I examine the adequacy of the causal graph-structural equations approach to causation for modeling biological mechanisms. I focus in particular on mechanisms with complex dynamics such as the PER biological clock mechanism in Drosophila. I show that a quantitative model of this mechanism that uses coupled differential equations – the well-known Goldbeter model – cannot be adequately represented in the standard causal graph framework, even though this framework does permit causal cycles. The reason is that the model contains dynamical information (...) about the mechanism that concerns causal properties but that does not correspond to variables that could be subject to independent interventions. Thus, a representation of the mechanisms as a causal structural model necessarily suppresses causally relevant information. (shrink)

Traditional approaches in philosophy of biology focus attention on biological concepts, explanations, and theories, on evidential support and inter-theoretical relations. Newer approaches shift attention from concepts to conceptual practices, from theories to practices of theorizing, and from theoretical reduction to reductive retooling. In this article, I describe the shift from theory-focused to practice-centered philosophy of science and explain how it is leading philosophers to abandon fundamentalist assumptions associated with traditional approaches in philosophy of science and to embrace scientific pluralism. This (...) article comes in three parts, each illustrating the shift from theory-focused to practice-centered epistemology. The first illustration shows how shifting philosophical attention to conceptual practice reveals how molecular biologists succeed in identifying coherent causal strands within systems of bewildering complexity. The second illustration suggests that analyzing how a multiplicity of alternative models function in practice provides an illuminating approach for understanding the nature of theoretical knowledge in evolutionary biology. The third illustration demonstrates how framing reductionism in terms of the reductive retooling of practice offers an informative perspective for understanding why putting DNA at the center of biological research has been incredibly productive throughout much of biology. Each illustration begins by describing how traditional theory-focused philosophical approaches are laden with fundamentalist assumptions and then proceeds to show that shifting attention to practice undermines these assumptions and motivates a philosophy of scientific pluralism. (shrink)

Consensus conferences are social techniques which involve bringing together a group of scientific experts, and sometimes also non-experts, in order to increase the public role in science and related policy, to amalgamate diverse and often contradictory evidence for a hypothesis of interest, and to achieve scientific consensus or at least the appearance of consensus among scientists. For consensus conferences that set out to amalgamate evidence, I propose three desiderata: Inclusivity, Constraint, and Evidential Complexity. Two examples suggest that consensus conferences can (...) readily satisfy Inclusivity and Evidential Complexity, but consensus conferences do not as easily satisfy Constraint. I end by discussing the relation between social inclusivity and the three desiderata. (shrink)

Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments or simulations, (...) per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive. (shrink)

Examples from the sciences showing that mechanisms do not always succeed in producing the phenomena for which they are responsible have led some authors to conclude that the regularity requirement can be eliminated from characterizations of mechanisms. In this article, I challenge this conclusion and argue that a minimal form of regularity is inextricably embedded in examples of elucidated mechanisms that have been shown to be causally responsible for phenomena. Examples of mechanistic explanations from the sciences involve mechanisms that have (...) been shown to produce phenomena with a reproducible rate of success. By contrast, if phenomena are infrequent to the point that they amount to irreproducible observations and experimental results, they are indistinguishable from the background noise of accidental happenings. The inability to detect or measure the phenomenon of interest against the background noise of accidental correlations makes it impossible to elucidate a mechanism by experimental means, to demonstrate that a proposed mechanism actually produces the phenomenon, and ultimately to justify why a hypothetical scenario involving an irregular mechanism should be preferred over attributing irreproducible happenings to chance. (shrink)

This article examines a metaphilosophical issue, namely existing disagreements in philosophy of science about the significance of using multiple means of determination in scientific practice. We argue that this disagreement can, in part, be resolved by separating different questions that can be asked about the use of multiple means of determination, including the following: what can be concluded from the convergence of data or the convergence of claims about phenomena? Are the conclusions drawn from the convergence of data and of (...) statements about phenomena of special importance to the debate about realism and antirealism? Do inferences based on multiple means of determination have stronger epistemic force than inferences that are secured in other ways? Is the epistemic goal of deploying multiple means of determination well entrenched within the scientific community? Most of these questions can be discussed both in a formal and in an empirical perspective. If the differences in perspective are taken into account, some disagreements can be easily resolved. In part, however, the disagreements reflect historiographical challenges that are very difficult, if not impossible to meet. (shrink)

David Chalmers and Frank Jackson have promoted a strong program of conceptual analysis, which accords a significant philosophical role to the a priori analysis of concepts. They found this methodological program on an account of concepts using two-dimensional semantics. This paper argues that Chalmers and Jackson’s account of concepts, and the related approach by David Braddon-Mitchell, is inadequate for natural kind concepts as found in biology. Two-dimensional semantics is metaphysically faulty as an account of the nature of concepts and concept (...) possession. It is also methodologically flawed as a guideline for how to study scientific concepts. Proponents of two-dimensional semantics are criticized for not taking seriously semantic variation between persons and for failing to adequately account for the rationality of semantic change. I suggest a more pragmatic approach to natural kind term meaning, arguing that the epistemic goal pursued by a term’s use is an additional semantic property. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...) different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

