What does money mean? : frames of wealth and economic identity in U.S. politics, 1980-2020
In this dissertation, I interrogate the ways political candidates’, elite journalists’, and everyday peoples’ discourses address the U.S. political hierarchy in terms of the role(s) of money in politics and of wealth and wealth-based identities. I am interested in if and how groups in the U.S. use or ignore differences in class and wealth to order who and what is important in our democratic republic. This dissertation focuses on that concern in six chapters. In the first chapter, I overview the historic and contemporary contexts of wealth in the United States, address the place of money in politics, and provide a theoretical framework for the project. In Chapter Two, I present the research design and methodological choices for the three cases that compose my analysis. In the subsequent chapters, I present my results. Chapter Three is an inductive, computer-assisted, quantitative analysis of wealth-based frames promoted by presidential candidates across 40 years of U.S. elections (1980-2020). Chapter Four uses a deductive, human-coded, quantitative content analysis to assess the frames propagated by print and television news organizations across the same period. Chapter Five uses open-ended survey responses from 2020 to inductively and qualitatively examine how the language of everyday individuals frames money and political power. In the closing chapter, I synthesize my findings and compare the wealth-based hierarchies crafted by presidential candidates, elite journalists, and everyday individuals in political and public life in the U.S. In the end, I argue there is a top-down effort to background class-based identities and flatten different socioeconomic experiences to the moniker of middle class, but there is also a ground-up rebuttal to challenge the overdetermining power of money in U.S. political life and use that power to create a moral, equitable democracy.
Political communication, Class, Inequality, Economics, Rhetoric, Content analysis, Topic modeling, Wealth, Money, Income, Identity, United States
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