How do models represent reality? There are two conditions that scientific models must satisfy to be representations of real systems, the aboutness condition and the epistemic condition. In this article, I critically assess the two main fictionalist theories of models as representations, the indirect fiction view and the direct fiction view, with respect to these conditions. And I develop a novel proposal, what I call ‘the new fiction view of models’. On this view, models are akin to fictional stories; they (...) represent real-world phenomena if they stand in a denotation relation with reality; and they enable knowledge of reality via the generation of theoretical hypotheses, model–world comparisons and direct attributions. (shrink)

This survey of major developments in North American philosophy of science begins with the mid-1960s consolidation of the disciplinary synthesis of internalist history and philosophy of science (HPS) as a response to criticisms of logical empiricism. These developments are grouped for discussion under the following headings: historical metamethodologies, scientific realisms, philosophies of the special sciences, revivals of empiricism, cognitivist naturalisms, social epistemologies, feminist theories of science, studies of experiment and the disunity of science, and studies of science as practice and (...) culture. A unifying theme of the survey is the relation between historical metamethodologists and scientific realists, which dominated philosophical work in the late 1970s. I argue that many of the alternative cognitive naturalisms, social epistemologies, and feminist theories that have been proposed can be understood as analogues to the differences between metamethodological theories of scientific rationality and realist accounts of successful reference to real causal processes. Recent work on experiment, scientific practice, and the culture of science may, however, challenge the underlying conception of the field according to which realism and historical rationalism (or their descendants) are the important alternatives available, and thus may take philosophy of science in new directions. (shrink)

That biology provides explanations is not open to doubt. But how it does so must be a vexed question for those who deny that biology embodies laws or other generalizations with the sort of explanatory force that the philosophy of science recognizes. The most common response to this problem has involved redefining law so that those grammatically general statements which biologists invoke in explanations can be counted as laws. But this terminological innovation cannot identify the source of biology's explanatory power. (...) I argue that because biological science is historical, the problem of biological explanation can be assimilated to the parallel problem in the philosophy of history, and that the problem was solved by Carl Hempel. All we need to do is recognize that the only laws that biology—in all its compartments from the molecular onward—has or needs are the laws of natural selection. (shrink)

This article elaborates on McShea and Brandon’s idea that drift is unlike the rest of the evolutionary factors because it is constitutive rather than imposed on the evolutionary process. I show that the way they spelled out this idea renders it inadequate and is the reason why it received some objections. I propose a different way in which their point could be understood, that rests on two general distinctions. The first is a distinction between the underlying mathematical apparatus used to (...) formulate a theory and a concept proposed by that theory. With the aid of a formal reconstruction of a population genetic model, I show that drift belongs to the first category. That is, that drift is constitutive of population genetics in the same sense that multiplication is constitutive in classical mechanics, or that circle is constitutive in Ptolemaic astronomy. The second distinction is between eliminating a concept from a theory and setting its value to zero. I will show that even though drift can be set to zero just like the rest of the evolutionary factors, eliminating drift is much harder than eliminating those other factors, since it would require changing the entire mathematical apparatus of standard population genetic theory. I conclude by drawing some other implications from the proposed formal reconstruction. (shrink)

This article elaborates on McShea and Brandon’s idea that drift is unlike the rest of the evolutionary factors because it is constitutive rather than imposed on the evolutionary process. I show that the way they spelled out this idea renders it inadequate and is the reason why it received some objections. I propose a different way in which their point could be understood, that rests on two general distinctions. The first is a distinction between the underlying mathematical apparatus used to (...) formulate a theory and a concept proposed by that theory. With the aid of a formal reconstruction of a population genetic model, I show that drift belongs to the first category. That is, that drift is constitutive of population genetics in the same sense that multiplication is constitutive in classical mechanics, or that circle is constitutive in Ptolemaic astronomy. The second distinction is between eliminating a concept from a theory and setting its value to zero. I will show that even though drift can be set to zero just like the rest of the evolutionary factors, eliminating drift is much harder than eliminating those other factors, since it would require changing the entire mathematical apparatus of standard population genetic theory. I conclude by drawing some other implications from the proposed formal reconstruction. (shrink)

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)

