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Policing and public health calls for service in Philadelphia. 费城的警察和公共卫生部门需要服务。
IF 6.1
Crime Science Pub Date : 2021-01-01 Epub Date: 2021-03-02 DOI: 10.1186/s40163-021-00141-0
Jerry H Ratcliffe
{"title":"Policing and public health calls for service in Philadelphia.","authors":"Jerry H Ratcliffe","doi":"10.1186/s40163-021-00141-0","DOIUrl":"https://doi.org/10.1186/s40163-021-00141-0","url":null,"abstract":"<p><p>This contribution outlines various spatial and temporal aspects of medical or public-health related calls for service from the public to police in Philadelphia in 2019. These incidents comprise about 8% of the police department's workload that originates from the public. Calls appear to be highly concentrated in a few areas, and specifically the Center City and Kensington neighborhoods. They are also more likely to occur late afternoon and evening. The article shows that some medical or public health activity initially masquerades as crime or other policing work and some events eventually determined to be police/crime activity can initially appear to be public health related. About 20% of activity in this area does not appear predictable from the initial call type as handled by police dispatch.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":" ","pages":"5"},"PeriodicalIF":6.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-021-00141-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25446951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 20
Functional and dysfunctional fear of COVID-19: a classification scheme. 对COVID-19的功能性和功能性恐惧:分类方案。
IF 6.1
Crime Science Pub Date : 2021-01-01 Epub Date: 2021-02-05 DOI: 10.1186/s40163-020-00137-2
Reka Solymosi, Jonathan Jackson, Krisztián Pósch, Julia A Yesberg, Ben Bradford, Arabella Kyprianides
{"title":"Functional and dysfunctional fear of COVID-19: a classification scheme.","authors":"Reka Solymosi,&nbsp;Jonathan Jackson,&nbsp;Krisztián Pósch,&nbsp;Julia A Yesberg,&nbsp;Ben Bradford,&nbsp;Arabella Kyprianides","doi":"10.1186/s40163-020-00137-2","DOIUrl":"https://doi.org/10.1186/s40163-020-00137-2","url":null,"abstract":"<p><p>Worry about COVID-19 is a central topic of research into the social and economic consequences of the COVID-19 pandemic. In this paper, we present a new way of measuring worry about catching COVID-19 that distinguishes between worry as a negative experience that damages people's quality of life (dysfunctional) and worry as an adaptive experience that directs people's attention to potential problems (functional). Drawing on work into fear of crime, our classification divides people into three groups: (1) the unworried, (2) the functionally worried (where worry motivates proactive behaviours that help people to manage their sense of risk) and (3) the dysfunctionally worried (where quality of life is damaged by worry and/or precautionary behaviour). Analysing data from two waves of a longitudinal panel study of over 1000 individuals living in ten cities in England, Scotland and Wales, we find differing levels of negative anxiety, anger, loneliness, unhappiness and life satisfaction for each of the three groups, with the dysfunctionally worried experiencing the most negative outcomes and the functionally worried experiencing less negative outcomes than unworried. We find no difference between groups in compliance and willingness to re-engage in social life. Finally, we show a difference between the dysfunctionally worried compared with functional and unworried groups in perceptions of risk (differentiating between likelihood, control and consequence). This finding informs what sort of content-targeted messaging aimed at reducing dysfunctional worry might wish to promote. We conclude with some thoughts on the applicability of our measurement scheme for future research.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":" ","pages":"4"},"PeriodicalIF":6.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00137-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25372409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
The new normal of web camera theft on campus during COVID-19 and the impact of anti-theft signage. 新冠疫情期间校园网络摄像头盗窃的新常态及防盗标识的影响。
IF 6.1
Crime Science Pub Date : 2021-01-01 DOI: 10.1186/s40163-021-00159-4
William A Chernoff
{"title":"The new normal of web camera theft on campus during COVID-19 and the impact of anti-theft signage.","authors":"William A Chernoff","doi":"10.1186/s40163-021-00159-4","DOIUrl":"https://doi.org/10.1186/s40163-021-00159-4","url":null,"abstract":"<p><strong>Objective: </strong>The opportunity for web camera theft increased globally as institutions of higher education transitioned to remote learning during COVID-19. Given the thousands of cameras currently installed in classrooms, many with little protection, the present study tests the effectiveness of anti-theft signage for preventing camera theft.</p><p><strong>Methods: </strong>Examined web camera theft at a southern, public university located in the United States of America by randomly assigning N = 104 classrooms to receive either anti-theft signage or no signage. Camera theft was analyzed using Blaker's exact test.</p><p><strong>Results: </strong>Classrooms not receiving anti-theft signage (control) were 3.42 times more likely to exhibit web camera theft than classrooms receiving anti-theft signage (medium effect size).</p><p><strong>Conclusions: </strong>Using classrooms as the unit of analysis presents new opportunities for not only future crime prevention experiments, but also improving campus safety and security. Also, preventing web camera theft on campus is both fiscally and socially responsible, saving money and ensuring inclusivity for remote learners.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"10 1","pages":"23"},"PeriodicalIF":6.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8527821/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10799541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Exploring regional variability in the short-term impact of COVID-19 on property crime in Queensland, Australia. 探讨2019冠状病毒病对澳大利亚昆士兰州财产犯罪短期影响的区域差异。
