Crime Science最新文献_第9页

RETRACTED ARTICLE: Do offenders avoid offending near home? A systematic review of the buffer zone hypothesis 文章撤回:违法者会避免在家附近犯案吗?对缓冲地带假说的系统回顾

IF 6.1

Crime Science Pub Date : 2020-05-27 DOI: 10.1186/s40163-020-00118-5

W. Bernasco, Remco van Dijke

引用次数: 9

Near-repeat victimization of sex crimes and threat incidents against women and girls in Tokyo, Japan 在日本东京，针对妇女和女孩的性犯罪和威胁事件几乎重复发生

IF 6.1

Crime Science Pub Date : 2020-05-13 DOI: 10.1186/s40163-020-00114-9

Mamoru Amemiya, T. Nakaya, T. Shimada

引用次数: 5

Further rejection of the cybercrime hypothesis 进一步否定网络犯罪假说

IF 6.1

Crime Science Pub Date : 2020-05-12 DOI: 10.1186/s40163-020-00113-w

Graham Farrell, Daniel Birks

引用次数: 0

Initial evidence on the relationship between the coronavirus pandemic and crime in the United States 关于冠状病毒大流行与美国犯罪之间关系的初步证据

IF 6.1

Crime Science Pub Date : 2020-04-27 DOI: 10.31235/osf.io/ep87s

M. Ashby

{"title":"Initial evidence on the relationship between the coronavirus pandemic and crime in the United States","authors":"M. Ashby","doi":"10.31235/osf.io/ep87s","DOIUrl":"https://doi.org/10.31235/osf.io/ep87s","url":null,"abstract":"The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43871188","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: 169

Learning to rank spatio-temporal event hotspots 学习对时空事件热点进行排序

IF 6.1

Crime Science Pub Date : 2020-03-20 DOI: 10.1186/s40163-020-00112-x

George Mohler, Michael Porter, Jeremy Carter, Gary LaFree

{"title":"Learning to rank spatio-temporal event hotspots","authors":"George Mohler, Michael Porter, Jeremy Carter, Gary LaFree","doi":"10.1186/s40163-020-00112-x","DOIUrl":"https://doi.org/10.1186/s40163-020-00112-x","url":null,"abstract":"Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk crime and social harm hotspots in a city. A crucial step in the implementation of these strategies is the construction of scoring models used to rank spatial hotspots. While these methods are evaluated by area normalized Recall@k (called the predictive accuracy index), models are typically trained via maximum likelihood or rules of thumb that may not prioritize model accuracy in the top k hotspots. Furthermore, current algorithms are defined on fixed grids that fail to capture risk patterns occurring in neighborhoods and on road networks with complex geometries. Results We introduce CrimeRank, a learning to rank boosting algorithm for determining a crime hotspot map that directly optimizes the percentage of crime captured by the top ranked hotspots. The method employs a floating grid combined with a greedy hotspot selection algorithm for accurately capturing spatial risk in complex geometries. We illustrate the performance using crime and traffic incident data provided by the Indianapolis Metropolitan Police Department, IED attacks in Iraq, and data from the 2017 NIJ Real-time crime forecasting challenge. Conclusion Our learning to rank strategy was the top performing solution (PAI metric) in the 2017 challenge. We show that CrimeRank achieves even greater gains when the competition rules are relaxed by removing the constraint that grid cells be a regular tessellation.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"21 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882404","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

Constellations of youth criminogenic factors associated with young adult violent criminal behavior 与青少年暴力犯罪行为相关的青少年犯罪诱因组合

IF 6.1

Crime Science Pub Date : 2020-01-30 DOI: 10.1186/s40163-020-0111-2

Menno Segeren, Thijs Fassaert, Matty de Wit, Arne Popma

引用次数: 0

What is security worth to consumers? Investigating willingness to pay for secure Internet of Things devices 安全对消费者来说值多少钱？调查安全物联网设备的支付意愿

IF 6.1

Crime Science Pub Date : 2020-01-08 DOI: 10.1186/s40163-019-0110-3

John M. Blythe, Shane D. Johnson, Matthew Manning

{"title":"What is security worth to consumers? Investigating willingness to pay for secure Internet of Things devices","authors":"John M. Blythe, Shane D. Johnson, Matthew Manning","doi":"10.1186/s40163-019-0110-3","DOIUrl":"https://doi.org/10.1186/s40163-019-0110-3","url":null,"abstract":"The Internet of Things (IoT) is considered the next technological revolution. IoT devices include once everyday objects that are now internet connected, such as smart locks and smart fridges, but also new types of devices to include home assistants. However, while this increased interconnectivity brings considerable benefits, it can and does increase people’s exposure to crime risk. This is particularly the case as most devices are developed without security in mind. One reason for this is that there is little incentive for manufacturers to make devices secure by design, and the costs of so doing do not encourage it. The principle aim of the current paper was to estimate the extent to which consumers are willing to pay for improved security in internet connected products. The second aim was to examine whether this is conditioned by their exposure to security-related information. Using an experimental design, and a contingent valuation method, we find that people are willing to pay for improved security and that for some devices, this increases if they are exposed to information about security prior to stating their willingness to pay. The implications of our findings for industry and the secure by design agenda are discussed.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"47 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882406","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

