The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case (...) study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology. (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)

I defend the view that many biological categories are defined by homology against a series of arguments designed to show that all biological categories are defined, at least in part, by selected function. I show that categories of homology are `abnormality inclusive'—something often alleged to be unique to selected function categories. I show that classifications by selected function are logically dependent on classifications by homology, but not vice-versa. Finally, I reject the view that biologists must use considerations of selected function (...) to abstract away from variation and pathology to form a canonical description of a class of biological systems. (shrink)

This paper investigates what molecular biology has done for our understanding of the gene. I base a new account of the gene concept of classical genetics on the classical dogma that gene differences cause phenotypic differences. Although contemporary biologists often think of genes in terms of this concept, molecular biology provides a second way to understand genes. I clarify this second way by articulating a molecular gene concept. This concept unifies our understanding of the molecular basis of a wide variety (...) of phenomena, including the phenomena that classical genetics explains in terms of gene differences causing phenotypic differences. (shrink)

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

A number of philosophers and ‘evolutionary psychologists’ have argued that attacks on adaptationism in contemporary biology are misguided. These thinkers identify anti-adaptationism with advocacy of non-adaptive modes of explanation. They overlook the influence of anti-adaptationism in the development of more rigorous forms of adaptive explanation. Many biologists who reject adaptationism do not reject Darwinism. Instead, they have pioneered the contemporary historical turn in the study of adaptation. One real issue which remains unresolved amongst these methodological advances is the nature of (...) ‘phylogenetic inertia’. To what extent is an adaptive explanation needed for the persistence of a trait as well as its origin? (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...) this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

There is a fairly long-standing distinction between what are called the ideographic as opposed to nomothetic sciences. The nomothetic sciences, such as physics, offer explanations in terms of the laws and regular operations of nature. The ideographic sciences, such as natural history, cast explanations in terms of narratives. This article offers an account of what is involved in offering an explanatory narrative in the historical sciences. I argue that narrative explanations involve two chief components: a possibility space and an explanatory (...) causal mechanism. (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)

The “negative view” is the claim that natural selection cannot explain why a particular individual has one trait, rather than another. Here, I modify an example from Lewens to show that this claim is sometimes false. I then advance a variation on the negative view. It is the claim that selection at the organism level within a lineage cannot explain why a particular individual in that lineage has one allele, rather than another. This formulation better describes the explanatory role of (...) selection. (shrink)

An influential argument due to Elliott Sober, subsequently strengthened by Denis Walsh and Joel Pust, moves from plausible premises to the bold conclusion that natural selection cannot explain the traits of individual organisms. If the argument were sound, the explanatory scope of selection would depend, surprisingly, on metaphysical considerations concerning origin essentialism. I show that the Sober-Walsh-Pust argument rests on a flawed counterfactual criterion for explanatory relevance. I further show that a more defensible criterion for explanatory relevance recently proposed by (...) Michael Strevens lends support to the view that natural selection can be relevant to the explanation of individual traits. (shrink)

One approach to assess the explanatory power of natural selection is to ask what type of facts it can explain. The standard list of explananda includes facts like trait frequencies or the survival of particular organisms. Here, I argue that this list is incomplete: natural selection can also explain a specific kind of individual-level fact that involves traits. The ability of selection to explain this sort of fact vindicates the explanatory commitments of empirical studies on microevolution. Trait facts must be (...) distinguished from a closely related kind of fact, that is, the fact that a particular individual x has one trait rather than another. Whether or not selection can explain the latter type of fact is highly controversial. According to the so-called ‘Negative View’ it cannot be explained by selection. I defend the Negative View against Nanay’s objection. (shrink)

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

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

We explore the evidential relationships that connect two standard claims of modern evolutionary biology. The hypothesis of common ancestry (which says that all organisms now on earth trace back to a single progenitor) and the hypothesis of natural selection (which says that natural selection has been an important influence on the traits exhibited by organisms) are logically independent; however, this leaves open whether testing one requires assumptions about the status of the other. Darwin noted that an extreme version of adaptationism (...) would undercut the possibility of making inferences about common ancestry. Here we develop a converse claim—hypotheses that assert that natural selection has been an important influence on trait values are untestable unless supplemented by suitable background assumptions. The fact of common ancestry and a claim about quantitative genetics together suffice to render such hypotheses testable. Furthermore, we see no plausible alternative to these assumptions; we hypothesize that they are necessary as well as sufficient for adaptive hypotheses to be tested. This point has important implications for biological practice, since biologists standardly assume that adaptive hypotheses predict trait associations among tip species. Another consequence is that adaptive hypotheses cannot be confirmed or disconfirmed by a trait value that is universal within a single species, if that trait value deviates even slightly from the optimum. 1 Two Darwinian hypotheses 2 Logical independence 3 How adaptive hypotheses bear on the tree of life hypothesis 4 How the tree of life hypothesis bears on adaptive hypotheses 5 What do adaptive hypotheses predict? 6 Common ancestry and quantitative genetics to the rescue 7 Conclusion. (shrink)

