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Despite abundant research on spatial predictors of violent victimization, few studies have explored the varying effects of these predictors on victims of different demographic backgrounds. This study seeks to bridge this gap by integrating perspectives from social disorganization, routine activity, risky lifestyles, and broken windows theories. Utilizing 2017–2019 crime data from Arlington, TX, the authors employ generalized spatial two-stage least-squares models to dissect the nuanced effects of place characteristics across different racial and ethnic groups. The findings highlight the importance of victim race/ethnicity in predicting robbery victimization within high-risk areas, uncovering the disparate effects the same place features have on people of different racial or ethnic backgrounds.
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Semukhina et al. (2024) studied this question.
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