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Newton, Andrew D. (2015)
Publisher: Springer
Languages: English
Types: Article
Subjects:
This paper examines crime hot spots near licensed premises in the night-time economy (NTE) to investigate whether hot spots of four different classification of crime and disorder co-occur in time and place, namely violence, disorder, drugs and criminal damage. It introduces the concept of multi-classification crime (MCC) hot spots; the presence of hot spots of more than one crime classification at the same place. Furthermore, it explores the temporal patterns of identified MCC hot spots, to determine if they exhibit distinct spatio-temporal patterns. Getis Ord (GI*) hot spot analysis was used to identify locations of statistically significant hot spots of each of the four crime and disorder classifications. Strong spatial correlations were found between licensed premises and each of the four crime and disorder classifications analysed. MCC hot spots were also identified near licensed premises. Temporal profiling of the MCC hot spots revealed all four crime types were simultaneously present in time and place, near licensed premises, on Friday through Sunday in the early hours of the morning around premise closing times. At other times, criminal damage and drugs hot spots were found to occur earlier in the evening, and disorder and violence at later time periods. Criminal damage and drug hot spots flared for shorter time periods, 2–3 h, whereas disorder and violence hot spots were present for several hours. There was a small spatial lag between Friday and Saturday, with offences occurring approximately 1 h later on Saturdays. The implications of these findings for hot spot policing are discussed.
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    • Ashby, M., & Chainey, S. (2012). Problem solving for neighbourhood policing. London: UCL Press.
    • Block, R. L., & Block, C. R. (1995). Space, place and crime: Hot spot areas and hot places of liquor-related crime. In D. Weisburd & J. E. Eck (Eds.), Crime and place: crime prevention studies (4th ed., pp. 145-184). Monsey: Criminal Justice Press.
    • Booth, A., Meier, P., Stockwell, T., Sutton, A., Wilkinson, A., Wong, R., & Taylor, K. (2008). Independent review of the efects of alcohol pricing and promotion. Part A: systematic reviews. Shefield: University of Shefield.
    • Bowers, K. (2014). Risky facilities: crime radiators or crime absorbers? A comparison of internal and external levels of theft. Journal of Quantitative Criminology, 30(3), 389-414.
    • Braga, A., Papachristos, A., & Hureau, D. (2012). Hot spots policing efects on crime: Campbell Systematic Reviews, 8, 1-97.
    • Brantingham, P. J., & Brantingham, P. L. (1993). Environment, routine and situation: toward a pattern theory of crime. Advances in criminological theory, 5, 259-294.
    • Brantingham, P. J., & Brantingham, P. L. (1995). Criminality of place: crime generators and crime attractors. European Journal on Criminal Policy and Research, 3, 5-26.
    • Chainey, S. (2014). Examining the extent to which hotspot analysis can support spatial predictions of crime. Doctoral thesis, UCL (University College London).
    • Chainey, S., & Ratclief, J. H. (2005). GIS and crime mapping. Chichester: Wiley.
    • Chikritzhs, T., & Stockwell, T. (2002). The impact of later trading hours for Australian public houses (hotels) on levels of violence. Journal of Studies on Alcohol, 63, 591-599.
    • Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: a routine activity approach. American Sociological Review, 588-608.
    • Conrow, L., Aldstadt, J., & Mendoza, N. S. (2015). A spatio-temporal analysis of on-premises alcohol outlets and violent crime events in Bufalo, NY. Applied Geography, 58, 198-205.
    • Dingwall, G. (2013). Alcohol and Crime: Cullompton: Willan Publishing.
    • Eck, J., Chainey, S., Cameron, J., & Wilson, R. (2005). Mapping crime: understanding hotspots. Washington DC: National Institute of Justice.
    • Eck, J. E., Clarke, R. V., & Guerette, R. T. (2007). Risky facilities: crime concentration in homogeneous sets of establishments and facilities. In G. Farrell, K. Bowers, S. D. Johnson, & M. Townsley (Eds.), Crime prevention studies (pp. 225-264). Cullompton: Willan Publishing.
    • Ekblom, P. (2011). Crime Prevention, Security and Community Safety using the 5Is Framework. Basingstoke: Palgrave Macmillan.
    • Elvins, M., & Hadfield, P. (2003). West end stress area: night-time economy profiling: a demonstration project: Durham. UK: Department of Sociology and Social Policy, University of Durham.
    • Finney, A. (2004). Violence in the night-time economy: Key findings from the research. Research Findings, 214 (pp. 1-6). London: Home Ofice.
    • Getis, A., & Ord, J. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206.
    • Goldstein, H. (1990). Problem oriented policing. New York: McGraw-Hill.
    • Gorman, D. M., Speer, P. W., Gruenewald, P. J., & Labouvie, E. W. (2001). Spatial dynamics of alcohol availability, neighborhood structure and violent crime. Journal of Studies on Alcohol, 62, 628-636.
    • Graham, K., & Homel, R. (2008). Raising the Bar: Preventing aggression in and around bars, pubs and clubs. Cullompton: Willan Publishing.
    • Gro,f E. R., Ratclief, J. H., Haberman, C. P., Sorg, E. T., Joyce, N. M., & Taylor, R. B. (2015). Does what police do at hot spots matter? The Philadelphia Policing Tactics Experiment: Criminology, 53(1), 23-53.
    • Hadfield, P., & Newton, A. (2010). Factsheet: alcohol, crime and disorder in the night-time economy. London: Alcohol Concern.
