Abstract
Research Question
Is the vast majority of crime harm in one police force area over 1 year suffered by a small percent of all known victims, with many of those most-harmed victims suffering repeated and perhaps preventable crimes if more police resources were to be invested in them?
Data
All 30,244 crimes recorded as committed against all 25,831 persons with one or more known victimization reported between 1 June 2015 and 31 May 2016 in Dorset, UK.
Methods
Each criminal event was weighted by the Cambridge Crime Harm Index (CHI) method, using the number of days of imprisonment recommended by the Sentencing Council for England and Wales as the “starting point” for sentencing offenders convicted in each crime category. Regardless of whether an offender was detected or convicted, each crime was coded with the starting point penalty. The total number of days assigned was then summed across all crimes in Dorset and individually for each victim, with the victims rank-ordered from highest to lowest number of total days of recommended imprisonment assigned to each (the Cambridge CHI value).
Findings
Under 4% of victims (968) suffered 85% of the CHI value of total days of recommended punishment for the crimes against all victims, with sex offences and robbery contributing almost two thirds of total CHI harm (63%).Almost one third (29%) of the harm were committed against repeat victims, including their first victimization within the 1-year period. Slightly over half of the harm against those repeat victims (57% of the harm across 4211 victimizations against repeat victims) occurred after their first victimization, equal to 15% of total harm to all victims that year. Just 256 repeat victims, comprising 1% of all victims, suffered 26% of total victim harm, ranging from 2 to 14 victimizations per person. The mean CHI value for each of these repeat victims was 1396 days (∼4 years) of recommended imprisonment for the totals of anywhere from 2 to 14 crimes against each member of this beleaguered 1%. The overall concentration of harm in a tiny fraction of all victims forms a “disproportionality ratio” of 15:1, with the “power few” most-harmed 4% of victims suffering 15 times more harm than expected if all victims suffered equal harm, with the highest disproportionality ratios of any offence types, 19 to 1 for sex offences and 5 to 1 for robbery. Conversely, the total CHI value of thefts was 0.143:1 or only one seventh of what it would have been with an equal distribution of harm across all criminal events. The ratio for burglary was 0.25:1, and even for violence (0.67:1), there was 33% less harm than expected for equal harm by crime type.
Conclusion
The vast majority of crime harm in one UK police force area over 1 year was suffered by a small percent of all known victims, with 15% of total harm occurring as repeat victimizations. This finding demonstrates the value of better algorithms for predicting repeat victimizations to allocate prevention resources, starting with the Cambridge CHI value of each first offence against each victim.
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References
Barnes, G. & Hyatt, J. (2012). Using Random Forest Risk Prediction in the Philadelphia Probation Department. Washington, DC: National Criminal Justice Reference Service, Document NCJ241346.
Berk, R., Sherman, L., Barnes, G., Kurtz, E., & Ahlman, L. (2009). Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learning. Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, 191–211.
Bland, M., & Ariel, B. (2015). Targeting escalation in reported domestic abuse evidence from 36,000 callouts. International criminal justice review, 25(1), 30–53.
Dorset County Council, (2016). Dorset County Council, Dorset statistics and census information. Retrieved 27 September 2016 from https://www.dorsetforyou.gov.uk/statistics
Echo, (2016). Bournemouth Daily Echo. Retrieved 26 October 2016 from http://www.bournemouthecho.co.uk/news/crime/14813910.Crime_in_Dorset_up_14_per_cent_in_last_year__figures_reveal/
Economist (2016), “Measuring crime: Bobbies on the spreadsheet. A new way to count crimes could reduce the amount of harm they cause” London: The Economist 1 September.
Her Majesty’s Inspectorate of Constabulary. (2014). Crime data integrity: inspection of Dorset Police November. London: HMIC.
HMIC (a), (2016). Her majesty’s inspectorate of constabulary, Dorset 2015, PEEL Assessment. Retrieved 27 September 2016 from http://www.justiceinspectorates.gov.uk/hmic/peel-assessments/peel-2015/dorset/
IPCC, (2016). Independent Police Complaints Commission, IPCC report into the contact between Fiona Pilkington and Leicestershire Constabulary 2004–2007. Retrieved 27 September 2016 from https://www.ipcc.gov.uk/sites/default/files/Documents/investigation_commissioner_reports/pilkington_report_2_040511.pdf
Jackman, Ralph (2015). “Measuring harm in a cohort of sex offenders in Norfolk.” Thesis for the M.St. in Applied Criminology and Police Management, Institute of Criminology, University of Cambridge.
Kerr, J. (2016). A descriptive analysis of the characteristics, seriousness and frequency of Aboriginal intimate partner violence in the Northern Territory, Australia: a strategy for targeting high harm cases. Thesis submitted for the M.St. in applied criminologyand police management, University of Cambridge.
Knowles, Gabrielle (2016). “Police target hit list of domestic abusers” The West Australian, December 14.
