We know that discrimination is common in organizations, in the economy, and in our social life. People are treated differently depending on a broad range of criteria, starting with race and gender, and there seems to be no form of training, qualification, or accomplishment that can help people escape discrimination. A classic example are Asian-Americans, who are a so-called “model minority” with a well-known taste for higher education. They suffer discrimination first through the accusation that they somehow do not deserve the education they have earned and then, more nastily, through violent attacks following the Covid-19 pandemic.
The fact of discrimination is well known, but the reasons are less clear – in part because there are too many explanations, and they contradict each other. Two well-known ones are taste discrimination and statistical discrimination. Taste discrimination is simple: people discriminate because they dislike, usually because others (parents? friends?) have told them who to dislike. Statistical discrimination is more complicated because the idea here is that some of those who are discriminated against should be assessed negatively, but it is hard to tell who, so the safe option is to discriminate against all. For example, an employer may think that some young women will get pregnant and quit soon and may decide that all young women should be thought of as short-term employees who do not need to be trained for promotion.
To many of us, statistical discrimination sounds like an excuse that may be true occasionally, but we assume most discrimination is based on cultural beliefs. But is that really so? Bryan Stroube has some interesting findings in research published in Administrative Science Quarterly. The findings were based on the discovery of transactions that offered reasons for statistical discrimination in one period, but these were removed later. In a peer-to-peer lending platform, there is always the concern that the loan may not be repaid, so statistical discrimination could be used to fund loans only to the most trusted social group. If the platform issues repayment guarantees, this motive for discrimination goes away. That is exactly what happened in the platform he studied.
So, what happened to the discrimination? This was a platform in China, where discrimination against women is common in economic arenas, even though women are thought to be reliable in paying back loans. You can probably suspect what happened. Women were discriminated against before the loan guarantee. After the loan guarantee, the economic security of women as lenders was no longer an issue, so women were even more strongly discriminated against.
Where does that leave the explanation of discrimination? Clearly people are capable of considering economic consequences and adjusting to them, and this affects the degree of discrimination. But at its core, discrimination is based on distaste and is culturally determined. Money is no excuse.
Stroube, Bryan K. 2021. Economic Consequences and the Motive to Discriminate. Administrative Science Quarterly, forthcoming.
This blog is devoted to discussions of how events in the news illustrate organizational research and can be explained by organizational theory. It is only updated when I have time to spare.