konv. A, fol. 99r–104v.

75 Magyar országgyűlési emlékek, 4.

76 Bogdán, Magyarországi hossz- és földmértékek, 87.

77 StLA Laa. A., Antiquum XIII, Schachtel 236, [no pagination].

78 StLA Laa. A., Antiquum XIII, Schachtel 236, [no pagination].

79 Steinwentner, “Materialien,” 99, 136, no. LXXXIII as well as Ziegerhofer-Prettenthaler, “Ferdinand I.,” 136. Cf. May 25, 1549, Prague, ÖStA HHStA UA AA, Fasc. 55, Konv. B, fol. 69r–v.

80 Bidermann, “Die Grenze,” 95–96. Cf. Sallai, “A magyar–osztrák határ,” 290–92.

http://www.hunghist.org

 

 

pdfVolume 8 Issue 1 CONTENTS

Rural Society at the Time of the Cholera Outbreak: Household and Social Structure, Taxation and the Cholera Outbreak in Endrőd (1834–1836)

Gábor Koloh
Hungarian Agricultural Museum
This email address is being protected from spambots. You need JavaScript enabled to view it.

Endrőd is a village in Békés County along the Körös River. A census taken by the local church administration presents the composition of 663 household from 1835. From the perspective of household structure studies, this source is unique in length, age, and complexity. Furthermore, cholera destroyed the settlement the year before and after the census was taken. The census and parish registers offer sources on which one can study the impact of the epidemic on households. The tax register from 1834/1835 allows for the classification of family heads into tax categories, so we can extend the test to the relationship between financial background and mortality rate. This multivariate analysis uses the sources and methods used in epidemic history, social history, and historical demography.

Keywords: cholera, historical demography, tax registers 1834/35, mortality and welfare, spatial patterns

While browsing the archives of the parish of Endrőd, I came across a parish family book (“register of souls”) dated 1835, the first page of which (after the cover decorated with floral patterns) bore the title Az Endrődi Hivek Összeirása 1835ik Esztendötöl Kezdve G[öndöcs] J[ózsef káplán] (“Register of the Believers of Endrőd as of 1835 A.D. [Chaplain] J[ózsef] G[öndöcs].”

Endrőd today forms part of the town of Gyomaendrőd in southeastern Hungary on the banks of the Körös River. According to András Vályi’s description, it is a “Hungarian village in Békés County, the lord of the manor is Baron Harucher, the inhabitants are Catholic, situated near Gyoma and Ötsöd, belonging to the estate of Gyula, its arable lands are mostly good, meadows similarly, pasture is suitable for cattle of several herds, though some parts of its arable lands are flooded and some parts are nitrous, few woods and reeds, mill is negligible, marketplace is second-class due to its distance.”1 It would require a separate analysis to determine what Vályi meant precisely by “Hungarian village.” In fact, Johann Georg Harruckern, council member of the Hofkammer (the Exchequer of the Habsburg Empire), who received the settlement as part of the estate of Gyula, settled Hungarians and Slavs here in the 1720s and 1730s, mainly from the north of the Kingdom of Hungary, but following the initial period, during the work of parish priest Sámuel Pálfy (1772–1780), celebration of the mass in Slavic languages stopped,2 and as Elek Fényes put it in the mid-nineteenth century, “Slovaks also came, but they have now become entirely monolingual Hungarian.”3 In Fényes’s description, the arable lands are not only “mostly good,” but “they have such fertile, black clay soil mixed with sand that its winter wheat produces 15 seeds and its spring wheat produces 20.”4 Almost all (according to Fényes, 98 percent) of the inhabitants were Roman Catholic. The lord of the manor in the period under examination was baron Flórián Drechsel’s wife, Countess Karolina Stockhammer of the naturalized Stockhammer family.5 Regarding its geographical location, the village is a blank spot for analyses from the perspective of household structure, historical demography, or a deeper social history; only local ethnographic research has produced some serious results.6

The scholarship on household structure is “confusingly rich,”7 so I can present here only a very brief overview. In his book Property, Production, and Family in Neckarhausen 1700–1870, which was published in 1990, David Warren Sabean outlined the following evolution of household structure research: he named Frédéric Le Play and Wilhelm Riehl as the prominent representatives of the first generation of researchers in the field.8 Although the closely related Hungarian literature considers Le Play a sociologist, Sabean emphasizes the ethnographic character (Volskunde) of the research and conclusions of the first generation, where Le Play and Riehl saw the original patriarchal structure of the family9 as a continuous and functional whole with a head and dependent members.10 Le Play defined the stem family (famille-souche, when a married child remains in the parents’ household) and Riehl the enclosed household estate11 (das ganze Haus) as transformations of this patriarchal structure. According to Le Play’s concept, the parent couple lived together with one of their children and his or her family, while the others left the household.12 Sabean regards Karl Bücher as a member of the second generation of researchers. According to Bücher, the basis of the functioning of a household is production and consumption, producing for its own needs, and the family members do not participate in the production of goods. Like Bücher, Alekxander Chayanov, in his analysis of Russian peasant society, also saw the key to the functioning of the household in the close interrelationship of production and consumption.13 The third approach was built on these concepts. It originated in the study of historical demography, mainly in the work of Peter Laslett, who by that time had serious doubts as to the reliability of the widely known concept formulated by Le Play.14

Laslett questioned the “statements regarding the average size and structure of pre-industrial families and households and the historical change they allegedly underwent.”15 He objected to the fact that, although it had not become an exclusively accepted concept (research by Marion Levy explicitly refuted this hypothesis), it still was a recurrent “stereotype to talk about structures consisting of 30–40 members and three to ten families. When, however, historians analyzed the totality of households of a settlement or estate on the basis of surviving census records, it turned out that in reality, most peasant households were significantly smaller than this.”16 Laslett et al. conducted research covering England and northwestern Europe in the seventeenth, eighteenth, and nineteenth centuries, which revealed a generally higher rate of nuclear families. Deviating results were found in analyses of family structures in the Balkans, where larger, more complex households occurred relatively often.17 The concept of patriarchal (married sons living in the same household with the parents) and stem family cohabitation was thus refuted, facilitating an understanding of the profound economic and social (including demographic) processes taking place in the nineteenth century. At the same time, Laslett’s typology of household structures and John Hajnal’s typology18 (its excessive complexities notwithstanding) also highlighted the relevance of cultural differences and the composition of the community, even if the acceptance of the role of the latter has now been overshadowed.19 The greatest difficulty faced in the research, hence, lies not in the various concepts, hypotheses, and further research prospects, but rather the lack of usable, reliable, and in particular dynamic sources. Although it is true that a dynamic analysis of the evolution of households would and could be more practical for the purpose of understanding the quality of cohabitation and also more meaningful than the mere exploration of regional samples, unfortunately these kinds of analyses can only be done in exceptional cases. Albeit Chaplain Göndöcs also started the parish family book with high hopes in 1835, by 1836 he mostly had recorded only the births up until that time and the information concerning those who had died of cholera (and not even everyone who belonged to this latter group!), and by 1837 only a small number of new or corrected entries had been added, and none were added in 1838. The national census of 1869 is the nearest in time to this period, but its record sheets have not survived from Endrőd (Mezőberény is the only settlement in the county for which the records survived).20

But this is just, so to speak, one of the basic problems regarding the analysis of households. The relevant literature has been discussing the problems of the term “household” for a long time. Gyula Benda used a succinct and witty definition, so it is worth quoting it in its entirety: “The household, i.e. basically a group people living under the same roof and of the same bread, is both an economic and social basic unit before industrialization. In the case of family estates, which were still dominant in the Early Modern period (whether agricultural or artisan in nature), the unit of production (and thus taxation) is also this cohabiting group. The family and the household are also the basal cell of accumulating and transferring wealth—their characteristics are closely related to the systems of inheritance. Finally, it is also a unit of consumption, everyday life is organized in its context.”21 Tamás Faragó, comparing the definition of the household with the definition of the family, wrote that the “household is different from the family both in its concept, content, organization, and system of activities, particularly in the pre-industrial era. Its members are bound by kinship (consanguinity, affinity, or fictive kinship) and by legal relationships (e.g. servants) and functional ties. Its core is usually but not necessarily a family.”22 Understanding and using the term becomes more difficult when it becomes apparent that households have various structures and different sizes even within individual settlements. In such cases, according to Benda, different models are developed which attempt either to present the different variations in their entirety or to present the shades of the various types through in-depth qualitative research, both on the international and domestic levels.23 The interpretation of the function of the households poses another set of problems. More than half a century ago, József Tamásy regarded them as mere economic communities, while Faragó emphasizes that the household group creates the necessary living conditions and ensures the socialization of new members, providing a material and mental “home space.”24 The more recent research of Péter Őri and Levente Pakot highlights the demographic and economic roles of the household, which are easier to grasp in quantitative terms.25

Tamásy highlighted the cohabitation of Croatian extended families in the eighteenth-century Kingdom of Hungary, where the average number of people in one household was over eight, while in Transylvania, Transdanubia, the Great Hungarian Plain, and the northern region of the country not many more than five people lived in the same household (with only minor differences in the different regions).26 Later domestic macroanalyses confirmed the proportion of households with an average of more than five people from the second half of the eighteenth century to the first decades of the nineteenth. Although the nuclear household could still be regarded as the dominant type, “the proportion of complex (extended and multiple-family) households was not insignificant, and at least in some areas, the majority of the population lived in such types of households type in one or another stage of their lives (...).”27 Furthermore, it is important to note that “households with a great number of people and a complex structure occurred primarily among serf peasantry, and only very rarely among landless layers of society.”28 Even though Faragó emphasizes the lack of sources, he did demonstrate the dynamic transformation of the household structure in the period of more than half a century in question. He concludes that in order to avoid the fragmentation of estates, becoming a landless serf (zsellér), or impoverishment, the proportion of complex households increased between 1787 and 1828, but at the same time, the household structures of different villages show various differences on a regional and ethno-cultural level.29 Micro research both confirmed the above conclusions and may have also refined them with restrictions to local circumstances. Such research includes the study conducted by Andorka and Sándor Balázs-Kovács in Sárpilis, where they repeated the above with respect to the size and composition of the households. Faragó broke down his data according to social strata in his examples from Pest county, but his micro findings verify the nationwide conclusions. The study by Magdolna Balázs and László Katus focusing on Central Transdanubia emphasizes the similarity with the Balkan and eastern household structure, while Gyula Benda’s analysis in Keszthely also establishes the dominance of the nuclear family and the more complex structures observed among farmers, serfs and merchants. Thanks to her sources, Ildikó Husz was able to perform an in-depth analysis of the households of Zsámbék in their dynamics, and she confirmed Faragó’s conclusion regarding the temporary increase in households of a more complex composition, similarly to Balázs Heilig’s analysis in Szőlősardó.30

My source, in the absence of any reference to a higher order, is a “church register of souls,” or a status animarum.31 In the source, the households are not distinguished from one another consistently, which also reinforces the foregoing. At the beginning of the family book, the relationships to the head of the household are accurately described, and later the indication of relations perceived as unambiguous (i.e. children) is omitted. In the second half of the book, even the status of alien persons (mainly servants) is often omitted. The heading of the family book is the following: Háznak aszáma, Vezeték és Kereszt Nevek, Sorsa, Kora (Eszt., Holn., Nap), Egy Házi Család Száma, Idegen Vallásúak, Észrevételek, or House Number, Family and Given Names, Fate, Age (Year, Month, Day), Number of People in the Household, Foreign Faith, Comments. As regards people who belonged to a so-called foreign faith, József Göndöcs recorded their number but failed to provide more details. Taking house number 9 as an example, we can first see the name of Mihály Bentsik (Fate: Landowner farmer), followed by his wife and daughters, then a female servant. Without any separation, the records continue with György Vaszkó (Fate: tenant) with his wife, daughter, and siblings. This row is then closed by a horizontal line, the Number of People in the Household is 10, then István Bálint (Fate: in the great vineyard) with his wife and two children. The family number thus increases to 14 people. As far as I know, there were no close family relations between Mihály Bentsik and György Vaszkó, but still, the two family heads were not separated from each other in the family book. In another example, in the case of house number 96, tenant Imre Fülöpp starts the row, followed by his wife, then Mihály Denitska, furrier, tenant, and his wife and daughter. The row is separated by a line from István Farkas (Fate: in the great vineyard), his wife, and son. Then, another line separates them from György Batsa, homeowner farmer, and his family, who should have been in the first place according to the generally applied logic of the family book.

If one compares the values of the earlier censuses and our source, although the number of households would probably have approximated the previous values if I had calculated the number of households along the lines drawn by the chaplain, due to the inconsistencies indicated above, it seemed more practical to apply the considerations of Őri and Pakot. While processing and coding the data, I considered one household where even though several family nuclei lived together, it was clear that they were close relatives, and I distinguished them from those in which, though not separated by a line, the tenants, gardeners, servants, and other employees were not relatives, but had a family.32 According to this method, a total of 960 households could be unambiguously distinguished.

 

Table 2. Average size of households and the number of married men per household, Endrőd, 1835

De facto

population

Number of married men

Number of households

Average

size of households

Number of married men

per household

5,527

1,109

960

5.75

0.92

Source: Believers of Endrőd 1835. GySzIPL

The average size of households in 1835 does not indicate a cardinal deviation from the value of slightly more than five, which is treated as average in the literature. Therefore, the values of Endrőd correspond to the national average, so they (including the number of married men per household) can be considered representative values.

I used the Laslett–Hammel typology to classify the households in which (as seen from Table 3) 65 percent were nuclear households, which fits well in the series of literature refuting the theory of the dominance of stem families. According to the source, in addition to then 25-year-old homeowner farmer, Mátyás Juhász, who was in the lower category of taxpayers with his tax of 3 forints and 5 kreutzer, three widows lived alone: Mrs. István Palócz aged above seventy, Mrs. Mátyás Roncsek nearing her fortieth year of age (Widow Landowner), and Mrs. Mátyás Tímár (aged 22) spent their year of mourning in the period of the family book (October/November 1835).33 Those living in households with no family included János Lábos, the parish priest of Endrőd between 1825 and 1840, the Curator of the Church (caretaker) József Szölösy, and the unmarried manservants working at the slaughterhouse. Lábos’s household included the author of the source, the 28-year-old chaplain József Göndöcs, as well as chaplain János Piringer, the priest’s sister, and two servants. I considered “unclassifiable” the House of the Lord of the Manor, the House of the Village, and the Arany Patkó lodging house, which Göndöcs records as a separate house, even though he also notes that its tenants have been recorded under house no. 2. In the case of another two houses, albeit the Tenants themselves are known, the source only comments on the others that “at this house live a total of ununited Vlachs: 7.” In these cases, the relationships were impossible to explore.

The rate of 19.7 percent of households with multiple families is nearest to the 1808 value of Tiszacsege (18.4 percent), so corresponding to the classification of Faragó with the help of the Laslett–Hammel system, it constituted a temporary group.34 This is worth noting because for Faragó’s group, this temporary nature can be demonstrated in both Calvinist and Roman Catholic settlements, as well as in both Hungarian-speaking and Slovak-speaking settlements, and in this regard, Endrőd has all these attributes. It was predominantly Catholic but with a significant proportion of neighboring Calvinist settlements; it was Hungarian but part of the population was of Slavic origin. The average size of households (obviously) increased with the complexity of the households, and in comparison with the 1869 value, the values of Endrőd (apart from nuclear households) are on average higher by one person.35

 

Table 4. Breakdown of households according to the gender and age of the household head, Endrőd, 1835

 

Age groups

Total

<25

25–34

35–44

45–54

55–64

64<

no data

N

( percent)

Male

66

218

225

174

136

56

3

878

91.5

Female

4

15

13

18

20

7

2

79

8.2

No data

0

0

0

0

0

0

3

3

0.3

Total

70

233

238

192

156

63

8

960

100.0

Source: Believers of Endrőd 1835. GySzIPL

If we look at the distribution of household heads according to gender, the dominance of male household heads is apparent. Men aged between 25 and 44 constituted the main body. More than half of all the men belonged to this age group, while this ratio is only 6.4 percent in the case of men above 64. However, only rarely were older men living in the family not the head of the household as well: in all seven such cases, the man (whether he was the household head’s father or other) was 70 years old or older. In the case of women, a greater number in the older age group of 45–64 became household heads upon becoming widows. The age of non-head cohabiting elder women was 65 or higher.

 

Table 5. Households according to the household head’s gender and the main categories of household structure, Endrőd, 1835

 

Household type

Total

1

2

3

4

5

6

No data

N

percent

Male

0.1

0.7

66.1

13.1

19.9

0.1

0.0

878

91.5

Female

3.8

1.3

55.7

20.3

17.7

1.3

0.0

79

8.2

Total

0.5

0.9

65.3

14.1

20.2

0.8

0.0

957

99.7

Source: Believers of Endrőd 1835. GySzIPL

The correlations between the household types and the household head’s gender are shown by the percentages in table 4. These indicate that higher rates of men are heads of nuclear and multiple-family households, while women have greater proportions in the other variations. The situation of female household heads belonging to the first type has been discussed above. Households with no family show higher values for women only because of the proportions: this is actually one woman, 23-year-old Ágnes Goda, who lived in a household with her siblings. In the case of households with complex families, we can speak about households in which widows lived together with one or more of their married children and the widow did not transfer the household headship to one of her children. This was the case for Mrs. András Cz. Tóth, the widow of a landowner farmer, who paid taxes on nine acres of arable land, 5.5 acres of meadow and 1.5 acres of vineyard and lived together with her two sons, András (25) and István (20) and their wives and children. Accordingly, the conclusions deriving from the values in the table correspond to the findings of the MOSAIC project.36

 

Table 6. Household structure according to the age groups of male household heads, Endrőd, 1835

Household category

Age groups

N

<25

25–34

35–44

45–54

55–64

64<

 

1. Solitaries

0.0

0.5

0.0

0.0

0.0

0.0

0.1

2. No family

4.5

0.5

0.0

0.6

0.7

0.0

0.7

3. Nuclear

71.2

75.2

81.8

64.4

41.9

23.2

65.9

4. Extended

19.7

18.3

8.0

9.8

11.8

19.6

13.1

5. Multiple

4.5

5.5

10.2

25.3

45.6

55.4

20.0

6. Unclassifiable

0.0

0.0

0.0

0.0

0.0

1.8

0.1

Total ( percent)

100.0

100.0

100.0

100.0

100.0

100.0

100.0

N

66

218

225

174

136

56

875

Source: Believers of Endrőd 1835. GySzIPL

The conclusions suggested by the values contained in table 6 also correspond to national trends. Male household heads under 54 years of age dominate in the case of nuclear households, while men in higher age groups are heads of multiple-family households. Those who became household heads young either became heads upon getting married and leaving the parents’ home or inherited the household after their parents had died. They most often were the heads of nuclear households. Less often, if they were not yet married, they lived alone or maybe with other unmarried persons.”37 Aging men, however, lived together with their married child(ren) and their families in increasing proportions.

 

Table 7. Household structure according to the age groups of female household heads, Endrőd, 1835

Household category

Age groups

N

<25

25–34

35–44

45–54

55–64

64<

 

1. Solitaries

25.0

0.0

7.7

0.0

0.0

14.3

3.9

2. No family

25.0

0.0

0.0

0.0

0.0

0.0

1.3

3. Nuclear

50.0

100.0

69.2

44.4

45.0

14.3

57.1

4. Extended

0.0

0.0

15.4

22.2

40.0

14.3

19.5

5. Multiple

0.0

0.0

7.7

33.3

15.0

57.1

18.2

6. Unclassifiable

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Total (percent)

100.0

100.0

100.0

100.0

100.0

100.0

100.0

N

4

15

13

18

20

7

77

Source: Believers of Endrőd 1835. GySzIPL

 

In accordance with the above, the ratio of female household heads was continuously shifting from the nuclear to the complex household structure over time. In the latter cases, typically the widowed mothers were the heads of the households, so they continued to manage the household after their husbands deaths. The dynamics of change according to age groups can be seen in the case of both the male and female household heads. In Endrőd, too, younger household heads typically managed the simple (nuclear) households, while elders managed the complex households. It was less typical but did occur occasionally that the aged household head passed the management of the household on to one of his or her children.

For the analysis of the distribution of household structures according to social (specifically, social, occupational, and ethnic) strata, I followed the category system derived from the source, with minor simplifications. This resulted in a total of nine social strata (groups). I analyzed the Roma separately, although they primarily belonged to the landless serf (zsellér) or farmhand (béres) categories.

 

Table 8. Household structures according to the social / occupational situation of the household heads, Endrőd, 1835

Household category

intellectuals

landowner farmers

artisans

small traders

homeowner landless serfs

landless serfs without own home

gardeners

farmhands

Roma

no data

Total

1. Solitaries

0.0

0.3

0.0

0.0

1.1

0.0

0.0

0.0

0.0

0.0

4

2. No family

42.9

0.3

1.7

0.0

0.0

0.5

0.0

11.1

0.0

0.0

7

3. Nuclear

28.6

38.1

88.3

100.0

62.8

93.0

84.2

88.9

63.6

33.3

624

4. Extended

28.6

17.2

6.7

0.0

19.2

5.6

7.9

0.0

18.2

22.2

131

5. Multiple

0.0

44.0

3.3

0.0

16.9

0.0

7.9

0.0

18.2

11.1

189

6. Unclassifiable

0.0

0.0

0.0

0.0

0.0

0.9

0.0

0.0

0.0

33.3

5

Total (percent)

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

N

7

302

60

5

266

215

76

9

11

9

960

Source: Believers of Endrőd 1835. GySzIPL

The results of Table 8 reflect the findings of previous microanalyses and macroanalyses. Typically farming serfs (or “farmers” to use the term used in the source) lived in this era in multiple-family households in larger proportions, although I should note that their majority in comparison with nuclear households is only relative. For intellectuals, living in households with no family (as seen from the examples above) was characteristic of the lifestyle arising from the nature of their occupations. Local intellectuals were not connected to the local society as regards their family relations. They formed a passing stratum, so to speak: the tenants of the parish house, including the parish priest and the chaplains, were replaced over time, and they typically did not integrate into the local society from the perspective of their family relations. While approximately 36 percent of homeowner landless serfs and Roma lived in more complex households, the ratio was much lower or zero for the others.

The distribution can be refined by performing the above classification also based on the data of the tax census of 1834–1835. Albeit there seemed to be several ways to classify tax censuses, all of them require a more comprehensive processing work encompassing multiple sources, which is currently not possible. Relying on the correlations of production volumes and the amount of taxes paid,38 I evaluated the first nine, then the subsequent one hundred, two hundred and the other taxpayers based on tax values.

By connecting the tax censuses and the household heads, I managed to achieve a two-thirds identification rate. There are some taxpayers in the censuses from Csejt-puszta: administratively, they belonged to Endrőd at this time, but Göndöcs did not record them in his parish family book. The identification was made quite difficult by the fact that in the case of some family names that are very common locally, it was impossible to identify the correct persons without a full analysis of the registers: Hornoks, Tímárs, and Uhrins lived in the settlement in great numbers, and even if the taxpayer was distinguished by an indication of the father’s given name, this was not always adequate to remove all the doubts.

 

Table 9. Household structures according to the taxation category of the household heads, Endrőd, 1835

Household category

Taxpayer’s serial number (tax amount)

 

1–9

(136–295)

10–99 (40–118)

100–199 (19–40)

200–299

(11–19)

300–399

(6–11)

400–499 (2–6)

500–539 (0.1–2)

Total

1. Solitaries

0.0

0.0

0.0

0.0

0.0

0.7

0.0

4

2. No family

0.0

0.0

1.2

0.0

1.1

0.0

0.0

7

3. Nuclear

25.0

31.6

42.7

56.0

63.6

70.5

76.8

624

4. Extended

0.0

12.3

9.8

15.5

15.9

13.0

8.6

131

5. Multiple

75.0

56.1

46.3

28.6

19.3

14.4

14.6

189

6. Unclassifiable

0.0

0.0

0.0

0.0

0.0

1.4

0.0

5

Total (percent)

100.0

100.0

100.0

100.0

100.0

100.0

100.0

960

N

8

57

82

84

88

146

151

616

Source: Believers of Endrőd 1835. GySzIPL; MNL BéML IV. A. 6. 1834–1835.

It should be noted for the interpretation of Table 9 that the taxpayers’ serial number was the same in the case of equal tax amounts, and that is why each group of hundreds could contain more than one hundred taxpayers. However, due to the two-thirds identification rate indicated above, I was not able to include everyone in my analysis. The value of the tax amount was determined by converting the kreutzer to forints and adding it to the forint value. The table indicates that the biggest taxpayers lived in multiple-family households in an outstandingly large proportion (75 percent), but the majority of household heads belonging to the first hundred taxpayer classes also lived and farmed in this form of cohabitation. István Hanyecz paid the most taxes in the tax year of 1834–1835: 237 Forints and 38 kreutzer. He is followed by military officer Imre Mészáros, then Mihály Gubucz. Hanyecz lived together with his wife, two sons, and daughters-in-law, as well as his grandchildren, his sibling, and their family, as well as a 16-year old servant boy. Imre Mészáros lived with his wife, children, and the family of one of his sons, as well as one manservant and one female servant. Mihály Gubucz lived and farmed together with his two sons and their families.

All taxpayers in the first tax class are landowners, while the second class also includes a gardener, Imre Vaszkó, and a homeowner landless serf (zsellér), Imre Farkas. Both lived in nuclear households. The number of landless taxpayers increases in the third class, there is a growing number of homeowner landless serfs and also artisans. So, in fact, the tax census indicates that a direct proportionality can be identified among those living from agriculture between the extent of their farming activity and living in households of complex families.

 

Table 10. The proportion of households employing external labor according to household structure categories, Endrőd, 1835

 

Household structure categories

1

2

3

4

5

6

Total

Households employing external

labor ( percent)

0.0

57.1

15.9

27.5

34.4

0.0

21.3

N (total households)

4

7

624

131

189

5

960

Source: Believers of Endrőd 1835. GySzIPL

Households often employed external laborers for a shorter or longer period of time. Upon examining the household categories with families, one sees that the proportion of the households employing external labor increased together with the complexity of the household. These laborers, in most of the cases, were male or female servants. Gáspár Czinger, the town clerk, had two Lutheran housekeepers (though he belonged to a household with no families, while being in the second tax category), while the nobleman and cantor Károly Balla, who lived with his wife, son, and mother, had not only a female servant but also a coachman. The average age of manservants was 17. That of the female servants was 15.

 

Table 11. Ratio of average household size and households employing external laborers according to the household head’s age, Endrőd, 1835

 

Household head’s age

<25

25–34

35–44

45–54

55–64

64<

External laborer

15.7

19.7

20.2

19.3

22.4

38.1

General size of household

1.0

4.3

4.8

6.2

9.0

1.2

Source: Believers of Endrőd 1835. GySzIPL

Table 11 indicates that as the household head’s age increased, external laborers became increasingly involved in the management of the household. The higher percentages appearing in the older age groups suggest that aging household heads tried to replace the younger members of the family having left the household this way.

Regarding the year 1836, Historia Domus of Endrőd recorded the conditions according to which Kornélia Stockhammer leased her estates in Endrőd to the village, as well as (and especially) the assets the church purchased. It also noted that Mátyás Habdza had a wooden cross erected on the outskirts of Endrőd, for which he established a foundation of 50 Forints.39 Homeowner landless serf Mátyás Habdza died in July 1836, aged 75 according to the registers and 80 according to chaplain Göndöcs. The cause of death was senectus, which could be translated today as old age.40 Whether it was he who had the cross erected as a form of thanksgiving for his long life (particular for the era) or his son Mátyás (if one accepts that middle-aged Mátyás Habdza was the son of the deceased, Göndöcs’s error would be quite a big deviation, almost 10 years!) is impossible to determine based on this information: the Historia Domus did not record the month and the day. Either way, according to contemporary popular belief, erecting a cross could be justified by the fact that cholera, which had ravaged in Endrőd in the summer of 1836, had spared Mátyás Habdza’s household.41

Göndöcs made, among others, the following entries at the end of the book: Approx. 200 died in the Year 1831 A.D. in Cholera, and a little below that: in (Year) 1836 A.D. Again approx. 100 died of Cholera. As I have mentioned, Göndöcs completed the family book with, among others, the names of those died in the 1836 cholera outbreak in the following year. Comparing this with the entries of the death register, 75 people died between July 6 and August 21, 1836. In the parish family book, Göndöcs added cholera as the cause of death subsequently for 60 people. Collating the people’s data found in the register and the family book, Göndöcs indicated that a person died of cholera in 10 cases where this is not indicated in the register, and the register mentions cholera as the cause of death in a further 26 cases where it is not added to the family book. This means that a total of 86 people are known to have died of cholera, of whom 71 could be connected to the household register.

 

Table 12. Ratio of households with a member who died of cholera according to household structure categories, Endrőd, 1835

 

Nuclear

Extended

Multiple

Total

Households with a member who died of cholera (percent)

4.8

6.9

10.1

6.1

N (total households)

624

131

189

944

Source: Believers of Endrőd 1835, Register of Deaths of Endrőd, 1835–1836. GySzIPL

 

Our sample makes it possible to compare the ratio of households with a member who died of cholera and the composition of the households. Cohabitation, which meant frequent contact among multiple people, constituted a higher risk factor for the spread of diseases, as reflected by the values of Table 12. Those who died of cholera in the families were in larger proportions women (54.7 percent) than men (46.3 percent). A significant group of the deceased included those aged 1–3 and 45–65.

In this paper, I conducted a closer examination of a geographical area hitherto unexplored in terms of household structure analyses, namely the settlement of Endrőd in Békés County. It was useful to process the previously dormant parish family book to get a better understanding not only of the geographical space, but also of the period after 1828. I was able to use a complete source which is rather rare from the 1830s, or even the immediately preceding or subsequent decades, which could be used well both in terms of the richness and (with some reservations) the quality of the data. In summary, the results correspond nicely to the findings of earlier macroanalyses and microanalyses, and therefore the main conclusions can be extended to this region. My findings confirm the dominance of nuclear households. However, I was able to point out that due to the relatively higher proportion of complex households, the village has an interim character, so we may have managed to record a state in the ongoing process of the simplification of households. We can regard as a characteristic specific to this settlement that older household heads employed an external person in significantly larger proportions than the younger generations, which can be explained by the departure of the younger members of the family and thus can also be interpreted as a manifestation of disintegration. Furthermore, the analysis according to tax classes refines the uniform belief that typically peasant families lived in multiple-family household structures. The ratio of this type is much higher where the household head paid more taxes. The health risk arising from the cohabitation of multiple people is also worth noting, the real threat of which is reflected by the relevant difference in the number of deaths from cholera in each household structure.

Archival Sources

Békés County Archives of the Hungarian National Archives (MNL BéML)

IV. A. 6.: Békés vármegye adószedőjének iratai [Documents of the Tax Collector of Békés County] 1834–1835. Accesed on September 25, 2018. https://www.familysearch.org/search/catalog/435710?availability=Family percent20History percent20Library

V. B. 326. d.: Mezőberény nagyközség iratai [Documents of the Village of Mezőberény]. Census doc. 1869.

Archives of the Szent Imre Parish of Gyomaendrőd (GySzIPL)

Endrőd, Register of Deaths. Accessed on September 25, 2018

https://drive.google.com/drive/folders/0ByjN02LbwH6sb2FNdlg0NWFmdm8? usp=sharing

Believers of Endrőd 1835: Az Endrődi Hivek Összeirása 1835ik Esztendötöl Kezdve G[öndöcs] J[ózsef káplán] (Register of the Believers of Endrőd as of 1835 A.D. [Chaplain] J[ózsef] G[öndöcs]).

Historia Domus: Historia Ecclesiae, et Parochiae Endrődinensis conscriptu Anno 1833.

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1 Vályi, Magyarországnak leírása I, 577.

2 Márkus, Békés vármegye, 282; Pesty, Békés megye Pesty Frigyes helynévgyűjtésében, 40; Karácsonyi, Békésvármegye története II. kötet, 97; Iványi, 200 éves az endrődi Szent Imre templom, 52.

3 Fényes, Magyarország geographiai szótára.

4 Ibid.

5 Historia Domus: Historia Ecclesiae, et Parochiae Endrődinensis conscriptu Anno 1833, GySzIPL, 41; Szilágyi, “Egy 19. század eleji birtokelidegenítés esete,” 771–94; Szilágyi, “Indigenák és helyi társadalom,” 140–47.

6 See the Endrődi füzetek [Endrőd Journals] series published between 1992 and 2014.

7 Őri, and Pakot, “Háztartásszerkezet,” 165.

