Recent literature on the role of pictorial representation in the life sciences has focused on the relationship between detailed representations of empirical data and more abstract, formal representations of theory. The standard argument is that in both a historical and epistemic sense, this relationship is a directional one: beginning with raw, unmediated images and moving towards diagrams that are more interpreted and more theoretically rich. Using the neural network diagrams of Warren McCulloch and Walter Pitts as a case study, I (...) argue that while in the empirical sciences, pictorial representation tends to move from data to theory, in areas of the life sciences that are predominantly theoretical, when abstraction occurs at the outset, the relationship between detail and abstraction in pictorial representations can be of a different character. (shrink)

In the past five years, there have been a series of papers in the journal Evolution debating the relative significance of two theories of evolution, a neo-Fisherian and a neo-Wrightian theory, where the neo-Fisherians make explicit appeal to parsimony. My aim in this paper is to determine how we can make sense of such an appeal. One interpretation of parsimony takes it that a theory that contains fewer entities or processes, (however we demarcate these) is more parsimonious. On the account (...) that I defend here, parsimony is a ‘local’ virtue. Scientists’ appeals to parsimony are not necessarily an appeal to a theory’s simplicity in the sense of it’s positing fewer mechanisms. Rather, parsimony may be proxy for greater probability or likelihood. I argue that the neo-Fisherians appeal is best understood on this interpretation. And indeed, if we interpret parsimony as either prior probability or likelihood, then we can make better sense of Coyne et al. argument that Wright’s three phase process operates relatively infrequently. (shrink)

It's been 41 years since the publication of Ernst Mayr's Cause and Effect in Biology wherein Mayr most clearly develops his version of the influential distinction between ultimate and proximate causes in biology. In critically assessing Mayr's essay I uncover false statements and red-herrings about biological explanation. Nevertheless, I argue to uphold an analogue of the ultimate/proximate distinction as it refers to two different kinds of explanations, one dynamical the other statistical.

In addition to ensuring that appropriate standards of evidence are employed when attempting to identify adaptations, researchers should investigate all nonevolutionary factors that could potentially explain their results. Evolutionary analyses may be undermined by alternative, non-evolutionary explanations either because not all relevant information is included in an evolutionary analysis, or because inappropriate methods incapable of detecting an adaptation are employed.

1. A Historical Look at Unity 2. Field Guide to Modern Concepts of Reduction and Unity 3. Kitcher's Revisionist Account of Unification 4. Critics of Unity 5. Integration Instead of Unity 6. Reduction via Mechanisms 7. Case Studies in Reduction and Unification across the Disciplines.

In an incendiary 2010 Nature article, M. A. Nowak, C. E. Tarnita and E. O. Wilson present a savage critique of the best known and most widely used framework for the study of social evolution, W. D. Hamilton’s theory of kin selection. Over a hundred biologists have since rallied to the theory’s defence, but Nowak et al. maintain that their arguments ‘stand unrefuted’. Here I consider the most contentious claim Nowak et al. defend: that Hamilton’s rule, the core explanatory principle (...) of kin selection theory, ‘almost never holds’. I first distinguish two versions of Hamilton’s rule in contemporary theory: a special version (HRS) that requires restrictive assumptions, and a general version (HRG) that does not. I then show that Nowak et al. are most charitably construed as arguing that HRS almost never holds, while HRG buys its generality at the expense of explanatory power. While their arguments against HRS are fairly uncontroversial, their arguments against HRG are more contentious, yet these have been largely overlooked in the ensuing furore. I consider the arguments for and against the explanatory value of HRG, with a view to assessing what exactly is at stake in the debate. I suggest that the debate hinges on issues concerning the causal interpretability of regression coefficients, and concerning the explanatory function Hamilton’s rule is intended to serve. (shrink)

I consider some hitherto unexplored examples of teleological language in the sciences. In explicating these examples, I aim to show (a) that such language is not the sole preserve of the biological sciences, and (b) that not all such talk is reducible to the ascription of functions. In chemistry and biochemistry, scientists explaining molecular rearrangements and protein folding talk informally of molecules rearranging “in order to” maximize stability. Evolutionary biologists, meanwhile, often speak of traits evolving “in order to” optimize some (...) fitness-relevant variable. I argue that in all three contexts such locutions are best interpreted as shorthands for more detailed explanations which, were we to spell them out in full, would show that the relevant process would robustly converge towards the same end-point despite variation in initial conditions. This suggests that, in biology, such talk presupposes a substantial form of adaptationism. The upshot is that such shorthands may be more applicable in the physical sciences than the biological. (shrink)

