Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions-according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system-captures one important sense of "function" in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explanation. The synthesis produces an analysis of specifically mechanistic role functions, one that uses the characteristic (...) active, spatial, temporal, and hierarchical organization of mechanisms to add precision and content to Cummins' original suggestion. This synthesis also shows why the discovery of role functions is a scientific achievement. Discovering a role function (i) contributes to the interlevel integration of multilevel mechanisms, and (ii) provides a unique, contextual variety of causal/mechanical explanation. (shrink)

This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

How do fitness and natural selection relate to other evolutionary factors like architectural constraint, mode of reproduction, and drift? In one way of thinking, drawn from Newtonian dynamics, fitness is one force driving evolutionary change and added to other factors. In another, drawn from statistical thermodynamics, it is a statistical trend that manifests itself in natural selection histories. It is argued that the first model is incoherent, the second appropriate; a hierarchical realization model is proposed as a basis for a (...) statistical treatment. It emerges that natural selection does not cause evolution; it just is evolution. The theory incorporates relations of statistical correlation, but not the kind of causation found in fundamental physical processes. (shrink)

We distinguish dynamical and statistical interpretations of evolutionary theory. We argue that only the statistical interpretation preserves the presumed relation between natural selection and drift. On these grounds we claim that the dynamical conception of evolutionary theory as a theory of forces is mistaken. Selection and drift are not forces. Nor do selection and drift explanations appeal to the (sub-population-level) causes of population level change. Instead they explain by appeal to the statistical structure of populations. We briefly discuss the implications (...) of the statistical interpretation of selection for various debates within the philosophy of biologythe `explananda of selection' debate and the `units of selection' debate. (shrink)

Philosophers of science typically associate the causal‐mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon’s account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex‐systems approach avoids certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Recent discussions in the philosophy of biology have brought into question some fundamental assumptions regarding evolutionary processes, natural selection in particular. Some authors argue that natural selection is nothing but a population-level, statistical consequence of lower-level events (Matthen and Ariew [2002]; Walsh et al. [2002]). On this view, natural selection itself does not involve forces. Other authors reject this purely statistical, population-level account for an individual-level, causal account of natural selection (Bouchard and Rosenberg [2004]). I argue that each of these (...) positions is right in one way, but wrong in another; natural selection indeed takes place at the level of populations, but it is a causal process nonetheless. (shrink)

This paper presents a counterfactual account of what a mechanism is. Mechanisms consist of parts, the behavior of which conforms to generalizations that are invariant under interventions, and which are modular in the sense that it is possible in principle to change the behavior of one part independently of the others. Each of these features can be captured by the truth of certain counterfactuals.

Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...) change; they are not discrete, apportionable causes. Our objective here is to provide a definitive statement of the statistical position, so as to allay some confusions in the current literature. We outline four commitments that are central to statisticalism. They are: 1. Natural Selection is a higher order effect; 2. Trait fitness is primitive; 3. Modern Synthesis (MS)-models are substrate neutral; 4. MS-selection and drift are model-relative. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

We argue that a fashionable interpretation of the theory of natural selection as a claim exclusively about populations is mistaken. The interpretation rests on adopting an analysis of fitness as a probabilistic propensity which cannot be substantiated, draws parallels with thermodynamics which are without foundations, and fails to do justice to the fundamental distinction between drift and selection. This distinction requires a notion of fitness as a pairwise comparison between individuals taken two at a time, and so vitiates the interpretation (...) of the theory as one about populations exclusively. (shrink)

There are two competing interpretations of the modern synthesis theory of evolution: the dynamical (also know as ‘traditional’) and the statistical. The dynamical interpretation maintains that explanations offered under the auspices of the modern synthesis theory articulate the causes of evolution. It interprets selection and drift as causes of population change. The statistical interpretation holds that modern synthesis explanations merely cite the statistical structure of populations. This paper offers a defense of statisticalism. It argues that a change in trait frequencies (...) in a population can be attributed only to selection or drift against the background of a particular statistical description of the population. The traditionalist supposition that selection and drift are description‐independent causes of population change leads the dynamical interpretation into a dilemma: it must face a contradiction or accept the loss of explanatory power. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

