Understanding Changes in Patterns of Residential Mixing between Mexicans and Anglos in Southwest Cities
Understanding Changes in Patterns of Residential Mixing between Mexicans and Anglos in Southwest Cities
批准号:
9819292
负责人:
James Huff
金额:
$6.36万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-03-15 至 2001-09-30
中文摘要
直到最近,种族隔离学者才开始承认,社区、族裔和种族构成的变化取决于城市环境,城市环境确定了家庭决定社区搬迁或定居的一套选择方案。如果要解开社区变化的复杂性,就必须更好地理解隔离结构和住房市场的城市间差异的影响。这项拟议的研究将开发和评估西南城市内部邻里变化的分层模型。该项目的第一阶段旨在确定与社区种族特征的快速变化有关的社区和大都市层面的特征,特别关注墨西哥家庭和盎格鲁家庭不断变化的组合。该项目的第二阶段侧重于墨西哥人和盎格鲁人所做的社区选择,以及这些选择如何受到个人和家庭属性以及背景条件的影响,这些环境条件在不同的社区之间存在差异,并且在样本中的大都市地区也不同。将使用多尺度方法,其中包括用于在几个尺度上分析线性和非线性影响的分层统计技术、用于分析基于空间的邻里属性的地理信息系统以及对收入动态小组研究的地理编码样本的分析。
英文摘要
Only recently have segregation scholars begun to acknowledge that change in neighborhood ethnic and racial composition depends upon the urban context which defines the set of alternatives for households making decisions about neighborhood relocation or settlement. If the complexities of neighborhood change are to be unraveled, the effects of inter-city variations in segregation structure and housing markets must be better understood. The proposed research will develop and evaluate a hierarchical model of neighborhood change within cities of the Southwest. The first phase of the project is designed to identify neighborhood and metropolitan level characteristics associated with rapid changes in the ethnic character of neighborhoods with a specific focus on the changing mix of Mexican and Anglo households. The second stage of the project focuses on the neighborhood choices made by Mexicans and Anglos and how these choices are influenced by personal and household attributes in conjunction with contextual conditions that vary from one neighborhood to another and vary across the metropolitan areas in the sample. A multi-scale methodology will be used that incorporates hierarchical statistical techniques for analyzing linear and non-linear effects at several scales, geographical information systems to analyze spatially-based neighborhood attributes, and analysis of geo-coded samples from the Panel Study of Income Dynamics.
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