IF 6.1
Crime Science Pub Date : 2021-01-01 Epub Date: 2021-03-08 DOI: 10.1186/s40163-020-00136-3
Jason L Payne, Anthony Morgan, Alex R Piquero
{"title":"Exploring regional variability in the short-term impact of COVID-19 on property crime in Queensland, Australia.","authors":"Jason L Payne,&nbsp;Anthony Morgan,&nbsp;Alex R Piquero","doi":"10.1186/s40163-020-00136-3","DOIUrl":"https://doi.org/10.1186/s40163-020-00136-3","url":null,"abstract":"<p><p>Confronted by rapidly growing infection rates, hospitalizations and deaths, governments around the world have introduced stringent containment measures to help reduce the spread of COVID-19. This public health response has had an unprecedented impact on people's daily lives which, unsurprisingly, has also had widely observed implications in terms of crime and public safety. Drawing upon theories from environmental criminology, this study examines officially recorded property crime rates between March and June 2020 as reported for the state of Queensland, Australia. We use ARIMA modeling techniques to compute 6-month-ahead forecasts of property damage, shop theft, residential burglary, fraud, and motor vehicle theft rates and then compare these forecasts (and their 95% confidence intervals) with the observed data for March through to June. We conclude that, with the exception of fraud, all property offence categories declined significantly. For some offence types (shop stealing, other theft offences, and residential burglary), the decrease commenced as early as March. For other offence types, the decline was lagged and did not occur until April or May. Non-residential burglary was the only offence type to significantly increase, which it did in March, only to then decline significantly thereafter. These trends, while broadly consistent across the state's 77 local government areas still varied in meaningful ways and we discuss possible explanations and implications.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":" ","pages":"7"},"PeriodicalIF":6.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00136-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25477096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 40
Offline crime bounces back to pre-COVID levels, cyber stays high: interrupted time-series analysis in Northern Ireland. 线下犯罪反弹至疫情前水平,网络犯罪居高不下:北爱尔兰中断的时间序列分析
IF 6.1
Crime Science Pub Date : 2021-01-01 DOI: 10.1186/s40163-021-00162-9
David Buil-Gil, Yongyu Zeng, Steven Kemp
{"title":"Offline crime bounces back to pre-COVID levels, cyber stays high: interrupted time-series analysis in Northern Ireland.","authors":"David Buil-Gil,&nbsp;Yongyu Zeng,&nbsp;Steven Kemp","doi":"10.1186/s40163-021-00162-9","DOIUrl":"https://doi.org/10.1186/s40163-021-00162-9","url":null,"abstract":"<p><p>Much research has shown that the first lockdowns imposed in response to the COVID-19 pandemic were associated with changes in routine activities and, therefore, changes in crime. While several types of violent and property crime decreased immediately after the first lockdown, online crime rates increased. Nevertheless, little research has explored the relationship between multiple lockdowns and crime in the mid-term. Furthermore, few studies have analysed potentially contrasting trends in offline and online crimes using the same dataset. To fill these gaps in research, the present article employs interrupted time-series analysis to examine the effects on offline and online crime of the three lockdown orders implemented in Northern Ireland. We analyse crime data recorded by the police between April 2015 and May 2021. Results show that many types of traditional offline crime decreased after the lockdowns but that they subsequently bounced back to pre-pandemic levels. In contrast, results appear to indicate that cyber-enabled fraud and cyber-dependent crime rose alongside lockdown-induced changes in online habits and remained higher than before COVID-19. It is likely that the pandemic accelerated the long-term upward trend in online crime. We also find that lockdowns with stay-at-home orders had a clearer impact on crime than those without. Our results contribute to understanding how responses to pandemics can influence crime trends in the mid-term as well as helping identify the potential long-term effects of the pandemic on crime, which can strengthen the evidence base for policy and practice.</p>","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"10 1","pages":"26"},"PeriodicalIF":6.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10638335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
More crime in cities? On the scaling laws of crime and the inadequacy of per capita rankings—a cross-country study 城市犯罪率更高?论犯罪的比例规律与人均排名的不足——一项跨国研究
IF 6.1
Crime Science Pub Date : 2020-12-30 DOI: 10.1186/s40163-021-00155-8
Marcos A. C. Oliveira
{"title":"More crime in cities? On the scaling laws of crime and the inadequacy of per capita rankings—a cross-country study","authors":"Marcos A. C. Oliveira","doi":"10.1186/s40163-021-00155-8","DOIUrl":"https://doi.org/10.1186/s40163-021-00155-8","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"10 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42509172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Crime script analysis for adult image-based sexual abuse: a study of crime intervention points for retribution-style offenders 成人图像性虐待犯罪脚本分析:报应型罪犯犯罪干预点研究