This paper explores whether natural selection, a putative evolutionary mechanism, and a main one at that, can be characterized on either of the two dominant conceptions of mechanism, due to Glennan and the team of Machamer, Darden, and Craver, that constitute the “new mechanistic philosophy.” The results of the analysis are that neither of the dominant conceptions of mechanism adequately captures natural selection. Nevertheless, the new mechanistic philosophy possesses the resources for an understanding of natural selection under the rubric.

We have argued elsewhere that: (A) Natural selection is not a cause of evolution. (B) A resolution-of-forces (or vector addition) model does not provide us with a proper understanding of how natural selection combines with other evolutionary influences. These propositions have come in for criticism recently, and here we clarify and defend them. We do so within the broad framework of our own “hierarchical realization model” of how evolutionary influences combine.

Shapiro and Sober claim that Walsh, Ariew, Lewens, and Matthen give a mistaken, a priori defense of natural selection and drift as epiphenomenal. Contrary to Shapiro and Sober’s claims, we first argue that WALM’s explanatory doctrine does not require a defense of epiphenomenalism. We then defend WALM’s explanatory doctrine by arguing that the explanations provided by the modern genetical theory of natural selection are ‘autonomous-statistical explanations’ analogous to Galton’s explanation of reversion to mediocrity and an explanation of the diffusion ofgases. (...) We then argue that whereas Sober’s theory of forces is an adequate description of Darwin’s theory, WALM’s explanatory doctrine is required to understand how themodern genetical theory of natural selection explains large-scale statistical regularities. 1 Introduction2 Shapiro and Sober’s ‘Epiphenomenalism Do’s and Don’ts’3 WALM’s Explanatory Doctrine4 Galton’s Autonomous-Statistical Explanation5 A Second Example: The Statistical Explanation of the Diffusion of Gases6 Distinguishing Two Theories of Evolution by Natural Selection7 A Possible Objection: Are Statistical Laws Sufficient for Explanation?8 Conclusion. (shrink)

Skipper and Millstein (2005) argued that existing conceptions of mechanisms failed to "get at" natural selection, but left open the possibility that a refined conception of mechanisms could resolve the problems that they identified. I respond to Skipper and Millstein, and argue that while many of their points have merit, their objections can be overcome and that natural selection can be characterized as a mechanism. In making this argument, I discuss the role of regularity in mechanisms, and develop an account (...) of stochastic (i.e., probabilistic) mechanisms. Explaining the phenomenon of adaptation through the mechanism of natural selection illustrates the power and flexibility of using mechanistic strategies to explain natural phenomena. (shrink)

Recent papers by a number of philosophers have been concerned with the question of whether natural selection is a causal process, and if it is, whether the causes of selection are properties of individuals or properties of populations. I shall argue that much confusion in this debate arises because of a failure to distinguish between causal productivity and causal relevance. Causal productivity is a relation that holds between events connected via continuous causal processes, while causal relevance is a relationship that (...) can hold between a variety of different kinds of facts and the events that counterfactually depend upon them. I shall argue that the productive character of natural selection derives from the aggregation of individual processes in which organisms live, reproduce and die. At the same time, a causal explanation of the distribution of traits will necessarily appeal both to causally relevant properties of individuals and to causally relevant properties that exist only at the level of the population. (shrink)

Elliott Sober and his defenders think of selection, drift, mutation, and migration as distinct evolutionary forces. This paper exposes an ambiguity in Sober's account of the force of selection: sometimes he appears to equate the force of selection with variation in fitness, sometimes with ‘selection for properties’. Sober's own account of fitness as a property analogous to life-expectancy shows how the two conceptions come apart. Cases where there is selection against variance in offspring number also show that selection and drift (...) cannot be distinguished in the way Sober hopes for. These issues have significance beyond the parochial matter of the coherence of Sober's system. There is no good principled answer to the question of which features of a population should count among the contributors to fitness. This means there is no non-arbitrary account of the nature of selection. (shrink)

