The target of this article is the claim that natural selection accounts for the multiple realisation of biological and psychological kinds. I argue that the explanation actually offered does not provide any insight about the phenomenon since it presupposes multiple realisation as an unexplained premise, and this is what does all the work. The purported explanation mistakenly invokes the ?indifference? of selection to structure as an additional explanatorily relevant factor. While such indifference can be explanatory in intentional contexts, it is (...) not a causal factor at all in non-intentional nature. The upshot is that, once the necessary initial assumption about heterogeneity is accepted, there is no further explanation to do. (shrink)

In this paper I critically evaluate Reisman and Forber’s :1113–1123, 2005) arguments that drift and natural selection are population-level causes of evolution based on what they call the manipulation condition. Although I agree that this condition is an important step for identifying causes for evolutionary change, it is insufficient. Following Woodward, I argue that the invariance of a relationship is another crucial parameter to take into consideration for causal explanations. Starting from Reisman and Forber’s example on drift and after having (...) briefly presented the criterion of invariance, I show that once both the manipulation condition and the criterion of invariance are taken into account, drift, in this example, should better be understood as an individual-level rather than a population-level cause. Later, I concede that it is legitimate to interpret natural selection and drift as population-level causes when they rely on genuinely indeterministic events and some cases of frequency-dependent selection. (shrink)

There is a tension between, on the one hand, the view that natural selection refers to individual-level causes, and on the other hand, the view that it refers to a population-level cause. In this article, I make the case for the individual-level cause view. I respond to recent claims made by McLoone that the individual-level cause view is inconsistent. I show that if one were to follow his arguments, any causal claim in any context would have to be regarded as (...) vindicating a form of population-level cause view. I show why this is implausible and how a consistent individual-level cause position can be held within the interventionist account of causation. Finally, I argue that there is one sense in which natural selection might be said to refer to population-level causes of evolutionary change. The upshot is that, as noted by others, natural selection can be regarded as referring to a population-level cause in the context of frequency-dependent selection and other situations of fitness-altering interactions between the individuals of a population. But whether this statement is true will depend on the empirical case investigated, not some a priori conceptual distinction. Thus, even though situations of frequency dependence might be ubiquitous, it is orthogonal to the conceptual question of whether frequency-independent natural selection—McLoone’s target—refers to individual- or population-level causes. (shrink)

I distinguish two roles for a fitness concept in the context of explaining cumulative adaptive evolution: fitness as a predictor of gene frequency change, and fitness as a criterion for phenotypic improvement. Critics of inclusive fitness argue, correctly, that it is not an ideal fitness concept for the purpose of predicting gene-frequency change, since it relies on assumptions about the causal structure of social interaction that are unlikely to be exactly true in real populations, and that hold as approximations only (...) given a specific type of weak selection. However, Hamilton took this type of weak selection, on independent grounds, to be responsible for cumulative assembly of complex adaptations. In this special context, I argue that inclusive fitness is distinctively valuable as a criterion for improvement and a standard for optimality. Yet to call inclusive fitness a criterion for improvement and a standard for optimality is not to make any claim about the frequency with which inclusive fitness optimization actually occurs in nature. This is an empirical question that cannot be settled by theory alone. I close with some reflections on the place of inclusive fitness in the long running clash between ‘causalist’ and ‘statisticalist’ conceptions of fitness. (shrink)

This volume focuses on various questions concerning the interpretation of probability and probabilistic reasoning in biology and physics. It is inspired by the idea that philosophers of biology and philosophers of physics who work on the foundations of their disciplines encounter similar questions and problems concerning the role and application of probability, and that interaction between the two communities will be both interesting and fruitful. In this introduction we present the background to the main questions that the volume focuses on (...) and summarize the highlights of the individual contributions. (shrink)

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)

I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)

and was correct to conclude that the way a biological population is described should affect conclusions about whether natural selection occurs, but wrong to conclude that natural selection is therefore not a cause. After providing a new argument that ignored crucial biological details, I give a biological illustration that motivates a fairly extreme dependence on description. I argue that contrary to an implication of , biologists allow much flexibility in describing populations, as contemporary research on recent human evolution shows. Properly (...) understood, such description-dependence is consistent with descriptions capturing different causal relations involving the same population. I thus show that Walsh’s arguments fail for reasons that have not previously been understood; I argue that Walsh’s more recent “Sure Thing” argument fails for similar reasons. The resulting view provides a new perspective on causation in evolutionary processes. (shrink)

Sewall Wright ’s FST is a mathematical test widely used in empirical applications to characterize genetic and other differences between subpopulations, and to identify causes of those differences. Cockerham and Weir’s popular approach to statistical estimation of FST is based on an assumption sometimes formulated as a claim that actual populations tested are sampled from.