I adopt a cladistic view of species, and explore the possibility that there exists an equally valuable cladistic view of organismic traits. This suggestion seems to run counter to the stress on functional views of biological traits in recent work in philosophy and psychology. I show how the tension between these two views can be defused with a multilevel view of biological explanation. Despite the attractions of this compromise, I conclude that we must reject it, and adopt an essentially cladistic (...) conception of biological traits. (shrink)

A common view of how-possibly explanations in biology treats them as explanatorily incomplete. In addition to this interpretation of how-possibly explanation, I argue that there is another interpretation, one which features what I term “explanatory strategies.” This strategy-centered interpretation of how-possibly explanation centers on there being a different explanatory context within which how-possibly explanations are offered. I contend that, in conditions where this strategy context is recognized, how-possibly explanations can be understood as complete explanations. I defend this alternative interpretation by (...) analyzing the explanatory value of simple physical models the nineteenth century developmental biologist Wilhelm His constructed for animal development. (shrink)

The notion of how-possibly explanations emerged with William Dray in response to Carl Hempel’s influential deductive-nomological model of scientific explanation. Dray’s aim was to distinguish explanations of states of affairs that might occur, in contrast to the aim of D-N explanations working to establish that states of affairs must actually occur. More recently, interest in how-possibly explanations has been particularly keen among philosophers of biology. One of the concerns philosophers of biology have focused on is whether how-possibly explanations are “complete” (...) explanations. Dray considered how-possibly explanations to be complete explanations, but the view that they are incomplete explanations became prominent with Robert Brandon’s articulation of successful adaptation explanation in evolutionary biology. According to Brandon, how-possibly adaptation explanations are incomplete, since they lack the requisite empirical evidence. Moreover, Brandon’s characterization of how-possibly explanation can be seen as having set the stage for thinking broadly about how-possibly explanations in biology. Echoing Brandon’s account for adaptation explanations, for example, David Resnik contends that how-possibly explanations are inherently incomplete, and yet they serve an important heuristic role throughout biology by setting out an agenda for future research. (shrink)

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models concerns what the epistemic goal of toy modelling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this article is to precisely articulate and to defend this (...) claim. In particular, we will distinguish between autonomous and embedded toy models, and then argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. _1_ Introduction _2_ Embedded and Autonomous Toy Models _2.1_ Embedded toy models _2.2_ Autonomous toy models _2.3_ Qualification _3_ A Theory of Understanding for Toy Models _3.1_ Preliminaries and requirements _3.2_ The refined simple view _4_ Two Kinds of Understanding with Toy Models _4.1_ Embedded toy models and how-actually understanding _4.2_ Against a how-actually interpretation of all autonomous toy models _4.3_ The how-possibly interpretation of some autonomous toy models _5_ Conclusion. (shrink)

Kyle Stanford has recently given substance to the problem of unconceived alternatives, which challenges the reliability of inference to the best explanation (IBE) in remote domains of nature. Conjoined with the view that IBE is the central inferential tool at our disposal in investigating these domains, the problem of unconceived alternatives leads to scientific anti-realism. We argue that, at least within the biological community, scientists are now and have long been aware of the dangers of IBE. We re-analyze the nineteenth-century (...) study of inheritance and development (Stanford’s case study) and extend it into the twentieth century, focusing in particular on both classical Mendelian genetics and the studies by Avery et al. on the chemical nature of the hereditary substance. Our extended case studies show the preference of the biological community for a different methodological standard: the vera causa ideal, which requires that purported causes be shown on non-explanatory grounds to exist and be competent to produce their effects. On this basis, we defend a prospective realism about the biological sciences. (shrink)

This paper describes a pattern of explanation prevalent in the biological sciences that I call a ‘lineage explanation’. The aim of these explanations is to make plausible certain trajectories of change through phenotypic space. They do this by laying out a series of stages, where each stage shows how some mechanism worked, and the differences between each adjacent stage demonstrates how one mechanism, through minor modifications, could be changed into another. These explanations are important, for though it is widely accepted (...) that there is an ‘incremental constraint’ on evolutionary change, in an important class of cases it is difficult to see how to satisfy this constraint. I show that lineage explanations answer important questions about evolutionary change, but do so by demonstrating differences between individuals rather than invoking population processes, such as natural selection.1. Introduction2. Turning a ‘Scale’ into a ‘Plume’3. Lineage Explanations in Biology3.1. The evolution of eyes3.2. The evolution of feathers4. The Two Dimensions of a Lineage Explanation4.1. The production dimension4.2. The continuity dimension4.3. The dual role of the parts5. Constraining the Explanations6. Operational and Generative Lineages7. Explaining Change Without Populations8. Conclusion. (shrink)

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

Highly idealized models, such as the Hawk-Dove game, are pervasive in biological theorizing. We argue that the process and motivation that leads to the introduction of various idealizations into these models is not adequately captured by Michael Weisberg’s taxonomy of three kinds of idealization. Consequently, a fourth kind of idealization is required, which we call hypothetical pattern idealization. This kind of idealization is used to construct models that aim to be explanatory but do not aim to be explanations.

