Examining time to arrest for hate crime perpetrators: data from the New York City hate crimes repository - Chapa, Griselda (Journal of ethnicity in criminal justice, 2025)
This hate crimes study uses a structural violence framework and Cox proportional hazards regression to examine time to arrest for perpetrators. The analysis focuses on incidents that occurred between 2019 and 2024 in New York City. Data were retrieved from the NYC Open Data portal and represent police-reported hate crimes. Results reveal that arrests take longer for felonies, assaults, and cases involving Asian and Jewish victims, while cases involving Muslim and White victims tend to be resolved more quickly. Borough-level differences were less predictive than offense type or victim identity. The study highlights disparities in law enforcement response, suggesting that systemic biases may shape justice outcomes. Additionally, the lower number of hate crimes reported by Hispanics could suggest fear of police. These findings have significant implications for public health, equity, and trust in institutions tasked with addressing hate violence.