Andrew A. Reid

Uncovering the Spatial Patterning of Crimes A Criminal Movement Model (CriMM)

Objectives: The main objective of this study was to see if the characteristics of offenders’ crimes exhibit spatial patterning in crime neutral areas by examining the relationship between simulated travel routes of offenders along the physical road network and the actual locations of their crimes in the same geographic space. Method: This study introduced a Criminal Movement model (CriMM) that simulates travel patterns of known offenders. Using offenders’ home locations, locations of major attractors (e.g., shopping centers), and variations of Dijkstra’s shortest path algorithm we modeled the routes that offenders are likely to take when traveling from their home to an attractor. We then compare the locations of offenders’ crimes to these paths and analyze their proximity characteristics. This process was carried out using data on 7,807 property offenders from five municipalities in the Greater Vancouver Regional District (GVRD) in British Columbia, Canada. Results: The results show that a great proportion of crimes tend to be located geographically proximal to the simulated travel paths with a distance decay pattern characterizing the distribution of distance measures. Conclusion: These results lend support to Crime Pattern Theory and the idea that there is an underlying pattern to crimes in crime neutral areas.

Bars on blocks: A cellular automata model of crime and liquor licensed establishment density

Criminologists have extensively researched the problems generated by licensed establishments. Violent offending and disorderly behavior resulting from pubs, taverns, dance clubs and bars are of particular interest to this field of study. The relative density of these liquor establishments has been found to be associated with the level of violence and disorder in surrounding areas. A complex systems approach can be used to further understand the dynamic interplay between licensed establishments, violent offending and disorder, and urban planning decisions. The model presented here utilizes cellular automata as the mathematical framework to view the varying impact of liquor licensing density on crime. This study uses a sample of liquor establishments and crime data from the City of Vancouver in British Columbia. The cellular automata model incorporates transition rules which govern the change of city blocks from low-risk blocks to high-risk blocks. The results represented by a 50 50 cellular grid show that high-risk blocks multiply when liquor licenses are grouped. Two scenarios are presented to contrast the impact of grouping high-risk blocks which contain more liquor establishments and dispersing such blocks. A third scenario demonstrates how increasing the positive influence in a grouped scenario stops high-risk blocks from taking over the entire grid. Future iterations of this model will incorporate census data, public transportation data, land use data and entertainment districts from other cities to further analyze the effect of licensed establishments on the distribution of crime. 2012 Elsevier Ltd.

The strongest does not attract all but it does attract the most - evaluating the criminal attractiveness of shopping malls using fuzzy logic

Crime attractors are locations e.g. shopping malls that attract criminally motivated offenders because of the presence of known criminal opportunities. Although there have been many studies that explore the patterns of crime in and around these locations, there are still many questions that linger. In recent years, there has been a growing interest to develop mathematical models in attempts to help answer questions about various criminological phenomena. In this paper, we are interested in applying a formal methodology to model the relative attractiveness of crime attractor locations based on characteristics of offenders and the crime they committed. To accomplish this task, we adopt fuzzy logic techniques to calculate the attractiveness of crime attractors in three suburban cities in the Metro Vancouver region of British Columbia, Canada. The fuzzy logic techniques provide results comparable with our real-life expectations that offenders do not necessarily commit significant crimes in the immediate neighbourhood of the attractors, but travel towards it, and commit crimes on the way. The results of this study could lead to a variety of crime prevention benefits and urban planning strategies.

A Case Study of the Transformative Effect of Peer Injection Drug Users in the Downtown Eastside of Vancouver, Canada

Cette étude fut effectuée pour explorer la manière dont les pairs interviennent pour façonner les réseaux sociaux et saisir l’effet transformateur des interventions menées par des pairs dans le cadre de programmes locaux d’échange de seringues et au sein d’un établissement d’injection supervisé à Vancouver, au Canada. Des entrevues semi-structurées furent menées auprès de pairs bénévoles pendant leurs travaux routiniers. Les entrevues furent analysées de façon thématique au moyen de deux méthodes d’analyse de codage. Les résultats suggèrent que les pairs jouaient d’importants rôles en matière d’éducation et de sécurité et qu’ils pouvaient changer le comportement, l’attitude et l’intention d’utilisateurs de drogues injectables dans la région Downtown Eastside de la ville. De plus, les pairs ont pu rejoindre les personnes qui hésitaient à chercher de l’aide médicale, un logement ou des services de prévention. Les pairs servent d’agents de changement dans le Downtown Eastside permettant de distribuer des renseignements et d’offrir des outils en réduction de risque aux personnes marginalisées.

