2021/01/11 by Sasha Shen Johfre, Sasha Johfre, Jeremy Freese · 113 citations
Mathematics · Psychology · Social Sciences · #Artificial intelligence #Categorical variable #Categorization #Computer science #Family Dynamics and Relationships #Gender studies #Health disparities and outcomes #Interpretability #Mathematics #Psychology #Race (biology) #Social psychology #Sociology #Statistics #Urban, Neighborhood, and Segregation Studies
paper · doi:10.1177/0081175020982632
published in Sociological Methodology 51(2), 253-269 (SAGE Publishing)
crossref issued 2021/01/11 · crossref published 2021/01/11 · crossref published-online 2021/01/11 · openalex publication_date 2021/01/11 · crossref created 2021/01/14 · crossref published-print 2021/08/01 · openalex created_date 2025/10/10 · crossref deposited 2026/05/01 · crossref indexed 2026/08/01 · openalex updated_date 2026/08/01
Social scientists often present modeling results from categorical explanatory variables, such as gender, race, and marital status, as coefficients representing contrasts to a “reference” group. Although choosing the reference category may seem arbitrary, the authors argue that it is an intrinsically meaningful act that affects the interpretability of results. Reference category selection foregrounds some contrasts over others. Also, selecting a culturally dominant group as the reference can subtly reify the notion that dominant groups are the most “normal.” The authors find that three of four recently published tables in Demography and American Sociological Review that include race or gender explanatory variables use dominant groups (i.e., male or white) as the reference group. Furthermore, the tables rarely state what the reference is: only half of tables with race variables and one-fifth of tables with gender variables explicitly specify the reference category; the rest leave it up to the reader to check the methods section or simply guess. As an alternative to this apparently standard practice, the authors suggest guidelines for intentionally and responsibly choosing a reference category. The authors then discuss alternative ways to convey results from categorical explanatory variables that avoid the problems of reference categories entirely.