Drawing on the slate of human nature

Some of you have been reading me since 2002. Therefore, you’ve seen a lot of changes in my interests (and to a lesser extent, my life…no more cat pictures because my cats died). Whereas today I incessantly flog Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past, in 2002 I would talk about Steven Pinker’s The Blank Slate: The Modern Denial of Human Nature quite a bit. The reason I don’t talk much about The Blank Slate is that some point in the 2000s I realized my future deep interests were going to be in population genetics, rather than behavior genetics and cognitive psychology. If you are not a specialist who doesn’t follow the literature. Who doesn’t “read the supplements”. You’re going to stop gaining anything more from books at a certain point.

Similarly, after I read In Gods We Trust: The Evolutionary Landscape of Religion, I read a lot of books on the cognitive anthropology of religion. Until I didn’t. Now that Harvey Whitehouse has teamed up with Peter Turchin, I suspect I’ll check in on this literature again.

But life comes at you fast. Today I think the broad thesis of The Blank Slate seems so correct, that we are not a “blank slate”, that no one would argue with that. Rather, the implications of that thesis are highly “problematic,” and social and cultural constructionism has really gone much further on the Left operationally than they were in the early 2000s. To give a concrete example, you can admit that sex differences are real and significant, but you have to be very careful in mentioning or highlighting specific instances or cases where they matter.

Moving to a more controversial topic, for a long while I’ve pretty much ignored the genomic study of the normal variation of cognition. The reason is that until recently all the studies were very underpowered to detect much of anything. The sample sizes were too small in relation to the genetic architecture of the trait because of the “Fourth Law of Behavior Genetics.”

As 2018 proceeds I think we can say that we are now in new territory. On Twitter, Steve Hsu seems positively ecstatic over a paper that just came out in PNAS. His blog post, Game Over: Genomic Prediction of Social Mobility summarizes it pretty well, but you should read the open access paper.

Genetic analysis of social-class mobility in five longitudinal studies:

Genome-wide association study (GWAS) discoveries about educational attainment have raised questions about the meaning of the genetics of success. These discoveries could offer clues about biological mechanisms or, because children inherit genetics and social class from parents, education-linked genetics could be spurious correlates of socially transmitted advantages. To distinguish between these hypotheses, we studied social mobility in five cohorts from three countries. We found that people with more education-linked genetics were more successful compared with parents and siblings. We also found mothers’ education-linked genetics predicted their children’s attainment over and above the children’s own genetics, indicating an environmentally mediated genetic effect. Findings reject pure social-transmission explanations of education GWAS discoveries. Instead, genetics influences attainment directly through social mobility and indirectly through family environments.

Why does this matter? I’m assuming most of you have seen charts like the ones below, which “prove” how the game is rigged against the poor:

The problem that most behavior geneticists immediately have with these popular analyses, which now suffuse our public culture (e.g., the “representation” argument in academic science often takes as a cartoonish model that all groups will have equal representation in all fields given no discrimination; substantively almost everyone believes this isn’t true in some way, but for the sake of argumentation this is a bullet-proof line of attack which every white male academic is going to retreat away from), is that they ignore genetic confounds. This paper is an attempt to address that. Measure it. Quantify it. Characterize it.

The two most interesting results for me have to do with siblings and mothers. Unsurprisingly siblings who have a higher predicted educational attainment score genetically tend to have higher educational attainments. As you know, siblings vary in relatedness. They vary in the segregation of alleles from their parents. Some siblings are tall. Some are short. This is due to variation in genetics across the pedigree. People within a family are related to each other, but unless you are talking Targaryens they aren’t exactly alike. Similarly, some siblings are smart and some are not so smart, because they’re “born that way.”

We knew that. Soon we’ll understand that genomically I suspect.

Second, we see again the importance of maternal effects and non-transmitted alleles. Mothers who have a higher predicted level of education have children with more education even if those children don’t inherit those alleles.* One natural conclusion here is mothers with a particular disposition shaped by genes are creating particular environments for their children, and those environments let them flourish even if they do not have their mother’s genetic endowments. This actually has “news you can use” implications in life choices people make in relation to their partners.