8 Sabean, Property, production, and family, 89.

9 For more detail, see Andorka, “A család és háztartás nagysága,” 147.

10 Andorka, “A család és háztartás nagysága,” 147; Melegh, “A tizenkilencedik század eleji városi háztartások,” 135.

11 Translated by Gergely Krisztián Horváth; see Horváth, Bécs vonzásában, 35.

12 Sabean, Property, production, and family, 89; Andorka, “A család és háztartás nagysága,” 147. Melegh, “A tizenkilencedik század eleji városi háztartások,” 135–36.

13 Sabean, Property, production, and family, 95.

14 Sabean, Property, production, and family, 99; Bácskai, Család, háztartás, társadalom, 7; Andorka, “A család és háztartás nagysága,” 147–48.

15 Melegh, “A tizenkilencedik század eleji városi háztartások,” 135.

16 Andorka, and Faragó, “Az iparosodás előtti,” 402.

17 Ibid., 402–3.

18 Hajnal, “European Marriage Patterns,” 101–43; Hajnal, “Two Kinds of Preindustrial Household,” 449–94.

19 Fauve-Chamoux, “Strategies of Household Continuity,” 138; Bácskai, “Család, háztartás, társadalom,” 7; Derosas, and Saito, “Introduction,” 1; Oris, and Ochiai, “Family Crisis,” 23; Őri, and Pakot, “Háztartásszerkezet,” 166; Szołtysek, “Rethinking Eastern Europe,” 389–427; Szołtysek, “Spatial Construction,” 11–52.

20 MNL BéML V. B. 326. d.

21 Benda, “A háztartások nagysága,” 109.

22 Faragó, “Nemek, nemzedékek, rokonság, család,” 393–483. 455.

23 Benda, “A háztartások nagysága.”

24 Tamásy, “Az 1784–1787. évi első,” 527; Faragó, “Nemek, nemzedékek, rokonság, család,” 455. Faragó distinguishes these functions from the family by giving the following explanation: “albeit the terms of family and household can coincide, it is an undeniable fact that the two are not always the same. A family is not necessarily characterized by cohabitation, the socialization of new family members and the performance of household functions do not always occur within the family, and the ‘home space’ also often extends beyond the family.” Faragó, “Nemek, nemzedékek, rokonság, család,” 455–56.

25 “In past societies where reproduction of the population was connected primarily to the institution of marriage and where the households (groups of people actually living together and cooperating, whether they were relatives or not) represented the basic unit of work and consumption in addition to demographic reproduction, the marriage customs and the rules of forming a household had a direct impact on population development.” Őri, and Pakot, “Háztartásszerkezet,” 164.

26 Tamásy, “Az 1784–1787. évi első,” 530–31. Regarding the usability of extended family, see: Andorka, and Faragó, “Az iparosodás előtti,” 414.

27 Andorka, and Faragó, “Az iparosodás előtti,” 437.

28 Ibid., 437.

29 Andorka, and Faragó, “Az iparosodás előtti,” 437; Faragó, “Nemek, nemzedékek, rokonság, család,” 460–68; Faragó, “Különböző háztartás-keletkezési,” 36–37.

30 Andorka, and Balázs-Kovács, “A háztartások jellemzőinek,” 229–33; Andorka, and Faragó, “Az iparosodás előtti,” 417–21; Balázs, and Katus, “Közép-dunántúli paraszti,” 166; Benda, “A háztartások nagysága,” 134. Husz, Család és társadalmi reprodukció, 69–74; Heilig, “Paraszti háztartások”, 253–54.

31 Andorka, and Faragó, “Az iparosodás előtti,” 403.

32 Őri, and Pakot, “Háztartásszerkezet,” 171–72.

33 Mátyás Roncsek died in January 1835, István Palócz in February, and Mátyás Tímár in September.

34 Faragó, “Rokonsági viszonyok,” 256.

35 Őri, and Pakot, “Háztartásszerkezet,” 174.

36 “In higher age groups, there was a greater chance to live together with one or more married children, much as there was a higher chance of remaining alone after becoming widowed or living under the same roof with people other than relatives. The phenomenon of women becoming heads of the households was related to special stages of the life cycles of the households. Living alone could be typical both of younger and older household heads, recently widowed household heads with children tended to be younger women (nuclear households), while living together with married children as the heads of the household was more typical of older women (households with extended or multiple families). In conclusion, the household heads’ gender was an important factor of the composition of the household.” Őri, and Pakot, “Háztartásszerkezet,” 176.

37 Ibid.

38 Kövér, A tiszaeszlári dráma, 111–18.

39 Historia Domus: Historia Ecclesiae, et Parochiae Endrődinensis conscriptu Anno 1833. GySzIPL, 41., 59.

40 Endrőd, Register of Deaths, 10 July 1836. GySzIPL

41 On the implications of cholera in Hungary, see: Mádai, “Kolerajárványok,” 2–3. 330–51; Dávid, “Az 1831. évi kolera,” 293–312; Gecsei, Cholera morbus; Boa, “Kolerajárványok a 19. századi,” 193–205; Tamás Faragó conducted an in-depth qualitative analysis for Maramureş County, see: Faragó, “Humanitárius katasztrófák,” 19–78. For its implications regarding Békés County, see Magyary-Kossa, Magyar orvosi emlékek, 114; Dávid, “Az 1831. évi kolera,” 293–312; Mádai, “Hat nagy kolerajárvány,” 68.

 

Table 1. Number of houses and households in Endrőd (1787–1835)

 

1787

1817

1828

1828–1829

1830–1831

1835

 

Census

census

national census

census

taxation-related

census

parish family book

Houses

388

607

705

664

640

665

Households

504

862

780

821

688

960

General size of household

5.38

5.54

8.13

5.75

Total number of inhabitants

2,712

4,779

5,401

5,527

Source: Erdei, Békés megye, 113; Believers of Endrőd 1835. GySzIPL

 

Table 3. Household structure according to main household categories, average size of households, Endrőd, 1835

Types

Households

Population

Average

size of households

N

percent

N

percent

1. Solitaries

4

0.4

4

0.1

1.0

2. No family

7

0.7

30

0.5

4.3

3. Nuclear

624

65.0

2,979

53.9

4.8

4. Extended

131

13.6

810

14.7

6.2

5. Multiple

189

19.7

1,698

30.7

9.0

6. Unclassifiable

5

0.5

6

0.1

1.2

Total

960

100.0

5,527

100.0

5.6

Source: Believers of Endrőd 1835. GySzIPL

pdfVolume 8 Issue 1 CONTENTS

A Spatial Analysis of the Socio-economic Structure of Bonyhád Based on the Census of 1869*

Réka Gyimesi and Dániel Kehl
University of Pécs, Faculty of Humanities
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In this study, we examine the social structure of Bonyhád, a multi-ethnical and multi-confessional Transdanubian town in Tolna County. We analyze the individual level data of the census of 1869 and offer a visual rendering of the results on a historical map of the town. The surviving material of this inventory covers the entire population of Bonyhád, providing a detailed picture about 6,036 inhabitants. Records include the names, sex, birth year and place, marital status, occupation and occupational status, literacy, residence, and whether the person in question was present or absent at the time the census was taken. As in Tolna County a cadastral survey was finished in 1866, a contemporary cadastral map is also available. Combined, these sources provide rich information about the spatial structure of the town, because the coordinates are also available using the mapire.eu website, which is overlaid on the OpenStreetMap and the HERE satellite base map. One can use the degrees of longitude and latitude of each household and study the census and the map together in R, a free software environment for statistical computation and graphics.

Bonyhád was the economic center of a small region and had a position of strategic importance in the control of local trade routes. After the end of the period of Ottoman occupation, German settlers arrived and lived alongside the original Hungarian and Serb population. Later, a significant Jewish community settled in the area in the eighteenth and nineteenth centuries. The denominational composition of the population, according to the census of 1869, was 41 percent Roman Catholics, 31 percent Lutherans, 5 percent Calvinist and 23 percent Jewish. The analysis of the census-based information and the visual rendering of the results on the cadastral map explain valuable details about the socio-economic structure of Bonyhád, including the question of segregation, which would be difficult to demonstrate on the basis of qualitative sources, as is typically the case with historical research.

Keywords: socio-economic structure, spatial pattern, R software, segregation, nineteenth c. censuses

Introduction

Bonyhád acquired central functions in the Völgység, which can be described as an agricultural region in Tolna County. The settlement started to develop dynamically in the eighteenth century due to its role as a “geographical gate.” A trade route led through it, and two bridges made it possible for travelers to cross the valley. According to the secondary literature on the local history of the area, this increasingly urbanized town evolved into an industrial-commercial center, which became a market town in 1782 with the right to hold four fairs per year. In the 1850s, Bonyhád turned into the administrative center of the executive unit, called Völgység (which essentially means valley region).1 In the work of Vera Bácskai and Lajos Nagy on the urban structure of Hungary, Bonyhád was introduced as a settlement with local significance. Its fairs were mainly visited by its own inhabitants, as they did not attract people from a larger range.2 This essay also emphasizes the role of local merchants in arranging trade through Tolna County.3

After the Ottoman Era, the town was inhabited by Calvinist Hungarians and Orthodox Serbs, but a few years later, the settlement was considered uninhabited territory. Large-scale German settlement started in the early eighteenth century. It enjoyed the support of the state and the secular and clerical landowners, who sought to repopulate their lands. As a result of this process, Bonyhád evolved into a town with a Roman Catholic German majority.4 While in 1715, records indicate only seven Hungarian and nine Serb families were counted, in 1728 42 Hungarian and 15 German families were paying taxes, and in 1748, these figures had shifted to 11 Hungarian and 29 German families.5 Until the middle of the following century, the number of inhabitants steadily increased. In 1785, there were 2,999 people living in Bonyhád. By 1828, this number had risen to 4,639, and the census in 1850 indicated 6,524 inhabitants and the one in 1857 indicated 6,371.6

The German settlers were not all Roman Catholic. A large number of Lutherans also arrived. German Calvinists from Hessen settled in Bonyhád as they did in other towns in Tolna County, but they mostly assimilated into the Lutheran majority.7 Hungarians were Roman Catholics and Calvinists. In the eighteenth century, the settlement of Jews in the town began, a process which peaked in the 1780s, when there were more than 400 Jewish inhabitants in Bonyhád.8 As a result of the abovementioned denominational mix, five denominations and four churches were found in Bonyhád in the period in question. By the beginning of the nineteenth century, alongside the Roman Catholics, Calvinists and Lutherans were also building churches in the town, and a synagogue was also constructed.9

Sources and Methods

The analysis was based on the individual sheets of census 1869,10 which contain data concerning people living together in the same households. The fact that this source is even extant is exceptional, as the original individual sheets survived only in the case of a few settlements of present-day Hungary.11 Bonyhád offered a good research opportunity given the survival of these sources, and the population was heterogeneous from the religious and socio-economic perspective.

In our analysis, we examined and combined housing statistics and individual level data of inhabitants from the census material and projected the results on the nineteenth-century map of Bonyhád. In the first place, we concentrate on the denominational and occupational distribution of the population and the connection between these two variables. Our aim in this study is empirically to test some of the well-known relations between religious belonging and occupations (for example Jews were mainly occupied as merchants)12 and to compare results of previous studies to the data regarding Bonyhád. While there was no religious pattern or concentration of inhabitants in Sátoraljaújhely13 besides that of the Jewish population, we can assume that the results will be different in the case of a resettled community.14

According to the census, of the altogether 6036 inhabitants of Bonyhád in 1869, 2,961 were males and 3,075 were females, which means a sex ratio of 1,038 females to 1,000 males. The census registered housing statistics on a separate sheet (location, number of rooms and outbuildings, whether the building served as a place to live only or also as a shop, etc.), as it did in the case of domestic animals. On the middle sheet, the name, sex, year and place of birth, religion, marital status, occupation and occupational status, residence, presence or absence, and literacy of the inhabitants were given. Comments involving factors like e.g. illness, military service, place of absence, etc. were written in the last column. In cases of multiple households sharing the same house, a vertical line separated the Wohnparteien.15

The numbering of the houses was continuous in the settlement, so the figures started from one and increased to the number of the last house of the town, independently of the streets. 1306 Wohnparteien lived in Bonyhád in 763 houses, which means 1.7 households per houses. This figure is higher than the average for Pest County (1.3–1.4).16 The average size of households was 4.6 persons, which correspond to the national average at the time.17

In the course of our investigation, we applied five broader categories of occupations18 in order to increase the efficiency of analysis. We employed the method introduced by Péter Őri and Levente Pakot, who created the following socio-professional groups based on HISCLASS:19 (1) Groups of higher status (non-manual), (2) Craftsmen (artisans and merchants), (3) Farmers (landowners), (4) Groups of lower status (unskilled) and (5) Other.20

We do not endeavor or claim to offer any detailed examination of demographic characteristics like marital customs or the number of children in a family without the use of parish registers. We cannot arrive at reliable conclusions concerning demographic phenomena exclusively on the basis of census data, because census data provide detailed information on the population on a particular date. We know how many people lived in the town on December 31, 1869, but we have no information concerning the total number of children who were born in the family or the number of those who left their homes. Likewise, we do not know how many children were born after this day in the same family. The census material makes possible the analysis of the spatial pattern of the distribution of the household-types using Laslett’s categories.21 Laslett’s method introduced categories based on the relationships among the household-members, not the number of the inhabitants, so the uncertainty caused by the lack of all the life events can be solved by drawing on his work. Using the census data, we also can analyze the spatial distribution of the age-groups, but neither the age-distribution nor the Laslett classification showed characteristic spatial arrangement, so we decided to exclude these aspects in what follows.

We also examined household members who were not blood-related to the family, like servants or apprentices, and we compared them to their employers from the perspective of their religion or place of birth. Although there is a column for residence in the census sheet, in our opinion it’s not suitable to distinguish so-called foreigners from the resident population, because this distinction only refers to the period during which these people lived in the same place, not their origin (place of birth). The numbers of these columns confirm our assumption. 87 percent of the population belonged to the resident category according to which division, but only 75 percent had been born in Bonyhád.22

In the second half of the nineteenth century cadastral surveys were carried out in the Crownlands of Hungary, beginning in 1856 in the western part of the country and heading eastward. The survey of Tolna county was completed in the mid-1860s.23 Thus, we have a cadastral map from Bonyhád which is contemporary with the census.24 A historical map includes valuable information about the geographical situation of the town, but on the homepage of Mapire digitalized maps are available with coordinates. The webpage combined the historical maps with OpenStreetMap and Google Maps.25

By analyzing the spatial structure based on census data, we aimed to use free and/or open source software solutions that are also capable of performing transformations of raw data and proper statistical analysis. This approach makes this research much more reproducible and could help researchers conduct similar studies in the future.26 Steps followed in creating the maps are to be found at the end of our study in the annex.

Spatial Distribution

Housing statistics

Data from the census enable us to investigate housing circumstances of the inhabitants of Bonyhád. The differences are best shown by the population density (mean number of residents in a room). This value is 2.64 people/room on average in Bonyhád according to the 1869 census. However, there are differences among the houses in this respect, as shown on figure 1.27

As the map shows, most of the houses had a population density around the mean of 2.64, but there are some houses where more than four inhabitants shared one room. In the southern and southeastern parts of the town, we see buildings with low population densities. These bigger houses were owned by the Perczels and other landowning nobles. According to the map, in several cases, there were parks or large gardens on these properties behind the house. Of the 763 houses of the settlement, only 20 were two-story houses. The largest number of rooms was 23 in one house, but there were 20 households sharing the edifice, so number of rooms alone does not mean that the inhabitants were wealthy. That is why we decided to put the population density on the map, and based on the result, we can conclude that Bonyhád was more an agricultural settlement than urban.

Spatial distribution of denomination

Based on census data, Bonyhád had 2,463 Roman Catholic (40.8 percent), 1,890 Lutheran (31.3 percent), 1,359 Jewish (22.5 percent), 317 Calvinist (5.3 percent), and seven Orthodox (0.1 percent) inhabitants in 1869. In the literature, we find statements about the spatial patterns which agree in part with these figures. One source indicates that Hungarians settled down in the southern part of the town, while Germans chose the northern part.28 Others call the eastern line of houses the “Hungarian Bonyhád,” while the western line of houses was referred to as “German Bonyhád.”29 These two approaches were synthesized by Wilhelm Knabel, according to whom the two landholders of Bonyhád (baron Schilson and Ferenc Kun) split the settlement in 1729. To south and west of the main square, the “German village” developed, with the tavern, butchery, and three mills which belonged to the baron. Ferenc Kun gained the northern and eastern part of the settlement, the so-called “Hungarian village,” with the wine shop and the brewery. The part of the town inhabited primarily by German speakers tended to prefer Roman Catholic settlers, while the Hungarian-speaking community preferred Calvinists. Several Lutherans moved into the Hungarian part of the town from the surrounding settlements.30

This statement is underpinned by the map showing the spatial distribution of denominations. Protestants are found in the northern part of the settlement, and Roman Catholics populated the south. Religion seems to have had a stronger effect on spatial patterns than nationality. Many sources also state that Lutheran and Calvinist settlers did not live in the German village, and both villages had inhabitants belonging to both nationalities.31 The contention that denominational belonging was the most important single factor in determining settlement patterns within the town is also supported by the placement of cemeteries and churches, which reflects the spatial distribution observable on our map. This confirms the sources cited and also shows that the religiously differentiated structure which evolved at the time of resettlement remained stable one century later.

Jews formed their own closed community in the city center between the German and Hungarian villages. Their activities turned Bonyhád into the trading center of the region in this era.32

Spatial distribution of occupation

The census registered the occupation and occupational status of the inhabitants, and on the basis of this, we categorized the inhabitants of the settlement into the abovementioned five groups. These columns are usually left blank in the cases of women and small children, but data were available concerning household heads, older children, and other residents. Thanks to this data, we know the sources of income for 2,155 inhabitants of Bonyhád. Broken down into occupational groups, 99 of these people belonged to a stratum which had a higher status (they performed non-manual labor), 462 were artisans and merchants, 228 were landowners, and 1,302 were members of lower strata (i.e. unskilled laborers). 64 people couldn’t be categorized into the abovementioned classes (e.g. almsmen).

As over half of the inhabitants belonged to the unskilled category, which is in line with the agricultural characteristics of Bonyhád, we decided to create two subcategories. One of them includes unskilled agricultural workers only (e.g. unskilled farm workers, farm servants), while the other consists of unskilled workers who worked together with artisans (e.g. apprentices, journeymen) and other servants and maids.

As can be observed on the map, most of the merchants and artisans lived in the center of the settlement, while the northern and southern parts of the settlement were populated by landowners, especially the Protestant parts. Using our subcategories, we acquire a more detailed picture of the spatial pattern of the unskilled stratum: the distribution of unskilled workers reflects that of the artisans and landowners (agricultural unskilled workers lived outside the center of town, while apprentices and journeymen in the center). The inhabitants who did non-manual labor and therefore belonged to a higher social stratum also tended to live in the middle of the settlement.

The spatial distribution of different occupations is quite different. In some cases, artisans with the same profession lived throughout the settlement (e.g. masons), while most of the merchants were concentrated in the center, as were tailors. Weavers were only found on the periphery. Innkeepers and tavern owners opened shops both in the center and next to commercial routes in the southeastern area.

Occupation and religion

The settlement pattern according to denominational belonging shows similarities to that of occupation shown on the previous maps. We further analyzed this relationship between occupational class and denomination (leaving out Orthodox inhabitants due to their small number, we had information concerning the denominational belonging of 2,150 residents of the town). The resulting cross table shows a significant association between the two variables (p<0.001).

Table 1 shows the distribution of occupational groups within each of the four big denominations. The higher status group comprised 4.5 percent of the total population. This figure is somewhat less among Lutherans and higher in the case of Calvinists and Roman Catholics. The proportion of artisans is clearly highest among inhabitants belonging to the Jewish community (around 40 percent). It is close to 20 percent in the case of Roman Catholics and remains below 15 percent in the case of Protestants. Farmers made up almost 20 percent of the Lutheran and 15 percent of the Calvinist communities, while the ratio is below nine percent for Roman Catholics and under one percent in case of Jewish inhabitants. As we have already seen, the largest group was comprised of unskilled workers. Their proportion of the population remained under 50 percent in the case of Jews, but for people belonging to Christian denominations, it is between 60 and 66 percent. The last (Other) group has a low percentage of unskilled laborers, with minor differences between denominations.

 

Table 1. Distribution of occupational groups within denominations,
Bonyhád, 1869

 

Lutheran (percent)

Calvinist (percent)

Roman Catholic (percent)

Jewish (percent)

Total (percent)

Higher

1.21

6.62

6.54

4.50

4.51

Artisan

14.42

11.03

19.61

40.05

21.49

Farmer

18.82

14.70

8.68

0.71

10.60

Unskilled laborer

64.34

66.18

61.74

49.53

60.42

Other

1.21

1.47

3.43

5.21

2.98

Total

100.00

100.00

100.00

100.00

100.00

Nearly 200 different occupations are mentioned in the census data. Most professions had only a few representatives in the settlement. However, there are quite different occupational patterns in the case of the four denominations. We conducted a correspondence analysis which revealed that the main difference was between members of the Jewish community and people who belonged to the three Christian denominations. Most of the professions were avoided by Jews, while some were dominated by them. In some cases, however, the denominational distribution reflects the proportions of the population. Examples of each case are presented in Table 2.

 

Table 2. Denominational patterns in selected occupations,
Bonyhád, 1869

 

Lutheran

Calvinist

Roman Catholic

Jewish

Total

Carpenter

23

4

31

0

58

Furrier

0

0

0

20

20

Mason

11

3

26

0

40

Merchant

0

0

17

60

77

Shoemaker

1

9

4

0

14

Tailor

26

3

41

16

84

Tanner

24

3

42

6

73

Weaver

20

4

15

0

39

The relationship between denominations and occupations in itself is not novel, but the spatial analysis in this case of a resettled eighteenth-century town raises several questions. Sources and the map of the spatial pattern of denominations both underpin that the eighteenth-century separation of religions still strongly affected structure of society in the nineteenth century.

The relationship between Jews living in the settlement center and the concentration of artisans here seems obvious. For a long time, Jews were not allowed to own land.33 It is easy to see why they settled in the dense central parts of the town, where they could be more successful. But is the relationship between Protestants (in this case mainly Lutherans) and the class of farmers also that univocal? One simple explanation might be that the main goal of recruiting German settlers was to find farmers to (re)cultivate abandoned lands. However, sources and contemporary laws show evidence that allowances were given not only for agricultural workers, but also to artisans.34 New settlers arriving to Bonyhád were not only agricultural workers but also artisans. It seems clear that the settlement patterns in the eighteenth century were based on denomination, but the question remains: did this also cause the occupational differences, or did inhabitants adapt to this spatial structure and chose their occupation accordingly? In other words, the direction of the possible causal relationship between denomination and occupation is still unclear and requires further investigation.

Non-relatives – cooperation and separation

According to the census data, the denominations of servants and maids corresponded to the denomination of their employers. We also analyzed the birthplace of this group of non-relatives living together with a family , which was the most mobile stratum of the population of Bonyhád. Regarding the presence/absence columns, 498 people were absent (five people only temporarily), who were listed mainly as children in the households. Their occupations were not given in every case, but otherwise they were servants, maids, apprentices, journeymen, or people serving in the military, which demonstrates the extent of the mobility of these groups.

Table 3 presents the denominational or religious belonging of servants and maids alongside the denominational or religious belonging of their employers.

 

Table 3. Religion or denomination of servants and their employers, Bonyhád, 1869

 

Denominational belongings of heads of households (number)

Lutheran (18)

Calvinist (7)

Roman Catholic (44)

Jewish (37)

Total

Servant’s denominational belonging

Lutheran

15

2

10

5

32

Calvinist

1

1

6

3

11

Roman Catholic

4

8

54

18

84

Jewish

0

0

0

13

13

Total

20

11

70

39

140

Born in Bonyhád

5

1

11

7

24

Of these 140 servants, 28 were males and 112 were females. Therefore, in all cases the number of females was always higher than the number of males. All of the servants employed by Jewish households were female, including 13 Jewish maids. Jewish servants only served in Jewish households. We can observe a more open pattern among Roman Catholics and Protestants, and not only in the case of servants and maids, but also in the case of the craftsman-apprentice relationship (Table 4). 35

 

Table 4. Religion of apprentices and their employers, Bonyhád, 1869

 

Denominational belonging of heads of households (number)

Lutheran (28)

Calvinist (1)

Roman Catholic (42)

Jewish (19)

Total

Apprentice’s denominational belonging

Lutheran

12

0

10

0

22

Calvinist

1

0

3

0

4

Roman Catholic

24

2

67

5

98

Jewish

0

0

0

18

18

Total

37

2

80

23

142

Born in Bonyhád

3

1

7

4

15

On average, Roman Catholic heads of household employed the most servants (77 servants for 44 households) and apprentices (80 apprentices for 42 craftsmen). The most frequent number of servants/apprentices was one, but there were some exceptions.36 In Tables 2 and 3, the number of servants and apprentices who were born in Bonyhád is also presented. In all cases, we can see that the proportion of local born employees is quite low. This suggests that mobility was relatively high among members of this group.37

Summary

Based on the census of 1869, we examined the socio-economic spatial structure of the agricultural settlement of Bonyhád using the cadastral map from the 1860s as a visualization tool. After a short introduction of housing data in general, the study focused on settlement patters according to denomination and occupation. We verified that resettlement still had a strong influence on the denominational structure of the community in the nineteenth century. We demonstrated a statistically significant relationship between religion and occupation. Further analysis was completed about the denomination of non-relatives and households living together. As a result, we offered statistic evidence in support of contentions found in qualitative secondary literature and earlier studies according to which Jewish society in the town was much more closed than the Christian denominations. They only worked in houses belonging to people of their own religion and they lived in a well-separable place in the town center. Spatial patterns were investigated for every profession and some of them were represented on maps. In some cases, a particular occupation seemed to predominate among the community which belonged to a particular denomination, while other occupations seemed to have been less connected to a given religion or denomination. The study also indicated the complexity of the society under study and concluded that resettlement was an important factor which influenced the socio-economic and denominational structure of the town even a century later.

Our results underpin the strong relationship between denomination and occupation and settlement patterns within the town. However, the direction of the causation needs further investigation, as an important question remains unanswered: did the settlement patterns influence occupation, and if so, to what extent, or did settlers find their homes based on their profession.

Annex

Four steps were taken to complete the maps presented later in our paper:

1. based on the historical map, polygons were defined which represent houses, and they were used to connect data concerning inhabitants and their houses to the map;

2. the file containing the historical map was read into R and GPS coordinates were added;

3. polygons were read into R;

4. statistical calculations were made and the final maps were created based on previous results.

The first step was done in Inkscape,38 a free open source vector graphics editor. Inkscape uses the open standard SVG (Scalable Vector Graphics), which enables us to create small but scalable graphics. All other steps were performed in R,39 which is a free and open source software environment for statistical computing and graphics.40 The open source status makes it possible for users to contribute their own code to a central repository (CRAN). These contributions are called packages, and the number of packages grows rapidly. There are over 13,000 packages at the moment, and we use some of them for data manipulation and to create maps.

The resolution of the base map is 3080 x 6925 pixels. We read the base map into Inkscape and then used the appropriate tool to draw linear polygons on another layer to represent houses. The so-called Draw Bezier curves and straight lines tool seemed to be the best choice, as it is able to snap nodes to polygons which have already been defined, which means we could easily draw polygons which are perfectly matching and which cover the entire map. One property of all objects in Inkscape is their ID, where we used the house numbers of the census to make it easier to connect polygons to census data later on. Filling the polygons which had already been drawn with a somewhat transparent color makes the manual process even simpler.

Figure 5. Manually creating polygons in Inkscape

 

As a result, we created a vector graphic map of nineteenth-century Bonyhád which is zoomable, small, and easy to read. There are several format options available to store polygon data. We chose the so-called absolute coordinates (instead of relative coordinates), which are easier to process in R as an XML file. Once we finished drawing all the polygons, we could remove the base map and save the final vector graphic map of the settlement.

In the R environment, there are several plotting packages. We used ggplot241 and its extension for maps called ggmap.42 This latter package is applied to create visual renderings of spatial data on top of static maps from various online sources (Google Maps, OpenStreetMap, Stamen Mapsor CloudMade). The package assumes that one is plotting on a map which comes from the abovementioned online sources. However, we can convert our png file to a ggmap object by adding the bounding box data (lower left und upper right corner GPS coordinates). As a result of several lines of code in R, we now have a high resolution ggmap object which contains a raster and its place in the GPS coordinate system. As this is the basis of all the maps, we saved this into the native R datafile (RDa).

The next step was to read and convert the polygon dataset in R. As already mentioned, the svg file we created in the first step is basically an xml file which contains all polygons in nodes called path. All paths have multiple attributes, but we only need the ones named “d,” which contain the coordinates (in pixels), and the ones named “id,” which contain the house numbers. Reading and converting polygons to the GPS coordinate system enables us to produce different types of maps. On one side, we can draw the polygons with different colors representing various characteristics of the given house (e.g. population density, meaning people/room). On the other side, in several cases we plotted characteristics of the inhabitants of a given house. For instance, we put (equal size) pie charts in the center of the polygon (this approach seemed appropriate as the religion or denominational belonging of the inhabitants of a given building was usually not the same). We drew this type of map using the scatterpie package.43

 

 

Archival Sources

Tolna Megyei Levéltár [Tolna County Archives] (TML)

V. 709./c Közigazgatási iratok 1850–1949 [Administrational Documents, 1850–1949]. Bonyhád nagyközség iratai, 1869. évi népesség és háziállatok összeírása [Documents of Bonyhád, Census of 1869 and the Enumeration of Domestic Animals]. 512–513. box

Bibliography

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A Magyar Korona Országaiban az 1870. év elején végrehajtott népszámlálás eredményei a hasznos házi állatok kimutatásával együtt [Census 1870 in the Crownlands of Hungary, together with the numbers of farm animals], edited by Országos Magyar Királyi Statistikai Hivatal. Pest: Athenaeum, 1871.

Magyarország történeti statisztikai helységnévtára, 10. Tolna megye [Historico-statistical Gazetteer of Hungary, 10. Tolna County], edited by Andrásné Jeney, and Árpád Tóth. Budapest: MTA – KSH, 1966.

Tolna megye (Georeferált vármegyei kataszteri térképek): 1859–1864 [Tolna County (Georeferenced Cadastral Maps of the Counties): 1859–1864], edited by Sándor Biszak, and Gábor Timár. Budapest: Arcanum, 2010.

 

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Bácskai, Vera, and Nagy, Lajos. Piackörzetek, piacközpontok és városok Magyarországon 1828-ban [Market regions, market centers, and towns in Hungary in 1828]. Budapest: Akadémiai Kiadó, 1984.

Balázs Kovács, Sándor et al. Tolna megye kézikönyve [Handbook of Tolna county]. Magyarország Régiói, Dél-Dunántúli Régió [Regions of Hungary, region of South-Transdanubia], edited by Dezső Bunovácz. Budapest: Ceba Kiadó, 2005.

Bonyhád. Vasárnapi Ujság [Sunday Paper], 12, no. 20, (1865): 238. Accessed on September 19, 2018. http://epa.oszk.hu/00000/00030/00584/pdf/00584.pdf

Demeter, Gábor, and Bagdi, Róbert. A társadalom differenciáltságának és térbeli szerveződésének vizsgálata Sátoraljaújhelyen 1870-ben [The analysis of differentiation and spatial organization of society in Sátraljaújhely in 1870]. Debrecen – Budapest, 2016.

Faragó, Tamás. “Különböző háztartás-keletkezési rendszerek egy országon belül – változatok John Hajnal tézisére” [Different household formation systems in hungary at the end of the eighteenth century: Variations on John Hajnal’s thesis]. In KSH NKI Történeti Demográfiai Évkönyv, edited by Tamás Faragó, and Péter Őri, 19–63. Budapest: KSH NKI, 2001.

Fényes, Elek. Magyarország geographiai szótára, mellyben minden város, falu és puszta, betürendben körülményesen leiratik [Geographical dictionary of hungary. accurate description of every town and village in alphabetical order]. Pest, 1851. Accessed on September 19, 2018. https://www.arcanum.hu/hu/online-kiadvanyok/Lexikonok-magyarorszag-geografiai-szotara-fenyes-elek-BABC3/b-BAD42/bonyhad-BB0CC/

Gyimesi, Réka. “Mohácsi háztartás-rekonstrukció: Az 1869-es népszámlálás felvételi íveinek feldolgozása” [Household-reconstruction in Mohács based on the individual data of census 1869]. Demográfia 57, no. 2–3 (2014): 183–212.

Guangchuang, Yu. scatterpie: Scatter Pie Plot. R package version 0.1.2. Accessed on September 23, 2018. https://CRAN.R-project.org/package=scatterpie

Hajnal, John. “European Marriage Patterns in Perspective.” In Population in history: Essays in historical demography, edited by David V. Glass, and David E. C. Eversley 101–43. London, 1965.

