Burglary in London: insights from statistical heterogeneous spatial point processes

To obtain operational insights regarding the crime of burglary in London, we consider the estimation of the effects of covariates on the intensity of spatial point patterns. Inspired by localized properties of criminal behaviour, we propose a spatial extension to mixtures of generalized linear models from the mixture modelling literature. The Bayesian model proposed is a finite mixture of Poisson generalized linear models such that each location is probabilistically assigned to one of the groups. Each group is characterized by the regression coefficients, which we subsequently use to interpret the localized effects of the covariates. By using a blocks structure of the study region, our approach enables specifying spatial dependence between nearby locations. We estimate the proposed model by using Markov chain Monte Carlo methods and we provide a Python implementation

Local inequality and crime: exploring how variation in the scale of the inequality measures affects relationships betweeen inequality and crime

There is considerable interest in the role of inequality in affecting social outcomes yet there is also uncertainty and disagreement about the appropriate scale at which to measure inequality within such analyses. Whilst some have argued for larger-area inequality measures to be used there are good theoretical, empirical and intuitive grounds to think that local inequality may have relevance as a driver of social ills. This paper explores whether differing understandings of ‘local’ inequality does—or can—matter and, if so, within which contexts this is the case. Contrasting findings across the two areas support the notion that local inequality does have relevance to social outcomes but that the socio-spatial context matters

In and around: identifying predictors of theft within and near to major mass underground transit systems

This article identifies factors that encourage or reduce pick-pocketing at underground rail stations through a case study analysis of the London Underground. Negative binomial Poisson regression models found predictor variables of pick-pocketing selected from the internal characteristics of stations and features of their nearby surroundings. Factors that increased risk were those associated with greater congestion inside stations including lifts, waiting rooms and fewer platforms; and increased levels of accessibility near stations, more paths and roads. Features that reduced risk were those likely to encourage detection and guardianship; stations with more personal validators, staffing levels and shop rentals; and the presence of more domestic buildings nearby. Station type was also influential; those that were ‘attractors’ of crime and those frequently used by tourists were at greater risk. The findings suggest a transmission of theft risk between the internal settings of underground stations and their nearby surroundings

New urbanism, crime and the suburbs: a review of the evidence

Sustainability now influences government policy in the UK, Australia and USA and planning policy currently advocates high density, mixed-use residential developments in 'walkable', permeable neighbourhoods, close to public transport, employment and amenities. This clearly demonstrates the growing popularity, influence and application of New Urbanist ideas.This paper reviews the criminological research relating to New Urbanism associated with the three key issues of permeability, rear laneway car parking and mixed-use development. These key issues are discussed from an environmental criminology perspective and challenge New Urbanist assumptions concerning crime. The paper proposes that crime prevention through environmental design (CPTED) and its crime risk assessment model represents a valuable tool for New Urbanists to utilise to reduce opportunities for crime and tackle fear of crime in the community. Recommendations for future research and collaboration are discussed

A comparison of methods for temporal analysis of aoristic crime

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

Inkjet printed organic detectors with flat responsivity up to the NIR and inherent UV optical filtering

The use of printing technologies is widely recognized to be a major advantage for the deployment of large-area organic electronics and there is still plenty of room for exploring new strategies to exploit printing of solution processable conductors and semiconductors. In this paper, we show for the first time how an additive layer-by-layer deposition, achieved through inkjet printing, enables the fabrication of broadband organic photodetectors with a flat responsivity spectrum extending to the near-infrared (NIR). The use of narrow bandgap polymers enables light detection up to 1.1 μm. By controlling the photoactive layer thickness in a range between 150 nm and 4 μm, we could filter the contribution from UV and Vis absorption to the photocurrent, while keeping light detection in the NIR. The visible detection efficiency decreases of a 70% at 425 nm for thicknesses going from 250 nm up to 2 μm, while the NIR detection decreases only of 31% at 950 nm, and increases of 26% at 1020 nm. This photoactive layer thickness dependent UV–vis optical filtering enables the control over the shape of the responsivity spectra

It Looks Good, but What is it Like to Live There? Exploring the Impact of Innovative Housing Design on Crime

This paper reports on the findings of a collaborative project (funded by the Home Office and managed by the Commission for Architecture and the Built Environment - CABE) which was conducted in late 2009 and early 2010. The project set out to strengthen and update the evidence base on the impact of design on a range of crime types – with a specific focus upon housing developments acclaimed for their innovative design and award winning architecture. This paper presents the findings of an in-depth assessment of the impact of housing design features on crime. Utilising a comprehensive data collection exercise, the specific design features of thousands of homes were collated and assessed against police recorded crime data. The design features were based upon the key elements of Crime Prevention Through Environmental Design (CPTED) including road layout, house design, surveillance, territoriality, car parking, communal space, management and maintenance and physical security. The unique and painstaking methodology not only provided an excellent dataset for analysis, but also highlighted the need both for greater conceptual clarity within CPTED and for crime-risk assessments to be based on the careful operationalisation and measurement of CPTED factors. As well as assessing the impact of specific (and combined) design features upon crime, the research also resulted in the production of a new data collection tool designed to address the weaknesses of existing checklists in assessing innovative contemporary developments, which are often unconventional in nature. The paper explores the degree of conflict and/or synergy between the traditional principles of CPTED and contemporary directions in architecture and design. Finally the paper considers the extent to which traditional CPTED principles remain relevant within contemporary residential developments and explores whether areas of revision are required

Evaluating the No Cold Calling zones in Peterborough, England: application of a novel statistical method for evaluating neighbourhood policing policies

Some police forces in the UK institute ‘No Cold Calling’ (NCC) zones to reduce cold callings (unsolicited visits to sell products or services), which are often associated with rogue trading and distraction burglary. This paper evaluates the NCC-targeted areas chosen in 2005–06 in Peterborough and reports whether they experienced a measurable impact on their burglary rates in the period up to 2008. Time-series data for burglary at the census output area level are analysed using a Bayesian hierarchical modelling approach to address issues of data sparsity and lack of randomised allocation of areas to treatment groups that are often encountered in small-area quantitative policy evaluation. To ensure internal validity, we employ the interrupted time-series quasi-experimental design embedded within a matched case-control framework. Results reveal a positive impact of NCC zones on reducing burglary rates in the targeted areas compared with the control areas