Jonathan Kaplan

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton’s conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton’s findings were, in fact, supported, and Gould’s analysis biased. We take strong exception to Lewis et al.’s thesis that Morton was “right.” We maintain that Gould was right to reject Morton’s analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the “populations” in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton’s confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.

It is illegitimate to read any ontology about "race" off of biological theory or data. Indeed, the technical meaning of "genetic variation" is fluid, and there is no single theoretical agreed-upon criterion for defining and distinguishing populations (or groups or clusters) given a particular set of genetic variation data. Thus, by analyzing three formal senses of "genetic variation"—diversity, differentiation, and heterozygosity—we argue that the use of biological theory for making epistemic claims about "race" can only seem plausible when it relies on the user’s own assumptions about race; the move from biological measures to claims about “race” inevitably amounts to a pernicious reification. We also excavate assumptions in the history of the technical discourse over the concept of "race" (e.g., Livingstone's and Dobzhansky's 1962 exchange, Edwards' 2003 response to Lewontin 1972, as well as contemporary discussions of cladistic "race", and "races" as clusters). We show that claims about the existence (or non-existence) of "race" are underdetermined by biological facts, methods, and theories. Biological theory does not force the concept of "race" upon us; our social discourse, social ontology, and social expectations do. We become prisoners of our abstractions at our own hands, and at our own expense.

We are addressing this letter to the editors of Philosophical Psychology after reading an article they decided to publish in the recent vol. 33, issue 1. The article is by Nathan Cofnas and is entitled “Research on group differences in intelligence: A defense of free inquiry” (2020). The purpose of our letter is not to invite Cofnas’s contribution into a broader dialogue, but to respectfully voice our concerns about the decision to publish the manuscript, which, in our opinion, fails to meet a range of academic quality standards usually expected of academic publications.

This paper distinguishes three concepts of "race": bio-genomic cluster/race, biological race, and social race. We map out realism, antirealism, and conventionalism about each of these, in three important historical episodes: Frank Livingstone and Theodosius Dobzhansky in 1962, A.W.F. Edwards' 2003 response to Lewontin (1972), and contemporary discourse. Semantics is especially crucial to the first episode, while normativity is central to the second. Upon inspection, each episode also reveals a variety of commitments to the metaphysics of race. We conclude by interrogating the relevance of these scientific discussions for political positions and a post-racial future.

Biological research on race has often been seen as motivated by or lending credence to underlying racist attitudes; in part for this reason, recently philosophers and biologists have gone through great pains to essentially deny the existence of biological human races. We argue that human races, in the biological sense of local populations adapted to particular environments, do in fact exist; such races are best understood through the common ecological concept of ecotypes. However, human ecotypic races do not in general correspond with 'folk' racial categories, largely because many similar ecotypes have multiple independent origins. Consequently, while human natural races exist, they have little or nothing in common with 'folk' races.

Twenty years have passed since Gould and Lewontin published their critique of ‘the adaptationist program’ – the tendency of some evolutionary biologists to assume, rather than demonstrate, the operation of natural selection. After the ‘Spandrels paper’, evolutionists were more careful about producing just-so stories based on selection, and paid more attention to a panoply of other processes. Then came reactions against the excesses of the anti-adaptationist movement, which ranged from a complete dismissal of Gould and Lewontin’s contribution to a positive call to overcome the problems. We now have an excellent opportunity for finally affirming a more balanced and pluralistic approach to the study of evolutionary biology.

We attempt to improve the understanding of the notion of agene being `for a phenotypic trait or traits. Considering theimplicit functional ascription of one thing being `for another,we submit a more restrictive version of `gene for talk.Accordingly, genes are only to be thought of as being forphenotypic traits when good evidence is available that thepresence or prevalence of the gene in a population is the resultof natural selection on that particular trait, and that theassociation between that trait and the gene in question isdemonstrably causal. It is therefore necessary to gatherstatistical, biochemical, historical, as well as ecologicalinformation before properly claiming that a gene is for aphenotypic trait. Instead of hampering practical use of the `genefor talk, our approach aims at stimulating much needed researchinto the functional ecology and comparative evolutionary biologyof gene action.

