Demeter, Gábor – Bagdi, Róbert
Tracing the transforming urban elite and methods to analyze spatia... more Demeter, Gábor – Bagdi, Róbert Tracing the transforming urban elite and methods to analyze spatial patterns, social composition and wealth based on census data (NE-Hungary, 1870) This contribution attempts to outline methods that (1) can help identify the elite in urban societies as well as (2) analyze its spatial pattern, (3) social composition and welfare in the 19th c. Our research was based on the census data of 1870. The census of 1870 is a specific one in the sense, that the original household-level data sheets survived in some of the towns and villages, making it possible to carry out a more detailed inquiry (figure 1) compared to the material published officially, which aggregated data at settlement-level. The original census sheets contained the name, age, address, birth place, occupation and religion of the head of family, repeating these data for the wife, children, co-workers, servants and housemaids. It also provided the number of rooms, kitchens, economic buildings (stores, stables, cellars) for each household. As the census did not contain income data, the mentioned variables could also serve as a basis for the classification of groups regarding their wealth. These data were used in order to identify the elite and classify population into social layers. The selection of Sátoraljaújhely (the county seat of Zemplén County) as a sample area was ideal from several aspects. The 2150 households (10 000 inhabitants) offered substantial material for quantitative statistical analysis, and the timing itself was also fortunate. The railway was just opened in 1870, while guilds were dissolved in 1872, thus the parallel coexistence of traditional and modern social patterns and structures were also observable owing to the date of conscription. The acceleration of urbanization process made a melting pot from the town reflected in its religious diversity: 35% of the population was Jewish of origin, Roman catholics reached also 30%, Calvinist protestants 12-14%, Greek Catholics approximately 20%. We used 3 different methods to trace the elite(s). Besides the traditional classification based on the the prestige of occupation (Weber, Erdei) to identify groups, multivariate statistics (SPSS) were used for the other two classifications (cluster analysis, equation). Beside socio-demographic features (including inter-group and within-group differences), the spatial pattern of the location of the elite was also investigated using GIS (ArcGIS 10.1).
Demeter, Gábor – Bagdi, Róbert
Tracing the transforming urban elite and methods to analyze spatia... more Demeter, Gábor – Bagdi, Róbert Tracing the transforming urban elite and methods to analyze spatial patterns, social composition and wealth based on census data (NE-Hungary, 1870) This contribution attempts to outline methods that (1) can help identify the elite in urban societies as well as (2) analyze its spatial pattern, (3) social composition and welfare in the 19th c. Our research was based on the census data of 1870. The census of 1870 is a specific one in the sense, that the original household-level data sheets survived in some of the towns and villages, making it possible to carry out a more detailed inquiry (figure 1) compared to the material published officially, which aggregated data at settlement-level. The original census sheets contained the name, age, address, birth place, occupation and religion of the head of family, repeating these data for the wife, children, co-workers, servants and housemaids. It also provided the number of rooms, kitchens, economic buildings (stores, stables, cellars) for each household. As the census did not contain income data, the mentioned variables could also serve as a basis for the classification of groups regarding their wealth. These data were used in order to identify the elite and classify population into social layers. The selection of Sátoraljaújhely (the county seat of Zemplén County) as a sample area was ideal from several aspects. The 2150 households (10 000 inhabitants) offered substantial material for quantitative statistical analysis, and the timing itself was also fortunate. The railway was just opened in 1870, while guilds were dissolved in 1872, thus the parallel coexistence of traditional and modern social patterns and structures were also observable owing to the date of conscription. The acceleration of urbanization process made a melting pot from the town reflected in its religious diversity: 35% of the population was Jewish of origin, Roman catholics reached also 30%, Calvinist protestants 12-14%, Greek Catholics approximately 20%. We used 3 different methods to trace the elite(s). Besides the traditional classification based on the the prestige of occupation (Weber, Erdei) to identify groups, multivariate statistics (SPSS) were used for the other two classifications (cluster analysis, equation). Beside socio-demographic features (including inter-group and within-group differences), the spatial pattern of the location of the elite was also investigated using GIS (ArcGIS 10.1).
