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Sylvia Chenery

Neighborhood Watch or Home Watch is internationally regarded as the largest voluntary crime prevention activity in the world. It is typically citizen instigated and police facilitated, with local groups having substantial autonomy in the organization and leadership, some with access to support and materials from overarching national organizations, contingent upon adherence to basic common standards. The local group presents itself as a partnership of people coming together to try to make their community safer, and it is primarily seen as a scheme coordinated between local citizens and their police. The relative autonomy of local groups is reflected in a variety of working collaborations with local or municipal authorities, voluntary agencies, and private business. Neighborhood Watch aims to empower people to protect themselves and their properties and to reduce the fear of crime by means of improved home security, greater vigilance, increased guardianship, and reporting of incidents to the police, and by fostering a community spirit. A further aim of the organization is to improve police and community liaison by developing effective two-way communication processes by which Neighborhood Watch leaders can disseminate up-to-date information among the members. Examples of Neighborhood Watches are now to be found in many parts of the world, and while initially schemes were launched exclusively by the police, as time and the organization have progressed, active citizens are now often initiating the establishment and organization of their own schemes. The closer linkage between police and the Neighborhood Watch organizations is reflected in the fact that the United Kingdom’s Neighborhood Watch national headquarters is located within an operational police station.


Robert I. Mawby

While the term “defensible space” is widely referenced in literature on situational crime pre vention and Crime Prevention Through Environmental Design, it is commonly mentioned in passing, almost as an historical landmark, with its relationship to more recent work assumed rather than rigorously examined. Yet, Oscar Newman’s work bridged the gap between criminological theories and preventive approaches in the pre-1970s era and the more grounded and policy driven approaches that are common today. Consequently, this article looks at the context within which Newman developed his ideas and revisits his core work. It then considers the initial response from the criminology and planning communities, which focused on the methodological and theoretical weaknesses that undermined what were, essentially, a series of imaginative, exploratory propositions about the influence of design on crime patterns. In this sense, it is clear that Newman both provoked and inspired further research into the relationship between urban design and crime, and indeed, between crime, crime targets, and space, looking at the specific influence of design, technology, social engineering, and so on. Terms such as ownership, visibility, occupancy, accessibility, image, and juxtaposition, which Newman used, are now incorporated into more sophistical theories of situational crime prevention. This article thus offers a reanalysis of defensible space in the context of later refinements and the application of Newman’s ideas to current policies.


Fei Yang

Predictive policing, also known as crime forecasting, is a set of high technologies aiding the police in solving past crimes and pre-emptively fighting and preventing future ones. With the right deployment of such technologies, law enforcement agencies can combat and control crime more efficiently with time and resources better employed and allocated. The current practices of predictive policing include the integration of various technologies, ranging from predictive crime maps and surveillance cameras to sophisticated computer software and artificial intelligence. Predictive analytics help the police make predictions about where and when future crime is most likely to happen and who will be the perpetrator and who the potential victim. The underpinning logic behind such predictions is the predictability of criminal behavior and crime patterns based on criminological research and theories such as rational choice and deterrence theories, routine activities theory, and broken windows theory. Currently many jurisdictions in the United States have deployed or have been experimenting with various predictive policing technologies. The most widely adopted applications include CompStat, PredPol, HunchLab, Strategic Subject List (SSL), Beware, Domain Awareness System (DAS), and Palantir. The realization of these predictive policing analytics systems relies heavily on the technological assistance provided by data collection and integration software, facial/vehicle identification and tracking tools, and surveillance technologies that keep tabs on individual activities both in the physical environment and in the digital world. Some examples of these assisting technologies include Automatic License Plate Recognition (ALPR), Next-Generation Identification (NGI) System, the Global Positioning System (GPS), Automatic Vehicle Location (AVL), next-generation police body-worn cameras (BWC) with facial recognition and tracking functions, aerial cameras and unmanned aircraft systems, DeepFace, Persistent Surveillance Systems, Stingrays/D(i)RT-Box/International Mobile Subscriber Identity Catcher, SnapTrends that monitors and analyzes feeds on Twitter, Facebook, Instagram, Picasa, Flickr, and YouTube. This new fashion of using predictive analytics in policing has elicited extensive doubt and criticism since its invention. Whereas scholarly evaluation research shows mixed findings about how effectively predictive policing actually works to help reduce crime, other concerns center around legal and civil rights issues (including privacy protection and the legitimacy of mass surveillance), inequality (stratified surveillance), cost-effectiveness of the technologies, militarization of the police and its implications (such as worsened relationship and weakened trust between the police and the public), and epistemological challenges to understanding crime. To make the best use of the technologies and avoid their pitfalls at the same time, policymakers need to consider the hotly debated controversies raised in the evolution of predictive policing.