John Dupre

The topic of this paper is social constructivist doctrines about the nature of scientific knowledge. I don't propose to review all the many accounts that have either claimed this designation or had it ascribed to them. Rather I shall try to consider in a very general way what sense should be made of the underlying idea, and then illustrate some of the central points with two central examples from biology. The first thing to say is that, on the face of it, some doctrine of the social construction of science must self-evidently be true. The notion of science as progressing through the efforts of solitary geniuses may have had some plausibility in the seventeenth century, but it has none today. Science is a massively cooperative, social, enterprise. And surely it is constructed. Scientific knowledge doesn't grow on trees; it is produced through hard work by human agents. Putting these two banal points together we conclude that science is socially constructed

Daniel Dennett's review2 of my book, Human Nature and the Limits of Science,3 was apparently conceived as part of a multiple review, anticipating an author's response, so I am grateful for the opportunity to satisfy this expectation. Indeed, Dennett uses this excuse to justify devoting his own contribution to responding to those parts of the book directed explicitly at his own work, leaving other imagined reviewers to take care of other issues. Since he has things to say about most of the topics in the book he evidently interpreted this remit widely, in fact taking the book as “presented as an antidote of sorts to [his] own world view” (p. 482). Let me begin, therefore, by reassuring Dennett that, while I certainly had some critical things to say about some of his views, the book most certainly was not intended as an ad hominem attack. The nine pages (out of 187) on which his work is cited fairly accurately reflects the extent to which his views figured in my thinking. Curiously, his ire seems most strongly aroused by my assault on his views on free will in which, apparently, I agree with nearly everything he says and, worse still, fail to cite him at all.

We address three fundamental questions: What does it mean for an entity to be living? What is the role of inter-organismic collaboration in evolution? What is a biological individual? Our central argument is that life arises when lineage-forming entities collaborate in metabolism. By conceiving of metabolism as a collaborative process performed by functional wholes, which are associations of a variety of lineage-forming entities, we avoid the standard tension between reproduction and metabolism in discussions of life – a tension particularly evident in discussions of whether viruses are alive. Our perspective assumes no sharp distinction between life and non-life, and does not equate life exclusively with cellular or organismal status. We reach this conclusion through an analysis of the capabilities of a spectrum of biological entities, in which we include the pivotal case of viruses as well as prions, plasmids, organelles, intracellular and extracellular symbionts, unicellular and multicellular life-forms. The usual criterion for classifying many of the entities of our continuum as non-living is autonomy. This emphasis on autonomy is problematic, however, because even paradigmatic biological individuals, such as large animals, are dependent on symbiotic associations with many other organisms. These composite individuals constitute the metabolic wholes on which selection acts. Finally, our account treats cooperation and competition not as polar opposites but as points on a continuum of collaboration. We suggest that competitive relations are a transitional state, with multi-lineage metabolic wholes eventually outcompeting selfish competitors, and that this process sometimes leads to the emergence of new types or levels of wholes. Our view of life as a continuum of variably structured collaborative systems leaves open the possibility that a variety of forms of organized matter – from chemical systems to ecosystems – might be usefully understood as living entities

It has notoriously been supposed that the doctrine of determinism conflicts with the belief in human freedom. Yet it is not readily apparent how indeterminism, the denial of determinism, makes human freedom any less problematic. It has sometimes been suggested that the arrival of quantum mechanics should immediately have solved the problem of free will and determinism. It was proposed, perhaps more often by scientists than by philosophers, that the brain would need only to be fitted with a device for amplifying indeterministic quantum phenomena for the bogey of determinism to be defeated. Acts of free will could then be those that were initiated by such indeterministic nudges. Recently there has been some inclination to revive such a story as part of the fallout from the trend for chaos theory. Chaotic systems in the brain, being indefinitely sensitive to the precise details of initial conditions, seem to provide fine candidates for the hypothetical amplifiers of quantum events

