How heritability misleads about race

How Do Students Critically Evaluate Outdated Language That Relates to Gender in Biology?

Cisheteronormative ideologies are infused into every aspect of society, including undergraduate science. We set out to identify the extent to which students can identify cisheteronormative language in biology textbooks by posing several hypothetical textbook questions and asking students to modify them to make the language more accurate (defined as "correct; precise; using language that applies to all people"). First, we confirmed that textbooks commonly use language that conflates or confuses sex and gender. We used this information to design two sample questions that used similar language. We examined what parts of the questions students modified, and the changes they recommended. When asked to modify sample textbook questions, we found the most common terms or words that students identified as inaccurate were related to infant gender identity. The most common modifications that students made were changing gender terms to sex terms. Students' decisions in this exercise differed little across three large biology courses or by exam performance. As the science community strives to promote inclusive classrooms and embrace the complexity of human gender identities, we provide foundational information about students' ability to notice and correct inaccurate language related to sex and gender in biology.

Heritability within groups is uninformative about differences among groups: Cases from behavioral, evolutionary, and statistical genetics

Without the ability to control or randomize environments (or genotypes), it is difficult to determine the degree to which observed phenotypic differences between two groups of individuals are due to genetic vs. environmental differences. However, some have suggested that these concerns may be limited to pathological cases, and methods have appeared that seem to give-directly or indirectly-some support to claims that aggregate heritable variation within groups can be related to heritable variation among groups. We consider three families of approaches: the "between-group heritability" sometimes invoked in behavior genetics, the statistic [Formula: see text] used in empirical work in evolutionary quantitative genetics, and methods based on variation in ancestry in an admixed population, used in anthropological and statistical genetics. We take up these examples to show mathematically that information on within-group genetic and phenotypic information in the aggregate cannot separate among-group differences into genetic and environmental components, and we provide simulation results that support our claims. We discuss these results in terms of the long-running debate on this topic.

Heritability within groups is uninformative about differences among groups: cases from behavioral, evolutionary, and statistical genetics

Without the ability to control or randomize environments (or genotypes), it is difficult to determine the degree to which observed phenotypic differences between two groups of individuals are due to genetic vs. environmental differences. However, some have suggested that these concerns may be limited to pathological cases, and methods have appeared that seem to give-directly or indirectly-some support to claims that aggregate heritable variation within groups can be related to heritable variation among groups. We consider three families of approaches: the "between-group heritability" sometimes invoked in behavior genetics, the statistic P S T used in empirical work in evolutionary quantitative genetics, and methods based on variation in ancestry in an admixed population, used in anthropological and statistical genetics. We take up these examples to show mathematically that information on within-group genetic and phenotypic information in the aggregate cannot separate among-group differences into genetic and environmental components, and we provide simulation results that support our claims. We discuss these results in terms of the long-running debate on this topic.

A Wolf in Sheep's Clothing: Idealisations and the aims of polygenic scores

Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics.

On the big list of causes

The methodological shift from twin studies to genome-wide association studies (GWASs) diminished estimates of true genetic causation underlying statistical heritability of behavioral differences. The sum total of causal genetic influence on behavior is not zero, but, (a) no one cited in the target article ever thought this was the case, and (b) there is still little known about concrete instances of genetic causation.

Reductionist methodology and the ambiguity of the categories of race and ethnicity in biomedical research: an exploratory study of recent evidence

In this article, we analyse how researchers use the categories of race and ethnicity with reference to genetics and genomics. We show that there is still considerable conceptual "messiness" (despite the wide-ranging and popular debate on the subject) when it comes to the use of ethnoracial categories in genetics and genomics that among other things makes it difficult to properly compare and interpret research using ethnoracial categories, as well as draw conclusions from them. Finally, we briefly reconstruct some of the biases of reductionism to which geneticists (as well as other researchers referring to genetic methods and explanations) are particularly exposed to, and we analyse the problem in the context of the biologization of ethnoracial categories. Our work constitutes a novel, in-depth contribution to the debate about reporting race and ethnicity in biomedical and health research. First, we reconstruct the theoretical background assumptions about racial ontology which researchers implicitly presume in their studies with the aid of a sample of recent papers published in medical journals about COVID-19. Secondly, we use the typology of the biases of reductionism to the problem of biologization of ethnoracial categories with reference to genetics and genomics.

