{"title":"Partners in Criminology: Machine Learning and Network Science Reveal Missed Opportunities and Inequalities in the Study of Crime","authors":"T. B. Smith, Ruijie Mao, S. Korotchenko, M. Krohn","doi":"10.1007/s10940-023-09574-z","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":48080,"journal":{"name":"Journal of Quantitative Criminology","volume":"1 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Criminology","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1007/s10940-023-09574-z","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
期刊介绍：
The Journal of Quantitative Criminology focuses on research advances from such fields as statistics, sociology, geography, political science, economics, and engineering. This timely journal publishes papers that apply quantitative techniques of all levels of complexity to substantive, methodological, or evaluative concerns of interest to the criminological community. Features include original research, brief methodological critiques, and papers that explore new directions for studying a broad range of criminological topics.
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