“Polarizing Pluralism: Party Competition, Interest Group Strategy, and the Resurgent Mischiefs of Faction,” Alexander Furnas, Northwestern University

AMERICAN POLITICS & PUBLIC POLICY WORKSHOP

Abstract: Given their usual depiction as parochial and pragmatic policy-seekers, our findings in “Polarized Pluralism” (Crosson, Furnas, Lorenz 2020) regarding the polarization of modern-day interest groups are puzzling. Particularly in an era wherein predicting party control of government is especially difficult, why would policy-motivated interests seemingly align themselves with just one political party? In this book, we seek to answer this question. To do so, we draw on large-scale data collection of interest group position-taking over time and analyze these data using cutting-edge computational methods. Through a series of empirical exercises, we test a new theory of interest group partisanship, wherein we argue that the rise of insecure partisan majorities in Congress has led members of Congress to look for signals of allegiance to party, above and beyond the usual signals of alignment of (issue-specific) preferences. This is part of an ongoing book project with Jesse Crosson (Purdue) and Geoff Lorenz (Nebraska-Lincoln).

Alexander C. Furnas PhD (Zander), is a Research Assistant Professor at the Center for Science of Science and Innovation at the Kellogg School of Management, Northwestern University. He has a PhD in political science from the University of Michigan. He researches the political economy of information, with a focus on the production, dissemination and uptake of science and expertise in the policymaking process. He has published or forthcoming articles in the American Political Science Review, Proceedings of the National Academy of Sciences, Legislative Studies Quarterly, and the American Journal of Political Science among others. More generally, he studies the use of information, science, and expertise in policymaking, interest groups, and elite political behavior using survey, text analysis and network methods.

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