Collaborative Research: Deliberative E-Rulemaking Decision Facilitation Project (DEER)

合作研究：审议性电子规则制定决策促进项目 (DEER)

• 批准号: 0713143
• 负责人: Peter Muhlberger
• 金额: $ 13.23万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0713143&HistoricalAwards=false
• 关键词: Collaborative; Research; Deliberative; Rulemaking; Decision

This project will examine whether federal agency rulemaking can be improved with two innovations: a) multi-level deliberation (MLD), in which people discuss rulemakings in small groups that then select members to represent the group in a higher-level group and b) the combination of language technologies into an artificial discussion facilitation agent (DiFA). The project poses computer science challenges of combining several Natural Language Processing technologies (primarily Interactive QA, Dialogue Analysis, and Summarization) into a viable facilitation agent and in applying these technologies in an eclectic, multi-user discussion environment. We expect advances to be made within each component technology. For example, we hope to increase the utility of Dialogue Act tagging across applications and domains by using a set of general discussion tags for tracking and summarizing threads of discussion by combining dialogue structure and content analysis. We will also investigate how general our Question Answer approaches are. The social science herein breaks new ground in the nascent fields of e-rulemaking and democratic deliberation research. The project will advance research on measuring the quality of deliberation and the effects of deliberation and DiFA on individuals and communities. Research will involve four rulemaking experiments. The first three are subsets of the final one. The final 3X2 experiment crosses MLD, non-MLD deliberation, and non-deliberation with the presence or absence of DiFA. The success of the various conditions of these experiments will be measured using a multi-trait, multi-method approach that will include survey and focus group measures of agency official and participant perceptions and evaluations, a content analysis measure of the cognitive sophistication of rulemaking comments, both human-coded and automated content analyses of the quality of deliberation, measures of the impact of the deliberations on participants (knowledge, trust, citizenship), DiFA usage patterns, and continued participation in our user community.The federal agency rulemaking comment process represents an important potential avenues by which the American public can affect how it is governed. Such comments can make agency officials aware of likely adverse effects of the proposed rules. Unfortunately, the current rulemaking comment process faces a number of social and organizational problems including poorly informed and distrustful participants, lack of dialog among participants that could sharpen their reasoning, and problems of scale such as the large number of comments generated. Researchers believe that most rulemaking comments are low in quality or redundant?a product of form letters used by public interest groups. Rulemaking is not a plebiscite, but an effort to identify reasons to accept or modify proposed rules. This project will seek to address the problems of existing rulemaking by immersing rulemaking participants in small discussion groups that will be assisted by discussion facilitation software. The software will use cutting-edge technologies to help answer questions, summarize discussion, and provide feedback and suggestions on their discussion. Discussion itself will be organized into a hierarchy of representative groups to help the best ideas spread among participants and rise to the top. The value of the technology and of the deliberation methods will be thoroughly tested using experimental methods and data collected via surveys, focus groups, and by the software. The project will advance research in several areas. In computer science, it will seek to apply natural language technologies in a more general setting than before. The technology created could have broad application. It will also combine several technologies into a discussion facilitator that may be more widely used. The project will also advance research on democratic deliberation by improving and testing measures of deliberative quality and by adding to knowledge of how deliberation affects citizens.

该项目将研究是否可以通过两项创新来改进联邦机构的规则制定：a)多层次审议（MLD），人们在小组中讨论规则制定，然后选择成员代表更高级别的小组；b)将语言技术结合到人工讨论促进代理（DiFA）中。该项目提出了将几种自然语言处理技术（主要是交互式QA、对话分析和总结）结合到一个可行的促进代理中的计算机科学挑战，并将这些技术应用于折衷的多用户讨论环境中。我们期望每个组件技术都能取得进步。例如，我们希望通过结合对话结构和内容分析，使用一组通用讨论标签来跟踪和总结讨论线程，从而增加跨应用程序和领域的对话行为标签的效用。我们还将调查我们的问答方法有多普遍。社会科学在新兴的电子规则制定和民主审议研究领域开辟了新的领域。该项目将推进有关衡量审议质量以及审议和DiFA对个人和社区的影响的研究。研究将涉及四项规则制定实验。前三个是最后一个的子集。最后的3X2实验跨越了MLD、非MLD审议和有无DiFA的非审议。这些实验的各种条件的成功将使用一种多特征、多方法的方法来衡量，其中包括对机构官员和参与者的看法和评估的调查和焦点小组测量，对规则制定评论的认知复杂性的内容分析测量，对审议质量的人工编码和自动内容分析，对审议对参与者的影响的测量（知识、信任、公民身份），DiFA使用模式，并继续参与我们的用户社区。联邦机构的规则制定评论程序代表了美国公众可以影响其治理方式的重要潜在途径。这样的评论可以使机构官员意识到拟议规则可能产生的不利影响。不幸的是，目前的规则制定评论过程面临着许多社会和组织问题，包括参与者缺乏信息和不信任，参与者之间缺乏可以提高其推理能力的对话，以及产生大量评论等规模问题。研究人员认为，大多数制定规则的评论都是低质量的或多余的。公共利益团体使用的格式信函的产物。规则制定不是公民投票，而是努力找出接受或修改拟议规则的理由。该项目将寻求解决现有规则制定的问题，方法是让规则制定参与者参与小型讨论小组，并在讨论促进软件的协助下进行讨论。该软件将使用尖端技术来帮助回答问题，总结讨论，并就讨论提供反馈和建议。讨论本身将被组织成一个代表小组的等级制度，以帮助最好的想法在参与者中传播，并上升到最高层。技术和审议方法的价值将通过实验方法和通过调查、焦点小组和软件收集的数据进行彻底测试。该项目将推进几个领域的研究。在计算机科学方面，它将寻求在比以前更普遍的环境中应用自然语言技术。所创造的技术可能有广泛的应用。它还将几种技术结合成一个可能得到更广泛使用的讨论促进者。该项目还将通过改进和测试协商质量的措施，以及增加对协商如何影响公民的认识，推进民主协商的研究。