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JasonFletcherBackdoor to a Dead End: A Review Essay 1 The Genetic Lottery: Why DNA Matters for Social Equality by Kathryn Paige Harden

2022; Wiley; Volume: 48; Issue: 1 Linguagem: Inglês

10.1111/padr.12487

1728-4457

Jason M. Fletcher,

Cognitive Abilities and Testing

The social sciences have for more than half a century taken one of two stances on the importance of genetics for social science research—either aggressively denying that genetics matter or acknowledging genetics as a nuisance needing attention in order to get to the "real" social science questions. In the meantime, behavioral genetics has been ignored or treated as a joke by most social scientists (Goldberger 1979,22 Goldberger concludes that the central quantity in behavioral genetics, heritability: (p. 346): "On this assessment, heritability estimates serve no worthwhile purpose." ; Jencks 1980; Manski 2011). Kathryn Paige Harden's The Genetic Lottery: Why DNA Matters for Social Equality comes to this scene ready to battle for her discipline to be taken seriously in the analysis of social equality in the social sciences. This is not a book that aims for defensive retrenchment to fortify incremental gains from new genetic discoveries, but instead as an expansive, offensive campaign to secure additional space in social science and policy spheres. Not only do genes matter for most of the individual-level outcomes of interest to social science, she says, but the joke is on us because genes matter for societal outcomes and processes like social equality—which has been the sole purview of social science and never an interest to behavioral genetics. It is through incorporating genetics into our work that we can solve previously intractable problems in our fields of study. The book attempts an incredible reversal, where the branch of social science arguably most deeply connected to racism and eugenics makes a pitch to be central to some of social science's key preoccupations of social equality. Her book ends with a five-step program for anti-eugenic science, led by a behavioral geneticist. The book's main messages will appeal to a variety of researchers, many of whom are uninitiated into behavioral genetics. For many social scientists already working with genetic data, the book provides a desired cover for inevitable comments from colleagues that their work is racist-adjacent, if not eugenicist. But the laudable (and shared personal views from many researchers) social justice commitments in the book likely hide the many ways that the behavioral genetics tradition is largely incompatible with much social science research. Social scientists, who focus so much on taking seriously issues around modeling individual actions and choices, should note the lack of choice assumed in behavioral genetics, whose central mission is to partition outcome variance into "genetic" and "nongenetic" sources. That is, the commonality in end goals around social equality between social scientists and the claims in the book should be tempered with the vastly different roads taken to arrive there. So, let us discuss the road traveled in the book. The central frame in the book is around the titular The Genetic Lottery. Indeed, confusingly, there are two "the's" at work, two frames for the lottery, that are often difficult to keep separate in the reader's mind. One frame is luck, which I think of as a corollary to "choose your parents wisely." You inherit your genes from your biological parents; the extent to which you inherit genes that do not cause disorder is, indeed, luck and something to be thankful for, and has all the attendant ethical implications around just deserts and a Rawlsian veil of ignorance. These sections of the book are useful and thoughtful, though will have less effect in the social sciences, as they are often presumed to be operant in much work around social equality.33 Sir Michael Marmot said in a discussion about the book that he did not need genomics to form his commitments to social equality and anti-eugenics; I suspect many social scientists will feel the same way. https://www.youtube.com/watch?v=L0SBiYqjJXU&t=3246s A second lottery frame is around leveraging genetic laws in narrow instances that can be used to produce causal evidence of the extent to which genes matter for social outcomes. Simply put, biological siblings have equal chances of inheriting each bit of genetic luck/misfortune, and thus comparing how their inherited genes shape their outcomes can be framed around a "genetic lottery" that can tease apart causality (Fletcher and Lehrer 2011). This is similar to the use of the Vietnam draft "lottery" to examine the causal effects of military service on later life outcomes, and many other "natural experiments."44 Of more interest to social scientists, would be a focused discussion around how the genetic lottery both limits analysis to within-family rather than between-family variation and also needs to consider the many issues with sibling analysis that are well discussed in social science circles but left unaddressed