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.
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.
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.
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.
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.
Recently, against a backdrop of general reductions in acquisitive crime, increases have been observed in the frequency of metal theft offences. This is generally attributed to increases in metal prices in response to global demand exceeding supply. The main objective of this article was to examine the relationship between the price of copper and levels of copper theft, focusing specifically on copper cable theft from the British railway network. Results indicated a significant positive correlation between lagged increases in copper price and copper cable theft. No support was found for rival hypotheses concerning U.K. unemployment levels and the general popularity of theft as crime type. An ancillary aim was to explore offender modus operandi over time, which is discussed in terms of its implications for preventing copper cable theft. The authors finish with a discussion of theft of other commodities in price-volatile markets.
Using open crime data from police.uk and map data from OS OpenData, I’ve created a map of violent and sexual crime hotspots in London, based on 135,000 crimes that occurred between April 2012 and March 2013. The map is available as an A0-sized PDF under a CC-BY licence.
Objectives: To test the accuracy of various methods previously proposed (and one new method) to estimate offence times where the actual time of the event is not known.
Methods: For 303 thefts of pedal cycles from railway stations, the actual offence time was determined from closed-circuit television and the resulting temporal distribution compared against commonly-used estimated distributions using circular statistics and analysis of residuals.
Results: Aoristic analysis and allocation of a random time to each offence allow accurate estimation of peak offence times. Commonly-used deterministic methods were found to be inaccurate and to produce misleading results.
Conclusions: It is important that analysts use the most accurate methods for temporal distribution approximation to ensure any resource decisions made on the basis of peak times are reliable.
The paper is free to access online thanks to the journal editors’ gracious offer to assist with the article-processing fee.