Farrell, G and Pease, K (2014) Prediction and crime clusters. In: Bruinsma, G and Weisburd, D, (eds.) Encyclopedia of Criminology and Criminal Justice. Springer , New York , pp. 3862-3871. ISBN 978-1-4614-5689-6
Abstract
Predicting crime is a necessary condition for its prevention, and crime is most predictable along those dimensions in which it is concentrated. The most established forms of crime’s tendency to concentrate or cluster are repeat offending, repeat victimization, and geographical hot spots, with complementary concepts including supertargets, hot products, hot places, hot targets, risky facilities, risky routes, and crime sprees and spates. This entry charts the relationship between such clusters, observing how a broad conception of “near repeats,” incorporating crimes with similar situations and characteristics, is a useful unifying concept. Metrics of nearness, or conversely the difference between crime events, may inform efforts to understand and disperse crime clusters. The theories of repeat victimization and hot spots are shown to be overlapping and compatible and suggest a unified theory of clusters should result from greater conceptual integration in this field. The overall aim of such integration should be to inform cluster-busting crime prevention efforts.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Editors: |
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Keywords: | Crime concentration; Crime spates; Crime sprees; Hot dots; Hot products; Hot smudges; Hot spots; Hot targets; Near repeats; Repeat offending; Repeat victimization; Repeats; Risky facilities; Risky professions; Risky routes; Virtual repeats |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 May 2016 13:58 |
Last Modified: | 16 May 2016 19:59 |
Published Version: | http://dx.doi.org/10.1007/978-1-4614-5690-2_206 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-1-4614-5690-2_206 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:97491 |