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Objective: Examine the place-based correlates of robbery activity displaced by a foot-patrol intervention in Newark, NJ. We use constructs from Crime Pattern and Social Disorganization theories to test hypotheses concerned with associations between the structure of the environment and the displacement of crime. Method: Robbery incidents were spatially joined to street segments to study micro-level displacement processes. Predictor variables were operationalized using data from the Newark Police Department and Infogroup USA. Generalized Linear models tested associations between the characteristics of street segments and displaced robbery in the target area as compared to a control. Results: Environmental structure is important to understanding the settings of displacement, though this varied between spatial and temporal displacement. Relationships between displaced crime activity and model covariates did not always appear in expected directions. For example, bus stops predicted increased spatial displacement while corner stores predicted decreased levels of temporal displacement. Conclusions: While testing for displacement has become commonplace in place-based policing interventions, less attention has been paid to the micro-level factors that may facilitate the displacement of crime events. Both bus stops and corner stores show consistent associations with displaced crime activity, but the directions of these relationships suggest more complex processes requiring further examination.

In the last two decades, closed-circuit television (CCTV) surveillance cameras have come to occupy a central role in contemporary crime prevention across the world. Widely viewed as the “internatio...

Purpose Risk Terrain Modeling (RTM) has been effectively used to spatially diagnose risk for crimes such as robbery, aggravated assault , and gun violence. An important contribution is to consider how risk differs across individual crimes and different target types. This study tests four different robbery target types in unique models to examine the potential for variation across significant risk factors and high-risk locations. Methods Using the online diagnostic software RTMDx, individual robbery models were run for four robbery target types in Denver, Colorado: commercial (businesses), carjacking (driver/vehicle), residential (home/dwelling), and street (pedestrians). A conjunctive analysis of case configurations was also conducted to determine the potential for spatial differences in high-risk places across target types. Results The results indicate that there is variation across risk factors, and observable differences in risk factor spatial influence, operationalization and relative risk values in each target model. Convenience stores were the only risk factor significantly associated with every target type and the conjunctive analysis matrix found that very few places were high-risk for all four robbery types. Conclusions The findings suggest different target types should be analyzed individually and interventions should focus on different high-risk locations and be tailored to specific target types.

Objectives: Through the use of closed-circuit television (CCTV) video footage, the current study builds upon the drug transaction work of Piza and Sytsma by developing a crime script for open-air drug selling. Methods: Researchers conducted a systematic social observation of CCTV footage of open-air drug markets in Newark, NJ. The data were used to identify sequential stages of drug transactions. Fisher’s exact tests measured whether buyer and seller activities during specific acts of the drug transaction event were related to activities seen in subsequent stages. Results: This study finds three distinct acts to open-air drug events. During the pretransaction act, one party (usually the buyer) initiates the transaction. There must then be an exchange of narcotics for money, which typically occurs in one simultaneous transfer and in one location. There is necessarily posttransaction mobility, with sellers most commonly maintaining their anchor point within the drug territory—particularly when the interactions are buyer initiated. Conclusions: Results of this study contribute to the crime script and situational crime prevention literatures by demonstrating acts inherent in public drug selling and by advocating for a focus on the posttransaction period and seller anchor points within drug markets through leveraging the sentinel role of police officers.

Purpose This study tests whether the effect of police actions is influenced by similar crime generators and attractors (CGAs) that influence crime. Said differently, in recognition that the presence of CGAs presents higher risk of crime at certain places, we test whether CGAs similarly create a situation where specific police enforcement actions are more effective at certain types of places than others. Methods Using longitudinal logistic regression models incorporating panel data, we measure the effect of various police enforcement actions on gun violence in Newark, NJ. Risk Terrain Modeling (RTM) was further used to test whether the effect of the enforcement activities vary across spatial contexts. Results When considered on their own, police enforcement actions were associated with increased likelihood of gun violence. However, certain types of enforcement actions conducted where CGAs highly co-locate, as identified through RTM, were associated with decreased likelihood of gun violence. Conclusions Findings suggest that where officers conduct enforcement activities may be as important as what precise enforcement activities they enact. This has implications for the place-based policing tactics. Understanding the spatial context of high-crime areas can help police design strategies in a manner that maximizes their crime prevention utility.

Risk terrain modeling (RTM) is a geospatial crime analysis tool designed to diagnose environmental risk factors for crime and identify the places where their spatial influence is collocated to produce vulnerability for illegal behavior. However, the collocation of certain risk factors’ spatial influences may result in more crimes than the collocation of a different set of risk factors’ spatial influences. Absent from existing RTM outputs and methods is a straightforward method to compare these relative interactions and their effects on crime. However, as a multivariate method for the analysis of discrete categorical data, conjunctive analysis of case configurations (CACC) can enable exploration of the interrelationships between risk factors’ spatial influences and their varying effects on crime occurrence. In this study, we incorporate RTM outputs into a CACC to explore the dynamics among certain risk factors’ spatial influences and how they create unique environmental contexts, or behavior settings, for crime at microlevel places. We find that most crime takes place within a few unique behavior settings that cover a small geographic area and, further, that some behavior settings were more influential on crime than others. Moreover, we identified particular environmental risk factors that aggravate the influence of other risk factors. We suggest that by focusing on these microlevel environmental crime contexts, police can more efficiently target their resources and further enhance place-based approaches to policing that fundamentally address environmental features that produce ideal opportunities for crime.

