Is Police Misconduct Contagious? Non-trivial Null Findings from Dallas, Texas

Objectives Understanding if police malfeasance might be “contagious” is vital to identifying efficacious paths to police reform. Accordingly, we investigate whether an officer’s propensity to engage in misconduct is associated with her direct, routine interaction with colleagues who have themselves engaged in misbehavior in the past. Methods Recognizing the importance of analyzing the actual social networks spanning a police force, we use data on collaborative responses to 1,165,136 “911” calls for service by 3475 Dallas Police Department (DPD) officers across 2013 and 2014 to construct daily networks of front-line interaction. And we relate these cooperative networks to reported and formally sanctioned misconduct on the part of the DPD officers during the same time period using repeated-events survival models. Results Estimates indicate that the risk of a DPD officer engaging in misconduct is not associated with the disciplined misbehavior of her ad hoc, on-the-scene partners. Rather, a greater risk of misconduct is associated with past misbehavior, officer-specific proneness, the neighborhood context of patrol, and, in some cases, officer race, while departmental tenure is a mitigating factor. Conclusions Our observational findings—based on data from one large police department in the United States—ultimately suggest that actor-based and ecological explanations of police deviance should not be summarily dismissed in favor of accounts emphasizing negative socialization, where our study design also raises the possibility that results are partly driven by unobserved trait-based variation in the situations that officers find themselves in. All in all, interventions focused on individual officers, including the termination of deviant police, may be fruitful for curtailing police misconduct—where early interventions focused on new offenders may be key to avoiding the escalation of deviance.

A Case Study of Family Violence During COVID-19 in San Antonio

The current study investigates the effects of coronavirus restrictions on family violence in the seventh largest city in the country, San Antonio, Texas. Two streams of data were used to evaluate the potential change between what occurred during the lockdown period versus what would have been expected, including the COVID-19 Government Response Stringency Index and police calls for service from the San Antonio Police Department. The methodological approach used takes advantage of feature engineering, various machine learning time series forecasting techniques commonly leveraged in financial technical analysis, as well as cross-validation for optimized model selection. These techniques have not been considered in previous domestic or family violence-related research. During the lockdown period in San Antonio, we observed a larger than expected increase in calls to police for family violence incidents. Specifically, an increase of over fourteen percent of police calls for family incidents was observed. The findings of the current study suggest that social service and social welfare agencies consider and plan for how future pandemics or other major disasters will affect the incidence of family violence and take appropriate steps now to bolster resources and scale up for the future.

Impact of Focused Deterrence on Lived Experiences With Gangs and Gun Violence: Extending Effects Beyond Officially Recorded Crime

The study evaluates a geographically based focused deterrence (FD) intervention, extending knowledge about FD impact beyond crime data to also examine residents’ lived experiences with gangs and gun violence via a two-wave household survey. We employ a quasi-experimental design and utilize time-series analyses, coefficient difference tests, and mixed-effects ordinal logistic regression. The results show a significant reduction in shots fired incidents in the target area relative to comparison areas. Shots fired calls for service trended downward citywide, but the magnitude was doubled in the target area. Survey data showed substantive declines in the target area on all six gang and gun violence outcomes, significantly exceeding changes experienced in comparison areas. We conclude that focusing geographically as well as on repeat offenders is an effective FD approach, and evaluating community surveys provides an improved understanding of the community impact.

Re-assessing measurement error in police calls for service: Classifications of events by dispatchers and officers

Police calls for service are an important conduit by which officers and researchers can obtain insight into public requests for police service. Questions remain, however, about the quality of these data, and, particularly, the prevalence of measurement error in the classifications of events. As part of the present research, we assess the accuracy of call-types used by police dispatchers to describe events that are responded to by police officers. Drawing upon a sample of 515,155 calls for police service, we explore the differences among initial call-types, cleared call-types, and crime-types as documented in crime reports. Our analyses reveal that although the majority of calls for service exhibit overlap in their classifications, many still exhibit evidence of misclassification. Our analyses also reveal that such patterns vary as a function of call- and crime-type categories. We discuss our findings in light of the challenges of the classification process and the associated implications.

The Effect of COVID-19 on Domestic Violence and Assaults

The purpose of this research was to examine the effect of COVID-19 on four outcomes including calls for service for domestic violence, calls for service for assaults, arrests for domestic violence, and arrests for assaults in Burlington, Vermont. The data for each outcome collected over the time periods January 2012 through May 2021 were obtained from the Burlington Police Department website and then a monthly time-series data set were created. The analyses including an independent samples t-test, a Poisson regression test, and a monthly interrupted time-series analyses (ITSA) were employed to test the effects of COVID-19 on the previously mentioned outcomes. The results of the ITSA showed that in the first month following the onset of the COVID-19 pandemic, domestic violence calls statistically significantly increased, but no statistically significant change was observed in domestic violence arrests, while assault calls and assault arrests statistically significantly decreased. In addition, during COVID-19, there was a statistically significant decreasing trend in domestic violence calls and domestic violence arrests, while there was no statistically significant change in the trends of assault calls and assault arrests. The results suggest that COVID-19 had an immediate as well as a persistent effect on the numbers of domestic violence and assaults. The results and limitations of this study were also discussed.

The effect of the COVID-19 pandemic on mental health calls for police service

Drawing upon seven years of police calls for service data (2014–2020), this study examined the effect of the COVID-19 pandemic on calls involving persons with perceived mental illness (PwPMI) using a Bayesian Structural Time Series. The findings revealed that PwPMI calls did not increase immediately after the beginning of the pandemic in March 2020. Instead, a sustained increase in PwPMI calls was identified in August 2020 that later became statistically significant in October 2020. Ultimately, the analysis revealed a 22% increase in PwPMI calls during the COVID-19 pandemic than would have been expected had the pandemic not taken place. The delayed effect of the pandemic on such calls points to a need for policymakers to prioritize widely accessible mental health care that can be deployed early during public health emergencies thus potentially mitigating or eliminating the need for increased police intervention, as was the case here.