in the book. These are essentially SUTVA (stable unit treatment value assumption) violations and include sibling spillover effects, parental reactions to children, and others outlined in Boardman and Fletcher (2015); see also applications of polygenic scores in Fletcher et al. (2020, 2021). But now, we have two "lotteries" to manage when reading the book. The first is purely conceptual/ethical, and I believe already is taken for granted in social science around social equality. The second sets us up to be wowed by new evidence showcasing the need to include genetics, more generically, in all social science analysis, because of "big" causal effects on all outcomes we care about, especially those that generate social inequalities. However, here the book is incredibly underwhelming with actual new and compelling evidence (using the necessarily siblings designs above), instead relying mostly on sleights of hand and folk wisdom from behavioral genetics. But the book does not allow the lack of new genetic discoveries using sibling analysis to derail its mission. Instead, there is an aggressive, persistent bait and switch. The reader is told that differences in genetics between biological siblings are a "lottery"—in the Vietnam draft lottery sense—that can be used to demonstrate the causal effects of genetics on all the outcomes social science cares about. Indeed, children who share the same parents have equal opportunity in receiving the genetic variants they inherit, so comparing differences in the co-siblings' genes with their outcomes allows the conceptualization of a lottery and the induced causality that we covet. The use of siblings is essential here because genetic differences between you and me (two unrelated people) hold no special causal claims. However, it may shock you to confirm that nearly every paper55 I believe Belsky et al. (2018) is the single exception. and specific discovery reported in this book does not come from sibling analysis. Even though genetic lottery is the title of the book, the phrase is uttered nearly 40 times (lottery shows up an extra 21 times) in 250 pages. Even with major portions of chapters devoted to the importance of causal analysis, this book is mostly about non-(causal) lotteries dressed up as (causal) lotteries. Harden pursues this conflation of lotteries on page 31 when she outlines the fascinating combinatorics of sperm and egg mixing, noting that a pair of parents could produce over 70 trillion genetically unique offspring. Calling this a "Powerball" process where your DNA is "pure luck" attempts to confuse the reader between the sheer multiplicity of possible DNA combinations for a child born to two specific parents and a lottery used for causal analysis that compares two children born to the same parents who differ in their genetics by "luck" that is informative for causal analysis.66 "… in Powerball, the fact that you have your specific DNA sequence, out of all the possible DNA sequences that could have resulted from the union of your father and your mother, is pure luck. This is what I mean when I say that your genotype—your unique sequence of DNA—is the outcome of a genetic lottery" (Harden, 31). To further the Powerball analogy, though correctly: you and I are drawn from different urns—some lotto balls in your urn are not in mine and vice versa—but siblings are drawn from the same urn. Only the latter setting serves as a quasi-experiment with causal import. The problem is that nearly ever finding in the book does not use evidence from "pure luck" against a counter-factual outcome. But why do all this? Why set up a standard for demonstrating that genes matter and then cite tons of evidence that use different standards? The author helpfully provides the Rosetta Stone to this puzzle by writing (about non-behavior geneticists): "And people's definitions of the word ''cause'' are especially mercurial when the question at hand is whether genes can be causes. Poke in one direction or another, and people's definitions expand or contract, as need be, to encompass the things they want to embrace as causal and to evade others" (Harden, 96). The author is describing cases, similar to what I describe above, where researchers refuse to entertain the importance of genetic effects in their own work. But it also directly applies to the undercurrent of the whole book, where the author wants genes to be causal and essential for the practice of social science and policy and is willing to set any goal post that makes it so. My own view is that the past five years have demonstrated genes as contingent, of tiny individual effect, and as an exclusionary force against minority groups in social science and policy analysis.77 Much more can and should be said about how to read a book that focuses on social equality but features data/findings that exclude racial minorities. I hope other reviewers will explore this. Perhaps seeing this house of cards for what it is will allow social scientists to mostly go on as before—trying to more expertly understand genetics as mostly nuisance in social science research by continuing