Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.

Recently, a number of philosophers of biology have endorsed views about random drift that, we will argue, rest on an implicit assumption that the meaning of concepts such as drift can be understood through an examination of the mathematical models in which drift appears. They also seem to implicitly assume that ontological questions about the causality of terms appearing in the models can be gleaned from the models alone. We will question these general assumptions by showing how the same equation (...) — the simple 2 = p2 + 2pq + q2 — can be given radically different interpretations, one of which is a physical, causal process and one of which is not. This shows that mathematical models on their own yield neither interpretations nor ontological conclusions. Instead, we argue that these issues can only be resolved by considering the phenomena that the models were originally designed to represent and the phenomena to which the models are currently applied. When one does take those factors into account, starting with the motivation for Sewall Wright’s and R.A. Fisher’s early drift models and ending with contemporary applications, a very different picture of the concept of drift emerges. On this view, drift is a term for a set of physical processes, namely, indiscriminate sampling processes. (shrink)

‘Gouldian arguments’ appeal to the contingency of a scientific domain to establish that domain’s autonomy from some body of theory. For instance, pointing to evolutionary contingency, Stephen Jay Gould suggested that natural selection alone is insufficient to explain life on the macroevolutionary scale. In analysing contingency, philosophers have provided source-independent accounts, understanding how events and processes structure history without attending to the nature of those events and processes. But Gouldian Arguments require source-dependent notions of contingency. An account of contingency is (...) source-dependent when it is indexed to some pattern and some process. Positions like Gould’s do not turn on the mere fact of life’s contingency—that life’s shape could have been different due to its sensitivity to initial conditions, path-dependence or stochasticity. Rather, Gouldian arguments require that the contingency is due to particular kinds of processes: in this case, those which microevolutionary theory cannot account for. This source-dependent perspective clarifies both debates about the nature and importance of contingency, and empirical routes for testing Gould’s thesis. (shrink)

Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.

In this article, I consider the term “environment” in various claims and models by evolutionists and ecologists. I ask whether “environment” is amenable to a philosophical explication, in the same way some key terms of evolutionary theorizing such as “fitness,” “species,” or more recently “population” have been. I will claim that it cannot. In the first section, I propose a typology of theoretical terms, according to whether they are univocal or equivocal, and whether they have been the object of formal (...) or conceptual attempts of clarification. “Environment” will appear to be in a position similar to “population,” yet almost no extant attempt has been made to make sense of its meaning and reference. In the second section, I will present several theoretical claims or issues that refer to “environment” in apparently very diverse ways, but always supposing a contrastive term, which is not always the same. The third section directly considers models in evolution and in ecology, and asks “where” in them is the environment term. The fourth section proposes that “environment” refers to a distinction between a varying and an invariant term, but shows that this does not exhaust its meaning, which requires making more conceptual differences. Then, I take on the suggestion that there might be two “environment” terms, one in ecology and one in evolution, but show that is not the case. Finally I center on the specific notion of “complex environment,” which is the object of several research programs, and propose a typology of “complex environments” across theories. (shrink)

I consider recent uses of the notion of neutrality in evolutionary biology and ecology, questioning their relevance to the kind of explanation recently labeled ‘topological explanation’. Focusing on fitness landscapes and genotype-phenotype maps, I explore the explanatory uses of neutral subspaces, as modeled in two perspectives: hyperdimensional fitness landscapes and RNA sequence-structure maps. I argue that topological properties of such spaces account for features of evolutionary systems: respectively, capacity for adaptive evolution toward global optima and mutational robustness of genotypes. Thus (...) many models appealing to “neutral” manifolds provide topological alternatives to hypothetical mechanisms. (shrink)

‘Statisticalists’ argue that the individual interactions of organisms taken together constitute natural selection. On this view, natural selection is an aggregated effect of interactions rather than some added cause acting on populations. The statisticalists’ view entails that natural selection and drift are indistinguishable aggregated effects of interactions, so that it becomes impossible to make a difference between them. The present paper attempts to make sense of the difference between selection and drift, given the main insights of statisticalism; basically, it will (...) disentangle the various kinds of indistinguishability between selection and drift that happen within biology, by examining the epistemological and metaphysical nature of the distinction between selection and drift. It will be based on a ‘difference-making account’ of selection. The first section will explicate the inscrutability of selection and drift, its various types in the statisticalist writings, and its implications. The second section specifies concepts of natural selection and drift in the difference making account of selection I am using, and shows that one can derive from this the statistical signatures of selection and drift. On this basis I focus on one sort of indistinguishability issue about selection and drift, which I call epistemic opacity, and explain why it mostly affects small populations. The last section explains why epistemic opacity does not raise an genuine epistemic problem for evolutionary biology. (shrink)

