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比较弗吉尼亚州里士满市邻里不稳定的形式,作为暴力行为的预测指标。

Comparing forms of neighborhood instability as predictors of violence in Richmond, VA.

机构信息

Department of Psychology, Virginia State University, Petersburg, Virginia, United States of America.

Department of Surgery, Virginia Commonwealth University, Petersburg, Virginia, United States of America.

出版信息

PLoS One. 2022 Sep 6;17(9):e0273718. doi: 10.1371/journal.pone.0273718. eCollection 2022.

DOI:10.1371/journal.pone.0273718
PMID:36067172
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9447869/
Abstract

Violence events tend to cluster together geospatially. Various features of communities and their residents have been highlighted as explanations for such clustering in the literature. One reliable correlate of violence is neighborhood instability. Research on neighborhood instability indicates that such instability can be measured as property tax delinquency, yet no known work has contrasted external and internal sources of instability in predicting neighborhood violence. To this end we collected data on violence events, company and personal property tax delinquency, population density, race, income, food stamps, and alcohol outlets for each of Richmond, Virginia's 148 neighborhoods. We constructed and compared ordinary least-squares (OLS) to geographically weighted regression (GWR) models before constructing a final algorithm-selected GWR model. Our results indicated that the tax delinquency of company-owned properties (e.g., rental homes, apartments) was the only variable in our model (R2 = 0.62) that was associated with violence in all but four Richmond neighborhoods. We replicated this analysis using violence data from a later point in time which yielded largely identical results. These findings indicate that external sources of neighborhood instability may be more important to predicting violence than internal sources. Our results further provide support for social disorganization theory and point to opportunities to expand this framework.

摘要

暴力事件往往在地理上集中发生。文献中强调了社区及其居民的各种特征是这种集群的解释。暴力行为的一个可靠相关因素是邻里不稳定。关于邻里不稳定的研究表明,这种不稳定可以通过欠缴财产税来衡量,但目前还没有已知的工作将不稳定的外部和内部来源进行对比,以预测邻里暴力。为此,我们为弗吉尼亚州里士满的 148 个社区中的每一个收集了暴力事件、公司和个人欠税、人口密度、种族、收入、食品券和酒类销售点的数据。我们构建并比较了普通最小二乘法 (OLS) 和地理加权回归 (GWR) 模型,然后构建了最终的算法选择 GWR 模型。我们的结果表明,我们模型中的唯一变量是公司所有物业(例如出租房屋、公寓)的欠税(R2 = 0.62),除了里士满的四个社区外,其他所有社区的暴力事件都与该变量有关。我们使用稍后时间点的暴力数据重复了这项分析,结果基本相同。这些发现表明,邻里不稳定的外部来源可能比内部来源更能预测暴力。我们的结果进一步支持了社会解体理论,并为扩展该框架提供了机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/389aef61d4b1/pone.0273718.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/09aa64ddba05/pone.0273718.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/54e37a49a096/pone.0273718.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/389aef61d4b1/pone.0273718.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/09aa64ddba05/pone.0273718.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/54e37a49a096/pone.0273718.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/794f/9447869/389aef61d4b1/pone.0273718.g003.jpg

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