An updated version of the report I was involved in on gender differences in victims of child sexual exploitation has now been published in Sexual Abuse as ‘Immaterial Boys? A Large-Scale Exploration of Gender-Based Differences in Child Sexual Exploitation Service Users’, co-authored with Ella Cockbain and Helen Brayley. The main differences are more-detailed multivariate analysis and an expanded literature review.
The abstract of the paper is:
Child sexual exploitation is increasingly recognized nationally and internationally as a pressing child protection, crime prevention, and public health issue. In the United Kingdom, for example, a recent series of high-profile cases has fueled pressure on policy makers and practitioners to improve responses. Yet, prevailing discourse, research, and interventions around child sexual exploitation have focused overwhelmingly on female victims. This study was designed to help redress fundamental knowledge gaps around boys affected by sexual exploitation. This was achieved through rigorous quantitative analysis of individual-level data for 9,042 users of child sexual exploitation services in the United Kingdom. One third of the sample were boys, and gender was associated with statistically significant differences on many variables. The results of this exploratory study highlight the need for further targeted research and more nuanced and inclusive counter-strategies.
I have a new paper out with Lisa Tompson at UCL called ‘Routine Activities and Proactive Police Activity: A Macro-scale Analysis of Police Searches in London and New York City’. This has been really fun to do and shows how most of the variation in stops and searches in London and New York during the year is associated with temporal rhythms such as days of the week, public holidays and special events.
The paper is open access thanks to support from UCL and we’ve already had some good feedback from senior police officers. The abstract is:
This paper explored how city-level changes in routine activities were associated with changes in frequencies of police searches using six years of police records from the London Metropolitan Police Service and the New York City Police Department. Routine activities were operationalised through selecting events that potentially impacted on (a) the street population, (b) the frequency of crime or (c) the level of police activity. GLS regression results indicated that routine activity variables (e.g. day of the week, periods of high demand for police service) can explain a large proportion of the variance in search frequency throughout the year. A complex set of results emerged, revealing cross-national dissimilarities and the differential impact of certain activities (e.g. public holidays). Importantly, temporal frequencies in searches are not reducible to associations between searches and recorded street crime, nor changes in on-street population. Based on the routine activity approach, a theoretical police-action model is proposed.
I have a new paper in Criminology and Criminal Justice called ‘Is metal theft committed by organized crime groups, and why does it matter?’. Sadly it’s not open access, but the abstract is:
Using the example of metal theft in the United Kingdom, this study used mixed methods to evaluate the accuracy of police estimates of the involvement of organized crime groups (OCGs) in crime. Police estimate that 20-30 per cent of metal theft is committed by OCGs, but this study found that only 0.5 per cent of metal thieves had previous convictions for offences related to OCGs, that only 1.3 per cent were linked to OCGs by intelligence information, that metal thieves typically offended close to their homes and that almost no metal thefts involved sophisticated offence methods. It appears that police may over-estimate the involvement of OCGs in some types of crime. The reasons for and consequences of this over-estimation are discussed.
I have a new paper published in Applied Geography with Kate Bowers called “Concentrations of railway metal theft and the locations of scrap-metal dealers”. It’s open-access thanks to funding from the EPSRC so anyone can read it online. The abstract is:
Metal theft has become a substantial crime problem in many areas. In response, several countries have introduced legislation to regulate scrap-metal recycling yards. However, at present there is little evidence to support this use of the market reduction approach (MRA) in preventing metal theft. The present study sought to test the underlying assumption of the MRA that the presence of a market for stolen property (in this case provided by scrap yards) drives thefts in a local area. This study tested for a spatial association between the locations of scrap yards and those of metal thefts. The density of industry, local burglary rate and road-accessibility of an area were controlled for. Metal thefts from railway lines in England were shown to be significantly more common in areas with more scrap-metal yards, high road accessibility and high population density. The results support the use of the MRA in relation to metal theft.
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I’ve made available three more live-ish Twitter maps, to add to the Met Police map that I published last year.
The NPAS Twitter Map is for the National Police Air Service. This shows the most recent tweet by each police helicopter in England and Wales (the Police Scotland helicopter doesn’t have a Twitter feed). Police air-support Twitter feeds are really useful for finding out why a helicopter is keeping you awake, and they’re also a good source of aerial pictures (particularly @NPASLondon and @NPAS_Redhill).
The British Transport Police Twitter Map shows the latest tweets by all of the local police teams for that force, and some of their senior officers. I chose them as the second force to create a map for because most of their accounts specify the station that the account is based at, so its easy to post them on a map.
