ROLE OF THE STREET NETWORK IN BURGLARS' SPATIAL DECISION‐MAKING*

Explaining why crime is spatially concentrated has been a central theme of much criminological research. Although various theories focus on neighborhood social processes, environmental criminology asserts that the physical environment plays a central role by shaping people's activity patterns and the opportunities for crime. Here, we test theoretical expectations regarding the role of the road network in shaping the spatial distribution of crime and, in contrast to prior research, disentangle how it might influence offender awareness of criminal opportunities and the supply of ambient guardianship. With a mixed logit (discrete choice) model, we use data regarding (N = 459) residential burglaries (for the first time) to model offender spatial decision‐making at the street segment level. Novel graph theory metrics are developed to estimate offender awareness of street segments and to estimate levels of ambient guardianship, distinguishing between local and nonlocal guardianship. As predicted by crime pattern theory, novel metrics concerning offender familiarity and effort were significant predictors of residential burglary location choices. And, in line with Newman's (1972) concept of defensible space, nonlocal (local) pedestrian traffic was found to be associated with an increase (decrease) in burglary risk. Our findings also demonstrate that “taste” preferences vary across offenders, which presents a challenge for future research to explain.     

Guardianship and residential burglary

Guardianship is a key element in the routine activities approach to understanding crime. This paper examines the effects of guardianship on residential burglary. Several features distinguish these analyses from prior work: 1) both primary and proxy guardianship are included: 2) a more direct indicator of primary guardianship is used; and 3) the effects of guardianship on both the initial risk of burglary and the probability that the crime will be completed are examined. The findings suggest that the effects of guardianship on residential burglary may have been underestimated in prior research. The analyses also show that a complete understanding of the effects of guardianship—especially proxy guardianship—on the entire burglary process will require simultaneous consideration of victimization and offending perspectives.     

Behavioural case linkage with solved and unsolved crimes

Offender behaviour is used to distinguish between crimes committed by the same person (linked crimes) and crimes committed by different people (unlinked crimes) through behavioural case linkage. There is growing evidence to support the use of behavioural case linkage by investigative organisations such as the police, but this research is typically limited to samples of solved crime that do not reflect how this procedure is used in real life. The current paper extends previous research by testing the potential for behavioural case linkage in a sample containing both solved and unsolved crimes. Discrimination accuracy is examined across crime categories (e.g. a crime pair containing a car theft and a residential burglary), across crime types (e.g. a crime pair containing a residential burglary and a commercial burglary), and within crime types (e.g. a crime pair containing two residential burglaries) using the number of kilometres (intercrime distance) and the number of days (temporal proximity) between offences to distinguish between linked and unlinked crimes. The intercrime distance and/or the temporal proximity were able to achieve statistically significant levels of discrimination accuracy across crime categories, across crime types, and within crime types as measured by Receiver Operating Characteristic (ROC) analysis. This suggests that behavioural case linkage can be used to assist the investigation, detection and prosecution of prolific and versatile serial offenders.     

GENERATIVE EXPLANATIONS OF CRIME: USING SIMULATION TO TEST CRIMINOLOGICAL THEORY*

This study demonstrates that computational modeling and, in particular, agent‐based modeling (ABM) offers a viable compatriot to traditional experimental methodologies for criminology scholars. ABM can be used as a means to operationalize and test hypothetical mechanisms that offer a potential explanation for commonly observed criminological phenomena. This study tests whether the hypothesized mechanisms of environmental criminology are sufficient to produce several commonly observed characteristics of crime. We present an ABM of residential burglary, simulating a world inhabited by potential targets and offenders who behave according to the theoretical propositions of environmental criminology. A series of simulated experiments examining the impact of these mechanisms on patterns of offending are performed. The outputs of these simulations then are compared with several well‐established findings derived from empirical studies of residential burglary, including the spatial concentration of crime, repeat victimization, and the journey to crime curve. The results from this research demonstrate that the propositions of the routine activity approach, rational choice perspective, and crime pattern theory provide a viable generative explanation for several independent characteristics of crime.     

Using data on offender mobility in ecological research

This article presents some findings on neighborhood structure, police recorded crime, and offender mobility for the city of Utrecht, the Netherlands. The highest crime rates were found in the inner-city neighborhoods. The findings further show that the occurrence of different types of petty crime in residential neighborhoods is associated with different neighborhood characteristics. It was found that offenders reside predominantly in lower-social status neighborhoods. Using data on offender mobility it is shown that violent crime and vandalism are the more locally committed crimes, as compared to residential burglary and other property crime. Finally, it is proposed that data on offender mobility can be used to gain more insight into the link between certain neighborhood characteristics and crime.     

