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Evaluating the Accuracy of 2020 Census Block-Level Estimates in California.
Bozick, Robert; Burgette, Lane F; Sharygin, Ethan; Shih, Regina A; Weidmer, Beverly; Tzen, Michael; Kofner, Aaron; Brand, Jennie E; Beltrán-Sánchez, Hiram.
Afiliação
  • Bozick R; Department of Economics, Sociology, and Statistics, RAND Corporation, Santa Monica, CA, USA.
  • Burgette LF; Department of Economics, Sociology, and Statistics, RAND Corporation, Santa Monica, CA, USA.
  • Sharygin E; Population Research Center, Portland State University, Portland, OR, USA.
  • Shih RA; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
  • Weidmer B; Survey Research Group, RAND Corporation, Santa Monica, CA, USA.
  • Tzen M; California Center for Population Research, University of California-Los Angeles, Los Angeles, CA, USA.
  • Kofner A; Research Programming Group, RAND Corporation, Santa Monica, CA, USA.
  • Brand JE; Department of Sociology and California Center for Population Research, University of California-Los Angeles, Los Angeles, CA, USA.
  • Beltrán-Sánchez H; Department of Community Health Sciences, Fielding School of Public Health; and California Center for Population Research, University of California-Los Angeles, Los Angeles, CA, USA.
Demography ; 60(6): 1903-1921, 2023 Dec 01.
Article em En | MEDLINE | ID: mdl-38009227
ABSTRACT
In this study, we provide an assessment of data accuracy from the 2020 Census. We compare block-level population totals from a sample of 173 census blocks in California across three sources (1) the 2020 Census, which has been infused with error to protect respondent confidentiality; (2) the California Neighborhoods Count, the first independent enumeration survey of census blocks; and (3) projections based on the 2010 Census and subsequent American Community Surveys. We find that, on average, total population counts provided by the U.S. Census Bureau at the block level for the 2020 Census are not biased in any consistent direction. However, subpopulation totals defined by age, race, and ethnicity are highly variable. Additionally, we find that inconsistencies across the three sources are amplified in large blocks defined in terms of land area or by total housing units, blocks in suburban areas, and blocks that lack broadband access.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Etnicidade / Censos Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Etnicidade / Censos Idioma: En Ano de publicação: 2023 Tipo de documento: Article