Natural selection is a general process that operates in different populations. To characterise natural selection as a mechanism within the framework of the new mechanistic philosophy, it is required to identify a pertinent phenomenon for which natural selection is responsible. Firstly, every case identified by evolutionary biologists as instances of natural selection must align with this mechanistic characterisation. Secondly, natural selection should genuinely be responsible for the attributed phenomenon. While philosophers often posit producing adaptation as the quintessential phenomenon, Pérez-González and (...) Luque challenge this perspective, contending that not all instances of natural selection are cases where natural selection produces adaptation. This paper further supports Pérez-González and Luque’s objection and demonstrates that natural selection is also not responsible for the increased frequency of traits with a greater expected number of offspring. Furthermore, the paper argues that even if there is a phenomenon that allows for the mechanistic characterisation of natural selection to encompass all instances, it is improbable that natural selection assumes responsibility for it. Consequently, characterising natural selection as a mechanism emerges as an implausible stance. (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)

Despite the burgeoning interest in new and more complex accounts of the organism-environment dyad by biologists and philosophers, little attention has been paid in the resulting discussions to the history of these ideas and to their deployment in disciplines outside biology—especially in the social sciences. Even in biology and philosophy, there is a lack of detailed conceptual models of the organism-environment relationship. This volume is designed to fill these lacunae by providing the first multidisciplinary discussion of the topic of organism-environment (...) interaction. It brings together scholars from history, philosophy, psychology, anthropology, medicine, and biology to discuss the common focus of their work: entangled life, or the complex interaction of organisms and environments. (shrink)

The semantic view of theories is normally considered to be an ac-count of theories congenial to Scientific Realism. Recently, it has been argued that Ontic Structural Realism could be fruitfully applied, in combination with the semantic view, to some of the philosophical issues peculiarly related to bi-ology. Given the central role that models have in the semantic view, and the relevance that mathematics has in the definition of the concept of model, the fo-cus will be on population genetics, which is (...) one of the most mathematized areas in biology. We will analyse some of the difficulties which arise when trying to use Ontic Structural Realism to account for evolutionary biology. (shrink)

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)

We present a logically detailed case-study of Darwinian evolutionary explanation. Special features of Darwin’s explanatory schema made it an unusual theoretical breakthrough, from the point of view of the philosophy of science. The schema employs no theoretical terms, and puts forward no theoretical hypotheses. Instead, it uses three observational generalizations—Variability, Heritability and Differential Reproduction—along with an innocuous assumption of Causal Efficacy, to derive Adaptive Evolution as a necessary consequence. Adaptive Evolution in turn, with one assumption of scale (‘Deep Time’), implies (...) the observational generalization of Adaptation. It is a fascinating methodological task to regiment the premises and make the reasoning both rigorous and clear. Doing so reveals how surprisingly small an amount of mathematics is needed in order to carry out the argument. The investigation also reveals the crucial role played by heritability, and how heritability itself admits of Darwinian explanation. (shrink)

The propensity nature of evolutionary fitness has long been appreciated and is nowadays amply discussed. The discussion has, however, on occasion followed long standing conflations in the philosophy of probability literature between propensities, probabilities, and frequencies. In this paper, I apply a more recent conception of propensities in modelling practice to some of the key issues, regarding the mathematical representation of fitness and how it may be regarded as explanatory. The ensuing complex nexus of fitness emphasises the distinction between biological (...) propensities and the probability distributions over offspring numbers that they give rise to; and how critical it is to distinguish the possession conditions of the underlying dispositional properties from those of their probabilistic manifestations. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. 1 Introduction2 Biological Population, Broad and Narrow3 Difficulties with Narrow Biological Population Conditions3.1 Against the genealogical condition3.2 Against the conspecificity condition3.3 Against the proximity condition3.4 Against the typology condition4 Causal Connectivity5 Massively Multidimensional Population Constructs6 Population Uniqueness and Natural Selection6.1 Statisticalism and its discontents6.2 Price at what price?7 Conclusion. (shrink)