Which domains of biology do philosophers of biology primarily study? The fact that philosophy of biology has been dominated by an interest for evolutionary biology is widely admitted, but it has not been strictly demonstrated. Here I analyse the topics of all the papers published in Biology & Philosophy, just as the journal celebrates its thirtieth anniversary. I then compare the distribution of biological topics in Biology & Philosophy with that of the scientific journal Proceedings of the National Academy of (...) Science of the USA, focusing on the recent period 2003–2015. This comparison reveals a significant mismatch between the distributions of these topics. I examine plausible explanations for that mismatch. Finally, I argue that many biological topics underrepresented in philosophy of biology raise important philosophical issues and should therefore play a more central role in future philosophy of biology. (shrink)

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection is (...) the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism. (shrink)

The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and (...) momentum and establish a relation amongst the two variables, which we call Newton’s 2nd law. The specification of the unspecified elements of scientific laws, e.g. the force function in Newton’s 2nd law, is what would establish the link between the assertions of the theory and physical systems. In order to unravel how and with what conceptual resources scientific models are constructed, how they function and how they relate to theory, we need a view of theory-application that can accommodate our constructions of representation models. For this we need to expand our understanding of the process of abstraction to also explicate the process of specifying force functions etc. This is the second principal level at which abstraction enters in our theorising and in which I focus. In this paper, I attempt to elaborate a general analysis of the process of abstraction and concretisation involved in scientific- model construction, and argue why it provides an explication of the construction of models of the nuclear structure. (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)

This article characterizes various species concepts in terms of set-theoretic models that license biological inferences and illustrates the logical connections among different species concepts. Species in this construal are abstract models, rather than biological or even tangible entities, and relate to individual organisms via representation, rather than the membership or mereological whole/part relationship. The proposal sheds new light on vexed issues of species and situates them within broader philosophical contexts of model selection, scientific representation, and scientific realism.

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)

For a number of years, the debate in evolutionary biology over the ’levels of selection’ has attracted intense interest from philosophers of science. The main question concerns the level of the biological hierarchy at which natural selection occurs. Does selection act on organisms, genes, groups, colonies, demes, species, or some combination of these? According to traditional Darwinian theory the answer is the organism -- it is the differential survival and reproduction of individual organisms that drives the evolutionary process. But there (...) are alternative views too, including pluralist views which say that the choice between different levels of selection is often a matter of perspective, not empirical fact. (shrink)

The ‘levels of selection’ question is one of the most fundamental in evolutionary biology, for it arises directly from the logic of Darwinism. As is well-known, the principle of natural selection is entirely abstract; it says that any entities satisfying certain conditions will evolve by natural selection, whatever those entities are. (These conditions are: variability, associated fitness differences, and heritability (cf. Lewontin 1970).) This fact, when combined with the fact that the biological world is hierarchically structured, i.e. smaller biological units (...) are nested within larger ones, gives rise to the levels of selection question. For in principle, entities at many different hierarchical levels, above and below that of the ‘individual organism’, (e.g. gene, chromosome, cell, kin group, colony, lineage, species) can satisfy the requirements for Darwinian evolution. This possibility has long been recognised by biologists, from Darwin himself to contemporary proponents of ‘multi-level selection’; and there exist numerous biological phenomena which suggest that it has actually occurred. (shrink)

This paper compares two well-known arguments in the units of selection literature, one due to , the other due to . Both arguments concern the legitimacy of averaging fitness values across contexts and making inferences about the level of selection on that basis. The first three sections of the paper shows that the two arguments are incompatible if taken at face value, their apparent similarity notwithstanding. If we accept Sober and Lewontin's criterion for when averaging genic fitnesses across diploid genotypes (...) is illegitmate, we cannot accept Sober and Wilson's criterion for when averaging individual fitnesses across groups is illegitimate, and vice versa. The final section suggests a possible way of reconciling the two arguments, by invoking an ambiguity in the concept of genic selection. (shrink)

Two alternative statistical approaches to modelling multi-level selection in nature, both found in the contemporary biological literature, are contrasted. The simple covariance approach partitions the total selection differential on a phenotypic character into within-group and between-group components, and identifies the change due to group selection with the latter. The contextual approach partitions the total selection differential into different components, using multivariate regression analysis. The two approaches have different implications for the question of what constitutes group selection and what does not. (...) I argue that the contextual approach is theoretically preferable. This has important implications for a number of issues in the philosophical debate about the levels of selection. Introduction Group selection and the covariance formulation of selection The contextual approach A modification of the simple covariance approach Consequences: frameshifting and additivity 5.1 Frameshifting 5.2 Additivity Conclusion. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

