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年的合作选举研究（CES）是全美50多个不同大学研究团队的合作。 该小组共同设计并对至少50,000名美国成年人进行了大量样本调查。样本量非常大，研究人员可以拥有足够的数据来研究国家选民以及整个国家。该调查衡量了国家和州选举中的人口统计学，观点和态度以及投票行为。该调查用于研究谁的投票，原因，以及什么解释了选民做出的选择。该项目的数据被研究人员，记者和公众广泛使用，以了解美国选举和舆论。该调查有助于建立和维持对州和国家选举，调查设计和舆论感兴趣的研究人员网络。 2020年CES调查是由研究团队的财团开发的。 希望参与该项目的每个研究团队都会从同一公司购买1,000人的样本调查。 每个团队确定调查中的一半问题。内容的另一半（共同内容）是由设计委员会创建的，该委员会是由参与团队汲取的。常见内容包括每个团队都想衡量或需要大量样本的问题。 因此，该项目与团队一样多的调查领域，还会产生一个由共同内容组成的大型样本调查。 该调查是通过互联网进行的，其样本构成为全国代表。 每个团队都从其自己的1,000人调查中收到数据，以及一个由共同内容调查的50,000多个观察结果组成的数据集。 调查数据是使用选民验证验证的，并通过对每个州的子样本的调查结果进行比较。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估评估来获得支持的。

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