Racial Dynamics and Hate Crimes: A Community-Level Investigation in Chicago
Document Type
Presentation
Location
436 Hodges / Zoom Room B
Start Date
28-3-2025 1:25 PM
End Date
28-3-2025 1:45 PM
COinS
Mar 28th, 1:25 PM
Mar 28th, 1:45 PM
Racial Dynamics and Hate Crimes: A Community-Level Investigation in Chicago
436 Hodges / Zoom Room B
Comments
Objectives. Hate crime is a criminal act against individuals or groups based on socio-demographic makers, such as race, ethnicity, religion, gender, sexual orientation, and others (Gover, Harper, and Langton 2020; Perry 2002; Lyons 2007). In our understanding of the reciprocal influence of crime, particularly hate crimes, spatial arrangements and social dynamics cannot be isolated, since local social dynamics shape the likelihood of hate-motivated violence (Flint 2004; Hipp and Williams 2020; Lyon 2007).
This study explores the community-level mechanisms of racially motivated hate crimes in Chicago, where crime rates have consistently superseded the national averages, and a racial and ethnic diversity pronounced long history of residential segregation and other social problems (Bursik 1988; Massey and Denton 1993) These provide a suitable backdrop for examining patterns of hate crime clustering across Chicago communities. We seek to assess how community-level social conditions catalyze hate crime clustering across 77 Chicago communities, distinctively by each victim group.
Methods. We will gather community-level data in a geospatial unit to test the pattern of hate crime in the Chicago communities using the following two datasets. First, the Chicago Police Department publicizes the hate-motivate crime statistics, including the date reported, the hate motivations, and the location of each offense by 77 community areas. Second, we will also account for other demographic and socioeconomic characteristics that might shape hate incidents at a community level. These community-level variables will be gathered from the American Community Survey, prepared by Chicago Metropolitan Agency for Planning. We focus on the year 2023, when hate incidents in Chicago peaked after Chicago PD has officially published hate crime statistics and the most recent data are publicly available at the time of analysis.
For multivariate analysis, We will employ spatial autoregressive modeling (SAR) to analyze the spatial data. It allows us to account for the spatial interdependence between units to estimate the impact of explanatory variables on the outcome variable. The SAR modeling approach is broadly used in social science research examining the geospatial patterns of crime and policing practices (Golash-Boza and Oh 2021; Golash-Boza et al. 2023).
Findings. We expect that there will be more hate crimes against non-White racial and ethnic minorities in White affluent communities while there will more hate crime perpetrations against Whites in Black poor communities. We also anticipate that community-level distinctions in anti-Asian hate crimes, as compared to other race-based hate crimes, due to the characteristics of the hated group.
By considering neighborhood dynamics in the light of inseparable social and spatial factors, this study can contribute to providing a comprehensive approach addressing hate crimes with targeted neighborhood-based solutions.