Selection explanations explain some non-accidental generalizations in virtue of a selection process. Such explanations are not particulaizable - they do not transfer as explanations of the instances of such generalizations. This is unlike many explanations in the physical sciences, where the explanation of the general fact also provides an explanation of its instances (i.e. standard D-N explanations). Are selection explanations (e.g. in biology) therefore a different kind of explanation? I argue that to understand this issue, we need to see that (...) a standard D-N explanation of some non-accidental generalization (al Fs are Gs) may also ipso facto explain its contrapositive (all non-Gs are non-Fs), but the explanation is particularizable with respect to the former but not to the latter. This can be seen by noting that the Raven Paradox counterexample to the H-D model of confirmation also generates a counterexample to the D-N model of explanation (all ravens are black does not explain why the non-black shoe is a non-raven). In such cases it is natural to take the generalization with the positive predicates to have a particularizable explanation. However, this need not be the case, and in selection explanations it is the generalization with the positive predicates whose explanation is no particularizable. Thus there is no need to suppose that selection explanations are fundamentally different. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (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. (shrink)

Altruism is a deep and complex phenomenon that is analysed by scholars of various disciplines, including psychology, philosophy, biology, evolutionary anthropology and experimental economics. Much confusion arises in current literature because the term altruism covers variable concepts and processes across disciplines. Here we investigate the sense given to altruism when used in different fields and argumentative contexts. We argue that four distinct but related concepts need to be distinguished: (a) psychological altruism , the genuine motivation to improve others’ interests and (...) welfare; (b) reproductive altruism , which involves increasing others’ chances of survival and reproduction at the actor’s expense; (c) behavioural altruism , which involves bearing some cost in the interest of others; and (d) preference altruism , which is a preference for others’ interests. We show how this conceptual clarification permits the identification of overstated claims that stem from an imprecise use of terminology. Distinguishing these four types of altruism will help to solve rhetorical conflicts that currently undermine the interdisciplinary debate about human altruism. (shrink)

To generate explanatory theory, ecologists must wrestle with how to represent the extremely many, diverse causes behind phenomena in their domain. Early twentieth-century plant ecologists Frederic E. Clements and Henry A. Gleason provide a textbook example of different approaches to explaining vegetation, with Clements allegedly committed, despite abundant exceptions, to a law of vegetation, and Gleason denying the law in favor of less organized phenomena. However, examining Clements's approach to explanation reveals him not to be expressing a law, and instead (...) to be developing an explanatory structure without laws, capable of progressively integrating causal complexity. Moreover, Clements and Gleason largely agree on the causes of vegetation; but, since causal understanding here underdetermines representation, they differ on how to integrate recognized causes into general theory---that is, in their methodologies. Observers of the case may have mistakenly assumed that scientific representation across the disciplines typically aims at laws like Newton's, and that representations always reveal scientists' metaphysical commitments. Ironically, in the present case, this assumption seems to have been made even by observers who regard Clements as naı¨ve for his alleged commitment to an ecological law. (shrink)

There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.

The interventionist account of causal explanation, in the version presented by Jim Woodward (2003), has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as (...) presently formulated it is either unable to prefer high-level explanations to low, or systematically overshoots, recommending explanations at so high of a level as to be virtually vacuous. (shrink)

This paper argues that the increasingly dominant new mechanistic approach to scientific explanation, as developed to date, does not shed new light on explanatory practice. First, I systematize the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: 1) they must represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Then I argue that even the most promising attempts to flesh out these constraints have fallen far short. (...) Finally, I offer a diagnosis of the mechanistic project, locating a common source of both its virtues and shortcomings. (shrink)

This article serves as an introduction to the laws-of-biology debate. After introducing the main issues in an introductory section, arguments for and against laws of biology are canvassed in Section 2. In Section 3, the debate is placed in wider epistemological context by engaging a group of scholars who have shifted the focus away from the question of whether there are laws of biology and toward offering good accounts of explanation(s) in the biological sciences. Section 4 introduces two relatively new (...) pieces of science – metabolic scaling theory and ecological stoichiometry – that have not been topics of much discussion by philosophers but are relevant because they have at least some of the hallmarks of laws of nature. Section 5 concludes by pointing out that discovering laws of biology, if any there be, will not necessarily answer the questions raised by the debate in the first place: we will still want to know how biology compares to other sciences, how to characterize its systems and processes, and whether accounts in terms of laws always or usually constitute adequate explanations in various sciences. (shrink)

Proponents of Evidence-based medicine (EBM) do not provide a clear role for basic science in therapeutic decision making. Of what they do say about basic science, most of it is negative. Basic science resides on the lower tiers of EBM’s hierarchy of evidence. Therapeutic decisions, according to proponents of EBM, should be informed by evidence from randomised studies (and systematic reviews of randomised studies) rather than basic science. A framework of models explicates the links between the mechanisms of basic science, (...) experimental inquiry, and observed data. Relying on the framework of models I show that basic science often plays a role not only in specifying experiments, but also analysing and interpreting the data that is provided. Further, and contradicting what is implied in EBM’s hierarchy of evidence, appeals to basic science are often required to apply clinical research to therapeutic questions. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

