Defining Policy Issues: The Dynamics of Information Processing and Issue Definitions
Abstract
This dissertation examines how information is translated into issue definitions. Issue definitions---the way that policy issues are understood---have long been noted to be important for policy choices. In this project, I develop a model of issue definitions where issues are understood as a function of the various dimensions of the issue weighted by the importance of each dimension. I then incorporate this model into the theory of information processing developed by Jones and Baumgartner (2005). The theory of information processing posits that information can be understood as signals in the policymaking environment, and information processing is the collection and prioritizing of those signals. In this dissertation, I model these information signals as the salience of each dimension of an issue. Using the case of used nuclear fuel (UNF) management, this dissertation test hypotheses about the nature of issue definitions and policy change, institutions, and policy actors. Specifically, I estimate the dimensions of the UNF issue using latent Dirichlet allocation, a type of quantitative text analysis. Following the development of the UNF dimensions, I test hypotheses about how the salience of these dimensions are related to policy change, how institutional structures influence dimension salience, and how policy actors systematically highlight some dimensions over others.
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