This article presents a challenge that those philosophers who deny the causal interpretation of explanations provided by population genetics might have to address. Indeed, some philosophers, known as statisticalists, claim that the concept of natural selection is statistical in character and cannot be construed in causal terms. On the contrary, other philosophers, known as causalists, argue against the statistical view and support the causal interpretation of natural selection. The problem I am concerned with here arises for the statisticalists because the (...) debate on the nature of natural selection intersects the debate on whether mathematical explanations of empirical facts are genuine scientific explanations. I argue that if the explanations provided by population genetics are regarded by the statisticalists as non-causal explanations of that kind, then statisticalism risks being incompatible with a naturalist stance. The statisticalist faces a dilemma: either she maintains statisticalism but has to renounce naturalism; or she maintains naturalism but has to content herself with an account of the explanations provided by population genetics that she deems unsatisfactory. This challenge is relevant to the statisticalists because many of them see themselves as naturalists. (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)

A prominent approach to scientific explanation and modeling claims that for a model to provide an explanation it must accurately represent at least some of the actual causes in the event's causal history. In this paper, I argue that many optimality explanations present a serious challenge to this causal approach. I contend that many optimality models provide highly idealized equilibrium explanations that do not accurately represent the causes of their target system. Furthermore, in many contexts, it is in virtue of (...) their independence of causes that optimality models are able to provide a better explanation than competing causal models. Consequently, our account of explanation and modeling must expand beyond the causal approach. (shrink)

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that (...) unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible. Others suggest that there is a set of necessary features that can unify all explanations under a single account Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock’s dilemma. (shrink)

This paper analyzes two ways idealized biological models produce factive scientific understanding. I then argue that models can provide factive scientific understanding of a phenomenon without providing an accurate representation of the features of their real-world target system. My analysis of these cases also suggests that the debate over scientific realism needs to investigate the factive scientific understanding produced by scientists’ use of idealized models rather than the accuracy of scientific models themselves.

In this paper, we argue that rather than exclusively focusing on trying to determine if an idealized model fits a particular account of scientific explanation, philosophers of science should also work on directly analyzing various explanatory schemas that reveal the steps and justification involved in scientists’ use of highly idealized models to formulate explanations. We develop our alternative methodology by analyzing historically important cases of idealized statistical modeling that use a three-step explanatory schema involving idealization, mathematical operation, and explanatory interpretation.

This paper explores how work in the philosophy of science can be used when teaching scientific content to science students and when training future science teachers. I examine the debate on the concept of fitness in biology and in the philosophy of biology to show how conceptual pluralism constitutes a problem for the conceptual change model, and how philosophical work on conceptual clarification can be used to address that problem. The case of fitness exemplifies how the philosophy of science offers (...) tools to resolve teaching difficulties and make the teaching of scientific concepts more adequate to the actual state of affairs in science. (shrink)

The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...) five explananda have been assigned to the theory of natural selection and that four of them may be actually considered explananda of natural selection. For the second question, we claim that a probabilistic conception of causality and the statistical relevance concept of explanation are both good models for understanding the explanatory role of natural selection. We review the biological and philosophical disputes about the explanatory role of natural selection and formalize some explananda in probabilistic terms using classical results from population genetics. Most of these explananda have been discussed in philosophical terms but some of them have been mixed up and confused. We analyze and set the limits of these problems. (shrink)

A major debate in the philosophy of biology centers on the question of how we should understand the causal structure of natural selection. This debate is polarized into the causal and statistical positions. The main arguments from the statistical side are that a causal construal of the theory of natural selection's central concept, fitness, either (i) leads to inaccurate predictions about population dynamics, or (ii) leads to an incoherent set of causal commitments. In this essay, I argue that neither the (...) predictive inaccuracy nor the incoherency arguments successfully undermine the causal account of fitness. 1 Introduction2 The Importance of Trait Fitness3 Trait Fitness is not a Silver Bullet4 The Fundamental Incoherency Argument5 Car Racing and Trait Fitness Reversals6 Population Subdivisions and Evolution7 The STP and the Argument for the Incoherency of the Causal Account of Fitness8 Conclusions. (shrink)

