Collaborative Research: State Health, Institutions, and Politics Survey (SHIPS)

合作研究：国家卫生、机构和政治调查 (SHIPS)

• 批准号: 2241886
• 负责人: Katherine Ognyanova
• 金额: $ 28.87万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241886&HistoricalAwards=false
• 关键词: Collaborative; Research; State; Health; Institutions

The State Health, Institutions, and Politics Survey (SHIPS) project will give the research community access to large-scale state-by-state survey data collected at multiple points in time. SHIPS will enable scholars, policymakers, and citizens to explore the evolution of public attitudes about state and federal policies; trust in institutions, policymakers, and experts; economic, social, and psychological well-being; perceptions of domestic and international threats; and a wide variety of other topics. Researchers from heterogenous geographic locations, institutions, career stages, and demographic groups will get access to the project’s infrastructure and data. Investigators will be able to use SHIPS to identify variations in outcomes due to state institutions, history, and policies, as well as employing cutting-edge social science methods to identify causes of public beliefs. The scale of the project will allow researchers to examine public opinion not only across states, but also among specific subgroups that often evade study (e.g., people with low income or education). The project will engage students as part of the research team, as well as offering curriculum development and hands-on training. SHIPS will generate academic papers, public-facing reports, and make data trends easily digestible with interactive visualization and online dashboards.The main goal of The State Health, Institutions, and Politics Survey is to provide high-quality state-level longitudinal data on public opinion, allowing researchers to track and document cross-country trends. The research team has developed and validated an approach that allows for the regular collection and post-stratification weighting of large census-balanced samples from every state and Washington, DC. Large-scale survey waves with up to 25,000 respondents will be fielded at regular time intervals. The sample size will enable exploring heterogeneous effects and examining outcomes for small, difficult to study population subgroups. The project will also be flexible and reactive to sudden events that could prompt the need for immediate data collection. SHIPS will give scholars access to survey modules and results via a competitive application process. Half or more of the survey content fielded in each wave funded by this grant will be designed by applicants whose peer-reviewed proposals have been accepted. Successful applicants will have exclusive access to the collected data for one year, at which point it will be made public. The project thus aims to democratize access to high-quality, original multi-wave survey data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

国家健康、机构和政治调查(SHIPS)项目将使研究界能够获得在多个时间点收集的大规模各州调查数据。船舶将使学者、政策制定者和公民能够探索公众对州和联邦政策的态度的演变；对机构、政策制定者和专家的信任；经济、社会和心理健康；对国内和国际威胁的看法；以及广泛的其他主题。来自不同地理位置、不同机构、不同职业阶段和不同人口统计群体的研究人员将获得该项目的基础设施和数据。调查人员将能够使用船只来确定由于国家机构、历史和政策而导致的结果差异，并使用尖端的社会科学方法来确定公众信仰的原因。该项目的规模将使研究人员不仅可以检查各州的民意，还可以检查经常逃避研究的特定亚群(例如，低收入或受教育的人)。该项目将让学生成为研究团队的一部分，并提供课程开发和动手培训。Ships将生成学术论文、面向公众的报告，并通过交互式可视化和在线仪表板使数据趋势易于理解。国家健康、机构和政治调查的主要目标是提供高质量的国家级民意纵向数据，使研究人员能够跟踪和记录跨国趋势。研究小组开发并验证了一种方法，该方法允许定期收集来自每个州和华盛顿特区的大型人口普查平衡样本并进行分层加权。将定期部署最多25,000名受访者的大规模调查波。样本量将能够探索异质效应，并检查较小、难以研究的人口亚群的结果。该项目还将灵活应对可能促使需要立即收集数据的突发事件。船舶将允许学者通过竞争性申请程序获得调查模块和结果。在每一波由该基金资助的调查中，一半或更多的调查内容将由申请者设计，其同行评议的建议已被接受。成功的申请者将在一年内独家访问收集的数据，届时这些数据将被公开。因此，该项目旨在使高质量、原始的多波调查数据的获取民主化。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Divisive or Descriptive?: How Americans Understand Critical Race Theory

分裂性还是描述性？：美国人如何理解批判种族理论

• DOI: 10.1017/rep.2023.39
• 发表时间: 2024
• 期刊: and Politics
• 作者: Safarpour, Alauna;Lunz Trujillo, Kristin;Green, Jon;Pippert, Caroline High;Lin, Jennifer;Druckman, James N
• 通讯作者: Druckman, James N

Using General Messages to Persuade on a Politicized Scientific Issue

• DOI: 10.1017/s0007123422000424
• 发表时间: 2022-10-24
• 期刊: BRITISH JOURNAL OF POLITICAL SCIENCE
• 影响因子: 5
• 作者: Green, Jon;Druckman, James N.;Perlis, Roy H.
• 通讯作者: Perlis, Roy H.