How Racial Context Shapes Voting on Affirmative Action:A Cross-Racial Comparison

• In Event: Opinions on Race-Based Policies

Abstract

Affirmative action is at the center of contested policy debates in American Politics today. Even so, relatively few studies have sought out to understand more about the determinants of attitudes toward affirmative action. Here, we advance theories on the influence of social context on public opinion and argue that public support for race-conscious admissions is a function of the partisan and/or racial makeup of an area. The paper leverages the case of Proposition 16 to reinstate affirmative action in California in the 2020 statewide election. To do this, we analyze statewide voter files merged with aggregate-level racial and partisan composition variables. First, we conduct a cross-racial analysis using ecological inference in order to estimate support for affirmative action policies across Black, Latino, Asian, and White voters. Preliminary results from 17,403 election precincts show that racial context is significantly correlated with support for Proposition 16 but the direction of the relationship varies by racial group. For example, the level of White voter support for affirmative action was inversely proportional to the population density of Latinos living in their communities but for Asian American voter support was directly proportional to the population density of Latinos. In a test of partisan context, we find that Asian, Latino, and White voters who live in increasingly Democratic leaning areas were more likely to support Proposition 16. Taken together, the paper provides evidence for the important role of context in public opinion formation and how the effects of context vary across racial groups. This study has important implications for scholars of racial/ethnic politics, political behavior, and state and local politics, who may be interested in building coalitions to support racially inclusive public policies.

Authors

• Nathan Kar Ming Chan, Loyola Marymount University

• Vivien Leung, Santa Clara University

• Natalie Masuoka, University of California, Los Angeles

• Jessica HyunJeong Lee, California State University, Fullerton