Published online by Cambridge University Press: 14 May 2019
Do people judge some forms of wage discrimination to be more unfair than others? We report an experiment in an online labor market in which participants were paid based on discriminatory rules. We test hypotheses about fairness based on procedural justice, divisiveness, and affective polarization between partisans. Workers transcribed text and then learned that they earned more or less money than other workers for doing the same job. We manipulated whether the unequal pay was based on their political party, eye color, or an arbitrary choice between two doors. Consistent with the divisiveness hypothesis, participants judged discriminatory pay to be less fair when it was based on a stable characteristic, political party, or eye color, compared to a transient choice (between doors). We find mixed evidence about how affective polarization exacerbates the unfairness of partisan discrimination. We discuss implications for the procedural justice of wage discrimination.
We thank John Hibbing, Vittorio Merola, and Alex Shaw for helpful comments. The data, code, and any additional materials required to replicate all analyses in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at: doi: https://doi.org/10.7910/DVN/GPRPZL. The authors declare no financial conflicts of interest with respect to this study.