Segregation and Local Crime: An Integrated Spatial Analysis

隔离和当地犯罪:综合空间分析

基本信息

项目摘要

SES- 0528232Ruth PetersonChristopher BrowningCatherine CalderLauren KrivoMei-Po KwanOhio State University Urban areas in the U.S. are characterized by the uneven distribution of social groups across geographic space as evidenced in pervasive levels of residential segregation by race, ethnicity, and economic status. This segregation is associated with crime and other deleterious conditions for communities with high concentrations of disadvantaged and minority residents, but carries benefits for more advantaged and White localities. These differential outcomes of segregation have been interpreted as evidence that the spatial isolation of minority neighborhoods produces social problems by creating and reinforcing social and structural isolation. However, most crime studies rely on measures that do not take into account the location of segregated areas relative to one another. As such, they leave unanswered the question of how the inherently spatial nature of segregation is connected with the geographic distribution of criminal activity. This research draws on studies of segregation and its consequences, analyses of geographic variation in crime, and aggregate and multilevel crime research to develop a model that brings space into the analysis of crime. Our broad question is: How does racial, ethnic, and associated economic segregation affect the geographic distribution of crime? Answering this general question entails addressing four specific objectives: (1) developing more refined spatially-based measures of locally segregated (along a variety of dimensions) areas using the best Geographical Information Systems (GIS) data and techniques; (2) identifying what aspects of the physical infrastructure of local communities affect crime; (3) determining how the effects on crime of nearby localities vary across neighborhoods within cities; and (4) evaluating how the effects of local segregation on neighborhood crime varies across cities. Thus, the intellectual merit of the study consists of the light it will shed on the linkages among city-wide segregation, local segregation, and neighborhood crime through meeting these objectives. The project will analyze data for 10 large U.S. cities for circa 2000: Austin, Boston,Chicago, Columbus, Fort Worth, Jacksonville, Milwaukee, Oklahoma City, Phoenix, and Portland. The 10 cities cover a range of Black-White segregation, incorporate regional variation, and have relatively large Hispanic and/or Black populations. National Neighborhood Crime Study (NNCS) data will be combined with GIS-based measures of local segregation and physical and ecological characteristics of areas derived from GIS databases on digital transportation networks and parcel- and building-level land use, and other public sources. State-of-the-art GIS analyses and hierarchical Bayesian spatial statistical modeling techniques will be used to evaluate our theoretical model. The modeling strategy is designed to highlight the substantive spatial effects of different types of local segregation (e.g., by race, Hispanic origin, economic status) on crime, while controlling for residual spatial dependence in crime caused by unmeasured conditions. The hierarchical Bayesian approach also permits the within-city and between-city substantive issues to be explored in an integrated manner that accounts for residual spatial dependence. Broader Impacts. Substantively, the study will shed light on how a major social process (i.e., segregation) fosters inequality in the prevalence of crime among diverse groups within cities. Beyond its substantive impact, this work will: (1) integrate thinking in three different fields about the sources of neighborhood crime, laying a foundation for future advances in interdisciplinary work on this important policy topic; (2) develop methodological strategies that will serve as models for research in a variety of fields seeking to integrate multiple types of spatial data and concepts; (3) make available to the scientific community newly refined GIS-based measures of local segregation and neighborhood physical and ecological characteristics as supplements to the NNCS; and, (4) provide an attractive topic and diverse mentors for undergraduate and graduate students of color and from economically disadvantaged backgrounds seeking to enhance their ability to conduct research.
SES-0528232露丝·彼得森克里斯托弗·布朗宁凯瑟琳·卡尔德劳伦·克里沃梅-波·关俄亥俄州立大学美国城市地区的特点是社会群体在地理空间上的分布不均匀,这一点在种族、民族和经济地位的居住隔离中得到了证明。对于弱势群体和少数民族居民高度集中的社区来说,这种隔离与犯罪和其他有害条件有关,但对黑人和白色居民较多的地区来说却有好处。隔离的这些不同结果被解释为少数民族社区的空间隔离通过创造和加强社会和结构隔离而产生社会问题的证据。然而,大多数犯罪研究所依赖的措施并没有考虑到隔离区的相对位置。 因此,它们没有回答隔离的固有空间性质如何与犯罪活动的地理分布相联系的问题。这项研究借鉴了隔离及其后果的研究,犯罪的地理变异分析,以及聚合和多层次的犯罪研究,开发一个模型,将空间纳入犯罪分析。我们的主要问题是:种族、民族和相关的经济隔离如何影响犯罪的地理分布?解决这一一般性问题需要解决四个具体目标:(1)制定更精确的基于空间的地方隔离措施,(沿着各个方面)使用最佳地理信息系统数据和技术的地区;(2)查明当地社区有形基础设施的哪些方面影响犯罪;(3)确定城市内不同社区对邻近地区犯罪的影响如何变化;(4)评估地方隔离对社区犯罪的影响如何在不同城市之间变化。因此,这项研究的智力价值包括它将通过满足这些目标来揭示城市范围内的隔离,地方隔离和邻里犯罪之间的联系。该项目将分析2000年前后美国10个大城市的数据:奥斯汀、波士顿、芝加哥、哥伦布、沃斯堡、杰克逊维尔、密尔沃基、俄克拉荷马州、凤凰城和波特兰。 这10个城市涵盖了一系列的黑人白人隔离,纳入区域差异,并有相对较大的西班牙裔和/或黑人人口。将把全国邻里犯罪研究数据与基于地理信息系统的地方隔离措施以及从数字交通网络、地块和建筑物一级土地使用的地理信息系统数据库和其他公共来源获得的地区的自然和生态特征相结合。国家的最先进的GIS分析和层次贝叶斯空间统计建模技术将被用来评估我们的理论模型。建模策略旨在突出不同类型的局部隔离(例如,种族,西班牙裔,经济地位)对犯罪的影响,同时控制由不可测量的条件引起的犯罪的剩余空间依赖性。分层贝叶斯方法还允许城市内部和城市之间的实质性问题,以综合的方式进行探讨,占剩余的空间依赖。 更广泛的影响。实质上,这项研究将揭示一个主要的社会过程(即,隔离)助长了城市内不同群体之间犯罪率的不平等。除了产生实质性影响外,这项工作还将:(1)整合关于邻里犯罪来源的三个不同领域的思想,为今后在这一重要政策主题上开展跨学科工作奠定基础;(2)制定方法战略,作为各种领域研究的模式,以整合多种类型的空间数据和概念;(3)向科学界提供新改进的基于GIS的地方隔离和邻里物理和生态特征的措施,作为NNCS的补充;(4)为本科生和研究生提供一个有吸引力的主题和多样化的导师,这些学生来自经济上处于不利地位的背景,寻求提高他们进行研究的能力。