Philosophers have traditionally addressed the issue of scientific unification in terms of theoretical reduction. Reductive models, however, cannot explain the occurrence of unification in areas of science where successful reductions are hard to find. The goal of this essay is to analyse a concrete example of integration in biology—the developmental synthesis—and to generalize it into a model of scientific unification, according to which two fields are in the process of being unified when they become explanatorily relevant to each other. I (...) conclude by suggesting that this methodological conception of unity, which is independent of the debate on the metaphysical foundations of science, is closely connected to the notion of interdisciplinarity. 1 Introduction2 Some Troubles with Theory Reduction3 Interfield and Mechanistic Unification4 Foundations of the Developmental Synthesis5 Explanatory Relevance6 Concluding Remarks. (shrink)

In this paper, I argue against John Beatty’s position in his paper “The Evolutionary Contingency Thesis” by counterexample. Beatty argues that there are no distinctly biological laws because the outcomes of the evolutionary processes are contingent. I argue that the heart of the Caspar–Klug theory of virus structure—that spherical virus capsids consist of 60T subunits (where T = k 2 + hk + h 2 and h and k are integers)—is a distinctly biological law even if the existence of spherical (...) viruses is evolutionarily contingent. (shrink)

An amended bootstrapping can avoid Christensen's counterexamples. Earman and Edidin argue that Christensen's examples to bootstrapping rely on his failure to analyze background knowledge. I add an additional condition to bootstrapping that is motivated by Glymour's remarks on variety of evidence. I argue that it avoids the problems that the examples raise. I defend the modification against the charge that it is holistic, and that it collapses into Bayesianism.

The status of population genetics has become hotly debated among biologists and philosophers of biology. Many seem to view population genetics as relatively unchanged since the Modern Synthesis and have argued that subjects such as development were left out of the Synthesis. Some have called for an extended evolutionary synthesis or for recognizing the insignificance of population genetics. Yet others such as Michael Lynch have defended population genetics, declaring "nothing in evolution makes sense except in the light of population genetics" (...) (a twist on Dobzhansky's famous slogan that "nothing in biology makes sense except in the light of evolution"). Missing from this discussion is the use of population genetics to shed light on ecology and vice versa, beginning in the 1940s and continuing until the present day. I highlight some of that history through an overview of traditions such as ecological genetics and population biology, followed by a slightly more in-depth look at a contemporary study of the endangered California Tiger Salamander. I argue that population genetics is a powerful and useful tool that continues to be used and modified, even if it isn't required for all evolutionary explanations or doesn't incorporate all the causal factors of evolution. (shrink)

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of mechanistic reasoning where it is (...) not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences. (shrink)

One of the most important contributions of Einstein to the philosophy of science is the distinction between two types of scientific theories: ‘principle’ and ‘constructive’ theories. More recently, Flores proposed a more general distinction, classifying scientific theories by their functional role into ‘framework’ and ‘interaction’ theories, attempting to solve some inadequacies in Einstein’s proposal. Here, based on an epistemic criterion, we present a generalised distinction which is an improvement over Flores approach. In this work (i) we evaluate the shortcomings related (...) to Flores’s proposal, (ii) we present an epistemological criterion that opens the door for a more general classification of any scientific theory in all of the natural science into two distinct groups, which we call ‘mechanistic theories’ and ‘structural theories’, and (iii) we show that such a criterion is connected to Flores’ proposal while overcoming issues of all previous approaches. (shrink)

Using the context of controversies surrounding evolutionary developmental biology (EvoDevo) and the possibility of an Extended Evolutionary Synthesis, I provide an account of theory structure as idealized theory presentations that are always incomplete (partial) and shaped by their conceptual content (material rather than formal organization). These two characteristics are salient because the goals that organize and regulate scientific practice, including the activity of using a theory, are heterogeneous. This means that the same theory can be structured differently, in part because (...) theory presentations (as idealizations) intentionally depart from different features known to be present in a theory. Since there are diverse and potentially incompatible theory structures derived from heterogeneous goals found in scientific practices, a question arises about the absence of a unifying theory structure in the background. The notion of a “theory façade” offers a fruitful perspective on this potentially unsettling result. (shrink)

