Quantitative genetics (QG) analyses variation in traits of humans, other animals, or plants in ways that take account of the genealogical relatedness of the individuals whose traits are observed. “Classical” QG, where the analysis of variation does not involve data on measurable genetic or environmental entities or factors, is reformulated in this article using models that are free of hypothetical, idealized versions of such factors, while still allowing for defined degrees of relatedness among kinds of individuals or “varieties.” The gene (...) - free formulation encompasses situations encountered in human QG as well as in agricultural QG. This formulation is used to describe three standard assumptions involved in classical QG and provide plausible alternatives. Several concerns about the partitioning of trait variation into components and its interpretation, most of which have a long history of debate, are discussed in light of the gene-free formulation and alternative assumptions. That discussion is at a theoretical level, not dependent on empirical data in any particular situation. Additional lines of work to put the gene-free formulation and alternative assumptions into practice and to assess their empirical consequences are noted, but lie beyond the scope of this article. The three standard QG assumptions examined are: (1) partitioning of trait variation into components requires models of hypothetical, idealized genes with simple Mendelian inheritance and direct contributions to the trait; (2) all other things being equal, similarity in traits for relatives is proportional to the fraction shared by the relatives of all the genes that vary in the population (e.g., fraternal or dizygotic twins share half of the variable genes that identical or monozygotic twins share); (3) in analyses of human data, genotype-environment interaction variance (in the classical QG sense) can be discounted. The concerns about the partitioning of trait variation discussed include: the distinction between traits and underlying measurable factors; the possible heterogeneity in factors underlying the development of a trait; the kinds of data needed to estimate key empirical parameters; and interpretations based on contributions of hypothetical genes; as well as, in human studies, the labeling of residual variance as a non-shared environmental effect; and the importance of estimating interaction variance. (shrink)
The point Sesardic (Biol Philos 25: 143–162, 2010) makes about the possibility of distinguishing groups for which there is a lot of within-group variation is not sufficient to rehabilitate a biological concept of race. In this note, I sketch a number of issues that quickly arise once we delve more deeply into the relevant scientific knowledge, concepts, methods, and questions for inquiry.
This article examines eight “gaps” in order to clarify why the quantitative genetics methods of partitioning variation of a trait into heritability and other components has very limited power to show anything clear and useful about genetic and environmental influences, especially for human behaviors and other traits. The first two gaps should be kept open; the others should be bridged or the difficulty of doing so should be acknowledged: 1. Key terms have multiple meanings that are distinct; 2. Statistical patterns (...) are distinct from measurable underlying factors; 3. Translation from statistical analyses to hypotheses about measurable factors is difficult; 4. Predictions based on extrapolations from existing patterns of variation may not match outcomes; 5. The partitioning of variation in human studies does not reliably estimate the intended quantities; 6. Translation from statistical analyses to hypotheses about the measurable factors is even more difficult in light of the possible heterogeneity of underlying genetic or environmental factors; 7. Many steps lie between the analysis of observed traits and interventions based on well-founded claims about the causal influence of genetic or environmental factors; 8. Explanation of variation within groups does not translate to explanation of differences among groups. At the start, I engage readers’ attention with three puzzles that have not been resolved by past debates. The puzzles concern generational increases in IQ test scores, the possibility of underlying heterogeneity, and the translation of methods from selective breeding into human genetics. After discussing the gaps, I present each puzzle in a new light and point to several new puzzles that invite attention from analysts of variation in quantitative genetics and in social science more generally. The article’s critical perspectives on agricultural, laboratory, and human heritability studies are intended to elicit further contributions from readers across the fields of history, philosophy, sociology, and politics of biology and in the sciences. (shrink)
