{"title":"展示:联邦刑事判决的数据驱动仪表板","authors":"Ace Vo, Miloslava Plachkinova","doi":"10.17705/1jais.00796","DOIUrl":null,"url":null,"abstract":"The main purpose of the Sentencing Reform Act of 1984 was to provide more uniformity in sentencing and reduce interjudge disparity. Subsequently, the act created the federal sentencing guidelines to offer judges a possible sentencing range for offenses. However, since these recommendations were based on historical data, the guidelines amplified existing biases and increased inequality and the disproportionate sentencing of minorities. To address this problem, we developed an artifact called “ShowCase”—a data-driven dashboard—that is grounded in penal theory, organizational context theory, social bonds theory, and triangulation notion in design theory. The artifact helps judges make fairer and more objective decisions by integrating a variety of data points. We used a design science research methodology and mixed methods to guide the development and evaluation of the proposed dashboard. Our research inquiry revealed the legal and extralegal factors that contribute to more equitable judicial decisions. We also found support for integrating data science and more diverse viewpoints in the sentencing process. Our study shows that a validated data-driven dashboard can be used to promote fairness, objectivity, and transparency in the criminal justice system.","PeriodicalId":51101,"journal":{"name":"Journal of the Association for Information Systems","volume":"10 1","pages":"0"},"PeriodicalIF":7.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Showcase: A Data-Driven Dashboard for Federal Criminal Sentencing\",\"authors\":\"Ace Vo, Miloslava Plachkinova\",\"doi\":\"10.17705/1jais.00796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main purpose of the Sentencing Reform Act of 1984 was to provide more uniformity in sentencing and reduce interjudge disparity. Subsequently, the act created the federal sentencing guidelines to offer judges a possible sentencing range for offenses. However, since these recommendations were based on historical data, the guidelines amplified existing biases and increased inequality and the disproportionate sentencing of minorities. To address this problem, we developed an artifact called “ShowCase”—a data-driven dashboard—that is grounded in penal theory, organizational context theory, social bonds theory, and triangulation notion in design theory. The artifact helps judges make fairer and more objective decisions by integrating a variety of data points. We used a design science research methodology and mixed methods to guide the development and evaluation of the proposed dashboard. Our research inquiry revealed the legal and extralegal factors that contribute to more equitable judicial decisions. We also found support for integrating data science and more diverse viewpoints in the sentencing process. Our study shows that a validated data-driven dashboard can be used to promote fairness, objectivity, and transparency in the criminal justice system.\",\"PeriodicalId\":51101,\"journal\":{\"name\":\"Journal of the Association for Information Systems\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Association for Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17705/1jais.00796\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Association for Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17705/1jais.00796","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Showcase: A Data-Driven Dashboard for Federal Criminal Sentencing
The main purpose of the Sentencing Reform Act of 1984 was to provide more uniformity in sentencing and reduce interjudge disparity. Subsequently, the act created the federal sentencing guidelines to offer judges a possible sentencing range for offenses. However, since these recommendations were based on historical data, the guidelines amplified existing biases and increased inequality and the disproportionate sentencing of minorities. To address this problem, we developed an artifact called “ShowCase”—a data-driven dashboard—that is grounded in penal theory, organizational context theory, social bonds theory, and triangulation notion in design theory. The artifact helps judges make fairer and more objective decisions by integrating a variety of data points. We used a design science research methodology and mixed methods to guide the development and evaluation of the proposed dashboard. Our research inquiry revealed the legal and extralegal factors that contribute to more equitable judicial decisions. We also found support for integrating data science and more diverse viewpoints in the sentencing process. Our study shows that a validated data-driven dashboard can be used to promote fairness, objectivity, and transparency in the criminal justice system.
期刊介绍:
The Journal of the Association for Information Systems (JAIS), the flagship journal of the Association for Information Systems, publishes the highest quality scholarship in the field of information systems. It is inclusive in topics, level and unit of analysis, theory, method and philosophical and research approach, reflecting all aspects of Information Systems globally. The Journal promotes innovative, interesting and rigorously developed conceptual and empirical contributions and encourages theory based multi- or inter-disciplinary research.