INFORMAL SURVEILLANCE AND STREET CRIME: A COMPLEX RELATIONSHIP*

The systemic crime model predicts that informal surveillance of space reduces street crime. Conversely, community decline theory posits that street crime reduces informal surveillance by increasing residents' perception of risk and fear. Moreover, functions of crime theory suggests that some types of crime may increase surveillance. Using data for 100 urban neighborhoods, the analysis examines these predictions and disentangles reciprocal effects. Baseline recursive equations indicate that informal surveillance is inversely associated with robbery/stranger assault, and that robbery/stranger assault is inversely associated with informal surveillance. In contrast, burglary rates are not affected by informal surveillance, but burglary has a positive effect on surveillance when robbery/stranger assault is controlled. Simultaneous equations indicate that robbery/stranger assault has a moderately strong inverse effect on informal surveillance, and that it is mediated by residents' perceptions of risk. When risk perception is controlled, informal surveillance has an inverse effect on robbery/stranger assault. The latter analysis also indicates that burglary increases surveillance, suggesting that some types of crime serve positive functions. The results, therefore, lend support to systemic, community decline, and functions of crime theory, and they suggest that the relationship between informal surveillance and crime is complex. Implications for community crime research are discussed.     

Risk-based crime statistics: A forecasting comparison for burglary and auto theft

A major criticism of official statistics on crime is that they use inappropriate bases for computing rates. Here we investigate whether computing crime rates that contain in their denominators the number of exposures to risk of a specific event (e.g., residential burglary and auto theft) provides more accurate forecasts than employing the traditional FBI denominators as a base (e.g., the number of auto thefts and burglaries per 100, 000 persons living in the United States). Single equation, macrodynamic structural models are fitted to both the “traditional” and “alternative” forms of computing auto theft and burglary rates over the twenty-seven-year period from 1947–1974, in order to determine how well they perform on statistical and substantive grounds over the estimation period. Ex-post forecasts of the 1975–1979 observed crime rates, used to gauge the accuracy of these models, reveal few differences between the two kinds of rates in terms of how well they forecast. Both types of rates forecast well with the exogenous variables employed here and lead to similar substantive conclusions. The forecasts of the “traditional” rates are consistently, but only slightly, more accurate than those of the “alternative” rates (in most cases the differences are less than 1 percent). It is argued that the criticism of official data may be overstated and that little benefit accrues from the modification of the rate base for some purposes.     

From research to policy: Preventing residential burglary through a systems approach

This paper isolates crime prevention policy implications which stem from a series of interrelated environmental studies of residential burglaries. A number of crime prevention strategies are developed using a systems approach. It is argued that changes made to the environments of individuals, groups, communities, organizations, and society can achieve lower risks of residential burglary victimization.     

MACRO-MICRO INTEGRATION IN THE STUDY OF VICTIMIZATION: A HIERARCHICAL LOGISTIC MODEL ANALYSIS ACROSS SEATTLE NEIGHBORHOODS*

Recent contextual analyses of victimization survey data are extended by application of hierarchical logistic model techniques. Using a multi-stage sample of 5,090 Seattle residents, we estimate models for individuals' risks of violent crime and burglary victimization as a function of both individual crime opportunity factors (routine activity and personal lifestyle) and contextual indicators of neighborhood social disorganization (neighborhood incivilities on conditions of disorder, ethnic heterogeneity, and neighborhood density in terms of both residents and strangers). Strong contextual direct effects of density, disorder, and heterogeneity are observed for violent and or burglary risks. Further, the hierarchical method used here provides a richer type of contextual analysis, indicating that neighborhood factors also “condition” the impact of crime opportunity factors for risk of both violent and burglary victimization. Implications for theoretical integration, victimization prevention strategies, and crime control policies are discussed.     

Predicting Initiator and Near Repeat Events in Spatiotemporal Crime Patterns: An Analysis of Residential Burglary and Motor Vehicle Theft

Near repeat analysis has been increasingly used to measure the spatiotemporal clustering of crime in contemporary criminology. Despite its predictive capacity, the typically short time frame of near repeat crime patterns can negatively affect the crime prevention utility of near repeat analysis. Thus, recent research has argued for a greater understanding of the types of places that are most likely to generate near repeat crime patterns. The current study contributes to the literature through a spatiotemporal analysis of residential burglary and motor vehicle theft in Indianapolis, IN. Near Repeat analyses were followed by multinomial logistic regression models to identify covariates related to the occurrence of initiator (the first event in a near repeat chain) and near repeat (the subsequent event in a near repeat chain) events. The overall findings provide additional support for the argument that neighborhood context can influence the formation and context of spatiotemporal crime patterns.     

