2022 Cooperative Election Study

2022年合作选举研究

• 批准号: 2148907
• 负责人: Stephen Ansolabehere
• 金额: $ 89.76万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148907&HistoricalAwards=false
• 关键词: 2022; Cooperative; Election; Study

The 2020 Cooperative Election Study (CES) is a collaboration of over 50 different university research teams throughout the United States. Collectively this group designs and fields a large sample survey of at least 50,000 American adults. The very large sample size allows researchers to have sufficient data to study state electorates as well as the entire nation. The survey measures demographics, opinions and attitudes, and voting behavior in national and state elections. The survey is used to study who votes and why, and what explains the choices that voters make. The data from this project are used widely by researchers, journalists, and members of the public to understand American elections and public opinion. The survey helps to create and sustain a network of researchers interested in state and national elections, survey design, and public opinion. The 2020 CES survey is developed by a consortium of research teams. Each research team that wishes to be involved in the project purchases a 1,000-person sample survey from the same firm. Each individual team determines half of the questions on its survey. The other half of the content (Common Content) is created by a design committee, drawn from the participating teams. Common Content consists of questions that every team would like to measure or questions that are of broad interest and require a very large sample. The project, thus, fields as many surveys as there are teams and also produces a single large sample survey that consists of the Common Content. The survey is fielded over the Internet, with samples constructed to be nationally representative. Each team receives the data from its own 1,000-person survey and a dataset consisting of the 50,000+ observations from the Common Content survey. Survey data are validated using voter validation and through comparisons of state level election results to the survey results from the sub-samples for each state.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.

2020年合作选举研究（CES）是美国50多个不同大学研究团队的合作。 这个小组共同设计并实地调查了至少5万名美国成年人。非常大的样本量使研究人员有足够的数据来研究州选民以及整个国家。这项调查衡量了人口统计数据、意见和态度以及全国和州选举中的投票行为。该调查用于研究谁投票，为什么投票，以及如何解释选民的选择。该项目的数据被研究人员、记者和公众广泛使用，以了解美国选举和公众舆论。该调查有助于建立和维持一个对州和全国选举、调查设计和民意感兴趣的研究人员网络。 2020年CES调查由一个研究团队联盟开发。 每个希望参与该项目的研究小组都从同一家公司购买了1,000人的抽样调查。 每个小组决定其调查中的一半问题。另一半内容（公共内容）由设计委员会创建，该委员会来自参与团队。公共内容由每个团队都想衡量的问题或具有广泛兴趣并需要非常大样本的问题组成。 因此，该项目的实地调查数量与团队数量一样多，并且还产生了一个由共同内容组成的单一大型抽样调查。 调查通过互联网进行，抽样具有全国代表性。 每个团队都从自己的1，000人调查中获得数据，并从Common Content调查中获得50，000多个观察结果。 调查数据通过选民验证和州一级选举结果与每个州子样本调查结果的比较进行验证。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

The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level

种族两极分化投票的地理分布：校准地区一级的调查

• DOI: 10.1017/s0003055423000436
• 发表时间: 2023
• 期刊: American Political Science Review
• 影响因子: 6.8
• 作者: KURIWAKI, SHIRO;ANSOLABEHERE, STEPHEN;DAGONEL, ANGELO;YAMAUCHI, SOICHIRO
• 通讯作者: YAMAUCHI, SOICHIRO