The study ends on a cautionary note. Residual population substructure can cause issues, correcting which can attenuate or eliminate such subtle and small signals. The sample sizes could always get bigger. And ethnically diverse panels have to come into the picture at some point.

But Razib abides. This study had a combined sample size of >20,000 individuals. Then you have the other recent paper with 270,000 individuals, Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. All well and good, but I wait for greater things. There is no shame in waiting for better things. And I prophesy that a greater sample size shall come to pass before this year turns into the new.

And you know what’s better than 1 million samples? How about 1 billion samples!

* Note that the models are controlling for a lot of background socioeconomic variables.

The GRE is useful; range restriction is a thing

The above figure is from Beyond the Threshold Hypothesis: Even Among the Gifted and Top Math/Science Graduate Students, Cognitive Abilities, Vocational Interests, and Lifestyle Preferences Matter for Career Choice, Performance, and Persistence. It shows that even at very high levels of attainment on standardized tests there are differences in life outcome based on variation. The old joke is that results on intelligence tests don’t matter beyond a certain point…that point being whatever your own position is! But these results show that mathematics SAT outcomes at age 13 can still predict a lot of things across a wide range.

From personal experience people outside of psychology are pretty unaware of the power of cognitive aptitude testing. This includes many biologists. I was reminded of the above figure as I read portions of Richard Haier’s The Neuroscience of Intelligence. If you are a biologist curious about the topic, this is a highly recommended book.

The main reason I am posting this is because a friend in academia suggested it might be useful. There has recently been a backlash against the GRE exam, with support from the highest echelons of the science media. Additionally, many researchers in public forums are expressing objections to the GRE very vocally. Naturally this has resulted in counterarguments…but respondents have to be very careful how the couch their disagreement, because they fear being accused of being racist, sex, or classist. Such accusations might trigger social media mobs, which no one wants to be the target of (and if past experience is any guide, friends and colleagues will stand aside while the witch is virtually burned, hoping to avoid notice).

Because of the request above I finally decided to look at the two papers which are eliciting the current wave of GRE-skepticism, The Limitations of the GRE in Predicting Success in Biomedical Graduate School and Predictors of Student Productivity in Biomedical Graduate School Applications. To my eye they suffer from the same problem as all earlier criticisms: range restriction.

The issue is that if a university is using the GRE and other metrics well as filters for those admitted then there shouldn’t be that much variation to be left to be explained by those measures (the outcome being publications or some other important metric which actually leads to the production of science, as opposed to test scores and grades). The two papers above look at those admitted to biomedical programs at UNC and Vanderbilt, while another study looked at UCSF. These are all universities with standards high enough that there are either explicit or implicit cut-off scores so that many students are removed from the applicant pool immediately (the mean scores are well above the 50th percentile, you can see them in the paper yourself).

When I was in graduate school I was on a fellowship committee for several years, and I had access to GRE scores and grades. But I didn’t really pay much attention to them because there wasn’t that much range. And to be honest if the student was beyond their first year I didn’t look at all as time went on. In contrast, I did look really closely at the recommendations from their advisors. From talking to others on the committee this seemed typical. Once students were admitted they were judged based on how they were doing in graduate school. And how they were doing in graduate school had to do with research, not their graduate school GPA or what they scored on the GRE to get in.

As an empirical matter I do think that it is likely many universities will follow the University of Michigan in dropping the GRE as a requirement. There will be some resistance within academia, but there is a lot of reluctance to vocally defend the GRE in public, especially from younger faculty who fear the social and professional repercussions (every time a discussion pops up about the GRE I get a lot of Twitter DMs from people who believe in the utility of the GRE but don’t want to be seen defending it in public because they fear becoming the target of accusations of an -ism). My prediction is that after the GRE is gone people will simply rely on other proxies.

