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The quality and representativeness of longitudinal datasets play a central role in historical migration research. In this study, we apply the child-ladder (CL) method to a population-scale family tree dataset to analyze U.S. interstate family migration from 1850 to 1920. The CL method infers moves from changes in birthplaces between successive children, allowing for more precise dating of migration events. However, it is limited to families with at least two children. To evaluate the representativeness and utility of family trees for migration research, we compare the CL data to the IPUMS Multigenerational Longitudinal Panel (MLP), which tracks household moves across census decades and serves as a proxy for broader population migration. The CL data reveal higher migration rates, suggesting a likely closer approximation to migration levels in the overall population. Also, by capturing intercensal and return migrations, the CL method provide a detailed view of migration patterns across space and time. Despite differences in migration rates, both datasets reveal similar regional migration structures, especially in the earlier periods. These findings show that population-scale family trees when analyzed using the CL method, offer a valuable complement to linked census data by enhancing our understanding of long-term U.S. migration patterns and regional divisions.more » « lessFree, publicly-accessible full text available July 3, 2026
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Koylu, Caglar; Torkashvand, Maryam; Kwon, Hoeyun; Kasakoff, Alice Bee (, Proceedings of the 6th ACM SIGSPATIAL International Workshop on Geospatial Humanities)Moncla, Ludovic; Martins, Bruno; McDonough, Katherine (Ed.)Using a population-scale family tree dataset, this paper proposes a study of migration regions and their evolution in the U.S. between 1789 and 1924. To extract migration events, we use the child ladder approach, which traces family moves based on changes in birthplaces of consecutive children in each individual family. We calculate a time series measure of migration rate and partition the time into optimal periods so that each period has a distinct migration network. We apply community detection to derive migration regions from each network of different periods. We map these regions and use a pair-counting measure to statistically compare the similarity of regions in consecutive time periods. Migration regions reveal the extent to which the strong regional identities we see today, and, in the past, which were rooted in migration. The North/South divide was pervasive not only in the early periods but throughout U.S. history. Migration regions are important for understanding the development of regional and national cultural forms such as music, literature, foodways, and dialects, as well as political divisions and events.more » « less
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