BCC - Building Community and Capacity for Transformative Data-Intensive Criminal Research

BCC - 建设变革性数据密集型犯罪研究的社区和能力

• 批准号: 1439453
• 负责人: David Eagleman
• 金额: $ 49.94万
• 依托单位: Baylor College of Medicine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1439453&HistoricalAwards=false
• 关键词: BCC; Building; Community; Capacity; Transformative

Crime records are housed in hundreds of counties across the nation, each employing local laws and idiosyncratic information management systems. As a result, it is difficult to analyze detailed crime records across time and place. To address this challenge, the researcher proposes to build a database for integrating 23 million crime records in Houston, NY and Miami. The researcher proposes a workshop strategy to address three distinct aims: 1) Build an interdisciplinary community including statisticians, criminologists, legal scholars, behavioral scientists, neuroscientists, economists, sociologists and programmers, all of whom share an interest in the intersection of crime and their fields. 2) Work with the community to prototype a database of deep criminal records obtained via public access laws. 3) Work with the community to design advanced interface and visualization tools for the data, opening the data to the widest possible audience. This project builds capacity for data-intensive research on national criminal records, guided at all stages by the stakeholder research communities. Previously, criminal research has relied on the FBI's Uniform Crime Reports, a tool with two weaknesses: no unique identifiers to identify re-offense rates, and a lack of detail that dilutes the ability to use 21st century tools and analysis techniques. The project breaks the information bottleneck by building a community of quantitative researchers - from a range of disciplines in the social, behavioral, and economic sciences - with a shared interest in next-generation questions at the intersection of crime and their fields. Through multiple workshops, the community establishes database ontologies and prototypes a transformative database of millions of criminal records spanning several decades (obtained via public access laws). The researchers also implement advanced interface and visualization tools to maximize the user audience for the database. This project provides an unprecedented level of detail about offenders, their crimes, and their interactions with the criminal justice system. By enabling an exploration of the relationships between external factors like legal policies and a decision to commit a crime, this project promises results across and beyond the contributing disciplines. Critically, the prototype database will include anonymized identifiers to enable exploration of desistance from crime, greatly advancing the study of recidivism (reoffenses). Such advances should in turn help efforts to identify high-risk offenders, allowing policy makers to base law enforcement decisions on direct, proven, open-source assessments of human behavior.

犯罪记录存放在全国数百个县，每个县都采用当地法律和特殊的信息管理系统。因此，很难分析跨时间和地点的详细犯罪记录。为了应对这一挑战，研究人员建议建立一个数据库，用于整合纽约州休斯顿和迈阿密的2300万条犯罪记录。研究人员提出了一个研讨会的战略，以解决三个不同的目标：1）建立一个跨学科的社区，包括统计学家，犯罪学家，法律的学者，行为科学家，神经科学家，经济学家，社会学家和程序员，所有这些人都有兴趣在犯罪和他们的领域的交叉点。2)与社区合作，建立一个通过公共访问法获得的深层犯罪记录数据库的原型。3)与社区合作，为数据设计高级界面和可视化工具，向尽可能广泛的受众开放数据。该项目在利益攸关方研究界的所有阶段指导下，建设对国家犯罪记录进行数据密集型研究的能力。此前，犯罪研究一直依赖于联邦调查局的统一犯罪报告，这一工具有两个弱点：没有唯一的标识符来确定重新犯罪率，缺乏细节，削弱了使用21世纪世纪工具和分析技术的能力。该项目通过建立一个定量研究人员社区来打破信息瓶颈-来自社会，行为和经济科学的一系列学科-对犯罪及其领域交叉的下一代问题有共同的兴趣。通过多个研讨会，社区建立了数据库本体，并建立了一个跨越几十年的数百万犯罪记录（通过公共访问法获得）的转型数据库。研究人员还实施了先进的界面和可视化工具，以最大限度地提高数据库的用户受众。该项目提供了前所未有的详细信息，包括罪犯、他们的罪行以及他们与刑事司法系统的互动。 通过探索法律的政策等外部因素与犯罪决定之间的关系，该项目有望在贡献学科之外取得成果。至关重要的是，原型数据库将包括匿名标识符，以使停止犯罪的探索，大大推进累犯（重新犯罪）的研究。这些进步反过来应该有助于识别高风险罪犯的努力，使政策制定者能够根据对人类行为的直接、经证实的开源评估做出执法决定。