Suchergebnisse

The study of how the environment, local geography, and physical locations influence crime has a long history that stretches across a number of research traditions. These include the neighborhood-effects approach developed by the Chicago school of sociology in the 1920s; modern environmental criminology that explains the geographic distribution of crime; the criminology of place, which focuses on crime rates at specific places over time; and a newer approach that attends to the perception of crime and disorder in communities. Aided by new mobile and digital technologies as well as improved data reporting in recent decades, research in environmental criminology has developed at a rapid pace within each of these approaches. Despite these advances, research in the subfield of environmental criminology remains fragmented, and competing theories are often kept apart.

The Iraqi Insurgency (2003-2011) has commonly been characterized as demonstrating the tendency for violence to cluster and diffuse at the local level. Recent research has demonstrated that insurgent attacks in Iraq cluster in time and space in a manner similar to that observed for the spread of a disease. The current study employs a variety of approaches common to the scientific study of criminal activities to advance our understanding of the correlates of observed patterns of the incidence and contagion of insurgent attacks. We hypothesize that the precise patterns will vary from one place to another, but that more attacks will occur in areas that are heavily populated, where coalition forces are active, and along road networks. To test these hypotheses, we use a fishnet to build a geographical model of Baghdad that disaggregates the city into more than 3000 grid cell locations. A number of logistic regression models with spatial and temporal lags are employed to explore patterns of local escalation and diffusion. These models demonstrate the validity of arguments under each of three models but suggest, overall, that risk heterogeneity arguments provide the most compelling and consistent account of the location of insurgency. In particular, the results demonstrate that violence is most likely at locations with greater population levels, higher density of roads, and military garrisons. Adapted from the source document.

AbstractCounterfeits harm consumers, governments, and intellectual property holders. They accounted for 3.3% of worldwide trades in 2016, having an estimated value of $509 billion in the same year. Estimations in the literature are mostly based on border seizures, but in this paper, we examined openly labeled counterfeits on darknet markets, which allowed us to gather and analyze information from a different perspective. Here, we analyzed data from 11 darknet markets for the period Jan-2014 and Sep-2015. The findings suggest that darknet markets harbor similar counterfeit product types to those found in seizures but that the share of watches is higher while the share of electronics, clothes, shoes, and Tobacco is lower on darknet markets. Also, darknet market counterfeits seem to have similar shipping origins as seized goods, with some exceptions, such as a relatively high share (5%) of dark market counterfeits originating from the US. Lastly, counterfeits on dark markets tend to have a relatively low price and sales volume. However, based on preliminary estimations, the equivalent products on the surface web appear to be advertised for a multiple of the prices found for darknet markets. We provide some suggestions on how information about darknet market counterfeits could be used by companies and authorities for preventative purposes, showing that insight gathering from the dark web is valuable and could be a cost-effective alternative (or compliment) to border seizures. Thus, monitoring darknet markets can help us understand the counterfeit landscape better.

AbstractCrisis and disruption are often unpredictable and can create opportunities for crime. During such times, policing may also need to meet additional challenges to handle the disruption. The use of social media by officials can be essential for crisis mitigation and crime reduction. In this paper, we study the use of Twitter for crime mitigation and reduction by UK police (and associated) agencies in the early stages of the Covid-19 pandemic. Our findings suggest that whilst most of the tweets from our sample concerned issues that were not specifically about crime, especially during the first stages of the pandemic, there was a significant increase in tweets about fraud, cybercrime and domestic abuse. There was also an increase in retweeting activity as opposed to the creation of original messages. Moreover, in terms of the impact of tweets, as measured by the rate at which they are retweeted, followers were more likely to 'spread the word' when the tweet was content-rich (discussed a crime specific matter and contained media), and account holders were themselves more active on Twitter. Considering the changing world we live in, criminal opportunity is likely to evolve. To help mitigate this, policy makers and researchers should consider more systematic approaches to developing social media communication strategies for the purpose of crime mitigation and reduction during disruption and change more generally. We suggest a framework for so doing.

AbstractThis paper explores ways in which civil conflict can be simulated using numerical methods. A general two-party model of conflict is developed by extending an approach proposed by [Christia, F., (2012), Alliance Formation in Civil Wars, Cambridge University Press, New York], which is based on a metric of the 'relative power' that exists between the state and a rebel group. Various definitions of relative power are considered and one of these is chosen to illustrate different types of two-sided armed conflict, namely direct-fire, guerrilla and asymmetric warfare. The additional suggestion of Christia that random or stochastic events can lead to unexpected conflict outcomes is also further extended in this paper. The inclusion in the model of terms describing concurrent rebel recruitment of civilians and state deployment of troops are then described. Examples are presented for various hypothetical cases. It is demonstrated that numerical simulation techniques have great potential for modelling civil war. The Christia approach is shown to provide an excellent basis from which numerical models of civil conflict can be built and from which the progress of a conflict can usefully be visualised graphically.