Among philosophers, controversy over the notion of drift in population genetics is ongoing. This is at least partly because the notion of drift has an ambiguous usage among population geneticists. My goal in this paper is to explicate the causal dimension of drift, to say what causal influences are responsible for the stochasticity in population genetics models. It is commonplace for population genetics to oppose the influence of selection to that of drift, and to consider how the dynamics of populations (...) are altered when each has greater or lesser influence. I define the causes that are referred to as drift when researchers speak this way. Introduction Populations and Variant Types The Cause–Effect Ambiguity of Drift Non-directional Factors in Population Genetics How N ev Is Used in Population Genetics Causal Conceptions of Drift 6.1 The Millstein/Beatty conception of drift 6.2 Rosenberg and Bouchard: Drift as initial conditions NINPICs 7.1 Why drift is instituted by NINPICs 7.2 How NINPICS work 7.3 NINPICs and random sampling 7.4 Independent sampling and effective population size 7.5 Variance in progeny number 7.6 Population effects of NINPICs NINPICs and the Stochastic Character of Selection Theory Conclusion Appendix CiteULike Connotea Del.icio.us What's this? (shrink)

Fitness is a central but notoriously vexing concept in evolutionary biology. The propensity interpretation of fitness is often regarded as the least problematic account for fitness. It ties an individual's fitness to a probabilistic capacity to produce offspring. Fitness has a clear causal role in evolutionary dynamics under this account. Nevertheless, the propensity interpretation faces its share of problems. We discuss three of these. We first show that a single scalar value is an incomplete summary of a propensity. Second, we (...) argue that the widespread method of “abstracting away” environmental idiosyncrasies by averaging over reproductive output in different environments is not a valid approach when environmental changes are irreversible. Third, we point out that expanding the range of applicability for fitness measures by averaging over more environments or longer time scales (so as to ensure environmental reversibility) reduces one's ability to distinguish selectively relevant differences among individuals because of mutation and eco‐evolutionary feedbacks. This series of problems leads us to conclude that a general value of fitness that is both explanatory and predictive cannot be attained. We advocate for the use of propensity‐compatible methods, such as adaptive dynamics, which can accommodate these difficulties. (shrink)

. Philosophers and scientists often cite ontic factors when explaining the methods and success of scientific inquiry. That is, the adoption of a method or approach is explained in reference to the kind of system in which the scientist is interested: these are explanations of why scientists do what they do, that appeal to properties of their target systems. We present a framework for understanding such “Opticks to his Principia. Newton’s optical work is largely experiment-driven, while the Principia is primarily (...) mathematical, so usually, each work is taken to exemplify a different kind of science. However, Newton himself often presented them in terms of a largely consistent method. We use our framework to articulate an original and plausible position: that the differences between the Opticks and the Principia are due to the kinds of systems targeted. That is, we provide an ontic-driven explanation of methodological differences. We suspect that ontic factors should have a more prominent role in historical explanations of scientific method and development. (shrink)

Several recent arguments by philosophers of biology have challenged the traditional view that evolutionary factors, such as drift and selection, are genuine causes of evolutionary outcomes. In the case of drift, advocates of the statistical theory argue that drift is merely the sampling error inherent in the other stochastic processes of evolution and thus denotes a mathematical, rather than causal, feature of populations. This debate has largely centered around one particular model of drift, the Wright–Fisher model, and this has contributed (...) to the plausibility of the statisticalists’ arguments. However, an examination of alternative, predictively inequivalent models shows that drift is a genuine cause that can be manipulated to change population outcomes. This case study illustrates the influence of methodological assumptions on ontological judgments, particularly the pernicious effect of focusing on a particular model at the expense of others and confusing its assumptions and idealizations for true claims about the phenomena being modeled. (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)

ABSTRACTIn Darwinian Population and Natural Selection, Peter Godfrey-Smith brought the topic of natural selection back to the forefront of philosophy of biology, highlighting different issues surro...