Horváth, Gergely Krisztián. “Város a városban: főhercegi ingatlanok Magyaróváron az 1869. évi népszámlálás tükrében” [Town within a town: Archducal properties in Magyaróvár according to the census of 1869]. In A város és társadalma: Tanulmányok Bácskai Vera tiszteletére: a Hajnal István Kör Társadalomtörténeti Egyesület 2010. évi, Kőszegen megrendezett konferenciájának kötete [The town and its society: Studies in honor of Vera Bácskai], edited by István H. Németh, Erika Szívós, Árpád Tóth, 249–57. Budapest: Hajnal István Kör Társadalomtörténeti Egyesület, 2011.

Kahle, David, and Wickham, Hadley. “ggmap: Spatial Visualization with ggplot2.” The R Journal, no. 5 (2013): 144–61. Accessed on September 23, 2018. http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf

Katus, László. A modern Magyarország születése – Magyarország története 1711–1914 [The birth of modern Hungary – The history of Hungary, 1711–1914]. Pécs: Kronosz Kiadó, 2012.

Knabel, Wilhelm. Geschichte Bonyháds (Bonnhards) von der Urzeit bis 1945 [The history of Bonyhád from prehistorical times to 1945]. Munnich, 1972.

Kolta, László. “A közigazgatás változásai Bonyhádon” [Changes in the administration of Bonyhád]. In A Völgység huszadik százada: Struktúrák és konfliktusok: III. Völgységi Konferencia [The twentieth century of Völgység. Structures and conflicts: the 3rd conference of Völgység], edited by László Szita, and Zoltán Szőts, 15–20. Bonyhád: Völgységi Múzeum, 2001.

Laslett, Peter. “Introduction: The history of the family.” In Household and family in past time, edited by Peter Laslett, and Richard Wall, 1–89. Cambridge: Cambridge University Press, 1972.

Lippényi, Zoltán, Marco H. D. van Leeuwen, Ineke Maas, and Péter Őri. “Social status homogamy in a religiously diverse society: Modernization, religious diversity, and status homogamy in Hungary between 1870–1950.” The History of the Family, (2017): 1–23. Accessed October 3, 2018. DOI: 10.1080/1081602X.2017.1319399

Őri, Péter, and Levente Pakot. “Háztartásszerkezet a 19. századi Magyarországon: A Mosaic-adatbázis elemzésének első eredményei” [Household structure in nineteenth-century hungary: first results of the analysis of the Hungarian MOSAIC Sample]. Korall, no. 65 (2016): 164–92.

Őri, Péter, and Levente Pakot. “Residence patterns in nineteenth-century Hungary: Evidence from the Hungarian MOSAIC sample.” Working Papers on Population, Family and Welfare, no. 20. Budapest: Hungarian Demographic Research Institute, 2014.

Őri, Péter. “Család és házasodás a 18–19. századi Magyarországon. Pest–Pilis–Solt–(Kiskun) megye, 1774–1900” [Family and marriage in eighteenth-century and nineteenth-century Hungary. Pest–Pilis–Solt–(Kiskun) County, 1774–1900]. Korall, no. 30 (2007): 61–98.

Őri, Péter. “Kiskunhalas népessége 1869-ben” [Population of Kiskunhalas in 1869]. In Kiskunhalas története 3: Tanulmányok Kiskunhalasról a 19. század közepétől a 20. század közepéig, [History of Kiskunhalas 3: Studies about Kiskunhalas from the middle of the nineteenth century to the middle of the twentieth century], 269–92. Edited by József, Ö. Kovács and Aurél Szakál. Kiskunhalas, 2005.

Pakot, Levente. “Családok és háztartások két székelyföldi településen a 19. század második felében” [Families and households in nineteenth-century Transylvania]. Demográfia 55, no. 4 (2012): 268–91.

Pozsgai, Péter. “Családok és háztartások: Torna megye társadalma a 19. század közepén.” [Families and households: Society of Torna County in the middle of the nineteenth century]. PhD diss., Budapest, Eötvös Loránd Tudományegyetem Bölcsészettudományi Kar, 2006.

R Development Core Team. R. A language and environment for statistical computing. R Foundation for Statistical Computing. Accessed September 23, 2018. http://www.R-project.org.

Schmidt, János. Német telepesek bevándorlása Hesszenből Tolna-Baranya-Somogyba a XVIII. század első felében [Immigration of German settlers from Hessen to Tolna–Baranya–Somogy in the first half of the eighteenth century]. Győr: Baross Nyomda, 1939.

Solymár, Imre. “A történeti Völgység” [The historical Völgység]. In Tanulmányok Bonyhád történetéből [Studies on the History of Bonyhád], edited by Ernő Bábel, and Péter László, 9–38. Bonyhád: Bonyhád Város Tanácsa és a Tolna Megyei Lapkiadó Vállalat, 1987.

Solymár, Imre. “Bonyhád – hajdan Bonyha” [Bonyhád – in bygone times Bonyha]. In Tanulmányok Bonyhád történetéből [Studies on the history of Bonyhád], edited by Ernő Bábel, and Péter László, 39–63. Bonyhád: Bonyhád Város Tanácsa és a Tolna Megyei Lapkiadó Vállalat, 1987.

Szilágyi, Mihály. “Az újratelepülő Tolna megye 1710–1720” [Tolna County resettled: 1710–1720]. In Tanulmányok Tolna megye történetéből 10 [Studies on the history of Tolna County], edited by János K. Balog, 33–169. Szekszárd, 1983.

Szita, László. “A lutheránus németség bevándorlása és településtörténete Tolna megyében a 18. században” [The immigration and history of the Lutheran Germans in Tolna County in the eighteenth century]. In Tolna Megyei Levéltári Füzetek 5, edited by Gyula Dobos 5–163. Szekszárd: Tolna Megyei Önkormányzat Levéltára, 1996.

Szőts, Zoltán. A völgységi nemzetiségi-etnikai csoportok együttélése a második világháborútól napjainkig [The cohabitation of national-ethnical groups in Völgység from World War II to the present day]. Völgységi Múzeum, 2007.

Török, Enikő. “A kataszteri részletes felmérés előrehaladása Magyarországon 1856 és 1916 között” [The progression of the cadastral detailed survey in Hungary between 1856 and 1916]. Catastrum: Évnegyedes Katasztertörténeti Folyóirat 2, no. 1 (2015): 11–18.

Várady, Zoltán. “Bonyhád a törökkor végétől Mária Terézia koráig [Bonyhád from the end of the era of Turkish occupation to the rise of Maria Theresa]. In Előkészületek Bonyhád monográfiájához: előadások a IV. Völgységi Konferencián [Preparatory work for a monograph on Bonyhád: Presentations held at the Fifth Völgység Conference], edited by János László, and Zoltán Szőts, 83–92. Bonyhád, 2006.

Van Leeuwen, M. H. D. and Maas, I. HISCLASS: A Historical International Social Class Scheme. Leuven: Leuven University Press, 2010.

Wickham, Hadley. ggplot2: Elegant Graphics for Data Analysis. New York: Springer, 2016.

1 Szőts, A völgységi nemzetiségi-etnikai csoportok együttélése, 196.

2 Bácskai and Nagy, “Piackörzetek,” 49, 222.

3 Ibid., 252.

4 Solymár, “Bonyhád – hajdan Bonyha,” 42.

5 Várady, “Bonyhád a törökkor végétől,” 88.

6 Magyarország történeti statisztikai helységnévtára, 42.

7 Schmidt, Német telepesek bevándorlása, 81.

8 Várady, “Bonyhád a törökkor végétől,” 88.

9 Szita, A lutheránus németség bevándorlása, 7–8. Fényes, Magyarország geographiai szótára; Bonyhád, 238.

10 TML V. 709./c

11 Péter Őri and Levente Pakot introduced the preservation of Hungarian individual-level materials of the census of 1869, see Őri and Pakot, “Háztartásszerkezet.” The following studies analysed these sources on the micro-level: Torna County: Pozsgai, “Családok és háztartások;” Magyaróvár: Horváth, “Város a városban;” Kiskunhalas: Őri, “Kiskunhalas népessége;” Sátoraljaújhely: Demeter and Bagdi, A társadalom differenciáltsága; Mohács: Gyimesi, “Mohácsi háztartás-rekonstrukció.”

12 Katus, Modern Magyarország, 158, 175.

13 Where a similar investigation was carried out for the census sheets of 1869.

14 Demeter and Bagdi, A társadalom differenciáltsága, 17.

15 The problematics of Wohnparteien is inevitable for researchers who are working with census materials. The expression was transferred to the Hungarian vocabulary from the German instructions for the census in 1850. The differentiation of the notions of Wohnpartei and households led to difficulties and differences in interpretation because of varying practices used by the census takers. Detailed explanation of this topic: Őri and Pakot Residence patterns, 14–15; Őri and Pakot, “Háztartásszerkezet,” 169–71. In our analysis, we use the notion of Wohnparteien in the sense of households adjusting to the practices of census takers.

16 Őri, “Család és házasodás,” 75. The difference can be caused by the abovementioned diversity of the practices of census takers, but in all likelihood it shows real disparity.

17 The average size of households in Pest County (1869): 4.65 people (Őri, “Család és házasodás,” 75.). In Mohács (1869): 4.5–4.6 people (Gyimesi, “Mohácsi háztartás-rekonstrukció,” 12.). In Sátoraljaújhely (1869): 4.6 people (Demeter and Bagdi, A társadalom differenciáltsága, 13, 60.). Levente Pakot found higher values in the Székely Land: 5.4 people per households (Pakot, “Családok és háztartások,” 272).

18 Almost two hundred different occupations were identified in this column.

19 Van Leeuwen and Maas, HISCLASS.

20 Őri and Pakot, “Residence patterns,” 17.

21 Laslett, Introduction, 1–89.

22 “filling in the column of ‘citizenship’ notice, according to which everyone who has been settled in the community for a year now and has lived there permanently and has no residence in another village at the time of the census is a resident.” Népszámlálás 1869. 4.

23 Török, “A kataszteri részletes felmérés,” 11.

24 Biszak and Timar, Tolna megye.

26 Demeter and Bagdi did a similar analysis of the spatial patterns of settlement in Sátoraljaújhely. Our study attempts to reflect their aims. Demeter and Bagdi, A társadalom deifferenciáltsága.

27 The same indicator in Sátoraljaújhely in 1869 is 2.9 people/room (1.5 room/family), which means that in Bonyhád less residents were living in one room on average. Demeter and Bagdi, A társadalom differenciáltsága, 19.

28 Kolta, “A közigazgatás változásai Bonyhádon,” 15.

29 Solymár, “A történeti Völgység,” 20.

30 Knabel, Geschichte Bonyháds, 13.

31 Ibid., 14. Settlement according to denomination: Solymár, “A történeti Völgység,” 21. Principle of one village – one religion: Schmidt, Német telepesek, 49.

32 Knabel, Geschichte Bonyháds, 19.

33 Jews only began to be permitted to settle freely, engage in a trade freely, and purchase land in the 1840s. Katus, Modern Magyarország, 107.

34 The laws of Charles III encouraging resettlement with “1723. évi CIII. törvénycikk az ország benépesítéséről” [law of peopling the country] (promising 6 years of tax exemption for every free person). In the same year, another law arranged for the “support for the arrival of various craftsmen to the country” (1723. évi CXVII. törvénycikk), promising 15 years of tax exemption for them. Landlords also wanted to find workers to work on their estates, so in the early eighteenth century, they began to offer three years of tax exempt-status for the arable lands and mills and six years for the vineyards. Szilágyi, “Újratelepülő Tolna,” 35.

35 The isolation among denominational and occupational groups is observed in the case of marital customs. Roman Catholics and people belonging to the Orthodox Church were more closed in this respect than Lutherans and Calvinists. Marriage between Catholics and Jews was not allowed until the end of the nineteenth century. Lippényi et al., “Social status,” 8.

36 The results of analysis of employees partly correspond to the conclusions in case of Sátoraljaújhely (e.g. Jewish servants/maids served in Jewish households), but some issue was different according to the data of Bonyhád. The phenomenon of Calvinists preferring employees from the same denomination was not confirmed by our data, but the reason behind this could be the small number of Calvinists in Bonyhád. Demeter and Bagdi, A társadalom differenciáltsága, 21.

37 The employees emerged from younger age-groups than the average (the mean age of the total population in Bonyhád was 26.75, while in the case of servants it was 25.84 years and in the case of apprentices it was 25.91 years. Most of them were single, which fits the lifecycle-servant part of Hajnal’s theory (Hajnal, “European marriage patterns”). Hajnal thought this was a West European phenomenon, but more research has shown that this statement should perhaps be reconsidered. This topic is discussed in Faragó, “Különböző háztartás-keletkezési rendszerek.”

40 R Development Core Team, 2008.

41 Wickham, ggplot2.

42 Kahle and Wickham, ggmap.

43 Guangchuang, scatterpie.

* Supported by the ÚNKP-18-3-IV-PTE-323 New National Excellence Program of the Ministry of Human Capacities.

Figure 1. Population density (people/room), Bonyhád, 1869

3_lakosuruseg_atl.png

Figure 2. Religion of the population, Bonyhád, 1869

4%20religion_atl%20(1).jpg

Figure 3. Occupation of the population, Bonyhád, 1869

5_occ_code2_atl%20(1).jpg

Figure 4. Spatial distribution of certain artisans, Bonyhád, 1869

6_nehany_fogl_atl.png
Gyimesi-k%c3%a9p.jpg
Gyimesi-k%c3%a9p2.jpg

Figure 6. Main square of Bonyhád on the final vector graphic map

pdfVolume 8 Issue 1 CONTENTS

The Notion of Space on Railway Maps of the Habsburg Monarchy / Austria–Hungary

Arlene Peukert
Andrássy Universität Budapest
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In this article, the notion of space on railway maps of the Habsburg Monarchy/Austria-Hungary is analyzed and interpreted. Two railway maps from the 1840s and one network map from the 1860s are examined from the perspectives of their visual language and inherent communication mechanisms. A reciprocal approach to maps is applied. The context in which maps are created (production and consumption) is taken into consideration, as is the context which is created by maps (spaces as cultural products). The desired outcome is a synopsis of the plurality of spaces envisioned in the mid-nineteenth century contrasted with the process of unification of space spurred on by the continuous expansion of railway networks. Topics addressed in this article are the rendering of nature and terrain on maps, the beginning development of a railway corridor into a network of lines, the depiction of networks, the hierarchization of territory in the visual language of maps, and the marking of space as a national territory.

Keywords: railway, maps, cartography, space, network, Habsburg Monarchy, Austria–Hungary

Introduction

In the first half of the nineteenth century, the railway started to transform the landscape and, with it, people’s perceptions of the world around them and the ways in which they moved through it.1 Novel notions of space found themselves translated into railway maps produced by engineers, planers, railway companies, publishing houses of maps, guide books, and atlases.
This paper focuses on three railway maps from the middle of the nineteenth century (1845, 1843, 1869), with the aim to show how the presentation of space in the Habsburg Monarchy/Austria-Hungary differed from map to map in the same railway project and also changed significantly over the course of only two to three decades. I outline factors accounting for these altered perceptions of space and their manifestations on maps.
My intention is to provide a synopsis of the diversity of spaces (physical, perceived, and conceived)2 on mid-century railway maps of Austrian/Austro-Hungarian provenance.

In his 1988 essay “Maps, knowledge, and power,” historian and geographer John Brian Harley (1932–1991) formulates the hypothesis that maps are cultural products which have different layers of meaning.3 Maps are never to be seen only as a presentation of geographical features, but rather must be read as a form of manipulated knowledge.4 Contextualizing maps is, according to Harley, an effective method of making maps speak about the “social worlds of the past.”5 Since at least the Middle Ages, when new structures of governance started to form, maps were used to document and legitimize claims of power in space. Images and symbols on the maps which dealt with historical, political, and mythological episodes underline these claims and are part of the communicative vocabulary of cartography.6 Although maps over time became more accurate due to improving measuring techniques and gained an aura of relative objectivity, they were nevertheless value-laden products of society.7

In order to decode the visual language of maps an interdisciplinary approach is advisable. Following Harley’s methodology, pictorial, textual, and sociological components of railway maps are going to be taken into consideration to reveal communicative patterns and mechanisms of power in maps8 and offer, on the basis of this, insights into the ways in which maps can be interpreted as expression of and tools with which to shape perceptions of space.

Railway maps are a relevant addition to the broad field of research related to the history of railway and railway transport in the Habsburg Monarchy/Austria-Hungary. Although in recent decades, especially since the proclamation of different “turns” in the humanities and social sciences, more attention has been paid to the cultural, social, economic, etc. aspects of the railway, plans and maps of railway lines and the inscribed notions of space continue to constitute a hitherto overlooked topic.9 Consequently, reflecting on historic topics from a spatial perspective can perhaps yield new insights which will prompt further research on railway history.

How the railway Transformed Space and Time – Manifestations of Spatial Perceptions on Railway Maps

Space10 and time are complex phenomena. They constitute the coordinate system of our terrestrial existence in which, knowingly or instinctively, we place every subject, object, and act. Orientation without the context of space and time is impossible.11 Without reference points, we would inevitably be lost, and we would lack any understanding of who we are and where we come from.12 Humanity has continuously endeavored to develop an understanding of time and space and arrive at systems with which to measure them. The invention of calendars and clocks turned time into a cultural product. The superimposed linearity and sequentialness of time, which are also reflected in the ways in which some human languages are composed, make it easy for us to locate events in a chronological order.13 Historical events become narratable: event A happened at a point in time before event B took place. Both events can be marked with a clear beginning and ending and stand in relation to each other.14

Space, however, eludes from our efforts to document and narrate it due to its multidirectional dimensions and the simultaneousness and coexistence of coordinates. Space is not linear.15 In order not to get lost, we apply similar methods to tracing space as we use to structure time. Movements in space are transformed into lines which can then be transferred to a two-dimensional surface: a map. In the form of lines and points on maps, space, which has no beginning and no ending and is consequently hard to narrate, becomes fixed and more controllable.16 Maps, thus, are always a reflection of how people see the environment.

The railway system (and maps thereof) can be understood as manifestation of a new spatial awareness and at the same time as tool(s) which shaped space and produced a new form of cultural space.

Historian Wolfgang Schivelbusch argues, that with the reduction of travel time, the railway helped shrink space and brought places closer together. At the same time, the increased speed of travel meant that people could reach faraway places in a much shorter time. For travelers, the space between stations lost importance, while beginning and end points of travel became increasingly significant.17

Last but not least, schedules oriented around departure and arrival times made the introduction of a standard time necessary, that by the 1890s replaced local times in Central Europe.

The railway touched and changed many parts of life in the nineteenth century and consequently also replaced an old space-time continuum with a new one.18 By tracing this novel perception of space on railway maps, we can enhance our understanding of the specific view map producers and map users had of a place or territory (mental maps19) and the ways in which this view changed over time. We can learn how authorities, stakeholders, constructors, landowners, and key political players positioned themselves and others in space, how they constructed their identities within a newly emerging understanding of space, and how this understanding of space itself was shaped and controlled.

The Development of the Railway and Railway Maps in the Habsburg Monarchy/Austria–Hungary

The history of the Austrian railway in the nineteenth and early twentieth centuries is commonly divided according to the phases of ownership and financing of railway projects.20 It should be mentioned however, that a clear timeline of railway periods cannot always be followed, as gaps between the order and final implementation of railway-related laws occurred.

Following a pioneering phase of private funding and planning of the first railway lines between 1824 and 1841, a phase of railway construction under state initiative took place from 1841 to 1854/5821. Having finally grasped the potential of this new means of transportation, the state wanted to bring the railway under its control in order to push the construction of new lines and connections independent of the financial aims of private investors. The expansion of the lines of the Emperor Ferdinand Northern Railway and the Southern Railway were among the most urgent infrastructural development plans.22 Furthermore, the Milan-Venice railway line (Venedig-Mailänder Bahn) was completed in 1846, and the challenging Semmering railway (Semmering Bahn), as part of the Southern Railway, and the Empress Elisabeth Railway (Kaiserin Elisabeth-Bahn) were built under state control. Financial restrictions put an end to the first state phase in 1854. A new railway law aimed at private investors obliged them to disclose the details of their planned railway projects for the state to check and approve.23 Between 1854/58 and 1873/80 the railway network of the monarchy grew significantly. However, private investors recoiled from financing railway projects that made sense only for the infrastructural development of the monarchy and promised less profit. Lines deemed important by the state, like the Arlberg Railway (Arlbergbahn) or a railway along the Dalmatian coast, could not be realized during that period. The financial crisis of 1873 forced the state to engage more actively in the railway program once more. The construction of the Arlberg tunnel in 1880 marked the beginning of a second phase of railway construction under state control.24 In addition to investing more money in private railway projects, the state also funded the construction of lines of pressing importance. In 1896, the k.k. Railway Ministry in Vienna was founded with the function of monitoring and controlling railway traffic and railway projects in the Austrian lands of the Dual Monarchy. In the last phase of railway politics, the New Alps Railways were built.25 Also, minor connections were created. The collapse of the Austro-Hungarian Monarchy in 1918 lead to the breakup of the vast railway network, as huge parts of it were then situated in the neighboring countries, two of which were newly created states.

Numerous diary entries, episodes from fictional literature, drawings, and paintings demonstrate how the novelty of rail travel was perceived in the nineteenth century.26 This new medium not only found novel forms of expression in art and literature, it also demanded improved techniques and approaches in the scientific documentation of railway tracks.

Before people engaged in travel on a grand scale, the military and the state were the primary users of most of the manuscript maps produced in the eighteenth and nineteenth centuries. These maps were to a large extent kept under strict control and treated as secrets, as in times of conflict and war detailed maps of the territory could provide the enemy with crucial information.27 The development of the street network in the Habsburg Monarchy and the emergence of the stage coach system in the seventeenth century resulted in the production of new road maps and stage coach maps which were made available to the public as well.28 At the beginning of this phase, roads and stage coach connections were often added to topographic maps, for instance from the Austrian land surveys.29 Later, with the rise of rail and steam boat travel, further traffic connections had to be integrated into the maps. In the interest of legibility, thematic travel maps were made in the nineteenth century.30 Slowly but surely, railway maps started to supersede the stage coach maps.31 Due to the growing density of the railway network from the middle of the century onwards, railway maps grew in scale and complexity; detailed traffic and railway atlases were published. Furthermore, thematic travel maps were adapted to the users’ needs.32

The railway line Wiener Neustadt–Ödenburg – A case study on Two Different Perceptions of Space In Early Railway Maps

One of the earliest railways of the monarchy, the line between Ödenburg (Sopron, Šopron) in the Hungarian lands of the empire and Wiener Neustadt was planned and built between 1840 and 1847.33 The plan for this line was a joint venture of the Hungarian aristocrats Pál Esterházy (1786–1866), count István Széchenyi (1791–1860), and the banker Georg Simon von Sina (1783–1856). The Hungarian nobles wanted the railway to come to Hungarian lands. Count Széchenyi greeted the project commissioned by the king Ferdinand I of Austria (1793–1875)34 with great enthusiasm:

With this [project] a bright star rose for the West of Hungary; its growing radiance will illuminate the tracks of its [Hungary’s] future rapid progress. (Ein heller Stern ist damit dem Westen Ungarns aufgegangen, dessen wachsender Strahlenglanz die Bahnen seines zukünftigen raschen Fortschrittes erleuchten wird.)35

In 1845, construction work under the oversight of Mathias Schönerer (1807–1881)36 began. The track between Ödenburg and Wiener Neustadt is 31.9 kilometers long and passes through slightly hilly terrain. Leaving Wiener Neustadt, the train crosses the river Leitha (Lajta) and, thus, the former Austrian-Hungarian border. On its way to Ödenburg, the train passes by the villages Katzelsdorf and Neudorf/Neudörfl (Lajtaszentmiklós/Najderflj). The track then runs alongside the Rosalien Mountains. Several embankments and cuttings were built to cover height differences of the terrain. Before reaching Mattersdorf (since 1924 Mattersburg/Nagymarton/Matrštof), the train has to ascend the steepest part of the track (with an incline of 10.5 percent). The station in Mattersdorf was the largest on the entire line. After crossing another hill, the train passes by the villages Marz (Martz/Márcfalva/Marca), Rohrbach (Fraknónádasd/Orbuh), Loipersdorf (Lépesfalva), Schattendorf (Somfalva/Šundrof), and Agendorf (Ágfalva/Agendrof). The station on the western periphery of Ödenburg was then to constitute the end of the line.37 From the beginning of the planning period, the railway line was laid out to be double-tracked, which shows that planners expected a high volume of traffic for the line, which potentially would be prolonged to the south.38

Two monumental viaducts were built by Schönerer for the track: the Mattersburger Viadukt and the Wiesenviadukt. Both viaducts show architectural features similar to the architecture later employed in the Semmering route. It is likely that ideas for the challenging Semmering project built as part of the Southern Railway between 1848 and 1854 by Carl von Ghega (1802–1860) were put to the test in this less demanding terrain.39 Shortly after the line opened in 1847, traffic volume on the route was high, bringing economic growth to the region of Mattersdorf and Ödenburg for a short time.40

A brief comparison of the two railway maps of the same line from Ödenburg to Wiener Neustadt produced in 1843 and 1845 (Figure 1 and Figure 3) shows that different ways of presenting one and the same railway line can lead to very different visual results. Consequently, the spaces captured and reimagined by the mapmakers and commissioners differ to some extent.
Different reasons might explain the different approaches to the representations chosen for the manuscript maps, with the date of map production, the function of the map, and the prospective audiences being the most obvious. However, we often have little information concerning these kinds of factors, in particular the functions of the maps and the prospective audiences, and thus we can do little more at this point than venture guesses. If we consider the possible visual strategies of which these two maps seem to be the product, we can, however, hazard some hypotheses concerning the aims of the mapmakers.

The Role of Nature In Early Railway Maps

Map number one, entitled Uibersichtskarte der zwischen Oedenburg und Wiener-Neustadt im Jahre 1845 im Bau begriffenen LOCOMOTIV-EISENBAHN (Figure 1), is a manuscript map on paper with relatively large measurements (106 × 85 cm). The terrain is not shown in its entirety and the image does not fill the sheet; rather, the user of the map is given a cut-out of the topographic landscape stretching diagonally between Wiener Neustadt and Ödenburg. Large blank spaces on the map’s edges are used for the heading (top center) and a scale bar (bottom left). Linear measures on the map are indicated in Wiener Klafter (Vienna fathom), 158 mm = 2400 Kl. or 1 : 29,000.41 Further inscriptions are featured either directly on the topographic drawing or next to it. Roads are featured as thin black lines. The border between Austria and Hungary is shown as a thicker, broken line. Still, the border is not over-accentuated or strikingly prominent on this map.42

The projected railway line is colored red, establishing also a visual connection between Ödenburg and Wiener Neustadt. Interestingly, shortly before it reaches Mattersdorf, the track forks, which shows that in 1845 (relatively late in the planning process of the line), another option for the track which had been discussed in 1838 had not been ruled out.43 Crossing the valley near Mattersdorf was a challenging task which Schönerer was only able to solve almost ten years after the first plans were made with better knowledge of railway construction, which he acquired in part during his travels to England and America.44 The two town plans of Ödenburg and Wiener Neustadt are executed in greater detail and colored red as well. This accentuation automatically establishes a visual hierarchy among the villages and towns on the map: Ödenburg and Wiener Neustadt are of greater significance.

The visually most striking feature of the map, however, is the depiction of the terrain. Although declared in the title of the map, the projected railway track is not its sole focus. The topography of the landscape is much more prominent to the eye. This begs the question: why did the mapmaker, whose name was not indicated, chose this mode of presentation? Can we perhaps identify visual traditions to which the mapmaker was harking back which would explain the accentuation of nature and the terrain?

The dense placement of hachures to model the form and height of hills and slopes and the use of primarily dark colors like browns and greens make it hard to read the cartographic symbols and labels and spot the course of the railway line at a single glance. Color patches and hachures form a solid visual entity. The visual dominance of landscape features and landscape rendering indicates that the concept of space inscribed into the map was still routed in an environment dominated by nature. Building traffic infrastructure still meant an adaption to landscape. Although humans remodeled the environment according to their needs, until the nineteenth century, hills, mountains, and rivers still presented barriers that could only be overcome only with difficulty and effort. The course of a street or the position of a dwelling, harbor, or bridge were strongly geo-determined.45 It is thus comprehensible that topographic features seem to be disproportionally presented in especially early railway maps: the supremacy of nature and the achievement of partly overcoming natural barriers (for instance by building viaducts46) are inscribed into the visual language of the map: the railway starts to subdue nature. Moreover, for constructors and financers, the exact course of the line, possible obstacles on the way, the position of stations and the feasibility of a project (which depended on these factors) were of central importance. Maps for this user group had to be detailed and precise.

The visual language of the map from 1845 is from many perspectives in line with stylistic traditions of eighteenth-century and early nineteenth-century topographic cartography. Extensive field measurements were being taken with increasing frequency and regularity in Western and Central Europe in the eighteenth century, as absolute rulers sought to document their entire sovereign space. These were the first attempts to measure every detail of the environment scientifically, resulting in accurate maps of the terrain. The first official field measurements of the Austrian crownlands were taken during the reign of Maria Theresia (1717–1780) by the military (Josephinian Land Survey/Josephinische Landesaufnahme/Erste Landaufnahme, 1764–1786).47 Between 1764 and 1786, more than 3,500 maps were drawn. A second Austrian land survey was conducted in the first half of the nineteenth century (Franziszeische Landesaufnahme, 1806–1869). Topographic maps produced during both land surveys show stylistic characteristics similar to the stylistic characteristics of the railway map from 1845. From the perspectives of image section, choice of colors, script, cartographic symbols, depiction of terrain, use of hachures, depiction of infrastructure, framing of the cartographic content, etc., especially maps from the second Austrian land survey show striking similarities to railway map.

As pointed out by Krenn, particularly during an early stage of the railway age, railway lines were additionally drawn into older topographic maps.48 Is the railway map from 1845 thus actually an updated version of an older topographic map from the region between Ödenburg and Wiener Neustadt? Without an in-depth analysis of topographic maps from the two land surveys, this assumption cannot be proven or ruled out.

New topographic maps of the area around Wiener Neustadt were made in 1820.49 For the Hungarian land, however, the latest maps were only from around 1782–1785.50 The area behind the Austrian-Hungarian border was not officially mapped again until 1856 (e.g. Pöttsching (Pecsenyéd/Pečva), Pöttelsdorf (Petőfalva), Mattersdorf, Sopron, Agendorf).51 The different dates of origin of the survey maps suggest that the mapmaker of the railway map from 1845, rather than adding information to an older map, used different topographic maps from the area to draw the railway map Uibersichtskarte der zwischen Oedenburg und Wiener-Neustadt im Jahre 1845 im Bau begriffenen LOCOMOTIV-EISENBAHN.

Because no information about the cartographer of the map, its customer, or place of presentation or publication is given on the map sheet, we can only speculate about the purpose of the map. Furthermore, we do not know whether copies of the manuscript map were made. A higher number of publicly available copies would also imply a larger circle of potential map users. Given the year in which the map was produced (in 1845, the railway line was still under construction), the prominent heading, and the way in which the railway connection is presented as a red line cutting across the hilly and challenging landscape, it is imaginable that the map addressed potential buyers of stocks for the railway line rather than travelers. In April 1845, during the general assembly in Ödenburg, it became obvious that the railway project would be much more expensive than estimated. Instead of 1.5 million Gulden, construction of the railway line would cost more than 2 million Gulden. The two monumental viaducts, changes in the track, and a restaurant near the station in Ödenburg led to an increase in costs. New stocks had to be sold in order to cover the expenses and advance construction work.

Space as a corridor: The narrow view of mapmakers concerning
the railway line from Ödenburg to Wiener Neustadt

A phenomenon present especially in early railway maps is a corridor-like view of the mapmakers concerning the railway lines and the landscapes along the track. The geo-determinacy of infrastructure apparent from the visual language of map one is also reflected in the mapmaker’s relatively narrow view of the terrain. Apart from the projected railway line, other factors relevant for the construction of the track are mapped, such as the terrain, nearby settlements, and infrastructure. As noticeable from map one, a favorable course of the route through uneven, hilly landscape required to some extent an adaption of the track to the terrain, resulting in a situation in which the railway line is more or less enclosed by natural barriers (hills, slopes, rivers, streams, etc.). One gets the impression of a natural corridor. The terrain outside the sphere of influence of the railway line is irrelevant to the project and user groups of the map, and consequently, this area is not featured (blank spaces on map).