All eyes are turned towards genomic data and models as the source of knowledge about whether human races exist or not. Will genomic science make the final decision about whether racial realism (e.g., racial population naturalism) or anti-realism (e.g., racial skepticism) is correct? We think not. We believe that the results of even our best and most impressive genomic technologies underdetermine whether bio-genomic races exist, or not. First, different sub-disciplines of biology interested in population structure employ distinct concepts, aims, measures, and models, producing cross-cutting categorizations of population subdivisions rather than a single, universal bio-genomic concept of "race." Second, within each sub-discipline (e.g., conservation biology, phylogenetics), genomic results are consistent with, and map multiply to, racial realism and anti-realism. Indeed, racial ontologies are constructed conventionally, rather than discovered. We thus defend a /constructivist conventionalism/ about bio-genomic racial ontology. Choices and conventions must always be made in identifying particular kinds of groups. Political agendas, social programs, and moral questions premised on the existence of naturalistic race must accept that no scientifically grounded racial ontology is forthcoming, and adjust presumptions, practices, and projects accordingly.

Phylogenetic information is often necessary to distinguish between evolutionary scenarios. Recently, some prominent proponents of evolutionary psychology have acknowledged this, and have claimed that such evidence has in fact been brought to bear on adaptive hypotheses involving complex human psychological traits. Were this possible, it would be a valuable source of evidence regarding hypothesized adaptive traits in humans. However, the structure of the Hominidae family makes this difficult or impossible. For many traits of interest, the closest extant relatives to the human species are too phenotypically different from humans for such methods to provide meaningful data. While phylogenetic information can be useful for testing adaptive hypotheses in humans, these generally involve traits that are (a) not widely shared in the species or (b) fairly widely shared in the Hominidae family, and hence likely of a lower order of complexity than the sorts of traits evolutionary psychology has so far been interested in.

Some authors defending the “hereditarian” hypothesis with respect to differences in average IQ scores between populations have argued that the sorts of environmental variation hypothesized by some researchers rejecting the hereditarian position should leave discoverable statistical traces, namely changes in the overall variance of scores or in variance–covariance matrices relating scores to other variables. In this paper, I argue that the claims regarding the discoverability of such statistical signals are broadly mistaken—there is no good reason to suspect that the hypothesized environmental causes would leave detectable traces of the sorts suggested. As there remains no way to gather evidence that would permit the direct refutation of the environmental hypotheses, and no direct evidence for the hereditarian position, it remains the case, I argue, that the hereditarian position is unsupported by current evidence

Recently, Estes and Arnold claimed to have “solved” the paradox of evolutionary stasis; they claim that stabilizing selection, and only stabilizing selection, can explain the patterns of evolutionary divergence observed over “all timescales.” While Estes and Arnold clearly think that they have identified the processes that produce evolutionary stasis, they have not. Instead, Estes and Arnold identify a particular evolutionary pattern but not the processes that produce that pattern. This mistake is important; the slippage between pattern and process is common in population and quantitative genetics and contributes to a persistent misunderstanding of the nature of explanations in evolutionary biology. †To contact the author, please write to: Philosophy Department, 208 Hovland Hall, Oregon State University, Corvallis, OR 97331‐3902; e‐mail: [email protected].

Making Sense of Evolution explores contemporary evolutionary biology, focusing on the elements of theories—selection, adaptation, and species—that are complex and open to multiple possible interpretations, many of which are incompatible with one another and with other accepted practices in the discipline. Particular experimental methods, for example, may demand one understanding of “selection,” while the application of the same concept to another area of evolutionary biology could necessitate a very different definition.

The concepts of adaptive/fitness landscapes and adaptive peaks are a central part of much of contemporary evolutionary biology; the concepts are introduced in introductory texts, developed in more detail in graduate-level treatments, and are used extensively in papers published in the major journals in the field. The appeal of visualizing the process of evolution in terms of the movement of populations on such landscapes is very strong; as one becomes familiar with the metaphor, one often develops the feeling that it is possible to gain deep insights into evolution by thinking about the movement of populations on landscapes consisting of adaptive valleys and peaks. But, since Wright first introduced the metaphor in 1932, the metaphor has been the subject of persistent confusion, from equivocation over just what the features of the landscape are meant to represent to how we ought to expect the landscapes to look. Recent advances—conceptual, empirical, and computational—have pointed towards the inadequacy and indeed incoherence of the landscapes as usually pictured. I argue that attempts to reform the metaphor are misguided; it is time to give up the pictorial metaphor of the landscape entirely and rely instead on the results of formal modeling, however difficult such results are to understand in ‘intuitive’ terms.