Macbeth, E., (2015). “Evidence-based vs. experience-based targeting of crime and harm spots in northern Ireland.” Thesis for the M.St. in applied criminology and police management, University of Cambridge.
Maguire, M. (1980). The impact of burglary upon victims. The British Journal of Criminology, 20(3), 261–275.
Office for National Statistics. (2016). Research outputs: developing a crime severity score for England and Wales using data on crimes recorded by the police. London: Office for National Statistics https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice/articles/researchoutputsdevelopingacrimeseverityscoreforenglandandwalesusingdataoncrimesrecordedbythepolice/2016-11-29.
Pareto, V. (1896). Cours d’Economie Politique. Geneva: Droz [As cited in Taleb 2007].
Ratcliffe, J.H., (2014). Towards an index for harm-focussed policing. Policing. Oxford University Press. pp. 164–182.
Rossi, P. H., Waite, E., Bose, C. E., & Berk, R. E. (1974). The seriousness of crimes: normative structure and individual differences. American Sociological Review, 39, 224–237.
Sellin, T., & Wolfgang, M. E. (1964). The measurement of delinquency. New York: Wiley.
Shapland, J., & Hall, M. (2007). What do we know about the effects of crime on victims? International Review of Victimology, 14(2), 175–217.
Sherman, L. (2007). ‘The power few: experimental criminology and the reduction of harm’. The 2006 Joan McCord prize lecture. Journal of Experimental Criminology, 3(4), 299–321.
Sherman, L. (2011). Al Capone, the sword of Damocles, and the police-corrections budget ratio. Criminology and Public Policy, 10, 195–206.
Sherman, L. W. (2013). The rise of evidence-based policing: targeting, testing, and tracking. Crime and justice, 42(1), 377–451.
Sherman, L. W., (1992). Attacking Crime: Police and Crime Control. In Norval Morris and Michael Tonry (Ed.), Modern Policing: Crime and Justice, Vol. 15, (pp. 159–230). Chicago: University of Chicago Press.
Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: routine activities and the criminology of place. Criminology, 27(1), 27–56.
Sherman, L., Neyroud, P., & Neyroud, E. (2016a). The Cambridge Crime Harm Index: measuring total harm from crime based sentencing. Policing, 10(3), 171–183.
Sherman, L. W., Bland, M., House, P., & Strang, H. (2016b). Targeting family violence reported to western Australia police, 2010–2015: the felonious few vs. the miscreant many. Perth, Australia: Western Australia Police https://www.police.wa.gov.au/About-Us/News/New-approach-needed-on-family-violence.
Taleb, N. N. (2007). The black swan: the impact of the highly improbable. London: Penguin.
Tourist Academy, (2016). National Costal Tourism Academy, facts and figures about Bournemouth’s visitors. Retrieved 27 September 2016 from http://nctastaging.com.gridhosted.co.uk/uploads/Bournemouth_Facts_and_Figures_pages1.pdf
Wallace, Marnie (2009). Police-reported crime statistics in Canada, 2008. Juristat July. Statistics Canada Publication 85–002-X.
Weinborn, Cristobal (2017). PhD Dissertation, Institute of Criminology, University of Cambridge.
Weisburd, D. (2015). Weisburd, David. “the law of crime concentration and the criminology of place.”. Criminology, 53.2(2015), 133–157.
Wolfgang, M. E., Figlio, R. M., Tracy, P. E., & Singer, S. I. (1985). The national survey of crime severity. Washington, DC: US Department of Justice, Bureau of Justice Statistics.
Yule, G. U. (1925). A mathematical theory of evolution, based upon the conclusions of Dr. J.C. Willis, F.R.S. Philosophical Transactions of the Royal Society of London, Series B, 213, 21–87.
Zipf, G. K. (1932). Selective studies and the principle of relative frequency in language. Cambridge, Mass: Harvard University Press.
Acknowledgements
This research was supported by a (UK) College of Policing bursary for Gavin Dudfield to complete the M.St. course in applied criminology and police management at the University of Cambridge, matched by equal funding and additional support from Senior Officers of the Dorset Police, including the data management assistance of Paul Marsh, Rachel Winbow, and Emma Knipe of the Dorset Police. The authors acknowledge the substantial value added to this analysis by Peter and Eleanor Neyroud for creating the “Beta Version” of the Crime Harm Index, used in this research. Points of view and conclusions stated in this article are those of the authors and do not necessarily represent the views of Dorset Police or the Dorset Police and Crime Commissioner.
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Dudfield, G., Angel, C., Sherman, L.W. et al. The “Power Curve” of Victim Harm: Targeting the Distribution of Crime Harm Index Values Across All Victims and Repeat Victims over 1 Year. Camb J Evid Based Polic 1, 38–58 (2017). https://doi.org/10.1007/s41887-017-0001-3
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DOI: https://doi.org/10.1007/s41887-017-0001-3