Objective: The identification of neighborhoods where registered sex offenders (RSOs) reside may facilitate evidence-based service delivery and increase neighborhood capacity building. This study aims to determine if there is a patterned spatial aggregation of RSOs and to identify the neighborhood characteristics of RSO locations. Method: We used ArcGIS to match residential information from 938 Ohio ZIP Code areas with census data and conducted spatial autocorrelation analyses to explore and map spatial clustering of RSO residential locations. We used ordinary least squares and spatial regression models to estimate the association between neighborhood characteristics and the rate of RSOs. Results: The percentages of non-Hispanic Black population, Hispanic population, and poverty were positively associated with the rate of RSO residences; percentages of female-headed households, having a bachelor’s degree, and owner-occupied households were negatively associated with the rate of RSO residences. Overall, RSOs were spatially aggregated in socially disorganized areas. Conclusions: The findings can be used to promote evidence-informed policies to manage decarcerated RSOs, distribute limited resources to assist former offenders’ rehabilitation, and empower communities in disadvantaged neighborhoods to advance smart decarceration.

中文翻译：

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性犯罪者居住地的邻里特征：来自俄亥俄州的证据

目的：确定注册性犯罪者所居住的社区可能有助于提供循证服务并增强社区能力建设。这项研究旨在确定RSO的空间聚集是否存在，并确定RSO位置的邻域特征。方法：我们使用ArcGIS将来自938个俄亥俄州邮政编码区域的居民信息与人口普查数据进行匹配，并进行了空间自相关分析，以探索和绘制RSO居民区的空间聚类。我们使用普通最小二乘和空间回归模型来估计邻域特征和RSO率之间的关联。结果：非西班牙裔黑人人口，西班牙裔人口和贫困的百分比与RSO居住率呈正相关；具有学士学位的女户主家庭的百分比以及自有住房的家庭与RSO居住率负相关。总体而言，RSO在空间上聚集在社会混乱的地区。结论：研究结果可用于促进有证据依据的政策，以管理被监禁的RSO，分配有限的资源以帮助前罪犯的康复，并授权处境不利社区的社区推进明智的监禁。