e). BDC Seminar Series | 27th November 2018

Title:

“Re-examining the ‘law of crime concentration’ at place: theory, simulation, and application”

Abstract:

Over the past two decades the field of quantitative criminology has given great focus to the theory of “crime concentration at place”, with many researchers now referring to this theory as the “law of crime concentration”. The law states “for a defined measure of crime at a specific micro-geographic unit, the concentration of crime will fall within a narrow bandwidth of percentages for a defined cumulative proportion of crime” Weisburd, 2014. Despite the vague terms of this law, the common understanding in the field suggests that less than 1.5% of all “street segments” will account for at least 25% of crime for any geographical area. We examine this law, and the fine-grained spatial discretisation of crime in general, by means of theoretical examination, mathematical simulation and real-world application, to assess the veracity of the claims that the distribution of crime throughout an area exhibits law-like behaviours.

Author:

Pete Harding completed his PhD on the mathematical modelling of physical forces during building evacuations, at MMU in 2008. Since this time, he has primarily worked in Bio-medical Imaging and Diagnostics, where he designed and trialled a system that allows for the automated diagnosis of amyotrophic lateral sclerosis via standard clinical ultrasound, working with the Lancashire Teaching Hospitals NHS Trust and the Motor Neuron Disease Association. Alongside this clinical work, Pete also researched the use of deep learning algorithms for use in ultrasound imaging, and the advancement of ultrafast medical imaging techniques for the measurement of in-vivo muscle activation. Since leaving this biomedical research, Pete has been working in the Crime and Well-being Big Data Centre at MMU, investigating the spatio-temporal clustering of crime, and the multi-scale modelling of crime and criminality using agent-based modelling techniques.