"Not In Your Genome"
The New York Review of Books' critique of Conley's "The Social Genome" by Feldman and Riskin turns into the usual Jewish vs. WASP spat we've seen since Lewontin, Kamin, and Rose's "Not In Our Genes."
Dalton Conley is a professor of sociology at Princeton, who was kind of hardcore even for a sociology professor. From Wikipedia: “Conley gave his children unusual names for sociological reasons: he has a daughter named E and a son named Yo Xing Heyno Augustus Eisner Alexander Weiser Knuckles Jeremijenko-Conley.”
But, Conley did something unusual among academics interested in nature vs. nurture. He got a second Ph.D. in biology from NYU in 2014.
His expertise on both sides of the big divide is annoying to more conventional academics, as this review of his latest book, The Social Genome, in the New York Review of Books shows:
M.W. Feldman and Jessica Riskin
M.W. Feldman is the Burnet C. and Mildred Finley Wohlford Professor of Biology at Stanford and the founder and codirector of Stanford’s Center for Computational, Evolutionary and Human Genomics.
Jessica Riskin is the Frances and Charles Field Professor of History at Stanford. Her book The Power of Life: The Invention of Biology and the Revolutionary Science of Jean-Baptiste Lamarck was published this spring.
Generations of “sociobiologists” have tried and failed to argue that genetic analysis offers the key to understanding social inequality. A new book fares no better.
June 11, 2026 issue
Reviewed: The Social Genome: The New Science of Nature and Nurture by Dalton Conley
Norton, 292 pp., $29.99
It turns out that if you begin an assertion with “it turns out” and sprinkle it with statistics and acronyms—especially if it’s expressed in the passive voice and followed by a footnote—up to 83 percent of the variation in whether people buy it is explained by their SCI (science credulity index) and 78 percent by their BDS (baloney detection score).
Here’s how it works. “It turns out,” writes Dalton Conley, the Henry Putnam University Professor in Sociology at Princeton, in his new book The Social Genome, “that almost every trait that has been studied is at least partially influenced” by genetic differences, including “about 40 percent” of the variation in how far people advance in school. “For income,” he continues, “it’s 70 percent. For cognitive ability, 75 percent.” Turning to the footnote, we find no evidence but instead a further assertion that PGIs (“polygenic indices”)—statistical treatments of genetic variants—are “incredibly useful for studying the social world.”
The reviewers are shocked, shocked to hear that nature influences nurture (and vice-versa).
This is Conley’s central claim: that genetic analysis offers the key to understanding not just people’s biology but their social environment. To grasp what a PGI is, you need another acronym, GWAS, for “genome-wide association study.” …
Conley is a true believer in the power of the PGI. “We can take a saliva sample from a baby,” he writes, extract its DNA, calculate a PGI, and “predict that baby’s odds of completing college.” (He adds the caveat that the predictiveness of the PGI depends on the environment, and if the society changes, “all bets are off.” But this is trivially true and therefore not really a caveat, as we will see.) Elsewhere in The Social Genome he writes that PGIs “have become the FICO scores of human genetics” and declares that “the PGI, with its X-ray powers, has revealed the hidden logic of social life.”
According to Conley, a PGI is “a single number that summarize[s] a person’s genetic tendency for a particular disease or trait—for instance, blood pressure, height, or cognitive functioning.” But one of these things is not like the others. It’s easy to measure height and possible to measure blood pressure, though even in these cases there’s no causal pathway from DNA to trait, since height and blood pressure are highly polygenic, meaning that researchers have found minute correlations with thousands of regions of the DNA as well as epigenetic and environmental factors. “Cognitive functioning,” on the other hand, is difficult to define, let alone to measure.
How about if you are trying to predict who will subscribe to the highbrow New York Review of Books? I mean, it’s pretty weird that writers for the New York Review act like cognitive functioning is utterly impossible to measure when they almost all got measured repeatedly when young and did very well on tests.
And what percentage of regular readers of the NYRoB would score below 100 on an IQ test?
And yet throughout The Social Genome Conley assumes that nebulous personal qualities can be not only quantified as though they were straightforward physical characteristics but also correlated with genetic variants to predict the course of people’s lives.
Well, yeah, quantifying personal qualities has been a giant project in the human sciences for well over a century.
The evidence that polygenic scores have this kind of predictive power is between extremely weak and nonexistent. (In fact Conley’s assertion that genes can help predict a baby’s odds of completing college is apparently contradicted by his own research: a 2022 article on which he’s listed twenty-seventh of forty authors states that “the PGI cannot be used to meaningfully predict” an individual’s educational attainment.)
The study that the reviewers cite of 3 million individuals (mostly of European descent) found that about 75% of those who score in the top decile in PGI scores go on to college vs. about 25% of those in the lowest decile. On the other hand, PGI only accounted for about 12% to 16% of total variance, quite a bit less than would be expected from twin and adoption studies.
We shall see over the next decade or two or three how that is resolved.
And of course educational attainment is hardly determined solely by genes. For example, a 100 IQ white kid in New England is probably quite a bit more likely to go to college rather than join the military compared to a 100 IQ white kid in the coal-mining belt.
Scientists look at educational attainment a lot because it’s a checkbox on a huge variety of medical forms. And, whether trustworthy or not, they trust it more than asking people to guess their IQs. (And medical forms seldom include cognitive tests to avoid discouraging people in need of medical care.)
Statistical genetics hasn’t led to new understandings of diseases or medical therapies, as Conley acknowledges, and its validity remains unproven in the biomedical sciences.
In the social sciences, meanwhile, not only are the traits in question often difficult or impossible to define or measure; the correlations also have no demonstrated causal meaning. Conley twice repeats the familiar adage that “correlation is not causation.” You might find a statistically significant correlation between, say, a genetic variant that makes it difficult to metabolize alcohol, common in East Asian populations, and the use of chopsticks, but such a correlation would obviously be causally meaningless. (Conley even discusses an article titled “Beware the Chopsticks Gene.”)
But wouldn’t genetics that simply discourage you from becoming an alcoholic be of some potential life and social importance?
There was a life-long longitudinal study of Harvard students from around 1940 (JFK was one of the subjects). One of the big things it found was that among privileged kids born on third base, whether or not they became alcoholics was a huge factor in how their lives turned out.
Similarly, a lot of talented aboriginal individuals have struggled with binge drinking since their ancestors only became exposed to alcohol a limited number of generations ago.
And yet his book posits lots of hypothetical “pathways” connecting PGIs with cognitive and behavioral traits. The implication is that these contain causal mechanisms, but neither Conley nor anyone else has ever identified any.
We know a lot about genetic pathways that lower IQ, like many types of mental retardation. The genetic pathways that raise IQ are more complex, just as the blueprints that make your car work are more complicated than the dead battery that keeps your car from working right now.
In 2022 we reviewed another book that ascribes cognitive and behavioral traits to genetic causes.
Kathryn Paige Harden’s The Genetic Lottery, which I reviewed in 2021.
We think it’s important to confront these claims and the movement they represent, which Conley variously calls “sociogenomics,” “behavioral genetics (or BG as it is known),” “genoeconomics,” and “biosociology,” the last an inversion of the 1970s term “sociobiology.” This movement includes prominent faculty at elite universities and commands an increasingly wide audience. The Social Science Genetic Association Consortium, the main association for sociogenomics, founded in 2011, has grown into a multi-institution international collaboration that draws millions of dollars in grants and uses data from millions of people.
“Millions of dollars”!
Sounds pretty sinister!
A surge in the production of PGIs in recent years has led to their increasing prominence in popular writing and culture and their widening use outside research settings. For instance, in assisted reproduction, companies now offer to test embryos for PGIs that purportedly influence traits such as intelligence.
Well, how soon can we find out if these companies’ services work or not? Another 5 or 10 years for the children born from them to reach the age, around 8, at which IQ tests give pretty stable results?
Yet the claims of sociogenomics are dangerously misleading and essentially groundless. Its advocates use spurious scientism—an alphabet soup of acronyms and elaborate statistical practices that exploit vast, cheaply accessible genetic databases—to disguise social ideologies as scientific facts.
Feldman and Riskin seem pretty irate.
“Today, I am a self-proclaimed biosociologist,” Conley announces in chapter 3 of his book, but this wasn’t how he began. His dissertation in sociology, which he completed at Columbia in 1996, treated the “racial wealth gap” in relation to other social disparities. Later, however, he questioned his conclusions. “Perhaps,” he recalls thinking, “the parents’ assets, per se, didn’t drive a child’s success…but rather the underlying traits that led the parents to accumulate the assets.” He decided that he and other sociologists had been wrong when they “waved away the huge effects of genes.” From there he embarked on a quest to discover the genetic causes of “wealth accumulation,” which he aptly if puzzlingly likens to Ahab’s pursuit of Moby Dick.
To represent the relationship between genes and environment, Conley uses the metaphor of a Möbius strip. Imagine a twisted loop of paper that appears to have two surfaces, but if you trace either with your finger, you soon find yourself tracing the other, showing that there’s just one continuous surface. Genes and environment, Conley writes, are a Möbius-like continuum, because genes have different effects in different environments, while they also, he says, mold your social environment in various ways. They direct you toward genetically similar people. They send you to college or to a low-wage job in the service sector. They evoke certain treatment by your parents and teachers. They act within your family and friends, shaping their behavior toward you.
For many readers the claim that genetics affects social and economic success will carry a whiff of biological determinism in general and of scientific racism in particular. It has become standard in Conley’s field for authors to reassure readers on both counts. We needn’t worry that there’s a risk of scientific racism in sociogenomics, they argue, because their claims aren’t, for the moment, “portable.” Conley cautions that “PGIs have been developed and work within only a given ancestral population” and that “comparing PGIs across groups tells us nothing about genetic differences between those groups.” He also writes that it’s “fairly clear” that social causes such as Jim Crow and redlining were the “primary drivers of racial wealth gaps,” although elsewhere he says that in his dissertation he “overlooked” the importance of “pedigree” and that “genetics played a much bigger role in the lives of the children I studied than I had imagined.”
As for biological determinism more generally, Conley sometimes seems to avoid deterministic formulations, for instance by invoking “influences” rather than “causes.” He writes, for example, that society became more tolerant of homosexuality after “the discovery of the biological (read: genetic) influences on sexual orientation,” and he suggests the same might happen with addiction and depression once people understand that “genes influence important outcomes.” (The “gay gene” claims of the 1990s have been thoroughly debunked.)
Where are we at in 2026 with the causes of male exclusive homosexuality, anyway? …
Paywall here.