In addition to creating a depiction of nature and natural barriers as a corridor, the engineers’ and mapmakers’ view of space also resulted in a narrow corridor perspective that ultimately was translated onto the map. The design of the railway track, the beginning and end points, and stops on the way compose the corridor. Especially in the first decade of steam-powered rail traffic, when a network of rails had not yet been established and connections existed primarily between cities or other points of economic interest, it was not yet seen as necessary to document other long-distance traffic connections. From the point where a railway line stopped or ended, travel was continued using means which had been in use before the age of the railway: by stage coach or on foot.

On the railway map from 1845 as well as on the map from 1843, roads are shown, but they mostly lead to nowhere. Still, we find indications of direction (e.g. Weg nach Froschdorf, Figure 1).

The railway map from 1843, Situations Plan der Neu anzulegenden Eisenbahn, von Oedenburg bis Wiener Neustadt (Figure 3), pushes the notion of space as corridor even further.

 

Figure 3. Situations Plan der Neu anzulegenden Eisenbahn, von Oedenburg bis Wiener Neustadt, (General site plan for the future railway from Oedenburg to Wiener Neustadt), Mihály Vágner, (222 × 48,5 cm), hand drawn, colored, on paper, 1843. Accessed on October 7, 2018.
https://maps.hungaricana.hu/en/MOLTerkeptar/7688/view/?bbox=-1170%2C-8926%2C27792%2C2862

 

Map three shows another, not realized trace design in which the railway track was planned to go through the villages Pöttelsdorf, Draßburg (Darufalva/Rasporak), and Baumgarten (Sopronkertes/Pajngrt). The mapmaker was Mihály Vágner from Ödenburg. The map is relatively large in size (222 × 48,5 cm), has an elongated format,52 and is hand-drawn on paper. The elongated manuscript map focuses almost exclusively on the planned railway line, and the surrounding area is left out. From the perspective of style, the map resembles traditional road plans and maps for waterways.

In comparison to the map from 1845, surroundings are rendered more schematic. Landscape characteristics are presented in a plain, nearly geometrical form, as was typical for cadastral maps and site plans of that time. The environment along the track is given little importance. Forests, fields, and streams are cut off at the edge of the corridor. The planned railway line is superimposed onto the existing network of villages and roads, establishing a linear connection between both cities and, thus, a new hierarchy within the region. Within the spatial corridor of the future railway line, the distance between the cities Ödenburg and Wiener Neustadt shrinks significantly. The space to the left and the right the track is considered irrelevant to the new form of travel. Or to use Schivelbusch’s phrasing, the space untouched by the railway gets eliminated.53

Another interesting component of the map from 1843 is that the area behind the Austro-Hungarian border (around Wiener Neustadt) is almost left blank. It is possible that Vágner, who was a Hungarian engineer, official of Sopron County, and land surveyor, had no detailed cadastral information about the Austrian land and that part of the railway line at hand. Also, in 1843, there were still two railway companies responsible for the construction of the line, which is why Vágner might have produced this manuscript map especially for the Hungarian planning team of the Ödenburg-Wiener Neustadt company. A signature on the map sheet with the note “Copirt” indicates that the map is a copy of the original Vágner Situations Plan. The map thus might have been copied several times and spread among a wider group of users. We do not yet know by whom (e.g. constructors, investors, the public) and to what purpose copies of the Vágner railway plan were used.

From corridor to network – The growing importance of traffic junctions on railway maps

Although, as discussed above, the Situations Plan from 1843 does not provide information about the landscape on the Austrian side of the planned railway line, the future traffic junction in Wiener Neustadt (marked as Stationsplatz) is already indicated on the map.54 Here, the line from Gloggnitz to Vienna was going to cross, forming a traffic connection between the Austrian and the Hungarian lands. Though frequent travel by train was not yet very common in the 1840s because a network of lines had not yet been established,55 both maps nonetheless seem to presage the importance of traffic junctions for movement and communication in the Habsburg Monarchy. Although in 1843 the line between Ödenburg and Wiener Neustadt had not yet been built and the southbound railway line was only completed between Vienna Südbahnhof and Gloggnitz, Vágner and/or the potential initiator of the map deemed this traffic junction and the growing network of lines significant for the region.

For the next roughly eighty to one hundred years to follow, until the emergence of automobiles and air traffic, railway lines and train stations remained the most powerful hubs and channels along which people, goods, ideas, images, innovation, and ideologies traveled. They hastened the pace of industrialization, migration, and urbanization, as well as the exploitation of nature.

 

The railway map published in 1869 by Lehmann & Wentzel in Vienna entitled Neueste Eisenbahnkarte der ÖSTERREICHISCH-UNGARISCHEN MONARCHIE: mit Berücksichtigung der Montan und Industrie Bahnen (Figure 4) shows many characteristics with which the modern-day user of traffic maps is accustomed: a stereographic projection of the area’s surface, a network indicating actual geographic position and schematized layout, station names arranged above one another for better legibility, and a color code for the single branches to simplify orientation. The user finds a coordinate system and a legend listing railway lines and associated color codes. Lines planned or under construction are marked with different graphic signatures (e.g. two thin black lines for a planned track and an alternating pattern of black and white stripes for a railway line under construction). Over the course of twenty to thirty years, a map language for railway lines used in travel developed in Europe and the Habsburg Monarchy/Austria-Hungary which in many ways is still valid today. Given the need to document the growing network and most of all to facilitate travel, the map language focuses on overview and orientation.

The title of the map, displayed in a rectangular cartouche, denotes the fast rate with which the railway network grew at the time. The user holds in his/her hands the newest railway map (die Neueste Eisenbahnkarte) which shows that map production tried to keep pace with the expansion of the network. In the second half of the century, updated maps had to be published frequently; also, the demand for maps was high. Network maps were among the most common in the second half of the century.56 Between 1857 and 1866 the railway network of the monarchy grew at a yearly rate of 327.5 kilometers. As of 1867, that rate rose to 1,352 kilometers of new railway tracks per year.57 Isolated corridors evolved into far-reaching networks with travel connections to many parts of the Dual Monarchy and beyond. The network stretches from the Austrian-German border in the northwest to the Adriatic coast in the south, from Innsbruck in the west to Karlsburg (Alba Iulia/Gyulafehérvár) in Transylvania. Particularly in the northwest, Austrian railway lines connect with the German network, making travel and trade truly international.

As a single glance at the map reveals, Vienna is in the center of the railway network. A majority of the lines built by the middle of the century radiate from the capital Vienna towards national traffic junctions, the most important of them being Pest/Buda, Brünn (Brno), and Prague. From here, the network further expands to regional traffic junctions. In the Austrian part of the empire, the railway network is much denser than in the eastern lands of the monarchy. Many of the lines towards Galicia and Transylvania were still under construction at the end of the 1860s, resulting in cities like Lemberg (Lwiw/Lwów), Czernowitz (Csernyivci, Czerniowce, Cernăuţi), Kronstadt (Braşov/Brassó), and Hermannstadt (Sibiu/Nagyszeben/Hermestatt) being at the far-flung periphery of the monarchy’s network and thus difficult to reach.

The map language, cartographic symbols, and layout and arrangement of content on the map sheet direct the user’s gaze and influence the way the map is read. The center-periphery dichotomy, for example, automatically results in a hierarchy in the virtual space created by the map, which also translates back into perceptions of the physical space. When they see a given site in a central position, map users consciously or unconsciously associate it with power and control.58 All the other points on the map are of subordinate importance compared to the center, in this case, Vienna. Spatial distance is one factor in the establishment or maintenance of a hierarchy. The duration, frequency, and possibility of travel to a place are others. Mapmakers inevitably create hierarchies in space in the sense that the map language always implies a syntactic ordering of its elements. The reader of a map cannot avoid comparing the sites designated on the map and constructing hierarchical relationship among them.

In contrast to the map from 1845, the display of terrain and landscape features is of minor significance on the network map from 1869. On map four, landscape characteristics were reduced to mere markers for orientation. Lakes, rivers, and coastlines help the user of the map get a rough sense of location. Compared to the visual language of the railway map from 1845, where the terrain was very prominent to the eye, there is nothing overwhelming anymore in nature or natural barriers on the 1869 map. The reasons for this are, on the one hand, the changed purpose and thus user group of network maps and, on the other, the modified significance of nature for the railway. The most important reason, however, was simply the growth in rail travel. In the era of industrialization and growing railways, more than ever before, men remodeled nature according to their needs. Tunnels, viaducts, bridges, and embankments are evidence of men’s desire to tame nature and foster mobility. If feasible, a railway track no longer adapts to the terrain. Rather, it cuts through nature in a straight, linear path. Seen from the window of a train, nature and natural barriers lose parts of their daunting quality. While nature is still of importance for engineers, constructors, and investors in railway lines, for passengers, as can be seen in the network map from 1869, the environment becomes a sign on a sheet of paper, helpful if one wants an overview.

In the same sense, as the significance of natural barriers fade, the importance of the display of the country’s frontier rises. Apart from the railway lines, the border is the only feature on the map rendered in color (light red), and this draws the attention of the map user to it. Furthermore, the width of the border is remarkable. In comparison to the border of Austria-Hungary, the inner frontiers are barely visibly, presented as fine, dotted lines which can easily be overlooked among the railway lines and rivers. The idea of space and territory envisioned by the commissioner and/or mapmaker is one of unification and openness. The map talks about one space: one space of traffic, even one space of language and nationality, communicated by the exclusive use of German. Not only are the title and the legend of the map in German (only), names of cities, towns, and lands are also given only in German (assuming they had German names). This gesture erases or denies differences in language and ethnicity, making space seem more national. The multi-ethnic nature of the Dual Monarchy is overlooked (or denied) on the map. The network of railway lines is what binds the space together.

Conclusion

One objective of this paper was to show, on the basis of three railway maps of Austrian /Austro-Hungarian provenience, how the railway shaped space and produced new forms of (cultural) space and how these forms of altered spatial awareness found expression in maps. Taking the methodological approach of Harley into consideration, I analyzed two railway maps of the same railway project, the line from Wiener Neustadt to Ödenburg, from the perspective of the presentation of certain visual components. I showed that the dominance of presentations of nature in early railway cartography was related to a stronger geo-determinacy of early railway lines. Nature was still seen and also depicted in maps as a barrier which confined travel and was only overcome progressively by the middle of the century. In addition, the purpose and user groups of early railway maps could account for the strong accentuation of the terrain and nature in maps. In particular, investors wanted to be informed about the exact course of the line, the terrain, stations and stops along the track, etc. Natural barriers and the (comparatively narrow) range of use of early maps resulted in a corridor perspective concerning the railway lines. Once a railway line was finished, route maps were also used by travelers. Findings drawn from the 1843 map align with the general notion that the railway helped shrink space and even make space disappear.59 As fast train connections between important cities and villages were established, the space between stations lost its relevance for travelers, merchants, etc. It started to disappear from maps and, consequently, also from people’s mental maps. The railway also accelerated the hierarchization of space, which gains increasingly importance with the network maps appearing in the second half of the nineteenth century. Network maps were aimed at a broader public wishing to travel through the monarchy. Nature in these maps has lost its restricting character and became, as shown in the map of 1869, a marker for orientation. At the same time, while space was being hierarchized (e.g. a hierarchy of centers versus peripheries), it was also bound together and unified by the network of railway lines, which went parallel with the political aspirations of the time in the Dual Monarchy. The visual language of the network map from 1869 also suggests the nationalization of space. The perspective chosen on the land, the use of German, the emphasis on governmental centers (and thus power), and the stressing of the outer border of the Dual Monarchy are indications of a progressing nationalization and delimitation of space towards neighboring countries. Further research on the notion of space in railway maps will help provide answers to some of the questions raised in this essay.

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Wawrik, Franz. “Historische und Kulturhistorische Informationen in den Werken österreichischer Kartographen des 16. Jahrhunderts, mit besonderer Berücksichtigung des Wolfgang Lazius.“ In Geschichtsdeutung auf alten Karten, Archäologie und Geschichte Wolfenbütteler Forschungen, edited by Dagmar Unverhau, 193–212. Wiesbaden: Harrassowitz Verlag, 2003.

 

1 For an introduction to the history of the railway and its impact on space and time, see: Schivelbusch, Geschichte der Eisenbahnreise, 35–50.

2 The notion of a plurality of spaces emerged once space was no longer perceived as a container (or dead, passive stage, as Schlögel puts it). Spaces are historically constituted. They have a beginning and an end. They can disappear again. Consequently, we are not dealing with only one space, but a multitude of spaces which exist parallelly. See Schlögel, Im Raume lesen wir die Zeit, 68–69; and also: Marc Augé, Orte und Nicht-Orte: Vorüberlegungen zu einer Ethnologie der Einsamkeit (Frankfurt am Main: S. Fischer, 1994).

3 Harley, “Maps, Knowledge, Power,” 279.

4 In his seminal essay, Harley assumes that every map is a socially constructed form of knowledge. The specific codes embedded in the wider geographical discourse can tell us (cartographic communication/cartographic manipulation of perception) about power structures logged by the mapmakers. Harley lists several scenarios in which maps can be employed to convey a distinct message or function as a tool of communication: maps in the context of military and bureaucratic utilization, maps as a propaganda tool, maps as a surveillance tool, maps for legitimizing territorial claims. Harley puts maps in the large family of images, which is why he suggests an iconological approach, as derived from Erwin Panofsky (1892–1968), to decode symbols and imagery of maps. Furthermore, he writes about a cartographic language. Methods drawn from semiotics and literary criticism are suitable to identify the rhetorical and persuasive mechanisms in maps. Lastly, Harley points out the social constructiveness of maps. On the basis of Michel Foucault’s (1926–1984) and Anthony Giddens’ (1938) theories on historiography and social systems, Harley raises the argument that (manipulated) map knowledge is in itself a form of power that lies mainly in the hands of state authorities and transports political and ideological messages. Compare: Harley, “Maps, Knowledge, Power,” 277–312. The author, Rainer Vollmar, delivers a very on-point summary of Harley’s approach: Vollmar, “Die Vielschichtigkeit von Karten,” 381–95.

5 Harley, “Maps, Knowledge, Power,” 277.

6 Wawrik, “Historische und Kulturhistorische Informationen,” 193.

7 Harley, “Maps, Knowledge, Power,” 278.

8 See: footnote 4.

9 The first research on Austrian railway maps was conducted by Bettina Krenn and Johannes Dörflinger. In her diploma thesis from 1998, Krenn lists railway maps of Austrian provenance from the nineteenth and early twentieth centuries according to their type and field of use and delivers a description of the maps. See Krenn, “Eisenbahnkarten,” 1–221. Johannes Dörflinger also published on cartography and Austrian maps. An essay about Austrian railway maps from the beginning of the era until the outbreak of World War II is part of the small canon of scientific literature about railway maps of Austrian origin. See Dörflinger, “Österreichische Eisenbahnkarten,” 157–74.

10 Within the framework of this paper, it is impossible to give a solid introduction to the concept of space as understood in the humanities and cultural studies. The reader can consult the following introductory literature: Henri Lefebvre The Production of Space, translated by Donald Nicholson-Smith, 33rd ed. Oxford: Blackwell Publishing, 2013; Jörg Dünne, Stephan Günzel, eds., Raumtheorie: Grundlagentexte aus Philosophie und Kulturwissenschaften. Frankfurt am Main: Suhrkamp, 2006; David Harvey, “On the History and Present Condition of Geography: An Historical Materialist Manifesto.” In The Professional Geographer, 36 no. 1 (February 1984): 1–11; Stephen Kern. The Culture of Time and Space, 1880–1918. Cambridge/Mass.: Harvard University Press, 1983; Karl Schlögel. Im Raume lesen wir die Zeit: Über Zivilisationsgeschichte und Geopolitik Munich/Vienna: Carl Hanser Verlag, 2003; Edward W. Soja. Postmodern Geographies: The Reassertion of Space in Critical Social Theory, 8th ed. London: Verso, 1989; Martin Warnke. Politische Landschaft: Zur Kunstgeschichte der Natur. Munich/Vienna: C. Hanser, 1992; Martina Löw. Raumsoziologie. Frankfurt am Main: suhrkamp taschenbuch wissenschaft, 2001.

11 Schlögel, Im Raume lesen wir die Zeit, 49–51.

12 On space and identity, see Aleida Assmann. Erinnerungsräume: Formen und Wandlungen des kulturellen Gedächtnisses. Munich: Beck, 2006.

13 Schlögel, Im Raume lesen wir die Zeit, 50.

14 Ibid.

15 Ibid., 48–51.

16 Ibid., 51.

17 Schivelbusch, Geschichte der Eisenbahnreise, 35–39.

18 Ibid., 43–44.

19 Regarding the function of mental maps and mental mapping in spatial research in the social sciences and humanities see Sabine Damir-Geilsdorf, ed. Mental maps, Raum, Erinnerung: Kulturwissenschaftliche Zugänge zum Verhältnis von Raum und Erinnerung. Münster: LIT, 2005; Roger M. Downs, David Stea. Maps in minds: Reflections on cognitive mapping. New York et al.: Harper & Row, 1982; Frithjof Benjamin Schenk. “Mental Maps: Die kognitive Kartierung des Kontinents als Forschungsgegenstand der europäischen Geschichte.” Europäische Geschichte Online (EGO), Mainz: Leibniz-Institut für Europäische Geschichte, June 5, 2013, accessed on October 4, 2018. http://www.ieg-ego.eu/schenkf-2013-de

20 For a history of the Austrian railway see Karl Gutkas, ed. Verkehrswege und Eisenbahnen: Beiträge zur Verkehrsgeschichte Österreichs aus Anlaß des Jubiläums “150 Jahre Dampfeisenbahn in Österreich.” Vienna: Österr. Bundesverl. 1989; Harald Heppner. Der Weg führt über Österreich: Zur Geschichte des Verkehrs- und Nachrichtenwesens von und nach Südosteuropa. 18. Jahrhundert bis zur Gegenwart. Vienna et al.: Böhlau, 1996.

21 De jure the railway concession law from 1854 set an end to the phase of railway construction under state initiative. However, it took until 1858 to transfer railway lines to private owners/ enterprises.

22 Krenn, Eisenbahnkarten,” 7 and Bachinger, Das Verkehrswesen, 278–322.

23 Waldmüller, Quellenkundliche Forschungen, 73 and Krenn, Eisenbahnkarten, 7.

24 Krenn, Eisenbahnkarten, 7.

25 Praschinger, “Die österreichischen Eisenbahnen als wirtschaftlicher Faktor,” 104.

26 Needless to say, the railway and the new form of travel inspired arts, culture, and literature in the nineteenth century. William Turner’s (1775–1851) painting Rain, Steam and Speed – The Great Western Railway from 1844 or Claude Monet’s (1840–1926) railway and rail station paintings from the 1870s are a celebration of the new power of industrialization and travel. In the nineteenth century novel, authors like Max Eyth (1836–1906) and Max Maria von Weber (1822–1881) sought to capture every facet of life, putting the focus on engineers and train drivers. In his novel “Eine Winternacht auf der Lokomotive” from 1865 Weber portraits the hardship of a train driver during a winter night trying to keep the engine running, while the passengers enjoy themselves in the heated compartments. For further information on the railway as a motif in German literature see Mahr, Eisenbahnen, 46–51.

27 Lindner, “Landesaufnahmen deutscher Territorien,” 411–41.

28 Krenn, “Verkehrsgeschichte im Kartenbild,” 28–31. For more information on the stage coach system see Monika Diketmüller, Von der Postkutsche zur Eisenbahn in Niederösterreich im 19. Jahrhundert, PhD diss., University of Vienna, 1992; Christine Kainz. Österreichs Post. Vom Botenposten zum Postboten. Vienna: Verlag Christian Brandstätter, 1995.

29 Krenn, Eisenbahnkarten, 8.

30 Ibid.

31 Ibid.

32 Krenn, Eisenbahnkarten, 8–9.

33 For the history of railway travel in Burgenland, see Chmelar, 150 Jahre Eisenbahn.

34 In November 1844, the line between Wiener Neustadt and Ödenburg was commissioned by Emperor Ferdinand I. Capital stock of the railway came to 1.5 million Gulden; one stock was 200 Kronen. The commission and contract signed between the railway company and the vicegerent of Ofen was seen as valid for 50 years. Count Széchenyi, count Heinrich Zichy, and Eduard Tschurl signed the contract as representatives of the railway company. Chmelar, 150 Jahre Eisenbahn, 28; Benedek, Mattersburger Viadukt, 10–13.

35 Extract from a short speech in German delivered by Count Széchenyi during the general assembly for the commissioned railway line in March 1845 in Ödenburg. (Translation into English by the author.)
Hans Chmelar, 150 Jahre Eisenbahn, 14, quoted from Paul Mechtler. Die erste Eisenbahn im Burgenland. Burgenländische Heimatblätter, März 1962, 83.

36 Mathias Schönerer was a railway engineer of the Habsburg Monarchy. He was involved in the construction of the horse-drawn railway Linz–Budweis–Gmund (1827–1836). In 1841 the first railway tunnel on Austrian territory (near Gumpoldskirchen) was built under his lead. Later, he was responsible for the railway projects Vienna–Gloggnitz and Mödling–Laxenburg. During the revolution of 1848/49 Schönerer organized the first military transports via railway. From 1856 he was member of the board of administration of the Empress Elisabeth Railway (Kaiserin Elisabeth-Bahn), and from 1867 member of the board of administration of the Emperor Franz Joseph Railway (Kaiser Franz Josephs-Bahn). For his merits for the railway in the Habsburg Monarchy, Schönerer received knighthood in 1860. Accessed on 3 October, 2008.

http://www.literature.at/viewer.alo?viewmode=overview&olfullscreen=true&objid=12540&page=168; Benedek, Mattersburger Viadukt, 16.

37 Chmelar, 150 Jahre Eisenbahn, 18–19.

38 The double-tracked version of the line was not built, however, because of political tensions between Austria and Hungary in the 1840s. The Southern Railway should not run over Hungarian territory. See Chmelar, 150 Jahre Eisenbahn, 22 and Benedek, Mattersburger Viadukt, 10.

39 Chmelar, 150 Jahre Eisenbahn, 24–27 and Benedek, Mattersburger Viadukt, 12.

40 During the Hungarian revolution of 1848/49, traffic on the track between Ödenburg and Wiener Neustadt came to a halt. On April 10, 1848, local peasants of Mattersdorf damaged parts of the track markings because they never received compensation for their land, which they gave to the railway company in 1845. In an attempt to stop them, 224 soldiers from Ödenburg were sent to Mattersdorf. However, only troops from Vienna could finally cause the enraged peasants to withdraw. In autumn 1848, the border between Austria and the Hungarian lands was closed. These developments resulted in financial losses to the railway company. Although, the traffic in goods was profitable, the line generally did not yield the profit stockholders had hoped to get. In 1854, the line between Ödenburg and Wiener Neustadt was sold to the state. Chmelar, 150 Jahre Eisenbahn, 28, 35–36.

41 Figure 1 and accompanying metadata in the online database Hungaricana: https://maps.hungaricana.hu/en/MOLTerkeptar/3664/[October 5, 2018].

42 Because the railway line is a cross-border connection, the question of ownership and responsibility was addressed early in the planning process. It was foreseen that the part of the railway line on Austrian territory was run by the Vienna-Gloggnitz railway company, the newly founded Ödenburg–Wiener Neustadt company would be responsible for the part of the track on Hungarian soil. Both railway companies belonged to the banking empire of Sina. Finally, in March 1846, it was decided that the Austrian railway company should take over the management for the entire track. The division of responsibility between the two railway companies is not apparent, however, from the map, which suggests that it was of minor importance to the mapmaker. Chmelar, 150 Jahre Eisenbahn, 18.

43 On a map from 1838 entitled “Übersichtskarte der projectierten Tracen der Wien–Raaber Eisenbahn sammt Nebenzweigen. In der Ausführung begriffen unter der Leitung des Civil Ingenieurs M. Schönerer,” the railway line to Ödenburg was planned to follow a different route north of Mattersdorf. See Chmelar, 150 Jahre Eisenbahn, 12–13.

44 Ibid.

45 Denecke, 168–71.

46 The construction of the viaduct in Mattersdorf was challenging. Never before had a project of this size been completed. 4,000 workers, mostly from Bohemia, lived and worked under dreadful conditions. Landslides, accidents, and infectious diseases threatened the lives of the workers. Still, the viaduct was finished within two years. Benedek, Mattersburger Viadukt, 11.

47 The name Josephinian Land Survey relates to Maria Theresia’s son, Joseph (1741–1790), who from 1765 was responsible for military affairs and thus also supervised field measurements of the crownlands. See also:
Lindner, “Landesaufnahmen deutscher Territorien,” 426–428.

48 Krenn, Eisenbahnkarten,” 8.

51 For further information, study the georeferenced cadastral maps of the second land survey (Franziszeische Landesaufnahme) at https://mapire.eu/de/map/cadastral/?layers=osm%2C3%2C4&bbox= 1829206.8178942474%2C6055223.618854407%2C1853341.8095752918%2C6062867.321682924 Accessed on October 7, 2018.

52 The elongated format is typical for route maps. The format was first applied in England in the second half of the seventeenth century for the presentation of the most important streets in England. Later, especially during the 1830s and 1840s, route maps were used to document the first railway lines. The two main functions of these map types in the Habsburg Monarchy identified by Krenn, Kretschmer, and Dörflinger was to inform travelers and/or investors about details of the railway line (either for travel purposes or to provide an overview of the railway project). See Krenn, Eisenbahnkarten,” 9; Ingrid Kretschmer. Gebrauchskarten für den Verkehr. In Austria Picta: Österreich auf alten Karten und Ansichten, edited by Franz Wawrik, Elisabeth Zeilinger. Graz: Akademische Druck- u. Verlagsanst., 1989, 172, and Johannes Dörflinger, Eisenbahnkarte. In Lexikon zur Geschichte der Kartographie, edited by Ingrid Kretschmer, Johannes Dörflinger, Franz Wawrik, Vol. 1, Vienna: Deuticke, 1986, 187.

53 Schivelbusch, Geschichte der Eisenbahnreise, 35, 37.

54 The crossing of the two railway lines is also indicated on the map from 1845.

55 In the early age of rail travel, the number of passengers on the few existing lines was rather low compared to the number of passengers in the second half of the century. In 1848, approximately three million passengers were transported by railway. In 1873, this number grew to 43 million passengers per year. With the increase in the number of passengers, the importance of railway maps for travel grew. See: Waldmüller, Quellenkundliche Forschungen, 75.

56 Krenn, Eisenbahnkarten, 79.

57 Franz Baltzarek, “Die Finanzierung des Eisenbahnsystems,” 222.

58 Monika Gibas uses the term “myth of the middle” in her essay on German collective identity to denote certain topoi in which a group of people identifies with the middle as a place of power and superiority. Myths or narratives about the middle oftentimes serve to establish a sense of belonging and shared identity or to preserve inner territorial stability. See Gibas, “Auf der Suche nach dem deutschen Kernland,” 198.

 

59 Schivelbusch, Geschichte der Eisenbahnreise, 35–37.

1_Uibersichtskarte%20der%20zwischen%20Oedenburg%20Peukert.jpg

Figure 1. Uibersichtskarte der zwischen Oedenburg und Wiener-Neustadt im Jahre 1845 im Bau begriffenen LOCOMOTIV-EISENBAHN, (overview map for the locomotive railway line under construction in 1845 between Oedenburg and Wiener-Neustadt), colored drawing on paper, 106x85 cm, 1845, Inv.nr. E 96 1845, 9:14, National Archives of Hungary. Accessed on October 7, 2018. (https://maps.hungaricana.hu/en/MOLTerkeptar/3664/)

FranzLA_Preitenegg.jpg

Figure 2. Von Roesgen, lieutenant, Historic map, 2nd land survey, sheet sectio 02 Eastern colonne III Eastern Carinthia, Koralm area, area Preitenegg, Hebalm, sea level, Waldenstein, 1834/35, Militärgeographisches Institut der österreichisch-ungarischen Monarchie - Franziszeische Landesaufnahme, Preitenegg westlich der Hebalm. Accessed on October 7, 2018. https://upload.wikimedia.org/wikipedia/commons/0/0e/FranzLA_Preitenegg.jpg

3_Situations%20Plan%20der%20Neu%20PEUKERT.jpg
ac04078710_lehmann_oesterreich_1869.jpg

Figure 4. Neueste Eisenbahnkarte der ÖSTERREICHISCH-UNGARISCHEN MONARCHIE: mit Berücksichtigung der Montan und Industrie Bahnen, (Newest railway map of the Austro-Hungarian Monarchy: considering also the montane and industrial railway), publisher: Lehmann & Wentzel 50 × 69 cm, lithography, on paper, Vienna 1869
http://sammlung.woldan.oeaw.ac.at/layers/geonode:ac04078710_lehmann_oesterreich_1869 Accessed on October 7, 2018.

 

pdfVolume 8 Issue 1 CONTENTS

Social Differentiation and Spatial Patterns in a Multiethnic City in the Nineteenth Century: Potential Uses of GIS in the Study of Urban History*

Gábor Demeter and Róbert BagdiŰ
Research Centre for the Humanities, Hungarian Academy of Sciences
This email address is being protected from spambots. You need JavaScript enabled to view it.

This study is a GIS-aided quantitative statistical analysis which aims to explain the spatial patterns of sociodemographic phenomena in an urban community in the era of transition from preindustrial to industrial society. It is also a methodological attempt to use a unique source type and compare different methods used for social classification. Using the Hungarian census data from 1870, we tried to assess the wealth levels of different social groups indirectly and compare the internal inequalities within these groups with internal inequalities within social groups in other regions. The source also provided material on the basis of which we were able to reconstruct social networks, migration patterns, different strategies adopted by different religious communities, patterns involving occupation and age group, etc. We were able to compare the potential uses (and limits) of this source with the uses and limits of other sources. Our main goal was to put more emphasis on a spatial-regional approach, which is underrepresented in the Hungarian historiography, while geographers tend to refrain from putting their research into historical frames and contexts.

Keywords: HGIS (GIStory), urbanization, spatial patterns, social stratification, classification methods, quantitative analysis, wealth, 1870 census data

Aims

Although our study essentially aimed to (1) analyze and explain spatial patterns of sociodemographic phenomena in an urban community in the era of transition from preindustrial to industrial society by testing the potentials of a unique source (the census of 1870), other, primarily methodological aspects also arose which are worth further discussion and which put this article into a broader context. We have attempted (2) to outline three different methods which can help researchers identify different social layers in urban societies. We also attempted (3) to give an indirect estimate of the wealth levels of different social groups in the late nineteenth century by using the census data and to compare local internal inequalities with inequalities measured in other urban settlements and regions. We also considered (4) the potential applications and limitations of the source in question in attempts to reconstruct social networks and migration patterns, and we compared the uses of this source to other source types.

The applications of HGIS1 might be familiar to geographers and historians in the West, but the use of this method in Hungarian historical research is underrepresented at the moment (the only existing concise database, compiled for the city of Debrecen on the basis of census data from 1870, remains unevaluated).2 Geographers dealing with GIS-aided planning refrain from engaging in research focusing on the past, though the lack of knowledge of the histories of peripheral areas may lead to the adoption of mistargeted policies in development planning. Historians use a “vertical” (sociological) approach instead of spatial (regional) one, but recent studies have shown that the regional diversity in Hungary was not negligible. Thus, generalizations based on small datasets extrapolated to the whole country (and terms like “average”) can be misleading. Our fifth goal, therefore, was to test the applicability of GIS in the field of history. This study can be considered a draft project for the later, more broadly framed projects, such as GISta Hungarorum (2015–2017).3

Data

The source on which we based our inquiry was chosen because of its uniqueness. which enabled us to investigate and map certain phenomena into which other sources yielded no insights. The census of 1870 was the first modern census taken by Hungarian authorities, and (far more importantly) it was the only state inquiry that was based on household level (Figure 1) and not on individual data sheets (later censuses were based on individual data sheets). Furthermore, almost at the same time, a cadastral mapping was also done in 1865 indicating every house with its identification number, which was identical with that of the numbers used in the census sheets.4 This temporal proximity and the survival of the original unpublished sheets in some counties5 (data were published officially only at the district level in the census volumes) made it possible for us to illustrate sociodemographic phenomena on maps at the household level and even to assess wealth levels based on property at the beginning of the era of industrialization.

The original census sheets from 1870 contained the name, age, address, birthplace, occupation, and religion of the head of the family, and these data were repeated for the wife, children, coworkers/employees, servants, and housemaids living in the same “household.”6 The sheets also provided the number of rooms, kitchens, auxiliary buildings (storage areas, stables, cellars) for each household. As the census did not contain income data, some of the abovementioned variables were utilized as proxies for wealth in order to divide the population into social (i.e. income-related) layers. Beyond wealth, general sociodemographic phenomena with or without spatial patterns (such as the average number of children of different occupational groups, the average number of children of groups belonging to different religions, migration patterns, interreligious marriages, territorial aspects of marriage patterns, territorial distribution of religious groups, etc.) were also traced using the aforementioned variables.7 The data also made it possible to create new indicators beyond those given in the census, such as population density (room/person) and ratio of earners per family. These derived data were also used as proxy variables to approximate wealth.

