Differential Neighborhood Organization: A Multi-Level Theory of Crime

SES-096662罗斯松田华盛顿大学这个项目解决了当代美国面临的一个重要社会问题：地方社区的犯罪暴力。该项目的一个创新是详细说明了一个多层次模型，其中个人选择产生社区社会资本，从而影响犯罪率。这种影响的方向取决于社会资本的使用方式-是促进犯罪还是控制犯罪。 犯罪率被假设为当有利于犯罪的组织强大时犯罪率高，当反对犯罪的组织强大时犯罪率低。该项目通过研究邻里社会资本和集体效能是如何产生的来研究组织打击犯罪。假设居民的行为是理性的：当他们有动机这样做时，他们会交换好处和信息（例如，需要帮助修理汽车）并且没有约束（例如，他们有时间回报）。反过来，这些激励和约束被假设为更广泛的社区结构和资源的功能。居民之间的交换具有正外部性--创造邻里社会资本，包括信任、社会关系、义务和规范。由此产生的社会资本为集体效能提供了资源，社区解决当地问题的能力，如犯罪。集体效能，反过来，假设减少邻里刑事暴力。最后一个有待检验的假设是，基于破窗假设的邻里关系混乱和暴力之间的相关性实际上是虚假的，因为集体效能既解释了混乱，也解释了暴力。该项目还通过测试一个假设，即基于街道代码的暴力街头文化在结构上处于不利地位的社区发展，来调查有利于犯罪的组织。居民，特别是年轻的黑人男性，被假设为人力资本较少，劳动力市场前景不佳，资源很少，导致与社会疏远。据推测，这种疏离感因观察到的种族偏见和警察的貌相而加剧，导致不信任，反过来又增加了诉诸街头解决争端和获得尊重、地位和信誉的可能性。有人假设，当这种异化的居民在社会资本的存在下达到临界质量时，他们的挫折感被转化为通过街道代码实现地位的邻里系统（例如，从不在战斗中退缩，当同伴不受尊重时总是报复，在街上树立坚韧的形象）。最后，集体效能和邻里街道代码的假设，以互动的暴力行为的影响。为了验证这些假设，该项目将使用在西雅图123个人口普查区收集的近6,000个家庭的调查数据，沿着社区人口普查数据和警方犯罪数据。嵌套设计将用于估计多水平广义线性模型，包括互惠交换和对警察不信任的个人层面理性选择模型以及集体效能和街道规范的社区层面模型。为了进一步探索个人行动转化为宏观结果的可能机制，该项目将对回归线上和回归线外的社区进行抽样，并对居民进行深入的定性访谈。这种探索性的分析将有助于确定模型中指定的因果机制，并通过检查离群社区，提供调查中未测量的机制的见解。更广泛的影响：该项目是种族民主，犯罪和正义网络的一个关键特征，该网络是NSF支持的研究网络，旨在促进种族，犯罪和正义的研究，并通过指导初级有色人种教师来增加学院的多样性。PI和项目团队的几名成员（色彩系）是RDCJN的核心成员。该项目将性别和种族多样化的研究生和本科生纳入研究过程。PI将把他的研究成果纳入本科和研究生教学，并向公众提供数据。

SES-096662Ross MatsuedaUniversity of WashingtonThis project addresses a crucial social problem facing contemporary America: criminal violence in local communities. An innovation of the project is the specification of a multi-level model, in which individual choices produce community social capital, which affects crime rates. The direction of this effect depends on how social capital is used--either to facilitate or control crime. Crime rates are hypothesized to be high when organization in favor of crime is strong and low when organization against crime is strong. The project studies organization against crime by examining how neighborhood social capital and collective efficacy are produced. Residents are hypothesized to act rationally: they exchange favors and information when they have an incentive to do so (e.g., needing help fixing a car) and are free of constraints (e.g., they have the time to reciprocate). In turn, these incentives and constraints are hypothesized to be a function of broader community structures and resources. Exchange among residents has a positive externality--the creation of neighborhood social capital, including trust, social ties, obligations, and norms. The resulting social capital provides resources for collective efficacy, the ability of a neighborhood to solve local problems, such as crime. Collective efficacy is, in turn, hypothesized to reduce neighborhood criminal violence. A final hypothesis to be tested is that the correlation between neighborhood disorder and violence, based on the broken windows hypothesis, is actually spurious because collective efficacy explains both disorder and violence. The project also investigates organization in favor of crime by testing the hypothesis that a violent street culture based on the code of the street develops in structurally disadvantaged neighborhoods. Residents, particularly young black males, are hypothesized to have less human capital, poor labor market prospects, and few resources, leading to alienation from society. This alienation is hypothesized to be exacerbated by observations of racial bias and profiling by police, which leads to distrust, and in turn, increases the likelihood of turning to the streets to resolve disputes and gain respect, status, and credibility. It is hypothesized that when such alienated residents reach a critical mass in the presence of social capital, their frustration is translated into a neighborhood system of achieving status through a code of the street (e.g., never back down from a fight, always retaliate when a peer is disrespected, project a tough image on the street). Finally, collective efficacy and neighborhood street codes are hypothesized to interact in their effects on violence. To test the hypotheses, the project will use survey data collected on nearly 6,000 households across 123 census tracts in Seattle, along with neighborhood census data and police crime data. The nested design will be used to estimate multilevel generalized linear models, including individual-level rational choice models of reciprocated exchange and distrust of police and neighborhood-level models of collective efficacy and codes of the street. To explore further the possible mechanisms by which individual action translates into macro-level outcomes, the project will sample neighborhoods on and off the regression lines, and conduct in-depth qualitative interviews of residents. This exploratory analysis will help identify causal mechanisms specified in the model, and by examining outlier neighborhoods, provide insights into mechanisms not measured in the survey.Broader Impacts: The project is a key feature of the Racial Democracy, Crime, and Justice Network, an NSF-supported research network for fostering the study of race, crime, and justice and increasing diversity in the academy by mentoring junior faculty of color. The PI and several members of the project team (faculty of color) are core members of RDCJN. The project incorporates a gender and racially diverse set of graduate and undergraduate students into the research process. The PI will incorporate his research findings Into both undergraduate and graduate teaching, and make data available to the public.