Measuring and Explaining Discrimination

Abstract

How can we measure discrimination? What drives it? How can we reduce it? My dissertation addresses these important questions. In the first part, I provide methodological guidance on how to conduct audit studies. In Chapter 2, I offer the first comprehensive guide to conducting audit studies in political science. In Chapter 3, I provide the first introduction that I am aware of to conducting audit studies via email. These chapters provide advice about how researchers can improve existing audit study designs and implement them with increased efficiency. In Chapter 4, I address one of the most important methodological issues involved in audit studies - name selection. I demonstrate that the probability of a name denoting a race varies considerably across contexts and that this is more of a problem for some names than others. This suggests limitations for (1) the generalizability of audit study findings and (2) the interpretation of geography-based conditional effects.

In the second part of my dissertation, I use audit and survey experiments to better understand racial, gender, and religious discrimination in America. The first set of chapters build on past audit studies by not only measuring discrimination but also attempting to identify its causes. In Chapter 5, I measure discrimination by county election officials during the 2016 election cycle, showing that the bias toward Latinos observed during the 2012 election has persisted. I also show that Arab/Muslim Americans face an even greater barrier to communicating with local election officials, and that this bias appears driven by implicit discrimination. I find no evidence of bias toward Blacks, however, indicating that discrimination against groups in political contexts might be sample dependent.

In Chapter 6, I examine religious discrimination among public-school principals, an important groups of street-level bureaucrats. I emailed the principals of more than 45,000 public schools and asked for a meeting, randomly assigning the religious affiliation/non-affiliation of the family and family belief intensity. I find evidence of substantial discrimination against Muslims and atheists, particularly when their religious beliefs are high, as well as bias against ardent protestants and Catholics. These results suggest that one of the mechanisms driving discrimination is belief intensity.

The remaining chapters in the second part of the dissertation extend prior work by not only identifying discrimination in important contexts but also by attempting to reduce it. In Chapter 7, I provide the results from an adapted audit experiment designed to test whether making local officials aware of their possible biases could reduce discrimination. I find no evidence that my informational treatment influences discriminatory behavior, but that White, local, elected officials are less responsive to Black constituents. This is concerning as local government is often the level that most directly affects citizens' daily lives.

In Chapter 8, I investigate racial discrimination by the police. I argue that it depends in a conditional way on the extent of egalitarian views among the police and the public. To test my theory, I conduct a survey experiment with American law enforcement administrators and elected officials who oversee the police. Elected politicians exhibit less racial discrimination in law enforcement oversight when informed that the public supports racial equality in policing. Police, though, do not react to perceived public demand for egalitarianism. My results suggest that public attitudes toward racial equality influence police discrimination perhaps only indirectly.