Our household-level database contained 2,150 entities (families, Wohnparthey), cca. 1,000 houses with approximately 10,000 persons and a dozen indicators. Phenomena with spatial pattern were analyzed using GIS (ArcGIS 10.1), while within-group and intergroup differences (like religious composition of occupation groups, differences in wealth levels of religious groups and occupations, ageing, migration, differences in fertility rate, etc.) were evaluated using SPSS.

Figure 1. Pages from the census, Nagy Piac str., nr. 9.

Source: MNL-BAZML SFL XV. 83. box 77–79.

The Place

The selection of the town of Sátoraljaújhely (the county seat of Zemplén County) as a sample area was ideal from several perspectives. The original census sheets were available for 2,150 households, thus offering substantial material for quantitative statistical analysis, and even the timing of the census itself (1870) was fortunate from the perspective of our inquiry, which focuses on the identification of persisting and transforming urban structures. As a basic step towards industrialization, the railway was opened in 1870, while guilds were dissolved only in 1872, and this implied the parallel coexistence of both traditional and modern social patterns and social layers. In addition, the town had had an inherently positive geographical position for centuries, as it was located along the market line, where the goods produced in the plains and in the mountains were exchanged. The physical geographical conditions allowed a north-south pattern of migration from the peripheries of Zemplén County (the border of which was also a state border) to the county seat, while in the southern part of the county an east-west migration route developed from the Great Plains towards the capital, Budapest. Although in 1775, the county seat was so peripheral that it was unable to extend its attraction zone very far even within its own administrative district, between 1810 and 1870, its population tripled, and this population growth was among the largest in comparison with the neighboring towns (Table 1). The nearby city of Eger, which was similar in size and had similar functions (it was also a county seat), showed only a 40 percent increase. By 1900, 50 percent of the inhabitants of Sátoraljaújhely were registered as not indigenous (i.e. born in a different locality),8 a figure which confirms the great role of horizontal mobility and migration. As the average number of children per household was only 1.8 in Sátoraljaújhely (1870), without migration, the population would not have increased at all.9 The acceleration of urbanization processes became more evident during industrialization (the population increase was only 50 percent between 1784–1825 and 1825–1870, but then it doubled in the next 40 years, exceeding the country average), making a melting pot of the town. This was reflected in its religious diversity. In 1870, 35 percent of the population was of Jewish origin, Roman Catholics constituted 30 percent, Calvinist protestants 12–14 percent, Greek Catholics approximately 18–20 percent, and there were some Lutheran inhabitants too. 10

 

Table 1. Population increase referring to the rate of urbanization (1825–1900) in Sátoraljaújhely compared to the surrounding significant towns

Town

Population increase (1825–1900)

Population in 1,000 (1825)

Population in 1,000 (1900)

Eger

+40%

17.5

24.5

Kassa (Košice)

+180%

13

38

Miskolc

+80%

22

40

Sátoraljaújhely

+200%

4 (1784), 6.3 (1825)

10 (1870), 19.9 (1910)

Source: Beluszky, Magyarország településföldrajza.

General Features of the Urban Society

The evaluation of the urban society began by creating a correlation matrix containing the quantifiable variables of the database. The correlation between demographic indicators was weak in many cases (no connection was observable between number of children and family wealth or between the proportion of earners and wealth) (Table 2), thus many of the recorded indicators can be interpreted statistically as independent variables. However, some of the indicators still showed correlations with other variables. Therefore, in order to interpret these phenomena, diagrams illustrating the internal distributions were also created. Some of the variables were not quantifiable (like religion), thus correlations could not be calculated. The relationships between these variables and other indicators were also illustrated on diagrams. In order to illustrate the internal differentiation within the dataset, both mean and standard deviation values were calculated for the whole population and were used as reference points when comparing subsets (Tables 3–11).

 

Table 2. Correlation between the quantifiable variables (for each family). Strong correlations are indicated by grey background

Indicator

Age

Servants

Coworkers

Total inhabitants

Proportion of earners

Number of rooms

Proportion of children

Inhabitant per 1 room

Wealth 1

Wealth 2

Age

1.000

-0.011

-0.134**

-0.047*

-0.006

-0.141**

-0.099**

0.099**

-0.158**

-0.171**

Servants

-0.011

1.000

0.097**

0.427**

-0.276**

0.513**

-0.071**

-0.122**

0.369**

0.537**

Coworkers

-0.134**

0.097**

1.000

0.408**

0.240**

0.236**

0.074**

0.152**

0.113**

0.426**

Total inhabitants

-0.047*

0.427**

0.408**

1.000

-0.560**

0.424**

0.610**

0.501**

-0.197**

0.103**

Proportion of earners

-0.006

-0.276**

0.240**

-0.560**

1.000

-0.194**

-0.539**

-0.330**

0.234**

0.183**

Number of rooms

-0.141**

0.513**

0.236**

0.424**

-0.194**

1.000

0.063**

-0.530**

0.613**

0.710**

Proportion of children

-0.099**

-0.071**

0.074**

0.610**

-0.539**

0.063**

1.000

0.523**

-0.416**

-0.304**

Inhabitant per 1 room

0.099**

-0.122**

0.152**

0.501**

-0.330**

-0.530**

0.523**

1.000

-0.796**

-0.601**

Wealth 1

-0.158**

0.369**

0.113**

-0.197**

0.234**

0.613**

-0.416**

-0.796**

1.000

0.911**

Wealth 2

-0.171**

0.537**

0.426**

0.103**

0.183**

0.710**

-0.304**

-0.601**

0.911**

1.000

Explanation:

Coworker: inhabitant living together with the family-head but having his or her own earnings but not his or her own home (servants are not included in this group, but craftsmen-students are); employees of the family head, or grown up relatives of the family head employed elsewhere.

Wealth 1: indicator for the economic potential of the “Wohnparthey” calculated based on an equation containing the number of household servants, coworkers, economic buildings, number of rooms, and family size.

Wealth 2: indicator for the economic potential of the “Wohnparthey” containing the number of household servants, coworkers, economic buildings, and number of rooms but not family size.

** significant, p=0.05. Calculated-derived indicators are indicated by italicized letters.

Base data: MNL-BAZML SFL XV. Census data from 1870.

 

Table 3. The size of “Wohnparthey” in Sátoraljaújhely in 1870 (prs and %)

Family members

1

2

3

4

5

6

7

8

9+

Total

household number

123

381

415

345

305

198

162

84

134

2,147

%

5.73

17.75

19.33

16.07

14.21

9.22

7.55

3.91

6.24

9434

 

Table 4. Inhabitant/room values for the “Wohnparthey” in Sátoraljaújhely (prs and %)

0–1

1.1–1.5

1.6–2

2.1–2.5

2.6–3

3.1–4

4+

Altogether

214

125

375

120

352

391

529

2,147

9.97

5.82

17.47

5.59

16.39

18.21

24.64

100

The general sociodemographic features of the town can be summarized as follows. The town had cca. 1,000 houses, but 2,150 registered “families,” which means that on average one house was home to at least two Wohnpartheys. (For example, one kitchen was often used jointly by two or three families). The average family size was 4.4 people for one Wohnparthey in 1870 in Sátoraljaújhely. 25 percent of the households had six or more and 23 percent had two or less members.11 The average population density was three people per room, but there was significant variety. 25 percent of the households were characterized by density above four people per room. In 10 percent of the families, at least every second family member was an earner, while in 8 percent of the families the earnings of one person were enough to maintain a family of ten. The average number of rooms per family was 1.5 in the town, but here too there were considerable discrepancies, and the average value was hardly greater than the value measured in villages.12 50 percent of families had only one room, and 8 percent had less than one, while only 10 percent had three or more rooms. 13 In Hungary, the average was 3.8 people per room in 1869 (and 3.5 in 1910). In Sátoraljaújhely, it was three people per room.14 Servants were abundant in only 25 percent of the households. They constituted 7.3 percent of the society. The average number of servants was 0.33 per family for the whole town. Earners without their own Wohnparthey constituted 10 percent of the population (978 persons), but only in 10 percent of the Wohnpartheys do we find more than one coworker, and 75 percent of the families had none. 28 percent of the “families” had no children (the family head was too young or was older and the children had already left the family home). In Belgrade, this figure was only 17 percent in 1900.15 On the other hand, 30 percent of the Wohnpartheys had more than two children (in Belgrade this was 26 percent). The average number of children was 1.8 per family. Jewish families had 2.4 children of average, Greek Catholics had only 1.4, and Roman Catholics and Calvinists had 1.6. Only 11 percent of the family heads were younger than 30. 11 percent was older than 60 (the average was 39). Altogether, 39 percent of the total population was under 18 years of age (the figure was similar for the whole of Hungary).

 

Table 5. Proportion of earners in the “Wohnpartheys” of Sátoraljaújhely in 1870 (prs and %)

0

0.1

0.2

0.3

0.4

0.5

0.6–0.9

1.0

Total

70

173

676

467

116

401

104

140

2,147

3.26

8.06

31.49

21.75

5.40

18.68

4.84

6.52

100

Table 6. Average number of rooms / family (Wohnparthey) in 1870 in Sátoraljaújhely
(number of rooms and %)

Number of rooms

under 0.5

1

2

3

4

5+

Total

households

170

1,175

488

150

69

55

2,147

%

7.92

54.73

22.73

6.99

3.21

2.56

100

Table 7. The number of servants in family households in 1870 in Sátoraljaújhely (prs and %)

Servants (prs)

0

1

2

3

4+

Altogether

households

1,665

336

91

34

21

2,147

%

76%

15.65

4.24

1.58

0.98

730

Table 8. Number of coworkers and earners (not in family-head position) in Sátoraljaújhely in 1870 (prs and %)

Coworkers

0

1

2

3

4+

Altogether

households

1537

383

143

46

38

2,147

%

71.59

17.84

6.66

2.14

1.77

100

Table 9. Number of children in the Wohnpartheys/families in Sátoraljaújhely in 1870 (prs and %)

Number of children

0

1

2

3

4

5+

Altogether

households

619

462

424

303

165

174

2,147

%

28.83

21.52

19.75

14.11

7.69

8.10

100

In Belgrade these figures were 17, 34, 24, 11, 7, and 7% respectively around 1900.

 

Table 10. The distribution of family heads in Sátoraljaújhely based on their date of birth
(prs and %)

Year of birth

–1809

1810–1819

1820–1829

1830–1839

1840–1849

after 1850

Altogether

family heads

238

447

578

645

236

3

2,147

%

11.09

20.82

26.92

30.04

10.99

0.14

100

Table 11. Demographic indicators in Sátoraljaújhely in 1870 (prs and %)

Indicator

Lutheran

Greek Cath.

Jew

Calvinist

Roman Catholic

Altogether

Total number of children

71

519

1,655

483

1,153

3,881 (39%)

%

1.83

13.37

42.64

12.45

29.71

100

number of families

41

373

692

302

735

2,143

%

1.91

17.41

32.29

14.09

34.30

100

children/Wohnparthey

1.73

1.39

2.39

1.60

1.57

1.81

Source: MNL–BAZML SFL XV. Census of 1870.

Local Mobility – Local Networks

As the registry of 1870 offers only a “snapshot” of the social situation, and as its structure differs from the later censuses, the usefulness of this material (unlike the usefulness of parish registers, for example) to identify social networks and relationships or to trace patterns of change of residence among members of the younger generation is rather limited. But in certain cases, the registry still offers significant data on the basis of which one can venture hypotheses concerning trends or patterns in household composition. The marriage of the Calvinist noble landowner family Evva, which played a crucial role in the life of the county and had five rooms and an additional two rooms rented to Jewish grain merchants, and the influential and rich Catholic Farkas family (a lawyer dynasty with eight servants and coworkers, owning six rooms and renting two rooms to merchants) offers an example of the unification of two elite families with different social roots and belonging to different denominations. (Inter-denominational marriages were relatively rare, coming to only 15 percent of all marriages). The old family head András Evva (1805–1888) had already been mentioned prior to 1848 as the leader of the reformist political opposition in Zemplén.16 He managed to keep his position even after the repressions between 1849 and 1867, and he became the president of the county jurisdiction. His wife, Teréz Balásházy, also hailed from an old, local noble family, mentioned early in the eighteenth century as one of the “urban” noble families.

Another example of the decreasing role of religion within the noble elite is given by the Catholic Spek family. Irma (1847–), a relative of Antal Spek (1804–) who was a member of the local town council, married the Lutheran lawyer Ignác Boros and settled down in the main street of the town (Kazinczy Street) near the widow of Ferenc Spek (house nr. 651 and 655). Thus, they were able to look after each other. Furthermore, the elder daughter of the latter widow married a royal official, thus broadening the family network. We may point out that, while at this time the intermingling traditional landowner and administrative elite had already accepted the “honoratior” layer (highly educated non-nobles in important position) as equal partners, the traditional elite living in the town still refrained from entering into relationships with the new financial elite.

The tightness of the relations among relatives can often be measured through territorial concentration, as the above example showed. Social networks had spatial patterns too, but there were remarkable differences in the cases of different strata. For example, the innkeepers of the town also tended to enter into family relationships with one another, but they settled relatively distant from one another as their main aim was to distribute the market between the possible competitors in order to maximize income and minimize competition.

A comparison of other (earlier) registries with ours offers even greater potential as a method of identifying networks, social (vertical) mobility, migration processes (horizontal mobility), etc., but it also requires more work. The noble Kapy family, the richest at the end of the eighteenth century with 90 hectares of land, had almost disappeared by 1870. Apart from one young a child, only one person from this family was registered as an inhabitant in Sátoraljaújhely, the wife (1837–) of Calvinist county official József Bárczy.17 The Marchalko family was also a prominent noble family in the eighteenth century in the town, but by 1870 only one person, the Roman Catholic wife (1817–) of another Calvinist, István Somogyi, bore this name.18 This also indicates that the fusion of the elites of different origins and denominations was in an advanced phase by that time. Protestants traditionally held leading positions in the urban and county administration in Zemplén (this is a specific feature of the county), and they were overrepresented compared to their proportion in the whole urban population. Roman Catholics were mainly landlords, and their weight in the county council and the urban government was smaller in the first half of the nineteenth century. Intermarriage and the general decline in the number of Protestants enhanced their position first on the urban council and then on the county council.

Family and kinship networks which existed at the time the registry was drawn up can also be traced, but only within limits.19 The maiden name of the wife of tailor János Keller, who lived at Papsor nr. 474, was Sztropkovics. Her mother also lived in the same household, while in the same house, but in another ’Wohnparthey’ a Sztropkovics boy established a family. In this case, the relatives remained relatively close to one another because of their limited financial means. The house was divided between the two Sztropkovics descendants, and the husband moved into his mother-in-law’s house. Another example of relatives from different communities living relatively close to one another reveals family and business strategies. Eszter Hell, the widow of a Jewish textile merchant (haberdasher) named Svajger, and the textile merchant Salamon Hell (who was her close relative) also lived in neighboring households (nr. 475 and 477). Another relative of her sons (the Svajger-children), Samuel Svajger also lived in the neighborhood (nr. 490, Széchenyi Square). Samuel Svajger was also a textile merchant (haberdasher). Adolf Hell, another haberdasher and relative, lived at nr. 498. Kinship and family ties also influenced business behavior. The marriage between the Svajger and the Hell merchant families promoted accumulation of capital, while it decreased competition. At the same time, the relative closeness made it easier for members of the families to provide care for widows, orphans etc.

Spatial Patterns: Religion, Occupation, Population Density

Though the town was depicted as a melting pot, the Jewish community had not been granted full rights in all fields of life in the 1860s. This naturally raises a question. Was there was any segregation observable between religious communities despite the diversity? Based on the map illustrating the religious distribution of the population (Figure 2),20 Jewish households were concentrated in the center of the city (they did not own the houses, but rather rented them from the local protestant elite). These houses were predominantly located at some of the major crossroads (Óhíd Str., now Dózsa Str.; Újhíd Str., now Rákóczi Str.; and Malom Str., now Munkácsy Str.) which ran perpendicular to the main road, which led in a north-south direction. Despite the presence of some clusters of houses inhabited exclusively by Jews21 and the prohibition of interreligious marriages between Jews and Christians at the time, we cannot speak about the segregation of Jews for two main reasons. First, the area of the settlement in which Jews lived in high concentrations included the road where the local elite lived and the major scenes of urban life (community spaces, administrative buildings) took place. The presence of Jewish residents of the town was also traced in the secondary main road leading eastward through the Ronyva-bridge, which means that they were integral part of the town. The fact that Jews were able to pay the high prices for rental properties in the center of the town and that the families of the elite lived alongside Jewish families (see the example of the Evva family) means that (1) the Jewish society (or societies) was a differentiated one and (2) the elite tolerated their presence, because Jews served as significant source of income for the traditional local elite, which refrained from capital investment in industry. The second reason is that still there were intersections and blocks of a religiously mixed character. 22

Calvinists lived in houses along the main streets running north to south. Some of these streets bear the names of traditional handicrafts (Gubás Str., now Esze Tamás Str.). Thus, protestants living in homes on these streets represented the imprints of the traditional socioeconomic structure (and this also reflects their once higher proportion and prestige within the population). Their spatial pattern originally showed a continuous line along the main road, but this was broken up by 1870, and the rich Calvinists (based on population/room, total number of rooms, etc.) in the city center became separated from the Calvinists craftsmen who belonged to the lower middle-class.

Greek Catholics lived in the northern and southernmost outskirts of the town, near the vineyards (which lay to the north and northwest) and the arable lands (which lay to the south). This clearly indicates their sectoral distribution and social position. Most of them were agrarian wage laborers or craftsmen of less prestigious occupations. Roman Catholics were abundant in the city center (mixed with Protestants) and on the fringes, which indicates advanced social differentiation among them. Jews also had a lower-class layer located on the outskirts, which was separated from the richer layers.

To summarize, though there were relatively homogeneous blocks or street sections (the Jewish blocks in the center, the streets in the north and the southeast—Kis Pazsic, Baracz—which were dominated by Greek and Roman Catholics, and the quarter inhabited by Protestant craftsmen in the south), segregation was not as characteristic of Sátoraljaújhely as it was of Bonyhád, for example.23 The spatial differentiation among people who belonged to different religions or denominations and people who pursued different occupations was advanced by 1870 and this differentiation was more based on social position than on the denominational differences. Interreligious marriages constituted 15 percent of the total, 24 though half of these took place between Greek and Roman Catholics and 23 percent between Roman Catholics and Calvinists. Houses were often inhabited by families belonging to different denominations, and sometimes even the distribution of markets was observable: the Jewish butcher shared a house with a Greek Catholic bacon-maker. This strange phenomenon drew our attention to another one: among butchers, Jews were overrepresented. They met the demands of their co-religionist population, but also those of other denominations. This indicates practical trust and reception of Jews in our interpretation, who were also overrepresented among merchants (Figure 3). Another (rather symbolic) sign of their emancipation was the fact that Jews and Greek Catholics (the latter constituted the poorer half of society) were also found among the urban and county officials (represented by 1-1 scribe), who were primarily Calvinists (Figure 9).

As for the spatial pattern of occupations, our general observation is that industrialization was not yet advanced enough (two years before the abolishment of guilds) to ruin traditional old structures completely. Tanners still lived along the Ronyva River, as water was essential to their craft. Their downstream and upstream concentration was also not surprising. Because of the stench (a by-product of their work), they were pushed out from the surroundings of the bridge across the Ronyva, which functioned as the main supply route leading to the town’s railway station. Tanners who were living downstream along the Ronyva did not affect the urban neighborhood negatively with their activity. The craftsmen who made heavy mantles lived mainly in the street named after them in the south (“Gubás,” from “guba,” a term used to refer to a mantle made of wool or felt) and in the north (dominated by the poor), and they were mostly Greek Catholics (for their relative wealth, see Table 22). Bootmakers, who were primarily Calvinists, lived in the southern districts on a “hidden” road parallel to the north-south main road, but many of them also lived on the western fringes called Zsólyomka, which was also among the poorer districts. Joiners (middlemen, based on Table 22) lived scattered and evenly dispersed, while butchers were lived to the west of the main road (no butchers lived in the northern districts). Tailors lived around the town center (Figure 8).

Investigations (discussed later in detail) proved that the location of the residences of people who pursued different occupations (i.e. the distance from the functional center of the town) correlates with the people’s wealth or social prestige. Urban and county officials lived along the north-south axis (teachers, school inspectors, state attorneys, judges, crown counsels, prosecutors), surrounded by representatives of freelance professions25 (pharmacists, architects, vets, doctors, goldsmiths, private lawyers, house owners). The outer circle of the town center was dominated by assistant officials, clerks (urban, financial, insurance, postmen, policemen) and by financial experts (banking). This was followed by the zone which was inhabited by craftsmen and the outermost circle, which was inhabited by agrarian workers (Figure 8). (Servants and agrarian daily wage-laborers dominated in the northern districts, the southeastern parts of the settlement, and the west, in Zsólyomka.)

Inns, mansions, and restaurants were concentrated in the center or around the bridge over the Ronyva and in the western parts of the town near the vineyards and arable lands, from where daily-wage laborers returned tired and thirsty day after day. The first houses along the streets leading to the town also functioned as inns or restaurants to offer shelter to those who arrived on foot or by cart from the surrounding regions. (The persistence of these suburban inns indicates that railway had not yet modified the traffic patterns; Figure 8). Merchants were concentrated in the town center and the west-east road leading to the Ronyva bridge, while shopkeepers (including chandlers and grocers) targeting different layers frequently lived in the eastern and western outskirts along the main roads leading to the arable lands.

 

 

 

 

 

 

 

Figure 4. The spatial pattern of population density (person/room) in Sátoraljaújhely in 1870

The Social and Religious Composition of Migrants

In urban environments, the role of natural reproduction in population growth has usually been smaller than that of migration. Even in the introverted Eger, which had an increase in its population of only 40 percent between 1825 and 1900 (the population of Sátoraljaújhely tripled over the course of this period), more than 75 percent of the increase was the result of migration, as the natural growth rate until 1873 was critically low (demographic pattern was characterized by high mortality beside the and a high birth rate).26 In Sátoraljaújhely, the main source of population growth was also migration, which played a key role in the transformation of the city’s character.

The transformation of traditional structures can also be examined by measuring the frequency of migrant intermarriages (and the spatial pattern of migrant intermarriages) alongside the frequency of religious intermarriages or the spatial pattern of occupations. (The latter two can also indicate theses transformations: a dispersed spatial pattern usually indicates the dissolution of original structures). Altogether, 33 percent of family heads were indigenous to the settlement, while the proportion of local-born wives was somewhat higher, reaching 45 percent. This means that the male population was more mobile and also that local-local marriages could not have been more than 30 percent in the town.27 In contrast, in the more traditional southern districts (note the abundance of guildsmen occupying certain jobs niches based on religious differences), which comprised 33 percent of the households, marriages between local born males and females reached 50 percent (178 cases). This indicates a higher degree of introversion in this district of the town. On the other hand, immigrant-immigrant marriages were overrepresented in the north. The latter indicates the belated integration of certain layers. Immigrant-indigenous marriages had no spatial pattern.

The changes in religious proportions also refer to transformations. The proportion of Calvinists decreased from 18 percent in the 1840s below the country average by 1870,28 while that of the Jews increased from 17 percent to 35 percent (their share among children was even higher, 42 percent in 1870). It fell back to 29 percent by 1910. (The increasing presence of Jews usually indicated industrialization and the emergence and spread of capitalism in Hungary). The proportion of Greek Catholics gradually decreased from 23 percent to 15 percent, which, given their primary occupations (for the most part, they were agrarian wage laborers and low-prestige craftsmen and artisans), also indicates transformations in general (Table 12).

These changes were partly driven by the changes in migration patterns and social strategies and partly by the different birth rates of the different denominations. Our database offers possibilities to estimate the role both of migration and natural growth rate for religious communities, and to reconstruct the social strategies of classes and denominations.

 

Table 12. The change in proportion of religious denominations in Sátoraljaújhely between 1840 and 1910

 Year, %

R. Cath.

Greek Cath.

Calvinist

Lutheran

Orthodox

Israelite

Altogether

1910, prs

7,936

2,943

2,878

381

34

5,730

19,902

1910, %

39.9

14.8

14.5

1.9

0.2

28.8

100

1870, prs*

3,335

1,676

1,195

155

12

3,215

9,946*

1870, %

34.5

17.0

12.5

1.6

0.1

33.5

100

cca. 1840, prs

2,401

1,464

1,174

120

26

1,125

6, 310

cca. 1840, %

38.1

23.2

18.6

1.9

0.4

17.8

100

* only 9587 known cases.

It is not surprising that the proportion of immigrants was higher among the cohort of 20-30 year old (over 65%), than among the inhabitants between 50 and 60 years (50%). More interesting conclusions can reached when investigating the subsets of the social classes, occupation groups, and denominations. The proportion of indigenous people exceeded the urban average only among the Jewish family heads (45 percent) and their wives, so the Jewish community must have been the most insular. This is surprising compared to old topoi and their behavior in other towns.29 The growth in numbers was the result of the high internal reproduction rate (an average of 2.4 children/Jewish Wohnparthey) and not of immigration (Table 11). The decrease in the proportion of Jews in the town after1870 (Table 12) despite the high number of children may indicate that Jews reached the “saturation point”: the town as a market did not have a demand for the professions typically practiced by Jews at that stage and pace of development, and this made it less appealing for potential Jewish immigrants and increased competition for the niches among the different factions.30

In contrast, Lutheran family heads were dominantly immigrants. Many of them were foreigners with special skills and occupations who came as experts to meet the demand generated by industrialization, which Hungarian schools were not yet able to cope with. The number of Lutherans in the town tripled between 1840 and 1910, a pace of growth which equaled the average growth rate of the whole town. The average number of children among them was only 1.8, which means that migration played a larger role than natural growth. (On the other hand, Lutheran family heads were somewhat younger than the average, as were Greek Catholic family heads, and this also explains the low birth rate within their households).

Among the Greek Catholic family heads, the proportion of newcomers was 75 percent, thus the gradual decrease in their share of the total population can be explained by their low birth rate (an average of 1.4/Wohnparthey in 1870) and by religious intermarriages. They were also relatively poorly off from the perspective of their social situation (the proportion of Wohnpartheys with only one room or less was the highest among them). The proportion of indigenous Roman Catholic family heads (compared to local Roman Catholic family heads) was also below the town average. The Calvinists tried to “balance” their bad demographic indicators (an ageing society with less than the average number of children) by relying on immigrants. Regarding the origins of wives and husbands, there was a great difference measured in the case of both Roman Catholics and Calvinists: mainly the men were newcomers, while most of the wives were local born inhabitants (Table 13).

Considering the group of coworkers and employees31 the share of Jews reaching 25 percent was well below their proportion measured among family heads and wives. This means, based on the general character of this social category comprising dominantly craftsmen,32 that among Jews, the significance of traditional guild-industry was of secondary importance. Though after 1848, Jews were allowed to work in guilds, they still tended to take other occupations. The proportion of Calvinists among employees (18 percent) was higher than their share of the total city population (12–13 percent), which implies a more traditional social structure and a strategy differing from that of the Jews. In the case of the Calvinists, employers showed a preference in their selection of employees/coworkers for other Calvinists. This preferential cooperation meant that a Calvinist guildsman was more likely to choose a Calvinist apprentice. This does not imply exclusiveness, however. Calvinists also hired Roman Catholic apprentices. This also meant that the children of lower middle-class Calvinists were more likely to turn to handicrafts than to pursue other occupations, and they were more likely to pursue these crafts than the children of Jews and Lutherans. These differences in strategies based on religion/denomination indicate the persistence of old structures.

Among the social group of servants, the proportion of Greek and Roman Catholics (26 and 41 percent respectively) exceeded their share of the total population, while Calvinists (9 percent) and Jews (15 percent) were underrepresented. This also reflects the different strategies they adopted in the pursuit of a livelihood. Jews, for example, tended to employ non-Jewish immigrants as servants, much as Calvinists tended to employ non-Calvinists.

Among employees and coworkers (without their own Wohnparthey), the proportion of local-born (except for the Jews with their 51 percent) remained under the city average (40 percent) (Table 13). The high share of local-born Jews among employees also indicates an insular society and a strategy differing from that of the Christians. In contrast with Jews, Calvinists preferred immigrants as coworkers and employees. The proportion of Roman Catholics among immigrant employees reached 40 percent (overrepresented compared to the proportion of Roman Catholic family heads and their wives). The share of Calvinists reached 22 percent (also overrepresented, much as Greek Catholics were too, with their 22 percent), while the proportion of Jews in the town remained around 20 percent. In contrast, in the whole set of coworkers and employees (including indigenous and immigrant), Roman and Greek Catholics were underrepresented compared to their share of the total population (24 percent vs. 33 percent of family heads and 11 percent vs. 17 percent of family heads, respectively). This means that the proportion of indigenous Greek Catholic employees was small and also that their proportion was high among servants. In the case of these two denominations, low-prestige fieldwork dominated among immigrant employees (as their geographic location within the town confirmed earlier).

Among the local-born servants and housemaids, Roman Catholics were overrepresented (while among employees they were underrepresented). 85 percent of the servants and housemaids were immigrants, which indicates that the strategy of local-born, lower-class/declassed people aimed to avoid these lines of work by becoming apprentices or coworkers. Among newcomer servants, Greek Catholics comprised 26 percent (a higher value than their share of the total urban population), while Jews reached only 15 percent (Table 14).

 

Table 13. The proportion of immigrants among occupational (family head-earners; employees-coworkers; servants and maids) and denominational groups

Family-heads*

Total persons

Local-born (%)

Local-born (%)

Wives

Total persons

Local-born (%)

Local-born (%)

Lutheran

41

12.2

0.7

Lutheran

33

27.3

1.1

Gr. Cath.

373

24.4

12.5

Gr. Cath.

309

33.0

12.6

Jew

692

44.5

42.5

Jew

619

47.3

36.2

Orthodox

3

33.3

0.1

Orthodox

5

60.0

0.4

Calvinist

302

35.8

14.9

Calvinist

193

60.6

14.4

R. Cath.

735

28.8

29.2

R. Cath.

552

51.6

35.2

Altogether

2147

33.8

100

Altogether

2147**

37.7

100

Coworkers, employees

Total persons

Local-born (%)

Local-born (%)

Servants, maids

Total persons

Local-born (%)

Local-born (%)

Lutheran

10

20.0

0.8

Lutheran

8

0.0

0.00

Gr. Cath.

109

24.0

10.8

Gr. Cath.

135

9.6

21.6

Jew

146

51.4

31.4

Jew

80

12.5

16.6

Calvinist

110

25.5

11.7

Calvinist

50

10.0

8.3

R. Cath.

212

27.0

23.8

R. Cath.

216

14.4

51.6

Altogether

600

40.0

100

Altogether

520

11.5

100

* Including widows (women) registered as family-heads.

** The difference between the number of Wohnparthey and the partial sums is due to the cca. 200 widows and widowers (10%) divorced and yet not remarried.

 

Table 14. The distribution of immigrants (%) based on religion and social groups

 

All family heads as a %

Immigrant family heads as a %

Immigrant wives as a %

Immigrant employees as a %

All employees as a %

All servants as a %

Immigrant servants as a %

Lutheran

2.0

2.7

2.7

2.2

1.6

1.5

1.7

Gr. Cath.

17.0

19.8

22.2

21.0

18.1

26.0

26.5

Jew

33.2

27.0

36.3

19.6

24.3

15.4

15.2

Calvinist

12.5

13.6

8.4

21.7

18.3

9.6

9.8

R. Cath.

35.1

36.8

29.6

41.0

35.3

41.5

40.2

The theoretical aggregated value in columns is 100% – differences are due to lack of data and rounding errors.

Social stratification of immigrants

With regards to the social elite (the methods according to which we have defined this group and identified the people who belonged to it are discussed later), in the case of family heads, 25 percent were born in Sátoraljaújhely. In the case of wives, this figure was a bit higher, 33 percent. This indicates the generally smaller horizontal mobility of women at time. Compared to the figures in the city of Eger, this still indicates an open society.33 Among the lower-class and deprived (for instance agrarian wage laborers and washerwomen, sewers, bread-makers, etc.), the proportion of local-born people was also low, around 30 percent (in the case of their wives, it was 37 percent), while in the case of the middle class (for instance merchants, innkeepers, shopkeepers, and chandlers), the figures were 40 and 48 percent, respectively. In the case of landowners, the proportion of local-born urban dwellers was around 50 percent, and in the case of people earned their livelihoods doing handicrafts, it was similarly high (41–58 percent). Thus, the latter two occupational groups can be considered the basis of the indigenous middle-class (Table 15).