Purpose To date script analysis has not been used in the field of criminology to further understand processes behind events involving non-offending criminal justice system actors. The purpose of this research is to conduct a pilot study to develop a police officer force escalation script. Methods Through the systematic social observation video data analysis of police-worn body camera footage, conjunctive analysis of case configurations is applied to develop force escalation scripts. Results Scripts consist of dominant officer and subject action configurations associated with an increased risk of escalation from soft empty-hand control to more severe types of force, as well as configurations of environmental and demographic characteristics. Conclusions Based on identified scripts, if study results are replicated using a larger sample size, results support the efficacy of persistent calm commands for reducing risk of escalation. Crisis intervention and procedural justice training is recommended for officers. To create a heightened awareness of the presence of a recording device, wearers of BWCs may consider narrating interactions as they unfold. Finally, pending replication, we advocate for immediate physical separation of victim and suspect when in a private space.

Purpose To determine if repeat and near repeat analysis is sensitive to the geocoding algorithm used for the underlying crime incident data. Methods The Indianapolis Metropolitan Police Department provided 2016 crime incident data for five crime types: (1) shootings, (2) robberies, (3) residential burglaries, (4) theft of automobiles, and (5) theft from automobiles. The incident data were geocoded using a dual ranges algorithm and a composite algorithm. First, descriptive analysis of the distances between the two point patterns were conducted. Second, repeat and near repeat analysis was performed. Third, the resulting repeat and near repeat patterns were compared across geocoding algorithms. Results The underlying point patterns and repeat and near repeat analyses were similar across geocoding algorithms. Conclusions While detailing geocoding processes increases transparency and future researchers can conduct sensitivity results to ensure their findings are robust, dual ranges geocoding algorithms are likely adequate for repeat and near repeat analysis.

Social scientists have long shown great interest in the spatial correlates of crime patterns. A subset of the literature has focused on how micro-level spatial factors influence the formation of crime hot spots. At the same time, tangential research has highlighted how neighbourhood disadvantage influences crime occurrence. The current study focuses on the intersection of these perspectives through a spatial analysis of Motor Vehicle Theft (MVT) and Motor Vehicle Recovery (MVR) in Colorado Springs, CO. We begin by conducting a Risk Terrain Modelling analysis to identify spatial risk factors significantly related to MVT and MVR occurrence. We then test whether the spatial influences of the criminogenic risk factors differ across traditional measures of neighbourhood disadvantage. Findings suggest that while a citywide effect is evident for multiple risk factors, their spatial influence on crime significantly varies across neighbourhood contexts.

The effects of gang membership on individual social, behavior, cognitive, and health outcomes are well documented. Yet, research consistently has shown that gang membership and the boundaries of gangs are often fluid and amorphous. The current study examines how social proximity to a gang member in one's co-offending network influences the probability of being a gunshot victim. We re-create and analyze the social network of all individuals who were arrested, summonsed for a quality-of-life violation, and subjected to noncustodial police contacts in Newark, New Jersey, during a 1-year time period (N = 10,531). A descriptive network analysis finds an extreme concentration of fatal and nonfatal gunshot injuries within a small social network: Nearly one third of all shootings in Newark occur in a network that contains less than 4 percent of the city's total population. Furthermore, a series of logistic regression models finds that being directly or indirectly linked to a gang member in one's co-offending network has a significant effect on one's probability of being a gunshot victim. Implications of these findings for the study of gangs, gun violence, and a public health approach to violence are discussed.

Prior research has applied risk assessment and spatial analysis techniques to the study of violence. This paper builds on those results, tying the practical outcomes of spatial risk analysis methods to broader spatial issues on the articulation of risky places for aggravated assault. We begin by conceptualizing key relationships, addressing the effects of environmental factors on creating distinct, identifiable areas that are conducive to crime. Propositions of the theory of risky places are posed and then empirically tested using a GIS based program, RTMDx, on aggravated assault data in an urban area. Given the current thinking about crime vulnerability based on concentration and spatial influence of features and events, this paper offers an analytical strategy to model risky places that combines the conceptual insights of crime emergence and persistence, advances in geo-spatial analytical techniques, and micro-level data.

Objectives: The current study contributes to the literature through a systematic social observation of the defensive actions of drug sellers within open-air retail markets. The study expands upon previous literature by incorporating a novel data collection and coding method. Methods: Video footage of narcotics transactions was extracted from the closed-circuit television (CCTV) system of the Newark, NJ Police Department. Researchers transcribed and coded the footage to measure the frequency of defensive actions incorporated by drug sellers. Fisher’s exact tests measured whether the frequency of each defensive action significantly differed across geographic setting or time of day. Results: The frequency of many defensive actions was significantly related to geographic setting and time of day. The strongest relationship was observed between the use of stash spots and setting. Overall, the findings suggest that drug sellers adopt tenets of Opportunity Theory to protect themselves from law enforcement, specifically by acting as guardians and place managers on their own behalf. Conclusions: This study extends prior techniques and provides an additional case study on the use of CCTV footage in the study of street-level crime. This methodology can be used in concert with more traditional ethnographic techniques in the study of the drug trade and in crime-and-place research in general.

The primary preventive mechanism of CCTV is considered to be deterrence. However, the relationship between CCTV and deterrence has been left implicit. Empirical research has yet to directly test whether CCTV increases the certainty of punishment, a key component of the deterrence doctrine. This study analyzes CCTV’s relation to punishment certainty in Newark, NJ. Across eight crime categories, CCTV and 9-1-1 calls-for-service case processing times and enforcement rates are compared through Mann-Whitney U and Fisher’s Exact tests, respectively, with a Holm-Bonferroni procedure correcting for multiple comparisons. ANOVA and negative binomial regression models further analyze the frequency of CCTV activity and the impact of various factors on the (downward) trend of detections and enforcement. Findings suggest that CCTV increases punishment certainty on a case-by-case basis. However, a reduction of CCTV activity caused by specific “surveillance barriers” likely minimized the effect of the enhanced enforcement.