ArticleHistorical methods2025
Historical Context and Creation of the IPUMS Ancestry Full Count Population Census Data 1900-1930.
Article in Historical methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- The pig in the python: US decennial labor flows and economic opportunity, 1910-2040.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
IPUMS recently released final versions of full count census data for the United States 1900-1930. The information contained in these files is the product of three broad work stages: historical census enumeration, digitization, and IPUMS processing. The data were produced within an evolving institutional context and subjected to subsequent processes that had important ramifications on the final product. This paper documents these histories and processes and their implications for research. Because of the datasets' sheer size and scale, the development of these files necessitated applying different methods and approaches to assess data quality and correct the data. We document cases where data quality was affected not only by choices made by the Census historically, but also by data transcription errors in the modern day. Finally, we describe our approaches to processing the data, and we note some of the implications for research these various decisions have. As with any dataset, researchers should use this resource critically for their particular research questions and consider the data creation process from respondent to digital dataset. Despite some limitations and liabilities, the IPUMS full count data provides a powerful and valuable resource to study demographic effects on a variety of health and socioeconomic questions.
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Registered trials
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