The Difference “Hate” Makes in Clearing Crime

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Studying hate crime clearance rates provides an opportunity to uncover the factors that influence police effectiveness for a relatively new legal category—one that was designed ostensibly to protect minorities, and that may pose unique challenges for police reporting, defining, and investigation. Using multiple years (2005-2010) of data from the National Incident-Based Reporting System (NIBRS), we estimate event history models to compare the incident-level predictors and relative probability of arrest for hate and nonbias crimes. As an aggregate category, we find hate crimes are less likely to clear than nonbias crimes. However, the most prototypical hate crimes—White-on-non-White incidents motivated by racial and ethnic bias—are as likely to clear as the most successfully cleared nonbias crimes. Our results suggest that only hate crimes that fit popular constructions of “normal victims and offenders” receive investigative outcomes comparable with otherwise similar nonbias offenses.

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Hate crimes have escalated significantly across the United States, with their frequency and targets varying according to shifting social dynamics and political ideologies. The importance of studying hate crimes stems from the growth of hate crimes and the destructive, lasting impacts even beyond the victim. With the Hispanic population accounting for 71% of the overall population growth in the United States between 2022 and 2023, there are over 65 million Hispanics, according to the most recent U.S. Census report. This indicator shows the need to focus on Hispanic victims of hate crimes and their unique characteristics. This study aims to use the 2020 National Incident-Based Reporting System to investigate the prevalence and characteristics of Hispanic hate crimes versus other racial/ethnic groups. We conducted standard inferential statistics to see significant differences in our findings. This study contributed to the limited body of hate crime literature by focusing on minority-targeted hate crimes.

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Evaluating the Availability of Uniform Crime Reporting Data, and Using Data Management to Make It More Powerful and Accessible
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Existing true raw for Uniform Crime Reporting (UCR) Hate Crime Data is available in ASCII, with each year as a separate file, or on the FBI website, where the abridged summary information omits most of the additional demographic information obtained from the switch to a National Incident Based Reporting System (NIBRS). The attached NIBRS information is critical, because it provides additional data for social science researchers, citizens, and law enforcement to most accurately assess at-risk groups and areas and determine the causes of hate crime offenses. The fully-detailed ASCII format data has been reformatted and recoded into a single unified Microsoft Excel database. The process to do so is described step-by-step.

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