Collaborative Research: Spatial Analytical Framework for Examining Community Risk Issues Over Space and Time

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。在全国范围内，被定罪的罪犯在被释放后又重新从事犯罪活动的案例比比皆是，这促使州和联邦立法者以及当地社区关注罪犯带来的公共安全风险，以及处理这一特殊群体的最适当方法。对被定罪罪犯的监督和管理是美国的一项主要政策考虑。许多联邦和州法规要求社区跟踪那些被判犯有某些罪行的人，在某些情况下，跟踪他们的一生，因为他们从一个地方搬到另一个地方。地方司法管辖区也扩大了对被定罪罪犯的联邦强制要求，制定了越来越严厉的条例，禁止罪犯居住在特定地点的特定距离内，并实施了分散和饱和法规，限制了居住在社区或当地的罪犯数量。该合作研究项目将(1)开发一个空间分析框架来解决罪犯问题；(2)为适当使用和规范方法建立指导方针，以解决各种情况，包括推理和优化方法；(3)建立反映公共政策的优化模型，从而评估不同政策情景下的空间影响；(4)开发犯罪者居住变更时空评估方法；(5)解释调查结果，以便更好地为公共政策和惩教实践提供有关立法影响、社区通知和罪犯再入的信息。调查人员最初将集中在俄亥俄州汉密尔顿县的一个案例研究上，努力完善一个空间分析框架，以确定适当的方法，解决规范问题，开发新方法，并在公共政策和纠正方面提供解释。该项目将开发一个空间分析框架和工具箱，以解决被定罪罪犯的居住问题。这将有助于利用新的和现有的探索性和验证性统计方法，以及新的和现有的空间优化模型，这些模型可用于分析影响以及制定和评估与被定罪罪犯管理有关的公共政策。空间分析框架和工具箱将实现社会影响、聚类和罪犯居住运动的时空分析和地理可视化，并提供检查居住选择因素的能力。为识别罪犯的时空移动以及与现有或拟议的管理罪犯的公共政策相关的突发事件而开发的建模技术将为执法机构提供司法趋势的信息，并将为执行地方和区域地理管理策略的空间和社会经济后果提供经验证据。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Nationally visible cases of convicted criminals who lapsed back into criminal activity following their release into the community have prompted state and federal legislators and local communities to focus on the public safety risk posed by offenders and the most appropriate means of dealing with this unique population. The monitoring and management of convicted offenders is a major policy consideration in the United States. Many federal and state regulations mandate that communities track those individuals who have been convicted of certain crimes, in some cases for their entire lives as they move from one location to another. Local jurisdictions have also extended these federally mandated requirements for convicted offenders with increasingly punitive ordinances that ban offenders from living within a specified distance of certain locations and imposing dispersion and saturation statutes that limit the number of offenders living within a community or local area. This collaborative research project will (1) develop a spatial analytical framework for addressing offender issues; (2) establish guidelines for the appropriate use and specification of methods to address a range of contexts, including inference and optimization approaches; (3) develop optimization models reflecting public policy, thereby enabling spatial impacts to be evaluated for alternative policy scenarios; (4) develop space-time methods for assessing offender residency change; and (5) interpret findings to better inform public policy and corrections practices with respect to legislative implications, community notification, and offender reentry. The investigators initially will focus on a case study in Hamilton County, Ohio, working to refine a spatial analytical framework that will identify appropriate methods, address specification issues, develop new methods, and provide interpretation in terms of public policy and corrections.This project will develop a spatial analytical framework and toolbox for addressing convicted offender residency issues. This will facilitate access to a combination of new and existing exploratory and confirmatory statistical methods and to new and existing spatial optimization models that can be used for analyzing impacts as well as developing and evaluating public policy associated with the management of convicted offenders. The spatial analytical framework and toolbox will enable spatio-temporal analysis and geovisualization of social impacts, clustering, and offender residency movements as well as provide the capacity to examine residency choice factors. Modeling techniques developed to identify the spatio-temporal movements of offenders and the contingencies associated with existing or proposed public policies for managing offenders will inform law enforcement agencies of jurisdictional trends, and they will provide empirical evidence of the spatial and socioeconomic consequences of enforcing geographic management strategies both locally and regionally.