Comparing Three Methods of Measuring Race/Ethnicity

Abstract In this research note, we explore compare and contrast three methods for measuring race. We utilize as our baseline, or “true”, measure expert coded racial categories, and to this compare two alternatives. The first is a hybrid Bayesian analysis of racial/ethnic surname lists and population...

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Bibliographic Details
Published inJournal of race, ethnicity, and politics Vol. 2; no. 1; pp. 124 - 139
Main Authors Shah, Paru R., Davis, Nicholas R.
Format Journal Article
LanguageEnglish
Published Cambridge Cambridge University Press 01.03.2017
Subjects
Accuracy
Bayesian analysis
Candidates
Census of Population
Crowdsourcing
Cultural identity
Elections
Ethnic groups
Ethnicity
Hispanic Americans
Linguistics
Natural language processing
Politics
Probability
Race
Racial identity
Reliability
Researchers
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Summary:Abstract In this research note, we explore compare and contrast three methods for measuring race. We utilize as our baseline, or “true”, measure expert coded racial categories, and to this compare two alternatives. The first is a hybrid Bayesian analysis of racial/ethnic surname lists and population distributions, which allow us to develop a race probability score for each candidate. The second is a novel and innovative crowdsourcing method that allows many contributors to classify the racial identity of candidates. We analyze and discuss the potential benefits, pitfalls, and tradeoffs of each method. We conclude with the implications of these new measures for future election research as well as race and politics scholarship more broadly.
ISSN:2056-6085
2056-6085
DOI:10.1017/rep.2016.27