Doctoral Dissertation: Criminal Offenders, Access to Resources, and Recidivism

由于贫困、残疾、失业、生活在高犯罪率社区和无家可归等问题，许多在刑事定罪后受到法院监督的人资源有限。虽然一个人的社交网络的成员可以提供获得这类资源的机会，但女性罪犯获得的网络支持特别有限，部分原因是定罪的污名化效应。该项目将与假释或缓刑的女性重罪犯进行访谈，以分析某些个人网络，包括专家、解决问题的帮助和个人支持，是否会影响累犯率。因此，该项目将考虑政策和做法（其中一些禁止罪犯与其他前罪犯等某些人交往）是否影响罪犯的社交网络、获得资源的机会和累犯。本研究将应用自我中心的社会网络分析理论与技术，来了解女性罪犯的结构与组成。个人网络和关键资源的访问。该项目将寻求确定获得资源与罪犯累犯可能性之间的关系。为此，该项目将采访来自密歇根州16个县的160名女罪犯，其中80人在假释期，80人在缓刑期，这些县包括农村、郊区、小城镇和城市地区。 将收集罪犯特征、网络成员特征、关系/关系特征和整体网络特征的数据。该项目的去识别数据将公开提供。该项目将测试单级和多级模型，以确定罪犯的社交网络对累犯的影响。

Many of those under court supervision after a criminal conviction have limited resources, due to issues such as poverty, disability, unemployment, living in high crime neighborhoods, and homelessness. While members of a person's social networks can provide access to such resources, women offenders have especially limited network support, in part due to the stigmatizing effects of a conviction. This project will conduct interviews with female felons on parole or probation as a way of analyzing whether certain personal networks, including experts, problem solving help, and personal support, influence rates of recidivism. Consequently, this project will consider whether policies and practices, some of which prohibit offenders from interacting with certain people such as other ex-offenders, influence offenders' social networks, access to resources, and recidivism. This project will apply egocentric social network analysis theories and techniques to understand the structure and composition of women offenders? personal networks and access to key resources. The project will seek to determine the association between access to resources and the likelihood of offenders' recidivism. To do so, the project will interview 160 women offenders, 80 of whom were on parole and 80 on probation, from 16 Michigan counties that include rural, suburban, small town, and urban areas. Data will be collected on offender characteristics, network member characteristics, tie/relationship characteristics, and overall network characteristics. De-identified data from the project will be made publicly available. The project will test single-level and multilevel models to ascertain the effects of offenders' social networks on recidivism.