Abstract:
The textbook legislative process is familiar to anyone with a basic understanding of US government. This narrative portrays lawmaking as a series of procedural steps – starting with the bill’s introduction in the House or Senate, moving to consideration in committee and on the floor, and concluding (hopefully) with the President signing it into law. We argue for a new narrative that focuses not on bill progress, but policy progress. We leverage computational text as data methods to investigate and more accurately describe how laws are actually made, how lawmaking has changed over time, and the sources of these changes.
John D. Wilkerson is the Donald R. Matthews Distinguished Professor in the Department of Political Science. He is co-author of Congress and the Politics of Problem Solving (Cambridge 2012) and lmages as Data for Social Science Research: An lntroduction to Convolutional Neural Nets for Image Classification (Cambridge Elements: Quantitative and Computational Methods for Social Science, 2020).
