Burt's target article oddly misses the important intellectual contribution of sociogenomics to our understanding of genetic evolution in contemporary human populations. Although social scientists' immediate research agendas are often not evolutionary in nature, I call for a better appreciation of the role of sociogenomics in answering important evolutionary questions.

Influences on social traits involve a tangled interplay of genetic, social, and environmental factors. Moreover, there is increasing awareness that gene–environment correlations are real and potentially measurable. Such gene–environment correlations can mislead if they are uncontrolled and genetic associations are interpreted as being purely because of direct genetic effects. This complexity is cause for more and better investigation, not a reason to refrain from researching one of the potentially important factors (genetics) influencing trait variation.

The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as “genetic propensities” for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents (...) argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene–environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d’être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications. (shrink)

It is a hotly contested issue whether polygenic scores should play a major role in the social sciences. Here, we defend a methodologically pluralist stance in which sociogenomics should abandon its hype and recognize that it suffers from all the methodological difficulties of the social sciences, yet nevertheless maintain an optimistic stance toward a more cautious use.

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often‐ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science—including genomewide association studies and polygenic indexes—can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. (...) SBG research that compares individuals within a group according to a “sensitive” phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk‐benefit profile. (shrink)

Burt formulates her critique at a general level of abstraction that highlights the methodological deficiencies of sociogenomics without also calling attention to precisely the same deficiencies in the social science model she seeks to defend against its encroachments. What might have been a methodological bulwark against the excesses of sociogenomics is instead a one-sided critique that merely renews its charter.

Burt's critique of using polygenic scores in social science conflates the “scientific costs” of sociogenomics with “sociopolitical and ethical” concerns. Furthermore, she paradoxically enlists recent advances in controlling for environmental confounding to argue such confounding is scientifically “intractable.” Disinterested social scientists should support ongoing efforts to improve this technology rather than obstructing progress and excusing genetically confounded research.

In discussing the relationship between genetically influenced differences and educational attainment (EA), Burt employs the concept of downward causation. I note the similarities between Burt's concept of downward causation and the sociogenomics concept of vertical pleiotropy and argue that her discussion of downward causation introduces an unnecessary normative component. The core problem concerns not the appropriateness of phenotypes that influence EA but mistaken assumptions about which phenotypes are being predicted.

We sympathize with many of the points Burt makes in challenging the value of genetics to advance our understanding of social science. Here, we discuss how recent reflections on epistemic validity in the behavioral sciences can further contribute to a reappraisal of the role of sociogenomics to explain and predict human traits, aptitudes, and achievement.