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Tracing the transforming urban elite and methods to analyze spatial patterns, social composition and wealth based on census data (NE-Hungary, 1870)
This contribution attempts to outline methods that (1) can help identify the elite in urban societies as well as (2) analyze its spatial pattern, (3) social composition and welfare in the 19th c. Our research was based on the census data of 1870.
The census of 1870 is a specific one in the sense, that the original household-level data sheets survived in some of the towns and villages, making it possible to carry out a more detailed inquiry (figure 1) compared to the material published officially, which aggregated data at settlement-level. The original census sheets contained the name, age, address, birth place, occupation and religion of the head of family, repeating these data for the wife, children, co-workers, servants and housemaids. It also provided the number of rooms, kitchens, economic buildings (stores, stables, cellars) for each household. As the census did not contain income data, the mentioned variables could also serve as a basis for the classification of groups regarding their wealth. These data were used in order to identify the elite and classify population into social layers.
The selection of Sátoraljaújhely (the county seat of Zemplén County) as a sample area was ideal from several aspects. The 2150 households (10 000 inhabitants) offered substantial material for quantitative statistical analysis, and the timing itself was also fortunate. The railway was just opened in 1870, while guilds were dissolved in 1872, thus the parallel coexistence of traditional and modern social patterns and structures were also observable owing to the date of conscription. The acceleration of urbanization process made a melting pot from the town reflected in its religious diversity: 35% of the population was Jewish of origin, Roman catholics reached also 30%, Calvinist protestants 12-14%, Greek Catholics approximately 20%.
We used 3 different methods to trace the elite(s). Besides the traditional classification based on the the prestige of occupation (Weber, Erdei) to identify groups, multivariate statistics (SPSS) were used for the other two classifications (cluster analysis, equation). Beside socio-demographic features (including inter-group and within-group differences), the spatial pattern of the location of the elite was also investigated using GIS (ArcGIS 10.1).
Tracing the transforming urban elite and methods to analyze spatial patterns, social composition and wealth based on census data (NE-Hungary, 1870)
This contribution attempts to outline methods that (1) can help identify the elite in urban societies as well as (2) analyze its spatial pattern, (3) social composition and welfare in the 19th c. Our research was based on the census data of 1870.
The census of 1870 is a specific one in the sense, that the original household-level data sheets survived in some of the towns and villages, making it possible to carry out a more detailed inquiry (figure 1) compared to the material published officially, which aggregated data at settlement-level. The original census sheets contained the name, age, address, birth place, occupation and religion of the head of family, repeating these data for the wife, children, co-workers, servants and housemaids. It also provided the number of rooms, kitchens, economic buildings (stores, stables, cellars) for each household. As the census did not contain income data, the mentioned variables could also serve as a basis for the classification of groups regarding their wealth. These data were used in order to identify the elite and classify population into social layers.
The selection of Sátoraljaújhely (the county seat of Zemplén County) as a sample area was ideal from several aspects. The 2150 households (10 000 inhabitants) offered substantial material for quantitative statistical analysis, and the timing itself was also fortunate. The railway was just opened in 1870, while guilds were dissolved in 1872, thus the parallel coexistence of traditional and modern social patterns and structures were also observable owing to the date of conscription. The acceleration of urbanization process made a melting pot from the town reflected in its religious diversity: 35% of the population was Jewish of origin, Roman catholics reached also 30%, Calvinist protestants 12-14%, Greek Catholics approximately 20%.
We used 3 different methods to trace the elite(s). Besides the traditional classification based on the the prestige of occupation (Weber, Erdei) to identify groups, multivariate statistics (SPSS) were used for the other two classifications (cluster analysis, equation). Beside socio-demographic features (including inter-group and within-group differences), the spatial pattern of the location of the elite was also investigated using GIS (ArcGIS 10.1).