Date of Degree
PhD (Doctor of Philosophy)
Boehmke, Frederick J
First Committee Member
Osborn, Tracy L
Second Committee Member
Third Committee Member
Menninga, Elizabeth J
Fourth Committee Member
Shipan, Charles R
State supreme courts are autonomous institutions with significant power. Yet, despite this authority, state supreme courts routinely rely on one another to explain why and how they reached their decisions. This puzzle of why state supreme courts cite each other in their opinions led me to pose two questions. First, under what conditions do state supreme courts cite other states supreme courts? And second, to whom do they turn for guidance? To answer these questions, I propose a new theory for evaluating state supreme court citations, the social learning model. I borrow policy diffusion’s learning mechanism and I pair it with network theory and methods to explain peer-to-peer state supreme court citations practices. I argue that courts are social actors who interact, influence, and learn from one another, and the citations are communications by and between the courts.
To model citations between courts, I apply a temporal exponential random graph network analysis model or TERGM. TERGMs simulate the evolution of the state-to-state citation network by including aspects of both the courts and the network structure. I argue that only by understanding how networks and issue areas evolve can we begin to understand how courts and justices make decisions. The network approach to citations specifically tests these endogenous relationships, it also directly models the complex dependencies of citation networks.
My findings demonstrate the courts became more connected over time and no single state supreme court leader emerges. I find that citations are endogenous; what one court does affects other courts. I also discover that the area of law matters a lot and it is insufficient to pool all legal issues into a single model. Finally, state supreme courts do not cite state supreme courts who look like them. Overall, the evidence suggests the courts are learning from each other. The courts’ written language discloses the mechanism. Courts state their own case law does not provide a solution to the question presented and they must seek answers elsewhere. Additionally, the courts do not always cite the same state, as we would expect from emulation. Together, these findings demonstrate that state supreme courts are connected, they learn from one another.
Judicial politics, Law, Network analysis, Policy Diffusion, State supreme courts
xii, 153 pages
Includes bibliographical references (pages 135-144).
Copyright © 2017 Abigail Anne Matthews
Matthews, Abigail Anne. "Connected courts: the diffusion of precedent across state supreme courts." PhD (Doctor of Philosophy) thesis, University of Iowa, 2017.