The Power of Policy Ideas: Tracing Language in Policymaking

政策理念的力量：追踪政策制定中的语言

• 批准号: 1224173
• 负责人: John Wilkerson
• 金额: $ 23.64万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1224173&HistoricalAwards=false
• 关键词: Power; Policy; Ideas; Tracing; Language

The purpose of the proposed project is to initiate the systematic study of policy ideas. Bills often contain a multitude of policy provisions and evolve during their consideration. This project addresses the extent to which successful bills incorporate policy ideas originally proposed by lawmakers other than the bill's sponsor. Is policy influence substantially more widespread when assessed in terms of the progress of policy ideas rather than bills? What personal and institutional factors promote or inhibit the incorporation of policy ideas? How do external focusing events or internal schedules such as reauthorizations shape opportunities to advance policy ideas?The project's intellectual merit is associated with its comprehensive data collection and analysis, interdisciplinary component, and attention to critical policy questions. To study these questions, the project uses a "big data" approach to examine the substance of the approximately 80,000 House and Senate bills introduced during the 1993-2011 time period. Each bill is divided, or parsed, by section (approximately 800,000 sections), before assessing the similarity of each section to each other section using algorithms developed to study "text reuse" in computer science. An underlying assumption is that similar sections found in different bills constitute the same policy idea. This allows the researcher to follow the progress of an idea as distinct from the progress of a particular bill. Validation will be a central focus of the project. The project will engage computer scientists to test alternative approaches to assessing section similarity to better understand their implications for Type I and Type II errors. It is expected that a study of policy ideas will lead to important insights into three topics integrally related to mainstream legislative research: policy influence, legislative agenda setting, and comparative committee processes.The broader impacts of the project are directly related to the data it will produce. The corpus will be a valued resource for future researchers and students in many fields. By partitioning complex and often large laws and bills into a researchable format, scholars will be able to systematically peer "under the hoods" of bills and therefore gain valuable new perspectives on the policymaking process. For example, the dataset will provide a valuable resource for scholars interested in legislative networks such as policy subsystems, policy representation, logrolling, lobbying influence, and many other topics. In addition, computer and information scientists will value the corpus as a test bed for natural language processing research. Finally, any citizen or reporter will be able to utilize our searchable database to trace the substance and progress of policy ideas proposed by a given lawmaker. Such a search will yield a more accurate assessment of priorities and policy influence.

拟议项目的目的是启动对政策思想的系统研究。法案通常包含大量的政策条款，并在审议过程中不断发展。这个项目研究成功的法案在多大程度上包含了法案发起人以外的立法者最初提出的政策思想。当以政策构想的进展而非以法案的进展来评估时，政策影响是否会广泛得多？哪些个人因素和制度因素促进或抑制了政策思想的融合？外部焦点事件或内部计划（如重新授权）如何塑造推进政策思想的机会？该项目的智力价值与其全面的数据收集和分析、跨学科组成部分以及对关键政策问题的关注有关。为了研究这些问题，该项目使用“大数据”方法来检查1993年至2011年期间提出的大约8万份参众两院法案的实质内容。在使用计算机科学中用于研究“文本重用”的算法评估每个部分与其他部分的相似性之前，每个账单都按部分（大约80万个部分）进行划分或解析。一个潜在的假设是，在不同法案中发现的类似章节构成了相同的政策理念。这使得研究人员可以跟踪一个想法的进展，而不是一个特定法案的进展。验证将是项目的中心焦点。该项目将邀请计算机科学家测试评估剖面相似性的替代方法，以更好地了解它们对I型和II型错误的影响。预计对政策理念的研究将导致对与主流立法研究相关的三个主题的重要见解：政策影响、立法议程设置和比较委员会程序。该项目的更广泛影响与它将产生的数据直接相关。该语料库将成为未来许多领域的研究人员和学生的宝贵资源。通过将复杂且往往庞大的法律和法案划分为可研究的形式，学者们将能够系统地了解法案的“幕后”，从而获得有关政策制定过程的宝贵新视角。例如，该数据集将为对立法网络感兴趣的学者提供宝贵的资源，如政策子系统、政策表示、滚动、游说影响和许多其他主题。此外，计算机和信息科学家将把语料库作为自然语言处理研究的试验台。最后，任何公民或记者都可以利用我们的可搜索数据库来追踪特定议员提出的政策构想的实质和进展。这种研究将对优先事项和政策影响作出更准确的评估。