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Dear Allstaters, Please find below information about a forthcoming RSS Leeds/Bradford Local Group Meeting. Further details can be found on our webpage: http://www.maths.leeds.ac.uk/statistics/rss/ All welcome! Regards, Paul =================================================================== Dr. Paul D. Baxter Secretary/Treasurer, RSS Leeds/Bradford Local Group, Department of Statistics, University of Leeds, Leeds, LS2 9JT, UK. ------------------------------------------------------------------- Leeds/Bradford: Thursday 9 February, 3.30pm, Room A126, Civic Quarter (City Site), Leeds Metropolitan University (Tea from 3pm) Michael Townsley (UCL Jill Dando Institute of Crime Science) Reducing Crime Scientifically: Applications beyond discourse, rhetoric, dogma and the status quo Crime science is a term coined to describe a type of crime reduction effort employing a wide range of relevant scientific disciplines. It is an analogue to medical science which incorporates biology, epidemiology, physics, chemistry, psychology and much more, for the sole purpose of reducing ill health (proactively and reactively). Crime science embraces the premise that most criminal acts are not undertaken by deviant psychopathic individuals, but are more likely to be carried out by ordinary people reacting to a particular situation with a unique economic, social, environmental, cultural, spatial and temporal context. It is these reactionary responses to the opportunities for crime which attract more and more people to become involved in criminal activities rather than entrenched delinquency. My talk will start by defining crime science and explain how it differs from mainstream criminology. Next, a range of modelling approaches (including naive Bayes networks and epidemiological models) that have been successfully employed in our research will be briefly be discussed. The final topic will consider some of the crime problems public sector agencies are likely to face over the next decade. The audience will be encouraged to suggest what modelling approaches - conventional or emerging - may best be employed to understand, and therefore prevent or diminish, these future threats.