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Collaborative Research: Studying Information Processing in Political Science: Improving Infrastructure, Testing Theory

Collaborative Research: Studying Information Processing in Political Science: Improving Infrastructure, Testing Theory
合作研究:研究政治学中的信息处理:改善基础设施、测试理论
批准号:
0647738
负责人:
David Redlawsk
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-05-01 至 2010-04-30

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Any complex social situation will present cognitively limited human perceivers with far more information than they can possibly process and store. We argue that the best way to study perception, judgment, and decision making is to observe the processes - strategies, heuristics, and algorithms - people employ while they are making a judgment or decision. We have developed a new dynamic process tracing methodology that is uniquely suited to studying information processing and decision making in complex social situations. We have used the methodology to examine voter decision making in a series of studies that have led to important new insights. But this methodology could be used to examine judgment and decision making in almost any complex social situation. To do so, however, requires that the software underlying the dynamic process tracing system be radically revised. The software that drives the system was developed over several years on an ad-hoc basis and was never made particularly "user friendly" for sharing with other researchers. This project will support the development and testing of a web-based system that will make it possible for others to use the dynamic process-tracing methodology. This new program will have administrative and user interface components and a data management system that will be able to replicate all of the manipulations from our previous experiments, and extend the capabilities of the program to accommodate the research needs of other social scientists working on related decision-making projects. The software, when complete, will be accessible to researchers in many fields, and will provide a base for designing projects meant to enhance our understanding of how people acquire and use information in their attempts to make decisions. While previous studies using dynamic process tracing have focused almost solely on voting, the new user-friendly environment will allow tests of questions in mass decision making broadly defined, elite decision making under a range of constraints, and will in fact will be adaptable to any environment in which decisions are made under uncertainty, within a limited timeframe, and where information availability changes over time.As democracy spreads across the world, what question could be more important for political scientists to address than how do citizens make their vote choices? This project will help develop a new generation of theories of voting behavior suitable for the 21st century, and make available to the research community a new research tool ideally suited to testing those theories. The project will train both graduate and undergraduate students in the value of experimental methods (in general) and detailed process tracing information more specifically. The research consciously studies ethnically diverse voters and candidates who will become an increasingly important part of American politics over the conceivable future. The results of these studies can inform policy makers as they contemplate alternative means for addressing social problems and of obtaining advice from citizens on just how those problems should be addressed.
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Collaborative Research: SoCS: Analysis of Social Media Driven By Theories of Political Psychology
  • 批准号:
    0968295
  • 项目类别:
    Standard Grant
  • 资助金额:
    $38.81万
  • 财政年份:
    2010
  • 负责人:
    David Redlawsk
  • 依托单位:
Multi-Investigator Multi-Site Experiments and Infrastructure Development
  • 批准号:
    1022551
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $19.99万
  • 财政年份:
    2010
  • 负责人:
    David Redlawsk
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
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