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

由于贫困、残疾、失业、居住在犯罪率较高的社区以及无家可归等问题，许多在刑事定罪后接受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对这种资源的访问，但女性罪犯的网络支持尤其有限，部分原因是定罪的污名效应。该项目将对假释或缓刑的女性重刑犯进行访谈，以此来分析某些个人网络，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是否会影响罪犯的社交网络、获取资源的途径和累犯，其中一些政策和做法禁止罪犯与其他有前科的人进行互动。本项目将应用以自我为中心的社会网络分析理论和技术来了解女性罪犯的结构和构成？个人网络和对关键资源的访问。该项目将寻求确定获得资源与罪犯再次犯罪的可能性之间的联系。为此，该项目将采访160名女性罪犯，其中80人假释，80人缓刑，来自密歇根州16个县，包括农村、郊区、小城镇和城市地区。将收集关于罪犯特征、网络成员特征、关系/关系特征以及整体网络特征的数据。该项目中未确认的数据将公之于众。该项目将测试单级和多级模型，以确定罪犯的社会网络对累犯率的影响。

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.