Thesis papers in progress
Whose Law Is It? Network Analysis of the Evolution of U.S. Environmental Law, 1973-2013
To what degree do precedents predict and constrain outcomes? Are the hypothesized political drivers of judicial decisions detectable in the legal record? In this project, I assemble a large dataset of court cases from the U.S. federal court system. I reconstruct the network of citations between them, where a citation indicates whether the case affirms or overrules the principles asserted in prior cases. Using network analytic measures, I create a measure of legal change to test whether changes in political coalitions influence legal decisions. The results have implications for understanding the commitment power afforded by judicial institutions.

Whom to Obey? Pandering and the Authority of Judges and Politicians
One of the concerns with electoral democracy is that politicians pander to the public. The evidence regarding the behavior of strong Courts is that they too are concerned with the public’s reaction, but in different ways. According to qualitative analyses, as well as judges themselves, they are concerned with compliance, not just for the sake of seeing their position implemented but also because compliance today affects their authority in the future, especially if people complied with a Court position that didn’t simply mimic that of politicians in power (Friedman, 2009). This paper develops a formal model of the authority dynamic between the two types of officials, one seeking legitimacy and one seeking re-election. The analysis seeks to understand how the interaction of these two types of officials allow the public to learn about and control the quality of policies, especially long-term and uncertain policies.

Other on-going projects
An Ecology of Causal Belief Systems on the topic of Climate Change (with Johannes Castner)
How diverse are the causal belief systems of Americans regarding the economic, political, social and technological causes and consequences of global climate change? How can we measure and classify these beliefs, and what factors explain their variation? How do they compare to those of their representatives? These are the questions that this study address, drawing on the pioneering work of Robert Axelrod (1976), who conceptualized belief systems as causal maps. To measure the beliefs of the population, we propose to survey a large number of respondents via Amazon Mechanical Turk (MTurk), a Web-based platform for recruiting and paying subjects to perform tasks.