People are pattern-seekers. When we observe patterns in the natural world we often seek a deeper explanation for them. An example of a pattern that has captured the attention of academics is the disparity between men and women in fields like mechanical engineering and pediatrics.
Culture is an obvious explanation for some disparities: if a wave of Irish immigrants to Boston joins fire departments, and Italians start restaurants, then we might expect that the next generation of Bostonians will contain a disproportionate number of Irish firefighters and Italian restaurant owners. Similarly, if low-skilled immigrants tend to work in jobs like construction and agriculture, we might expect to find a lot of low-skilled workers who move from Central America to the United States to work on construction sites and strawberry farms.
Another obvious way to explain divergent outcomes between groups is that some groups – ranging from races and sexes, to religions and political partisans – have been discriminated against or persecuted by others. In other words, members of some groups throughout history were not given the opportunity to show their true talents in some fields.
Historically, ethnic discrimination was the norm, not the exception. In fact, ethnic discrimination was almost certainly adaptive for our ancestors who had to decipher, however crudely, who to trust and who to shun. Discrimination often served the function of increasing trust within a group by preventing members of other groups from enjoying access to valuable social goods that took effort to produce and preserve.
Persistent Performance Gaps
When we want to explain performance gaps, the obvious places to start are culture, bias, and discrimination. But in the mid-to-late twentieth century nearly every Western country abolished discriminatory laws, and many also implemented affirmative action programs. Governments, universities, and private firms made active efforts to recruit traditionally persecuted minorities into schools and jobs to which they previously lacked full access.
Under these conditions, some groups improved their outcomes while others did not. Jews and Asians, in particular, have thrived in every Western country in which they are found, and in many cases, they make more money, commit fewer crimes, and attain higher levels of education than the majority group in the societies to which they have migrated.
Moreover, despite the tedious proclamations of politicians that women have a long way to go in Western countries, we are much closer to parity than many believe. The majority of college graduates are now women, and the pay gap between men and women is almost non-existent when we compare workers in the same occupation at the same level. (According to Harvard economist Claudia Golden, most pay gaps are due to choices made by men and women to work in different occupations based on personal interests: women who have children, for example, understandably prefer more flexible jobs, which often pay less.)
As explicit discrimination decreased, social scientists began proposing alternatives to explain remaining gaps. Two, in particular, became popular in the 1990s: stereotype threat and epigenetics. Stereotype threat (supposedly) occurs when people are asked to perform a task and then informed that, on average, members of their group are not especially good at that task. They then perform worse than they otherwise would have. Epigenetics refers to the fact that gene expression is influenced by extra-genomic factors. Some social scientists proposed that if genes can be expressed differently in different environments, perhaps stressful environments can lead some groups to perform more poorly than others by affecting gene expression.
But stereotype threat has turned out to be a spectacular failure in explaining achievement gaps. And epigenetics is unlikely to explain disparities like why Asians outperform Africans on math exams, and why Africans outperform Asians in sports that involve sprinting.
When the predictions generated by these explanations failed to pan out, many began to turn to invisible forces like “structural racism” and “implicit bias” to explain achievement gaps. One problem with these hypotheses (as they are often employed) is that they are impossible to falsify. In fact, that seems to be the point: if we can’t test the hypothesis that unconscious bias and structural racism explain achievement gaps, they become perfect candidates for an all-purpose explanation that can be held with the force of a religious dogma.
When we see an achievement gap, we can invoke bias without even thinking about alternatives, and dismiss as a “racist” or “sexist” anyone who proposes the hypothesis that biology plays a role in explaining some achievement gaps.
Of course, biases exist, and sometimes they are at odds with our explicit value judgments. In these cases, it’s worth spreading social norms that aim to combat unfair biases. But some biases are useful heuristics, and some stereotypes are rational generalizations, like the belief that we have a greater chance of being violently assaulted by a man than a woman, or that the next international chess champion is more likely to be Jewish than Eritrean. In these cases, it is arguably morally wrong to prevent ourselves from believing what the evidence suggests.
When we hear someone attribute achievement gaps to implicit bias or structural racism, an obvious question to ask is: What would count as evidence against your hypothesis?
Structural racism (or sexism) is such an amorphous term that it is hard to know how to analyze it. We might first look to government institutions and private firms and ask whether they have policies of discrimination. In some countries, government agencies and businesses alike have policies that explicitly discriminate against entire classes of people (for example, in Saudi Arabia a man’s testimony in court has twice the evidentiary value of a woman’s). But in many Western countries like the United States and Australia, discrimination on the basis of race, sex, and sexual orientation is explicitly forbidden by law. Affirmative action programs actually do allow employers to discriminate – but they typically discriminate against rather than in favor of men of Asian or European descent.
Of course, we might think that although laws forbid discrimination, implicit bias leads some people to unconsciously discriminate against potential employees and co-workers. Implicit bias is hard to test, but the best evidence we have so far suggests that even when implicit bias exists it does not affect behavior very much, if at all. Despite the weak evidence for implicit bias as an explanation for achievement gaps, many corporations, and educational institutions have diversity training programs aimed at combating its allegedly pernicious effects.
Similar claims can be made about “misogyny,” which is the new term for “sexism” coined by radical feminists who claim that even if most people don’t consciously discriminate against women, an unconscious hatred of women helps explain why men and women exhibit different characteristics, which lead to different outcomes.
Will those who cite implicit bias, structural racism, or internalized misogyny respond to the evidence against their claims? Or will they instead retreat to untestable claims couched in vague language which allows them to save their hypothesis no matter what scientists find?
Those of us who suspect biology plays a role in explaining some group differences do not deny the existence of bias, which is especially powerful in traditional societies that lack norms of toleration and laws that protect minorities. But we are skeptical that racism or sexism or other pernicious forms of bias can explain all of the gaps that we see. More importantly, our hypothesis is falsifiable. One way to falsify it would be to find that genes which influence physical and mental traits – including abilities and interests – are identically distributed across human groups.
If people want to search for the different causes of achievement gaps by proposing testable scientific hypotheses, we welcome them to the debate. But we are frustrated by the seemingly unfalsifiable nature of the hypotheses that are increasingly put forward to defend the view that all groups are the same, and that all indications of difference are evidence of evil.
Jonathan Anomaly is a core faculty member of the Department of Political Economy, and Assistant Professor in the PPEL Program, at the University of Arizona.