Despite their best efforts, scientists may be unable to construct models that simultaneously exemplify every theoretical virtue. One explanation for this is the existence of tradeoffs: relationships of attenuation that constrain the extent to which models can have such desirable qualities. In this paper, we characterize three types of tradeoffs theorists may confront. These characterizations are then used to examine the relationships between parameter precision and two types of generality. We show that several of these relationships exhibit tradeoffs and discuss (...) what consequences those tradeoffs have for theoretical practice. (shrink)

The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in the philosophy of biology, (...) situating the new ‘mechanismic program’ in this context. I argue that the leading advocates of the mechanismic program (i.e., Craver, Darden, Bechtel, etc.) inadvertently conflate the different senses of ‘mechanism’. Specifically, they all inappropriately endow causal mechanisms with the ontic status of machine mechanisms, and this invariably results in problematic accounts of the role played by mechanism-talk in scientific practice. I suggest that for effective analyses of the concept of mechanism, causal mechanisms need to be distinguished from machine mechanisms, and the new mechanismic program in the philosophy of biology needs to be demarcated from the traditional concerns of mechanistic biology. (shrink)

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into (...) two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (shrink)

There are two motivations commonly ascribed to historical actors for taking up statistics: to reduce complicated data to a mean value (e.g., Quetelet), and to take account of diversity (e.g., Galton). Different motivations will, it is assumed, lead to different methodological decisions in the practice of the statistical sciences. Karl Pearson and W. F. R. Weldon are generally seen as following directly in Galton’s footsteps. I argue for two related theses in light of this standard interpretation, based on a reading (...) of several sources in which Weldon, independently of Pearson, reflects on his own motivations. First, while Pearson does approach statistics from this "Galtonian" perspective, he is, consistent with his positivist philosophy of science, utilizing statistics to simplify the highly variable data of biology. Weldon, on the other hand, is brought to statistics by a rich empiricism and a desire to preserve the diversity of biological data. Secondly, we have here a counterexample to the claim that divergence in motivation will lead to a corresponding separation in methodology. Pearson and Weldon, despite embracing biometry for different reasons, settled on precisely the same set of statistical tools for the investigation of evolution. (shrink)

Advancing the reductionist conviction that biology must be in agreement with the assumptions of reductive physicalism (the upward hierarchy of causal powers, the upward fixing of facts concerning biological levels) A. Rosenberg argues that downward causation is ontologically incoherent and that it comes into play only when we are ignorant of the details of biological phenomena. Moreover, in his view, a careful look at relevant details of biological explanations will reveal the basic molecular level that characterizes biological systems, defined by (...) wholly physical properties, e.g., geometrical structures of molecular aggregates (cells). In response, we argue that contrary to his expectations one cannot infer reductionist assumptions even from detailed biological explanations that invoke the molecular level, as interlevel causal reciprocity is essential to these explanations. Recent very detailed explanations that concern the structure and function of chromatin—the intricacies of supposedly basic molecular level—demonstrate this. They show that what seem to be basic physical parameters extend into a more general biological context, thus rendering elusive the concepts of the basic level and causal hierarchy postulated by the reductionists. In fact, relevant phenomena are defined across levels by entangled, extended parameters. Nor can the biological context be explained away by basic physical parameters defining molecular level shaped by evolution as a physical process. Reductionists claim otherwise only because they overlook the evolutionary significance of initial conditions best defined in terms of extended biological parameters. Perhaps the reductionist assumptions (as well as assumptions that postulate any particular levels as causally fundamental) cannot be inferred from biological explanations because biology aims at manipulating organisms rather than producing explanations that meet the coherence requirements of general ontological models. Or possibly the assumptions of an ontology not based on the concept of causal powers stratified across levels can be inferred from biological explanations. The incoherence of downward causation is inevitable, given reductionist assumptions, but an ontological alternative might avoid this. We outline desiderata for the treatment of levels and properties that realize interlevel causation in such an ontology. (shrink)

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 inter dependence, and that this tension influences scientific methodology. (shrink)

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, optimality (...) and game-theoretic models best explain some central types of evolutionary phenomena. ‡Thanks to Michael Friedman, Helen Longino, Michael Weisberg, and especially Elliott Sober for comments on earlier drafts of this paper. †To contact the author, please write to: Department of Philosophy, Stanford University, Stanford, CA 94305-2155; e-mail: potochnik@stanford.edu. (shrink)

This book originated as a Festschrift to mark the publication of Volume 50 of the journal `Acta Biotheoretica' in 2002 and the journal's 70th anniversary in ...

