Statistical Methods for Environmental Social Science

环境社会科学统计方法

• 批准号: 9978238
• 负责人: Bradley Carlin
• 金额: $ 38.4万
• 依托单位: University of Minnesota-Twin Cities
• 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
• 起止时间: 1999-12-01 至 2003-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9978238&HistoricalAwards=false
• 关键词: Statistical; Methods; Environmental; Social; Science

Recently, there has been an explosion of both public and research interest in the cause-and-effect relationships between humans and their environment. Much of this interest has been directed at answering questions of environmental justice, i.e., determining whether certain sociodemographic subgroups bear an undue share of certain environmental hazards. Helping facilitate this interest has been the concurrent emergence of geographic information systems (GISs), sophisticated computer programs for "layering" multiple data sources over a common study area. However, such programs at present have no facility for statistical inference, which is necessary for determining whether the data offer "significant" evidence of injustice, or whether the findings could just as well have arisen completely by chance.This project focuses on developing necessary statistical hierarchical modeling methods for the improved analysis of such data sets, as well as corresponding user-friendly computing tools to enable use of the methods by non-expert statistical support staff. The project will focus on at least three environmental social science application areas. First, statistical methods for handling misaligned areal data (of the sort so easily mapped by GISs) will be considered. Here the methods must accommodate data aggregated over misaligned regional boundaries (say, zip codes and census tracts), as well as boundaries which evolve over time. Second, the methods will be extended to the case where data are not only misaligned, but of different types. For example, one variable might be available only as a regional aggregate (say, percent foreign-born by zip code), while another is available only at certain points in space (say, daily particulate matter levels at a collection of fixed monitoring stations). Finally, the methods will be further extended to incorporate formal tools for resolving multiple and conflicting priorities and goals. Achieving environmental equity often involves making tradeoffs between efficiency (i.e., maximizing the overall difference between costs and benefits) and equity (i.e., an evenhanded distribution of these costs and benefits). Benefits accruing to society will include improved environmental justice assessments, a systematic approach for handling data at different scales, and practical strategies for resolving conflicting analytic priorities and goals. These should be of interest and use to public policymakers as they grapple with the problems of cleaning up existing environmental hazards, as well as equitably siting future potentially hazardous facilities.

最近，公众和研究人员对人类与其环境之间的因果关系的兴趣激增。 这种兴趣很大程度上是为了回答环境正义问题，即确定某些社会人口亚群体是否过度承担某些环境危害。 地理信息系统（GIS）的同时出现，有助于促进这种兴趣，这是一种复杂的计算机程序，用于在公共研究区域“分层”多个数据源。 然而，此类程序目前没有统计推断的设施，而统计推断对于确定数据是否提供了不公正的“重大”证据，或者调查结果是否完全是偶然出现是必要的。该项目的重点是开发必要的统计分层建模方法，以改进对此类数据集的分析，以及相应的用户友好的计算工具，以使非专家统计支持人员能够使用这些方法。 该项目将重点关注至少三个环境社会科学应用领域。 首先，将考虑处理未对齐的区域数据（地理信息系统很容易绘制的那种数据）的统计方法。 这里的方法必须适应在未对齐的区域边界（例如邮政编码和人口普查区）以及随时间变化的边界上聚合的数据。 其次，这些方法将扩展到数据不仅未对齐而且类型不同的情况。 例如，一个变量可能仅作为区域总量提供（例如，按邮政编码列出的外国出生百分比），而另一个变量仅在空间中的某些点提供（例如，一组固定监测站的每日颗粒物水平）。 最后，这些方法将进一步扩展，纳入正式工具来解决多个且相互冲突的优先事项和目标。 实现环境公平通常涉及在效率（即最大化成本和收益之间的总体差异）和公平（即这些成本和收益的公平分配）之间进行权衡。 为社会带来的好处将包括改进的环境正义评估、处理不同规模数据的系统方法以及解决相互冲突的分析优先事项和目标的实用策略。 当公共政策制定者努力解决清除现有环境危害以及公平地安置未来潜在危险设施的问题时，这些应该会引起公共政策制定者的兴趣和使用。