Somehow I always end up alone: COVID-19, social isolation and crime in Queensland, Australia. 不知何故，我总是孤独终老:在澳大利亚昆士兰州，COVID-19、社会隔离和犯罪。

IF 6.1

Crime Science Pub Date : 2020-01-01 Epub Date: 2020-11-24 DOI: 10.1186/s40163-020-00135-4

Martin A Andresen, Tarah Hodgkinson

{"title":"Somehow I always end up alone: COVID-19, social isolation and crime in Queensland, Australia.","authors":"Martin A Andresen, Tarah Hodgkinson","doi":"10.1186/s40163-020-00135-4","DOIUrl":"https://doi.org/10.1186/s40163-020-00135-4","url":null,"abstract":"The COVID-19 pandemic has dramatically affected social life. In efforts to reduce the spread of the virus, countries around the world implemented social restrictions, including social distancing, working from home, and the shuttering of numerous businesses. These social restrictions have also affected crime rates. In this study, we investigate the impact of the COVID-19 pandemic on the frequency of offending (crimes include property, violent, mischief, and miscellaneous) in Queensland, Australia. In particular, we examine this impact across numerous settings, including rural, regional and urban. We measure these shifts across the restriction period, as well as the staged relaxation of these restrictions. In order to measure impact of this period we use structural break tests. In general, we find that criminal offences have significantly decreased during the initial lockdown, but as expected, increased once social restrictions were relaxed. These findings were consistent across Queensland's districts, save for two areas. We discuss how these findings are important for criminal justice and social service practitioners when operating within an extraordinary event.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"25"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00135-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38651721","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

Crime and coronavirus: social distancing, lockdown, and the mobility elasticity of crime. 犯罪和冠状病毒:社交距离、封锁和犯罪的流动性弹性。

IF 6.1

Crime Science Pub Date : 2020-01-01 Epub Date: 2020-07-06 DOI: 10.1186/s40163-020-00121-w

Eric Halford, Anthony Dixon, Graham Farrell, Nicolas Malleson, Nick Tilley

{"title":"Crime and coronavirus: social distancing, lockdown, and the mobility elasticity of crime.","authors":"Eric Halford, Anthony Dixon, Graham Farrell, Nicolas Malleson, Nick Tilley","doi":"10.1186/s40163-020-00121-w","DOIUrl":"https://doi.org/10.1186/s40163-020-00121-w","url":null,"abstract":"Governments around the world restricted movement of people, using social distancing and lockdowns, to help stem the global coronavirus (COVID-19) pandemic. We examine crime effects for one UK police force area in comparison to 5-year averages. There is variation in the onset of change by crime type, some declining from the WHO 'global pandemic' announcement of 11 March, others later. By 1 week after the 23 March lockdown, all recorded crime had declined 41%, with variation: shoplifting (- 62%), theft (- 52%), domestic abuse (- 45%), theft from vehicle (- 43%), assault (- 36%), burglary dwelling (- 25%) and burglary non-dwelling (- 25%). We use Google Covid-19 Community Mobility Reports to calculate the mobility elasticity of crime for four crime types, finding shoplifting and other theft inelastic but responsive to reduced retail sector mobility (MEC = 0.84, 0.71 respectively), burglary dwelling elastic to increases in residential area mobility (- 1), with assault inelastic but responsive to reduced workplace mobility (0.56). We theorise that crime rate changes were primarily caused by those in mobility, suggesting a mobility theory of crime change in the pandemic. We identify implications for crime theory, policy and future research.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"11"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00121-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38297536","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: 4

Disentangling community-level changes in crime trends during the COVID-19 pandemic in Chicago. 解开芝加哥COVID-19大流行期间社区层面犯罪趋势的变化。

IF 6.1

Crime Science Pub Date : 2020-01-01 Epub Date: 2020-10-27 DOI: 10.1186/s40163-020-00131-8

Gian Maria Campedelli, Serena Favarin, Alberto Aziani, Alex R Piquero

{"title":"Disentangling community-level changes in crime trends during the COVID-19 pandemic in Chicago.","authors":"Gian Maria Campedelli, Serena Favarin, Alberto Aziani, Alex R Piquero","doi":"10.1186/s40163-020-00131-8","DOIUrl":"10.1186/s40163-020-00131-8","url":null,"abstract":"Recent studies exploiting city-level time series have shown that, around the world, several crimes declined after COVID-19 containment policies have been put in place. Using data at the community-level in Chicago, this work aims to advance our understanding on how public interventions affected criminal activities at a finer spatial scale. The analysis relies on a two-step methodology. First, it estimates the community-wise causal impact of social distancing and shelter-in-place policies adopted in Chicago via Structural Bayesian Time-Series across four crime categories (i.e., burglary, assault, narcotics-related offenses, and robbery). Once the models detected the direction, magnitude and significance of the trend changes, Firth's Logistic Regression is used to investigate the factors associated to the statistically significant crime reduction found in the first step of the analyses. Statistical results first show that changes in crime trends differ across communities and crime types. This suggests that beyond the results of aggregate models lies a complex picture characterized by diverging patterns. Second, regression models provide mixed findings regarding the correlates associated with significant crime reduction: several relations have opposite directions across crimes with population being the only factor that is stably and positively associated with significant crime reduction.","PeriodicalId":37844,"journal":{"name":"Crime Science","volume":"9 1","pages":"21"},"PeriodicalIF":6.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40163-020-00131-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38555802","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: 85