"Theoretical pluralism" obtains when there are good evidential reasons for accommodating multiple theories of the same domain. Issues of "relative significance" often arise in connection with the investigation of such domains. In this paper, I describe and give examples of theoretical pluralism and relative significance issues. Then I explain why theoretical pluralism so often obtains in biology--and why issues of relative significance arise--in terms of evolutionary contingencies and the paucity or lack of laws of biology. Finally, I turn from explanation (...) to justification, and raise questions about the purpose and value of concerns and disagreements about relative significance. (shrink)

This paper considers recent heated debates led by Jerry A. Coyne andMichael J. Wade on issues stemming from the 1929–1962 R.A. Fisher-Sewall Wrightcontroversy in population genetics. William B. Provine once remarked that theFisher-Wright controversy is central, fundamental, and very influential.Indeed,it is also persistent. The argumentative structure of therecent (1997–2000) debates is analyzed with the aim of eliminating a logicalconflict in them, viz., that the two sides in the debates havedifferent aims and that, as such, they are talking past each other. (...) Given aphilosophical analysis of the argumentative structure of the debates,suggestions supportive of Wade's work on the debate are made that areaimed, modestly, at putting the persistent Fisher-Wright controversy on thecourse to resolution. (shrink)

Issues concerning scientific explanation have been a focus of philosophical attention from Pre- Socratic times through the modern period. However, recent discussion really begins with the development of the Deductive-Nomological (DN) model. This model has had many advocates (including Popper 1935, 1959, Braithwaite 1953, Gardiner, 1959, Nagel 1961) but unquestionably the most detailed and influential statement is due to Carl Hempel (Hempel 1942, 1965, and Hempel & Oppenheim 1948). These papers and the reaction to them have structured subsequent discussion concerning (...) scientific explanation to an extraordinary degree. After some general remarks by way of background and orientation (Section 1), this entry describes the DN model and its extensions, and then turns to some well-known objections (Section 2). It next describes a variety of subsequent attempts to develop alternative models of explanation, including Wesley Salmon's Statistical Relevance (Section 3) and Causal Mechanical (Section 4) models and the Unificationist models due to Michael Friedman and Philip Kitcher (Section 5). Section 6 provides a summary and discusses directions for future work. (shrink)

In The Origin of Species (1859) Darwin challenged many of the most deeply-held beliefs of the Western world. Arguing for a material, not divine, origin of species, he showed that new species are achieved by "natural selection." The Origin communicates the enthusiasm of original thinking in an open, descriptive style, and Darwin's emphasis on the value of diversity speaks more strongly now than ever. As well as a stimulating introduction and detailed notes, this edition offers a register of the many (...) writers referred to by Darwin in the text. (shrink)

Scientific models may be more useful for false assumptions they make than true ones when one is interested not in the fit of the model, but in the form of the residuals. Modeling Darwin’s “blending” theory of inheritance shows how it illuminates features of Mendelian theory. Insufficient understanding of it leads to incorrect moves in modeling population structure. But it may prove even more useful for organizing a theory of cultural evolution. Analysis of “blending” inheritance gives new tools for recognizing (...) population structure for culture and for understanding differences between biological and cultural inheritance. (shrink)

Scientific models may be more useful for false assumptions they make than true ones when one is interested not in the fit of the model, but in the form of the residuals. Modeling Darwin's “blending” theory of inheritance shows how it illuminates features of Mendelian theory. Insufficient understanding of it leads to incorrect moves in modeling population structure. But it may prove even more useful for organizing a theory of cultural evolution. Analysis of “blending” inheritance gives new tools for recognizing (...) population structure for culture and for understanding differences between biological and cultural inheritance. (shrink)

The ontological dependence of one domain on another is compatible with the explanatory autonomy of the less basic domain. That autonomy results from the fact that the relationship between two domains can be very complex. In this paper I distinguish two different types of complexity, two ways the relationship between domains can fail to be transparent, both of which are relevant to evolutionary biology. Sometimes high level explanations preserve a certain type of causal or counterfactual information which would be lost (...) at the lower level; I argue that this is central to the proper understanding of the adaptationist program. Sometimes high level kinds are multiply realised by lower level kinds: I argue that this is central to the understanding of macroevolution. (shrink)

Carl Hempel1 set the tone for subsequent philosophical work on scientific explanation by resolutely locating the problem he wanted to address outside of epistemology. “Hempel’s problem,” as I will call it, was not to say what counts as evidence that X is the explanation of Y. Rather, the question was what it means for X to explain Y. Hempel’s theory of explanation and its successors don’t tell you what to believe; instead, they tell you which of your beliefs (if any) (...) can be said to explain a given target proposition. (shrink)

H. B. D. Kettlewell's (1955, 1956) classic field experiments on industrial melanism in polluted and unpolluted settings using the peppered moth, Biston betularia, are routinely cited as establishing that the melanic (dark) form of the moth rose in frequency downwind of industrial centers because of the cryptic advantage dark coloration provides against visual predators in soot-darkened environments. This paper critiques three common myths surrounding these investigations: (1) that Kettlewell used a model that identified crypsis as the only selective force responsible (...) for the spread of the melanic gene, (2) that Kettlewell's field experiments alone established that selection for crypsis was the most important factor in the spread of melanic forms, and (3) that Kettlewell's investigations in an unpolluted wood near Dorset constituted a control for his earlier Birmingham studies (contra Hagen 1993, 1996). This analysis further identifies two features that distinguish manipulative experiments in evolutionary biology from experiments in other contexts. First, experiments in evolutionary biology rest on a wealth of information provided by strictly observational ecological studies; in the absence of such information experiments in evolutionary biology make no sense. Second, there is a trade-off between how much control investigators have over the conditions being studied and how informative the results of the experiment will be with regard to natural populations. (shrink)

Biologists in many different fields of research give how-possibly explanations of the phenomena they study. Although such explanations lack empirical support, and might be regarded by some as unscientific, they play an important heuristic role in biology by helping biologists develop theories and concepts and suggesting new areas of research. How-possibly explanations serve as a useful framework for conducting research in the absence of adequate empiri cal data, and they can even become how-actually explanations if they gain enough empirical support.

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model," is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory (...) confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories. (shrink)

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or “theory model” and “data model,” is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory (...) confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories. (shrink)

The recent literature in philosophy of biology has drawn attention to the different sorts of explanations proffered in the biological sciences—we have molecular, biomedical, and evolutionary explanations. Do these explanations all have a common structure or relation that they seek to capture? This paper will answer in the negative. I defend a pluralistic and pragmatic approach to explanation. Using examples from classical population genetics, I argue that formal demonstrations, and even strictly “mathematical truths,” may serve as explanatory in different historical (...) contexts. (shrink)

The object of this paper is to reply to Morrison's ([2000]) claim that while ‘structural unity’ was achieved at the level of the mathematical models of population genetics in the early synthesis, there was explanatory disunity. I argue to the contrary, that the early synthesis effected by the founders of theoretical population genetics was unifying and explanatory both. Defending this requires a reconsideration of Morrison's notion of explanation. In Morrison's view, all and only answers to ‘why’ questions which include the (...) ‘cause or mechanism’ for some phenomenon count as explanatory. In my view, mathematical demonstrations that answer ‘how possibly’ and ‘why necessarily’ questions may also count as explanatory. The authors of the synthesis explained how evolution was possible on a Mendelian system of inheritance, answered skepticism about the sufficiency of selection, and thus explained why and how a Darwinian research program was warranted. While today we take many of these claims as obvious, they required argument, and part of the explanatory work of the formal sciences is providing such arguments. Surely, Fisher and Wright had competing views as to the optimal means of generating adaptation. Nevertheless, they had common opponents and a common unifying and explanatory goal that their mathematical demonstrations served. Introduction: Morrison's challenge Fisher v. Wright revisited The early synthesis Conclusion: unification and explanation reconciled. (shrink)

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case-Maxime Lamotte's study of natural populations of the land snail, Cepaea nemoralis in the 1950s - shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations under study, Lamotte was able (...) to make a good case for a significant role for drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not impossible. (shrink)

Modelers often rely on robustness analysis, the search for predictions common to several independent models. Robustness analysis has been characterized and championed by Richard Levins and William Wimsatt, who see it as central to modern theoretical practice. The practice has also been severely criticized by Steven Orzack and Elliott Sober, who claim that it is a nonempirical form of confirmation, effective only under unusual circumstances. This paper addresses Orzack and Sober's criticisms by giving a new account of robustness analysis and (...) showing how the practice can identify robust theorems. Once the structure of robust theorems is clearly articulated, it can be shown that such theorems have a degree of confirmation, despite the lack of direct empirical evidence for their truth. (shrink)

Many of the things that we try to explain, in both our common sense and our scientific engagement with the world, are capable of being explained more or less finely: that is, with greater or lesser attention to the detail of the producing mechanism. A natural assumption, pervasive if not always explicit, is that other things being equal, the more finegrained an explanation, the better. Thus, Jon Elster, who also thinks there are instrumental reasons for wanting a more fine-grained explanation, (...) assumes that in any case the mere fact of getting nearer the detail of production makes such an explanation intrinsically superior: “a more detailed explanation is also an end in itself”. Michael Taylor agrees: “A good explanation should be, amongst other things, as fine-grained as possible.”. (shrink)

H. B. D. Kettlewell's field experiments on industrial melanism in the peppered moth, Biston betularia, have become the best known demonstration of natural selection in action. I argue that textbook accounts routinely portray this research as an example of controlled experimentation, even though this is historically misleading. I examine how idealized accounts of Kettlewell's research have been used by professional biologists and biology teachers. I also respond to some criticisms of David Rudge to my earlier discussions of this case study, (...) and I question Rudge's claims about the importance of purely observational studies for the eventual acceptance and popularization of Kettlewell's explanation for the evolution of industrial melanism. (shrink)

We develop an account of laboratory models, which have been central to the group selection controversy. We compare arguments for group selection in nature with Darwin's arguments for natural selection to argue that laboratory models provide important grounds for causal claims about selection. Biologists get information about causes and cause-effect relationships in the laboratory because of the special role their own causal agency plays there. They can also get information about patterns of effects and antecedent conditions in nature. But to (...) argue that some cause is actually responsible in nature, they require an inference from knowledge of causes in the laboratory context and of effects in the natural context. This process, cause detection, forms the core of an analogical argument for group selection. We discuss the differing roles of mathematical and laboratory models in constructing selective explanations at the group level and apply our discussion to the units of selection controversy to distinguish between the related problems of cause determination and evaluation of evidence. Because laboratory models are at the intersection of the two problems, their study is crucial for framing a coherent theory of explanation for evolutionary biology. (shrink)

In the 1960s molecular population geneticists used Monte Carlo experiments to evaluate particular diffusion equation models. In this paper I examine the nature of this comparative evaluation and argue for three claims: first, Monte Carlo experiments are genuine experiments: second, Monte Carlo experiments can provide an important meansfor evaluating the adequacy of highly idealized theoretical models; and, third, the evaluation of the computational adequacy of a diffusion model with Monte Carlo experiments is significantlydifferent from the evaluation of the emperical adequacy (...) of the same diffusion model. (shrink)

Realism and empiricism have always been contradictory tendencies in the philosophy of science. The view I will sketch is a synthesis, which I call Contrastive Empiricism. Realism and empiricism are incompatible, so a synthesis that merely conjoined them would be a contradiction. Rather, I propose to isolate important elements in each and show that they combine harmoniously. I will leave behind what I regard as confusions and excesses. The result, I hope, will be neither contradiction nor mishmash.

Discussions of the theory and practice of systematics and evolutionary biology have heretofore revolved around the views of philosophers of science. I reexamine these issues from the different perspective of the philosophy of history. Just as philosophers of history distinguish between chronicle (non-interpretive or non-explanatory writing) and narrative history (interpretive or explanatory writing), I distinguish between evolutionary chronicle (cladograms, broadly construed) and narrative evolutionary history. Systematics is the discipline which estimates the evolutionary chronicle. ¶ Explanations of the events described in (...) the evolutionary chronicle are not of the covering-law type described by philosophers of science, but rather of the how-possibly, continuous series, and integrating types described by philosophers of history. Pre-evolutionary explanations of states (in contrast to chroniclar events) are still widespread in "evolutionary" biology, however, because evolutionary chronicles are in general poorly known. To the extent that chronicles are known, the narrative evolutionary histories based on them are structured like conventional historical narratives, in that they treat their central subjects as ontological individuals. This conventional treatment is incorrect. The central subjects of evolutionary narratives are clades, branched entities which have some of the properties of individuals and some of the properties of classes. Our unconscious treatment of the subjects of evolutionary narratives as individuals has been the cause of erroneous notions of progress in evolution, and of views that taxa "develop" ontogenetically in ways analogous to individual organisms. We must rewrite our narrative evolutionary histories so that they properly represent the branching nature of evolution, and we must reframe our evolutionary philosophies so that they properly reflect the historical nature of our subject. (shrink)