Crime Science最新文献

Fuel prices have increased sharply over the past year. In this study we test the hypothesis that increases in the price of fuel are associated with increases in motorists filling their fuel tank and driving off without paying. We use weekly crime data from six police forces in England and Wales for the period January 2018 to July 2022, combined with regional data on the number of fuel sales and average fuel prices. Our results demonstrate an overall weak price-theft relationship for the 238 week study period, less so than in previous studies. However, we find strong evidence that the recent spike in fuel prices was associated with elevated levels of fuel theft. The implications of our findings for future research and crime prevention are discussed.

Research on pandemic domestic abuse trends has produced inconsistent findings reflecting differences in definitions, data and method. This study analyses 43,488 domestic abuse crimes recorded by a UK police force. Metrics and analytic approaches are tailored to address key methodological issues in three key ways. First, it was hypothesised that reporting rates changed during lockdown, so natural language processing was used to interrogate untapped free-text information in police records to develop a novel indicator of change in reporting. Second, it was hypothesised that abuse would change differentially for those cohabiting (due to physical proximity) compared to non-cohabitees, which was assessed via a proxy measure. Third, the analytic approaches used were change-point analysis and anomaly detection: these are more independent than regression analysis for present purposes in gauging the timing and duration of significant change. However, the main findings were largely contrary to expectation: (1) domestic abuse did not increase during the first national lockdown in early 2020 but increased across a prolonged post-lockdown period, (2) the post-lockdown increase did not reflect change in reporting by victims, and; (3) the proportion of abuse between cohabiting partners, at around 40 percent of the total, did not increase significantly during or after the lockdown. The implications of these unanticipated findings are discussed.

Supplementary information: The online version contains supplementary material available at 10.1186/s40163-023-00190-7.

Introduction: Lip print of an individual is distinct and could be a useful form of evidence to identify the ethnicity of a terrorist.

Objectives: The study analyzed the distribution of lip print patterns of two major ethnic groups in Nigeria; Ibo and Hausa, to develop a strategic plan to check the wave of ethnically driven terrorism in Nigeria, carried out by groups such as Boko Haram and Indigeneous People of Biafra (IPOB).

Materials and methods: The study comprised 800 participants of Ibo and Hausa ethnic groups (400 males and 400 females). The study adopted a digital method of lip print analysis and followed the guidelines outlined by the Institute of Medicine (IOM) for anthropometric measurements. The lip was classified, using Tsuchihashi and Suzuki method of classification.

Results: The predominant lip print patterns of Ibo were Type I with complete vertical groove and Type III with intersect of groove for male and Type III for female. Type I' with partial length groove was the predominant pattern for both male and female Hausa. The lip width and height of female Ibo were longer than that of the Hausa counterpart (P < 0.05), but none of the anthropometric variables could predict the lip print pattern.

Conclusion: The lip size and print could aid forensic investigation, though genetic diversity and heterogeneity of ethnic groups in Nigeria, especially that of Ibo, could setback use of lip print pattern to identify the ethnicity of an unknown individual in Nigeria to help determine the terrorist group to which they may belong.

Geostatistical methods currently used in modern epidemiology were adopted in crime science using the example of the Opole province, Poland, in the years 2015-2019. In our research, we applied the Bayesian spatio-temporal random effects models to detect 'cold-spots' and 'hot-spots' of the recorded crime numbers (all categories), and to ascertain possible risk factors based on the available statistical population (demographic), socio-economic and infrastructure area characteristics. Overlapping two popular geostatistical models in the analysis, 'cold-spot' and 'hot-spot' administrative units were detected which displayed extreme differences in crime and growth rates over time. Additionally, using Bayesian modeling four categories of possible risk factors were identified in Opole. The established risk factors were the presence of doctors/medical personnel, road infrastructure, numbers of vehicles, and local migration. The analysis is directed toward both academic and police personnel as a proposal for an additional geostatistical control instrument supporting the management and deployment of local police based on easily available police crime records and public statistics.

Supplementary information: The online version contains supplementary material available at 10.1186/s40163-023-00189-0.