1. Repeat and Near Repeat Victimisation Ken Pease

3. Kirkholt Too little cash to go round Victimisation best predictor Concentrated on preventing repeats Burglary fell to one third of previous level Decline driven by repeat reduction

4. Stockport In Stockport in the financial year 1996-7, with a divisional programme to prevent rv, domestic burglary fell by 21%. This decline was greater than that in the remainder of the force (5%), and to a statistically significant degree. Stockport showed a 44% reduction in the number of repeats, demonstrating that the overall reduction had indeed been largely achieved by the reduction of rv.

5. Huddersfield Olympic Approach

6. What to Count Prevalence (victims per head) Incidence (crimes per head) Concentration (crimes per victim)

7. Measuring Issues A domestic violence initiative increased the number of women calling the police (prevalence), but decreased the number of calls per caller (concentration), so that the total number of calls remained unchanged. This makes sense.

8. High Crime Areas Primarily high crime areas are high because of numbers of repeat victims. The British Crime Survey contains no area where more than half the people are victimised, but does contain areas where those victimised each suffer many times

12. Austin Residential Burglaries 1999

13. Austin Repeat Residential Burglaries 1999

14. Why Have People Not Noticed? The nature of police recording systems The fragmentation of police work Non-report The arithmetic is not straightforward

15. Bank Robbery Time Course

16. Why The Time Course A sports team loses the first two matches of the season. Why did it lose the second one? Was it because the first result reflected the fact that it was a poor team, and it was still a poor team at the time of the second match? This is a flag account. Alternatively, did the first result destroy its confidence so that it played tentatively in the second match? This is a boost account

17. Offender Accounts Ericsson (1995) interviewed twenty-one convicted multiple burglars at a category C prison in East Anglia. She found that “76% said they had gone back to a number of houses...., they were familiar with the features of the house. The reasons for going back for goods were things they had left behind... replaced goods... and unhidden cash.” (p23).

18. Ashton Brown and Senior “The house would be targeted again ‘a few weeks later’ when the stuff had been replaced and because the first time had been easy...”“It was a chance to get things which you had seen the first time and now had a buyer for”.“Once you have been into a place it is easier to burgle because you are then familiar with the layout, and you can get out much quicker”

19. More Ashton et al “X had stolen the stereo from the same car more than once. He would return to the same street and if he spotted the same car parked on the street he would take the stereo again if it had been replaced... You get more money for brand new things”

20. Gill and Pease (and Everson) repeat robbers of the same target were more determined, more likely to carry a loaded gun, and more likely to have committed a robbery where someone had been injured. They had longer criminal records, were more likely to have been in prison before, and for a sentence upwards of five years. They planned their robberies more, and were more likely to have worn a disguise.

21. Is rv relevant to all crimes? for all crime where there is a recognisable victim and where research has been conducted, the basic patterns are reproduced, even where it is difficult for them to show themselves (as in car theft, where a proportion of vehicles remains unrecovered, and their drivers hence not liable to rv)

22. Is rv worthwhile in rural areas? Consider an area of 10,000 homes of which 100 are burgled. Of that 100, 10 are burgled again. By choosing at random 100 unburgled homes to protect, one would prevent (on average) one burglary. If one chose to protect the 100 previously burgled homes, one could prevent ten burglaries. The key figure is not the absolute number of repeats, but their rate.

