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ANES WEB: American National Election Studies 2018-2021

ANES WEB: American National Election Studies 2018-2021
ANES 网站:2018-2021 年美国全国选举研究
批准号:
1835022
负责人:
Shanto Iyengar
金额:
$382.5万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-15 至 2023-08-31

项目摘要

项目成果

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中文摘要
翻译
ANES Web 2020研究旨在建立在世界上运行时间最长的民主生命体征调查数据的时间序列基础上。 通过揭示2020年总统选举中投票选择和政治参与的决定因素,2020年ANES将产生高质量的数据,重点关注民主治理的核心问题,包括公民对政府的满意度以及他们对政治领导人负责的能力。虽然2020年的研究延续了新的横截面样本的传统,但它还包括两个小组组成部分,使研究人员能够研究美国公众舆论在国家政治特别动荡时期的变化。 对2016年ANES受访者的重新采访将揭示特朗普总统当选后态度的长期变化。对在2020年春季完成综合社会调查的受访者子样本的重新采访将揭示2020年竞选期间信仰和观点的更多短期变化。总体而言,ANES 2020研究为研究人员提供了对选民决策动态的强大影响力。2020年的研究将继续作为美国民意研究的基准。这项研究将调查至少3,500名美国人,通过邮件招募他们在线填写问卷。这些参与者将在三个样本中招募:(1)1,200名美国人的新样本,使用通过2016年广泛测试开发的高响应率协议进行选择和招募;(2)与2016年完成ANES访谈的1,400名受访者进行重新访谈;(3)重新访问900名于2020年较早前完成综合社会调查的受访者。这些数据集将允许对许多重要问题进行开创性的研究,这些问题是单一的横截面研究所不可能实现的,为绘制美国政治的连续性和变化提供了独特的机会。2020年的研究还扩展了ANES最近和正在进行的努力,通过高质量的邮件到网络数据收集来重塑大规模调查研究的轨迹,并具有ANES和GSS之间的首次合作。大约500名拉丁美洲人和500名非洲裔美国人的子样本将超过以前的ANES研究,并允许研究人员调查种族在重塑主要政党联盟中的作用,以及推动选民投票的力量。鉴于性别对2016年选民态度的强大影响,2020年的研究将继续在调查工具中突出性别相关问题。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。
英文摘要
The ANES Web 2020 study is designed to build upon the world's longest-running time series of survey data on the vital signs of democracy. By uncovering the determinants of vote choice and political participation in the 2020 presidential election, the 2020 ANES will yield high-quality data focusing on questions that go to the heart of democratic governance including citizens' satisfaction with their government and their ability to hold political leaders accountable. While the 2020 study continues the tradition of a fresh cross-section sample, it also includes two panel components that allow researchers to examine changes in American public opinion over an especially turbulent period of national politics. Re-interviews with 2016 ANES respondents will shed light on long-term changes in attitudes following the election of President Trump. Re-interviews with a sub-sample of respondents who completed the General Social Survey in the spring of 2020 will illuminate more short-term shifts in beliefs and opinions over the course of the 2020 campaign. Overall, the ANES 2020 study provides researchers with strong leverage over the dynamics of voter decision making. The 2020 study will continue to serve as a benchmark for research on American public opinion. The study will survey at least 3,500 Americans, recruited by mail to complete questionnaires online. These participants will be recruited in three samples: (1) a new sample of 1,200 Americans, selected and recruited using a high-response-rate protocol developed through extensive testing in 2016; (2) re-interviews with 1,400 respondents who completed the ANES interviews in 2016; (3) re-interviews with 900 respondents who completed the General Social Survey earlier in 2020. These datasets will permit groundbreaking research on many important questions that would not be possible with a single cross-sectional study, providing unique opportunities to map continuity and change in American politics. The 2020 study also extends recent and ongoing ANES efforts to reshape the trajectory of large-scale survey research with high-quality mail-to-web data collection, and features the first-ever collaboration between ANES and GSS. Sub-samples of around 500 Latinos and 500 African-Americans will exceed previous ANES studies and allow researchers to investigate the role of race in reshaping major party coalitions and as a force that propels voters to the polls. Given the powerful effects of gender on voters' attitudes in 2016, the 2020 study will continue to highlight gender-related issues in the survey instrument.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.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
Measuring Political Knowledge and Not Search Proficiency in Online Surveys
在在线调查中衡量政治知识而不是搜索能力
DOI: 10.1093/ijpor/edac002
发表时间: 2022
期刊: International journal of public opinion research
影响因子: 1.8
作者: [DeBell, Matthew]
通讯作者: DeBell, Matthew
DOI: 10.1089/elj.2019.0610
发表时间: 2021
期刊: and Policy
影响因子: --
作者: [DeBell, Matthew, Iyengar, Shanto]
通讯作者: Iyengar, Shanto
A randomized experiment evaluating survey mode effects for video interviewing
评估视频采访调查模式效果的随机实验
DOI: 10.1017/psrm.2022.30
发表时间: 2023
期刊: Political Science Research and Methods
影响因子: 3.9
作者: [Endres, Kyle, Hillygus, D. Sunshine, DeBell, Matthew, Iyengar, Shanto]
通讯作者: Iyengar, Shanto
The Visible Cash Effect with Prepaid Incentives: Evidence for Data Quality, Response Rates, Generalizability, and Cost
预付费激励的可见现金效应:数据质量、响应率、普遍性和成本的证据
DOI: 10.1093/jssam/smac032
发表时间: 2022
期刊: Journal of Survey Statistics and Methodology
影响因子: 2.1
作者: [DeBell, Matthew]
通讯作者: DeBell, Matthew
共 6 条
    Collaborative Research: American National Election Studies (ANES) 2014 - 2017
    • 批准号:
      1444910
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $361.64万
    • 财政年份:
      2014
    • 负责人:
      Shanto Iyengar
    • 依托单位:
    Television Advertising in Political Campaigns: A Study of the 1992 California Senate Races
    Political Understanding: How People Explain Politics
    • 批准号:
      8420160
    • 项目类别:
      Standard Grant
    • 资助金额:
      $10.6万
    • 财政年份:
      1985
    • 负责人:
      Shanto Iyengar
    • 依托单位:
    Collaborative Research on Experimental Studies of Media Agenda-Setting
    • 批准号:
      8208714
    • 项目类别:
      Standard Grant
    • 资助金额:
      $5.79万
    • 财政年份:
      1982
    • 负责人:
      Shanto Iyengar
    • 依托单位:
    国内基金
    海外基金
    基于动态扩散模型与代码知识迁移的Web服务特征增强方法研究
    • 批准号:
      2026JJ80511
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2026
    • 负责人:
      肖勇
    • 依托单位:
    面向Web3D虚拟学习空间的教育智能体系统构建与应用
    • 批准号:
      2025JJ80330
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2025
    • 负责人:
      龙艳军
    • 依托单位:
    基于Web3D元宇宙的实时渲染关键技术研究和应用
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2025
    • 负责人:
      宋三泰
    • 依托单位:
    基于语义理解的多轮多约束Web服务推荐技术
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
    • 依托单位: