During the last three decades, reflections on the growth of scientific knowledge have inspired historians, sociologists, and some philosophers to contend that scientific objectivity is a myth. In this book, Kitcher attempts to resurrect the notions of objectivity and progress in science by identifying both the limitations of idealized treatments of growth of knowledge and the overreactions to philosophical idealizations. Recognizing that science is done not by logically omniscient subjects working in isolation, but by people with a variety of personal (...) and social interests, who cooperate and compete with one another, he argues that, nonetheless, we may conceive the growth of science as a process in which both our vision of nature and our ways of learning more about nature improve. Offering a detailed picture of the advancement of science, he sets a new agenda for the philosophy of science and for other "science studies" disciplines. (shrink)

Debates over adaptationism can be clarified and partially resolved by careful consideration of the ‘grain’ at which evolutionary processes are described. The framework of ‘adaptive landscapes’ can be used to illustrate and facilitate this investigation. We argue that natural selection may have special status at an intermediate grain of analysis of evolutionary processes. The cases of sickle-cell disease and genomic imprinting are used as case studies.

Godfrey-Smith ( 2001 ) has distinguished three types of adaptationism. This article builds on his analysis, and revises it in places, by distinguishing seven varieties of adaptationism. This taxonomy allows us to clarify what is at stake in debates over adaptationism, and it also helps to cement the importance of Gould and Lewontin’s ‘Spandrels’ essay. Some adaptationists have suggested that their essay does not offer any coherent alternative to the adaptationist programme: it consists only in an exhortation to test adaptationist (...) hypotheses more thoroughly than was usual in the 1970s. Here it is argued that the ‘Spandrels’ paper points towards a genuinely non-adaptationist methodology implicit in much evolutionary developmental biology. This conclusion helps to expose the links between older debates over adaptationism and more recent questions about the property of evolvability. (shrink)

Debate about adaptationism in biology continues, in part because within “the” problem of assessing adaptationism, three distinct problems are mixed together. The three problems concern the assessment of three distinct adaptationist positions, each of which asserts the central importance of adaptation and natural selection to the study of evolution, but conceives this importance in a different way. As there are three kinds of adaptationism, there are three distinct "anti-adaptationist" positions as well. Or putting it more formally, there are three different (...) dimensions here, and strongly adaptationist views, strongly anti-adaptationist views, and moderate views are possible for each dimension. (shrink)

an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the (...) key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments. (shrink)

Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...) building is successful even when models are predictively inaccurate for at least three reasons: models allow scientists to explore the possible behaviors of ecological systems; models give scientists simplified means by which they can investigate more complex systems by determining how the more complex system deviates from the simpler model; and models give scientists conceptual frameworks through which they can conduct experiments and fieldwork. Critics often mistake the purposes of model building, and once we recognize this, we can see their complaints are unjustified. Even though models in ecology are not always accurate in their assumptions and predictions, they still contribute to successful science. (shrink)

Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...) on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft. (shrink)

: Where there are cases of underdetermination in scientific controversies, such as the case of the molecular clock, scientists may direct the course and terms of dispute by playing off the multidimensional framework of theory evaluation. This is because assessment strategies themselves are underdetermined. Within the framework of assessment, there are a variety of trade-offs between different strategies as well as shifting emphases as specific strategies are given more or less weight in assessment situations. When a strategy is underdetermined, scientists (...) can change the dynamics of a controversy by making assessments using different combinations of evaluation strategies and/or weighting whatever strategies are in play in different ways. Following an underdetermination strategy does not end or resolve a scientific dispute. Consequently, manipulating underdetermination is a feature of controversy dynamics and not controversy closure. (shrink)

How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design (...) are untestable; whether they are discredited by the fact that many adaptations are imperfect; how evidence bears on whether present species trace back to common ancestors; how hypotheses about natural selection can be tested, and many other issues. His book will interest all readers who want to understand philosophical questions about evidence and evolution, as they arise both in Darwin's work and in contemporary biological research. (shrink)

The incredible achievements of modern scientific theories lead most of us to embrace scientific realism: the view that our best theories offer us at least roughly accurate descriptions of otherwise inaccessible parts of the world like genes, atoms, and the big bang. In Exceeding Our Grasp, Stanford argues that careful attention to the history of scientific investigation invites a challenge to this view that is not well represented in contemporary debates about the nature of the scientific enterprise. The historical record (...) of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself. Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true. (shrink)

Scientists often make surprising claims about things that no one can observe. In physics, chemistry, and molecular biology, scientists can at least experiment on those unobservable entities, but what about researchers in fields such as paleobiology and geology who study prehistory, where no such experimentation is possible? Do scientists discover facts about the distant past or do they, in some sense, make prehistory? In this book Derek Turner argues that this problem has surprising and important consequences for the scientific realism (...) debate. His discussion covers some of the main positions in philosophy of science - realism, social constructivism, empiricism, and the natural ontological attitude - and shows how they relate to issues in paleobiology and geology. His original and thought-provoking book will be of wide interest to philosophers and scientists alike. (shrink)

David Lewis defends the thesis of the asymmetry of overdetermination: later affairs are seldom overdetermined by earlier affairs, but earlier affairs are usually overdetermined by later affairs. Recently, Carol Cleland has argued that since the distinctive methodologies of historical science and experimental science exploit different aspects of this asymmetry, the methodology of historical science is just as good, epistemically speaking, as that of experimental science. This paper shows, first, that Cleland's epistemological conclusion does not follow from the thesis of the (...) asymmetry of overdetermination, because overdetermination is compatible with epistemic underdetermination. The paper also shows, contra Cleland, that there is at least one interesting sense in which historical science is epistemically inferior to experimental science, after all, because local underdetermination problems are more widespread in historical than in experimental science. (shrink)

In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I (...) argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline. (shrink)

Among the liveliest disputes in evolutionary biology today are disputes concerning the role of chance in evolution--more specifically, disputes concerning the relative evolutionary importance of natural selection vs. so-called "random drift". The following discussion is an attempt to sort out some of the broad issues involved in those disputes. In the first half of this paper, I try to explain the differences between evolution by natural selection and evolution by random drift. On some common construals of "natural selection", those two (...) modes of evolution are completely indistinguishable. Even on a proper construal of "natural selection", it is difficult to distinguish between the "improbable results of natural selection" and evolution by random drift. In the second half of this paper, I discuss the variety of positions taken by evolutionists with respect to the evolutionary importance of random drift vs. natural selection. I will then consider the variety of issues in question in terms of a conceptual distinction often used to describe the rise of probabilistic thinking in the sciences. I will argue, in particular, that what is going on here is not, as might appear at first sight, just another dispute about the desirability of "stochastic" vs. "deterministic" theories. Modern evolutionists do not argue so much about whether evolution is stochastic, but about how stochastic it is. (shrink)

Likelihoodists and Bayesians seem to have a fundamental disagreement about the proper probabilistic explication of relational (or contrastive) conceptions of evidential support (or confirmation). In this paper, I will survey some recent arguments and results in this area, with an eye toward pinpointing the nexus of the dispute. This will lead, first, to an important shift in the way the debate has been couched, and, second, to an alternative explication of relational support, which is in some sense a "middle way" (...) between Likelihoodism and Bayesianism. In the process, I will propose some new work for an old probability puzzle: the "Monty Hall" problem. (shrink)

Traditionally a scientific theory is viewed as based on universal laws of nature that serve as axioms for logical deduction. In analyzing the logical structure of evolutionary biology, Elisabeth Lloyd argues that the semantic account is more appropriate and powerful. This book will be of interest to biologists and philosophers alike.