A Next Generation Data Infrastructure to Understand Disparities across the Life Course

摘要 这项基础设施提案旨在进一步提高社会科学(广义)的能力，以 收集有关美国家庭和个人日常生活的数据。这些数据将更准确、更细粒度、 而且比目前传统的基于调查的研究更全面。这方面的背景是 了解美国研究(UAS)，这是我们在南加州大学建立的基于概率的互联网小组 自2014年以来。基础设施包括多种数据类型的组合(包括调查数据、信息 来自可穿戴设备、背景和管理链接、生态即时评估、自我记录 叙述和金融交易的电子记录)，以及与更广泛的 在数据传播以及就内容和方法征求意见方面，研究界都是如此。 UAS目前由大约10,000名美国居民组成(包括加州的2500人超额抽样)， 通过基于地址的抽样进行招募，并在需要时提供支持互联网的平板电脑。调查是 以英语和西班牙语进行。我们建议将UAS全国样本扩大到20,000名受访者， 黑人、亚洲人和西班牙裔美国人的亚样本各至少3000人。 收集的信息将集中于解释生活中种族和社会经济差异的因素 课程，包括种族歧视、获得教育和医疗保健的不平等、 物质和社会环境，以及更广泛地说，人们遇到的各种机会和障碍 在整个生命过程中。 拟议的项目组涵盖广泛的实质性专业知识，涉及差异、种族 歧视、环境健康、儿童发展、健康、对生命过程的认知以及 老龄化和退休、消费、工作和收入。为鼓励研究团体提供意见，我们 设想一项由外部研究人员提出的关于不平等相关主题的增加调查模块的方案，如 以及年度研究会议。 该项目的基本前提是全面调查的唯一可行方法 生命过程中的差异对观察到的不平等的影响是制定一种稳健的多方法方法 这为尽可能多的解释因素提供了解释手段。在这种背景下，很自然地 正在进行的实验可以被用来帮助确定感兴趣的因果路径(例如，当空气质量在 因工厂关闭而改善的社区；在某种程度上影响学校质量的政策变化 区域)。因此，我们提议的项目旨在创建并向研究界提供一个独特的 详细而集中地收集有关美国家庭和个人的信息。为了实现这一目标，我们的目标是 将选定的外部数据源与UAS调查数据进行战略性集成，并扩展已经广泛的数据集 UAS调查涵盖的主题。

Summary This infrastructure proposal aims to further advance capabilities in the social sciences (broadly defined) to collect data on the daily lives of U.S. families and individuals. These data will be more accurate, more granular, and more comprehensive than is currently possible in traditional survey-based research. The context for this is the Understanding America Study (UAS), the probability-based Internet panel we have been building at USC since 2014. The infrastructure includes the combination of many data types (including survey data, information from wearables, contextual and administrative linkages, ecological momentary assessments, self-recorded narratives, and electronic records of financial transactions), as well as an open communication with the wider research community both in data dissemination and in soliciting input on content and methods. The UAS currently comprises about 10,000 U.S. residents (including a 2,500 person California oversample), recruited by address-based sampling and provided with Internet-enabled tablets if needed. Surveys are conducted in English and Spanish. We propose to expand the UAS national sample to 20,000 respondents, with subsamples of Blacks, Asians, and Hispanics of at least 3,000 each. The information collected will focus on factors explaining racial and socio-economic disparities over the life course, including racial discrimination, inequalities in access to education and healthcare, differences in the physical and social environment, and, more generally, the various opportunities and obstacles one encounters over the life course. The proposed project team covers a broad spectrum of substantive expertise on disparities, racial discrimination, environmental health, child development, health, and cognition over the life course, as well as aging and retirement, consumption, work, and income. To encourage input from the research community, we envision a program of added survey modules on inequality-related topics proposed by outside researchers, as well as an annual research conference. The basic premise underlying the project is that the only feasible approach to comprehensively investigating the impact of differences in the life course on observed inequality is to enact a robust multi-method approach that provides the means of accounting for as many explanatory factors as possible. Within that context, naturally occurring experiments can be exploited to help identify causal pathways of interest (e.g., when air quality in a neighborhood improves due to a plant closure; a policy change that affects the quality of schools in a certain area). Thus, our proposed project aims to create and make available to the research community a uniquely detailed and focused collection of information on U.S. households and individuals. To achieve this goal, we aim to strategically integrate selected external data sources with UAS survey data and expand the already broad set of topics covered by UAS surveys.