Prospective crime mapping in operational context Final report

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The implication of the results is that the generation of three daily forecasts, one for eachpolice shift, should improve the efficiency of resources deployed. Thus, as a final change tothe system, the predictive model was developed so that it produced different maps for thedifferent shifts, weighting more heavily those events that occurred during the same shift asthat for which the prediction was made.ConclusionThe final Promap system was considerably more accurate than extant methods. The systemwas improved ‘on the hoof’ in a number of ways, partly in response to requests from thepolice Command Team. Risking tedious repetition, it must be stressed that the role ofpredictive mapping in crime reduction is emergent. It provides a tool which may modify policeand Crime and Disorder Reduction Partnerships’ (CDRPs’) practice. There may be falsestarts and initiatives that turn out to be ill-founded. A parallel may be made with cervicalscreening and PSA (Prostate Specific Antigen) testing for cervical and prostate cancerrespectively. Neither of these approaches affords perfect prediction, but both allow areconsideration of risk assessment and treatment prioritisation for the conditions concerned.The argument is that crime reduction is enabled by a more precise specification of risk, butany benefits are contingent upon the shaping of the craft of policing to take maximumadvantage of improved prediction.To give the reader an idea of what the GUI looked like, an example screen image is shown asFigure 4.2. As can be seen, the GUI was quite simple but provided some flexibility so that theanalysts could generate different kinds of maps. Appendix 4 provides further detail of thesoftware interface and illustrates how simple it is to use.Figure 4.2: An example image of the final GUI© Crown Copyright. All rights reserved. Derbyshire Constabulary 100021015.In the Chapters that follow, an account is given of the field trial of the system. Chapter fivediscusses what the police did and problems encountered. To anticipate the findings,41
unfortunately, implementation or use of the system was less than desired. As will becomeapparent, this was not because the utility of the system was perceived to be limited (in factthe reverse was true), problems associated with using the system or even a lack ofenthusiasm, but instead largely because policing priorities changed over the evaluationperiod. This was unavoidable and simply due to the fact that the rate of vehicle crimeincreased whilst burglary declined.42
Page 2 and 3: 1. UCL JILL DANDO INSTITUTE OF CRIM
Page 4 and 5: ContentsAcknowledgementsExecutive s
Page 6 and 7: 2.5 Illustration of a simple neares
Page 8 and 9: Project outcomesPatterns of burglar
Page 10 and 11: those that involved collaboration w
Page 12 and 13: 1. IntroductionThis report represen
Page 14 and 15: optimally calibrated system, the go
Page 16 and 17: e ij = n .j x n i.nWhere, e ij is t
Page 18 and 19: Table 2.2: Knox ratios for Mansfiel
Page 20 and 21: Table 2.6: Monte-Carlo results for
Page 22 and 23: Table 2.10: Weekly Knox ratios for
Page 24 and 25: Table 2.14: Monte-Carlo results for
Page 26 and 27: Figure 2.1: The five policing areas
Page 28 and 29: The results for area 5 again demons
Page 30 and 31: The bandwidth used to generate the
Page 32: a densely populated urban area this
Page 35 and 36: Table 2.24: Average number of crime
Page 37 and 38: Patrolling efficiencyAs discussed e
Page 39 and 40: 3. Tactical options and selecting a
Page 41 and 42: Selecting a pilot siteThe decision
Page 43 and 44: Table 3.2: Tactical options matrixT
Page 45 and 46: Type ofinterventionStudyUse ofintel
Page 47 and 48: Other potential tactical optionsAt
Page 49 and 50: 4. System development and evolution
Page 51: the same time of day as each other
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 and 104:
To recapitulate and elaborate, the
Page 105 and 106:
Concluding comments on methodThe te
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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