to fold them into our analysis in ways they can be useful. The studies that I have in mind are a waste because their research designs depend on correlating some aspects of a person's behavior or functioning with some aspect of the environment that is provided by a biological relative, such as a parent, without controlling for the fact that biological relatives can be expected to resemble each other just because they share genes. This methodical flaw would perhaps be excusable if these fields had a track record of rapid progress in the development of successful intervention programs to improve children's lives. But they don't. (Harden, 234) (Emphasis added) Here is the thing. The method used to discover every genetic effect reported in Harden's book suffers from the same methodological flaw of confounding that enrages the author so deeply in the quoted passage. If we switch the two underlined words in the quote, this would be a forceful critique of all current genome wide association studies, though I would not go so far as to then call them a "waste." My guess is that these revelations are a sufficient shield for many social scientists against the main tactics of this book's key points.88 Biological scientists have also raised very important concerns (Coop and Przeworski 2022); see also Martschenko (2021) The rest of the weapons, I believe, can be more easily absorbed in regular social science, because they already live here. A key point—and the link between genetics and social equality—is an expanded recapitulation of a truism that many social scientists take for granted, which is choose your parents wisely. The power and implications of this notion are vast and drive so much great social science research. This includes work directed at understanding how policies and people might intervene to undo the unfairness of being born in a disadvantaged family. To add a new ingredient to what is already by this point a well-digested meal in the social sciences, Harden attempts to split the choice of your parents into a "social" component and a "genetic" component—as if they are somehow two choices.99 "But there is another accident of birth that is also correlated with inequalities in adult outcomes: not the social conditions into which you are born, but the genes with which you are born" (Harden, 8). (Emphasis added.) In my mind, the main reason to pursue this unnatural division is not theoretical or empirical, but rhetorical. Knowing that nearly all of her evidence does not rely on siblings, the author needs to continue to invoke a "special" genetic lottery that differs from a social lottery of your parents. It is only in this context that the book can continue the construction of a purportedly essential and previously unarticulated road to get to social equality where a necessary pitstop is acceptance of the importance of genetic pathways to social science outcomes. Acceptance of the obvious truth that you inherit your parents' social and genetic advantages and disadvantages at the same lotto ball drawing is another indication that this book constructs an unnecessary detour. It is unnecessary because it includes only whites; it is unnecessary because of the need to focus on within family (and exclude between family) inequalities; it is unnecessary because there are no sentient humans on the road, only genes and environments. These negative responses to this book do not mean that I am unenthusiastic about the continuing integration of genetics with social science (Conley and Fletcher 2017, Boardman and Fletcher 2021). Indeed, I believe researchers who defend the position that genetics can be ignored are themselves asking to be considered as unserious, dogmatic scholars. However, my read on the current state of understanding in subfields of genetics that have direct relevance to the social science enterprise is a mix of disappointment and goalpost moving, which does give renewed assurance for the continued dominance of social science approaches, theories, and ideas. The specific advantages for integration are narrower and weaker than I thought a decade ago, but they do exist. First, attending to genetic factors, likely as primarily a nuisance, should continue and expand. Second, considering genetic factors—without interpreting their effects directly—as useful tools to reduce model variance or impute unmeasured factors continues to hold promise. Likewise, asking whether impacts of environmental and other factors vary with "genetic" measures could produce additional insights in future work. But what appears to be conclusive right now is that specific genetic variants have vanishingly small effects on the major set of outcomes we care about. Social science studies that include genetic measurements will continue to be obliged to exclude racial/ethnic minorities. Attempts at providing policy implications based on work with these caveats is premature at best, but likely much worse. Thus, the primary lens to examine social inequalities remains in the social sciences. Thanks to Alberto Palloni and Ben Domingue for helpful comments on earlier drafts.