IF 6.1
Crime Science Pub Date : 2020-12-01 DOI: 10.1186/s40163-020-00130-9
Abigail C. O’Hara, Ryan K. L. Ko, Lorraine Mazerolle, Jonah R. Rimer
{"title":"Crime script analysis for adult image-based sexual abuse: a study of crime intervention points for retribution-style offenders","authors":"Abigail C. O’Hara, Ryan K. L. Ko, Lorraine Mazerolle, Jonah R. Rimer","doi":"10.1186/s40163-020-00130-9","DOIUrl":"https://doi.org/10.1186/s40163-020-00130-9","url":null,"abstract":"Objective This research uses crime scripts to understand adult retribution-style image-based sexual abuse (RS-IBSA) offender decision-making and offending in offline and online environments. We explain the crime-commission process of adult RS-IBSA and identify crime intervention points at eight crime script stages. Methods Publicly released court transcripts of adult RS-IBSA prosecution cases (n = 18) in New Zealand from 2015 to 2018 were utilised to examine the crime-commission process of adult RS-IBSA. We analysed the court transcripts thematically at offence-level prior to constructing the crime scripts. Findings The study identified four types of adult RS-IBSA acts including the non-consensual dissemination of a victim’s intimate images, violent cyber sextortion, covert intimate photography, and unauthorised access of a victim’s phone/media. From our analysis, we identified three script tracks and constructed three distinct crime scripts: (1) threats, sextortion and dissemination; (2) unauthorised access of a victim’s mobile device and dissemination; and (3) covert intimate filming. We highlight areas for potential intervention for law enforcement agencies and policy makers to increase deterrence and personal security in online and offline spaces. Conclusion Adult RS-IBSA occurs in a range of dating and domestic contexts. This study develops crime scripts for adult RS-IBSA and advances our understanding of how the Internet/smartphones/digital media translates into virtual crime scenes with opportunities for maximum harm infliction. We offer several policy implications including revising current RS-IBSA legislation and supporting law enforcement agencies with policing online and offline intimate relationship spaces through situational prevention.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"58 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
To SPB or not to SPB? A mixed methods analysis of self-protective behaviours to prevent repeat victimisation from cyber abuse SPB 还是不 SPB?用混合方法分析自我保护行为,防止网络虐待的重复伤害
IF 6.1
Crime Science Pub Date : 2020-11-11 DOI: 10.1186/s40163-020-00134-5
Zarina I. Vakhitova, Rob I. Mawby, Clair L. Alston-Knox, Callum A. Stephens
{"title":"To SPB or not to SPB? A mixed methods analysis of self-protective behaviours to prevent repeat victimisation from cyber abuse","authors":"Zarina I. Vakhitova, Rob I. Mawby, Clair L. Alston-Knox, Callum A. Stephens","doi":"10.1186/s40163-020-00134-5","DOIUrl":"https://doi.org/10.1186/s40163-020-00134-5","url":null,"abstract":"This paper presents the findings from a mixed-methods examination of self-protective behaviours (SPBs) adopted by victims of cyber abuse from the rational choice perspective. The data from a sample of the U.S. adults ( $$N = 746$$ N = 746 ), members of an online opt-in panel, were analysed to first distinguish the types of SPBs adopted by victims of cyber abuse using a thematic analysis of open-ended responses. We then identified the factors associated with an increased likelihood of adopting SPBs and the specific identified types of SPBs using logistic regression with Bayesian variable selection and a stochastic search algorithm. Of the six identified types of SPBs, adjusting privacy settings was the most commonly reported response, and improving security (e.g. changing passwords, etc.) was the least common SPB. Older victims who reported higher than the average perceived impact from victimisation, were abused by a stranger and experienced either surveillance of their online activities or multiple types of abuse, were significantly more likely to adopt an SPB. Our findings inform strategies for both Internet user education and for preventing cyber abuse victimisation.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"2012 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A framework for estimating crime location choice based on awareness space 基于感知空间的犯罪地点选择估计框架
IF 6.1
Crime Science Pub Date : 2020-11-04 DOI: 10.1186/s40163-020-00132-7
Sophie Curtis-Ham, W. Bernasco, O. Medvedev, D. Polaschek
{"title":"A framework for estimating crime location choice based on awareness space","authors":"Sophie Curtis-Ham, W. Bernasco, O. Medvedev, D. Polaschek","doi":"10.1186/s40163-020-00132-7","DOIUrl":"https://doi.org/10.1186/s40163-020-00132-7","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00132-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43361221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
A machine learning analysis of serious misconduct among Australian police 对澳大利亚警方严重不当行为的机器学习分析
IF 6.1
Crime Science Pub Date : 2020-10-31 DOI: 10.1186/s40163-020-00133-6
Timothy I. C. Cubitt, K. Wooden, K. Roberts
{"title":"A machine learning analysis of serious misconduct among Australian police","authors":"Timothy I. C. Cubitt, K. Wooden, K. Roberts","doi":"10.1186/s40163-020-00133-6","DOIUrl":"https://doi.org/10.1186/s40163-020-00133-6","url":null,"abstract":"","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00133-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65836688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
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