项目成果

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Ruth Peterson其他文献

Ruth Peterson的其他文献

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{{ truncateString('Ruth Peterson', 18)}}的其他基金

Collaborative Research: Broadening Participation and Perspectives in the Study of Crime and Justice
合作研究:扩大犯罪与司法研究的参与和视角
  • 批准号:
    1530728
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Broadening Participation And Perspectives On Crime And Justice Research
扩大犯罪和司法研究的参与和视角
  • 批准号:
    1229038
  • 财政年份:
    2012
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Racial Democracy, Crime, and Justice: Broadening Research and Participation
种族民主、犯罪和司法:扩大研究和参与
  • 批准号:
    0925068
  • 财政年份:
    2009
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Dynamics of Space and Time Use: Patterns, Causes, and Consequences for Crime and Problem Behaviors
空间和时间利用的动态:犯罪和问题行为的模式、原因和后果
  • 批准号:
    0729466
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Race/Ethnicity, Crime, and Criminal Justice: Diverse Research and Participation in the Academy
种族/民族、犯罪和刑事司法:学院的多元化研究和参与
  • 批准号:
    0731473
  • 财政年份:
    2007
  • 资助金额:
    --
  • 项目类别:
    Continuing grant
Research and Training for a Better Understanding of the Race/Ethnicity-Crime and Criminal Justice Link
为了更好地理解种族/民族犯罪和刑事司法联系而进行的研究和培训
  • 批准号:
    0531536
  • 财政年份:
    2005
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Mixing, Metallicity, and Binaries on the Blue Horizontal Branch
蓝色水平分支上的混合、金属丰度和二元星
  • 批准号:
    0098725
  • 财政年份:
    2001
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Understanding Crime and Community: A National Neighborhood Crime Study
了解犯罪与社区:全国邻里犯罪研究
  • 批准号:
    0080091
  • 财政年份:
    2000
  • 资助金额:
    --
  • 项目类别:
    Continuing grant
Collaborative Project: A Comprehensive Survey of Hot Stars in the Galactic Bulge
合作项目:对银河核核中的热恒星进行全面调查
  • 批准号:
    9900582
  • 财政年份:
    1999
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Understanding Crime and Community: Feasibility Proposal for A National Neighborhood Crime Study
了解犯罪与社区:全国邻里犯罪研究的可行性建议
  • 批准号:
    9911902
  • 财政年份:
    1999
  • 资助金额:
    --
  • 项目类别:
    Standard Grant

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具有粘性逆Lax-Wendroff边界处理和紧凑WENO限制器的自适应网格local discontinuous Galerkin方法
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