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.
