Communities, Streets, and People: A Multi-level Study of the Correlates of Victimization.

The current study adds the context of the immediate microgeographic environment (measured as the street segment) to the study of individual victimization. Using residential survey and physical observation data collected on 449 street segments nested within 53 communities in Baltimore, MD, we employ multilevel logistic regression models to examine how individual risky lifestyles, the microgeographic context of the street, and community level measures influence self-reported property and violent crime victimization. Results confirm prior studies that show that risky lifestyles play a key role in understanding both property and violent crime victimization, and community indicators of disadvantage play a role in explaining violent crime victimization. At the same time, our models show that the street segment (micro-geographic) level adds significant explanation to our understanding of victimization, suggesting that three level models should be used in explaining individual victimization. The impact of the street segment is particularly salient for property crime.

Mean Streets and Mental Health: Depression and Post-Traumatic Stress Disorder at Crime Hot Spots.

This study explores the relationship between mental health and place at microgeographic units of analysis. We examine self-reported symptomology for depression and PTSD for 2,724 survey respondents interviewed in three types of randomly selected street segments: violent crime hot spots, cool spots, and cold spots. We find that the mean symptomology score is 61% higher for depression in violent crime hot spots than cold spots, and 85% higher for PTSD. Overall, we estimate that 14.8% of residents of violent crime hot spots meet thresholds for moderate depression or a diagnosis of PTSD. This can be compared to only 6.5% of residents at the cold spots. Using PSM and weighted negative binomial regression approaches we show that observable selection factors are not responsible for the relationships identified. Examining geographic influences, we find an important area effect of violent crime for both mental health measures, and an additional impact of the specific street of residence for PTSD.

The problem is not just sample size: the consequences of low base rates in policing experiments in smaller cities.

BACKGROUND: Hot spots policing is one of the most influential police innovations, with a strong body of experimental research showing it to be effective in reducing crime and disorder. However, most studies have been conducted in major cities, and we thus know little about whether it is effective in smaller cities, which account for a majority of police agencies. The lack of experimental studies in smaller cities is likely in part due to challenges designing statistically powerful tests in such contexts. OBJECTIVES: The current article explores the challenges of statistical power and "noise" resulting from low base rates of crime in smaller cities and provides suggestions for future evaluations to overcome these limitations. RESEARCH DESIGN: Data from a randomized experimental evaluation of broken windows policing in hot spots are used to illustrate the challenges that low base rates present for evaluating hot spots policing programs in smaller cities. RESULTS: Analyses show low base rates make it difficult to detect treatment effects. Very large effect sizes would be required to reach sufficient power, and random fluctuations around low base rates make detecting treatment effects difficult, irrespective of power, by masking differences between treatment and control groups. CONCLUSIONS: Low base rates present strong challenges to researchers attempting to evaluate hot spots policing in smaller cities. As such, base rates must be taken directly into account when designing experimental evaluations. The article offers suggestions for researchers attempting to expand the examination of hot spots policing and other microplace-based interventions to smaller jurisdictions.