Genetic determinism, essentialism and reductionism: semantic clarity for contested science

Research linking genetic differences with human social and behavioural phenotypes has long been controversial. Frequently, debates about the ethical, social and legal implications of this area of research centre on questions about whether studies overtly or covertly perpetuate genetic determinism, genetic essentialism and/or genetic reductionism. Given the prominent role of the '-isms' in scientific discourse and criticism, it is important for there to be consensus and clarity about the meaning of these terms. Here, the author integrates scholarship from psychology, genetics and philosophy of science to provide accessible definitions of genetic determinism, genetic reductionism and genetic essentialism. The author provides linguistic and visual examples of determinism, reductionism and essentialism in science and popular culture, discusses common misconceptions and concludes with recommendations for science communication.

New historical and philosophical perspectives on quantitative genetics

The aim of this virtual special issue is to bring together philosophical and historical perspectives to address long-standing issues in the interpretation, utility, and impacts of quantitative genetics methods and findings. Methodological approaches and the underlying scientific understanding of genetics and heredity have transformed since the field's inception. These advances have brought with them new philosophical issues regarding the interpretation and understanding of quantitative genetic results. The contributions in this issue demonstrate that there is still work to be done integrating old and new methodological and conceptual frameworks. In some cases, new results are interpreted using assumptions based on old concepts and methodologies that need to be explicitly recognised and updated. In other cases, new philosophical tools can be employed to synthesise historical quantitative genetics work with modern methodologies and findings. This introductory article surveys three general themes that have dominated philosophical discussion of quantitative genetics throughout history: (1) how methodologies have changed and transformed our knowledge and interpretations; (2) whether or not quantitative genetics can offer explanations relating to causation and prediction; and (3) the importance of defining the phenotypes under study. We situate the contributions in this virtual special issue within a historical framework addressing these three themes.

Building causal knowledge in behavior genetics

Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes such as educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. In this paper, we advance a framework for identifying instances of genetic causes, interpreting those causal relationships, and applying them to advance causal knowledge more generally in the social sciences. Central to thinking about genes as causes is counterfactual reasoning, the cornerstone of causal thinking in statistics, medicine, and philosophy. We argue that within-family genetic effects represent the product of a counterfactual comparison in the same way as average treatment effects (ATEs) from randomized controlled trials (RCTs). Both ATEs from RCTs and within-family genetic effects are shallow causes: They operate within intricate causal systems (non-unitary), produce heterogeneous effects across individuals (non-uniform), and are not mechanistically informative (non-explanatory). Despite these limitations, shallow causal knowledge can be used to improve understanding of the etiology of human behavior and to explore sources of heterogeneity and fade-out in treatment effects.

The apportionment of citations: a scientometric analysis of Lewontin 1972

‘The apportionment of human diversity’ (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This study's primary result—that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences—along with Lewontin's outspoken, politically charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we highlight four factors that may have played a role in shaping the paper's fame: (i) citations in influential publications across several disciplines; (ii) Lewontin's own popular books and media appearances; (iii) the renaissance of population genetics research of the early 1990s; and (iv) the serendipitous collision of scientific progress, influential books and papers, and heated controversies around the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the centre of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontin's legacy.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Half a century later and we're back where we started: How the problem of locality turned in to the problem of portability

In the 1970s, Lewontin sparked a debate about a problem of locality, by making the case that any given heritability estimate is local to the original population and environment studied, and could not be generalized to other populations and environments. Nearly 50 years later, a new problem of portability has emerged: the predictive accuracy of polygenic scores diminishes when applied to populations whose characteristics are different from the original population sample. This paper briefly reviews the nature of each problem and analyzes their similarities and differences in three areas: 1) conceptual underpinnings, 2) causal explanations, and 3) practical, social, and political implications. Although conceptually and methodologically different from the problem of locality in important respects, the problem of portability facing contemporary genomics today should come as no surprise, as it is an inevitable outcome of the kinds of problematic inferences detailed by Lewontin nearly half a century ago.