Abstract
In many disciplines, there is a wealth of primary evaluation research on what works, and systematic reviews that synthesize that evidence. This is, of course, extremely positive. However, the sheer scale of the information and the way in which it is indexed and presented can mean that it is difficult for practitioners to locate the best available evidence. For this reason, in health, education, and other disciplines, using techniques from information science, researchers have systematically assembled databases such as those hosted on healthevidence.org and educationendowmentfoundation.org which bring together the most reliable evidence. Hitherto, no such database has existed for crime and criminal justice interventions. This article sets out some of challenges and early findings of one exercise which aims to produce such a database, being completed as part of the What Works Centre for Crime Reduction initiative in collaboration with the College of Policing.

Riots are extreme events, and much of the early research on rioting suggested that the decision making of rioters was far from rational and could only be understood from the perspective of a collective mind. In the current study, we derive and test a set of expectations regarding rioter spatial decision making developed from theories originally intended to explain patterns of urban crime when law and order prevail—crime pattern and social disorganization theory—and consider theories of collective behavior and contagion. To do this, we use data for all riot‐related incidents that occurred in London in August 2011 that were detected by the police. Unlike most studies of victimization, we use a random utility model to examine simultaneously how the features of the destinations selected by rioters, the origins of their journeys, and the characteristics of the offenders influence offender spatial decision making. The results demonstrate that rioter target choices were far from random and provide support for all three types of theory, but for crime pattern theory in particular. For example, rioters were more likely to engage in the disorder close to their home location and to select areas that contained routine activity nodes and transport hubs, and they were less likely to cross the Thames River. In terms of contagion, rioters were found to be more likely to target areas that had experienced rioting in the previous 24 hours. From a policy perspective, the findings provide insight into the types of areas that may be most vulnerable during riots and why this is the case, and when particular areas are likely to be at an elevated risk of this type of disorder.

AbstractWith the increasing prevalence of police interventions implemented in micro hot-spots of crime, the accuracy with which officer foot patrols can be measured is increasingly important for the robust evaluation of such strategies. However, it is currently unknown how the accuracy of GPS traces impact upon our understanding of where officers are at a given time and how this varies for different GPS refresh rates. Most existing studies that use GPS data fail to acknowledge this. This study uses GPS data from police officer radios and ground truth data to estimate how accurate GPS data are for different GPS refresh rates. The similarity of the assumed paths are quantitatively evaluated and the analysis shows that different refresh rates lead to diverging estimations of where officers have patrolled. These results have significant implications for the measurement of police patrols in micro-places and evaluations of micro-place based interventions.

AbstractThe Internet of Things (IoT) is considered the next technological revolution. IoT devices include once everyday objects that are now internet connected, such as smart locks and smart fridges, but also new types of devices to include home assistants. However, while this increased interconnectivity brings considerable benefits, it can and does increase people's exposure to crime risk. This is particularly the case as most devices are developed without security in mind. One reason for this is that there is little incentive for manufacturers to make devices secure by design, and the costs of so doing do not encourage it. The principle aim of the current paper was to estimate the extent to which consumers are willing to pay for improved security in internet connected products. The second aim was to examine whether this is conditioned by their exposure to security-related information. Using an experimental design, and a contingent valuation method, we find that people are willing to pay for improved security and that for some devices, this increases if they are exposed to information about security prior to stating their willingness to pay. The implications of our findings for industry and the secure by design agenda are discussed.

Many countries have become increasingly aggressive in their efforts to stop unauthorized migration, but most evidence suggests that immigration enforcement policies do not effectively deter migrants. We draw on literature from social psychology, specifically the dual-system model of decision-making, which differentiates between judgments that are subject to considerations of risks and costs and judgments that are "non-consequentialist." Non-consequentialist decision-making is founded in moral intuition and rejects rational considerations of costs and benefits. This mental process would render the deterrence tools of the state powerless. We posit that some, but not all, forms of unauthorized migration will invoke non-consequentialist decision-making. When considering semi-legal strategies, which individuals may perceive as "bending the law" rather than breaking it, aspiring migrants are likely to weigh the risks and costs of enforcement policies. Meanwhile, when considering fully illegal migration strategies, aspiring migrants will prioritize moral considerations for breaking the law rather than the consequences of breaking the law. We find evidence for our theory using original population-based list experiments along with focus groups of aspiring migrants in an origin country.

AbstractMany countries have become increasingly aggressive in their efforts to stop unauthorized migration, but most evidence suggests that immigration enforcement policies do not effectively deter migrants. We draw on literature from social psychology, specifically the dual-system model of decision-making, which differentiates between judgments that are subject to considerations of risks and costs and judgments that are "non-consequentialist." Non-consequentialist decision-making is founded in moral intuition and rejects rational considerations of costs and benefits. This mental process would render the deterrence tools of the state powerless. We posit that some, but not all, forms of unauthorized migration will invoke non-consequentialist decision-making. When considering semi-legal strategies, which individuals may perceive as "bending the law" rather than breaking it, aspiring migrants are likely to weigh the risks and costs of enforcement policies. Meanwhile, when considering fully illegal migration strategies, aspiring migrants will prioritize moral considerations for breaking the law rather than the consequences of breaking the law. We find evidence for our theory using original population-based list experiments along with focus groups of aspiring migrants in an origin country.