LSE - Small Logo
LSE - Small Logo

Brianna A. Smith

June 27th, 2024

What music genre preference can tell us about attitudes towards race in America

0 comments | 2 shares

Estimated reading time: 7 minutes

Brianna A. Smith

June 27th, 2024

What music genre preference can tell us about attitudes towards race in America

0 comments | 2 shares

Estimated reading time: 7 minutes

Can we use people’s music preferences to measure how they feel about race? Measuring racial attitudes has traditionally not been easy for social scientists, but in new research, Brianna A. Smith theorizes that music genre preference can predict political attitudes related to race. Using four surveys which measure racial and political attitudes alongside music preferences, they find that these preferences were a better predictor of racial attitudes than more established measures.

When Old Town Road by Lil Nas X gained popularity in 2019, there was immediate debate over whether it counted as ‘country music.’ It reached 19 on the Billboard Hot Country charts, before being pulled from the list due to lack of ‘genre fit.’ Similar debates have been had over Beyoncé’s 2016 song Daddy Lessons, and her 2024 album Cowboy Carter. As other mainstream country musicians blur the lines between country, rap, rock, and blues, many have argued that musicians like Lil Nas X and Beyoncé are treated differently because Americans fundamentally perceive country as a genre made by white musicians for white listeners.

It’s not a new argument to say that music and racial identity are strongly intertwined in American history. And it’s also true that plenty of Black Americans make and listen to country music, while plenty of white Americans make and listen to rap. But as I listened to Old Town Road on loop, I was also wondering whether our perception of music as ‘Black’ or ‘white’ could be used to solve a major problem in survey research: measuring and understanding people’s attitudes about race. Over the next three years, I conducted four surveys tackling this problem. I found that white Americans’ music preferences are in fact strongly associated with their racial attitudes, and that music preferences are in many ways a better measure of racial attitudes than what most social scientists use today.

Using perceptions about music to measure attitudes about race

Racial attitudes, especially attitudes about Black Americans, are important for anyone trying to understand American society and public opinion. Over the decades, social scientists have used racial attitude measures to study why Americans supported or opposed policies like segregation and affirmative action, as well as politicians and public figures like Barack Obama and Colin Kaepernick.

Unfortunately, those racial attitude measures are widely regarded as flawed. Some of them are too blatant – imagine being simply asked ‘are you racist?’ Most people would immediately say no without thinking deeply about the question, and would probably be offended even to be asked. Other racial attitude measures are too political, blurring the lines between measuring ideology and racial attitudes. We know that both liberals and conservatives can hold racial prejudice – so it’s important to be able to measure these concepts separately.

The ideal measure of racial attitudes should be easy to answer, without involving politics or making people think there’s a ‘correct’ answer that they need to give. It should predict political attitudes related to race, like support for affirmative action or Black Lives Matter, and not predict other attitudes like support for environment and infrastructure spending. I theorized that music genre preference could be this ideal measure. Americans listen to a lot of music, and we can recognize the genre of a given song after listening for less than a second. We also recognize the racial stereotypes associated with different genres, even if we ourselves don’t conform to those stereotypes. Taken together, music preferences might tell us a lot about how people think about race.

Surveying music genre preferences and political attitudes

To find out, I conducted four surveys from 2019-2021, including about 2000 total participants. For this initial research I focused on the attitudes of white Americans toward Black Americans, but future research should include other groups as well as other types of music. I asked participants how much they liked ten different genres – five that are stereotypically associated with white culture (classical, country, rock, metal, and bluegrass), and five that are stereotypically associated with Black culture (jazz, rap, R&B, reggae, and disco). I then made a music preference measure by comparing participants’ average ratings across the two categories. To be clear, the measure doesn’t label participants as ‘more racist’ if they like country or don’t like rap. Instead, it simply assigns a score based on consistent preferences across all genres. The next step is seeing whether those genre preferences are associated with people’s political attitudes – and how they compare to other racial attitude measures.

Photo by FPVmat A on Unsplash

Participants saw either one or several racial attitude measures: my genre preference measure, a ‘stereotyping’ measure that asks blunt questions about whether Black and white Americans are ‘lazy’ or ‘violent,’ and a ‘racial resentment’ measure that is widely used but some have criticized as containing too much political content. All participants were also asked about a wide range of political issues, including issues closely tied to race and issues that have little to do with race, as well as questions about their personality and what they thought about the study. The results showed that how you measure racial attitudes can have a big impact on how we understand them – and that genre preference is in many ways one of the better measures you can use.

Music preferences are linked to attitudes about race

First, genre preference predicted people’s attitudes about racial issues, but not other political issues. Meanwhile racial resentment and stereotyping predicted all political attitudes, including those that seem to have little to do with race. Racial resentment was also strongly affected by people’s concern about being judged, while genre preference was unaffected. Most participants who answered the genre preference questions didn’t even think the study had anything to do with race, which might be why they were less likely to be affected by social judgment concerns. In all three cases, genre preference performed as well or better than the other, more established measures.

The genre preference measure is still being developed – the next step is to see how well it works for others groups of people, other countries, and other kinds of music. But for now, it’s a useful tool to measure racial attitudes and understand how they affect our politics. If you’re a social scientist, I strongly encourage you to use genre preference in your own projects – and I have a page on my website to help you get started. If you’re more of an interested layman, genre preference provides a case study for how our preferences and social lives can be tied back to politics, even if we don’t realize it. The next time you’re switching radio stations or scrolling through Spotify, maybe take a second to think about what your music might say about you. You might find yourself wanting to listen to something new!


About the author

Brianna A. Smith

Brianna A. Smith is an associate professor of Political Science at the United States Naval Academy. Their research focuses on the impact of threat and anxiety on political attitudes, as well as survey methodology and measurement. The views expressed in this article are those of the author, and do not represent the views of the United States Navy or the Department of Defense.

Posted In: Democracy and culture

Leave a Reply

Your email address will not be published. Required fields are marked *

LSE Review of Books Visit our sister blog: British Politics and Policy at LSE

RSS Latest LSE Events podcasts

This work by LSE USAPP blog is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported.