Reclaiming Lost Data on American Racial Inequality, 1865-1940
We seek to produce a Big-Data genealogy of the African-American past by combining algorithmic linking techniques with historical and genealogical methods. We propose to draw on the development of machine-learning algorithms to link individual census records over time with idiosyncratic data sources such as letters, marriage records, church registries, and oral histories.
Support from the Russell Sage Foundation has allowed us to develop new methods for linking historical data using rarely consulted types of historical evidence. This proposal is rooted on the idea that in order to link marginalized groups often excluded or missed from official tabulations, we need to rely on additional sources of historical and genealogical information.
INCITE is collaborating with researchers at the University of California-Berkeley, Harvard University, The Ohio State University, and the University of Washington for this project.
Peter Bearman, Columbia
Mara Loveman, UC Berkeley
Erick Shickler, UC Berkeley
Christopher Muller, UC Berkeley
Suresh Naidu, Columbia
James Feigenbaum, Boston University