Drift is often characterized in statistical terms. Yet such a purely statistical characterization is ambiguous for it can accept multiple physical interpretations. Because of this ambiguity it is important to distinguish what sorts of processes can lead to this statistical phenomenon. After presenting a physical interpretation of drift originating from the most popular interpretation of fitness, namely the propensity interpretation, I propose a different one starting from an analysis of the concept of drift made by Godfrey-Smith. Further on, I show (...) how my interpretation relates to previous attempts to make sense of the notion of expected value in deterministic setups. The upshot of my analysis is a physical conception of drift that is compatible with both a deterministic and indeterministic world. (shrink)

This thesis focuses on models of conceptual change in science and philosophy. In particular, I developed a new bootstrapping methodology for studying conceptual change, centered around the formalization of several popular models of conceptual change and the collective assessment of their improved formal versions via nine evaluative dimensions. Among the models of conceptual change treated in the thesis are Carnap’s explication, Lakatos’ concept-stretching, Toulmin’s conceptual populations, Waismann’s open texture, Mark Wilson’s patches and facades, Sneed’s structuralism, and Paul Thagard’s conceptual revolutions. (...) -/- In order to analyze and compare the conception of conceptual change provided by these different models, I rely on several historical reconstructions of episodes of scientific conceptual change. The historical episodes of scientific change that figure in this work include the emergence of the morphological concept of fish in biological taxonomies, the development of scientific conceptions of temperature, the Church-Turing thesis and related axiomatizations of effective calculability, the history of the concept of polyhedron in 17th and 18th century mathematics, Hamilton’s invention of the quaternions, the history of the pre-abstract group concepts in 18th and 19th century mathematics, the expansion of Newtonian mechanics to viscous fluids forces phenomena, and the chemical revolution. I will also present five different formal and informal improvements of four specific models of conceptual change. I will first present two different improvements of Carnapian explication, a formal and an informal one. My informal improvement of Carnapian explication will consist of a more fine-grained version of the procedure that adds an intermediate, third step to the two steps of Carnapian explication. I will show how this novel three-step version of explication is more suitable than its traditional two-step relative to handle complex cases of explications. My second, formal improvement of Carnapian explication will be a full explication of the concept of explication itself within the theory of conceptual spaces. By virtue of this formal improvement, the whole procedure of explication together with its application procedures and its pragmatic desiderata will be reconceptualized as a precise procedure involving topological and geometrical constraints inside the theory of conceptual spaces. My third improved model of conceptual change will consist of a formal explication of Darwinian models of conceptual change that will make vast use of Godfrey-Smith’s population-based Darwinism for targeting explicitly mathematical conceptual change. My fourth improvement will be dedicated instead to Wilson’s indeterminate model of conceptual change. I will show how Wilson’s very informal framework can be explicated within a modified version of the structuralist model-theoretic reconstructions of scientific theories. Finally, the fifth improved model of conceptual change will be a belief-revision-like logical framework that reconstructs Thagard’s model of conceptual revolution as specific revision and contraction operations that work on conceptual structures. -/- At the end of this work, a general conception of conceptual change in science and philosophy emerges, thanks to the combined action of the three layers of my methodology. This conception takes conceptual change to be a multi-faceted phenomenon centered around the dynamics of groups of concepts. According to this conception, concepts are best reconstructed as plastic and inter-subjective entities equipped with a non-trivial internal structure and subject to a certain degree of localized holism. Furthermore, conceptual dynamics can be judged from a weakly normative perspective, bound to be dependent on shared values and goals. Conceptual change is then best understood, according to this conception, as a ubiquitous phenomenon underlying all of our intellectual activities, from science to ordinary linguistic practices. As such, conceptual change does not pose any particular problem to value-laden notions of scientific progress, objectivity, and realism. At the same time, this conception prompts all our concept-driven intellectual activities, including philosophical and metaphilosophical reflections, to take into serious consideration the phenomenon of conceptual change. An important consequence of this conception, and of the analysis that generated it, is in fact that an adequate understanding of the dynamics of philosophical concepts is a prerequisite for analytic philosophy to develop a realistic and non-idealized depiction of itself and its activities. (shrink)