Ending genetic essentialism through genetics education

Genetic concepts are regularly used in arguments about racial inequality. This review summarizes research about the relationship between genetics education and a particular form of racial prejudice known as genetic essentialism. Genetic essentialism is a cognitive form of prejudice that is used to rationalize inequality. Studies suggest that belief in genetic essentialism among genetics students can be increased or decreased based on what students learn about human genetics and why they learn it. Research suggests that genetics education does little to prevent the development of genetic essentialism, and it may even exacerbate belief in it. However, some forms of genetics education can avert this problem. In particular, if instructors teach genetics to help students understand the flaws in genetic essentialist arguments, then it is possible to reduce belief in genetic essentialism among biology students. This review outlines our knowledge about how to accomplish this goal and the research that needs to be done to end genetic essentialism through genetics education.

The Meaning of "Cause" in Genetics

Causation has multiple distinct meanings in genetics. One reason for this is meaning slippage between two concepts of the gene: Mendelian and molecular. Another reason is that a variety of genetic methods address different kinds of causal relationships. Some genetic studies address causes of traits in individuals, which can only be assessed when single genes follow predictable inheritance patterns that reliably cause a trait. A second sense concerns the causes of trait differences within a population. Whereas some single genes can be said to cause population-level differences, most often these claims concern the effects of many genes. Polygenic traits can be understood using heritability estimates, which estimate the relative influences of genetic and environmental differences to trait differences within a population. Attempts to understand the molecular mechanisms underlying polygenic traits have been developed, although causal inference based on these results remains controversial. Genetic variation has also recently been leveraged as a randomizing factor to identify environmental causes of trait differences. This technique-Mendelian randomization-offers some solutions to traditional epidemiological challenges, although it is limited to the study of environments with known genetic influences.

The Cyclical Return of the IQ Controversy: Revisiting the Lessons of the Resolution on Genetics, Race and Intelligence

In 1976, the Genetics Society of America (GSA) published a document entitled "Resolution of Genetics, Race, and Intelligence." This document laid out the Society's position in the IQ controversy, particularly that on scientific and ethical questions involving the genetics of intellectual differences between human populations. Since the GSA was the largest scientific society of geneticists in the world, many expected the document to be of central importance in settling the controversy. Unfortunately, the Resolution had surprisingly little influence on the discussion. In 1979, William Provine analyzed the possible factors that decreased the impact of the Resolution, among them scientists' limited understanding of the relationship between science and ethics. Through the analysis of unpublished versions of the Resolution and exchanges between GSA members, I will suggest that the limited impact of the statement likely depended on a shift in the aims of the GSA due to the controversies that surrounded the preparation of the document. Indeed, the demands of the membership made it progressively more impartial in both scientific and political terms, decreasing its potential significance for a wider audience. Notably, the troubled history of the Resolution raises the question of what can make effective or ineffective the communication between scientists and the public-a question with resonance in past and present discussions on topics of social importance.

Insights into a possible role of glucagon-like peptide-1 receptor agonists in the treatment of depression