The London Police Twitter Map shows all the police Twitter accounts in London, including those run by the Metropolitan Police, City of London Police, British Transport Police, National Crime Agency and NPAS. There are loads of them so it might take a minute to load all the tweets.
All the maps update every five minutes and tweets from the past hour are marked with a larger icon.
Together with Ella Cockbain (@DrEllaC) and Helen Brayley (@hbrayley) I’ve written a new report for Barnardo’s called “Not just a girl thing: a large-scale comparison of male and female users of child sexual exploitation services in the UK”. This is part of a larger project funded by the Nuffield Foundation into the sexual exploitation of boys and young men. The report is available free to view online, and the issues discussed will be explored in further detail in a journal article at a later date.
I’m one of several authors led by Lisa Tompson (@Lisa_Tompson) on a new paper in Cartography and Geographic Information Science called “UK open source crime data: accuracy and possibilities for research”. The paper looks at the extent to which open crime data published on police.uk can be used for criminological research. The research was conducted using funding from the National Institute for Health Research and the paper is available free online as an open-access publication.
The abstract of the article is:
In the United Kingdom, since 2011 data regarding individual police recorded crimes have been made openly available to the public via the police.uk website. To protect the location privacy of victims these data are obfuscated using geomasking techniques to reduce their spatial accuracy. This paper examines the spatial accuracy of the police.uk data to determine at what level(s) of spatial resolution - if any - it is suitable for analysis in the context of theory testing and falsification, evaluation research, or crime analysis. Police.uk data are compared to police recorded data for one large metropolitan Police Force and spatial accuracy is quantified for four different levels of geography across five crime types. Hypotheses regarding systematic errors are tested using appropriate statistical approaches, including methods of maximum likelihood. Finally, a “best-fit” statistical model is presented to explain the error as well as to develop a model that can correct it. The implications of the findings for researchers using the police.uk data for spatial analysis are discussed.
I have a new open-access paper with my PhD supervisors out in the Security Journal titled “The when and where of an emerging crime type: The example of metal theft from the railway network of Great Britain”. The article tests a number of findings from previous work on spatial and temporal patterns of crime to see if those findings hold for the new problem of metal theft from the railway network. Many common patterns in time and space were found to apply to metal theft, but some were not.
The abstract of the article is:
Metal theft has become an increasingly common crime in recent years, but lack of data has limited research into it. The present study used police-recorded crime data to study the spatial and temporal concentration of metal theft from the railway network of Great Britain. Metal theft was found to exhibit only weak seasonality, to be concentrated at night and to cluster in a few locations close to - but not in - major cities. Repeat-victimisation risk continued for longer than has been found for other crime types. These and other features appear to point to metal theft being a planned, rather than opportunistic, offence and to the role of scrap-metal dealers as facilitators.
Thanks to the UCL Library open-access team, this article is free to view online.
As part of my interest in how UK police use Twitter, I’ve added a live-ish map showing all the Metropolitan Police Service (MPS) Twitter accounts and the most recent tweet from each account. The map updates every five minutes and automatically highlights the most-recent tweet and all accounts that have sent a tweet in the past hour.
Although the map is live-ish, to keep down calls to the Twitter API tweets are cached on a local server and then put on the map. This means that, depending on when you load the map you might not get the very latest tweets immediately.
At present I’ve only done this for the MPS because I have to geocode all the accounts manually and that takes time. I’ve geocoded borough and neighbourhood accounts to the geographic centre of the area that they serve, which may occasionally suggest an officer is based in the middle of a park (although I seem to have avoided any locations being in lakes). The main MPS account (@metpoliceuk) is geocoded to New Scotland Yard, @MPSinthesky to their base at Lippitts Hill, @MPSonthewater to their base at Wapping, @MPSSTC to their headquarters at Palestra in Blackfriars and @MetPoliceEvents to the Special Operations Room (or, in Daily-Mail speak, “secret bunker”) on Lambeth Road.
I couldn’t geocode some accounts such as @MPSOntheStreet, @MPSFootballUnit, @MPSSpecials, @CdrRodhouseMPS, @CdrLetchfordMPS and @BJH251 because they either don’t have a single base or I don’t know where they’re based. If you have locations for any of these accounts, please let me know on Twitter.
I haven’t tested the map on anything older than Internet Explorer 8, so if you’re using an old browser then browse happy (or ask your IT department to upgrade their software).