Geographic Profiling

Rossmo, Kim

doi:10.1201/9781420048780

Cited by 238 publications

(339 citation statements)

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“…2, in only 35% of cases, sex offenders exhibited no signs of premeditation. For a significant proportion of sex offenders (51%), they display what has been termed "premeditated opportunism," referring to the exploitation of criminal opportunities after an initial degree of preparation and planning (Rossmo 2000). Generally, offenders are triggered by some environmental or situational cues (e.g., a young woman walking alone late at night).…”

Section: Resultsmentioning

confidence: 99%

An Application of the Rational Choice Approach to the Offending Process of Sex Offenders: A Closer Look at the Decision-making

Beauregard

Leclerc

2007

Sex Abuse

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Although the study of both offense processes and implicit theories provides in-depth knowledge about the decision-making of sex offenders, these studies focus solely on the internal psychological processes of the offender leading to the commission of a sexual assault. These studies neglect to look specifically at the offender's decision-making during the offense in interaction with the immediate situations encountered at the offense scene, such as the choices of behavior while interacting with the victim in a specific context. Based on a rational choice approach, this study investigates the decision-making involved in the offending process of 69 serial sexual offenders who have committed their crimes against stranger victims. Semi-structured interviews were conducted with offenders in order to identify the rationale behind their actions during the pre-crime phase (premeditation of the crime, estimation of risk of apprehension by the offender, and forensic awareness of the offender), crime phase (use of a weapon, use of restraints, use of a vehicle, and level of force used), and the post-crime phase (event leading to the end of crime and victim release site location choice). Results show that sex offenders, even if traditionally described as "irrational" and impulsive individuals, are capable, up to a certain point, of an analysis of the costs/benefits related to their actions. Moreover, results emphasize the important role of situational factors, such as victim resistance, on the decision-making process of sex offenders. Implications of the results are briefly discussed in regard of clinical practice and crime prevention.

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Section: Resultsmentioning

confidence: 99%

An Application of the Rational Choice Approach to the Offending Process of Sex Offenders: A Closer Look at the Decision-making

Beauregard

Leclerc

2007

Sex Abuse

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“…As before, a cartel can ex ante set its collusive bases to avoid rejection of H 0 on expectation. 32 …”

Section: Bid-distance Correlationmentioning

confidence: 99%

“…Using the definition of distance (2), prices 32 If information on loosing bids is available in addition, cartels can select bases to avoid patterns in those. 33 This is discussed further in Section 7.…”

Section: Base Recoverymentioning

confidence: 99%

Tracing the Base: A Topographic Test for Collusive Basing-Point Pricing

Bos

Schinkel

2008

SSRN Journal

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Basing-point pricing is known to have been abused by geographically dispersed firms in order to eliminate competition on transportation costs. This paper develops a topographic test for collusive basing-point pricing. The method uses transaction data (prices, quantities) and customer project site locations to recover the basing-point(s) from which delivered prices were calculated. These bases are compared to the locations of the production mills in a test that discriminates between competitive and collusive basing-point pricing. We define a measure for the likelihood of collusion that can be used to screen industries that traditionally apply delivered pricing for the presence of cartels. We operationalize this screen with a software. The test is hard to beat for cartels using this otherwise elusive form of price-fixing. When a cartel was found to have abused the basing-point system, our method can be used to estimate antitrust damages.

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“…Crime mapping aids policy formation and resource allocation by describing geographical distribution of crime, highlighting areas of high risk, and generating and testing hypothesis (e.g., association between burglary and unemployment). Further applications of spatial analysis of crime include ecological analysis of spatial distributions of offences and/or offenders (Bowers et al 2004;Chainey and Ratcliffe 2005), geographic profiling (Rossmo 2000), and spatial integration of police perception and recorded crime data (Haining and Law 2007). Increasing use of spatial approaches in crime studies is in part due to increasing availability of geocoded crime data (usually acquired directly from the police) and crime-related spatial data (e.g., census and public transportation data), and improved spatial methodologies for analysing crime data at the small-area level.…”

mentioning

confidence: 99%

Bayesian Spatial Random Effect Modelling for Analysing Burglary Risks Controlling for Offender, Socioeconomic, and Unknown Risk Factors

Law

Chan

2011

Appl. Spatial Analysis

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This paper adopts a Bayesian spatial random effect modelling approach to analyse the risk of domestic burglary in Cambridgeshire, England, at the census output area level (OA). The model, in the form of Binomial spatial logistic regression, integrates offence and offender based theories and takes into account unknown local risk factors (represented as unexplained spatial autocorrelation in the model). A score of 'proximity to offenders' was calibrated for each OA based on the number of likely offenders in the county, the OAs they reside, and their proximities. Our results indicate that areas that have a score higher than the average score were at higher risks of being burgled. Household occupied by non-couple and economically inactivity are positively associated confounders. Household occupied by owner is a negatively associated confounder. These confounders diminish the effect of high score of proximity to offenders, which, however, remains positively associated with the risk of burglary. Bayesian spatial random effect modelling, which adds to the traditional (nonspatial) regression model a spatial random effect term, stabilizes estimated risks and remarkably improves model fit and causation inference. Mapping the results of spatial random effect reveals locations of high risk of burglary after controlling for offender and socioeconomic factors. Limitations of the study and strategies to deter burglaries based on the results of spatial random effect modelling are discussed.

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Geographic Profiling

Cited by 238 publications

References 0 publications

An Application of the Rational Choice Approach to the Offending Process of Sex Offenders: A Closer Look at the Decision-making

An Application of the Rational Choice Approach to the Offending Process of Sex Offenders: A Closer Look at the Decision-making

Tracing the Base: A Topographic Test for Collusive Basing-Point Pricing

Bayesian Spatial Random Effect Modelling for Analysing Burglary Risks Controlling for Offender, Socioeconomic, and Unknown Risk Factors

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