Depression is a highly prevalent mood disorder and one of the major health concerns in modern society. Moreover, it is characterized by a high prevalence of coexistence with many other diseases including metabolic disorders such as type 2 diabetes mellitus (T2DM) and obesity. Currently used antidepressant drugs, which mostly target brain monoaminergic neurotransmission, have limited clinical efficacy. Although the etiology of depression has not been fully elucidated, current scientific data emphasize the role of neurotrophic factors deficiencies, disturbed homeostasis between the nervous system and the immune and endocrine systems, as well as disturbances in brain energy metabolism and dysfunctions in the gut-brain axis as important factors in the pathogenesis of this neuropsychiatric disorder. Therefore, therapeutic options that could work in a way other than classic antidepressants are being sought to increase the effectiveness of the treatment. Interestingly, glucagon-like peptide-1 receptor agonists (GLP-1RAs), used in the treatment of T2DM and obesity, are known to show pro-cognitive and neuroprotective properties, and exert modulatory effects on immune, endocrine and metabolic processes in the central nervous system. This review article discusses the potential antidepressant effects of GLP-1RAs, especially in the context of their action on the processes related to neuroprotection, inflammation, stress response, energy metabolism, gut-brain crosstalk and the stability of the gut microbiota.

Genomic Contextualism: Shifting the Rhetoric of Genetic Exceptionalism

As genomic science has evolved, so have policy and practice debates about how to describe and evaluate the ways in which genomic information is treated for individuals, institutions, and society. The term genetic exceptionalism, describing the concept that genetic information is special or unique, and specifically different from other kinds of medical information, has been utilized widely, but often counterproductively in these debates. We offer genomic contextualism as a new term to frame the characteristics of genomic science in the debates. Using stasis theory to draw out the important connection between definitional issues and resulting policies, we argue that the framework of genomic contextualism is better suited to evaluating genomics and its policy-relevant features to arrive at more productive discussion and resolve policy debates.

Gene × Environment interaction: What exactly are we talking about?

An ambiguity exists in how psychological scientists use the word "interaction." This word can refer to physical interactions between components that form the mechanisms in complex systems, but it can also refer to statistical interactions revealed by General Linear Statistical Models (e.g., Analyses of Variance). Statistical interactions indicate that the nature of the relationship between two variables depends on a third variable, but the discovery of such interactions does not constitute evidence of physical interactions between components in a system. Studies conducted using traditional behavioral genetics methods sometimes reveal statistical interactions between genes and environments, but the presence or absence of such interactions tell us surprisingly little about actual, physical interactions between genes and their contexts. This is important, because it is only the latter kinds of interactions that cause the development of behavioral phenotypes, including developmental disabilities. Therefore, when behavioral scientists discover (or fail to discover) Genotype × Environment interactions, it is important to exercise care in interpreting their meaning and in assessing the utility of such findings.

The paradox of intelligence: Heritability and malleability coexist in hidden gene-environment interplay

Intelligence can have an extremely high heritability, but also be malleable; a paradox that has been the source of continuous controversy. Here we attempt to clarify the issue, and advance a frequently overlooked solution to the paradox: Intelligence is a trait with unusual properties that create a large reservoir of hidden gene-environment (GE) networks, allowing for the contribution of high genetic and environmental influences on individual differences in IQ. GE interplay is difficult to specify with current methods, and is underestimated in standard metrics of heritability (thus inflating estimates of "genetic" effects). We describe empirical evidence for GE interplay in intelligence, with malleability existing on top of heritability. The evidence covers cognitive gains consequent to adoption/immigration, changes in IQ's heritability across life span and socioeconomic status, gains in IQ over time consequent to societal development (the Flynn effect), the slowdown of age-related cognitive decline, and the gains in intelligence from early education. The GE solution has novel implications for enduring problems, including our inability to identify intelligence-related genes (also known as IQ's "missing heritability"), and the loss of initial benefits from early intervention programs (such as "Head Start"). The GE solution can be a powerful guide to future research, and may also aid policies to overcome barriers to the development of intelligence, particularly in impoverished and underprivileged populations. (PsycINFO Database Record

The heritability fallacy

The term 'heritability,' as it is used today in human behavioral genetics, is one of the most misleading in the history of science. Contrary to popular belief, the measurable heritability of a trait does not tell us how 'genetically inheritable' that trait is. Further, it does not inform us about what causes a trait, the relative influence of genes in the development of a trait, or the relative influence of the environment in the development of a trait. Because we already know that genetic factors have significant influence on the development of all human traits, measures of heritability are of little value, except in very rare cases. We, therefore, suggest that continued use of the term does enormous damage to the public understanding of how human beings develop their individual traits and identities. WIREs Cogn Sci 2017, 8:e1400. doi: 10.1002/wcs.1400 For further resources related to this article, please visit the WIREs website.