Recent molecular biology has seen the development of genomics as a successor to traditional genetics. This paper offers an overview of the structure, epistemology, and history of contemporary genomics. A particular focus is on the question to what extent the genome contains, or is composed of, anything that corresponds to traditional conceptions of genes. It is concluded that the only interpretation of genes that has much contemporary scientific relevance is what is described as the "developmental defect" gene concept. However, developmental defect genes typically only correspond to general areas of the genome and not to precise chemical structures . The parts of the genome to be identified for an account of the processes of normal development are highly diverse, little correlated with traditional genes, and act in ways that are highly dependent on the cellular and higher level environment. Despite its historical development out of genetics, genomics represents a radically different kind of scientific project

This chapter defends a pluralistic view of science: the various projects of enquiry that fall under the general rubric of science share neither a methodology nor a subject matter. Ontologically, it is argued that sciences need have nothing in common beyond an antipathy to the supernatural. Epistemically one central virtue is defended, empiricism, meaning just that scientific knowledge must ultimately be answerable to experience. Prima facie science is as diverse as the world it studies; and rejection of this prima facie diversity in favour of a spurious aspiration to unity is grounded in a priori assumption not experience. Disunity, however, does not mean disconnectedness, and the connections between different areas of knowledge are an important theme in the book.

Controversies about optimality models and adaptationist methodologies have animated the discussions of evolutionary theory in recent years. The sociobiologists, following the lead of E. O. Wilson, have argued that if Darwinian natural selection can be reliably expected to produce the best possible type of organism - one that optimizes the value of its genetic contribution to future generations - then evolution becomes a powerfully predictive theory as well as an explanatory one. The enthusiastic claims of the sociobiologists for the predictability and applicability that the optimalist approach engenders have been met with severe criticism by Richard C. Lewontin, Stephen Jay Gould, and other biologists and philosophers of biology. These original essays take up both sides of the controversy over the role of optimality models in evolutionary biology, providing a refreshingly insightful and balanced discussion of optimality issues by an interdisciplinary group of leading philosophers of biology, biologists, psychologists, anthropologists, and an economist. They focus on the current state of adaptationist and optimalist methodology in evolutionary theory, and on the possibility of extending such methodology to the human sciences, especially those of psychology and anthropology. Introduction / John Dupre -- Part 1. Methodological questions. Simple models of complex phenomena: the case of cultural evolution / Peter J. Richerson and Robert Boyd -- Natural selection and the null hypothesis / John Beatty -- Why not the best? / Philip Kitcher -- Part 2. Evolution and optimality. What is adaptationism? / Elliot Sober -- How to model evolution / John Maynard Smith -- Comments on Maynard Smith’s "How to Model Evolution" / Elliot Sober -- Reply to Sober / John Maynard Smith -- The shape of optimality / Richard C. Lewontin -- Part 3. Applications. Evolutionary ecology and the optimality assumption / John M. Emlen -- Optimality theory and behavior / John E.R. Staddon -- Part 4. Applications to human behavior. Optimization theory in anthropology: applications and critiques / Eric Alden Smith -- Evolution of a mesh between principles of the mind and regularities of the world / Roger N. Shepard -- From evolution to behavior: evolutionary psychology as the missing link / Leda Cosmides and John Tooby -- On the emotions as guarantors of threats and promises / Jack Hirschleifer -- Human kinds / John Dupre.

This paper attacks the perennial philosophical and scientific quest for a simple and unified vision of the world. Without denying the attraction of this vision, I argue that such a goal often seriously distorts our understanding of complex phenomena. The argument is illustrated with reference to simplistic attempts to provide extremely general views of biology, and especially of human nature, through the theory of evolution. Although that theory is a fundamental ingredient of our scientific world view, it provides only one of a number of perspectives that are required for an understanding of biology in general, and human behaviour in paticular. The argument is connected to the replacement of views of science in terms of universal laws with views that emphasise ranges of models more locally suited to specific phenomena

This article argues, in opposition to a common interpretation of Wittgenstein deriving from Winch, that there is nothing especially problematic about the social sciences. Familiar Wittgensteinian theses about language, notably on the open-endedness of linguistic rules and on the importance of family resemblance concepts, have great relevance not only to the social sciences but also to much of the natural sciences. The differences between scientific and ordinary language are much less sharp than Winch, and probably Wittgenstein, supposed.