Ambitiously identifying fresh issues in the study of complex systems, Peter J. Taylor, in a model of interdisciplinary exploration, makes these concerns accessible to scholars in the fields of ecology, environmental science, and science studies. Unruly Complexity explores concepts used to deal with complexity in three realms: ecology and socio-environmental change; the collective constitution of knowledge; and the interpretations of science as they influence subsequent research. For each realm Taylor shows that unruly complexity-situations that lack definite boundaries, where what (...) goes on "outside" continually restructures what is "inside," and where diverse processes come together to produce change-should not be suppressed by partitioning complexity into well-bounded systems that can be studied or managed from an outside vantage point. Using case studies from Australia, North America, and Africa, he encourages readers to be troubled by conventional boundaries-especially between science and the interpretation of science-and to reflect more self-consciously on the conceptual and practical choices researchers make. (shrink)
Ecology has had a lower profile in Biology & Philosophy than one might expect on the basis of the attention ecology is given in public discussions in relation to environmental issues. Our tentative explanation is that ecology appears theoretically redundant within biology and, consequently, philosophically challenging problemsrelated to biology are commonly supposed to be somewhere else, particularly in the molecular sphere. Richard Levins has recognized the genuine challenges posed by ecology for theoretical and philosophical thinking in biology. This essay sets (...) the stage for appreciating his work; it was preceded by four articles published in Biology & Philosophy 15(2),and is followed by a personal reminiscent. (shrink)
A key challenge in conceptualizing ecological complexity is to allow simultaneously for particularity, contingency, and structure, and for such structure to be internally differentiated,dynamically tied to its context, and subject torestructuring. Because all organisms live insuch dynamic ecological circumstances, philosophy of ecology could become the leading site for addressing difficult conceptual questions concerning the situatedness or positionality of organisms –humans included – in their changing and intersecting worlds.
This essay extends Levins'' 1966 analysis of modelbuilding in ecology and evolutionary biology. Amodel, as the product of modeling, might bevalued according to its correspondence to reality. Yet Levins'' emphasis on provisionality and changeredirects attention to the processes ofmodeling, through which scientists select and generatetheir problems, define their categories, collect theirdata, compare competing models, and present theirfindings. I identify several points where decisionsare required that are not determined by nature. Thisinvites examination of the social considerationsmodelers are reacting to at the (...) sites of sociality.Modelers must weave socio-ecological webs so thatthe models can be seen to represent their subjectmatter at the same time as the modelers secure thesupport of colleagues, collaborators and institutions,and enjoin others to act upon their conclusions. Notonly do theory justification and theory generationmerge, but the joint project becomes simultaneouslyphilosophical and sociological. (shrink)
I characterize and then complicate Solomon, Thagard and Goldman's framing of the issue of integrating cognitive and social factors in explaining science. I sketch a radically (...) class='Hi'>different framing which distributes the mind beyond the brain, embodies it, and has that mind-body-person become, as s/he always is, an agent acting in a society. I also find problems in Solomon's construal of multivariate statistics, Thagard's analogies for multivariate analysis, and Goldman's faith in the capacity of the community of users of scientific method to home in on true beliefs. (shrink)
Diagrams refer to the phenomena overtly represented, to analogous phenomena, and to previous pictures and their graphic conventions. The diagrams of ecologists Clarke, Hutchinson, and H.T. Odum reveal their search for physical analogies, building on the success of World War II science and the promise of cybernetics. H.T. Odum's energy circuit diagrams reveal also his aspirations for a universal and natural means of reducing complexity to guide the management of diverse ecological and social systems. Graphic conventions concerning framing and translation (...) of ecological processes onto the flat printed page facilitate Odum's ability to act as if ecological relations were decomposable into systems and could be managed by analysts external to the system. (shrink)
Ecologists grapple with complex, changing situations. Historians, sociologists and philosophers studying the construction of science likewise attempt to account for (or discount) a wide variety of influences making up the scientists' "ecologies of knowledge." This paper introduces a graphic methodology, mapping, designed to assist researchers at both levels-in science and in science studies-to work with the complexity of their material. By analyzing the implications and limitations of mapping, I aim to contribute to an ecological approach to the philosophy of science.