Full Citation
Title: Special issue introduction: IPUMS USA Full Count Census Data Collection
Citation Type: Journal Article
Publication Year: 2025
ISBN:
ISSN: 19401906
DOI: 10.1080/01615440.2025.2577530
NSFID:
PMCID:
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Abstract: In 1995–30 years ago–Historical Methods published the first of several special issues describing new and updated data collections available from the University of Minnesota (Vol 28:1–2). IPUMS was a novel dataset delivering U.S. microdata files from ten census years–spanning more than 100 years–using the same coding schemes and record layouts. In the subsequent years, IPUMS expanded to include more U.S. censuses and population, health and labor surveys and aggregate geographic data from around the world. For this special issue of Historical Methods, we focus on the U.S. historical census data collection at IPUMS. The 1995 special issue described efforts to create new 1% public use samples for the U.S. censuses of 1850, 1880 and 1920. In the last thirty years, the world–and scale–of historical microdata has been completely transformed: IPUMS historical census microdata now encompasses all respondents from the U.S. censuses of 1850 to 1950. These new datasets are available through collaborations with the world’s largest genealogical organizations–FamilySearch and Ancestry–who have donated transcriptions used for genealogical services and partnered with us to transcribe nearly every field on the census enumeration forms. These massive datasets pose new challenges for data production but also hold tremendous opportunity for innovative new research. We provide a short update on IPUMS below and then an overview of this special issue.
Url: https://www.tandfonline.com/doi/pdf/10.1080/01615440.2025.2577530
Url: https://doi.org/10.1080/01615440.2025.2577530
User Submitted?: No
Authors: Fitch, Catherine A.; Magnuson, Diana L.
Periodical (Full): Historical Methods: A Journal of Quantitative and Interdisciplinary History
Issue: 4
Volume: 58
Pages: 195-198
Data Collections: IPUMS USA, IPUMS USA - Ancestry Full Count Data
Topics: Population Data Science
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