An intrinsic part of hate crime perpetration is to be motivated in part or whole based on biases against another due to their identity. Yet, less is known about how hate crime impacts people who occupy multiple marginalized identities. This analysis moves our understanding forward by employing network analysis to capture how hate crimes and bias-motivated experiences cluster among different victim demographics. We focus here on Latino/a populations in the United States, which are at increased risk for hate crime victimization. Using a sample of Latino/a adults across three U.S. communities (n = 910), we assess the links between bias-motivated experiences based on multiple key demographic intersections. Results demonstrate that gender, immigrant status, and economic status distinctly impact how bias-motivated experiences cluster and relate, particularly when examined together. Findings suggest that it is imperative to look at people's victimization experiences holistically, especially when they hold multiple identities that fundamentally change their experiences with bias-motivated harm. These findings have implications for practitioners, particularly those in the criminal justice system, who seek to better identify and respond to victims of hate crime.
Lockwood et al. (2026) studied this question.