    • Holmes, J., Guo, Y., Maheswaran, R., Nicholl, J., Meier, P., & Brennan, A. (2014). The impact of spatial and temporal availability of alcohol on its consumption and related harms: a critical review in the context of UK licensing policies: drug Alcohol. Review, 33(5), 515-525.
    • Horvath, M., & Le Boutillier, N. (2014). Alcohol use and crime. The encyclopedia of criminology and criminal justice (pp. 1-7). USA: Blackwell Publishing Ltd.
    • Humphreys, D., & Eisner, M. (2014). Do flexible alcohol trading hours reduce violence: a theory-based natural experiment in alcohol policy? Social Science and Medicine, 102, 1-9.
    • Innes, M. (2004). Signal crimes and signal disorders: notes on deviance as communicative action. The British Journal of Sociology, 55(3), 335-355.
    • Levine, N. (2015). CrimeStat: A Spatial Statistics Program for the Analysis of Crime Incident Locations (v 4.02). Washington, D.C: Ned Levine & Associates, Houston, Texas, and the National Institute of Justice.
    • Livingston, M. (2008). Alcohol outlet density and assault: a spatial analysis. Addiction, 103, 619-628.
    • Madensen, T. D., & Eck, J. E. (2008). Violence in bars: exploring the impact of place manager decision-making. Crime Prevention & Community Safety, 10(2), 111-125.
    • Miethe, T. D., Hart, T. C., & Regoeczi, W. C. (2008). The conjunctive analysis of case configurations: an exploratory method for discrete multivariate analyses of crime data. Journal of Quantitative Criminology, 24(2), 227-241.
    • Newton, A., & Hirschfield, A. (2009a). Violence and the night-time economy: a multi-professional perspective. An introduction to the Special Issue. Crime Prevention and Community Safety, 11(3), 147-152.
    • Newton, A., & Hirschfield, A. (2009b). Measuring violence in and around licensed premises: the need for a better evidence base. Crime Prevention and Community Safety, 11(3), 171-188.
    • Newton, A., & Felson, M. (2015). Editorial: crime patterns in time and space: the dynamics of crime opportunities in urban areas. Crime Science, 4(11). doi:10.1186/s40163-015-0025-6.
    • Ofice, Home. (2003). Drinking, crime and disorder: home ofice research findings (Vol. 185). London: Home Ofice.
    • Popova, S., Giesbrecht, N., Bekmuradov, D., & Patra, J. (2009). Hours and days of sale and density of alcohol outlets: impacts on alcohol consumption and damage: a systematic review. Alcohol and Alcoholism, 44(5), 500-516.
    • Pridemore, W. A., & Grubesic, T. H. (2013). Alcohol outlets and community levels of interpersonal violence spatial density, outlet type, and seriousness of assault. Journal of Research in Crime and Delinquency, 50(1), 132-159.
    • Ratclief, J. (2008). Intelligence-led policing. Cullompton: Willan.
    • Ratclief, J. (2010). Crime mapping: spatial and temporal challenges. In A. Piquero & D. Weisburd (Eds.), Handbook of quantitative criminology (pp. 5-24). New York: Springer.
    • Ratclief, J. (2012). The spatial extent of criminogenic places: a changepoint regression of violence around bars. Geographical Analysis, 44(4), 302-320.
    • Ratclief, J., Taniguchi, T., Gro,f E., & Wood, J. (2011). The Philadelphia foot patrol experiment: a randomized controlled trial of police patrol eefctiveness in violent crime hot spots. Criminology, 49, 795-831.
    • Roach, J., & Pease, K. (2014). Police overestimation of criminal career homogeneity. Journal of Investigative Psychology and Ofender Profiling, 11(2), 164-178.
    • Scott, M., & Dedel, K. (2006). Assaults in and Around Bars, problem-oriented guides for police problem-specicfi guides series no. 1, 2nd edn. Washington, DC: Ocfie of Community Oriented Policing Services, US Department of Justice.
    • Shekhar, S., Mohan, P., Oliver, D., & Zhou, X. (2012). Crime pattern analysis: a spatial frequent pattern mining approach (No. TR-12-015): Minnesota: Dept Of Computer Science And Engineering, Minnesota University Minneapolis.
    • Shepherd, J. P., Ali, M. A., Hughes, A. O., & Levers, B. G. H. (1993). Trends in urban violence: a comparison of accident department and police records. Journal of the Royal Society of Medicine, 86(2), 87-88.
    • Sherman, L. W. (1995). Hot spots of crime and criminal careers of places. Crime and place, 4, 35-52.
    • Tompson, L. A., & Bowers, K. J. (2015). Testing time-sensitive influences of weather on street robbery. Crime Science, 8(4), 1-11.
    • Townsley, M. (2008). Visualising space time patterns in crime: the hotspot plot. Crime patterns and analysis, 1(1), 61-74.
    • Uittenbogaard, A., & Ceccato, V. (2012). Space-time clusters of crime in Stockholm, Sweden. Review of European Studies, 4(5), p148-p156.
    • Wilcox, P., & Eck, J. (2011). Criminology of the unpopular: implications for policy aimed at payday lending facilities. Criminology & Public Policy, 10, 473-482.
    • Wuschke,K., Clare, J., Garis, L. (2013). Temporal and geographic clustering of residential structure fires: a theoretical platform for targeted fire prevention. Fire Safety Journal, 62(A), 3-12.
    • Yang, S. M. (2010). Assessing the spatial-temporal relationship between disorder and violence. Journal of Quantitative Criminology, 26(1), 139-163.
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