Genetic Determinism

Recently, investigators in behavioral genetics have found loci on the genome (so-called `quantitative trait loci' or QTLs) that are associated with complex mental traits, such as anxiety or novelty seeking. The interpretation of these findings raises interesting theoretical questions. At first sight, the discovery of `genes-for-personality' seems to support genetic determinism and reductionism. Genetic determinism is the view that the phenotype is precoded in or determined by the genotype. However, evidence from developmental biology and neural modeling indicates that development is a result of interactive processes at many levels, not only the genome, so that geneticism must be rejected. Identifying QTLs and perhaps also the causal paths in the tangle of top-down and bottom-up influences between genome, organism and environment is best seen as a simplification. It amounts to considerably less than reduction in the classical sense of replacement via bridge laws or elimination. It is argued that higher (psychological and physiological) levels are functionally characterized and are irreducible to molecular-genetic levels. Therefore, it is to be expected that ideas about inter-level relations may be useful in clarifying the relation between loci on the genome (QTLs), gene products, the nervous system, behavior and personality, and to help identify the contribution of genetic factors in behavioral genetics.

Putting humanity back into the teaching of human biology

In this paper, I draw upon debates about race in biology and philosophy as well as the concepts of ineliminable pluralism and psychological essentialism to outline the necessary subject matter knowledge that teachers should possess if they desire to: (i) increase student understanding of scientific research on genetic and behavioral variation in humans; and (ii) attenuate inegalitarian beliefs about race amongst students.

The Nature/Culture of Genetic Facts

This review aims to explore the relationship between anthropology and genetics, an intellectual zone that has been occupied in different ways over the past century. One way to think about it is to contrast a classical “anthropological genetics” ( Roberts 1965 ), that is to say, a genetics that presumably informs anthropological issues or questions, with a “genomic anthropology” ( Pálsson 2008 ), that is to say, an anthropology that complements and relativizes modern genomics (on the model of, say, medical anthropology and legal anthropology). 1 This review argues that a principal contribution of anthropology to the study of human heredity lies in the ontology of genetic facts. For anthropology, genetic facts are not natural, with meanings inscribed on them, but are instead natural/cultural: The natural facts have cultural information (values, ideologies, meanings) integrated into them, not layered on them. To understand genetic facts involves confronting their production, which has classically been restricted to questions of methodology but which may be conceptualized more broadly. This review is not intended as a critique of the field of anthropological genetics, but as a reformulation of its central objects of study. I argue for reconceptualizing the ontology of scientific facts in anthropological genetics, not as (value-neutral) biological facts situated in a cultural context, but instead as inherently biocultural facts.

Simpson's paradox in psychological science: a practical guide

The direction of an association at the population-level may be reversed within the subgroups comprising that population—a striking observation called Simpson's paradox. When facing this pattern, psychologists often view it as anomalous. Here, we argue that Simpson's paradox is more common than conventionally thought, and typically results in incorrect interpretations—potentially with harmful consequences. We support this claim by reviewing results from cognitive neuroscience, behavior genetics, clinical psychology, personality psychology, educational psychology, intelligence research, and simulation studies. We show that Simpson's paradox is most likely to occur when inferences are drawn across different levels of explanation (e.g., from populations to subgroups, or subgroups to individuals). We propose a set of statistical markers indicative of the paradox, and offer psychometric solutions for dealing with the paradox when encountered—including a toolbox in R for detecting Simpson's paradox. We show that explicit modeling of situations in which the paradox might occur not only prevents incorrect interpretations of data, but also results in a deeper understanding of what data tell us about the world.