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

Kyle Stanford has recently given substance to the problem of unconceived alternatives, which challenges the reliability of inference to the best explanation (IBE) in remote domains of nature. Conjoined with the view that IBE is the central inferential tool at our disposal in investigating these domains, the problem of unconceived alternatives leads to scientific anti-realism. We argue that, at least within the biological community, scientists are now and have long been aware of the dangers of IBE. We re-analyse the nineteenth-century (...) study of inheritance and development (Stanford’s case study) and extend it into the twentieth century, focusing in particular on both classical Mendelian genetics and the studies by Avery et al. on the chemical nature of the hereditary substance. Our extended case studies show the preference of the biological community for a different methodological standard: the vera causa ideal, which requires that purported causes be shown on non-explanatory grounds to exist and be competent to produce their effects. On this basis, we defend a prospective realism about the biological sciences. 1 Introduction2 Stanford on Unconceived Alternatives3 Pangenesis: A Re-analysis4 The Vera Causa Ideal I: Negative Aspect5 Rendering Heredity Accessible6 The Vera Causa Ideal II: Positive Aspect7 Implications for Scientific Realism8 Conclusion. (shrink)

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this paper is to (...) precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. (shrink)

Highly idealized models, such as the Hawk-Dove game, are pervasive in biological theorizing. We argue that the process and motivation that leads to the introduction of various idealizations into these models is not adequately captured by Michael Weisberg’s taxonomy of three kinds of idealization. Consequently, a fourth kind of idealization is required, which we call hypothetical pattern idealization. This kind of idealization is used to construct models that aim to be explanatory but do not aim to be explanations.

Does natural selection explain why individual organisms have the traits that they do? According to "the Negative View," natural selection does not explain why any individual organism has the traits that it does. According to "the Positive View," natural selection at least sometimes does explain why an individual organism has the traits that it does. In this paper, I argue that recent arguments for the Positive View fail in virtue of running afoul of the doctrine of origin essentialism and I (...) demonstrate that other recent defenses of the Negative View depend upon my own for their plausibility. (shrink)

Some years ago, in the course of a general critique of what has sometimes been referred to as the covering law theory of explanation, I made the claim that perfectly satisfactory explanations can often be provided by indicating only one or a few necessary conditions, where we remain ignorant of the sufficient conditions, of what we nevertheless claim to understand. What seemed to me one identifiable type of such explanations I called “explaining how-possibly,” because it was a type more naturally (...) given in response to the question how it could be that a certain thing happened than to the more familiar question why it did so. In the present paper I propose to review certain objections to this thesis which have come to my attention in the interval, and to make such concessions as these seem to require. In fact, the concessions will be minor, since the general thesis still seems to me quite defensible. (shrink)

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

The “negative view” is the claim that natural selection cannot explain why a particular individual has one trait, rather than another. Here, I modify an example from Lewens (2001) to show that this claim is sometimes false. I then advance a variation on the negative view. It is the claim that selection at the organism level within a lineage cannot explain why a particular individual in that lineage has one allele, rather than another. This formulation better describes the explanatory role (...) of selection. (shrink)

In recent years, the concept of evolvability has been gaining in prominence both within evolutionary developmental biology (evo-devo) and the broader field of evolutionary biology. Despite this, there remains considerable disagreement about what evolvability is. This article offers a solution to this problem. I argue that, in focusing too closely on the role played by evolvability as an explanandum in evo-devo, existing philosophical attempts to clarify the evolvability concept have been overly narrow. Within evolutionary biology more broadly, evolvability offers a (...) robust explanation for the evolutionary trajectories of populations. Evolvability is an abstract, robust, dispositional property of populations, which captures the joint causal influence of their internal features on the outcomes of evolution (as opposed to the causal influence of selection, which is often characterized as external). When considering the nature of the physical basis of this disposition, it becomes clear that the many existing definitions of evolvability at play within evo-devo should be understood as capturing only aspects of a much broader phenomenon. 1 Introduction2 The Problem of Evolvability3 The Theoretical Role of Evolvability in Evolutionary Biology 3.1 The explanatory targets of evolutionary biology 3.2 Selection-based explanations 3.3 Lineage explanations 3.4 Evolvability-based explanations 3.5 What properties must evolvability have?4 What Evolvability Really Is 4.1 Making sense of ft 4.2 Making sense of x and b5 What of the Limbs? The Power of E6 Conclusion. (shrink)