Males are selectively afflicted with the neurodevelopmental and psychiatric disorders of childhood, a broad and virtually ubiquitous phenomenon that has not received proper attention in the biological study of sex differences. The previous literature has alluded to psychosocial differences, genetic factors and elements pertaining to male “complexity” and relative immaturity, but these are not deemed an adequate explanation for selective male affliction. The structure of sex differences in neurodevelopmental disorders is hypothesized to contain these elements: Males are more frequently afflicted, (...) females more severely; disorders arising in females are largely mediated by the genotype; in males, by a genotype by environment interaction; complications of pregnancy and delivery occur more frequently with male births; such complications are decisive and influence subsequent development. We hypothesize that there is something about the male fetus that evokes an inhospitable uterine environment. This “evocative principle” is hypothesized to relate to the relative antigenicity of the male fetus, which may induce a state of maternal immunoreactivity, leading either directly or indirectly to fetal damage. The immunoreactive theory thus constructed is borrowed from studies of sex ratios and is the only explanation consistent with negative parity effects in the occurrence of pregnancy complications and certain neurodevelopmental disorders. Although the theory is necessarily speculative, it is heuristic and hypotheses derived from it are proposed; some are confirmed in the existing literature and by the authors' research. (shrink)

This essay examines the origin of genotype-environment interaction, or G×E. "Origin" and not "the origin" because the thesis is that there were actually two distinct concepts of G×E at this beginning: a biometric concept, or \[G \times E_B\], and a developmental concept, or \[G \times E_D \]. R. A. Fisher, one of the founders of population genetics and the creator of the statistical analysis of variance, introduced the biometric concept as he attempted to resolve one of the main problems in (...) the biometric tradition of biology - partitioning the relative contributions of nature and nurture responsible for variation in a population. Lancelot Hogben, an experimental embryologist and also a statistician, introduced the developmental concept as he attempted to resolve one of the main problems in the developmental tradition of biology - determining the role that developmental relationships between genotype and environment played in the generation of variation. To argue for this thesis, I outline Fisher and Hogben's separate routes to their respective concepts of G × E; then these separate interpretations of G × E are drawn on to explicate a debate between Fisher and Hogben over the importance of G × E, the first installment of a persistent controversy. Finally, Fisher's \[G \times E_B\] and Hogben's \[G \times E_D \] are traced beyond their own work into mid-2Oth century population and developmental genetics, and then into the infamous IQ Controversy of the 1970s. (shrink)

Philosophers of science have developed an account of causal-mechanical explanation that captures regularity, but this account neglects variation. In this article I amend the philosophy of mechanisms to capture variation. The task is to explicate the relationship between regular causal mechanisms responsible for individual development and causes of variation responsible for variation in populations. As it turns out, disputes over this relationship have rested at the heart of the nature–nurture debate. Thus, an explication of the relationship between regular causal mechanisms (...) and causes of variation and between individual development and variation offers both the necessary amendment to the philosophy of mechanisms and the resources to mediate the dispute. (shrink)

Philosophers of science widely believe that the hereditarian theory about racial differences in IQ is based on methodological mistakes and confusions involving the concept of heritability. I argue that this "received view" is wrong: methodological criticisms popular among philosophers are seriously misconceived, and the discussion in philosophy of science about these matters is largely disconnected from the real, empirically complex issues debated in science.

Genetic differences can lead to phenotypic differences either directly or indirectly (via causing differences in external environments, which then affect phenotype). This possibility of genetic effects being mediated by environmental influences is often used by scientists and philosophers to argue that heritability is not a very helpful causal or explanatory notion. In this paper it is shown that these criticisms are based on serious misconceptions about methods of behavior genetics.

Many psychometricians and behavioral geneticists believe that high heritability of IQ test scores within racial groups coupled with environmental hypotheses failing to account for the differences between the mean scores for groups lends plausibility to explanations of mean differences in terms of genetic factors. This two-component argument cannot be sustained when viewed in the light of the conceptual and methodological themes introduced in Taylor . These themes concern the difficulties of moving from the statistical analysis of variance of observed traits (...) to investigation of measurable genetic factors and measurable environmental factors. One such theme is that quantities estimated by an AOV of observed traits cannot be equated with measurable genetic or environmental factors involved in the development of those traits. Once this distinction is clear, the argument that environmental factors have failed to explain the differences lacks weight because it does not consider whether genetic factors have been more successful. This article exposes additional flaws in the lines of thinking associated with the two-component argument, with the distinction between passive, reactive, and active associations between genetic and environmental factors, and with the reciprocal causation models Dickens and Flynn propose in order to reconcile high estimates of heritability and large IQ test score gains between generations. Human heritability estimates are irrelevant in developing explanations of differences across groups or across generations. My critique is directed at opening up more conceptual space for deriving empirically validated models of developmental pathways whose components are heterogeneous and differ among individuals at any one time and over generations. (shrink)

In this paper, I argue that epistemic injustice can result from transformative learning. Transformative learning causes a radical change in the structure of a student’s personal epistemic resources to bring them in line with the structure of a discipline’s shared epistemic resources. When those shared epistemic resources are biased, this transformation prevents students from retaining aspects of their personal epistemic resources which it is strongly in their interests (as well as in the interests of the broader epistemic community) to retain. (...) In these cases, transformative learning causes epistemic injustice in the form of inferential injustice. (shrink)

In contrast to the opinion of numerous authors (e.g. R. Rudner, P. Kitcher, L. R. Graham, M. Dummett, N. Chomsky, R. Lewontin, etc.) it is argued here that the formation of opinion in science should be greatly insulated from political considerations. Special attention is devoted to the view that methodological standards for evaluation of scientific theories ought to vary according to the envisaged political uses of these theories.

City College of New York The hereditarian theory of race differences in IQ was briefly revived with the appearance of The Bell Curve but then quickly dismissed. The authors attempt a defense of it here, with an eye to conceptual and logical issues of special interests to philosophers, such as alleged infirmities in the heritability concept. At the same time, some relevant post-Bell Curve empirical data are introduced.