Journal of Quantitative Criminology最新文献

Arrests and the Opioid Epidemic: An Investigation into the Spatial and Social Network Spillover of Opioid Overdoses in Chicago. 逮捕和阿片类药物流行：对芝加哥阿片类药物过量的空间和社会网络溢出效应的调查。

IF 3.3 1区社会学

Journal of Quantitative Criminology Pub Date : 2025-05-31 DOI: 10.1007/s10940-025-09612-y

Megan Evans, Corina Graif, Anna Newell

{"title":"Arrests and the Opioid Epidemic: An Investigation into the Spatial and Social Network Spillover of Opioid Overdoses in Chicago.","authors":"Megan Evans, Corina Graif, Anna Newell","doi":"10.1007/s10940-025-09612-y","DOIUrl":"10.1007/s10940-025-09612-y","url":null,"abstract":"Objectives: This study investigates the role of criminal justice intervention practices, i.e., opioid arrests, in effectively preventing or increasing opioid overdoses, paying particular attention to whether arrests in spatially proximate or socially connected communities lead to the displacement or prevention of opioid overdoses in a local community.Methods: Combining data from the Cook County medical examiner, emergency medical services information, arrest reports, and commuting network statistics for Chicago's 77 community areas between 2016 and 2019, this study uses fixed effects spatial autoregressive models with spatial lags to explain community-level opioid overdose rates.Results: We find evidence for the diffusion and displacement of overdose risk as well as the diffusion of overdose-reducing benefits. Findings suggest complex spatial and social spillover mechanisms that both diffuse and prevent opioid overdoses, dependent on the type of opioid-related crime and overdose rate investigated.Conclusions: These results have important implications for understanding the effectiveness of criminal justice policies in their goal of preventing opioid-related crime and overdoses and provide insights for designing more appropriate and effective policy responses to address substance use and illicit drug markets.","PeriodicalId":48080,"journal":{"name":"Journal of Quantitative Criminology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12952898/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147349411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives. 使用指令调整的大型语言模型识别警察事件叙述中的脆弱性指标。

IF 3.3 1区社会学

Journal of Quantitative Criminology Pub Date : 2025-01-01 Epub Date: 2025-06-17 DOI: 10.1007/s10940-025-09611-z

Sam Relins, Daniel Birks, Charlie Lloyd

{"title":"Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives.","authors":"Sam Relins, Daniel Birks, Charlie Lloyd","doi":"10.1007/s10940-025-09611-z","DOIUrl":"10.1007/s10940-025-09611-z","url":null,"abstract":"Objectives: Police routinely collect unstructured narrative reports of their interactions with civilians. These accounts have the potential to reveal the extent of police engagement with vulnerable populations. We test whether large language models (LLMs) can effectively replicate human qualitative coding of these narratives-a task that would otherwise be highly resource intensive.Methods: Using publicly available narrative reports from Boston Police Department, we compare human-generated and LLM-generated labels for four vulnerabilities: mental ill health, substance misuse, alcohol dependence, and homelessness. We assess multiple LLM sizes and prompting strategies, measure label variability through repeated prompts, and conduct counterfactual experiments to examine potential classification biases related to sex and race.Results: LLMs demonstrate high agreement with human coders in identifying narratives without vulnerabilities, particularly when repeated classifications are unanimous or near-unanimous. Human-LLM agreement improves with larger models and tailored prompting strategies, though effectiveness varies by vulnerability type. These findings suggest a human-LLM collaborative approach, where LLMs screen the majority of cases whilst humans review ambiguous instances, would significantly reduce manual coding requirements. Counterfactual analyses indicate minimal influence of subject sex and race on LLM classifications beyond those expected by chance.Conclusions: LLMs can substantially reduce resource requirements for analyzing large narrative datasets, whilst enhancing coding specificity and transparency, and enabling new approaches to replication and comparative analysis. These advances present promising opportunities for criminology and related fields.","PeriodicalId":48080,"journal":{"name":"Journal of Quantitative Criminology","volume":"41 4","pages":"647-684"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12612022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145543070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatiotemporal Crime Patterns Across Six U.S. Cities: Analyzing Stability and Change in Clusters and Outliers. 美国六个城市的时空犯罪模式:分析集群和异常值的稳定性和变化

IF 3.3 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-12-01 Epub Date: 2022-08-24 DOI: 10.1007/s10940-022-09556-7