Will a synthesis of developmental and evolutionary biology require a focus on the role of nongenetic resources in evolution? Nongenetic variation may exist but be hidden because the phenotypes are stable (developmentally canalized) under certain background conditions. In this case, those differences may come to play important roles in evolution when background conditions change. If this is so, then a focus on the way that developmental resources are made reliable, and the ways in which reliability fails, may prove to be of crucial importance to linking developmental and evolutionary biology. †To contact the author, please write to: 208 Hovland Hall, Philosophy Department, Oregon State University, Corvallis, OR 97331‐3902; e‐mail: [email protected].

Matthen (Philos Sci 76(4):464–487, 2009) argues that explanations of evolutionary change that appeal to natural selection are statistically abstractive explanations, explanations that ignore some possible explanatory partitions that in fact impact the outcome. This recognition highlights a difficulty with making selective analyses fully rigorous. Natural selection is not about the details of what happens to any particular organism, nor, by extension, to the details of what happens in any particular population. Since selective accounts focus on tendencies, those factors that impact the actual outcomes but do not impact the tendencies must be excluded. So, in order to properly exclude the factors irrelevant to selection, the relevant factors must be identified, and physical processes, environments, and populations individuated on the basis of being relevantly similar for the purposes of selective accounts. Natural selection, on this view, becomes in part a measure of the robustness of particular kinds of outcomes given variations over some kinds of inputs

This article is an introduction to the Synthese Special Issue, Philosophy of Epidemiology. The overall goals of the issue are to revisit the state of philosophy of epidemiology and to provide a forum for new voices, approaches, and perspectives in the philosophy of epidemiology literature. The introduction begins by drawing on Geoffrey Rose’s work on how to conceptualize and design interventions for populations, rather than individuals. It then goes on to highlight some themes that emerged in the articles that make up the issue: philosophy of epidemiology and epidemiological theory—what they are and what they ought to be, pluralism in measurement and causal attribution, epistemic and non-epistemic values in disputes epidemiological practices, decentering philosophy of epidemiology’s Eurocentrism, letting pragmatism guide uses of big data in epidemiology, and revisiting the lessons of classic texts in epidemiological causal inference. The introduction concludes with comments on a philosophy of epidemiology debate we see on, regarding the politics of philosophy of epidemiology.

In Understanding Evolution, Kostas Kampourakis has two related goals. The first is to demonstrate that there are conceptual hurdles to properly understanding evolutionary theory. Kampourakis argues that educators, and other promoters of evolutionary theory, have underestimated how difficult it is to understand evolutionary theory and have tended to treat some gaps in understanding that are in fact the result of conceptual difficulties as if they were instead the result of, e.g., religious intolerance to the theory. This, he thinks, is a mistake. Once we accept that there are aspects of evolutionary theory that are counterintuitive, and that a host of cognitive biases make accepting evolutionary biology difficult, we will be, he argues, in a better position to present compelling argument that can work against these biases. That is the second goal of the book—to present an explanation of contemporary evolutionary theory that is attentive to the ways in which the theory might seem problem ..

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.’s thesis that Morton was “right.” We maintain that Gould was right to reject Morton's analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the “populations” in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.

Recently, an article by Toshiko Tanaka, Takao Yamamoto, and Masahiko Haruno garnered a fair bit of media attention; in “Brain response patterns to economic inequity predict present and future depression indices”, they reported research that purported to show that “pro-social” individuals were more upset by unequal outcomes that didn’t directly disadvantage them than were “individualists.” Further, being pro-social was associated with a higher chance of developing depression. They linked this research with research showing that economic inequality is associated with poor health outcomes, including higher rates of depression. (They cite the epidemiologists Richard Wilkinson and Kate Pickett’s 2006 work...