Many people argue that history makes a special difference to the subjects of biology and psychology, and that history does not make this special difference to other parts of the world. This paper will show that historical properties make no more or less of a difference to biology or psychology than to chemistry, physics, or other sciences. Although historical properties indeed make a certain kind of difference to biology and psychology, this paper will show that historical properties make the same (...) kind of difference to geology, sociology, astronomy, and other sciences. Similarly, many people argue that nonhistorical properties make a special difference to the nonbiological and the nonpsychological world. This paper will show that nonhistorical properties make the same difference to all things in the world when it comes to their causal behavior and that historical properties make the same difference to all things in the world when it comes to their distributions. Although history is special, it is special in the same way to all parts of the world. (shrink)

Coordination of immune responses in the gut is a complex task. In order to fight pathogens and maintain a defined population of commensal microbes, the mucosal immune system has to coordinate information from the external (luminal) and internal (abluminal) environment and respond accordingly. Dendritic cells (DCs) are crucial cell types involved in this process as they integrate these signals and direct immunogenic or tolerogenic responses. Here, we review how various functions of DCs depend on microbial stimuli and how these stimuli (...) influence the course of immune activation. (shrink)

Review of Peter Mc. Laughlin *What Functions Explain" (2001).

This paper reviews the debate on the notion of biological function and on functional explanation as this takes place in philosophy. It describes the different perspectives, issues, intuitions, theories and arguments that have emerged. The author shows that the debate has been too heavily influenced by the concerns of a naturalistic philosophy of mind and argues that in order to improve our understanding of biology the attention should be shifted from the study of intuitions to the study of the actual (...) practice of biological inquiry. (shrink)

Following Mayr (1961) evolutionary biologists often maintain that the hallmark of biology is its evolutionary perspective. In this view, biologists distinguish themselves from other natural scientists by their emphasis on why-questions. Why-questions are legitimate in biology but not in other natural sciences because of the selective character of the process by means of which living objects acquire their characteristics. For that reason, why-questions should be answered in terms of natural selection. Functional biology is seen as a reductionist science that applies (...) physics and chemistry to answer how-questions but lacks a biological point of view of its own. In this paper I dispute this image of functional biology. A close look at the kinds of issues studied in biology and at the way in which these issues are studied shows that functional biology employs a distinctive biological perspective that is not rooted in selection. This functional perspective is characterized by its concern with the requirements of the life-state and the way in which these are met. (shrink)

This paper evaluates Kuipers' account of functional explanation in biology in view of an example of such an explanation taken from real biology. The example is the explanation of why electric fishes swim backwards (Lannoo and Lannoo 1993). Kuipers' account depicts the answer to a request for functional explanation as consisting only of statements that articulate a certain kind of consequence. It is argued that such an account fails to do justice to the main insight provided by the example explanation, (...) namely the insight into why backwards swimming is needed by fishes that locate their food by means of an electric radar. The paper sketches an improved account that does justice to this kind of insight. It is argued that this account is consistent with and complementary to Kuipers' insight that function attributions are established by means of a process of hypothetico-deductive reasoning guided by a heuristic principle. (shrink)

This article deals with a type of functional explanation, viability explanation, that has been overlooked in recent philosophy of science. Viability explanations relate traits of organisms and their environments in terms of what an individual needs to survive and reproduce. I show that viability explanations are neither causal nor historical and that, therefore, they should be accounted for as a distinct type of explanation.

This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings ‘functional explanations’. To avoid confusion with other uses of that phrase, I call them ‘design explanations’. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly exist. They are not (...) causal but appeal to functional dependencies between an organism’s different traits. These explanations point out that because an organism has certain traits (e.g., it lives on land), it cannot be alive if the trait to be explained (e.g., having lungs) were replaced by a specified alternative (e.g., having gills). They can be understood from a mechanistic point of view as revealing the constraints on what mechanisms can be alive. (shrink)

I argue that there are at least four different ways in which the term ‘function’ is used in connection with the study of living organisms, namely: (1) function as (mere) activity, (2) function as biological role, (3) function as biological advantage, and (4) function as selected effect. Notion (1) refers to what an item does by itself; (2) refers to the contribution of an item or activity to a complex activity or capacity of an organism; (3) refers to the value (...) for the organism of an item having a certain character rather than another; (4) refers to the way in which a trait acquired and has maintained its current share in the population. The recognition of a separate notion of function as biological advantage solves the problem of the indeterminate reference situation that has been raised against a counterfactual analysis of function, and emphasizes the importance of counterfactual comparison in the explanatory practice of organismal biology. This reveals a neglected problem in the philosophy of biology, namely that of accounting for the insights provided. (shrink)