Social identity, group representation, and unequal responsiveness in the US and UK

Dickson, Zachary P. (2024) Social identity, group representation, and unequal responsiveness in the US and UK. PhD thesis, University of Glasgow.

Abstract

Legislative responsiveness to the preferences of an informed electorate is a key characteristic of representative democracy. Yet, studies increasingly show that the degree to which representatives respond to voters is contingent upon a host of features such as gender, social class and ideology. In this thesis, I argue that group identity shapes responsiveness to constituents and representation more broadly. Is how that representation can be understood through the lens of inter group conflict, with shared identity acting as a defining pre-requisite for group responsiveness. The thesis consists of four empirical chapters, each of which feature original research that leverage new observational data collected from national representatives in the United States and the United Kingdom. Methodologically, I rely on a variety of computational approaches to the study of text data such as transformer based language models, neural networks, and supervised machine learning. Additionally, I apply a range of statistical methods that incorporate both Bayesian and frequentist approaches to probability and uncertainty. Although each of the four articles utilize state-of-the-art methods, one of the real values of the thesis comes in its substantive contributions to our understanding of representation and elite behavior.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: J Political Science > JC Political theory
• Colleges/Schools: College of Social Sciences > School of Social and Political Sciences > Politics
• Supervisor's Name: Gherghina, Dr. Sergiu and Pardos-Prado, Professor Sergi
• Date of Award: 2024
• Depositing User: Theses Team
• Unique ID: glathesis:2024-84140
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 25 Mar 2024 10:07
• Last Modified: 25 Mar 2024 10:10
• Thesis DOI: 10.5525/gla.thesis.84140
• URI: https://theses.gla.ac.uk/id/eprint/84140