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

任何复杂的社会情况都会给认知能力有限的人类感知者提供比他们可能处理和存储的更多的信息。我们认为，研究感知、判断和决策的最好方法是观察人们在做出判断或决策时使用的过程--策略、启发式和算法。我们开发了一种新的动态过程跟踪方法，这种方法特别适合研究复杂社会情况下的信息处理和决策。我们在一系列研究中使用了这种方法来检查选民的决策，这些研究带来了重要的新见解。但这种方法可以用来检查几乎任何复杂的社会情况下的判断和决策。然而，要做到这一点，需要从根本上修改作为动态过程跟踪系统基础的软件。驱动该系统的软件是在几年的时间里临时开发的，从来没有为了与其他研究人员共享而变得特别“用户友好”。该项目将支持开发和测试一个基于网络的系统，使其他人能够使用动态进程跟踪方法。这个新项目将有管理和用户界面组件，以及一个数据管理系统，它将能够复制我们以前实验中的所有操作，并扩展该项目的能力，以适应其他从事相关决策项目的社会科学家的研究需求。该软件完成后，许多领域的研究人员都可以使用，并将为设计项目提供基础，这些项目旨在加强我们对人们如何在做出决策的尝试中获取和使用信息的理解。虽然之前使用动态过程跟踪的研究几乎只关注投票，但新的用户友好环境将允许测试广泛定义的大规模决策中的问题，一系列约束下的精英决策，实际上将适用于任何在不确定情况下、在有限的时间框架内做出决策以及信息可获得性随时间变化的环境。随着民主在世界各地蔓延，对政治学家来说，还有什么问题比公民如何做出投票选择更重要？该项目将帮助开发适用于21世纪的新一代投票行为理论，并向研究界提供一种新的研究工具，非常适合测试这些理论。该项目将培训研究生和本科生关于实验方法的价值(一般)和更具体的详细过程跟踪信息。这项研究有意识地研究了不同种族的选民和候选人，他们将在可预见的未来成为美国政治中越来越重要的一部分。这些研究的结果可以让政策制定者在考虑解决社会问题的替代方法时提供信息，并就如何解决这些问题听取公民的建议。

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.