经历过度暴力犯罪的商业和财产类型:微观空间分析。

Journal of injury & violence research Pub Date : 2022-01-01 Epub Date: 2021-11-17 DOI:10.5249/jivr.v14i1.1566
Daniel A Bowen, Kurtis M Anthony, Steven A Sumner
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引用次数: 0

摘要

背景:除了酒精零售场所,大多数商业和财产类型在暴力犯罪研究中受到的关注有限。我们试图提供一个全面的检查,哪些财产经历了最暴力的犯罪在一个城市,以及暴力是如何分布在整个城市。方法:对于一个大城市,我们将警方报告的暴力事件数据与2012-2017年的市政税务评估人员数据合并,并将15种商业和公共财产类型的暴力犯罪模式制成表格。为了描述异常场所,我们计算了每种财产类型中经历超过该财产类型平均犯罪数量5倍的单个地块的比例,并绘制了暴力事件数量最多的25个地块的地图,以探索这些街区组中暴力犯罪的比例是由异常场所贡献的。结果:虽然酒店/住宿物业类型经历的暴力犯罪数量最多(2.72),但每种物业类型的异常场所经历的暴力犯罪数量是平均数量的5倍以上。15种财产类型中有12种(80%)的场所发生的暴力事件是平均数量的10倍以上。暴力犯罪最严重的25个地区包括购物中心、杂货店、加油站、汽车旅馆、公园、空地、公共街道、办公楼、中转站、医院、药房、学校、社区中心、电影院等各种场所,分布在城市的各个角落。在暴力犯罪数量最高的25个包裹中,有8个包裹占400米缓冲区内暴力犯罪的50%或更多。结论:所有财产类型都有异常场所,经历了暴力犯罪的增加。此外,该市25个最暴力的物业在物业类型上表现出显著的多样性。进一步研究评估其他财产类型的暴力犯罪风险可能有助于预防暴力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Business and property types experiencing excess violent crime: a micro-spatial analysis.

Background: Beyond alcohol retail establishments, most business and property types receive limited attention in studies of violent crime. We sought to provide a comprehensive examination of which properties experience the most violent crime in a city and how that violence is distributed throughout a city.

Methods: For a large urban city, we merged violent incident data from police reports with municipal tax assessor data from 2012-2017 and tabulated patterns of violent crime for 15 commercial and public property types. To describe outlier establishments, we calculated the proportion of individual parcels within each property-type that experienced more than 5 times the average number of crimes for that property-type and also mapped the 25 parcels with the highest number of violent incidents to explore what proportion of violent crime in these block groups were contributed by the outlier establishments.

Results: While the hotel/lodging property-type experienced the highest number of violent crimes per parcel (2.72), each property-type had outlier establishments experiencing more than 5 times the average number of violent crimes per business. Twelve of 15 property-types (80%) had establishments with more than 10 times the mean number of violent incidents. The 25 parcels with the most violent crime comprised a wide variety of establishments, ranging from a shopping center, grocery store, gas station, motel, public park, vacant lot, public street, office building, transit station, hospital, pharmacy, school, community center, and movie theatre, and were distributed across the city. Eight of the 25 parcels with the highest amount of violent crime, accounted for 50% or more of the violent crime within a 400-meter buffer.

Conclusions: All property-types had outlier establishments experiencing elevated counts of violent crimes. Furthermore, the 25 most violent properties in the city demonstrated remarkable diversity in property-type. Further studies assessing the risk of violent crime among additional property-types may aid in violence prevention.

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