 

Table 15. The proportion of local-born husbands and wives in 1870 in Sátoraljaújhely

Group

Husband (persons)

Wife (persons)

Husband, (local) %

Wife (local), %

elite, official elite, freelance professions

59

81

25

33

merchants, chandlers

140

166

40

48

artisans, craftsmen

278

396

41

58

poor, lower-class (cartmen, footmen, sewers, rag-pickers, washerwomen, itinerant merchants, etc.)

156

208

30

36

smallholders and large estate owners

54

57

46

49

The abovementioned “openness” of Sátoraljaújhely (which is a feature of towns which were becoming increasingly industrialized) is indicated by another fact: among the immigrant earners, the share of those who belonged to the elite was higher than among the local-born society (Table 16), in contrast with the situation in Eger.34 In Sátoraljaújhely local-born earners were overrepresented within the middle class, while lower layers were dominated by newcomers. However, the proportion of immigrants working in the agrarian sector did not exceed the proportion of local-born working in the same sector. From the perspective of their numbers and their share of the total population, newcomers were overrepresented among the industrial and tertiary low-wage earners.

The comparison of earners in the comparatively secluded city of Eger (a nearby county seat), the small town of Varannó (Vranov; a district center in Zemplén County), and Sátoraljaújhely (the county seat of Zemplén) yielded interesting results (Table 16). The lower middle class was the largest in the traditional Eger (this was particularly true of the autochtonous population), and the lower classes and middle class were both thinner (partly because of the larger lower middle class, partly because of the lack of industrial workers). The elite was also the broadest in Eger (15–20 percent vs. 3.5 and 7 percent; with its Lyceum, the town was able to reproduce its intelligentsia),35 despite the smaller significance of the elite among immigrants.36 In Varannó, the lower class was thin among immigrants, while among the autochtonous population lower layers were underrepresented).37

 

Table 16. The social stratification of the earners’ society in Eger,
Varannó and Sátoraljaújhely towns

Layer

Varannó,
total (%)

S.újhely,
total (%)

Eger,*
total (%)

Varannó, migrant
(%)

S. újhely, migrant
(%)

Eger,*
migrant
(%)

Varannó,
local-born
(%)

S. újhely,
local-born
(%)

Eger,*
local-born
(%)

Elite

7.1

3.4

20

8.1

3.8

12

5.8

2.5

22

Middle

48.3

41

33

40.8

36

49

58.2

50

25

Lower middle

6.1

3.5

24

8.6

3.3

12

2.9

5

28

Lower

38.5

52

22

42.5

58

25

33.1

39

20

Total (prs)

100%

(720)

100% (2,656)

100% (800)* 

100% (409)

100% (1,783)

100%

(311)

100%

(873)

*

Social stratification based on Ferenc Erdei’s theory of “staggered society” and the prestige of occupations according to Max Weber.

* Data for Eger are from 1883 based on marriages in parish registers (sample size cca. 250. The town was predominantly Roman Catholic)

Sources for Sátoraljaújhely and Varannó: MNL-BAZML SFL XV. Census of 1870;

Source for Eger: MNL-HML IV-416. Marriage registers from 1883.

 

Table 17. The representation of migrants in different social layers of Varannó and Sátoraljaújhely

Layer

Immigrants (%) of the layer, Sátoraljaújhely

Immigrants (%) of the layer, Varannó

Elite

74

65

Middle

60

48

Lower middle

62

80

Lower

75

63

Total

67 (1,783 immigrants)

57 (409 immigrants)

Measuring Wealth and Social Differentiation:
Methods, Spatial Patterns and Internal Differentiation Among Layers

In order to illustrate both spatial patterns and the distribution of wealth among social groups, wealth levels first had to be quantified. As income data were not available, we had to rely on the indirect census data referring to wealth. Because of this, the relevance of our investigation is limited. In order to reduce the subjective elements when classifying the single families into social groups, three different methods were tested.

The first method was based on Marxist sociologist and politician Ferenc Erdei’s concept of the so-called “staggered society.” Erdei contended that, in Hungary, each traditional class had a modern, capitalistic variant, and these variants existed in parallel and coalesced only gradually. We combined this theory with Max Weber’s classification based on the social prestige of given occupations. Though Erdei’s theory has been challenged and the classification based on Weber is considered too subjective, abandoning these old classifications and relying only on modern ones would render our investigations incomparable with old results. The results of this classification, including a sectoral distribution too, can be seen in Table 18 and 19.

 

Table 18. Social groups based on Erdei’s model of a “staggered” society and on the prestige of occupations (Weber) (method 1; prs and %)

e1

town and county elite

lawyers, chief clerks (state servants)

47

2.2%2

f

landowners

mainly middle estate owners

116

5.4%

p

freelance civil professions

teachers, doctors, railway engineers, photographers, clockmaker

91

4.2%

h

officials

state (lower class compared to ’e’) and private
(in banking and finances)

108

5%

g

agrarian experts

not independent but highly skilled agrarian wage-earners

34

1.6%

n

 

policemen, pandurs, postmen, etc.

30

1.5%

kk

merchants

innkeepers, railway entrepreneurs, merchants

216

10.1%

k, ka

 

lower financial officials (clerks), poor merchants, chandlers, grocers

151

7.0%

m

craftsmen

guild members: tailors, potters, bootmakers, etc.

677

31.5%

q

lower tertiary

transportation: cartsmen, waiters

60

2.8%

s

poor

daily wage earners in agriculture, beggars, bakers (women), washerwomen, scrap-iron collectors

508

23.7%

ö

widows

 

101

4.7%

Layers wealthier than the city average are indicated by grey.

1 Abbreviations used in maps and in charts.

2 This table did not contain data on 1,100 coworkers and 700 servants, thus the percentage values refer to 2,150 people and not to 4,000.

 

Table 19. Hypothetic social stratification based on the prestige of occupation
(family heads; %)

Group

Agrarian

Industrial

Tertiary

Private tertiary

Altogether

%

Upper

f (116)

 

e (47)

p (91)

cca. 250

12%* (7%)

Middle

g (34)

 

m (677)

 

kk (30)

h (108)

kk (190), h

cca. 550

25% (25%)

Lower middle

 

n (30)

k (132)

cca. 500

23% (25%)

Lower

s (343)

 

 

s (160),

q (60)

570 + some craftsmen = 800

38% (43%)

Total

cca. 500

cca. 700

cca. 200

cca. 600

cca. 2100

+101 widow households

%

25%

35%

10%

30%

100%

* Servants or coworkers not registered as family heads were omitted. See corrected % values including these layers in brackets.

These categories do not strictly refer to wealth or social status. Group “p” was traditionally considered as the part of the elite, although the wealth and economic power of the civil professions (including state teachers) was significantly weaker than that of groups “f” (landowners) and “e” (official-bureaucratic elite) based on number of rooms and the other two classification methods described later. Category “f” was also not homogeneous regarding wealth. Smallholders and large estate owners were also included here because of the lack of census data concerning estate size. Freelance civil professionals and state clerks were underrepresented in Sátoraljaújhely compared to other towns with similar functions, where their proportion exceeded 15 percent of the earners. Compared to this, the layer of merchants (kk, k) was quite strong (17 percent), possibly as the result of relatively high number of Jews in the town and its geographical location. The proportion of craftsmen (m) was high, but not remarkably. The same percent was measured in the larger city of Debrecen.38

The sectoral distribution of these groups is given in Table 18b. 35 percent of the family heads were involved in industry, but modern industrial branches were represented only by some 10 percent of the total family heads involved in industry. Guilds still dominated in this transitional period. The private tertiary reached 30 percent, reflecting the transformations (urbanization), while agriculture had already lost its dominant position (25 percent).

The second classification was based on quantifiable socioeconomic indicators derived from the census sheets (number of rooms, auxiliary buildings, number of servants, number of employed workers, household size). We used an equation to aggregate the values of the single indicators for all families, resulting in a dimensionless number, which refers to the per capita economic potential of the family. Based on the method of natural breaks, the 2,147 Wohnpartheys/families were divided into 13 groups of different sizes. The aggregated values in group 9–13 (comprising 30 percent of the households) exceeded the total town average (Table 20).

Table 20. The sociodemographic features of the 13 “social groups” (i.e. groups with different levels of wealth) defined by the method based on the equation using socioeconomic indicators (values above the average are indicated by bold letters: the average represents intergroup differences, standard deviation represents within-group differences)

Social group based on equation

Average number of children

Average number of servants

Household size

Proportion of earners

Average number of rooms

Average inhabitants per room

1 (127, 6%)

Mean

2.09

0.01

4.07

0.29

0.51

7.84

 

St. Dev.

1.60

0.09

1.73

0.20

0.39

3.61

2 (140, 6.5%)

Mean

2.24

0.01

4.32

0.28

0.81

5.31

 

St. Dev.

1.75

0.12

1.90

0.19

0.30

1.63

3 (233, 11%)

Mean

2.26

0.03

4.37

0.24

0.99

4.70

 

St. Dev.

1.50

0.20

1.60

0.10

0.29

2.43

4 (258, 12%)

Mean

1.65

0.04

3.81

0.33

1.06

3.60

 

St. Dev.

1.62

0.20

1.91

0.19

0.37

1.51

5 (158, 7.5%)

Mean

2.36

0.11

4.63

0.28

1.20

4.10

 

St. Dev.

1.77

0.32

1.92

0.16

0.49

1.65

6 (203, 9.5%)

Mean

1.87

0.11

4.17

0.33

1.22

3.52

 

St. Dev.

1.89

0.33

2.19

0.15

0.49

1.62

7 (264, 12%)

Mean

1.43

0.18

3.64

0.45

1.36

2.75

 

St. Dev.

1.73

0.40

2.24

0.30

0.58

1.64

8 (104, 5%)

Mean

1.94

0.36

4.55

0.35

1.60

2.91

 

St. Dev.

2.00

0.59

2.55

0.20

0.77

1.50

9 (164, 7.5%)

Mean

1.63

0.37

4.37

0.39

1.78

2.64

 

St. Dev.

1.62

0.59

2.42

0.25

0.83

1.58

10 (151, 7%)

Mean

1.28

0.49

3.90

0.43

1.95

2.10

 

St. Dev.

1.61

0.70

2.33

0.27

0.77

1.39

11 (83, 4%)

Mean

1.51

0.70

5.01

0.42

2.17

2.52

 

St. Dev.

1.69

0.79

2.95

0.30

1.07

1.65

12 (99, 4.5%)

Mean

1.60

0.88

5.14

0.41

2.59

2.18

 

St. Dev.

1.70

0.97

2.99

0.29

1.28

1.45

13 (162, 7.5%)

Mean

1.69

1.87

6.57

0.37

3.73

2.04

 

St. Dev.

1.89

1.62

3.87

0.26

1.66

1.64

Total (2,149)

Mean

1.81

0.34

4.39

0.35

1.53

3.50

St. Dev.

1.74

0.80

2.45

0.23

1.09

2.28

The third classification was also based on a quantitative approach using the same socioeconomic and demographic indicators, but this time automatic cluster analysis was used. (The subjective element here was the setting of cluster numbers. The reliability of this method was validated by discriminant analysis). As this classification did not contain family size as a variable, the results indicate the economic potential of the Wohnparthey as a whole.

Though automatic classifications usually lack any preconception (unlike method 1, based on the prestige of occupation), groups with well-definable social characteristics were generated when applying cluster analysis. Cluster 6, cluster 5, and cluster 1 were easily distinguishable from one another based on their socioeconomic characteristics (Table 21: the success rate of reclassification was above 90 percent here).39 The boundaries of other groups were unconsolidated, fuzzy (groups 2, 3, and 4).40 The fuzzy cluster 2 had one specific, conspicuous, distinctive feature: the proportion of Jews here was over 50 percent, which exceeded the town average (34 percent) and the proportion of Jews measured in other clusters. It seems that automatic clusterization confirmed the existence of the so-called “par excellence Jewish-middle class,” a layer that evolved parallel to the traditional middle class during the process of emancipation and the spread of capitalism, as supposed by Erdei. Its “fuzziness” indicates its transitional, unconsolidated character (as well as its wealth conditions), which also reflects its potential for assimilation to other groups.

 

Table 21. General sociodemographic characteristics of groups created by automatic clusterization of households

Cluster 6:

the poor: high children ratio, low proportion of earners, number of rooms under one

Cluster 5:

the poor: no servants, small household size (3 prs!), number of rooms around one

Cluster 1:

the rich: more than 2 servants, a low proportion of earners (0.2 – contrary to groups defined by the previous method, where it was over 0.4 – revealing that the two methods of defining the elite are not equivalent!), number of rooms around 4

Cluster 2:

the proportion of Jews within the group is over 50%: ’par excellence Jewish middle-class’

To test the correspondence/overlap of the three methods, a cross-tabulation matrix was created, which proved that, although there was a 70-70-70 percent overlap between the results of the 3 methods and the correlation coefficient was higher than 0.7, the three classifications are not equivalent (Figure 6). For example, the richest three groups (11–13) consisted of 341 families (15 percent) in the case of the second method (i.e. the equation referring to per capita economic power), while the richest two clusters comprised 332 family heads (the third method), but only 192 of the cases were common (60 percent).41 This means that the interpretation of the results is not independent from the selected method. Thus, in order to avoid preconceptions during generalization (i. e. the classification of earners into “social groups”), the economic potential was calculated for the different occupations as grouping variables, too (Table 22). Lawyers and doctors (33 persons), the thin layer of engineers and entrepreneurs, the 60 merchants, and the 60 innkeepers proved the wealthiest according to all three different calculations (see rankings in Table 22), though their household structure was quite different (for instance the number of children, proportion of earners, etc.).

Was social differentiation advanced at the time? According to Williamson, income inequalities (including both spatial and social differences) regularly grew in the first stage of capitalist transformations. Due to the lack of income data, we cannot test the relevance of this thesis. But based on “complex economic potential” calculated on the basis of the equation comprising socioeconomic indicators, some sort of social differentiation became measurable. The richest 15 percent of the Wohnpartheys comprised 20 percent of the cumulative wealth (for the sake of comparison, this figure could reach 40 percent in Ottoman towns in the eighteenth century).42 The second richest 15 percent was not significantly poorer than the first group. Altogether, one-third of the families (750) had higher per capita economic potential than the city average, and they accounted for 50 percent of the total wealth. The poorest 50 percent shared 25 percent of the total calculated wealth (see Figure 5 and compare it with the differences observed between the wealth levels and sizes of groups “e” and “s” in Table 18). In other words, the richer 50 percent of the population was three times richer than the poorer half. This inequality is not considered great compared to other regions in the world at the time.43

Figure 5. The distribution of economic potential (vertical axis) between groups of families (horizontal axis) as a %

The society was quite differentiated even based on single indicators, such as number of rooms, which indicated differing levels of wealth. Only 22 percent of the families had two rooms, and only 10 percent had three or more rooms (Table 6). On the other hand, the average 1.5 room/family is not greater than the value measured in Belgrade after 1900.44 While the average population density was 3.5 persons/room (and in 25 percent of households there were four or more inhabitants per room), in wealth groups 9–13 (representing 15 percent of Wohnpartheys), this improved to 1.5 person/room.45

The classification results also confirm, that our pre-defined categories (method 1: based on the prestige of occupation) “e,” “f,” “kk,” and “h” are considered the richest, followed by “p.” Thus, our preconception is not flawed (Table 23). The minor differences between the cluster-based and equation-based classification are due to the fact that the latter measures total wealth of a family regardless of family size. Group “f” is considered poorer if per capita wealth is calculated (instead of household wealth), because agriculture was (and remained) a labor intensive sector in Hungary, traditionally characterized by larger family size.

As for the internal differentiation among these groups, 90 percent of family heads had two or more than two rooms in group “e.” This figure was 60 percent in group “f,” 70 percent in groups “kk” and “Hungary,”46 and only 40 percent among households in category “p” (freelance professions).47 In the case of layers “s,” “q,” and “n,” 60 percent of the families were classified into the poorest four categories (1–4), while this was under 10 percent among inhabitants grouped into categories “kk,” “f,” “p,” “e,” and “h.” In these latter categories, the wealthiest four (9–13) constituted 40–70 percent of these groups (Figure 6). This figure reached 70 percent in group “e” (official-bureaucratic elite) and only 40 percent in group “p” (freelance professions).

These data also reflect the weakening of the traditional agrarian elite (or the fact that smallholders were also included in this group), but the merchant elite was not yet strong enough to take over the positions of the bureaucrats. The agrarian elite successfully transformed its economic power into political power, while the positions of people with freelance occupations were relatively weak compared to those of the state bureaucracy. As groups 9–13 represent a broad swath of more than 600 hundred families, it is not surprising that some artisans (20 percent) also appear in these aggregated groups.

 

Table 23. The rankings of the social layers pre-defined by prestige of occupation – using the two different statistical classification methods (cluster-based; equation-based)

 

e (47)

h (108)

f (116)

kk (214)

p

(91)

ö (101)

Total (2149)

k (132)

m (677)

g (34)

q

(60)

n

(30)

s

(508)

average cluster membership

2.45

2.8

3.2

3.06

3.71

3.85

3.93

3.91

3.97

4.21

4.49

4.48

4.75

ranking

1

2

4

3

5

6

8

7

9

10

12

11

13

average equation-­based wealth

4.52

2.85

2.57

2.12

1.84

1.81

1.49

1.41

1.33

1.04

0.83

0.82

0.66

ranking

1

2

3

4

5

6

7

8

9

10

11

12

13

Compare with Table 22. The numbers in brackets represent the family heads classified into the group.

Figure 6. Internal differentiation among social groups based on the prestige of occupations

Groups 1–4 refer to poor, groups 9–13 are wealthier than the average.

Spatial Pattern of Wealth and Social Classes

We have already investigated the spatial pattern of religions and occupations, but the spatial pattern of wealth also shows interesting features. The town was generally characterized by a concentric center-periphery accommodation pattern. This is true both for social groups (first method) and wealth classes. The wealthiest families lived along the main street of the town, which formed a north-south axis (Figure 7). Perpendicular to this street another road led to the east across the Ronyva River, where the concentration of rich people was also higher compared to other parts of the town. Based on the complex indicator of wealth, the northernmost and southernmost districts were inhabited by the poor. The map showing the social classes (based on the modified Erdei-model, Figure 8) and the map illustrating the number of rooms per family (used as a proxy for wealth) also confirms this phenomenon. The picture becomes more complicated if population density is illustrated on the map (Figure 4), 48 because one can find both large and small families among both the rich and the poor. In other words, the correlation between the size of the Wohnparthey (or number of children) and wealth was insignificant. On the contrary, based on these maps, there seemed to be evident connection between wealth and certain religions (Figure 2 and 7; Figure 9) and between wealth and occupation (Figures 7, 8, and 15). These variables were previously omitted from the investigations as they were not quantifiable. In order to measure and compare the relative wealth levels of different religious communities and occupations, a statistical analysis was carried out (Table 23).

With regards to religious differences, the Protestants (both Calvinists and Lutherans) had the greatest economic potential, followed by Jews (Figure 9). Greek Catholics were poorer than the average. Differentiation within the religious groups also advanced by 1870. Standard deviation values were high (there were poor artisans among Protestants and beggars and scrap-metal collectors among Jews). Protestants were overrepresented within category “h,” while Jews were overrepresented among members of group “kk” (both constituting the part of the elite). Within group “e” and group “f,” no similar trends could be observed (Figure 13). The differences in population density (persons/room) regarding religions were also significant (Figure 10). Age also influenced wealth (Figure 11).

Figure 13. Differences in religious composition of different occupation groups
(based on the Erdei-Weber method)

 

Figure 14. Differences in religions regarding the number of rooms / Wohnparthey

 

Figure 15. Internal differentiation among occupations based on number of rooms

Summary

To summarize our results, the GIS-aided evaluation of the 1870 census sheets managed to bring a new approach (an examination of various social divisions from the perspective of settlement patterns) into Hungarian urban and social history. HGIS contributed to the reevaluation of debated questions (the existence of a Jewish middle class, the transformation of the elite, the shift of power from the old agrarian elite, spatial segregation of Jews, the extent of amalgamation of emerging capitalist social divisions and the traditional classes, etc.). Some phenomena formerly investigated through individual case studies were statistically verified. We managed to reconstruct the accommodation pattern of the town in the beginning of the period of industrialization, and we also succeeded in tracing persisting and transforming elements regarding the location of occupations (tanners lived near water, bootmakers were concentrated in one street in the southern quartier) and the marriage behavior of different communities. The role of migration in the transformation processes was examined in a comparative context (by analyzing the immigrant and host societies of three towns), and the participation of different occupational and religious groups in this was also traced, along with their strategies. At the same time, we tried to utilize the hidden pontentials of the 1870 census by creating new sociodemographic indicators (proportion of children/family; proportion of earners/family; population density measured by inhabitants/room, room/family, etc.) and to measure the wealth or economic potential of the households. We tested three different methods to classify the population into social groups, and the three methods yielded partly corresponding results. The spatial patterns of the investigated sociodemographic phenomena and indicators were also mapped.

The core of the elite can be described as the common set of the three different methods (190 households). Altogether a maximum of 15 percent of the households could have been said to have belonged to the upper class. We defined the local elite as households with three rooms or more and two servants/coworkers. Protestants were overrepresented among them, but their positions were declining, and they were bound to the traditional official-bureaucratic elite. The new capitalist elite, composed of Jewish merchants, entrepreneurs, and Lutheran engineers was still weak in 1870. Despite their physical closeness of these two groups (living in the same streets), they did not really begin to amalgamate.

 

Archival Sources

Magyar Nemzeti Levéltár Borsod-Abaúj Megyei Levéltárának Sátoraljaújhelyi Fióklevéltára [Hungarian National Archives, County Archives of Borsod-Abaúj-Zemplén, Archives at Sátoraljaújhely] (MNL-BAZML SFL) XV. and XXXIII.

Magyar Nemzeti Levéltár Heves Megyei Levéltára [Hungarian National Archives, County Archives of Heves] (MNL-HML IV-416)

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Mazsu, János. “‘Inside borders.’ Jewish settlement in banned cities: Jewish immigration in Debrecen (Hungary) in the period between 1790 –1870.” Metszetek 7, no. 2. (2018)

Milanovic, Branko, Peter Lindert, and Jeffrey G. Williamson. “Measuring Ancient Inequality.” NBER Working Papers, 13550. Cambridge, MA, 2007.

Őri, Péter. “Család és házasodás a 18–19. századi Magyarországon: Pest–Pilis–Solt–(Kiskun) megye, 1774–1900” [Family and marriage in the eighteenth and nineteenth centuries in Hungary: Pest–Pilis–Solt–(Kiskun) County, 1774–1900.] Korall 8, no. 30 (2007): 61–98.

Pozsgai, Péter. “Görög és római katolikus nemzetiségek házasságainak jellemzői Torna megyében a 19. század közepén” [Marriage patterns among Greek and Roman Catholic minorities in Torna County in the nineteenth c.]. Korall 8, no. 27 (2007): 45–93.

Todorova, M.: Situating the family of Ottoman Bulgaria within the European pattern. The History of the Family 1 no. 4 (1996): 443-459.

Veliky, János. A változások kora. Polgári szerepkörök és változáskoncepciók a reformkor második évtizedben. Budapest: Új Mandátum, 2009.

Vuksanović-Anić, D. “Urbanistički razvitak Beograda u periodu izmedu dva svetska rata (1919–1941)” [Urban development of Belgrade during the Interwar period, 1919–1941]. In Istorija XX. veka. Zbornik radova 9. 458–465. Beograd, 1968.

Sólem Áléchem. Tevje a tejesember, avagy hegedűs a háztetőn [Tevje the Milkman, or Fiddler on the Roof]. Budapest: Tericum, 2001.

1 HGIS = Historical Geographical Information System (or GIStory, or GIS-aided historical research). For GIS-aided historical research the term HGIS is more common than GIStory. See Gregory, Ian N. A place in History: A short introduction to HGIS by the lead developers of GBHGIS. http://hds.essex.ac.uk/g2gp/gis/index.asp; or https://www.gislounge.com/find-gis-data-historical-country-boundaries/ and http://www.hgis-germany.de/, http://www.hgis.org.uk/resources.htm#top. GIStory is also accepted (see GIS and the City conference in Darmstadt, 2018: https://www.geschichte.tu-darmstadt.de/index.php?id=3633). Many thanks to János Mazsu for drawing our attention to the terminological problems.

2 Project OTKA 81 488. Principal investigator: János Mazsu. The reconstruction of social and spatial patterns of Debrecen, 1870–72 was considered the predecessor of this investigation. Recently, Réka Gyimesi initiated a similar project.

4 Source: MNL–BAZML SFL XV. 83. box. 77–79. Now www.hungaricana.hu and www.mapire.eu (containing settlement level cadastral maps) offer new instruments to find maps with good resolution and information on identification numbers.

5 The data sheets from Zemplén, Ung, and Sáros Counties also survived almost intact in the county archives.

6 The term household and family are not synonyms: a word describing the situation more properly is the German “Wohnparthei”. In the following, we use the three terms as synonyms despite the minor differences.

7 Demeter and Bagdi, A társadalom.

8 This value is high compared to neighboring towns and towns with similar sizes and functions. In Mukačeve (Munkács) the same figure was only 45 percent. Dányi describes Sátoraljaújhely as a “para-center.” Dányi, “Regionális vándorlás,” 99–103. Despite its development, the town was still unable to attract its larger “Hinterland” in the nineteenth century (despite the high birth rate the population decreased in the northern part of Zemplén County and in the northern part of Sáros County by 20 percent between 1880 and 1910 due to massive emigration to America and not to local centers.

9 While Eger became peripheral as major railway routes bypassed it, Sátoraljaújhely became a traffic center, an intermediate station of population movements towards Budapest. The main source area was Upper Hungary: the proportion of migrants arriving to Sátoraljaújhely from this direction was higher than that of migrants arriving from Zakarpatiya and from the regions beyond the Tisza River. Demeter and Bagdi, “Sátoraljaújhely,” Table 3.

10 The country averages were as follows: Roman Catholic: 52 percent, Greek Catholic: 10 percent, Calvinist: 12,5 percent, Israelites: 4.5 percent, Lutheran: 6.5 percent. So Greek Catholics and Jews were overrepresented and Roman Catholics and Lutherans were underrepresented in the town compared to national average. Katus, A modern Magyarország, 483.

11 The average for Pest County in 1896 was 4.6. Őri, “Család és házasodás,” 75. For Istanbul, this figure was 4.1 people around 1900. In some of the immigrant-dominated quarters it fell below 3.8. Based on a sample of 2,500 people, the average Bulgarian and Muslim household size in towns in the 1860s was 4.4 and 4.7 people respectively, while in Muslim villages this reached 4.9. Todorova, “Situating the family,” 452.

12 In 1930, 70 percent of the houses in Slovenia had only one room. Malojčić, Selo i tuberkuloza.

13 Three rooms are considered as a minimum to consider a family “middle class” according to Gerő. Thus, in Sátoraljaújhely, approximately 13 percent of the households fit into this category. Gerő, Dualizmusok, 149.

14 Ibid., 148.

15 Malojčić, Selo i tuberkuloza.

16 Veliky, A változások kora.

17 Of course, migration was not the only factor. A family name might go extinct if there were no sons, and this limits the relevance of our investigations.

18 Barta, Ha Zemplin vármegyét, 298. 312–13.

19 The census does not mention family ties between the Wohnpartheys. This hinders reconstructions without the aid of parish registers. The same constraints are valid for the investigations of matrilocality or patrilocality.

20 http://www.gistory.hu/g/hu/gistory/gismaps. See maps: chapter 8, urban society.

21 The blocks inhabited by Jews cannot be considered fully homogeneous because of the Christian servants and maids. The sources provide no information regarding the separation of Orthodox and Neologue Jews: in Sátoraljaújhely each group had a synagogue.

22 Most of the Jews in Debrecen also lived in the city center (along Hatvan Str. and Piac Str. near the Great Church of the Calvinists): 40 percent of the Jewish households dwelled in six streets. See Mazsu, “Inside borders” and Mazsu, “Piac, kereskedelem, kapitalizálódás.” In Sátoraljaújhely the preference of north-south and east-west main roads was observable among Jews, and though the east-west axis was of secondary importance regarding migration routes, it was a non-negligible direction concerning the movements of goods (grain trade).

23 Gyimesi and Kehl, “Spatial analysis of the socio-economic structure.”

24 Pozsgai registered 5–7.5 percent in the two districts and cca. 40 settlements in the rural Torna County in 1870. Compared to this, Sátoraljaújhely was really functioning as a melting pot. See Pozsgai, “Görög és római katolikus nemzetiségek.”

25 Supplemented by craftsmen serving the high-elite with their specialized knowledge.

26 The demographic transition in Hungary began only after the last great cholera epidemics (1873).

27 The proportion of the indigenous population reached 50 percent only together with the children, among whom immigrants were rare.

28 Their representation in the urban and county elite was traditionally higher.

29 In the larger city of Debrecen (which at the time only had 2,000 Jewish inhabitants), only 30 percent of the Jews were local-born. Another 20 percent was indigenous in the county, and another 30 percent arrived from the northeast. The average size of the 340 Jewish households indicates larger family sizes (5.5) than the town average, as was also true in Sátoraljaújhely (4.5). See Mazsu, “Inside borders.”

30 The Jews in Sátoraljaújhely were divided among traditionalist, modernist, and “status quo ante” factions.

31 Without own home/Wohnparthey, cca 1000 persons.

32 Pharmacists, assistant teachers, waiters, and merchant-assistants were also grouped here.

33 Demeter, “A dualizmus kori Eger.”

34 In Eger, the elite was underrepresented within the immigrant society. In the middle class, artisans were overrepresented, while lower “national” officials (porters, policemen, postmen) were recruited from local-born people.

35 In the case of Eger, the use of sources of a different character, namely the parish registers, limited the reliability of the classification and the comparison. The statistics were based on 167 marriages from 1883, where the occupation and place of origin of the husband, the husbands’ father, and the wives’ father were mentioned too.

36 In Eger, the local elite was also stronger compared to the immigrant elite society (22 vs. 12 percent).

37 In Varannó, the officials, bureaucrats, and lower-ranking state officials were all immigrants. Lacking a secondary school, the townlet was unable to reproduce its elite. Merchants, artisans, and entrepreneurs were underrepresented among immigrant earners (constituting 57 percent of all earners in Varannó, but 67 percent in Sátoraljaújhely, Table 17). 60 percent of the locals were classified into the middle classes (among migrants, this figure was only 40 percent). 33 percent of the local-born society was poor. 42 percent of the migrant society was poor.

38 Widow(er)s (family heads) were treated separately, as we did not have information about their professions.

39 Discriminant analysis was applied as a control for clusterization.

40 The success rate of reclassification by discriminant analysis was low, under 50 percent.

41 They could be considered the “core elite,” followed by a “buffer-transition” group of an additional 100 families.

42 Canbakal and Filiztekin, “Wealth and Inequality.”

43 The richest 2 percent owned 25 percent of wealth in China. In New-Spain, the richest 10 percent owned 55 percent of the wealth in 1790. In Bihar (India), in 1804 the richest 20 percent owned 50 percent of the wealth, and in Naples in 1811 the richest 10 percent owned 33 percent of the wealth. Milanovic, Lindert and Williamson, “Measuring Ancient Inequality.”

44 In Belgrade 60 percent of the houses had not more than one room in 1907 (as in the case of Wohnpartheys in Sátoraljaújhely), but the density was 3.5 prs/house, while in the Hungarian town it was 9 prs (calculating with two households/house). Vuksanović-Anić, “Urbanistički razvitak Beograda,” 458–65.

45 The narrow elite (group 11–13) was characterized by a low number of children, but this was equalized by the auxiliary workforce (Table 19). The proportion of earners was higher than the city average. The average population density (prs/room) and number of rooms in the households of the elite (above two) were similar to the figures measured in groups 9 and 10.

46 In 1926, a merchant family or the family of an official in Belgrade had 2.5 rooms, artisans had 1.9, and workers had 1.5. The former values are similar to the values for Hungary, while the latter is higher. Calic, Sozialgeschichte Serbiens, 323–25.

47 Or, using a different approach, in cluster 1 each family had two or more than two rooms (90 percent had more than 3), while it was only 60 percent in cluster 2.

48 The number of rooms per family was high along the north-south axis of the town, while population density was great in the north and on the eastern outskirts and in Zsólyomka.

* This study was realized with the support of the NKFIH FK 128 978 (Knowledge, Landscape, Nation and Empire: Practices of Knowing and Transforming Landscape in Hungary and the Balkans, 1850–1945) research project.