Permeability and Burglary Risk: Are Cul-de-Sacs Safer?

That crime is concentrated in space is now accepted as commonplace. Explanations for why it clusters at particular locations are various reflecting the range of factors which are held to influence crime placement. In this article, we focus on the role of the permeability of the street network on the location of crime. We first review the research conducted hitherto, summarising the different approaches to analysis and the findings that have so far emerged. Then we present original analyses conducted at the street segment level to examine the issues at hand. In contrast to much of the prior research, in this study we examine the patterns for a large study area in which there is considerable variation in street network configuration. Moreover, and in contrast to all of the previous research, the approach to analysis takes into account the multi-level structure of the data analysed. The findings demonstrate that increased permeability is associated with elevated burglary risk, that burglary risk is lower on cul-de-sacs (particularly those that are sinuous in nature), and that the risk of burglary is higher on more major roads and those street segments that are connected to them. In the conclusion of the paper we outline an agenda for future research.     

STREET NETWORK STRUCTURE AND CRIME RISK: AN AGENT‐BASED INVESTIGATION OF THE ENCOUNTER AND ENCLOSURE HYPOTHESES

Street networks shape day‐to‐day activities in complex ways, dictating where, when, and in what contexts potential victims, offenders, and crime preventers interact with one another. Identifying generalizable principles of such influence offers considerable utility to theorists, policy makers, and practitioners. Unfortunately, key difficulties associated with the observation of these interactions, and control of the settings within which they take place, limit traditional empirical approaches that aim to uncover mechanisms linking street network structure with crime risk. By drawing on parallel advances in the formal analyses of street networks and the computational modeling of crime events interactions, we present a theoretically informed and empirically validated agent‐based model of residential burglary that permits investigation of the relationship between street network structure and crime commission and prevention through guardianship. Through the use of this model, we explore the validity of competing theoretical accounts of street network permeability and crime risk—the encounter (eyes on the street) and enclosure (defensible space) hypotheses. The results of our analyses provide support for both hypotheses, but in doing so, they reveal that the relationship between street network permeability and crime is likely nonlinear. We discuss the ramifications of these findings for both criminological theory and crime prevention practice.     

Value of DNA evidence in detecting crime

DNA material is now collected routinely from crime scenes for a wide range of offences and the timely processing of the DNA is seen as key to its success in investigating and detecting crime. An analysis of DNA material recovered from the volume crime offences of residential burglary, commercial burglary, and theft of motor vehicle in Northamptonshire, U.K., in 2004 has enabled the DNA to be categorized into seven sources. Further analysis using a logistical regression has revealed a number of predictors, other than timeliness, that greatly influence whether the DNA material recovered from a crime scene enables the crime to be detected. The results indicate that a number of these predictors are of statistical significance and may be just as relevant in determining whether DNA successfully detects the crime as the timeliness of the processing of the DNA material. The most significant predictor was found to be investigating officer accreditation with location, quantity, and type of DNA material at the crime scene also being relevant. Accreditation of the Crime Scene Examiner recovering the DNA material was found not to be significant. Consideration is given to where further emphasis is needed by the U.K. police service to maximize the opportunities to detect volume crime with DNA.     

The value of DNA material recovered from crime scenes

Abstract:  DNA material is now collected routinely from crime scenes for a wide range of offenses and its timely processing is acknowledged as a key element to its success in solving crime. An analysis of the processing of approximately 1500 samples of DNA material recovered from the property crime offenses of residential burglary, commercial burglary, and theft of motor vehicle in Northamptonshire, U.K. during 2006 identified saliva and cigarette ends as the main sources of DNA recovered (approximately 63% of samples) with blood, cellular DNA, and chewing gum accounting for the remainder. The conversion of these DNA samples into DNA profiles and then into matches with offender profiles held on the U.K. National DNA database is considered in terms of the ease with which Crime Scene Examiners can recover DNA rich samples of different sources, the location of the DNA at the crime scene, and its mobility. A logistical regression of the DNA material recovered has revealed a number of predictors, other than timeliness, that greatly influence its conversion into a DNA profile. The most significant predictor was found to be Crime Scene Examiner accreditation with offense type and DNA sample condition also being relevant. A similar logistical regression of DNA samples profiled that produced a match with an offender on the U.K. National DNA database showed no significance with any of the predictors considered.     

