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dc.contributor.authorTompson, Lisa
dc.contributor.authorTownsley, Michael
dc.date.accessioned2017-05-03T12:54:15Z
dc.date.available2017-05-03T12:54:15Z
dc.date.issued2010
dc.date.modified2011-04-18T06:56:26Z
dc.identifier.issn14613557
dc.identifier.doi10.1350/ijps.2010.12.1.148
dc.identifier.urihttp://hdl.handle.net/10072/36910
dc.description.abstractCrime analysts attempt to identify regularities in police recorded crime data with a central view of disrupting the patterns found. One common method for doing so is hotspot mapping, focusing attention on spatial clustering as a route to crime reduction (Chainey & Ratcliffe, 2005; Clarke & Eck, 2003). Despite the widespread use of this analytical technique, evaluation tools to assess its ability to accurately predict spatial patterns have only recently become available to practitioners (Chainey, Tompson, & Uhlig, 2008). Crucially, none has examined this issue from a spatio-temporal standpoint. Given that the organisational nature of policing agencies is shift based, it is common-sensical to understand crime problems at this temporal sensitivity, so there is an opportunity for resources to be deployed swiftly in a manner that optimises prevention and detection. This paper tests whether hotspot forecasts can be enhanced when time-of-day information is incorporated into the analysis. Using street crime data, and employing an evaluative tool called the Predictive Accuracy Index (PAI), we found that the predictive accuracy can be enhanced for particular temporal shifts, and this is primarily influenced by the degree of spatial clustering present. Interestingly, when hotspots shrank (in comparison with the all-day hotspots), they became more concentrated, and subsequently more predictable. This is meaningful in practice; for if crime is more predictable during specific timeframes, then response resources can be used intelligently to reduce victimisation.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent278204 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherVathek Publishing
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom23
dc.relation.ispartofpageto40
dc.relation.ispartofissue1
dc.relation.ispartofjournalInternational Journal of Police Science and Management
dc.relation.ispartofvolume12
dc.rights.retentionY
dc.subject.fieldofresearchCriminology
dc.subject.fieldofresearchPolicy and administration
dc.subject.fieldofresearchOther law and legal studies not elsewhere classified
dc.subject.fieldofresearchcode4402
dc.subject.fieldofresearchcode4407
dc.subject.fieldofresearchcode489999
dc.title(Looking) Back to the Future: using space-time patterns to better predict the location of street crime
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© 2010 Vathek Publishing Ltd. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
gro.date.issued2010
gro.hasfulltextFull Text
gro.griffith.authorTownsley, Michael K.


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