51_old.jpg

Figure 2. Spatial patterns of religious and denominational belonging
(family heads) in Sátoraljaújhely in 1870

Source: MNL-BAZML SFL XV. 83. box. 77–79.

fig%202%20religion.tif
legend%20fig%202.JPG
Demeter3a.jpg
Demeter3b.jpg

Figure 3. Religious differentiation (occupations)

fig%204%20person%20per%20room.tif
legend%20fig%204.JPG

Table 22. The sociodemographic features of occupations
(values under the average are indicated by Italic letters)

Occupation

Average number of children per family

Proportion of earners

Average number of rooms

Inhabitant /room (avg.)

Average wealth (equation)

Average household size

Average number of servants

Average coworker number

Relative ranking based on wealth (equation)

Relative ranking based on cluster-membership

Relative ranking based on number of rooms

lawyer and doctor (33)

1.39

0.36

3.64

1.43

4.01

5.36

1.91

0.24

1

1

1

innkeeper, restaurant owner (60)

2.9

0.27

2.32

2.77

2.39

5.73

0.68

0.42

5

2

2

landowner (106)

2.03

0.35

2.3

2.92

2.66

4.85

0.82

0.39

2

3

3

wheat and flour merchant (21)

2.48

0.22

1.81

3.69

1.35

5.62

0.57

0.05

11

4

8

merchant (38)

0.83

0.46

1.89

1.85

2

3.28

0.83

0.06

3

5

5

engineer (18)

0.83

0.46

1.89

1.85

2

3.28

0.83

0.06

4

6

6

joiner (35)

1.69

0.39

1.84

3.52

2.24

5.57

0.23

1.63

6

7

7

entrepreneur (13)

2.23

0.23

2.08

2.67

1.35

4.85

0.31

0.31

7

8

4

butcher (27)

2.15

0.27

1.56

3.76

1.25

5.04

0.44

0.44

9

9

10

tanner (37)

1.86

0.36

1.27

3.58

1.21

4.22

0.19

0.41

12

10

16

craftsmen who made heavy mantles (46)

1.57

0.37

1.34

3.06

1.02

3.93

 

0.7

17

11

13

bootmaker (144)

2.19

0.37

1.33

4.01

1.03

4.78

 

 

14

12

14

Total sample

1.81

0.35

1.52

3.52

1.49

4.4

0.34

0.46

13

13

11

grocer, chandler (27)

2.63

0.25

1.19

4.39

0.81

5

0.41

0.11

18

14

18

teacher (15)

2.27

0.32

1.77

2.91

1.22

4.67

0.53

0.07

10

15

9

tailor (103)

1.81

0.37

1.33

3.67

1.16

4.52

0.17

0.64

15

16

15

shoemaker (47)1

1.55

0.33

1.36

3.67

1.16

4.87

0.19

0.79

16

17

12

bread-maker and sewer women (37)

1.51

0.61

1.2

2.58

1.46

2.78

0.03

0.54

8

18

17

cartmen (52)

1.75

0.35

1.03

4.05

0.87

4.12

0.17

0.19

20

19

19

personal servant (55)

1.36

0.48

1

3.93

0.79

3.27

0.11

0.29

19

20

20

agrarian wage laborer (343)

1.28

0.39

0.86

4.41

0.54

3.28

0.01

0.15

21

21

21

1 Shoemakers were not considered wealthy by contemporary writers. Among Jews, this was a despised (but frequent) occupation according to Sólem Áléchem.

fig5.jpg
fig6.jpg
fig%207%20vagyon.tif

Figure 7. Spatial pattern of wealth based on the method using an equation composed of sociodemographic indicators, 1870

 

legend%20fig%207.JPG
fig%208%20sauh%20tarsadalom.tif

Figure 8. Spatial pattern of social groups in Sátoraljaújhely in 1870

For the detailed legend see Table 18a.

legend%20fig%208%20kimaradt.JPG
Demeter9.jpg

Figure 9. Connection between religion and economic potential based on the complex indicator (average, std. dev.)

 

Demeter11.jpg

Figure 11. Connection between average economic potential (complex indicator based on the equation) and the age of the family head

 

Demeter10.jpg

Figure 10. Differences in population density (inhabitants /room) based on religion (average and std. dev.) 1

1 Mean is dark. Std. Deviation is indicated by light grey.

Demeter12.jpg

Figure 12. Differences in population density (inhabitants /room) based on social groups defined by the prestige of occupation (Erdei-Weber method) (average and std. dev.)

 

Demeter13a.jpg
Demeter14.jpg
Demeter13b.jpg

Total

79987.png
79980.png

pdfVolume 8 Issue 1 CONTENTS

Regional Differences in Development and Quality of Life in Hungary During the First Third of the Twentieth Century*

Zsolt Szilágyi
University of Debrecen
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In this essay, I look for answers to the following three questions: to what extent did the borders of Hungary after the 1920 Treaty of Trianon overlap with borders of structural development in 1910 and in 1930; what does the term “development” mean when we are talking about the Carpathian Basin; and how did geographical differences in standards of living change in the territories under discussion over the course of these two decades. To some extent, the new political borders which were drawn in 1920 in the Carpathian Basin overlapped with the borders which reflected the different levels and patterns of development in the region. This is a consideration which has been given little attention in the secondary literature in Hungary. The developmental structure of the Carpathian Basin in 1910 can be mapped using the GISta Hungarorum Database. One discerns in this structure a major line of development. Within this line, one finds an area in which the level of development was higher than average and, in some places, considerably higher than average. Another distinctive feature of this area was that is had several centers, and this fact was of particular importance from the perspective of the Treaty of Trianon and its alleged consequences. In recent years, groundbreaking research on economic history has persuasively shown that Hungary managed to recover economically relatively quickly after 1920. Numerous factors played a role in this recovery. One of the more decisive, I argue in this study, was the geographical developmental structure of Trianon Hungary, which had several centers. Although the territory of Trianon Hungary was considerably more developed than other areas of the Carpathian Basin, it is quite clear that the economic fault lines which existed after Trianon had in fact existed before Trianon too, and the internal peripheral areas had already formed (and remained essentially unchanged throughout the interwar period). Thus, the Treaty of Trianon did not play any role in the emergence of formation of these areas. The treaty may well have had grave consequences for the country and region, but the developmental geographical structure of Hungary in the interwar period, which ultimately exerted a shaping influence on development in Hungary for the rest of the twentieth century, was not a result of Trianon.

Keywords: HDI change, regional differences in development, Interwar Hungary

Theoretical and Methodological Frameworks

During the last roughly three decades of the twentieth century, both in the fields of geography and history, research focusing on structural analyses was gradually pushed into the background as new analytical perspectives and frameworks gained ground and agent experience became a priority. Thus, quantitative sources and methods which rely on quantitative sources seemed to lose a lot of their significance by the turn of the century. A series of novel postmodern approaches gained ground. This prompted some scholars to raise scientific concerns. For instance, Geoffrey Crossick, professor at the University of London, highlighted that overemphasis on cultura l questions leads to the striking neglect of structural issues and a drop in the number of empirical studies. 1

Crossick was one of the first scholars to encourage the renewal of empirical studies, which was appreciably furthered by the digital revolution, which accelerated dramatically at the turn of the twentieth and twenty-first centuries. Due to the widespread use of personal computers, the sophisticated table management and data management programs, and the increasing use of the geospatial systems in the science of history, a new era of empirical studies dawned. The new quantitative historical studies were inspired in part by a need for a “new materialism” that came in the wake of postmodern history recordings and also by the overwhelmingly popular2 spatial turn.3

The pioneering 2006 study by Róbert Győri entitled “Bécs kapujában” (“At the Gates of Vienna”),4 which was published in the Hungarian periodical Korall, has played a crucial part in scholarship and research in Hungary. The study is an extended chapter from Győri’s doctoral dissertation, in which he lays a new historical geographic bases for measuring differences in the rates of local regional development.5 As far as the selection of variables was concerned, Győri chose indicators of literacy, economics, and infrastructure.6 He used the following six indicators (Table 1–2).

 

Table 1
Indicators of regional developmental studies conducted by Győri

Code

Specification

Source

m1

literacy rate among the population over 6 in 1910

MSK Ús. Vol. 42

m2

rate of patients undergoing medical treatment between1901 and 1910

MSK Ús. Vol. 46

m3

rate of high-quality residential buildings in 1910

MSK Ús. Vol. 42

m4

rate of migration balance between 1901–1910

MSK Ús. Vol. 46

m5

rate of non-agricultural workers in the labor force in 1910

MSK Ús. Vol. 48

m6

net cadastral income per agricultural employee in 1908/1910

MSK Ús. Vol. 39*

Source: Győri, “Bécs kapujában,” 233.

Remark: *) rates of net cadastral income recorded by Győri followed by the corrections published in 1914, while during a later inspection of the Alföld region, the same process was conducted based on the data from 1935 (Szilágyi, “A fejlettség területi különbségei,” 49).

Table 2
CDI calculation method for component indicators

 

Indicators (m1–6), base variables (v1–13)

Number of records

Data missing

Mathematical formulas for indicator calculation

Code

Description

m1

v01

number of people under 6, 1910

12 542

0

m1=v03×100/(v02–v01)

 

v02

total population in 1910

12 542

0

 

 

v03

literacy rate, 1910

12 542

0

 

m2

v04

annual mortality rate, 1901–1910

12 535

7

m2=v05×100/v04

 

v05

annual average rate of fatalities receiving medical treatment (from all deaths), 1901–10

12 536

6

 

m3

v06

number of stone or brick houses, 1910

12 542

0

m3=(v06+v07)×100/v08

 

v07

number of adobe or mud houses with stone or brick foundation, 1910

12 542

0

 

 

v08

total number of houses, 1910

12 542

0

 

m4

v09

total population in 1900

12 537

5

m4=(v02–v09–v10)×100/v09

 

v02

total population specific to the date 1910

12 542

0

 

 

v10

rate of natural population change, 1901–10

12 535

7

 

m5

v11

number of agricultural traders, 1910

12 542

0

m5=(v12–v11)*100/v12

 

v12

total number of earners in 1910

12 542

0

 

m6

v13

cadastral net income from total land tenures in Hungarian Koronas, 1908

12 434

108

m6=v13/v11

 

v11

number of agricultural earners, 1910

12 542

0

 

Totals (v1–v13)

162 913

133

 

Source: CBRDD, compared to the original sources, GHD <> MSK Ús. 39, 42, 46, 48, own editing.

Note: variables in italics have been listed previously. Description of m1–6 indicators are included in Table 1.

The average derived from the normalized value of six developmental indicators (m1–6) makes the Complex Developmental Index (CDI). If this methodological procedure is taken as the basis on which to identify and compare regional differences, then we are given not an overall picture of the rate of modernization and development, but rather an incomplete sketch based on subsequently selected indicators. In practical terms, we can only see what the development indicators measure compared to prior circumstances, which allows for interpretation of the developmental overview of a simplified version.

As for the rate of development and the quality of life, further methods are available with which to measure them. In recent decades, the use of Human Development Index (HDI)7 has gained ground, especially in the social sciences. Today, primarily sociology, geography, and political science utilize HDI. This multivariable index is adapted mainly to classify the regions as “developed,” “less developed,” and “underdeveloped” and also to map the regional differences in the quality of life. In the 1970s and 1980s, there was a growing need among social researchers to develop a multivariable index8 which would replace the “one-dimensional” GDP9 already widely used to measure the rate of economic development. There was need of an index which would be reactive not just to economic factors, but also to other (individual) circumstances (skills and opportunities). Income is one factor on the basis of which “human welfare” can be gauged. But human welfare is perhaps better gauged via an assessment of choice options. In particular, the extension of choice options as a process gives meaning to the term “human development.”

The method of according to which the HDI is attainted was published in the first issue of the series Human Development.10 The calculation method on which HDI is based has been refined over the course of the last couple of years (e.g. in 1991, 1999), but the process itself has remained unchanged. The value of HDI takes the arithmetic average of three component indicators (lifespan, knowledge gained from education, and standard of living). The component indicators are defined as follows: lifespan via life expectancy at birth; knowledge via the average of literacy and numeracy added to the combined key indicators of the elementary, secondary, and higher education levels; standard of living via the volume index of per capita GDP measured by purchasing power parity (PPP).11 The Hungarian historical sources do not allow us to map differences in development within the area of the country via the UN method of HDI calculations. In order to arrive at an informative map, HDI must be modified in the Hungarian case. The rates used are as follows: rate of life expectancy at birth instead of raw death rates, literacy rate among those above six years of age instead of education component indicator; rate of land tax, real estate tax, corporation tax, and tantième tax out of the ordinary tax system instead of GDP (Table 3).

Table 3
Source of required variables for HDI component indicator

Code

Description

Source

k1

Average of deaths (1901–10)

MSK Ús. Vol. 46

Population (1910)

MSK Ús. Vol. 42

Average of deaths (1921–30), data broken down by year

KSH 1969.

Population (1930)

MSK Ús. Vol. 83

k2

Literacy rate (1910)

MSK Ús. Vol. 42

Population above 6 (1910)

MSK Ús. Vol. 42

Population (1910)

MSK Ús. Vol. 42

Literacy rate (1930)

MSK Ús. Vol. 83

Population above 6 (1930)

MSK Ús. Vol. 83

Population (1930)

MSK Ús. Vol. 83

k3

Municipal substitute taxation of which base relies on state taxation of 1908 (K)

MSK Ús. Vol. 39

Land tax, house tax, income tax levied on urban residents, taxes and other direct taxes levied on guilds, companies liable to public accountability (1910, K)

MSK Ús. Vol. 58

Population (1910)

MSK Ús. Vol. 42

Total state taxes serving as the basis for municipal substitute taxation (1934, P)

MSK Ús. Vol. 93

Tax estimates for towns (method of calculation is listed in the text):

 

· Land tax paid by municipal cities (1933/34, P)

AS 1934: 51

· House tax paid by municipal cities (1933/34, P)

AS 1934: 77

· Company tax and tantième tax paid by municipal cities (1933/34, P)

AS 1934: 149

· Land tax paid in county towns (corporate towns) (1933/34, P)

AS 1934: 51

· Total of land tax paid within the country (1933/34, P)

AS 1934: 51

· Cadastral income from lands agriculturally cultivated by towns (1935, AK)

MSK Ús. Vol. 99

· Total of house tax paid in county towns (1933/34, P)

AS 1934: 77

· Utility value of dwellings used by owners in county towns (1933/34, P)

AS 1934: 82

· Raw income from leased dwellings in county towns (1933/34, P)

AS 1934: 83

· Company and tantième tax paid by county towns (1933/34, P)

AS 1934: 149

· Number of residents working in industry, trade, and travel (1930)

MSK Ús. Vol. 86

Sources: in addition to the above, the date 1910 is listed: GHD, own editing.

Note: the dissolving of k1–3 is listed in the methodological description of HDI calculation.

I have obtained details from three databases for the calculations of territorial inequalities in regional development and quality of life: 1. GISta Hungarorum Database (GHD, 7.3 million data entries, Gábor Demeter),12 2. Kárpát-medencei Területi Fejlettségi Adatbázist /Carpathian Basin Regional Development Database/ (CBRDD, 0.4 million data entries, Zsolt Szilágyi), 3. Magyarországi Életminőség-alakulás Történeti Adatbázisa (Hungarian Quality of Life Historical Database (HQLHD, 0.5 million data entries, Zsolt Szilágyi).

The development the Spatial Structure of the Carpathian Basin
at the Beginning of the 20
th Century (CDI)

The first complex, multivariable development studies of the Carpathian Basin were done relatively late, in 2000, when Pál Beluszky published his findings.13 Beluszky used twelve indicators in his study.14 He sought to select indicators (drawing on his years of scientific experience and his intuition) which would enable him to map both the economic and social changes effectively. The results profoundly rewrote all the concepts formed on the spatial structure of modernization in the Carpathian Basin at the turn of the nineteenth and twentieth centuries.15

On the basis of Beluszky’s findings, we can conclude that the majority of the country had reached a level of modernization at the beginning of the century. Beluszky introduced the Kisalföld and the Great Plain as the regions which had led the process of modernization,16 where the former market towns claimed the leading position in this process.17 No further advancement has been made until now. (With regards to national politics of regional development, János Pénzes has recently done studies from the perspective of geography.)18

Figure 1 was created using the unified development indicators (m1–6) after the standardization of the indicators based on the average values (CDI). It indicates regional differences. The two central regions, Vienna and Budapest, conspicuously stand out. The leap of development in Budapest, which was influenced from the east, is significantly harsher than it was in the case of Vienna. Apparently, the development of the region between the two capital cities was outstandingly high: probably the two metropolises enhanced each other’s influence. It is also obvious that spatial contact was stronger between the mine basin around Tatabánya (Dorog) and the capital than it was between any other regions. It is also clear that the Hungarian capital’s economic hinterland was made up not just of the abovementioned regions, but also of the areas to the south of Budapest along the Danube, which were rich in German horticultures, and areas to the southeast of Budapest, which were fruit and vegetable farmlands at the rim of the towns of Kecskemét, Nagykőrös, and Cegléd.

Figure 1. Development spatial structure in the Carpathian Basin based on CDI, 1910
Source: CBRDD, own calculations and compositions

 

Central regions which as peaks stood out with significantly lower rates of modernization were the surroundings of Resicabánya (today Reşiţa in Romania), Petrozsény (Petroşani, Romania), and Beszterce (Bistriţa, Romania). Regions which showed less significant development were around the cities of Rozsnyó (Rožňava, Slovakia) and, in the south, Zombor (Sombor, Serbia; Sombor lies in the region known as Eszék, which is not included in this study). At the beginning of the century, what at the time was known as Upper Hungary was a more or less coherent area with an above-average level of development. It included the cities of Zsolna (Žilina), Poprád (Poprad), Kassa (Košice), Rozsnyó, and Besztercebánya (Banská Bystrica), all of which are found in Slovakia today. The area around the cities of Nagykanizsa, Kaposvár, and Szekszárd was similarly developed, as were the triangle formed by Zombor, Szabadka (Subotica, Serbia), and Újvidék (Novi Sad, Serbia) and the market town belt over the Tisza River (the formed by the cities of Szeged and Debrecen). Towards the Székely Land, a region in the eastern stretch of Transylvania, two “development corridors” appeared: the gateway towards the north, which was bordered on either side by the cities of Szatmárnémeti (Satu Mare), Nagybánya (Baia Mare), and Beszterce (Bistriţa) to the northeast and Marosvásárhely (Târgu Mureş), Kolozsvár (Cluj), and Nagyvárad (Oradea) to the southwest, and the one lying towards the south, south of the Maros River, following the crest of the southern Carpathian Mountains across the so-called Saxon Lands (a region of Transylvania which had a strong Saxon present until the last decades of the twentieth century).

At the beginning of the century, the regions which had below-average development rates were the Zalai hills, the sand lands of Bugac, the plains of the Hortobágy, and the so-called Nyírség. These areas were either densely populated small villages with no regional centers or uninhabited areas where the biogeographic indicators (such as low total annual rainfall, etc.) impeded the emergence of settlements. Over the main structure line, in the north of the peripheral region, a narrow zone and in the east an expanded zone appeared, both with development rates which were well below average.

Based on the above descriptions of the different regions (which are confirmed by numerus sources in the Hungarian secondary literature), the so-called “development slope,” according to which the rate of development shows a gradual decrease following the direction from the western regions towards the eastern part within the territory of historical Hungary, proves incorrect. The new results allow us to deconstruct the “slope thesis.” We should not regard the surface forms of development as a slope, but rather should consider them a hilly land which slopes from the direction of west towards east and from south towards north and also shows rises in the form of coherent areas or islands. These “high areas” are divided by lowland valleys which prove to have high (metaphorical) altitudes in patches, but mostly have surprisingly low points. As a consequence, the rigid “slope image” should be rejected in favor of an image of a “development membrane” with varied and flexible forms.

The development membrane reveals the developmental spatial structure of the Carpathian Basin in the most visual way possible. The most apparent feature of Figure 2 is that the developmental terrain is the inverse of the geographical terrain. At places where tall mountains were found in reality these regions had low rates of development. In places where a basin was found, there can be found the most developed regions. Certainly, this statement is not well founded yet. However, it highlights the fact that though there had been raw material resources for possible industrial purposes in the mountainous area, and also energy resources were also easily available, the processing plants and the low energy-demand industries were set in the basin-related divisions. Literacy rates and access to basic health were better in the middle of the country (i.e. the flatlands), and immigration rates were higher. All these facts make is clear that the Carpathian Basin was at an above-average development level at the beginning of the twentieth century. This region was a dynamically developing part of the country at the beginning of the twentieth century, with a high level of economic innovation compared to its surroundings, and it offered higher standards of living. On the whole, this region was a basin which attracted people who hoped not simply to earn a livelihood, but also sought to invest.

 

Figure 2. Development terrain (membrane) of historical Hungary, 1910
Source: CBRDD, own calculations and compositions.

 

Based on this, we must reject the notion that, from the perspective of modernization, the two capital cities and the surrounding areas were the only parts of the Carpathian Basin at the beginning of the twentieth century which enjoyed promising rates of development. On the contrary, we can clearly construct a multi-centered developmental structure of the Carpathian Basin based on the subsequently selected indicators. Our study reveals that a developmental main structure line existed at the turn of the century in the Carpathian Basin, in other words a kind of “break line” (Figure 1). The areas over the main structure line can undoubtedly be regarded as peripheral in the narrative of the economic development rate of the area. Our study indicated the need for further research to determine whether this line overlaps with the eastern borders of Hungary established by the Treaty of Trianon and, if so, to what extent. Gábor Demeter has shown that “the new country borders, as internal break lines, existed before the Treaty of Trianon, and they did not simply constitute break lines defined merely by differences in language.”19 The extent to which some of the newly created national borders in the Carpathian Basin correlated with the developmental spatial structure of the greater area is unclear. This question merits further study.

Within the main line of development structure lay a region which was not homogeneous at all and showed above average (often very above average) rates of development (Figure 2). It was a multi-centered region, which gained specific meaning in the narrative of the Treaty of Trianon. The pioneering economic historic research of recent years have clearly proven that the country regained its stability relatively quickly after 1920.20 This economic success was due to many factors, but on the basis of our study, it is clear that one of the most important elements was the multi-centered developmental spatial structure of Hungary after the Trianon Peace Treaty.

Regional Differences in Quality of Life in Hungary in 1910–1930

Based on the calculations, the national average of HDI in 1910 was 0.451, which showed a slight rise of 2% to 0.461 as a result not just of the past economic and social changes but also as a consequence of distortion stemming from the adapted resources. Practically, in 1924, the community tax base components had seen modifications following an Administrative Circular specified by the Ministry of Home Affairs.21 Consequently, the calculations were based on four specific indicators: land tax, real estate tax, corporation tax, and tantième.22 Thus, income tax and mine tax were deleted from the base of substitute tax. Corporate tax and tantième were “theoretically” equal to the previous tax paid by public companies and associations also the tax on equity interest and the benefit tax. The conditions of taxability, however, had seen profound alterations in the meantime. Consequently, the substitute component indicators for GDP from 1910 and 1930 (which consist of the abovementioned taxes) can only be compared to a limited extend. With regard to these factors, the spatial structure of territorial inequalities related to quality of life had remarkable features: the major part of Transdanubia, the agglomeration of the capital city, and the rim of the towns in Tiszántúl were more developed according to this narrative than any other parts of the country. Societies in the northern regions which were industrially more developed were in a favorable position, as were town dwellers. An additional distinctive feature of the emerging spatial structure is that when taking into consideration the territory of the country as it was later defined by the Treaty of Trianon, the northeastern region of the Great Plain was acknowledged as a periphery even in 1910. Peripheral regions were clearly marked by the Nyírség, the region of Közép-Tisza and Jászság, and also parts in the Hills of Zala and the wider surroundings of Bugac. The results derived by two different methods of calculation (CDI, HDI) closely overlap (Figure 3).

Figure 3. Regional differences in the quality of life between 1910 and 1930
Source: GHA, MÉTA, own calculations and compositions.

The overall picture becomes more complex as we investigate the volume of changes in certain regions. It is clear that more than 40 percent of the territorial units were substantially “stable.” Between 1910 and 1930, there were no towns or districts in these regions that would have shown a “leap” forwards or backwards of more than 20 points in an imaginary ranking. This kind of regional attribute can be identified with most of Transdanubia, the Sárrétek district of Tiszántúl, the third of the western region between the Danube and the Tisza Rivers, the Zemplén, the Bükk, and the Cserhát Mountains. The northern area of the Great Plain was in a particularly disadvantageous situation, as were the districts of Kiskunhalas and Kiskunfélegyháza and the majority of the districts in the border areas east of the Danube River. This contributed to the emergence of a state in which the pre-Trianon internal peripheral regions faced further deterioration and their positions became more disadvantageous. In the districts that were transformed into border areas, the pace of development apparently became slower. By contrast, the towns, especially the capital city and its agglomeration and the towns of Northern Transdanubia (including Miskolc), kept their previous momentum. From the perspective of development, they made dramatic leaps in the national ranking. The Győri basin near Vienna was an interrelated unity which showed a different developmental trajectory, as were the extended environment of the Pre-Alps and the city of Szombathely. In the north, only Miskolc underwent this different process of development, and in the Great Plain, only the areas lying next to the railway between Budapest, Szolnok, and Debrecen and the southern parts of Békés County (Figure 4).

Figure 4. Changes in the quality of life between 1910 and 1930
Source: GHA, MÉTA, own calculations and compositions

A new consideration which is important if one seeks to place the data in a meaningful context lies with the calculation of the variation coefficient.23 A further question arises here as to whether the differences in development (quality of life) among the regions, towns, and villages showed decreasing or rising tendencies. If the value of the variation coefficient proves lower for the period under study then the rate of regional development discrepancies among the areas compared also shows a decrease, which indicates a favorable outcome. This case indicates convergence; otherwise, the opposite should indicate divergence. (Table 4, Figure 5).

 

Table 4
Variation coefficient changes within the area of Hungary after the Treaty of Trianon,
1910–1930

Description

Variance

Average

Variable coefficient

Difference

1910

1930

1910

1930

1910

1930

points

%

 

Covering the total area of the country after the Treaty of Trianon

Counrty area including Budapest

0.11

0.10

0.45

0.46

23.35

21.20

−2.15

−9.22

Country area excluding Budapest

0.10

0.09

0.45

0.46

22.28

20.51

−1.78

−7.97

Counties

0.07

0.07

0.44

0.46

16.75

15.32

−1.43

−8.55

Districts

0.09

0.08

0.42

0.44

20.24

17.91

−2.33

−11.51

Towns

0.12

0.12

0.52

0.52

22.51

22.10

−0.41

−1.84

Towns excluding Budapest

0.11

0.11

0.52

0.52

20.32

20.88

0.56

2.75

 

Statistics by regions

Towns

 

 

 

 

 

 

 

 

Transdanubia

0.08

0.09

0.59

0.56

14.15

16.06

1.91

13.50

North Great Plain including

0.11

0.07

0.46

0.48

24.28

15.39

−8.89

−36.62

Budapest

0.12

0.13

0.51

0.51

24.42

25.07

0.65

2.65

Great Plain excluding Budapest

0.10

0.12

0.49

0.50

20.17

23.11

2.93

14.55

Districts

 

 

 

 

 

 

 

 

Transdanubia

0.05

0.05

0.49

0.49

10.30

9.69

−0.61

−5.97

North

0.05

0.04

0.40

0.41

13.67

10.36

−3.31

−24.23

Great Plain

0.09

0.09

0.37

0.40

23.04

22.23

−0.81

−3.50

Regions

 

 

 

 

 

 

 

 

Transdanubia

0.07

0.07

0.51

0.50

13.89

13.12

−0.77

−5.56

North

0.07

0.05

0.41

0.42

17.17

12.85

−4.32

−25.16

Great Plain

0.12

0.12

0.42

0.44

28.29

26.72

−1.57

−5.55

Source: GHD, HQLHD, own calculations.

Figure 5. Variation coefficient changes, 1910–1930
Source: HQLHD, own calculation and editing

Between 1910 and 1930, in the area of the country as it was defined by the Treaty of Trianon, there was a decrease not only in regional development disparities related to the rate between districts (−11.5%), but also related to the rate between towns (−1.8%), which suggests that, overall, the disparities among towns showed only minimal differences in comparison to the disparities among districts, where the rate of convergence was six times higher. If we examine the shifts in disparities among towns excluding Budapest, then a kind of divergence can be traced (+2.8%), which means that while the regional differences between the capital and the other towns decreases, in the case of the statuses among towns, a completely different tendency can be observed. An ongoing increase is traceable. The status is different if we inspect the differences based on regional sections. Convergence can only be seen among the towns of the northern region (−36.6%), while the gap between the towns on the Great Plain shows a more remarkable increase (+14.6%) than between Transdanubian towns (+13.5%). In contrast with these trends, the differences among the villages in the three macro-regions of the country showed further decreases, especially in Transdanubia, where the convergence of villages was five or six times more in volume than the villages in the other two regions. Therefore, the disparities among the villages in Transdanubia became less traceable at a remarkably higher space and rate than in any other region of the country.

As a consequence, we can also determine which region, given its own attributes, was more preferably influenced by the equalization process of regional differences. It is demonstrable that it was neither the Great Plain nor Transdanubia which marked the process, but surprisingly, the northern region proves to have taken the lead, where convergence reached rates five times higher than the rates found in other regions. This remarkably preferable status can be primarily attributed to the higher rate of disparity equalization between Northern towns (Figure 5).

Figure 6. Settlement density in Hungary, 1933
Source: HQLHD, own calculation and own editing.

Overall, the rate of gap decrease showed more considerable moderation for the villages in Transdanubia, while the rate of gap decrease showed more considerable moderation for towns in the northern regions. However, the data relevant to the Great Plain indicate that a process completely different from the formerly sketched ones took place. As was the case in Transdanubia, the disparities among the towns of the Great Plain continued to grow; the regional disparities among the villages continued to show no decrease, but only slight moderation, unlike in the other regions. So, in the Great Plain, travel processes between the villages and the towns slowed down after World War I, which was not typical neither to Transdanubia nor to the Northern Region. Furthermore, the regional differences in lifestyles showed faster growth than the “adjustment” itself, which indicates that the gap between the agricultural towns in the Great Plain and the villages saw further “depths.” This exceptional process can be correlated with the unique settlement structure of the land, and it also indicates that the population density of the Great Plain was much lower than the population density of other regions. (Figure 6).

The Development of Quality of Life in Hungary Based on International Comparisons

Using the data assembled by Nicholas Crafts,24 Béla Tomka has taken European data-based comparisons related to Hungary on the basis of HDI. Sine some of the data was unobtainable, Crafts could not determine the index related to Hungary at the beginning of the twentieth century, so the calculations for 1913 were made complete by Béla Tomka. This has enabled historians to analyze the status of Hungary in correlation with a Western European context. Based on the results, it is apparent that the quality of life in Hungary compared to Northern and Western Europe was clearly even more unpreferable than it had been in 1913. (Figure 7). Over the course of the following decades, the gap displayed significant shrinking: while at the beginning of the century the HDI index was only 78% of the Western European average, by the mid period of the century it took 93%.25

 

 

 

Figure 7. HDI rate in Hungary, compared to Western Europe, 1913
Source: Tomka, Gazdasági növekedés, 191. Own editing.

In recent years, Leandro Prados de la Escosura has collected the base data from different countries of the world. His work enables us to determine the three component indicators of HDI in 1870 when focusing on different time sections. The researcher had taken the point at the beginning of his studies that the HDI (UNHDI) calculated via UN methods can only be utilised at a confined birth rate in case of historical perspectives and in the global context, which induced him to make changes to the calculation methods (he has introduced the use of the geometric mean instead of the arithmetic mean) and also to give the index a new name: Historical Index of Human Development (HIHD).26

Based on the data available, Prados has published HIHD indexes about 164 countries. These indexes enable one to sketch a quantitative image generated via the most modern methods of the quality of life validatable for both countries and eras. Consequently, the time and space dynamics of the changes in the quality of life have become constructible. (Figure 8).

