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历史背景与IPUMS祖先全计数人口普查数据(1900 - 1930年)的创建

Historical Context and Creation of the IPUMS Ancestry Full Count Population Census Data 1900-1930.

作者信息

Nelson Matt A, Magnuson Diana L, Sobek Matthew, Huynh Lap, Ruggles Steven

机构信息

University of Minnesota.

出版信息

Hist Methods. 2025 Apr 12. doi: 10.1080/01615440.2025.2485464.

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.

摘要

综合公共使用微观数据系列(IPUMS)最近发布了1900年至1930年美国完整人口普查数据的最终版本。这些文件中包含的信息是三个广泛工作阶段的成果:历史人口普查枚举、数字化以及IPUMS处理。这些数据是在不断演变的制度背景下产生的,并经历了对最终产品有重要影响的后续过程。本文记录了这些历史和过程及其对研究的影响。由于数据集规模庞大,这些文件的开发需要应用不同的方法和途径来评估数据质量并纠正数据。我们记录了数据质量不仅受到历史上人口普查所做选择的影响,还受到现代数据转录错误影响的案例。最后,我们描述了处理数据的方法,并指出这些不同决策对研究的一些影响。与任何数据集一样,研究人员应根据其特定的研究问题批判性地使用这一资源,并考虑从受访者到数字数据集的数据创建过程。尽管存在一些局限性和不利因素,但IPUMS完整人口数据为研究人口统计学对各种健康和社会经济问题的影响提供了强大而有价值的资源。

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