Amongst the Peelian principles in the establishing of the professional police in the nineteenth century, the notion that the police should be judged not upon their arrests but upon the absence of crime seems to have been somewhat forgotten.
It may be worse than the principle has simply been forgotten – it may be that in many ways culturally we’ve simply given up on the very notion that we could ever achieve an absence of crime. Some might say such an aim is over ambitious and even niave. Yet consider how such ambitious goals have helped shaped progress in medicine towards the incremental eradication of disease and the ‘green agenda’ and the subsequent reduction of carbon emissions.
New research at Loughborough University is aiming to take on this challenge and explore to what extent an absence of crime is possible and what we can learn from low crime areas in order to inform, to prevent and desist, high crime in other areas.
Much criminological research effort over the years has focussed on high crime areas; its causes, manifestations and even target hardening tactics. Yet there has been surprisingly little research into why crime is low in some places and what can be gleaned through the (analogous) notion of ‘studying the healthy rather than ill’ in combating disease. This means exploring why an area has low crime, rather than the more traditional question of asking why a high crime area is high. To ask about the causes of no crime, or the absence of crime, rather than just the causes of crime.
Tacit knowledge and presumption may well suggest that there are some ‘obvious’ answers to why crime is low in some areas yet high in others – but any such presumptions are set to be put to the test to examine whether the available evidence supports such views or not.
Professor John Coxhead, who works on policing innovation and enterprise at Loughborough University, is seeking research students who are interested in contributing to this project, to help compare ‘high output’ with ‘low output’ crime areas. There are multiple open access data sets widely available, meaning data access is relatively straightforward, so the focus is in seeking a rich overlaying of such data sets to establish any patterns and correlations.
This approach in may ways echoes established approaches in medicine, using epidemiological scientific principles, but applying these in a social scientific context, to crime. Epidemiology is a method to help uncover causes in health outcomes, using systematic evidence of determinants.
Any research students, undergraduate or postgraduate, are invited to get in touch, and the opportunity may appeal particularly to students of disciplines such as Applied Mathematics.
Tell me more
Students might be curious to know what sort of activity would be involved in this project. It is envisaged that – using open source data sources (such as ukcrimestats.com, www.police.uk, checkmystreet.co.uk, ourwatch.org.uk/crime-map, nsi.org.uk/information-centre/information-for-home-owners/crime-in-my-area, gov.uk/government/news/crime-on-your-street-revealed) – ‘super output’ crime areas could be tabled opposite low crime areas. This would act as a starting point to overlay multiple sources of additional data to create a rich picture.
The richer the data the better, so that can include social media for example, as at this stage we are looking for any patterns that might exist particularly in those low crime areas. If we do find patterns we can later apply fresh interrogative systematic approaches to enquire further and build more rigorous data searches.
That first stage of pattern seeking may generate some working hypothesis (‘could it be because of X?’) or we might use some existing hypothesis (‘some people seem to think it’s because of Y’) to test as a starting point.
Are low crime areas influenced by the amount of community ‘agency’ that exists locally that bonds the community together? Where does such bonding come from and what are its conditions of possibility?
As this will be a team effort, a number of people will be looking at a number of places (with the same goal in mind) and we will compare notes with each other as we go along.
Here’s an example of how easy it is to access data using open source links – the one below illustrates how you can cross-compare crime statistics across neighbourhoods from anywhere across the UK, from high to low crime – but where our ongoing question is to ask ‘why is low crime low?’
John Coxhead, Professor of Policing Innovation and Enterprise at Loughborough University, can be reached at firstname.lastname@example.org if you are interested in getting involved.