23. Virtual repeats One relevant point emerged from the Ashton et al. (1998) interviews with burglars. One pointed out that the floor plan of all new petrol stations belonging to one major chain was identical, so that having burgled one, the burglar had acquired the knowledge to burgle any. These are virtual repeats

24. Elapsed time and repeats Quick repeats are more similar to the original offence than repeats after some time. This means that preventive packages which seek to have enduring effects should be more complete in what they protect against. Anniversary repeats (ie repeats which take place after exactly one year) are of special interest

25. Is rv just a fad? This is the question that is not frequently asked, but which should be. Inflexible and unimaginative use of rv information will lead to its failure as an aid to crime reduction. The question in the heading should be asked often

26. Magic bullet deployment on places Focusing on repeats automatically concentrates effort on areas of highest crime without the need for any supplementary deployment decisions;

27. Magic bullet deployment on people Focusing on repeats automatically concentrates on individuals at greatest risk of future victimisation

28. Magic bullet deployment: time The time course of repeats suggests that resources can be focused temporally as well as spatially

29. Crime Prevention & Victim Support It fuses the roles of victim support and crime prevention which have been historically separated;

30. Detection > Prevention Insofar as repeated offences against the same target are the work of the same perpetrator(s), clearance of a series of crimes and linked property recovery is made more likely than was the case when events were seen as independent. It thus explicitly links the police tasks of prevention and detection;

31. Offender Targeting without Pain Insofar as the provisional evidence is confirmed that repeated crimes are disproportionately the work of prolific offenders, the prevention/detection of attempts at repetition provides an uncontentious way of targeting prolific offenders

33. Knowsley Quick security survey by response officer; Follow-up by neighbourhood officer; Special service for the demonstrably vulnerable; Burglary alert cards; Consolidated data about weak points to housing providers.

34. Is the risk of burglary communicable?

38. Communicability of risk

39. Ross and Pease (2007): “In domestic burglary, for example, the danger of a further crime is greatest at the home of the original victim and spreads out to some 400 metres, but disappears over six weeks to two months … instead of mapping past events in the conventional way we should map the risk they generate for nearby homes, with the map being dynamic to reflect how the risk declines over time.” Every day 00:00-04:00, Particularly 02:00-03:00 Also 16:00-19:00 Friday and Monday Practical Application Respons e

40. Predictive Mapping Evaluation Burglary Dwelling Counts Over 2 years Trafford has experienced a 38.2% decrease in Burglary Dwelling offences £1.85million saved to the public purse (Home Office cost of crime £3,925 per burglary) Assessmen t Still 61% within predicted areas (random 10 week testing) - suggests limited displacement Type Displacement: Pedal Cycle Theft - Increase against GMP Baseline

41. Number of Repeat Victims In 2011/12 only 2% of our BDW victims have been repeats (National Ave. 15-20%) up to 50up to 50 51-10051-100 101-200101-200 201-300201-300 301-400301-400 up to 2 daysup to 2 days 0.210.21 0.60.6 0.310.31 0.320.32 0.350.35 3-7 days3-7 days 0.240.24 0.560.56 0.350.35 0.370.37 0.350.35 8-15 days8-15 days 0.330.33 0.560.56 0.390.39 0.440.44 0.380.38 16-30 days16-30 days 0.310.31 0.50.5 0.410.41 0.340.34 0.40.4

42. up to 5051-100 101- 200 201- 300 301- 400 up to 2 days0.210.60.310.320.35 3-7 days0.240.560.350.370.35 8-15 days0.330.560.390.440.38 16-30 days0.310.50.410.340.4

45. Johnson, S.D., & Bowers, K.J. (2004). The Burglary as Clue to the Future: The beginnings of Prospective Hot-Spotting. Bowers, K.J., & Johnson, S.D. (2005). Domestic Burglary Repeats and Space-time Clusters: the Dimensions of Risk. Johnson, S.D., & Bowers, K.J. (2004). The Stability of Space-time Clusters of Burglary. Bowers, K.J., Johnson, S.D., & Pease, K. (2004). Prospective Hot-spotting: The Future of Crime Mapping? Bowers, K.J., & Johnson, S.D. (2004). A Test of the Boost explanation of Near Repeats. Western Criminology Review. Johnson, S.D., Bowers, K.J., Pease, K. (2005). Predicting the Future or Summarising the Past? Crime Mapping as Anticipation. Launching Crime Science. Publications