Tag: ethics

How conflating terminology helps racists validate their racism.

Somewhat related to a recent post of mine, I came across this troubling article in the NY Times by David Reich, a Harvard geneticist who seems to regularly be described as “eminent”, in which he argues that “it is simply no longer possible to ignore average genetic differences among ‘races.'” He seems to have positive intentions — he even begins the article by acknowledging that race is a social construct — and I have no doubt that his knowledge of genetics is lightyears beyond my own non-existent knowledge of that subject, but despite his intentions and knowledge in that field, he seems to not have consulted with social scientists at all. The crux of the issue is that he conflates “race” with “population”. Indeed, immediately after acknowledging that race is a social construct, he states the following:

The orthodoxy goes further, holding that we should be anxious about any research into genetic differences among populations.

He seems to be using the two terms as synonyms, or at the very least, he’s being careless enough with his use of the two that it appears that he’s using them as synonyms. I seriously doubt that there are any respected geneticists who would argue that genetic differences among populations do not exist, but that’s not at all the same as making an argument about whether genetic differences between races exist.

There are already two good responses to the article, one in BuzzFeed, co-signed by some 67 scientists, and another by sociologist Ann Morning, who also co-signed the BuzzFeed article. These do a pretty good job of explaining the problem with Reich’s article — although I think the BuzzFeed article would have been better if they had not attempted to comment on genetic findings as much — so I just want to talk about Reich’s example from his own research supposedly showing how race can be used productively to study genetics. Here’s the relevant quote from his article:

To get a sense of what modern genetic research into average biological differences across populations looks like, consider an example from my own work. Beginning around 2003, I began exploring whether the population mixture that has occurred in the last few hundred years in the Americas could be leveraged to find risk factors for prostate cancer, a disease that occurs 1.7 times more often in self-identified African-Americans than in self-identified European-Americans. This disparity had not been possible to explain based on dietary and environmental differences, suggesting that genetic factors might play a role.

Self-identified African-Americans turn out to derive, on average, about 80 percent of their genetic ancestry from enslaved Africans brought to America between the 16th and 19th centuries. My colleagues and I searched, in 1,597 African-American men with prostate cancer, for locations in the genome where the fraction of genes contributed by West African ancestors was larger than it was elsewhere in the genome. In 2006, we found exactly what we were looking for: a location in the genome with about 2.8 percent more African ancestry than the average.

When we looked in more detail, we found that this region contained at least seven independent risk factors for prostate cancer, all more common in West Africans. Our findings could fully account for the higher rate of prostate cancer in African-Americans than in European-Americans. We could conclude this because African-Americans who happen to have entirely European ancestry in this small section of their genomes had about the same risk for prostate cancer as random Europeans.

Reich offers this as an example of how using race as a variable can be fruitful, but I think what he really does is undermine his own argument. What he’s ultimately talking about here is not African-Americans, but people with a section of their genome matching that which was commonly found in people who lived in West Africa. This appears to be the population that’s relevant to his study, yet he insists on talking about his results in terms of a race instead, repeatedly referring to African-Americans, a culturally diverse group that’s too often treated as monolithic and who don’t even necessarily have this ancestry, a fact that Reich admits in this very passage.

The use of the label African-American in his explanation serves no explanatory purpose and in fact is not even very precise. What it does do is make it easy for racists to claim that some Harvard geneticist has validated their racism, and confuse laymen who aren’t versed in subtle terminology distinctions for referring to groups of people, which Reich himself doesn’t even seem to be versed in. He repeatedly describes these subjects as “self-identified”, which I assume he does in order to take responsibility for using the label out of his own hands, but as I explained in my previous post, this strategy offers no protection at all for people who would be hurt by the stereotypes that are generated when using social variables like race.

Indeed, my admittedly unscientific survey of Twitter has led me to what appear to be three types of reactions to the piece: 1) social scientists pointing out how irresponsible the article is, 2) geneticists mocking “soft scientists” and/or praising the article as a fantastically delicate treatment of a difficult topic, and 3) blatant, hardcore racists using the article as validation for their racism. (3) should be troubling enough to those in (2) to convince them to go talk to those in (1) about how to better deal with the social side of their research.

The importance of anonymizing groups under study.

It’s been a long time since I’ve written a post here, but I promise, there’s a good reason: I was finishing up my master’s thesis. However, now that it’s submitted, I can talk a bit about what I did.1

Because I made use of social network analysis to detect communities in the study, there was little motivation to class subjects by social variables like ethnic group, race, religion, etc. In fact, I wouldn’t have been able to do so if I wanted to, because I assembled the corpus from tweets sent by some 200k people. Ultimately, the only variable that I can call a social variable that I used was the number for the community to which the subject belonged.

The advantage of this situation is that I completed avoided imposing stereotypes on the subjects or minimizing the differences between their identities by avoiding classifying them with people from elsewhere. A typical example of the problem in sociolinguistics is the variable of race. Some celebrated studies, like Labov’s (1966) and Wolfram’s (1969), classified their subjects according to their races, so that one ends up identifying some as African-American, for example. Even if these subjects don’t live together nor interact, they inevitably end up being viewed as constituting a single group. From there, these groups’ diverse identities are minimized.

This problem has already been recognized in sociolinguistics, and several solutions have been proposed, mainly the implementation of the concept of communities of practice and more reliance on self-identification. For example, in Bucholtz’ (1999) study, she studied a group whose members she identified according to an activity: being a member of a club. Unfortunately, she applied a label to the member of this club; she called them “nerds”. This name links them to nerds from elsewhere, regardless of the differences between this group and other groups of nerds. She wasn’t able to avoid minimizing the identity of the group that she studied by the simple implementation of the concept of communities of practice. Likewise, Eckert (2000) relied on self-identification of her subjects as either “jock” or “burnout”, but one ends up with the same problem: even if the subjects self-identify, they can choose labels that link them to distant groups. Jocks surely exist elsewhere, but these others jocks can be exceptionally different from the jocks in Eckert’s study. So, one cannot avoid minimizing identities by the simple reliance on self-identification, either.

In my thesis, I identified communities simply with ID numbers, so I never classified the subjects with other groups to which they didn’t belong. The fact that I used social network analysis to automatically detect these communities allowed me to more easily avoid applying labels to the subjects that could minimize their identities, but this is possible in any study, even if the researcher employs classic social variables. In the same way that one anonymizes the identities of individuals, one can anonymize the identities of the groups under study. Why is it necessary to know that the races in a study are “black” and “white or that the religions are “Jewish” and “Catholic”? If a researcher is interested in the way that their subjects navigate stereotypes that are relevant to their lives, that’s one thing, but most variationist studies don’t take up this question, so most studies can do more to protect marginalized people.


1. For those who don’t know the topic of my thesis, I analyzed the use of the linguistic variable (lol), made up of lol, mdr, etc., on Twitter.


Bucholtz, M. (1999). “Why Be Normal?”: Language and Identity Practices in a Community of Nerd Girls. Language in Society, 28(2), 203–223. https://doi.org/10.1017/s0047404599002043

Eckert, P. (2000). Linguistic Variation as Social Practice: The Linguistic Construction of Identity in Belten High. Madlen, MA: Blackwell Publishers, Inc.

Labov, W. (2006). The Social Stratification of English in New York City (2nd ed.). Cambridge, England: Cambridge University Press. (Originally published in 1966)

Wolfram, W. (1969). A sociolinguistic description of Detroit negro speech. Washington, D.C: Center for Applied Linguistics.

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