Abstract Purpose Crime is known to concentrate in micro places, with urban facilities often acting as crime generators or attractors. While studies in the Global North have widely examined the association between urban facilities and property crime, systematic empirical evidence from Global South cities remains limited. This study investigates how different categories of urban facilities are associated with property crime in Nagpur, India. Methods Police-recorded incidents of property crimes like robbery, burglary, and theft were spatially analyzed in relation to eighteen categories of urban facilities, including ATMs, banks, markets, schools, hospitals, and transit places. Kernel Density Estimation was used to delineate 341 sub-zones of varying crime intensity. Location Quotient quantified the relative geospatial distribution of property crimes and urban facilities. Multiple Linear Regression models were employed to assess statistical associations between property crimes and urban facilities. Results The analysis reveals systematic associations between property crimes and urban facilities: robbery clustered around hospitals and markets, burglary around banks, colleges, schools, religious places, and shops, and theft around a wide array of urban facilities, including ATMs, bars, hotels, and office buildings. Conclusions These findings highlight the importance of integrating urban facility-based risk factors into crime-prevention strategies. Targeted interventions, such as enhanced surveillance, place management, and design modifications at high-crime urban facilities, can be more effective than uniform citywide measures. This study advances environmental criminology by extending empirical evidence to a Global South context and demonstrating a replicable geospatial assessment framework.
The nature of crime is changing, and so are the opportunities that enable it. Fifty years since the seminal work on crime as opportunity, we suggest that there is a need to consider ways to measure how and why opportunities have evolved. Specifically, we propose four mechanisms of crime opportunity evolution, inspired by biological speciation theory and adapted here to account for the cultural transmission of criminal behaviour, with evolution measured through changes in modus operandi. These are the SUPA mechanisms: Space-Driven (allopatric), Utility-Motivated (sympatric), Pressure-Driven (peripatric), and Attraction-Led (parapatric). We connect these mechanisms of evolution to crime opportunity theory and situational crime prevention. Space-driven opportunities arise through distinct geographic contexts; utility-motivated as a result of success (through choice or chance) within the same opportunity context (often made possible by new tools or technologies); pressure-driven evolution through the blocking of prior crime context-mechanism combinations; and, attraction-led evolution through a voluntary change in context. We illustrate each mechanism with historical examples, discuss how we might best prepare for each type, and consider how the SUPA mechanisms might apply to horizon scanning and future crime prevention practice.
Abstract Purpose Fairness in Predictive Policing (PP) has been explored by many researchers. However, to the best of our knowledge, no work has quantified the impact of event-level data incompleteness in spatio-temporal prediction on each ethnicity. In this paper, we propose a model to quantify the impact of recorded crime data incompleteness on ethnic disparities in policing. We also examine whether these disparities depend on where in the city data are missing. Methods We introduce a neighbourhood-level method that allocates PP prediction errors (false positives as potential over-policing, false negatives as potential under-policing) to ethnic groups in proportion to their share of the neighbourhood population. Using Chicago crime records (2022–2024), census data, and HAGEN (a state-of-the-art spatial-temporal PP model), we explore data incompleteness by reducing the original crime data at varying ratios in two settings: (i) 25–100% reductions in neighbourhoods with low racial diversity; (ii) 50% or 100% reductions in communities dominated by a single ethnicity (Hispanic, Non-Hispanic Black, Non-Hispanic White, or Non-Hispanic Asian). Enforcement bias outcomes are then compared across ethnicities and scenarios. Results Removing records from a single-ethnicity-majority community generally reduces predicted over-policing and increases predicted under-policing for that ethnicity across the whole study area, with Asian-majority scenarios a consistent exception. In low-diversity neighbourhoods, greater missingness amplifies prediction bias against Non-Hispanic Black residents specifically: predicted over-policing falls and predicted under-policing rises, with the opposite holding for other groups. The largest overall shifts occur when data are removed from Black-majority communities. Conclusions Incomplete crime records could propagate into substantial, ethnically unequal disparities in model-predicted policing exposure, whose direction depends on where missingness concentrates. The findings motivate auditing missingness and its demographic distribution as a prerequisite for deploying event-level PP systems.
This study examines organisational participation in the Goldstein Awards for Excellence in Problem-Oriented Policing between 1993 and 2023. The analysis covers all 1,208 submissions available in the award repository, representing 391 organisations. Participation was predominantly episodic and highly concentrated. Most organisations submitted once, while a small group accounted for a disproportionate share of entries and participated over extended periods. Detailed analysis of 238 projects from the most frequent participants found little evidence of project iteration within the submission record, although authors and problem types recurred across entries. The findings map the distribution, concentration and recurrence of Goldstein Award participation over three decades. They show how the submission of POP activity for external recognition has been sustained by a relatively small group of organisations and provide a basis for further research into the organisational conditions associated with repeated participation.
Police authorities breached several encrypted chat services in a series of data driven investigations. These services are mostly used by offenders, and the results were thousands of arrests. Limited research has studied the ensuing court cases. In this study, we discuss the strengths and limitations of this data source, and compare the contents of three services: EncroChat, SkyECC, and Anom. We use a sample of 195 court cases from Sweden between 2019 and 2024, where evidence from the encrypted chats was used. The cases involved 667 individuals and 1519 prosecuted offenses, mostly serious drug offences. Network analysis indicates that serious drug offences are strongly connected to violence and weapons in EncroChat, cross-border drug trafficking in SkyECC, and weapons offences in Anom. The average sentence length did not differ between the platforms. Given the sequential breach of the services, this suggests that offenders continued using them for planning serious offending, despite public knowledge of the police interventions. Information from encrypted chat services is an important supplement for research, policy, and practice concerning criminal groups.
