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Cited by 137Racial and Ethnic Identity ResearchSurvey Methodology and NonresponseIntergenerational and Educational Inequality Studies

Double-Checking the Race Box: Examining Inconsistency between Survey Measures of Observed and Self-Reported Race

Saperstein, A.·2006·Social Forces
DOI 10.1353/sof.2006.0141
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Abstract

Social constructivist theories of race suggest no two measures of race will capture the same information, but the degree of “error” this creates for quantitative research on inequality is unclear. Using unique data from the General Social Survey, I find observed and self-reported measures of race yield substantively different results when used to explain income inequality in the United States. This occurs because inconsistent racial classification is correlated with other respondent characteristics such as immigrant generation, educational attainment and age.

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  • These mismatches can significantly impact health statistics, population statistics, and measures of social inequality.

    “This in turn can significantly impact health statistics [62, 101], population statistics [8, 74], and measures of social inequality [102].”

    From Towards a critical race methodology in algorithmic fairness (2020) · cites this paper as [102]

  • Racial category and measurement choices can affect outcomes being measured in survey research.

    “a growing body of survey research has highlighted the impact that racial category and measurement choices can have on outcomes being measured [102-104].”

    From Towards a critical race methodology in algorithmic fairness (2020) · cites this paper as [102]

  • When race is utilized as a descriptive category, the choices about what categories to use and how to assign individuals to categories significantly impacts the results of analysis.

    “When race is utilized as a descriptive category, the choices about what categories to use and how to assign individuals to categories significantly impacts the results of analysis [18, 102, 114, 115].”

    From Towards a critical race methodology in algorithmic fairness (2020) · cites this paper as [102]

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Authors
Saperstein, A.
Affiliations
University of California, Berkeley (US)
Corresponding author
Saperstein, A.
ORCID
Saperstein, A.
Venue
Social Forces
Publisher
Oxford University Press (OUP)
Published
2006-09-01
Volume
85
Issue
1
Pages
57-74
ISSN
  • 0037-7732 (ISSN-L)
  • 1534-7605
DOI
10.1353/sof.2006.0141
OpenAlex
W2170463344
Cited by
137
References
21
Citations by year
2026: 4 · 2025: 4 · 2024: 6 · 2023: 5 · 2022: 12 · 2021: 11 · 2020: 7 · 2019: 8 · 2018: 8 · 2017: 8 · 2016: 10 · 2015: 11 · 2014: 7 · 2013: 8 · 2012: 5
FWCI
5.80
Type
journal article
Language
en
Open access
closed
Locations
  • Social Forces (publishedVersion)
  • Project Muse (Johns Hopkins University) (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
  • Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
Keywords
racial classification, self-reported race, measurement discrepancy, income inequality, social construction of race, immigrant generations, educational attainment, age, General Social Survey

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