Collaborative Research: U.S. Institutions after COVID-19: Trust, Accountability, and Public Perceptions

合作研究:COVID-19 后的美国机构:信任、责任和公众看法

基本信息

  • 批准号:
    2116189
  • 负责人:
  • 金额:
    $ 8.03万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-12-01 至 2023-11-30
  • 项目状态:
    已结题

项目摘要

COVID-19 upended social, economic, and political systems throughout the world. The United States has faced particular challenges due to its heterogeneity and federal nature. The COVID States project is a large-scale data collection that includes over-time data from diverse state-level samples. The project tracks state-level post-pandemic recovery, studying topics such as trust in institutions, information acquisition and impact, accountability, and economic inequality. It also documents how federal and state policies affect the populace when it comes to these topics. Further, the COVID States project provides access to researchers from all backgrounds, types of academic institutions, and career stages through a competition for survey module time and provides a user-friendly website with data trackers for use by researchers, students, journalists, policymakers, and the public.The COVID States project conducts over-time state-level surveys from all 50 states and D.C. Each survey includes up to 30,000 total respondents, using quota sampling by state. This allows for generalizable inferences at the state and national levels. Post-pandemic data provide an unprecedented opportunity for novel over-time and across-space research designs. The project over-samples demographic minority respondents to facilitate study of heterogeneous social groups. This includes data on trust in political figures and institutions, knowledge and information, political evaluations, behavioral adaptation, physical health, economic well-being, mental health, and more. It also contains detailed social network batteries that allow for the study of inter-household and inter-group transmission of health and information. This is complemented by Twitter data from survey respondents who allow it. This enables the project to identify information sharing and study political discourse.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.
COVID-19颠覆了世界各地的社会、经济和政治制度。由于其异质性和联邦性质,美国面临着特殊的挑战。COVID States项目是一个大规模的数据收集项目,包括来自不同州一级样本的长期数据。该项目跟踪国家一级的疫情后复苏,研究对机构的信任、信息获取和影响、问责制和经济不平等等主题。它还记录了在这些主题方面,联邦和州政策如何影响民众。此外,COVID States项目通过竞争调查模块时间,为来自所有背景、类型的学术机构和职业阶段的研究人员提供访问机会,并提供一个用户友好的网站,提供数据跟踪器,供研究人员、学生、记者、政策制定者、和公众。COVID州项目在所有50个州和哥伦比亚特区进行了长期的州一级调查。每次调查包括多达30,000名受访者,按州进行配额抽样这允许在州和国家一级进行可推广的推论。大流行后的数据为新的跨时间和跨空间研究设计提供了前所未有的机会。该项目对人口统计学上的少数民族答卷人进行了过度抽样,以便于对不同社会群体进行研究。这包括对政治人物和机构的信任、知识和信息、政治评估、行为适应、身体健康、经济福祉、心理健康等方面的数据。它还包含详细的社会网络电池,以便研究家庭间和群体间的健康和信息传播。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值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

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David Lazer其他文献

Categorizing the non-categorical: the challenges of studying gendered phenomena online
对非分类进行分类:在线研究性别现象的挑战
The effects of Facebook and Instagram on the 2020 election: A deactivation experiment
Facebook 和 Instagram 对 2020 年大选的影响:一项停用实验
  • DOI:
    10.1073/pnas.2321584121
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    11.1
  • 作者:
    Hunt Allcott;M. Gentzkow;Winter Mason;Arjun S. Wilkins;Pablo Barberá;Taylor Brown;Juan Carlos Cisneros;Adriana Crespo;Drew Dimmery;Deen Freelon;Sandra González;A. Guess;Young Mie Kim;David Lazer;Neil Malhotra;D. Moehler;Sameer Nair;Houda Nait El Barj;Brendan Nyhan;Ana Carolina Paixao de Queiroz;Jennifer Pan;Jaime Settle;Emily A. Thorson;Rebekah Tromble;Carlos Velasco Rivera;Benjamin Wittenbrink;Magdalena Wojcieszak;Saam Zahedian;Annie Franco;Chad Kiewiet de Jonge;N. Stroud;Joshua A. Tucker
  • 通讯作者:
    Joshua A. Tucker
Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives
利用共同分享来识别主流新闻在推广潜在误导性叙述方面的使用情况
  • DOI:
    10.1038/s41562-025-02223-4
  • 发表时间:
    2025-06-10
  • 期刊:
  • 影响因子:
    15.900
  • 作者:
    Pranav Goel;Jon Green;David Lazer;Philip S. Resnik
  • 通讯作者:
    Philip S. Resnik
A Normative Framework for Assessing the Information Curation Algorithms of the Internet.
评估互联网信息管理算法的规范框架。
DomainDemo: a dataset of domain-sharing activities among different demographic groups on Twitter
域演示:推特上不同人口群体之间的域共享活动的数据集
  • DOI:
    10.1038/s41597-025-05604-6
  • 发表时间:
    2025-07-16
  • 期刊:
  • 影响因子:
    6.900
  • 作者:
    Kai-Cheng Yang;Pranav Goel;Alexi Quintana-Mathé;Luke Horgan;Stefan D. McCabe;Nir Grinberg;Kenneth Joseph;David Lazer
  • 通讯作者:
    David Lazer

David Lazer的其他文献

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{{ truncateString('David Lazer', 18)}}的其他基金

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:
    2241887
  • 财政年份:
    2023
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Mid-scale RI-1 (M1:IP): Observatory for Online Human and Platform Behavior
中型 RI-1 (M1:IP):在线人类和平台行为观察站
  • 批准号:
    2131929
  • 财政年份:
    2021
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Cooperative Agreement
RAPID: Real time monitoring of information consumption regarding the coronavirus
RAPID:实时监控有关冠状病毒的信息消耗
  • 批准号:
    2026631
  • 财政年份:
    2020
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Collaborative research: Network Dynamics and Corporate Strategies
合作研究:网络动力学和企业战略
  • 批准号:
    1226834
  • 财政年份:
    2012
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Collaborative Research BCC-SBE: Using Archival Resources to Conduct Data-Intensive Internet Research
协作研究 BCC-SBE:利用档案资源进行数据密集型互联网研究
  • 批准号:
    1244730
  • 财政年份:
    2012
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
CDI-Type II: Collaborative Research: Dynamical processes in interdependent techno-social networks
CDI-类型 II:协作研究:相互依赖的技术社交网络中的动态过程
  • 批准号:
    1125095
  • 财政年份:
    2011
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Collaborative Research: Connecting to Congress: The Adoption and Use of Web Technologies Among Congressional Offices
协作研究:连接国会:国会办公室对网络技术的采用和使用
  • 批准号:
    1057868
  • 财政年份:
    2010
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Continuing Grant
Sharing Innovation Across Government Organizations
跨政府组织共享创新
  • 批准号:
    1049595
  • 财政年份:
    2010
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Computational Social Science Workshop at Harvard University's Institute for Quantitative Social Science in January 2010.
2010 年 1 月在哈佛大学定量社会科学研究所举办的计算社会科学研讨会。
  • 批准号:
    0949108
  • 财政年份:
    2009
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant
Sharing Innovation Across Government Organizations
跨政府组织共享创新
  • 批准号:
    0621242
  • 财政年份:
    2006
  • 资助金额:
    $ 8.03万
  • 项目类别:
    Standard Grant

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合作研究:COVID-19 后的美国机构:信任、责任和公众看法
  • 批准号:
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