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What is the best way for law enforcement to deal with crime 'hot spots'? In recent years, police forces have tended to favor tougher enforcement strategies which proactively focus on the most problematic places. In new research which studies policing strategies in Newark, New Jersey, Eric L. Piza finds that what he calls 'guardian actions' such as citizen contacts, business, taxi and bus checks were much more effective at reducing the likelihood of violent crime compared to enforcement actions like arrests and interrogations.

AbstractResearch outside the field of policing has shown that job satisfaction predicts job performance. While policing research has demonstrated performing community-oriented policing (COP) activities generally improves police officer job satisfaction, the mechanism through which it occurs remains unclear. This study contributes to the community-policing literature through a survey of 178 police officers at the Toronto Police Service. The survey instrument measures the mechanism through which job satisfaction is impacted. Results indicate that primary response officers are more likely to be somewhat or very unsatisfied with their current job assignment compared with officers with a COP assignment—confirming what previous research has found. Further, those who interact with the public primarily for the purpose of engaging in problem-solving are more likely to be very satisfied with their current job assignment compared with those who do so primarily for the purpose of responding to calls for service. Engaging in problem-solving increases the odds of being very satisfied in one's job assignment, and the combination of frequent contacts with the public and problem-solving is less important than problem-solving alone. The implications of the study findings for COP strategies are discussed.

Risk-based policing is a research advancement that improves public safety, and its applications prevent crime specifically by managing crime risks. In Risk-Based Policing, the authors analyze case studies from a variety of city agencies including Atlantic City, New Jersey; Colorado Springs, Colorado; Glendale, Arizona; Kansas City, Missouri; Newark, New Jersey; and others. They demonstrate how focusing police resources on risky places and basing police work on smart uses of data can address the worst effects of disorder and crime while improving community relations and public safety. Topics include the role of big data; the evolution of modern policing; dealing with high-risk targets; designing, implementing, and evaluating risk-based policing strategies; and the role of multiple stakeholders in risk-based policing. The book also demonstrates how risk terrain modeling can be extended to provide a comprehensive view of prevention and deterrence

AbstractEvidence-based policing emphasizes the evaluation of interventions to create a catalogue of effective programs and practices. Program evaluation has primarily been considered the purview of academic researchers, with police agencies typically uninvolved in the evaluation of their own interventions. Scholars have recently advocated for police to take more ownership over program evaluation, often arguing for an increased role of three primary entities: embedded criminologists, police pracademics, and crime analysts. While an emerging body of literature has explored these entities individually, research has yet to explore the unique contributions each can make to police-led science. The current study is a survey of scholars who authored or co-authored one or more studies included in the evidence-based policing matrix. The authors explore four distinct research questions pertaining to police-led science. Findings suggest that embedded criminologists, police pracademics, and crime analysts may each have a unique role to play in promoting police-led science.

AbstractThe current study analyzes police use of force as a series of time‐bound transactions between officers, civilians, and bystanders. The research begins with a systematic social observation of use‐of‐force events recorded on police body‐worn cameras in Newark, New Jersey. Researchers measure the occurrence and time stamps for numerous participant physical and verbal behaviors. Data are converted into a longitudinal panel format measuring all observed behaviors in 5‐second intervals. Panel logistic regression models estimate the effect of each behavior on use of force in immediate and subsequent temporal periods. Findings indicate certain variables influence use of force at a distinct point in time, whereas others exert influence on use of force across multiple time periods. The most influential variables relate to authority maintenance theoretical constructs. This finding supports prior perspectives arguing that police use of force largely results from officer attempts to maintain constant authority over civilians during face‐to‐face encounters. Nonetheless, a range of additional variables reflecting procedural justice, civilian resistance, and bystander presence significantly affect when police use force during civilian encounters. Results provide nuance to theoretical frameworks considering use of force as resulting from the interplay between officer and civilian actions and reactions.

Background: Evaluations are routinely conducted by government agencies and research organizations to assess the effectiveness of technology in criminal justice. Interdisciplinary research methods are salient to this effort. Technology evaluations are faced with a number of challenges including (1) the need to facilitate effective communication between social science researchers, technology specialists, and practitioners, (2) the need to better understand procedural and contextual aspects of a given technology, and (3) the need to generate findings that can be readily used for decision making and policy recommendations. Objectives: Process and outcome evaluations of technology can be enhanced by integrating concepts from human factors engineering and information processing. This systemic approach, which focuses on the interaction between humans, technology, and information, enables researchers to better assess how a given technology is used in practice. Subjects: Examples are drawn from complex technologies currently deployed within the criminal justice system where traditional evaluations have primarily focused on outcome metrics. Although this evidence-based approach has significant value, it is vulnerable to fully account for human and structural complexities that compose technology operations. Conclusions: Guiding principles for technology evaluations are described for identifying and defining key study metrics, facilitating communication within an interdisciplinary research team, and for understanding the interaction between users, technology, and information. The approach posited here can also enable researchers to better assess factors that may facilitate or degrade the operational impact of the technology and answer fundamental questions concerning whether the technology works as intended, at what level, and cost.

AbstractGunshot detection technology (GDT) is expected to impact gun violence by accelerating the discovery and response to gunfire. GDT should further collect more accurate spatial data, as gunfire is assigned to coordinates measured by acoustic sensors rather than addresses reported via 9-1-1 calls for service (CFS). The current study explores the level to which GDT achieves these benefits over its first 5 years of operation in Kansas City, Missouri. Data systems are triangulated to determine the time and location gunfire was reported by GDT and CFS. The temporal and spatial distances between GDT and CFS are then calculated. Findings indicate GDT generates time savings and increases spatial precision as compared to CFS. This may facilitate police responses to gunfire events and provide more spatially accurate data to inform policing strategies. Results of generalized linear and multinomial logistic regression models indicate that GDT benefits are influenced by a number of situational factors.