Rebecca J Walter, Marie Skubak Tillyer, Arthur Acolin

{"title":"Spatiotemporal Crime Patterns Across Six U.S. Cities: Analyzing Stability and Change in Clusters and Outliers.","authors":"Rebecca J Walter, Marie Skubak Tillyer, Arthur Acolin","doi":"10.1007/s10940-022-09556-7","DOIUrl":"10.1007/s10940-022-09556-7","url":null,"abstract":"Objectives: Examine the degree of crime concentration at micro-places across six large cities, the spatial clustering of high and low crime micro-places within cities, the presence of outliers within those clusters, and extent to which there is stability and change in micro-place classification over time.Methods: Using crime incident data gathered from six U.S. municipal police departments (Chicago, Los Angeles, New York City, Philadelphia, San Antonio, and Seattle) and aggregated to the street segment, Local Moran's I is calculated to identify statistically significant high and low crime clusters across each city and outliers within those clusters that differ significantly from their local spatial neighbors.Results: Within cities, the proportion of segments that are like their neighbors and fall within a statistically significant high or low crime cluster are relatively stable over time. For all cities, the largest proportion of street segments fell into the same classification over time (47.5% to 69.3%); changing segments were less common (4.7% to 20.5%). Changing clusters (i.e., segments that fell into both low and high clusters during the study) were rare. Outliers in each city reveal statistically significant street-to-street variability.Conclusions: The findings revealed similarities across cities, including considerable stability over time in segment classification. There were also cross-city differences that warrant further investigation, such as varying levels of spatial clustering. Understanding stable and changing clusters and outliers offers an opportunity for future research to explore the mechanisms that shape a city's spatiotemporal crime patterns to inform strategic resource allocation at smaller spatial scales.","PeriodicalId":48080,"journal":{"name":"Journal of Quantitative Criminology","volume":"39 1","pages":"951-974"},"PeriodicalIF":3.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12520604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44964357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Social Change, Cohort Effects, and Dynamics of the Age–Crime Relationship: Age and Crime in South Korea from 1967 to 2011 社会变迁、世代效应与年龄-犯罪关系的动态:1967 - 2011年韩国的年龄与犯罪

1区社会学

Journal of Quantitative Criminology Pub Date : 2023-09-19 DOI: 10.1007/s10940-023-09579-8

Myunghee You

引用次数: 0

Now You See It, Now You Don’t: A Simulation and Illustration of the Importance of Treating Incomplete Data in Estimating Race Effects in Sentencing 现在你看到它，现在你没有:模拟和说明处理不完整数据在估计量刑中种族影响的重要性

1区社会学

Journal of Quantitative Criminology Pub Date : 2023-09-16 DOI: 10.1007/s10940-023-09577-w

Benjamin Stockton, C. Clare Strange, Ofer Harel

引用次数: 0

Can We Compare Attitudes Towards Crime Around the World? Assessing Measurement Invariance of the Morally Debatable Behavior Scale Across 44 Countries 我们能比较一下世界各地对犯罪的态度吗？44个国家道德争议行为量表的测量不变性评估

IF 3.6 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-09-04 DOI: 10.1007/s10940-023-09578-9

Sandy Schumann, Michael Wolfowicz

引用次数: 0

Impulsivity, Peers, and Delinquency: A Dynamic Social Network Approach. 冲动、同伴和犯罪：一种动态社会网络方法

IF 3.3 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-09-01 Epub Date: 2022-06-18 DOI: 10.1007/s10940-022-09547-8

Daniel T Ragan, D Wayne Osgood, Derek A Kreager

{"title":"Impulsivity, Peers, and Delinquency: A Dynamic Social Network Approach.","authors":"Daniel T Ragan, D Wayne Osgood, Derek A Kreager","doi":"10.1007/s10940-022-09547-8","DOIUrl":"10.1007/s10940-022-09547-8","url":null,"abstract":"Objectives: Drawing on criminological research about peer delinquency and self-control, we employ a network perspective to identify the potential paths linking impulsivity, peers, and delinquency. We systematically integrate relevant processes into a set of dynamic network models that evaluate these interconnected pathways.Methods: Our analyses use data from more than 14,000 students in Pennsylvania and Iowa collected from the evaluation of the PROSPER partnership model. We estimate longitudinal social network models to disentangle the paths through which impulsivity and delinquency are linked in adolescent friendship networks.Results: We find evidence of both peer influence and homophilic selection for both impulsivity and delinquency. Further, results indicate that peer impulsivity is linked to individual delinquent behavior through peer influence on delinquency, but not on impulsivity. Finally, the results suggest that impulsivity moderates both influence and selection processes, as adolescents with higher levels of impulsivity are more likely to select delinquent peers but less likely to change their behavior due to peers.Conclusions: In sum, this study offers a more holistic framework and stronger theoretical tests than similar studies of the past. Our results illustrate the need to consider the simultaneous network processes related to peers, impulsivity, and delinquency. Further, our findings reveal that a large dataset with ample statistical power is a valuable advantage for detecting the selection processes that shape friendship networks.","PeriodicalId":48080,"journal":{"name":"Journal of Quantitative Criminology","volume":"39 1","pages":"735-768"},"PeriodicalIF":3.3,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13148287/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47495350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Racial Bias in Criminal Records 犯罪记录中的种族偏见

IF 3.6 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-09-01 DOI: 10.1007/s10940-023-09575-y

Ben Grunwald

引用次数: 0

Investigating the Dynamics of Outlaw Motorcycle Gang Co-Offending Networks: The Utility of Relational Hyper Event Models 摩托车团伙协同犯罪网络动力学研究——关系超事件模型的应用

IF 3.6 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-07-20 DOI: 10.1007/s10940-023-09576-x

David Bright, G. Sadewo, J. Lerner, Timothy I. C. Cubitt, Christopher Dowling, Anthony Morgan

引用次数: 2

Partners in Criminology: Machine Learning and Network Science Reveal Missed Opportunities and Inequalities in the Study of Crime 犯罪学伙伴：机器学习和网络科学揭示了犯罪研究中错失的机会和不平等

IF 3.6 1区社会学

Journal of Quantitative Criminology Pub Date : 2023-07-06 DOI: 10.1007/s10940-023-09574-z

T. B. Smith, Ruijie Mao, S. Korotchenko, M. Krohn

引用次数: 1