Valerie Spicer

A cellular automata model on residential migration in response to neighborhood social dynamics

Residential migration patterns result from complex processes involving households and their neighborhoods. Simulation models assist in understanding this relationship by contextualizing residential mobility within a theoretical framework. The objective of this study is to model these migration patterns created by the interaction between changes in the social structure of households and the positive or negative social attractors in the neighborhood. Specifically, this study links residential mobility to the dynamic interplay between the micro-environment existing within a household and the meso-environment that structures a neighborhood. The cellular automata model developed in this study incorporates transition rules which govern households in their decision to move. The results represented by a cellular grid demonstrate that residential mobility is significantly influenced by density rates, individual household factors and neighborhood attractors. Three contrasting scenarios are presented in this paper to illustrate the impact of occupancy, density, neighborhood social influence, and the effect of a conglomeration of negative social attractors in a neighborhood. Future iterations of this model will incorporate census and crime data in order to test whether the rules governing this model are an accurate reflection of residential mobility in a mid-sized Canadian city.

The social impact in a high-risk community: A cellular automata model

a b s t r a c t This research examines the spread of criminal behavior and hard drug consumption using a mathemat- ical approach called cellular automata (CA). This CA model is based on two behavioral concepts. Firstly, peer association impacts criminal involvement. Secondly, addiction can heighten criminal activity. The model incorporates four types of actors who interact in a high-risk social community and one interven- tion method. The actors exert a social influence on each other by encouraging or discouraging drug use and criminal behavior. The intervention method called Incapacitation has a probabilistic impact on the individuals in the model. The results identify the threshold where positive influences on a population reduce the number of high-rate offenders in the community. These results are discussed to further the knowledge about the social influences in a high-risk community and how these influences can effect decisions on offender management.

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.

Testing perception of crime in a virtual environment

Fear of crime is a central topic in the field of victimization. In particular, criminologists are interested in the environmental structures and cues that generate fear. Research has shown that fear of crime has a direct impact on pedestrian navigation through the urban setting. Most studies have used traditional methods such as surveys or interviews. Researchers have debated the methodological issues stemming from these methods. This article introduces two explorative studies which use a virtual environment (VE) as a research tool for the study of fear of crime. The benefits associated to using VEs in this field of research are discussed. The development, implementation and results of these two studies are presented. The limitations and future directions of VE experiments are discussed.

Testing Elderly People's Fear of Crime Using a Virtual Environment

The fear of crime refers to the fear of being a victim of potential crimes. This fear often restricts normal daily activities and lowers the quality of life. For elderly people, fear of crime has a practical effect on their activities. Thus, the study of the fear of crime has been one of the important subjects in the victimization study. However, since there was no common agreement on the definition of the fear of crime among researchers, the methodological issues of measuring the fear of crime have been debated for decades. The methods that are most frequently used in measuring fear of rime are victimization surveys and interviews. These methods have inherent limitations of measuring fear of crime particularly with elderly people. This paper explores a new way of measuring fear of crime using a virtual environment from the behavioural aspects. The case study shows the research experiments with the elderly people who make a choice of routes in the virtual environment that replicates the Vancouver Chinatown. The experimental results suggest that this new method of measuring fear of crime using a virtual environment has many benefits particularly when it is used with elderly people. The limitations of this method and the future research are discussed.

Crime Ridges: Exploring the Relationship between Crime Attractors and Offender Movement

In this paper we present a new approach in the analysis of crime patterns by creating a formal framework for merging the concepts of crime attractors and the pull of certain locations on offender movement. This directionality, inherent to city infrastructure, underlies the decision processes of offenders when choosing movement paths towards attractors. We explore the aggregate movement patterns of offenders within six municipalities of metropolitan Vancouver. In particular, this research focuses on the relationship between multiple strong crime attractors, offender movement and the formation of crime ridges. We use a visualization technique to show how the flow of offenders towards crime attractors creates associated crime ridges connecting the crime attractors.

Crime on the edges: patterns of crime and land use change

ABSTRACT Criminologists have long-known that different locations have varying levels of risk for criminal victimization. Based on the geometry of crime and its corresponding crime generators and crime attractors, edges (boundaries between relatively homogeneous neighborhoods) are locations with an elevated risk of criminal victimization. In this article, we investigate the importance of edges. We find that criminal victimization rates are 2–3 times on an edge compared to elsewhere. However, this effect decreases very quickly moving away from these locations, with the effect gone at 40 meters. This general effect is identified in a number of contexts and locations.

The edge effect: Exploring high crime zones near residential neighborhoods

Crime Pattern Theory offers a theoretical framework for a micro level explanation of the dynamics of crime in an urban environment. The research focuses on the novel use the concept of boundaries or edges to analyze micro level differences in crime in various urban neighborhoods. Edges are identified where there is dissimilarity between adjacent areas. Crime is more likely to occur along edges. Edges can be physical, social, temporal and economical or a product of these dimensions. This study compares crime data from the Municipality of Burnaby in British Columbia, Canada with patterns in land use data. Single family residential neighborhoods are constructed by joining adjacently zoned single family areas. The edges of these neighborhoods are the areas where the single family zoning changes to commercial, parks and higher density residential zoning The results finds crime is sixty four percent higher in these edges than in the interior of the neighborhoods. The results are discussed and future research proposed to repeat and enhance the model.

A Decision Support System for Crowd Control Using Agent-Based Modeling and Simulation

Crowd control has been one of the important responsibilities for law enforcement officers. Whether a crowdis formed for political reasons or sporting events, they can turn to be violent, disrupting public peace/order and damaging properties in a public place. Effective and efficient crowd control tactics can keep the safety of both the innocent public and the crowd who are involved with (violent) collective behaviours. In order to devise and test such tactics, a decision support system called SimCrowd Control has been developed using the technique of agent-based modeling and simulation (ABMS). The system employs a realistic crowd model developed based on social science research studies. At the early stage of the SimCrowd Control system, simple crowd control tactics were tested against the crowd model by simulating the Vancouver Stanley Cup Riot which happened in 2011. The limitations of the current system and future plans are discussed.

Bridging the perceptual gap: variations in crime perception of businesses at the neighborhood level

Current research on fear of crime reveals a recurrent theme of disorder in explanations of fear of crime and perceptions of security. This disorder is scalable, ranging from proximal cues associated with specific encounters between people or defined micro locations through to distal feelings of fear about areas, activity nodes, or major pathways. The research presented here compares two samples (n = 235) of businesses surveyed during the summer of 2012 in Grandview-Woodland, a diverse neighborhood, in the City of Vancouver, Canada. A visualization technique is presented to demonstrate how aggregate cognitive maps about perception of crime can be created and used by civic agencies when determining strategies aimed at reducing fear of crime. The results show that although both samples are taken from the same geographical neighborhood, their specific location within the community generates two very distinct perceptual patterns. Differences between the impact of proximal and distal cues on perception is explored. Other variations in perception are studied including differences between males and females, business owners and employees and those who have been victims of property crime versus personal crime. The results are presented and future research directions discussed.