GENPOP SIGNED

Project "GENPOP" data sheet

The following table provides information about the project.

 Partnership

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 Project objective

This is the first comprehensive study that combines historical and contemporaneous data to understand how population processes evolve via three interrelated channels: (1) multigenerational transmission, (2) assortative mating and (3) migration. Existing research focuses on recent factors to explain contemporaneous population trends, missing the long-view of demographic changes. As population processes (fertility and mortality) evolve slowly across generations, we urgently need to adopt a long-term perspective to comprehend demographic phenomena and design effective policies. I address this need by using newly available data on internet-based genealogies, micro-census data and genetics, to investigate long-term population processes in family networks. Building on my previous research on demography and genetics, I first develop a new theoretical model of transmission of differential fertility and mortality in family networks. Second, I examine diversity between and within families and its persistence across generations. Third, I use innovative Big Data from genealogy social networks and micro-census data to understand the long-term effect of migration on multiple generations. Fourth, I describe the long-term patterns of assortative mating combining data from genetics and genealogy. This project will infuse new data linkages and produce methodological development in the use of Big Data in demography and beyond. The project will focus on the historical period from approximately 1800 until now in Europe and United States, a period of dramatic demographic and epidemiological changes that radically transformed our societies. This transdisciplinary project will overturn established links and deliver major breakthroughs in our understanding of demographic change. This project is not only ground breaking by setting a new research agenda, but due to the inclusion of genealogy data and their linkage with micro-census data, will yield major innovations in social sciences.