Racism (29): A Natural or An Acquired Vice?

We now have strong evidence that human evolution has produced natural tendencies to favor members of the same group and to distrust and disadvantage outsiders. Insider-outsiders distinctions seem to be innate. This is the consequence of the substantial benefits of group solidarity in early human evolution, and we still live with it today.

Psychologist Catherine Cottrell at the University of Florida and her colleague Steven Neuberg at Arizona State University, argue that human prejudice evolved as a function of group living. Joining together in groups allowed humans to gain access to resources necessary for survival including food, water, and shelter. Groups also offered numerous advantages, such as making it easier to find a mate, care for children, and receive protection from others. However, group living also made us more wary of outsiders who could potentially harm the group by spreading disease, killing or hurting individuals, or stealing precious resources. To protect ourselves, we developed ways of identifying who belongs to our group and who doesn’t. Over time, this process of quickly evaluating others might have become so streamlined that it became unconscious. (source)

So, to some extent, our brains are wired for bias. Even the most liberal among us show some level of implicit bias when tested for it. All we can do is try to be aware of our prejudices as much as possible, and then correct for them.

Some want to extrapolate from these relatively uncontroversial findings and argue that racism as well is innate, even though racism is a relatively recent phenomenon unknown to early humans who almost never met members of other races.

Those who argue that racism is a natural tendency can appeal to certain findings to back up their claims. Studies have found that when whites see black faces there is increased activity in the amygdala, a brain structure associated with emotion and, specifically, with the detection of threats (source).

The problem with this sort of argument is that a biological fact doesn’t have to be innate. In fact, in this case, it has been shown that the detected brain reaction – a biological fact – does not occur in young people:

In a paper that will be published in the Journal of Cognitive Neuroscience, Eva Telzer of UCLA and three other researchers report that they’ve performed these amygdala studies–which had previously been done on adults–on children. And they found something interesting: the racial sensitivity of the amygdala doesn’t kick in until around age 14. What’s more: once it kicks in, it doesn’t kick in equally for everybody. The more racially diverse your peer group, the less strong the amygdala effect. At really high levels of diversity, the effect disappeared entirely. The authors of the study write that ”these findings suggest that neural biases to race are not innate and that race is a social construction, learned over time.” (source)

In a sense, this is good news, because it means that people can be taught not to be racist, even if we can’t be taught to be completely unprejudiced.

More on race as a social construction is here. More posts in this series are here.

Measuring Human Rights (24): Measuring Racism, Ctd.

Measuring racism is a problem, as I’ve argued before. Asking people if they’re racist won’t work because they don’t answer this question correctly, and understandably so. This is due to the social desirability bias. Surveys may minimize this bias if they approach the subject indirectly. For example, rather than simply asking people if they are racist or if they believe blacks are inferior, surveys could ask some of the following questions:

  • Do you believe God has created the races separately?
  • What do you believe are the reasons for higher incarceration rates/lower IQ scores/… among blacks?
  • Etc.

Still, no guarantee that bias won’t falsify the results. Maybe it’s better to dump the survey method altogether and go for something even more indirect. For example, you can measure

  • racism in employment decisions, such as numbers of callbacks received by applicants with black sounding names
  • racism in criminal justice, for example the degree to which black federal lower-court judges are overturned more often than cases authored by similar white judges, or differences in crime rates by race of the perpetrator, or jury behavior
  • racial profiling
  • residential racial segregation
  • racist consumer behavior, e.g. reluctance to buy something from a black seller
  • the numbers of interracial marriages
  • the numbers and membership of hate groups
  • the number of hate crimes
  • etc.

A disadvantage of many of these indirect measurements is that they don’t necessarily reflect the beliefs of the whole population. You can’t just extrapolate the rates you find in these measurements. It’s not because some judges and police officers are racist that the same rate of the total population is racist. Not all people who live in predominantly white neighborhoods do so because they don’t want to live in mixed neighborhoods. Different crime rates by race can be an indicator of racist law enforcement, but can also hide other causes, such as different poverty rates by race (which can themselves be indicators of racism). Higher numbers of hate crimes or hate groups may represent a radicalization of an increasingly small minority. And so on.

Another alternative measurement system is the Implicit Association Test. This is a psychological test that measures implicit attitudes and beliefs that people are either unwilling or unable to report.

Because the IAT requires that users make a series of rapid judgments, researchers believe that IAT scores may reflect attitudes which people are unwilling to reveal publicly. (source)

Participants in an IAT are asked to rapidly decide which words are associated. For example, is “female” or “male” associated with “family” and “career” respectively? This way, you can measure the strength of association between mental constructs such as “female” or “male” on the one hand and attributes such as “family” or “career” on the other. And this allows you to detect prejudice. The same is true for racism. You can read here or here how an IAT is usually performed.

Yet another measurement system uses evidence from Google search data, such as in this example. The advantage of this system is that it avoids the social desirability bias, since Google searches are done alone and online and without prior knowledge of the fact that the search results will be used to measure racism. Hence, people searching on Google are more likely to express social taboos. In this respect, the measurement system is similar to the IAT. Another advantage of the Google method, compared to traditional surveys, is that the Google sample is very large and more or less evenly distributed across all areas of a country. This allows for some fine grained geographical breakdown of racial animus.

More specifically, the purpose of the Google method is to analyze trends in searches that include words like “nigger” or “niggers” (not “nigga” because that’s slang in some Black communities, and not necessarily a disparaging term). In order to avoid searches for the term “nigger” by people who may not be racially motivated – such as researchers (Google can’t tell the difference) – you could refine the method and analyze only searches for phrases like “why are niggers lazy”, “Obama+nigger”, “niggers/blacks+apes” etc. If you find that those searches are more common in some locations than others, or that they become more common in some locations, then you can try to correlate those findings with other, existing indicators of racism such as those cited above, or with historic indicators such as prevalence of slavery or lynchings.

More posts in this series are here.