title: Population relationships by isonymy in frontier Pennsylvania.
abstract: Data from the 1800 US census were used to study relationships by isonymy among 7 civil subdivisions of Bedford County, Pennsylvania. Two analyses of the data were conducted. In the first analysis heads of household served as the unit of analysis. In the second analysis the total number of individuals in each household was used to correct for varying family sizes. All measures of internal differentiation were approximately doubled when the complete population numbers were used. The head-of-household analysis produced FST and RST values of 0.0012 and 0.0007, respectively; the complete population analysis yielded 0.0021 for FST and 0.0015 for RST. Interpopulation a priori kinship estimations were similar using both methods. Conditional kinship estimations varied more, with almost all values negative, but the head-of-household estimates were less negative. Multidimensional scaling of isonymy values coincided fairly well with actual geographic relationships, but a Mantel test revealed no significant relationship between geographic distances and isonymy, and isolation by distance values indicated a low relationship between the 2 measures. The population of the county was heterogeneous, with low kinship between its constituent communities. This appears to be a result of kin-structured long-distance migration rather than of local processes. The head-of-household values are more comparable with other studies and more representative of population relationships; complete population values exaggerate heterogeneity because of random fluctuations in household size.
authors.affiliation: Department of History and Anthropology, Augusta State University, GA 30904-2200, USA.
authors.forename: A F
authors.initials: AF
authors.lastname: Christensen
mesh_terms: D004641:Emigration and Immigration / Q000266:history*; D005260:Female; D049673:History, 20th Century; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009275:Names; D010414:Pennsylvania; D011159:Population Surveillance