Based on the latest findings, the rate of “development” could have been more balanced than was suspected earlier. The region-based comparison also highlights the fact that, compared to other northern and western European countries, a significant improvement was traceable in Hungary between 1870 and 1925. It clear that the increase in the quality of life shows balance between 1870 and 1913, though perhaps a slight slowdown is observable at the turn of the century. Although, it is clear that in the regions of northern and western Europe there was a favorable improvement with higher rates and faster paces of modernization and improvements in quality of life (which theoretically was correlated to the prospering economy) at the beginning of the twentieth century until the outbreak of World War I. As for the quality of life, which was theoretically (also) in correlated to the prospering status of the economy, The trend commencing in 1913 went onwards, and this contributed to further apparent gap decreases in Hungary as compared to northern and Western European average. This trend stemmed from the increase in national HIHD between 1913 and 1925. Then, it correlated with the slowdown of transformation in the Northern and Western regions between 1925–1929. At the same time, it is also clear that in the Northern and Western European regions, the transformation of the quality of life was asserted with more unfavorable effects due to the recession (1929–1933) than in Hungary. The data also indicate that during the first half of the twentieth century, in 1938 the quality of life as a national average was the closest to the northern and Western European standard: while this average in 1870 was 54% of the former standard, and in 1913 was still just 64%, then in 1938, right before the outbreak of World War II, it took 81 percent. In addition, the “improvement” of national quality of life correlates or in other words relates with the central European processes, while as opposed to the southern- European status, it shows an acceleration in the speed of changes detouring the national quality of life into a favourable direction. Finally, from the perspective of Austria, it is essential to mention that in the decades right after the Austro-Hungarian Comprise, the quality of life shows more remarkable increases in Austria than in Hungary. Practically, Austria converged at an accelerating space towards the quality of life dictated by the northern and Western European countries, which it actually reached in 1929. From this point onwards, it advanced in complete correlation at the same level.

Conclusion

On the basis of our study, in the narrative of Carpathian Basin, the territory of post-Trianon Hungary was significantly more developed as compared to its surrounding regions. Even prior to the Treaty of Trianon, the break lines already existed, and the internal/peripheral regions had already emerged. As a result, the emergence of these gaps cannot be attributed to the consequences of Treaty of Trianon. The territorial inequalities related to quality of life owned remarkable features: the territory of the country was divided into a western region of the Danube and an eastern part of the Danube. It is essential to emphasize that although the Great Plain had a multi-centered development spatial structure as an agricultural region, it still ensured a sustainable basis for economic stability; and via the developed status of its center divisions it also ensured the balance of transition. These regions were the innovation centers that ensured the background to structure transition and to the temporary expansion of garden cultivation culture. The Treaty of Trianon has had serious consequences, but one must admit that it was not the Treaty of Trianon that resulted in the internal spatial structure which defined the developmental spatial potentials of Hungary for the rest of the twentieth century.

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APPENDIX

Changes in differences in the quality of life (HDI- Human Development Index) in Hungary after the Treaty of Trianon between 1910 and 1930

Remarks on the Table

Adapted details have been published based on the decreasing order of HDI records of 1930.

ID

Identification number. Consists of three parts (separated by periods). First part: processus/district (1) or town (2), second part: codes for a county in the Kingdom of Hungary (1–25), third part: the number for a processus/district or town within a county

The counties of Hungary in 1930: vm. = vármegye (county), keevm. = közigazgatásilag egyelőre egyesített vármegye (county administratively unified), MH 1933

01 =

Abaúj-Torna vm.

10 =

Győr, Moson és Pozsony keevm.

19 =

Szabolcs és Ung keevm.

02 =

Bács-Bodrog vm.

11 =

Hajdu vm.

20 =

Szatmár, Ugocsa és Bereg keevm.

03 =

Baranya vm.

12 =

Heves vm.

21 =

Tolna vm.

04 =

Békés vm.

13 =

Jász-Nagykun-Szolnok vm.

22 =

Vas vm.

05 =

Bihar vm.

14 =

Komárom és Esztergom keevm.

23 =

Veszprém vm.

06 =

Borsod, Gömör és Kishont keevm.

15 =

Nógrád és Hont keevm.

24 =

Zala vm.

07 =

Csanád, Arad és Torontál keevm.

16 =

Pest-Pilis-Solt-Kiskun vm.

25 =

Zemplén vm.

08 =

Csongrád vm.

17 =

Somogy vm.

 

 

09 =

Fejér vm.

18 =

Sopron vm.

 

 

 

A

j. = járás (district), rtv. = rendezett tanácsú város (corporate town), szfv. = székesfőváros (royal seat and capital), thjv. = törvényhatósági jogú város (municipal town).

B

1910–1930 HDI difference (100%=1910).

C

The country average of HDI in 1910 100%=0,451, while in 1930 100%=0,461

D

The difference between the relative positions of 1910 and 1930.

E

The direction of the change in position (+).

Sources for Tables

Databases: GHA, MÉTA

Statistical journals: AS 1934, KSH 1969, MH 1933, MSK Ús 39, 42, 46, 58, 83, 86, 93, 99 volume.

Own calculations and compositions.

*

 

HDI regional differences in the area of Hungary after the Treaty of Trianon broken down by processus and towns between 1910 and 1930

ID

Name of administrative unit

A

HDI

Compared to the average HDI (%)

Relative position (order)

E

1910

1930

B (%)

1910

1930

C

1910

1930

D

2.16.13

Budapest

szfv.

0.933

0.844

−9.55

206.78

183.27

−23.52

1

1

0

 

2.16.09

Rákospalota

rtv.

0.635

0.731

15.17

140.70

158.78

18.07

11

2

9

+

2.16.06

Kispest

rtv.

0.673

0.729

8.33

149.19

158.36

9.17

4

3

1

+

2.16.08

Pestszenterzsébet

rtv.

0.638

0.729

14.29

141.27

158.20

16.93

10

4

6

+

2.16.01

Budafok

rtv.

0.575

0.728

26.66

127.42

158.14

30.72

23

5

18

+

2.16.11

Újpest

rtv.

0.662

0.691

4.49

146.60

150.10

3.50

6

6

0

 

2.18.01

Sopron

thjv.

0.718

0.686

−4.40

159.04

148.98

−10.06

2

7

−5

 

2.14.02

Komárom

rtv.

0.633

0.676

6.69

140.32

146.69

6.37

12

8

4

+

2.10.02

Győr

thjv.

0.687

0.670

−2.50

152.31

145.51

−6.81

3

9

−6

 

2.22.01

Kőszeg

rtv.

0.653

0.636

−2.59

144.66

138.06

−6.60

7

10

−3

 

1.16.11

Központi (PPSK)

j.

0.552

0.617

11.85

122.20

133.93

11.73

29

11

18

+

2.22.02

Szombathely

rtv.

0.671

0.612

−8.84

148.74

132.85

−15.89

5

12

−7

 

2.09.01

Székesfehérvár

thjv.

0.623

0.603

−3.09

137.93

130.97

−6.96

13

13

0

 

2.23.01

Pápa

rtv.

0.644

0.602

−6.43

142.65

130.78

−11.86

9

14

−5

 

2.16.10

Szentendre

rtv.

0.449

0.588

30.94

99.48

127.63

28.15

108

15

93

+

2.06.01

Miskolc

thjv.

0.609

0.585

−3.99

134.95

126.96

−7.99

14

16

−2

 

1.18.01

Csepregi

j.

0.597

0.581

−2.57

132.22

126.23

−5.99

15

17

−2

 

1.22.03

Sárvári

j.

0.582

0.576

−1.07

129.06

125.10

−3.96

18

18

0

 

2.03.02

Pécs

thjv.

0.581

0.572

−1.50

128.70

124.22

−4.49

19

19

0

 

2.10.01

Magyaróvár

rtv.

0.572

0.571

−0.23

126.77

123.92

−2.85

24

20

4

+

1.22.05

Szombathelyi

j.

0.578

0.570

−1.28

127.99

123.80

−4.19

20

21

−1

 

2.16.12

Vác

rtv.

0.540

0.567

4.93

119.71

123.08

3.37

33

22

11

+

2.08.04

Szeged

thjv.

0.544

0.564

3.57

120.56

122.35

1.78

32

23

9

+

1.18.04

Soproni

j.

0.545

0.562

3.00

120.85

121.97

1.11

31

24

7

+

2.04.01

Békéscsaba

rtv.

0.393

0.562

43.06

86.99

121.94

34.95

158

25

133

+

1.10.01

Magyaróvári

j.

0.577

0.561

−2.76

127.83

121.80

−6.03

22

26

−4

 

1.24.02

Balatonfüredi

j.

0.571

0.557

−2.44

126.49

120.91

−5.58

25

27

−2

 

2.11.05

Debrecen

thjv.

0.644

0.557

−13.56

142.74

120.89

−21.85

8

28

−20

 

1.16.06

Gödöllői

j.

0.480

0.549

14.38

106.34

119.18

12.84

74

29

45

+

2.15.02

Salgótarján

rtv.

0.515

0.548

6.46

114.01

118.93

4.92

46

30

16

+

1.23.02

Enyingi

j.

0.584

0.545

−6.77

129.44

118.25

−11.20

17

31

−14

 

1.18.02

Csornai

j.

0.519

0.542

4.41

114.92

117.57

2.65

43

32

11

+

1.22.01

Celldömölki

j.

0.529

0.541

2.22

117.30

117.48

0.18

37

33

4

+

2.24.02

Zalaegerszeg

rtv.

0.595

0.541

−9.04

131.78

117.44

−14.33

16

34

−18

 

1.16.17

Váci

j.

0.524

0.541

3.12

116.15

117.37

1.21

39

35

4

+

1.10.04

Tósziget-csilizközi

j.

0.491

0.538

9.65

108.71

116.79

8.08

70

36

34

+

1.18.03

Kapuvári

j.

0.491

0.538

9.39

108.88

116.70

7.83

69

37

32

+

1.10.03

Sokoróaljai

j.

0.516

0.537

3.99

114.40

116.57

2.17

44

38

6

+

1.21.06

Völgységi

j.

0.530

0.536

1.19

117.44

116.44

−1.00

36

39

−3

 

2.23.02

Veszprém

rtv.

0.551

0.536

−2.59

121.99

116.42

−5.56

30

40

−10

 

2.13.05

Szolnok

rtv.

0.465

0.534

14.94

103.03

116.03

13.00

89

41

48

+

1.22.06

Vasvári

j.

0.505

0.531

5.29

111.82

115.36

3.54

53

42

11

+

1.14.02

Gesztesi

j.

0.504

0.527

4.66

111.58

114.42

2.84

56

43

13

+

1.22.02

Körmend–németújvári

j.

0.523

0.524

0.23

115.93

113.85

−2.08

40

44

−4

 

2.13.03

Kisújszállás

rtv.

0.577

0.523

−9.46

127.86

113.43

−14.43

21

45

−24

 

1.21.04

Simontornyai

j.

0.526

0.522

−0.72

116.45

113.28

−3.17

38

46

−8

 

2.14.01

Esztergom

rtv.

0.537

0.520

−3.19

118.91

112.80

−6.11

35

47

−12

 

1.14.03

Tatai

j.

0.475

0.518

9.04

105.31

112.52

7.21

78

48

30

+

1.03.01

Baranyavári

j.

0.505

0.516

2.26

111.80

112.02

0.22

54

49

5

+

2.13.04

Mezőtúr

rtv.

0.492

0.515

4.78

108.91

111.82

2.91

68

50

18

+

1.09.04

Székesfehérvári

j.

0.560

0.515

−8.03

124.08

111.81

−12.27

28

51

−23

 

1.21.01

Dombóvári

j.

0.500

0.515

2.98

110.78

111.77

1.00

59

52

7

+

1.16.07

Gyömrői

j.

0.462

0.512

10.73

102.44

111.14

8.70

92

53

39

+

1.23.04

Veszprémi

j.

0.483

0.510

5.52

107.08

110.71

3.63

73

54

19

+

1.04.04

Orosházi

j.

0.449

0.509

13.29

99.58

110.54

10.96

106

55

51

+

2.08.03

Hódmezővásárhely

thjv.

0.567

0.506

−10.82

125.59

109.75

−15.84

27

56

−29

 

1.04.05

Szarvasi

j.

0.510

0.504

−1.14

112.95

109.42

−3.53

48

57

−9

 

2.16.02

Cegléd

rtv.

0.497

0.502

1.04

110.09

108.99

−1.10

64

58

6

+

2.17.01

Kaposvár

rtv.

0.498

0.501

0.70

110.31

108.84

−1.47

61

59

2

+

1.16.13

Monori

j.

0.446

0.500

12.05

98.87

108.55

9.68

111

60

51

+

1.15.06

Szobi

j.

0.476

0.499

4.69

105.50

108.22

2.72

77

61

16

+

1.10.02

Pusztai

j.

0.466

0.497

6.68

103.23

107.90

4.67

88

62

26

+

1.09.05

Váli

j.

0.500

0.494

−1.17

110.68

107.18

−3.50

60

63

−3

 

1.17.09

Tabi

j.

0.540

0.494

−8.55

119.57

107.14

−12.43

34

64

−30

 

1.23.01

Devecseri

j.

0.496

0.493

−0.68

109.87

106.92

−2.94

66

65

1

+

1.08.03

Mindszenti

j.

0.399

0.492

23.31

88.45

106.86

18.42

153

66

87

+

2.24.01

Nagykanizsa

rtv.

0.519

0.492

−5.18

114.95

106.80

−8.15

41

67

−26

 

1.04.01

Békési

j.

0.461

0.489

6.14

102.14

106.22

4.09

94

68

26

+

1.06.06

Putnoki

j.

0.450

0.489

8.69

99.64

106.12

6.48

103

69

34

+

1.23.03

Pápai

j.

0.508

0.488

−4.08

112.64

105.86

−6.78

49

70

−21

 

2.07.01

Makó

rtv.

0.504

0.485

−3.79

111.62

105.22

−6.40

55

71

−16

 

1.21.05

Tamási

j.

0.501

0.483

−3.51

111.00

104.94

−6.06

58

72

−14

 

2.12.01

Eger

rtv.

0.429

0.483

12.78

94.96

104.94

9.98

124

73

51

+

1.04.02

Gyomai

j.

0.447

0.482

7.68

99.10

104.56

5.46

110

74

36

+

1.03.05

Pécsváradi

j.

0.479

0.481

0.42

106.08

104.38

−1.70

75

75

0

 

1.16.04

Biai

j.

0.462

0.479

3.82

102.33

104.09

1.76

93

76

17

+

1.16.16

Ráckevei

j.

0.477

0.476

−0.23

105.62

103.25

−2.37

76

77

−1

 

1.24.03

Keszthelyi

j.

0.470

0.475

1.01

104.23

103.17

−1.07

83

78

5

+

2.08.02

Szentes

rtv.

0.503

0.474

−5.64

111.38

102.98

−8.40

57

79

−22

 

1.03.03

Mohácsi

j.

0.450

0.473

5.26

99.65

102.78

3.13

102

80

22

+

2.11.04

Hajduszoboszló

rtv.

0.460

0.473

2.87

101.94

102.74

0.81

96

81

15

+

1.24.11

Zalaszentgróti

j.

0.464

0.473

1.96

102.77

102.68

−0.10

90

82

8

+

1.06.04

Miskolci

j.

0.463

0.473

2.18

102.55

102.67

0.12

91

83

8

+

1.24.09

Tapolcai

j.

0.452

0.473

4.56

100.18

102.63

2.46

99

84

15

+

1.09.03

Sárbogárdi

j.

0.487

0.473

−2.98

107.92

102.59

−5.33

71

85

−14

 

1.16.15

Pomázi

j.

0.428

0.472

10.41

94.73

102.49

7.76

125

86

39

+

2.19.01

Nyíregyháza

rtv.

0.472

0.472

0.00

104.47

102.36

−2.11

81

87

−6

 

1.11.02

Püspökladányi

j.

0.467

0.471

0.96

103.40

102.29

−1.11

87

88

−1

 

1.17.05

Lengyeltóti

j.

0.449

0.471

4.73

99.54

102.15

2.61

107

89

18

+

1.16.05

Dunavecsei

j.

0.495

0.470

−5.03

109.73

102.11

−7.63

67

90

−23

 

2.16.07

Nagykőrös

rtv.

0.512

0.470

−8.23

113.41

101.98

−11.44

47

91

−44

 

1.24.08

Sümegi

j.

0.452

0.470

3.98

100.05

101.93

1.89

100

92

8

+

1.07.05

Torontáli

j.

0.356

0.469

31.79

78.84

101.81

22.97

169

93

76

+

1.21.03

Központi (Tolna)

j.

0.515

0.469

−9.07

114.16

101.72

−12.44

45

94

−49

 

1.09.02

Móri

j.

0.421

0.467

10.86

93.25

101.29

8.04

137

95

42

+

1.17.02

Csurgói

j.

0.506

0.464

−8.24

112.02

100.71

−11.31

52

96

−44

 

1.17.03

Igali

j.

0.485

0.464

−4.33

107.42

100.70

−6.72

72

97

−25

 

1.22.04

Szentgotthárd–muraszombati

j.

0.445

0.464

4.21

98.55

100.63

2.08

113

98

15

+

1.09.01

Adonyi

j.

0.450

0.462

2.50

99.80

100.24

0.44

101

99

2

+

1.24.07

Pacsai

j.

0.415

0.458

10.24

91.95

99.32

7.37

142

100

42

+

1.23.05

Zirci

j.

0.427

0.457

6.91

94.65

99.15

4.50

127

101

26

+

1.24.10

Zalaegerszegi

j.

0.443

0.454

2.51

98.08

98.51

0.43

115

102

13

+

2.13.02

Karcag

rtv.

0.568

0.452

−20.45

125.79

98.04

−27.75

26

103

−77

 

1.17.06

Marcali

j.

0.475

0.451

−4.91

105.20

98.01

−7.19

79

104

−25

 

1.24.05

Nagykanizsai

j.

0.443

0.451

1.76

98.25

97.96

−0.29

114

105

9

+

1.24.06

Novai

j.

0.394

0.450

14.37

87.24

97.77

10.53

157

106

51

+

1.05.01

Berettyóújfalusi

j.

0.427

0.450

5.39

94.62

97.71

3.09

128

107

21

+

2.16.03

Kalocsa

rtv.

0.471

0.450

−4.45

104.34

97.69

−6.65

82

108

−26

 

1.15.01

Balassagyarmati

j.

0.461

0.450

−2.39

102.12

97.66

−4.46

95

109

−14

 

1.07.03

Központi (CsAT)

j.

0.421

0.450

6.72

93.38

97.64

4.26

136

110

26

+

2.11.03

Hajdunánás

rtv.

0.496

0.449

−9.39

109.90

97.58

−12.33

65

111

−46

 

1.05.05

Sárréti

j.

0.412

0.449

8.94

91.27

97.42

6.15

146

112

34

+

1.14.01

Esztergomi

j.

0.425

0.447

5.26

94.13

97.08

2.95

131

113

18

+

1.01.04

Szikszói

j.

0.445

0.446

0.18

98.61

96.79

−1.81

112

114

−2

 

1.15.02

Nógrádi

j.

0.450

0.444

−1.16

99.62

96.47

−3.14

104

115

−11

 

1.01.05

Tornai

j.

0.450

0.444

−1.16

99.60

96.46

−3.14

105

116

−11

 

1.17.07

Nagyatádi

j.

0.473

0.444

−6.13

104.71

96.31

−8.40

80

117

−37

 

1.17.01

Barcsi

j.

0.470

0.443

−5.83

104.13

96.09

−8.04

84

118

−34

 

1.03.02

Hegyháti

j.

0.439

0.442

0.65

97.36

96.01

−1.35

120

119

1

+

1.03.07

Szentlőrinci

j.

0.497

0.441

−11.27

110.11

95.73

−14.37

63

120

−57

 

1.06.07

Sajószentpéteri

j.

0.441

0.440

−0.27

97.67

95.44

−2.23

117

121

−4

 

1.06.05

Ózdi

j.

0.417

0.437

5.02

92.29

94.97

2.68

139

122

17

+

1.21.02

Dunaföldvári

j.

0.427

0.434

1.54

94.70

94.22

−0.48

126

123

3

+

1.17.04

Kaposvári

j.

0.454

0.434

−4.39

100.51

94.16

−6.35

97

124

−27

 

2.02.01

Baja

thjv.

0.453

0.433

−4.36

100.26

93.95

−6.31

98

125

−27

 

1.15.05

Sziráki

j.

0.405

0.432

6.84

89.69

93.89

4.20

149

126

23

+

1.05.04

Derecskei

j.

0.469

0.432

−7.81

103.91

93.86

−10.04

86

127

−41

 

2.25.01

Sátoraljaújhely

rtv.

0.497

0.432

−13.08

110.16

93.82

−16.34

62

128

−66

 

1.04.06

Szeghalmi

j.

0.413

0.432

4.46

91.54

93.70

2.16

144

129

15

+

1.16.03

Aszódi

j.

0.398

0.431

8.18

88.22

93.51

5.29

155

130

25

+

2.03.01

Mohács

rtv.

0.422

0.430

1.87

93.52

93.35

−0.18

135

131

4

+

1.25.04

Tokaji

j.

0.415

0.428

2.92

92.05

92.82

0.78

141

132

9

+

1.01.01

Abaújszántói

j.

0.414

0.426

2.97

91.74

92.56

0.82

143

133

10

+

2.08.01

Csongrád

rtv.

0.334

0.426

27.60

74.00

92.52

18.52

176

134

42

+

1.16.08

Kalocsai

j.

0.448

0.425

−5.14

99.22

92.22

−7.00

109

135

−26

 

1.01.03

Gönci

j.

0.398

0.423

6.11

88.26

91.76

3.50

154

136

18

+

2.12.02

Gyöngyös

rtv.

0.274

0.421

53.76

60.64

91.37

30.72

194

137

57

+

1.24.01

Alsólendvai

j.

0.508

0.420

−17.20

112.48

91.26

−21.22

50

138

−88

 

1.16.09

Kiskőrösi

j.

0.387

0.420

8.57

85.69

91.15

5.46

159

139

20

+

1.16.12

Kunszentmiklósi

j.

0.416

0.418

0.62

92.15

90.85

−1.30

140

140

0

 

1.13.03

Központi (JNSz)

j.

0.372

0.418

12.55

82.37

90.84

8.46

164

141

23

+

1.03.04

Pécsi

j.

0.438

0.417

−4.77

97.09

90.59

−6.49

121

142

−21

 

1.17.08

Szigetvári

j.

0.423

0.417

−1.38

93.67

90.52

−3.16

133

143

−10

 

1.13.04

Tiszai alsó

j.

0.417

0.416

−0.21

92.46

90.40

−2.05

138

144

−6

 

1.05.02

Biharkeresztesi

j.

0.425

0.415

−2.48

94.24

90.05

−4.19

130

145

−15

 

1.06.02

Mezőcsáti

j.

0.409

0.415

1.37

90.61

90.00

−0.61

147

146

1

+

1.03.06

Siklósi

j.

0.519

0.414

−20.10

114.92

89.97

−24.95

42

147

−105

 

1.05.03

Cséffa-nagyszalontai

j.

0.413

0.413

0.03

91.52

89.70

−1.82

145

148

−3

 

2.16.14

Kecskemét

thjv.

0.423

0.412

−2.61

93.81

89.52

−4.29

132

149

−17

 

1.02.03

Jánoshalmi

j.

0.422

0.412

−2.36

93.58

89.52

−4.05

134

150

−16

 

1.07.01

Battonyai

j.

0.383

0.412

7.77

84.77

89.51

4.74

160

151

9

+

1.15.04

Szécsényi

j.

0.380

0.412

8.55

84.13

89.48

5.35

161

152

9

+

1.02.02

Bajai

j.

0.404

0.411

1.65

89.52

89.16

−0.36

150

153

−3

 

2.13.06

Túrkeve

rtv.

0.439

0.410

−6.64

97.37

89.07

−8.30

119

154

−35

 

1.25.03

Szerencsi

j.

0.432

0.409

−5.35

95.73

88.77

−6.95

123

155

−32

 

1.16.02

Alsódabasi

j.

0.371

0.407

9.67

82.28

88.41

6.13

165

156

9

+

2.15.01

Balassagyarmat

rtv.

0.442

0.404

−8.54

97.87

87.70

−10.17

116

157

−41

 

1.01.02

Encsi

j.

0.406

0.403

−0.88

90.00

87.41

−2.59

148

158

−10

 

1.07.04

Mezőkovácsházi

j.

0.301

0.398

32.25

66.68

86.41

19.73

191

159

32

+

1.04.03

Gyulai

j.

0.302

0.397

31.52

66.81

86.10

19.29

189

160

29

+

1.16.01

Abonyi

j.

0.341

0.396

15.96

75.65

85.96

10.31

175

161

14

+

1.12.03

Hatvani

j.

0.365

0.395

8.18

80.93

85.79

4.85

167

162

5

+

1.12.06

Tiszafüredi

j.

0.427

0.393

−7.81

94.52

85.38

−9.14

129

163

−34

 

1.06.03

Mezőkövesdi

j.

0.354

0.391

10.21

78.52

84.80

6.27

171

164

7

+

1.12.02

Gyöngyösi

j.

0.347

0.390

12.19

76.97

84.61

7.64

174

165

9

+

1.06.01

Edelényi

j.

0.404

0.388

−3.95

89.49

84.22

−5.27

151

166

−15

 

2.11.01

Hajduböszörmény

rtv.

0.507

0.388

−23.60

112.38

84.13

−28.25

51

167

−116

 

1.15.03

Salgótarjáni

j.

0.311

0.381

22.29

68.98

82.65

13.68

184

168

16

+

1.25.02

Sárospataki

j.

0.348

0.377

8.49

77.07

81.93

4.86

173

169

4

+

1.12.01

Egri

j.

0.326

0.377

15.80

72.13

81.84

9.71

179

170

9

+

1.02.01

Bácsalmási

j.

0.398

0.376

−5.42

88.12

81.66

−6.46

156

171

−15

 

1.13.06

Tiszai közép

j.

0.372

0.375

0.76

82.45

81.40

−1.05

163

172

−9

 

1.13.02

Jászsági felső

j.

0.314

0.370

17.87

69.49

80.25

10.76

183

173

10

+

1.13.05

Tiszai felső

j.

0.400

0.368

−8.10

88.66

79.84

−8.82

152

174

−22

 

1.08.01

Csongrádi

j.

0.239

0.368

53.61

53.04

79.83

26.79

201

175

26

+

1.13.01

Jászsági alsó

j.

0.355

0.367

3.24

78.69

79.60

0.91

170

176

−6

 

1.16.14

Nagykátai

j.

0.264

0.366

38.36

58.59

79.43

20.84

197

177

20

+

1.20.02

Fehérgyarmati

j.

0.373

0.363

−2.73

82.68

78.80

−3.88

162

178

−16

 

1.20.04

Vásárosnaményi

j.

0.320

0.361

12.93

70.90

78.45

7.55

181

179

2

+

1.24.04

Letenyei

j.

0.357

0.361

1.10

79.09

78.35

−0.74

168

180

−12

 

2.11.02

Hajduhadház

rtv.

0.440

0.360

−18.09

97.40

78.17

−19.23

118

181

−63

 

1.19.01

Dadai alsó

j.

0.366

0.358

−2.11

81.10

77.79

−3.31

166

182

−16

 

2.21.01

Szekszárd

rtv.

0.469

0.357

−23.99

103.99

77.45

−26.54

85

183

−98

 

2.04.02

Gyula

rtv.

0.318

0.355

11.56

70.46

77.01

6.56

182

184

−2

 

2.16.05

Kiskunhalas

rtv.

0.434

0.354

−18.56

96.20

76.77

−19.43

122

185

−63

 

1.07.02

Eleki

j.

0.311

0.349

12.18

68.85

75.69

6.83

185

186

−1

 

2.13.01

Jászberény

rtv.

0.333

0.348

4.77

73.68

75.64

1.96

177

187

−10

 

1.16.10

Kiskunfélegyházi

j.

0.267

0.345

29.03

59.20

74.84

15.64

196

188

8

+

2.16.04

Kiskunfélegyháza

rtv.

0.270

0.343

26.79

59.85

74.36

14.51

195

189

6

+

1.25.01

Bodrogközi

j.

0.320

0.338

5.39

70.98

73.30

2.32

180

190

−10

 

1.20.01

Csengeri

j.

0.301

0.337

11.88

66.66

73.07

6.41

192

191

1

+

1.05.06

Székelyhidi

j.

0.332

0.334

0.52

73.65

72.55

−1.11

178

192

−14

 

1.08.02

Kiskundorozsma

j.

0.301

0.333

10.39

66.78

72.23

5.45

190

193

−3

 

1.12.04

Hevesi

j.

0.354

0.332

−6.19

78.36

72.03

−6.34

172

194

−22

 

1.11.01

Központi (Hajdu)

j.

0.310

0.331

7.03

68.60

71.94

3.34

186

195

−9

 

1.19.02

Dadai felső

j.

0.302

0.331

9.48

66.93

71.80

4.86

188

196

−8

 

1.12.05

Pétervásári

j.

0.253

0.325

28.49

56.06

70.57

14.52

199

197

2

+

1.19.09

Tiszai

j.

0.306

0.294

−4.07

67.91

63.83

−4.08

187

198

−11

 

1.19.03

Kisvárdai

j.

0.290

0.275

−5.01

64.22

59.77

−4.45

193

199

−6

 

1.19.07

Nyírbátori

j.

0.225

0.255

13.64

49.81

55.46

5.65

203

200

3

+

1.20.03

Mátészalkai

j.

0.256

0.251

−1.80

56.72

54.58

−2.14

198

201

−3

 

1.19.08

Nyírbogdányi

j.

0.220

0.240

9.02

48.82

52.15

3.33

204

202

2

+

1.19.05

Nagykállói

j.

0.240

0.210

−12.39

53.17

45.64

−7.53

200

203

−3

 

1.19.06

Nyírbaktai

j.

0.226

0.209

−7.58

50.10

45.37

−4.73

202

204

−2

 

1.19.04

Ligetaljai

j.

0.148

0.149

0.86

32.71

32.32

−0.38

205

205

0

 

 

1 Quoted by Kidd and Nicholls, Introduction, xxi.

2 Benda, Zsellérből polgár; Novák, “Az erőszak topográfiája;” Kövér, A tiszaeszlári dráma;” Majorossy, “A foglalkozás;” Szilágyi, Homokváros.

3 Soja, Postmodern Geographies; Warf and Arias, The Spacial Turn; Szilágyi, “A társadalmi tér;” Izsák, “A tértudás;” Izsák and Dúll, “Városi térfordulatok.”

4 Győri, “Területi fejlettségi.”

5 Győri, “A térszerkezet.”

6 Győri, “Területi fejlettségi,” 233.

7 Human Development Report 1990, 109.

8 Hicks and Sreeten.

9 According to Farhad Noorbakhsh, GNP, the specific indicator (of measuring standard of living), was commonly adopted following a recommendation included in a UN report in 1954. Noorbakhsh, “A Modified Human,” 517.

10 Human Development Report 1990, 109.

11 Ibid.; Nemes Nagy, Terek, helyek, 301–05. Tomka, Gazdasági növekedés, 187–94.

12 OTKA K 111766: Implementation of geoinformatical system to execute research on the history of Hungary and the Austro–Hungarian Monarchy (1869–1910).

13 Beluszky, “Egy félsiker.”

14 Beluszky and Győri, Magyar városhálózat, 85–86.

15 Beluszky, A Nagyalföld történeti földrajza; Szilágyi, “A fejlettség területi különbségei.”.

16 Timár, Vidéki városlakók, 21; Beluszky, “Kárpát-medence országrészeinek,” 348; Beluszky, A Nagyalföld történeti földrajza, 239; Beluszky and Győri, Magyar városhálózat, 85.

17 Beluszky and Győri, Magyar városhálózat, 87; Beluszky, “Kárpát-medence országrészeinek,” 354.

18 Pénzes, Periférikus térségek, 14–18.

19 Demeter, “Történeti kérdések földrajzi szemszögből,” 30.

20 Tomka, “Gazdasági rekonstrukció;” Pogány, “A nagy háború hosszú árnyéka.”

21 177.200/1924 BM (Ministry of Interior), MSK Ús vol. 93: 14*.

22 100/1927 PM (Ministry of Finances), 10,000/1927, 1929-23-1§; 200/1927 PM, 20,000/1927 1929-2§, 1929-29§, 1390/1933 ME 1§; 400/1927 PM, 40,000/1927, 2030/1932 ME 6–10§, 1390/1933 ME 2§, 2600/1933 ME 4–6§. AS 1934: 49, 75, 147.

23 VE=S/X×100, where variation is indicated via S, average is indicated via X. Csite and Németh, Az életminőség területi, 31–38.

24 Crafts, The Human Development Index.

25 Tomka, Gazdasági növekedés, 199.

26 Prados, “Improving the Human Development Index.”

* Supported by the ÚNKP-17-4-III-DE-187 New National Excellence Program of the Ministry of Human Capacities.

hhr-fig-01.jpg
hhr-fig-02.jpg
végleges-600dpi -- HDI 1910-30 c.jpg
végleges-600dpi -- HDI 1910-30 különbség.jpg
végleges - konverg-diverg - 1910-30.jpg
végleges - településsűrűség - 1933.jpg
végleges - településsűrűség - 1933.jpg
végleges - településsűrűség - 1933.jpg

Figure 8. Changes in HIHD in Hungary based on the comparison of international data,
1870–1950
Source: WHD 1870–2015, own editing.

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