The Potential Role for Supervised Injection Facilities in Canada’s Largest City, Toronto:

Supervised injection facilities (SIFs) or supervised consumption rooms are a component of harm reduction strategies that attempt to reduce drug overdoses and risky injection behaviors among injection drug users. The purpose of this study is to determine whether expanding SIFs into the City of Toronto, Ontario, would be a fiscally responsible decision. By analyzing secondary data gathered in 2013, this article relies on mathematical models to estimate the number of new HIV and hepatitis C virus infections prevented as a result of SIF locations in Toronto. After factoring in the costs associated with SIFs, the models produce cost–benefit and cost-effectiveness outputs. With very conservative estimates, it is predicted that establishing SIF locations in Toronto is cost effective with an average benefit–cost ratio of 1:1.2 for the first two facilities based on the sensitivity analysis at 30% sharing rate. Consequently, funding SIFs in Canada’s largest city appears to be an efficient and effective use of financial resources in the public health domain with cost savings in excess of CAN

Exploring the structural characteristics of social networks in a large criminal court database

728,620 per year for the first two facilities.

A Computational Model for Predicting the Location of Crime Attractors on a Road Network

Social network analysis refers to the study of structural aspects in networks to understand and interpret social entities and related patterns. This form of research has proven to be very useful in the study of illicit networks. To date, however, large criminal court datasets that include a comprehensive scope of cases have yet to be explored. The current work begins to explore this potential by applying social network analysis methods to CourBC-an extensive multi-year database of adult criminal court records in the Province of British Columbia, Canada. Through a variety of network analysis methods, the authors explore the topology and structure of the database. Results demonstrate that the structure of the dataset is similar to that of other large criminal justice datasets yet there are some notable differences. The potential for this type of data in illicit network research and some specific areas for continued research in the field are discussed.

Interdisciplinary teaching and learning in computing science: three years of experience in the MoCSSy program

Crime Pattern Theory argues that offenders often commit their crimes at major criminal attractors or along the routes that lead to these attractors from other activity nodes in their awareness space. Without knowledge about each offenders awareness space, however, it is not possible to know the nodes they travel to. In this paper, it is assumed that each offender commits their crime along the way to a particular end-destination that they frequent. It thus follows that, for each crime location of an offender, there is an activity path nearby which starts at the offenders home location and ends at a nearby activity node. Since the activity node is not known, but the crime and home locations of offenders are, the method presented in this paper determines the locations of the attractors by statistically extending the path along the road-network from the offenders home location to their crime location. Each offenders movement pattern is based on probabilities assigned to each road segment that are determined by examining the angle of the road in relation to an offenders journey from home, and how frequently the road segment is taken by commuters on the road network. After generating paths for all offenders, attractor locations are identified by calculating the most frequently travelled nodes in the network. The aim of the model is to investigate the influence that crime attractors and other major activity nodes have on the locations of crimes to better understand the target selection behaviour of known offenders.

Celerity in the Courts: The Application of Fuzzy Logic to Model Case Complexity of Criminal Justice Systems

Simon Fraser University introduced the Modelling of Complex Social Systems Program (MoCSSy) as an interdisciplinary research program aimed at complex societal issues. Since its inception, the MoCSSy program has engaged a number of students from computing science, who worked on problems brought by their peers in fields such as obesity and criminology. In this paper, we introduce the organization and structure of MoCSSy, pointing to the importance of computing science in meeting the specific goals and objectives of the Program. Through an analysis of surveys completed with MoCSSy students, we conducted a preliminary assessment on the impact of the program for computing science majors and non majors. We found that the program successfully achieved many of its goals, as computing science majors and non-majors appreciated working with each other and made academic contributions that would not have been possible without this synergy. Finally, we analyze current challenges and identify a strategy for the way forward.

A cost-benefit/cost-effectiveness analysis of proposed supervised injection facilities in Ottawa, Canada

There are many complex phenomena in the criminal justice system that are difficult to understand because they contain features or concepts that are fuzzy in nature; in other words, it is difficult to assign a crisp value or label to them. Fuzzy Logic is a mathematical concept developed to deal with these very problems. Fuzzy Logic techniques are capable of dealing with approximate facts and partial truths, and not just precise values to model complex issues and processes. While Fuzzy Logic has been used in a number of criminology and criminal justice research efforts, it has not been applied to issues in the criminal court system. Case management is critical to ensure court systems run efficiently and understanding case complexity is an important part of that task. In this chapter we propose Fuzzy Logic as a technique that could be used to model the complexity of cases using general characteristics that are known before cases enter the court system. Using the adult criminal court system in British Columbia as an example, we propose a model that could predict case complexity immediately following the laying of charges by Crown prosecutors. By understanding case complexity a priori, courts may be able to enhance early case consideration procedures such as screening and scheduling to create a more effective and efficient justice system.