The aim of this article is to discuss and develop the diagnose of the Hardy-Weinberg law made by van Fraassen (1987, p. 110), according to which: 1) that law cannot be considered a law used as an axiom for the classical population genetics as a whole, since it is an equilibrium-law that holds only under certain special conditions; 2) it just determines a subclass of models; 3) its generalization shades off into logical vacuity; and 4) more complex variants of the (...) law can be deduced for more realistic assumptions. The discussion and development of such a diagnose will be carried out with the notions of another semantic conceptions of theories, related to that of van Fraassen, namely, the structuralist view of theories, and a rational reconstruction of classical population genetics made within the framework of such a metatheory, also presented in this paper. (shrink)

I argue that four of the fundamental claims of those calling themselves `genic pluralists'Philip Kitcher, Kim Sterelny, and Ken Watersare defective. First, they claim that once genic selectionism is recognized, the units of selection problems will be dissolved. Second, Sterelny and Kitcher claim that there are no targets of selection. Third, Sterelny, Kitcher, and Waters claim that they have a concept of genic causation that allows them to give independent genic causal accounts of all selection processes. I argue that each (...) one of these claims is either false or misleading. Moreover, the challenge that arises from the availability of genic causal accounts, namely, the inability to choose on rational grounds among genic and higher-level accounts, is unsupported. (shrink)

Today's climate models are supported in a couple of ways that receive little attention from philosophers or climate scientists. In addition to standard 'model fit', wherein a model's simulation is compared to observational data, there is an additional type of confirmation available through the variety of instances of model fit. When a model performs well at fitting first one variable and then another, the probability of the model under some standard confirmation function, say, likelihood, goes up more than under each (...) individual case of fit alone. Thus, two instances of fit of distinct variables of a global climate model using distinct data sets considered collectively will provide stronger evidence for a model than either one of the instances considered individually. This has consequences for model robustness. Sets of models that produce robust results will, if their assumptions vary enough and they each are observationally sound, provide reasons to endorse common structures found in those models. Finally, independent empirical support for aspects and assumptions of the model provides an additional confirmational virtue for climate models, contrary to what is implied by some current philosophical writing on this topic. (shrink)

Most models of generational succession in sexually reproducing populations necessarily move back and forth between genic and genotypic spaces. We show that transitions between and within these spaces are usually hidden by unstated assumptions about processes in these spaces. We also examine a widely endorsed claim regarding the mathematical equivalence of kin-, group-, individual-, and allelic-selection models made by Lee Dugatkin and Kern Reeve. We show that the claimed mathematical equivalence of the models does not hold. *Received January 2007; revised (...) April 2008. †To contact the authors, please write to: Elisabeth Lloyd, Department of History and Philosophy of Science, 130 Goodbody Hall, Indiana University, Bloomington, IN 47405; e-mail: [email protected]; Richard Lewontin, Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA 02138; Marcus Feldman, Department of Biological Sciences, Stanford University, Stanford, CA 94305; e-mail: [email protected]. (shrink)

Most models of generational succession in sexually reproducing populations necessarily move back and forth between genic and genotypic spaces. We show that transitions between and within these spaces are usually hidden by unstated assumptions about processes in these spaces. We also examine a widely endorsed claim regarding the mathematical equivalence of kin-, group-, individual-, and allelic-selection models made by Lee Dugatkin and Kern Reeve. We show that the claimed mathematical equivalence of the models does not hold.

I admire Wilson & Sober's (W & S's) aim, to alert social scientists that group selection has risen from the ashqs, and to explicate its relevance to the behavioral sciences. Group selection has beenwidely misunderstood; furthermore, both authors have been instrumental in illuminating conceptual problems surrounding higher-level selection. Still, I find that this target article muddies the waters, primarily through its shifting and confused definition of a "vehicle" of selection. The fundamental problem is an ambiguity in the definition of "adaptation." (...) On the one hand, any evolutionary change that results from a selection process could be called an adaptation, by definition; I call this the "weak" view of adaptation. A "strong" view of adaptation, on the other hand, includes some notion of design - the evolution of a specific complex trait understood, in an engineering sense, to provide a mechanism favoring its owner's success in contributing to the evolutionary lineage. (shrink)

Since the fundamental challenge that I laid at the doorstep of the pluralists was to defend, with nonderivative models, a strong notion of genic cause, it is fatal that Waters has failed to meet that challenge. Waters agrees with me that there is only a single cause operating in these models, but he argues for a notion of causal ‘parsing’ to sustain the viability of some form of pluralism. Waters and his colleagues have some very interesting and important ideas about (...) the sciences, involving pluralism and parsing or partitioning causes, but they are ideas in search of an example. He thinks he has found an example in the case of hierarchical and genic selection. I think he has not. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...) models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)