Skipper and Millstein analyze natural selection and mechanism, concluding that natural selection is not a mechanism in the sense of the new mechanistic philosophy. Barros disagrees and provides his own account of natural selection as a mechanism. This discussion identifies a missing piece of Barros's account, attempts to fill in that piece, and reconsiders the revised account. Two principal objections are developed: one, the account does not characterize natural selection; two, the account is not mechanistic. Extensive and persistent variability causes (...) both of these difficulties, so further attempts to describe natural selection as a mechanism are also unlikely to succeed. (shrink)

The traditional view of evolutionary theory asserts that we can usefully understand natural selection, drift, mutation, migration, and the system of mating as forces that cause evolutionary change. Recently, Denis Walsh and Robert Brandon have objected to this view. Walsh argues that the traditional view faces a fatal dilemma and that the force analogy must be rejected altogether. Brandon accepts the force analogy but argues that drift, rather than the Hardy-Weinberg law, is the best candidate for a zero-force law. Here (...) I defend the traditional view against these objections. (shrink)

Fodor argue that Darwinism cannot be true on the grounds that there are no laws of selection to support counterfactuals about why traits are selected-for. Darwinian explanations, according to this objection, amount to mere ‘plausible historical narratives’. I argue that the objection is predicated on two problematic assumptions: A nomic-subsumption account of causation and causal explanation, and a fine-grained view of the individuation of selected-for effects. Against the former, I argue that Darwinian explanations are a historical species of mechanistic explanation (...) and that mechanisms are causally productive and counterfactual supporting in the absence of appropriate laws. Once this mechanistic framework is in place, the demand for laws of selection vanishes and the historical cum causal coherence of Darwinism is restored. As for the second assumption, I argue that it is an artefact of the teleosemantic program with no basis in evolutionary biology and that properly understood, Darwinian evolutionary biology shows just why teleosemantics cannot succeed. (shrink)

This paper investigates the conception of causation required in order to make sense of natural selection as a causal explanation of changes in traits or allele frequencies. It claims that under a counterfactual account of causation, natural selection is constituted by the causal relevance of traits and alleles to the variation in traits and alleles frequencies. The “statisticalist” view of selection (Walsh, Matthen, Ariew, Lewens) has shown that natural selection is not a cause superadded to the causal interactions between individual (...) organisms. It also claimed that the only causation at work is those aggregated individual interactions, natural selection being only predictive and explanatory, but it is implicitly committed to a process-view of causation. I formulate a counterfactual construal of the causal statements underlying selectionist explanations, and show that they hold because of the reference they make to ecological reliable factors. Considering case studies, I argue that this counterfactual view of causal relevance proper to natural selection captures more salient features of evolutionary explanations than the statisticalist view, and especially makes sense of the difference between selection and drift. I eventually establish equivalence between causal relevance of traits and natural selection itself as a cause. (shrink)

In “Two Ways of Thinking About Fitness and Natural Selection” (Matthen and Ariew [2002]; henceforth “Two Ways”), we asked how one should think of the relationship between the various factors invoked to explain evolutionary change – selection, drift, genetic constraints, and so on. We suggested that these factors are not related to one another as “forces” are in classical mechanics. We think it incoherent, for instance, to think of natural selection and drift as separate and opposed “forces” in evolutionary change (...) – that it makes sense to say, for instance, that selection contributed 80% to the actual evolutionary history of the human eye, and drift only 20%. We proposed instead a statistical view of the Theory of Evolution, a view in which fitness is not a cause of evolution, but rather a measure of growth. We also argued for a “hierarchical realization model” for thinking about the relationship between evolutionary factors such as those mentioned above, and suggested that in a “fully specified model”, as we call it below, there is no distinction between natural selection and evolution. (shrink)