If the GRE is not required, but can be taken, then students who do well on the GRE will put that on their application. Sometimes strong students encounter tragedies in their undergraduate years which strongly impact their grade point averages, and very strong GREs can help show admissions committees that they can do the coursework despite their undergraduate record (I’m not positing a hypothetical, but recounting real individuals I’ve known of and seen). It seems cruel to deny these students the chance to submit their test scores. This means that those professors who believe the GRE is valid will show preference to students who take the test and have strong scores (and to be sure, many more care about the GRE when it means someone concretely joining their lab, as opposed to the abstraction of who gets admitted to the department).

More broadly, professors who are taking students will look more at proxies for GRE score, such as undergraduate institution, or the prestige of the people writing recommendation letters. That is, pedigree will matter a lot more. In some places, such as Britain, standardized testing emerged in part as a way to identify strong students from underprivileged backgrounds. These are not the type of students who would ever be able to present a prestigious letter of recommendation. This is a sort of student which still exists (often they are from non-academic backgrounds, being the first to graduate from college in their family; what they lack in polish they compensate for in aptitude, but that takes the right environment to express).

The recourse to other variables besides the GRE score will likely have mixed results at best. Consider the successful campaign to ban asking for job applicants’ criminal records. It turns out that just increased discrimination against all young black men, because employers could not longer differentiate. In general I think removing the GRE would probably hurt graduates of less prestigious state universities the most (and of course students from East Asia, who tend to have a comparative advantage on standardized tests). I’m pretty sure we’ll see, as the experiment will be run.

Addendum: There are professors at relatively prestigious research universities who had mediocre or sub-par GRE scores. We all know them. To some extent I think many of these individuals almost take pride in the fact that they accomplished so much in science despite negative feedback due to their unimpressive test scores. But remember that we’re talking about trends and averages, not deterministic predictions. Nothing in science is guaranteed, and even if you start at Harvard with undergraduate publications (not first author, but still) in Nature you may not make it that far (I’m thinking of a friend of mine, alas, who picked the wrong lab/project and couldn’t recover).

Applying intelligence to genes for intelligence

Carl Zimmer has an excellent write up on the new new Nature study of the variants associated with IQ, In ‘Enormous Success,’ Scientists Tie 52 Genes to Human Intelligence.

The issue with intelligence is that it’s a highly polygenic trait for which measurement is not always trivial. You need really large sample sizes. It’s about ten times less tractable than height as a quantitative trait. There are still many arguments about its genetic nature (though a majority position that it’s not rare variants of large effect seems to be emerging).

But all in good time.

Science is divided into many different fiefdoms, and people don’t always talk to each other. For example I know a fair number of population genomicists, and I know behavior geneticists who utilize quantitative genomic methods. The two are distinct and disparate groups. But the logic of cheap sequencing and big data is impacting both fields.

Unfortunately when you talk to population genomicists many are not familiar much with psychology, let alone psychometrics. When it comes to the behavior geneticists many come out of psychology backgrounds, so they are not conversant in aspects of genetic theory which harbor no utility for their tasks at hand. This leads to all sorts of problems, especially when journalists go to get comments from researchers who are really opining out of domain.

Some writers, such as Carl Zimmer, are very punctilious about the details. Getting things right. But we have to be cautious, because many journalists prefer a truth-themed story to the truth retold in a story format. And, some journalists are basically propagandists.

Over the next five years you will see many “gene and IQ” studies come out, with progressively greater and greater power. Read the write-ups in The New York TimesScience, and Nature. But to my many readers with technical skills this is what you should really do:

  1. pull down the data.
  2. re-analyze it.

My plain words are this: do not trust, and always verify.

I’m a big fan of people educating themselves on topics which they have opinions on (see: population genetics). If intelligence is of some interest to you, you should read some things. Arthur Jensen’s classic The g Factor: The Science of Mental Ability can be quite spendy (though used copies less so). But Stuart Ritchie’s Intelligence: All That Matters and Richard Haier’s The Neuroscience of Intelligence are both good, and cheaper and shorter. They hit all the basics which educated people should know if they want to talk about the topic of intelligence in an analytical way.