Differential Neighborhood Organization: A Multi-Level Theory of Crime

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：当地社区的犯罪暴力。该项目的一项创新是指定了一个多层次模型，在该模型中，个人选择产生社区社会资本，社会资本影响犯罪率。这种效果的方向取决于如何利用社会资本--要么促进犯罪，要么控制犯罪。当支持犯罪的组织强大时，犯罪率被假设为高，而当反对犯罪的组织强大时，犯罪率被假设为低。该项目通过考察社区社会资本和集体效能是如何产生的来研究组织打击犯罪的。假设居民的行为是理性的：当他们有动机(例如，需要帮助修理汽车)并且没有限制(例如，他们有时间回报)时，他们就会交换帮助和信息。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的外部性--创造邻里社会资本，包括信任、社会联系、义务和规范。由此产生的社会资本提供了集体效能的资源，即社区解决当地问题(如犯罪)的能力。反过来，假设集体效能是为了减少邻里犯罪暴力。有待检验的最后一个假设是，基于破窗假说的邻里混乱和暴力之间的相关性实际上是虚假的，因为集体效能既可以解释混乱，也可以解释暴力。该项目还通过检验一种假设，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中发展，来调查有利于犯罪的组织。居民，特别是年轻的黑人男性，被假设人力资本较少，劳动力市场前景黯淡，资源稀少，导致与社会的疏远。这种疏远被认为会因观察到的种族偏见和警察的刻板印象而加剧，这会导致不信任，进而增加走上街头解决争端并获得尊重、地位和可信度的可能性。假设当这种被疏远的居民在社会资本存在的情况下达到临界点时，他们的挫折感会转化为通过街头准则获得地位的邻里体系(例如，永远不要放弃战斗，当同伴不受尊重时总是进行报复，在街道上投射强硬的形象)。最后，假设集体效能和社区街道规范在其对暴力的影响中相互作用。为了验证假设，该项目将使用从西雅图123个人口普查区域收集的近6000户家庭的调查数据，以及社区普查数据和警察犯罪数据。采用嵌套设计估计多层次广义线性模型，包括个体层次的互惠交换与不信任警察理性选择模型和邻里层次的集体效能与街道规范模型。为了进一步探索个人行动转化为宏观结果的可能机制，该项目将在回归线上和回归线下抽样社区，并对居民进行深入的定性访谈。这一探索性分析将有助于确定模型中指定的因果机制，并通过检查离群点社区，提供对调查中未测量的机制的洞察。广泛影响：该项目是种族民主、犯罪和正义网络的关键功能，该网络是NSF支持的研究网络，旨在通过指导初级有色人种教师来促进对种族、犯罪和正义的研究，并增加学院的多样性。PI和项目团队的几名成员(色彩学院)是RDCJN的核心成员。该项目将不同性别和种族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生和研究生教学，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.