Сравнение на методи

	Family Reconstitution	Historical Nominal Record Linkage
Област	Historical Demography	Historical Demography
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1956	2016
Създател	Louis Henry and Michel Fleury; refined by E. A. Wrigley and R. S. Schofield (Cambridge Group)	Ivan Fellegi and Alan Sunter (probabilistic theory); James Feigenbaum, Ran Abramitzky, Leah Boustan (historical ML methods)
Тип	Nominative record-linkage and demographic estimation	measurement-linkage
Основополагащ източник	Wrigley, E. A., Davies, R. S., Oeppen, J. E., & Schofield, R. S. (1997). English Population History from Family Reconstitution 1580-1837. Cambridge University Press. ISBN: 9780521590150	Abramitzky, R., Boustan, L., Eriksson, K., Feigenbaum, J., & Perez, S. (2021). Automated Linking of Historical Data. Journal of Economic Literature, 59(3), 865-918.
Други названия	Parish register reconstitution, Nominative family linkage, Henry-Fleury method, Cambridge Group reconstitution	Record linkage, Census linking, Fellegi-Sunter matching, Historical individual linkage
Свързани	4	3
Резюме	Family reconstitution is the nominative technique that rebuilds the demographic experience of historical communities by linking individual baptism, marriage and burial entries from parish registers into the reproductive and mortality histories of identifiable families. Developed by Louis Henry and Michel Fleury in 1950s France and brought to its fullest expression by the Cambridge Group for the History of Population and Social Structure under Wrigley and Schofield, the method transforms an undifferentiated stream of vital events into Family Reconstitution Forms, each documenting a marriage, the births of children, and the deaths of family members. From these forms the analyst derives age-specific fertility, age at marriage, birth intervals, infant and child mortality, and adult survivorship. Because it works at the individual level it can isolate demographic behaviours—such as spacing or stopping—invisible to aggregate counts, making it the gold standard for pre-census population history.	Historical nominal record linkage is the task of recognising when records in different sources, two censuses, a census and a draft register, a baptism and a marriage, refer to the same person, even though no shared identifier exists and names are misspelled, ages misreported, and places renamed. Linkage is the engine behind longitudinal historical micro-data: it builds the life-course panels that underpin studies of migration, mobility, mortality, and the long-run effects of early-life conditions. Three families of methods dominate. Deterministic linkage applies hand-crafted rules; the probabilistic Fellegi-Sunter framework weights field agreements and disagreements by their discriminating power; and supervised machine learning, trained on hand-linked examples, learns to classify candidate pairs. Modern historical practice, led by Abramitzky, Boustan, Feigenbaum, and collaborators, emphasises transparent, replicable algorithms and, crucially, explicit measurement of linkage error, since false matches and missed links can bias every downstream estimate.