Journal of Quantitative Criminology最新文献

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.

Objectives: The residential population of an area is an incomplete measure of the number of people that are momentarily present in the area, and of limited value as an indicator of exposure to the risk of crime. By accounting for the mobility of the population, measures of ambient population better reflect the momentary presence of people. They have therefore become an alternative indicator of exposure to the risk of crime. This study considers the heterogeneity of the ambient population by distinguishing residents, employees and visitors as different categories, and explores their differential impact on thefts, both on weekdays and weekends.

Methods: We analyze one-year of police recorded thefts across 2104 1 km² grid cells in a central area in Beijing, China. Controlling for the effects of attractiveness, accessibility, and guardianship, we estimate a series of negative binominal models to investigate the differential effects of the three groups (residents, employees and visitors) in the ambient population on crime frequencies, both on weekdays and during weekends and holidays.

Results: Overall, larger ambient populations imply larger theft frequencies. The effect of visitors is stronger than the effects of residents and employees. The effects of residents and employees vary over the course of the week. On weekdays, the presence of residents is more important, while the reverse holds true during weekends and holidays.

Discussion: The effects of ambient population on thefts vary by its composition in terms of social roles. The larger role of visitors is presumably because in addition to being potential victims, residents and employees may also exercise informal social control. In addition, they spend more time indoors than where risk of theft is lower, while visitors might spend more time outdoors and may also bring about greater anonymity and weaken informal social control.

Objectives: Examine and visualise the temporal concentration of different crime types and detect if their intensity varies through distinct moments of the week.

Methods: The "heartbeat of the crime signal" is constructed by overlapping the weekly time they were suffered. This study is based on more than 220,000 crimes reported to the Mexico City Police Department between January 2016 and March 2020 to capture the day and time of crimes and detect moments of the week in which the intensity exceeds the average frequency. A new metric for the temporal concentration of crime is constructed for different types of crime and regions of the city based on the corresponding heartbeats.

Results: The temporal concentration of crime is a stable signature of different types of crime. The intensity of robberies and theft is more homogeneous from Monday to Sunday, but robberies of a bank user are highly concentrated in a week, meaning that few hours of the week capture most of the burning moments. The concentration is not homogeneously distributed in the city, with some regions experiencing a much higher temporal concentration of crime.

Conclusions: Crime is highly concentrated when observed in its weekly patterns, but different types of crime and regions exhibit substantially distinct concentration levels. The temporal trace indicates specific moments for the burning times of different types of crime, which is a critical element of a policing strategy.

Objectives: Routine activity theory suggests that levels of crime are affected by peoples' activity patterns. Here, we examine if, through their impact on people's on- and off-line activities, COVID-19 restriction affected fraud committed on- and off-line during the pandemic. Our expectation was that levels of online offending would closely follow changes to mobility and online activity-with crime increasing as restrictions were imposed (and online activity increased) and declining as they were relaxed. For doorstep fraud, which has a different opportunity structure, our expectation was that the reverse would be true.

Method: COVID-19 restrictions systematically disrupted people's activity patterns, creating quasi-experimental conditions well-suited to testing the effects of "interventions" on crime. We exploit those conditions using ARIMA time series models and UK data for online shopping fraud, hacking, doorstep fraud, online sales, and mobility to test hypotheses. Doorstep fraud is modelled as a non-equivalent dependent variable, allowing us to test whether findings were selective and in line with theoretical expectations.

Results: After controlling for other factors, levels of crime committed online were positively associated with monthly variation in online activities and negatively associated with monthly variation in mobility. In contrast, and as expected, monthly variation in doorstep fraud was positively associated with changes in mobility.

Conclusions: We find evidence consistent with routine activity theory, suggesting that disruptions to people's daily activity patterns affect levels of crime committed both on- and off-line. The theoretical implications of the findings, and the need to develop a better evidence base about what works to reduce online crime, are discussed.

Supplementary information: The online version contains supplementary material available at 10.1007/s10940-022-09564-7.