• Built environment attributes and crime: an automated machine learning approach

      Dakin, Kyle; Parkinson, Simon; Saad, Kahn; Monchuck, Leanne; Pease, Ken; University of Huddersfield; University of Derby (BMC, 2020-07-08)
      This paper presents the development of an automated machine learning approach to gain an understanding of the built environment and its relationship to crime. This involves the automatic capture of street-level photographs using Google Street View (GSV), followed by the use of supervised machine learning techniques (specifically image feature recognition) to recognise features of the built environment. In this exploratory proof-of-concept work, 8 key features (building, door, fence, streetlight, tree, window, hedge, and garage) are considered and a worked case-study is demonstrated for a small geographical area (8300 square kilometres) in Northern England. A total of 60,100 images were automatically collected and analysed across the area where 5288 crime incidents were reported over a twelve- month period. Dependency between features and crime incidents are measured; however, no strong correlation has been identified. This is unsurprisingly considering the high number of crime incidents in a small geographic region (8300 square kilometres), resulting in an overlap between specific features and multiple crime incidents. Further- more, due to the unknown precise location of crime instances, an approximation technique is developed to survey a crime’s local proximity. Despite the absence of a strong correlation, this paper presents a first-of-a-kind cross-disci- pline approach to attempt and use computation techniques to produce new empirical knowledge. There are many avenues of future research in this fertile and important area.
    • Crime concentrations: Hot dots, hot spots and hot flushes.

      Ignatans, Dainis; Pease, Ken; University of Huddersfield; University College London (Oxford University Press, 2018-09-14)
      None
    • First-generation immigrant judgements of offence seriousness: evidence from the crime survey for England and Wales

      Los, Greg; Ignatans, Dainis; Pease, Ken; University of Kent; University of Huddersfield; University College London (Springer, 2017-03-17)
      This exploratory paper delves into differences and similarities in the rated seriousness of offences suffered by victims of different national origins. The issue is important because a mismatch between police and victim assessments of seriousness is likely to fuel discord. It was found that first-generation immigrants did not differ in their rating of the seriousness of offences against the person from either the indigenous population or according to region of birth. However, those of Asian origin rated vehicle and property crime they had suffered as more serious than did other groups about crimes they suffered. The anticipated higher seriousness rating of offences reported to the police was observed for all groups. People of Asian origin reported to the police a smaller proportion of offences they rated trivial than did people in other groups. Analysis of seriousness judgements in victimization surveys represents a much-underused resource for understanding the nexus between public perceptions and criminal justice responses.
    • How to morph experience into evidence.

      Roach, Jason; Pease, Ken; University of Huddersfield; Loughborough University (Routledge, 2017-04-21)
    • Is it just a guessing game? The application of crime prevention through environmental design (CPTED) to predict burglary.

      Monchuk, Leanne; Pease, Ken; Armitage, Rachel; University of Huddersfield; University College London; Applied Criminology & Policing Centre, University of Huddersfield, Huddersfield, UK; UCL Jill Dando Institute of Security and Crime Science, London, UK; Applied Criminology & Policing Centre, University of Huddersfield, Huddersfield, UK (Taylor and Francis, 2018-08-27)
      Crime prevention through environmental design (CPTED) aims to reduce crime through the design of the built environment. Designing out crime officers (DOCOs) are responsible for the delivery of CPTED by assessing planning applications, identifying criminogenic design features and offering remedial advice. Twenty-eight experienced DOCOs from across England and Wales assessed the site plan for one residential development (which had been built a decade earlier) and identified crime risk locations. Predictions of likely locations were compared with 4 years’ police recorded crime data. DOCOs are, to varying extents, able to identify locations which experienced higher levels of crime and disorder. However, they varied widely in the number of locations in which they anticipated burglary would occur.
    • On whom does the burden of crime fall now? Changes over time in counts and concentration.

      Ignatans, Dainis; Pease, Ken; University of Huddersfield; University College London; University of Huddersfield, UK; University College London, UK (Sage, 2015-11-03)
      A recent publication (Ignatans and Pease, 2015) sought to examine the changed distribution of crime across households in England and Wales over a period encompassing that of the crime drop common to Western countries (1982–2012). It was found that while crime against the most victimised households declined most in absolute terms, the proportion of all crime accounted for by those most victimised increased somewhat. The characteristics associated with highly victimised households were found to be consistent across survey sweeps. The pattern suggested the continued relevance to crime reduction generally of prioritising repeat crimes against the same target. The present paper analyses the changed distribution of crime by offence type. Data were extracted from a total of almost 600,000 respondents from all sweeps of the Crime Survey for England and Wales (CSEW) 1982–2012 to determine which types of victimisation became more or less concentrated across households during the overall crime drop. Methodological issues underlying the patterns observed are discussed. Cross-national and crime type extension of work of the kind undertaken here are advocated as both intrinsically important and likely to clarify the dynamics of the crime drop.
    • Self-selection policing: Theory, research and practice.

      Roach, Jason; Pease, Ken; University of Huddersfield; Loughborough University (Palgrave Macmillan, 2016)