RECIDIVIST IMPACTS OF DIFFERENTIAL SENTENCING PRACTICES FOR BURGLARY OFFENDERS

The research reported here attempts to examine the recidivist impacts of probationary sentences versus incarceration. Statistically controlled comparisons were run on a probability sample of 100 offenders sentenced for residential or commercial burglary convictions in 1971. Subsequent arrest, conviction. and imprisonment data were gathered from official agency records through March of 1975. The results of this study indicate that for persons sentenced for burglary the likelihood of subsequent conviction for a felony or for any crime is less for probationer offenders than for any other sentence type. The strongest predictors of recidivism (defined as subsequent conviction for crime) were age, previous incarceration experience, and sentence type. Length of sentence. type of release, and number of previous arrests were essentially unrelated to subsequent rates of recidivism.     

FAMILY MATTERS: EFFECTS OF FAMILY MEMBERS’ RESIDENTIAL AREAS ON CRIME LOCATION CHOICE*

According to crime pattern theory, offenders are likely to select crime locations within their awareness space. Previous studies have shown that offenders often commit crimes within their current and former residential areas and in areas they previously targeted. However, offenders’ awareness spaces obviously consist of more locations that potentially influence their crime location choices. This study examines the importance of the residential areas of offenders’ family members. Most offenders visit their families at least occasionally and consequently get familiar with the areas in which their families live. It is hypothesized that family members’ residential areas are at increased risk of being targeted. Unique data were used to reconstruct residential histories of the parents, siblings, and children of 7,910 offenders who committed 19,420 offenses. The results of discrete spatial choice models showed that residential areas of family members are indeed at increased risk of being targeted. Current familial residential areas had stronger and more consistent effects than had former familial residential areas. Effects were strongest for the residential areas of offenders’ children compared with those of their parents and siblings. The residential areas of male and female family members affected the crime location choices of male and female offenders equally.     

POVERTY, INCOME INEQUALITY, AND COMMUNITY CRIME RATES

This paper examines the relationship between crime rates and aggregate economic conditions for 57 small social areas. The principal analyses address a continuing controversy—are community crime rates associated with absolute poverty, relative poverty (i.e., income inequality), or both. Using victimization data from 57 small residential neighborhoods, the analyses examine the association between absolute and relative poverty and rates of violent crime and burglary. The findings indicate that absolute poverty is more strongly associated with neighborhood crime rates, although the relationship is conditional on the type of crime considered. The implications of the findings are discussed within a perspective of community social control.     

The effect of temporary residences on burglary: A test of criminal opportunity theory

Previous work testing the criminal opportunity/routine activities theory of burglary has been marked by three recurrent problems: (1) a neglect of testing the theory in rural areas (2) the use of indicators which confound opportunity with disorganization effects (3) failure to control for alternative theories of burglary. The present paper contributes to the literature by correcting these shortcomings. The results of a multiple regression analysis of county level data from Michigan indicate that the greater the criminal opportunity, the greater the rate of burglary. These results are independent of indicators taken from economic strain and social disorganization theories. The model explains 69% of the variance in burglary rates overall and 84% of the variance in rural counties. While there may be higher levels of social cohesion and lower anonymity in rural areas, these factors are not sufficient to offset the influence of criminal opportunity.     

EXTENDING SOCIAL DISORGANIZATION THEORY: MODELING THE RELATIONSHIPS BETWEEN COHESION,DISORDER, AND FEAR*

In this study, we build on recent social disorganization research, estimating models of the relationships between disorder, burglary, cohesion, and fear of crime using a sample of neighborhoods from three waves of the British Crime Survey. The results indicate that disorder has an indirect effect on burglary through fear and neighborhood cohesion. Although cohesion reduces disorder, nonrecursive models show that disorder also reduces cohesion. Part of the effect of disorder on cohesion is mediated by fear. Similar results are obtained in nonrecursive burglary models. Together, the results suggest a feedback loop in which decreases in neighborhood cohesion increase crime and disorder, increasing fear, in turn, further decreasing cohesion.     

Predicting Property Crime Risk: an Application of Risk Terrain Modeling in Vancouver,Canada

Research on the spatial dimension of crime has developed significantly over the past few decades. An important aspect of this research is the visualization of this dimension and its underlying risk across space. However, most methods of such visualization, and subsequent analyses, only consider crime data or, perhaps, a population at risk in a crime rate. Risk terrain modeling (RTM) provides an alternative to such methods and can incorporate the entire environmental backcloth, data permitting. To date, the RTM literature has dominantly focused on violent crime in the United States. In this paper, we apply RTM to property crime victimization (residential burglary) in Vancouver, Canada. We are able to show that not only does RTM have applicability in a Canadian context but provides insight into nonviolent victimization.