GENEWATCH
 
A LESSON IN RACE, GENES, AND IQ
By Peter Taylor
 

"Some people suggest that race is coded in genes and genes determine IQ test scores. A slightly less simple but similar supposition is that differences among races are associated with differences in genes that people have, which, in turn, are associated with differences in IQ test scores. Yet everyone has a sense that such claims are controversial. What should you think about them?"

With this introduction I kicked off an interactive presentation to high school students visiting the exhibit "Race: Are We So Different" at the Museum of Science in Boston in 2011. In preparing the talk I had been concerned that the efforts of many critics to counter claims that link race, genes, and IQ test scores were too easily discounted by people entertaining the hypothetical: "Suppose that one day advances in genetics show direct links..." So I wanted not to assert from a position of professorial authority that this or that scientist was wrong about the facts or interpretations. I sought instead to render simple direct relationships implausible and to provide angles of critical questioning that would help students respond to any new facts that might emerge in the future. In this spirit, the presentation started with the introduction above, announced the take-home lesson - "The world is not that simple" - then moved through the script reproduced below. I do not have data to show how successful I was, so let me suggest that readers evaluate the educational approach for themselves by formulating their own answers at each step. At the end, see whether you have a clearer sense of why it is implausible that race, genes, and IQ test scores can be linked in any direct fashion.

Two preliminaries: Firsly, "IQ test scores" is used where most commentators use the shorthand "IQ." To avoid any connotation that the data concern intelligence, I wanted to remind students that the data are about scores on some test, no more than that. Secondly, a single schematic of the different data is used, but the actual data are not so different and support the conceptual points being made.1

The Lesson

In this presentation, I want to get you to think like a scientist: Ask questions. Put forward explanations. Evaluate whether they fit the data. Debate alternatives.

Start with these data [see image at right].

(I won't tell you yet what groups 1 and 2 are, but you would know if you were in them.)

Notice that the average of Group 2 is quite a bit higher than that for Group 1. What would you make of these patterns if you were in Group 1? In Group 2? Also think about how your answer might be different if you know that you are near the bottom, middle or top of the group.

First lesson: Individuals in groups differ from the group average and should not be treated as if the group average is what they are.

Second lesson: Science is more than getting at causes.

Already, you [in the audience responses] were talking about what you would do and what more you would want to know (e.g., is the IQ test biased towards Group 1?). So let me highlight the two interlinked questions that will run through the presentation:

1. What would you do on the basis of these patterns?  (E.g., a community leader in Group 1 might push for better schools or get depressed because Group 2 will stay ahead.)

2. What more would you want to know about these patterns before you decided what to do? (E.g., an IQ researcher might work with a geneticist to look for genes that Group 2 have that Group 1 does not.)

Now imagine you are.... [Students looked at the card each had been given that assigned them to one of these roles: a community leader in Group 1, community leader in Group 2, teacher of children from both groups, government policy-maker, genetics researcher, or IQ researcher]. How would you react to these patterns in IQ test scores - specifically, how would you answer questions 1 or 2 above?

What would you do on the basis of these patterns: We already have some examples from a Group 1 community leader. In addition, a government policy-maker might accept income inequality because it comes from IQ inequality. A teacher might make more effort to teach people in Group 1.

What more would you want to know about these patterns before you decided what to do: A government policy-maker might look for situations in which Group 1 and Group 2 are more equal and learn from that. An IQ researcher might work with a geneticist to look for genes that Group 2 have that Group 1 does not have.

Stop for a moment. Why would an IQ researcher ask a geneticist to look for genes that Group 2 have that Group 1 does not? Well, their reasoning might be:

Because there is variation within each group and genes are involved in variation of other traits, e.g., height.

And the gap has been there for a while in the USA and has not changed much.

And there is no simple environmental or social factor that explains the gap.

And what are the alternatives?

If that is what they are thinking, consider the results of a study from France:

New information:
Group 1 = people who were adopted by poor families.
Group 2 = their brothers and sisters who were adopted by well-off families.


Perhaps the IQ researcher should ask a social scientist to look for social conditions that Group 2 have that Group 1 does not.

But that is too simple. Indeed, it is too simple even to say it must be a combination of genes and environment so both the geneticist and the social scientist should look, respectively, for genes and social conditions. To see why, consider results that are common across many industrialized countries:

New information:
Group 1 is your grandparents' generation.
Group 2 is your parents' generation.


What would you now do on the basis of these patterns?

OR

What more would you now want to know about these patterns before you decided what to do?

 

It turns out there is no simple environmental or social factor that explains the increase.

Would we then look for genes to explain this increase? Recall the line of reasoning used by the IQ researcher in asking a geneticist to look for genes:

There is variation within each group and genes are involved in variation of other traits, e.g., height.

And the gap has been there in many countries.

And there is no simple environmental or social factor that explains the increase.

And what are the alternatives?

But we know that genes do not change much from one generation to the next, so there must be something wrong in the logic for explaining the gap between groups. There must be alternative explanations. To develop them, we need to think about more dynamic explanations.

[Here we discussed what Flynn (2007) and his collaborator Dickens say about basketball in the age of TV to convey a model in which there is a matching of environments to differences that may initially be small (e.g., children who show an earlier interest in reading will be more likely to be given books and receive encouragement for their reading and book learning), and a social multiplier through which society's average level for the attribute in question influences the environment of the individual (e.g., if people grow up and are educated with others who, on average, have higher IQ test scores, this will stimulate their own development).]

We now have a sense that more dynamic explanations are needed, that genes versus environment - nature versus nurture - is too simple. So now turn to a last form of Group 1-2 differences:

New information:
Group 1 are African-Americans in the USA.
Group 2 are Euro-Americans ("whites") in the USA.


What would you now do on the basis of these patterns?

OR

What more would you now want to know about these patterns before you decided what to do?

Why propose that genes could - if not now, then some day - explain the differences in averages between the two groups? After all, we have seen that differences in generations are associated with differences in average IQ test scores, but these cannot be associated with differences in genes.

Realizing this takes away the plausibility of proposing that differences in races are associated with differences in average IQ test scores because both are associated with differences in genes.

(If this last proposal is still plausible to you despite generational differences not being different genetically, ask yourself if factors outside the data are influencing your thinking.)

Third lesson: The world is not a simple matter of genes eventually explaining anything and everything living. Be skeptical of anyone who wants you to think it could be simple. (They are not being true to the science of average group differences.)  Ask questions - dig deeper into the complexity, looking for dynamic explanations.

In the meantime, when thinking about what would you do on the basis of any patterns resulting from statistical comparison of groups, remember also the first lesson: Individuals in groups differ from the group average and should not be treated as if the group average is what they are. nnn

 

Peter Taylor, PhD,is Professor of Critical & Creative Thinking at the University of Massachusetts Boston, and is director of the Science in a Changing World graduate track.

 

ENDNOTES

1. For an accessible entry-point, see Flynn, J. R. (2007) What is intelligence? Cambridge University Press.

 
 
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