A major debate in the philosophy of biology centers on the question of how we should understand the causal structure of natural selection. This debate is polarized into the causal and statistical positions. The main arguments from the statistical side are that a causal construal of the theory of natural selection's central concept, fitness, either (i) leads to inaccurate predictions about population dynamics, or (ii) leads to an incoherent set of causal commitments. In this essay, I argue that neither the (...) predictive inaccuracy nor the incoherency arguments successfully undermine the causal account of fitness. 1 Introduction2 The Importance of Trait Fitness3 Trait Fitness is not a Silver Bullet4 The Fundamental Incoherency Argument5 Car Racing and Trait Fitness Reversals6 Population Subdivisions and Evolution7 The STP and the Argument for the Incoherency of the Causal Account of Fitness8 Conclusions. (shrink)

Biological fitness is a foundational concept in the theory of natural selection. Natural selection is often defined in terms of fitness differences as “any consistent difference in fitness (i.e., survival and reproduction) among phenotypically different biological entities” (Futuyma 1998, 349). And in Lewontin’s (1970) classic articulation of the theory of natural selection, he lists fitness differences as one of the necessary conditions for evolution by natural selection to occur. Despite this foundational position of fitness, there remains much debate over the (...) nature of fitness, especially whether fitness differences can truly be said to cause evolutionary change. In recent years these debates have crystalized into two camps: (1) causalists, who see fitness differences as being one of the causes of evolutionary change, and (2) statisticalists, who deny the causal efficacy of fitness and instead hold that “fitness is a mere statistical, noncausal property of trait types” (Walsh 2010, 148). (shrink)

The debate between the dynamical and the statistical interpretations of natural selection is centred on the question of whether all explanations that employ the concepts of natural selection and drift are reducible to causal explanations. The proponents of the statistical interpretation answer negatively, but insist on the fact that selection/drift arguments are explanatory. However, they remain unclear on where the explanatory power comes from. The proponents of the dynamical interpretation answer positively and try to reduce selection/drift arguments to some of (...) the most prominent accounts of causal explanation. In turn, they face the criticism raised by statisticalists that current accounts of causation have to be violated in some of their core conditions or otherwise used in a very loose manner in order to account for selection/drift explanations. We propose a reconciliation of both interpretations by conveying evolutionary explanations within the unificationist model of scientific explanation. Therefore, we argue that the explanatory power in natural selection arguments is a result of successful unification of individual- and population-level facts. A short case study based on research on sympatric speciation will be presented as an example of how population- and individual-level facts are unified to explain the morphological mosaic of bill shape in island scrub jays. (shrink)

One hotly debated philosophical question in the analysis of evolutionary theory concerns whether or not evolution and the various factors which constitute it may profitably be considered as analogous to “forces” in the traditional, Newtonian sense. Several compelling arguments assert that the force picture is incoherent, due to the peculiar nature of genetic drift. I consider two of those arguments here – that drift lacks a predictable direction, and that drift is constitutive of evolutionary systems – and show that they (...) both fail to demonstrate that a view of genetic drift as a force is untenable. I go on to diagnose the reasons for the stubborn persistence of this problem, considering two open philosophical issues and offering some preliminary arguments in support of the force metaphor. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

Over the past decade philosophers of biology have discussed whether evolutionary theory is a causal theory or a phenomenological study of evolution based solely on the statistical features of a population. This article reviews this controversy from three aspects, respectively concerning the assumptions, applications, and explanations of evolutionary theory, with a view to arriving at a definite conclusion in each contention. In so doing I also argue that an implicit methodological assumption shared by both sides of the debate, namely the (...) overconfidence in conceptual analysis as a tool to understand the scientific theory, is the real culprit that has both generated the problem and precluded its solution for such a long time. (shrink)

Causalism is the thesis that natural selection can cause evolution. A standard argument for causalism involves showing that a hypothetical intervention on some population-level property that is identified with natural selection will result in evolution. In a pair of articles, one of which recently appeared in the pages of this journal, Jun Otsuka has put forward a quite different argument for causalism. Otsuka attempts to show that natural selection can cause evolution by considering a hypothetical intervention on an individual-level property. (...) Specifically, Otsuka identifies natural selection with the causal relationship between a trait and fitness, claims an intervention on the strength of this relationship can cause evolution, then concludes that natural selection can cause evolution. Below I describe why Otsuka’s argument for causalism is unconvincing. Central to my criticism is that Otsuka’s argument works only if one adopts an indefensible account of natural selection, according to which natural selection can occur in the absence of trait or fitness variation. I go on to explain why any attempt to demonstrate the truth of causalism via a hypothetical intervention on an individual-level property would appear to require one to adopt an account of natural selection that is inadequate for the same reason. This in turn means the plausibility of causalism does indeed depend on the plausibility of the claim that population-level properties, which supervene on the properties of the individuals in the population, can be causally efficacious. (shrink)

The statistical interpretation of the Theory of Natural Selection claims that natural selection and drift are statistical features of mathematical aggregates of individual-level events. Natural selection and drift are not themselves causes. The statistical interpretation is motivated by a metaphysical conception of individual priority. Recently, Millstein, Skipper, and Dietrich (2009) have argued (a) that natural selection and drift are physical processes, and (b) that the statistical interpretation rests on a misconception of the role of mathematics in biology. Both theses are (...) contested. (shrink)

In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track can (...) be captured by three features - namely, quasi-axiomaticity (QA), generative potential (GP), and empirical shielding (ES) - which are exhibited to a maximal degree by the examples Friedman deploys, particularly in his analysis of Newtonian mechanics. I argue that not all varieties of 'constitutivity' can be captured by the kind of gradualism implicit in Friedman's view, although developing the gradualism itself might provide useful insights. To show this, I analyse the function of the Hardy-Weinberg principle (HWP) in population genetics in terms of its QA, GP, and ES. Whereas the HWP does not count as constitutive in classical philosophical interpretations (Sober 1984), nor does it within Friedman's framework, it does nonetheless perform a minimally constitutive function. By means of historical details and considerations on the prospects of replacing the HWP, I show that the HWP is minimally constitutive by being a counterfactual instantiation of a paradigmatically constitutive stability principle, where the latter might itself be regarded as an enabling condition for a variety of modelling practices across the sciences. (shrink)

Matthen (Philos Sci 76(4):464–487, 2009) argues that explanations of evolutionary change that appeal to natural selection are statistically abstractive explanations, explanations that ignore some possible explanatory partitions that in fact impact the outcome. This recognition highlights a difficulty with making selective analyses fully rigorous. Natural selection is not about the details of what happens to any particular organism, nor, by extension, to the details of what happens in any particular population. Since selective accounts focus on tendencies, those factors that impact (...) the actual outcomes but do not impact the tendencies must be excluded. So, in order to properly exclude the factors irrelevant to selection, the relevant factors must be identified, and physical processes, environments, and populations individuated on the basis of being relevantly similar for the purposes of selective accounts. Natural selection, on this view, becomes in part a measure of the robustness of particular kinds of outcomes given variations over some kinds of inputs. (shrink)

In this paper, I identify two general positions with respect to the relationship between environment and natural selection. These positions consist in claiming that selective claims need and, respectively, need not be relativized to homogenous environments. I then show that adopting one or the other position makes a difference with respect to the way in which the effects of selection are to be measured in certain cases in which the focal population is distributed over heterogeneous environments. Moreover, I show that (...) these two positions lead to two different interpretations—the Pricean and contextualist ones—of a type of selection scenarios in which multiple groups varying in properties affect the change in the metapopulation mean of individual-level traits. Showing that these two interpretations stem from different attitudes towards environmental homogeneity allows me to argue: that, unlike the Pricean interpretation, the contextualist interpretation can only claim that drift or selection is responsible for the change in frequency of the focal trait in a given metapopulation if details about whether or not group formation is random are specified; that the traditional main objection against the Pricean interpretation—consisting in arguing that the latter takes certain side-effects of individual selection to be effects of group selection—is unconvincing. This leads me to suggest that the ongoing debate about which of the two interpretations is preferable should concentrate on different issues than previously thought. (shrink)

This paper is aimed at identifying how a model’s explanatory power is constructed and identified, particularly in the practice of template-based modeling (Humphreys, Philos Sci 69:1–11, 2002; Extending ourselves: computational science, empiricism, and scientific method, 2004), and what kinds of explanations models constructed in this way can provide. In particular, this paper offers an account of non-causal structural explanation that forms an alternative to causal–mechanical accounts of model explanation that are currently popular in philosophy of biology and cognitive science. Clearly, (...) defences of non-causal explanation are far from new (e.g. Batterman, Br J Philos Sci 53:21–38, 2002a; The devil in the details: asymptotic reasoning in explanation, reduction, and emergence, 2002b; Pincock, Noûs 41:253–275, 2007; Mathematics and scientific representation 2012; Rice, Noûs. doi:10.1111/nous.12042, 2013; Biol Philos 27:685–703, 2012), so the targets here are focused on a particular type of robust phenomenon and how strong invariance to interventions can block a range of causal explanations. By focusing on a common form of model construction, the paper also ties functional or computational style explanations found in cognitive science and biology more firmly with explanatory practices across model-based science in general. (shrink)

