Prospective crime mapping in operational context Final report

Table 5.2: Sample characteristicsNumber %SexRankTime in RankSectionMale 42 73.7Female 15 26.3PoliceConstable49 86.0Sergeant 6 10.5Inspector 1 1.8SpecialConstable1 1.8Less than 1year6 10.51-5 years 30 52.6More than 5years20 35.1No answer 1 1.8Alfreton 9 15.8Belper 13 22.8Ilkeston 15 26.3Long Eaton 12 21.1Ripley 8 14.0Table 5.3 shows the number of respondents who had heard of prospective mapping, bysection. In all sections, aside from Ilkeston, the majority of respondents had heard of Promap.In Ilkeston, only four of the fifteen respondents in that section, had heard of the pilot. 5 Thosewho had heard of Promap were asked how they would define Promap in their own words.Two researchers, one who did not work on the project and one who did, examined theresponses to ensure that there was no bias of interpretation. The inter-rater reliability for thetwo researchers was high (Cronbach’s Alpha=0.99) and thus the coding appropriate. 52 percent (21) correctly identified the definition of Promap, i.e. the maps ‘predict where burglariesare likely to occur’. Those that did not provide an accurate definition showed a basicunderstanding of the system (e.g. ‘shows burglary hotspots’ and ‘shows crime hotspots’). Afew respondents, 21 per cent (8) did not fully understand the maps as they thought that theyillustrated both burglary and auto crime hotspots.5 It was suggested by a member of the Command Team that one possibility why the number of respondents is so lowis because of the terminology used in the questionnaires. It seems that the Division was using the term ‘JDI maps’when referring to the pilot, whereas the questionnaire specifically asked if respondents had heard of ‘ProspectiveMapping’. One would assume that if this were the case, however, that the same trends would have been evident inthe other four Sections.53