DOI

10.17077/etd.talvw2za

Document Type

Dissertation

Date of Degree

Summer 2017

Degree Name

PhD (Doctor of Philosophy)

Degree In

Political Science

First Advisor

Boehmke, Frederick J.

First Committee Member

Osborn, Tracy L.

Second Committee Member

Pacheco, Julianna

Third Committee Member

Menninga, Elizabeth J.

Fourth Committee Member

Shipan, Charles R.

Abstract

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 Finally, state supreme courts do not cite state supreme courts who look like them.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.

Keywords

Judicial politics, Law, Network analysis, Policy Diffusion, State supreme courts

Pages

xii, 153 pages

Bibliography

Includes bibliographical references (pages 135-144).

Copyright

Copyright © 2017 Abigail Anne Matthews

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