An evaluation of the concept of innateness

The concept of innateness is often used in explanations and classifications of biological and cognitive traits. But does this concept have a legitimate role to play in contemporary scientific discourse? Empirical studies and theoretical developments have revealed that simple and intuitively appealing ways of classifying traits (e.g. genetically specified versus owing to the environment) are inadequate. They have also revealed a variety of scientifically interesting ways of classifying traits each of which captures some aspect of the innate/non-innate distinction. These include things such as whether a trait is canalized, whether it has a history of natural selection, whether it developed without learning or without a specific set of environmental triggers, whether it is causally correlated with the action of certain specific genes, etc. We offer an analogy: the term 'jade' was once thought to refer to a single natural kind; it was then discovered that it refers to two different chemical compounds, jadeite and nephrite. In the same way, we argue, researchers should recognize that 'innateness' refers not to a single natural kind but to a set of (possibly related) natural kinds. When this happens, it will be easier to progress in the field of biological and cognitive sciences.

From Theory Construction to Deconstruction

Theoretical psychology seems to have moved from helping theory construction in mainstream psychology to deconstructing and criticizing it. Three projects for theoretical psychology are sketched: theory construction (Kukla), naturalism (the Churchlands) and its variant metascience, and social constructionism (Gergen). It is argued that each is in itself valuable, but also that each is lacking in important respects. Metascience has no resources for a critical distance; social constructionism seems often stuck in de(con)structive mode; and theory construction seems captive to an outdated divide between data and theory. The thesis is that we may conceive of theoretical psychology as a continuum from theory construction to deconstruction, with different degrees of reflection, interpretation, integration, and criticism of research programs in psychology. Furthermore, reflection will often start from existing empirical research ( contra Kukla, and, in a different way, contra Gergen), but nevertheless have the resources to criticize it ( contra ultra-naturalistic metascience). Some examples of theoretical projects are listed to illustrate this picture.

Misuse of Genetic Data in Environmental Epidemiology

The implications of attributing health and diseases more to "nature" (genes) or "nurture" (the environment) have been debated for a long time. Although considerable advancements have been made both in theoretical clarification of concepts, and in the study of the origins of disease, there is still much confusion, for example, in the press and in the beliefs of the population. There is a large consensus, among scientists, that only a small fraction of diseases is due to genes in the usual meaning, that is, according to mendelian inheritance (say around 5% of all diseases), whereas the vast majority of cases are due to environmental exposures or to "gene-environment interactions." In this article I will briefly discuss a model for gene-environment interactions, and I will recall an important discussion that took place decades ago around the mistakes related to attributing diseases or other traits to inheritance. Finally, I will describe a specific example of potential misuse of genetic information.

Causal models in epidemiology: past inheritance and genetic future

The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification) and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional uncertainty in quantifying interaction and assigning etiologic fractions to different necessary causes because of ignorance about the components of the sufficient cause.

Genetics of brain structure and intelligence

Genetic influences on brain morphology and IQ are well studied. A variety of sophisticated brain-mapping approaches relating genetic influences on brain structure and intelligence establishes a regional distribution for this relationship that is consistent with behavioral studies. We highlight those studies that illustrate the complex cortical patterns associated with measures of cognitive ability. A measure of cognitive ability, known as g, has been shown highly heritable across many studies. We argue that these genetic links are partly mediated by brain structure that is likewise under strong genetic control. Other factors, such as the environment, obviously play a role, but the predominant determinant appears to be genetic.

Intelligence, race, and genetics

In this article, the authors argue that the overwhelming portion of the literature on intelligence, race, and genetics is based on folk taxonomies rather than scientific analysis. They suggest that because theorists of intelligence disagree as to what it is, any consideration of its relationships to other constructs must be tentative at best. They further argue that race is a social construction with no scientific definition. Thus, studies of the relationship between race and other constructs may serve social ends but cannot serve scientific ends. No gene has yet been conclusively linked to intelligence, so attempts to provide a compelling genetic link of race to intelligence are not feasible at this time. The authors also show that heritability, a behavior-genetic concept, is inadequate in regard to providing such a link.