Prospective crime mapping in operational context Final report

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Figure A3.4: The proportion of events belonging to different k-event series before and duringthe pilot40% of events that are the last in a k- event (ormore) series3530252015105AfterBefore02 3 4 5 6 7 8 9 10 11 12Chain length (k -events)Considering the patterns for the periods before and during the pilot, there are some differences. First,the longest series (12 events, of which there were three examples) identified occurred in the periodbefore intervention. More generally, longer series were identified in the period before the pilot, thanduring it. Conversely, during the pilot there was a slightly higher proportion of shorter series (two orthree events). On the face of it, this finding is in line with what would be expected if the pilot had beensuccessful. However, the reader should be mindful of two things.a. For the period during the pilot, a smaller number of burglaries were committed, whichmay have affected the pattern of results. For what it is worth, sampling only the samenumber of events for the period before (the first 554 events) as that after generatedexactly the same pattern of results. Consequently, differences in sample sizes wouldnot appear to explain the results observed.b. Perhaps more importantly, the effect observed was very subtle. This is notunexpected given that implementation, or rather the use of the system, was at bestonly minimally realised. With such a small effect size, and under the circumstances ofpartial implementation, it is inappropriate to conduct inferential statistical tests. 13Thus, this finding is interpreted as being inconclusive, but the analytic approachderived suggested a useful method for future research concerned with the stability ofclusters of crime.13 Such a test would involve comparing the observed distribution of k-event series with what would be expected if the timing andlocation of events were random. Thus, a variant of the Monte-Carlo approach used elsewhere in this report would seemappropriate.93
Concluding comments on methodThe techniques described illustrate a number of ways in which particular ‘signatures’ that mightbespeak mechanism may be sought. Only by conducting such analyses is it possible to differentiatebetween the likely contributions of different plausible mechanisms of crime reduction. Unfortunately,methods of this kind are in their infancy and hence there is a need to develop and disseminate thosethat might have wider application.94
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1. UCL JILL DANDO INSTITUTE OF CRIM
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ContentsAcknowledgementsExecutive s
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2.5 Illustration of a simple neares
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Project outcomesPatterns of burglar
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those that involved collaboration w
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1. IntroductionThis report represen
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optimally calibrated system, the go
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e ij = n .j x n i.nWhere, e ij is t
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Table 2.2: Knox ratios for Mansfiel
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Table 2.6: Monte-Carlo results for
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Table 2.10: Weekly Knox ratios for
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Table 2.14: Monte-Carlo results for
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Figure 2.1: The five policing areas
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The results for area 5 again demons
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The bandwidth used to generate the
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a densely populated urban area this
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Table 2.24: Average number of crime
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Patrolling efficiencyAs discussed e
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3. Tactical options and selecting a
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Selecting a pilot siteThe decision
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Table 3.2: Tactical options matrixT
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Type ofinterventionStudyUse ofintel
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Other potential tactical optionsAt
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4. System development and evolution
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the same time of day as each other
Page 53 and 54: unfortunately, implementation or us
Page 55 and 56: any tactical options were employed
Page 57 and 58: the end of the pilot. In addition t
Page 59 and 60: Figure 5.1: Promap dissemination pr
Page 61 and 62: the busy schedule of the new Divisi
Page 63 and 64: Tactical deliveryCommand Team daily
Page 65 and 66: Table 5.3: Number of respondents wh
Page 67 and 68: permitted, up to four plain clothed
Page 69 and 70: observation made by those who used
Page 71 and 72: A simple time-series analysis (see
Page 73 and 74: Two approaches were used to compute
Page 75 and 76: Figure 6.3: Changes in the proporti
Page 77 and 78: Figure 6.5: Changes in the proporti
Page 79 and 80: With respect to implementation real
Page 81 and 82: ReferencesAggresti, A. (1996) An In
Page 83 and 84: Johnson, S.D., Summers, L., and Pea
Page 85 and 86: Appendix 1. The information technol
Page 87 and 88: Figure A1.2: Stand-alone applicatio
Page 89 and 90: Recommendations that may be realise
Page 91 and 92: Section 1: knowledge and understand
Page 93 and 94: Extra Comments (please outline any
Page 95 and 96: In relation to the evaluation of in
Page 97 and 98: Time-series analysisFor the purpose
Page 99 and 100: Figure A3.1: Changes in the spatial
Page 101 and 102: Figure A3.2: Lorenz curves showing
Page 103: To recapitulate and elaborate, the
Page 107 and 108: Figure A5.2: An enlargement of the
Page 109 and 110: Figure A5.6: Prospective map magnif
Page 111: Produced by the Research Developmen
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