Neighborhoods in Space-Time Contexts

该研究项目将推进城市社会科学研究中社区定义的方式。社会经济邻里的定义是许多研究领域的一个重要和核心问题。邻里作为组织单位，对各种各样的问题进行了实证研究，包括社交网络在空间背景下产生集体效能的能力，集中的贫困陷阱和暴力之间的关系，空间分类和隔离，以及邻里作为更广泛的城市经济发展种子的作用。尽管如此重要，但关于如何在实践中运作社区尚未达成共识。此外，空间结构的作用在很大程度上被忽略了现有的方法来定义邻里。该项目将利用地理信息科学和空间统计学的最新发展，提出新的邻里识别和分析方法。这些新方法将增强城市社会科学工具包，使研究人员能够开展可复制的实证工作，从而将城市政策研究推向更强大的分析基础。新的方法和分析将在公开的开源纵向邻里分析包中实施。该项目将为博士后研究助理提供培训，并将包括学术界和工业界之间的伙伴关系，并将其应用于商业市场细分和分析。该研究项目将促进对社区空间维度的理解。该项目将侧重于三个中心目标。首先，将研究一些与在空间和时间背景下定义邻域相关的未充分研究的问题。这些问题与当前文献中缺乏空间明确的邻域定义方法以及忽略空间聚类和异质性动态的影响有关。第二个目标是开发解决这些问题的邻域划分和分析的新方法。这些新方法将包括确定单个城市地区内邻里变化热点的地方措施，以及总结给定大都市地区空间变化总量的全球措施。活动的第三个领域将是在一个开源框架中实施新的邻里划定方法，为社会科学家提供一个灵活，可扩展和先进的时空聚类方法平台，支持复制和加强现有的城市动态社会科学研究基础设施。

This research project will advance the way in which neighborhoods are defined in urban social science research. The definition of a socioeconomic neighborhood is an important and central issue across many research domains. Neighborhoods serve as the organizational units to frame empirical research that has examined a wide array of issues, including the ability of social networks to produce collective efficacy in a spatial context, the relationships between concentrated poverty traps and violence, spatial sorting and segregation, and the role of neighborhoods as seeds for wider urban economic development. Despite this importance, consensus has not yet emerged regarding how to operationalize neighborhoods in practice. Moreover, the role of spatial structure largely has been ignored in existing approaches to neighborhood definition. This project will produce new methods for neighborhood identification and analysis that draw on recent developments in geographic information science and spatial statistics. These new methods will enhance the urban social science toolkit enabling researchers to carry out empirical work that can be replicated, thereby moving urban policy research onto stronger analytic foundations. The new methods and analytics will be implemented in a publicly available open-source longitudinal neighborhood analysis package. The project will provide training to a post-doctoral research associate and will include a partnership between academia and industry, with applications to commercial market segmentation and analysis.This research project will advance understanding of the spatial dimensions of neighborhoods. The project will focus on three central aims. First, a number of underexamined issues associated with defining neighborhoods in spatial and temporal contexts will be investigated. These issues are related to the lack of a spatially explicit approach to neighborhood definition in the current literature and the impacts of ignoring the dynamics of spatial clustering and heterogeneity. The second aim is to develop new methods for neighborhood delineation and analysis that address these issues. These new methods will include local measures to identify hot-spots of neighborhood change within individual urban areas as well as global measures that summarize the overall amount of spatial change in a given metropolitan area. The third area of activity will be the implementation of the new methods for neighborhood delineation in an open-source framework to provide social scientists with a platform of flexible, scalable, and advanced spatio-temporal clustering methods that support replication and enhance the existing infrastructure of social science research on urban dynamics.