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Fairness According to Whom? Divergent Perceptions of Fairness among White and Black Americans and Its Effect on Trade Attitudes

Published online by Cambridge University Press:  14 February 2025

DANIEL LOBO*
Affiliation:
University of California, Berkeley, United States
RYAN BRUTGER*
Affiliation:
University of California, Berkeley, United States
*
Corresponding author: Daniel Lobo, PhD Student, Department of Sociology, University of California, Berkeley, United States, daniel_lobo@berkeley.edu.
Ryan Brutger, Associate Professor, Department of Political Science, University of California, Berkeley, United States, brutger@berkeley.edu.
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Abstract

Racial divides in American attitudes toward trade are often explained by labor market discrimination and traits like nationalism. However, recent research shows that perceptions of fairness, particularly “asymmetric fairness” concerns about “falling behind” other countries, significantly shape these attitudes. We theorize that linking these perspectives offers new insights. Drawing on critical race theory and cognitive psychology, we theorize that Black Americans, unlike their white counterparts, do not view trade through the lens of asymmetric fairness. Since Black Americans have not benefited from the same social, economic, and political privileges, they are less concerned with “falling behind” and instead focus on fairness as equality. This leads them to evaluate trade agreements through a “principled fairness” lens, contributing to support for trade policies that benefit both the home and foreign country, as opposed to prioritizing an “America First” trade agenda. We test this theory in a national survey experiment and find strong support.

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Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of American Political Science Association
Figure 0

Table 1. OLS Regression of Fairness Assessment on Equal and Favorable Treatment Conditions and Race

Figure 1

Figure 1. Fairness Evaluations of White and Black RespondentsNote: Figure displays the average fairness score by treatment type, measured from −2 (Very Unfair) to 2 (Very Fair), with 95% confidence intervals. Higher values represent greater perceived fairness of the trade agreement. The results are divided based on whether respondents identified as white or Black.

Figure 2

Figure 2. Support for Trade Agreement of White and Black RespondentsNote: Figure displays the average support score by treatment type, measured from −2 (Strongly Oppose) to 2 (Strongly Support), with 95% confidence intervals. Higher values represent greater levels of support for the trade agreement. The results are divided based on whether respondents identified as white or Black.

Figure 3

Figure 3. Support for Trade Agreement of White and Black RespondentsNote: Figure displays the ACME, ADE, and total effect of the favorable treatment compared to the unfavorable baseline condition. Perceived fairness is the mediator and support for the trade agreement is the dependent variable, measured from −2 (Strongly Oppose) to 2 (Strongly Support), with 95% confidence intervals. Higher values represent greater levels of support for the trade agreement. The results are divided based on whether respondents identified as white or Black.

Figure 4

Table 2. OLS Regression of Fairness Assessment on Equal and Favorable Treatment Conditions and Race, Controlling for Nationalism

Figure 5

Table 3. OLS Regression of Fairness Assessment of White Respondents by Partisanship and Ideology

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