Recently some philosophers have emphasized a potentially irreconcilable conceptual antagonism between the statistical characterization of natural selection and the standard scientific discussion of natural selection in terms of forces and causes. Other philosophers have developed an account of the causal character of selectionist statements represented in terms of counterfactuals. I examine the compatibility between such statisticalism and counterfactually based causal accounts of natural selection by distinguishing two distinct statisticalist claims: firstly the suggested impossibility for natural selection to be a cause (...) acting upon populations and secondly the conceptualization that all evolutionary causes occur at the level of interactions between individual organisms. I argue that deriving the latter from the former involves supplementary assumptions concerning precisely what causation is. I critically examine two of these assumptions purportedly preventing natural selection being regarded as a cause: the locality claim and the modularity claim. I conclude that justifying the strongest version of statisticalism—i.e. evolutionary causation only occurs at the level of individual interactions between organisms—would require further metaphysical arguments that are likely to be deemed highly problematic. Additionally, I argue that such a metaphysical position would be considered incongruous with both our scientific and ordinary use of the concepts of causality and explanation as employed within our everyday epistemological framework. (shrink)

A subarea of the debate over the nature of evolutionary theory addresses what the nature of the explanations yielded by evolutionary theory are. The statisticalist line is that the general principles of evolutionary theory are not only amenable to a mathematical interpretation but that they need not invoke causes to furnish explanations. Causalists object that construction of these general principles involves crucial causal assumptions. A recent view claims that some biological explanations are statistically autonomous explanations (SAEs) whereby phenomena are accounted (...) for statistically and which prescind from micro-causal details. I raise three major problems for this account and then advance a view which unifies SAEs as mathematical explanations: the MSAE view. The MSAE view not only resolves the issues bedeviling the original SAE account but serves to importantly broaden the class of non-causal explanations in population biology. (shrink)

In this article, I propose a new way of thinking about natural necessity and a new way of thinking about biological laws. I suggest that much of the lack of progress in making a positive case for distinctively biological laws is that we’ve been looking for necessity in the wrong place. The trend has been to look for exceptionlessness at the level of the outcomes of biological processes and to build one’s claims about necessity off of that. However, as Beatty (...) (1995) observed, even when we are lucky enough to find a biological ‘rule’ of some sort, that rule is apt to be a victim of ‘the rule-breaking capabilities of evolutionary change’. If indeed no distinctively biological generalization—even an exceptionless one—is safe, we need to locate necessity elsewhere. A good place to start is, I think, precisely the point at which Beatty sees the possibility of lawhood as breaking down—namely, at the level of chances. 1 The ‘Necessity’ Objection to Biological Laws2 Necessary Chances2.1 Necessary chances: random drift2.2 Necessary chances: fitness3 But is it Biological?4 Conclusion. (shrink)

Analogies between Newtonian mechanics and evolutionary processes are powerful but not infinitely versatile tools for generating explanations of particular biological phenomena. Their explanatory range is sensitive to a preliminary decision about which processes count as background conditions and which as special forces. Here I argue that the defenders of the zero-force evolutionary law are mistaken in defending their decision as the only appropriate one. The Hardy–Weinberg principle remains a viable option that is consistent with the epistemic role of Newton’s own (...) first law, and the strengths and weaknesses of each analogy are sufficiently distinct to justify their continued coexistence. (shrink)

What is natural selection? I address this question by exploring the relation between two debates: Is natural selection a mechanism? Is natural selection a causal or a statistical theory? I argue that the first can be assessed only relative to a model and that, following the second, there are two fundamentally different and independent kinds of models, Modern-Synthesis and Darwinian models. MS-models, I argue, are not mechanistic even if they are causal. D-models, in contrast, are mechanistic. A causal-mechanistic interpretation of (...) D-models is thus compatible with a statistical interpretation of MS-models. Natural selection, I conclude, lacks a single, unifying nature. (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)