Dynamic Modeling of Racially Motivated Hate Crime in Los Angeles

• In Event: Patterns of Prejudice: Modeling and Analyzing Hate Crime Distribution in American Cities

Abstract

Black’s theory of social time and conflict management offers a framework to understand racial conflict and identity-motivated harm, with his core argument being that any movement of social time underlies conflict and social control. More specifically, social time is the dynamic aspect of social life, which includes shifts in vertical, cultural, and relational aspects of social space, reflected in changes in stratification, intimacy, and diversity. We translate Black’s work into testable propositions and apply it to racially motivated hate crime in the City of Los Angeles (LA). Using hate crime data from the LA Police Department (2010-2023) and LA City Census tracts, we employ dynamic modeling to identify predictors of racially motivated hate crime, focusing on crimes targeting Asian, Black, Hispanic, and White victims. We found that neighborhoods with increased White unemployment rates had higher rates of anti-Black and Hispanic hate crimes. Additionally, hate crimes against Black victims were more frequent in neighborhoods with higher rates of White residents without a high school degree and those becoming more racially diverse. Increased racial diversity also predicted greater counts of anti-White hate crimes. Taken together, these findings offer important implications for future research and policy and clarify the dynamic foundation of racial conflict.

Authors

• Eaven Holder, University of Central Florida

• Marian Borg, University of Florida