This paper examines causal theories of reference with respect to how plausible an account they give of non-physical natural kind terms such as ‘gene’ as well as of the truth of the associated theoretical claims. I first show that reference fixism for ‘gene’ fails. By this, I mean the claim that the reference of ‘gene’ was stable over longer historical periods, for example, since the classical period of transmission genetics. Second, I show that the theory of partial reference does not (...) do justice to some widely held realist intuitions about classical genetics. This result is at loggerheads with the explicit goals usually associated with partial theories of reference, which is to defend a realist semantics for scientific terms. Thirdly, I show that, contrary to received wisdom and perhaps contrary to physics and chemistry, neither reference fixism nor partial reference are necessary in order to hold on to scientific realism about biology. I pinpoint the reasons for this in the nature of biological kinds, which do not even remotely resemble natural kinds (i.e., Lockean real essences) as traditionally conceived. (shrink)

http://dx.doi.org/10.5007/1808-1711.2012v16n1p53 Ratifying Haeckel and contradicting Kant’s negative prophesy, in this paper I try to show that Darwin was, really, the Newton of the blade of grass . Darwin showed how the configurations according to goals of the living beings, could be explained from a naturalistic point of view, without having to postulate the existence of an intentional agent that had arranged or prearranged then. This achievement, nevertheless, was obtained by a way that Kant could not foresee and that Haeckel could (...) not understand: Darwin came there showing that there was more natural science than that Newton, Kant and Haeckel could conceive. (shrink)

Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...) broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation. (shrink)

Abstract Although noting the importance of organization in mechanisms, the new mechanistic philosophers of science have followed most biologists in focusing primarily on only the simplest mode of organization in which operations are envisaged as occurring sequentially. Increasingly, though, biologists are recognizing that the mechanisms they confront are non-sequential and the operations nonlinear. To understand how such mechanisms function through time, they are turning to computational models and tools of dynamical systems theory. Recent research on circadian rhythms addressing both intracellular (...) mechanisms and the intercellular networks in which these mechanisms are synchronized illuminates this point. This and other recent research in biology shows that the new mechanistic philosophers of science must expand their account of mechanistic explanation to incorporate computational modeling, yielding dynamical mechanistic explanations. Developing such explanations, however, is a challenge for both the scientists and the philosophers as there are serious tensions between mechanistic and dynamical approaches to science, and there are important opportunities for philosophers of science to contribute to surmounting these tensions. Content Type Journal Article Category Original paper in Philosophy of Science Pages 1-16 DOI 10.1007/s13194-012-0046-x Authors William Bechtel, Department of Philosophy, Center for Chronobiology, and Science Studies Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0119, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912. (shrink)

The inapplicability of variations on theory reduction in the context of genetics and their irrelevance to ongoing research has led to an anti-reductionist consensus in philosophy of biology. One response to this situation is to focus on forms of reductive explanation that better correspond to actual scientific reasoning (e.g. part–whole relations). Working from this perspective, we explore three different aspects (intrinsicality, fundamentality, and temporality) that arise from distinct facets of reductive explanation: composition and causation. Concentrating on these aspects generates new (...) forms of reductive explanation and conditions for their success or failure in biology and other sciences. This analysis is illustrated using the case of protein folding in molecular biology, which demonstrates its applicability and relevance, as well as illuminating the complexity of reductive reasoning in a specific biological context. (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)

Kenneth Waters and Marcel Weber argue that the joint use of distinct gene concepts and the transfer of knowledge between classical and molecular analyses in contemporary scientific practice is possible because classical and molecular concepts of the gene refer to overlapping chromosomal segments and the DNA sequences associated with these segments. However, while pointing in the direction of coreference, both authors also agree that there is a considerable divergence between the actual sequences that count as genes in classical genetics and (...) molecular biology. The thesis advanced in this paper is that the referents of classical and molecular gene concepts are coextensive to a higher degree than admitted by Waters and Weber, and therefore coreference can provide a satisfactory account of the high level of integration between classical genetics and molecular biology. In particular, I argue that the functional units/cistrons identified by classical techniques overlap with functional elements entering the composition of molecular transcription units, and that the precision of this overlap can be improved by conducting further experimentation. (shrink)

It is customary to distinguish experimental from purely observational sciences. The former include physics and molecular biology, the latter astronomy and palaeontology. Experiments involve actively intervening in the course of nature, as opposed to observing events that would have happened anyway. When a molecular biologist inserts viral DNA into a bacterium in his laboratory, this is an experiment; but when an astronomer points his telescope at the heavens, this is an observation. Without the biologist’s handiwork the bacterium would never have (...) contained foreign DNA; but the planets would have continued orbiting the sun whether or not the astronomer had directed his telescope skyward. The observational/experimental distinction would probably be difficult to make precise 1, as the notion of an ‘intervention’ is not easily defined, but it is intuitively fairly clear, and is frequently invoked by scientists and historians of science. Experimentation, or ‘putting questions to nature’, is often cited as a hallmark of the modern scientific method, something that permitted the enormous advances of the last 350 years. And it is sometimes said that the social sciences lag behind the natural because controlled experiments cannot be done so readily in the former. Moreover in certain sciences, e.g. epidemiology, students are explicitly taught that experimental data is preferable to observational data, particularly for doing causal inference. So the distinction between observational and experimental science has quite wide currency, and is often regarded as methodologically significant. Surprisingly, mainstream philosophy of science has had rather little to say about the observational/experimental distinction. 2 For example, discussions of confirmation usually invoke a notion of ‘evidence’, to be contrasted with ‘theory’ or ‘hypothesis’; the aim is to understand how the evidence bears on the hypothesis. But whether this ‘evidence’ comes from observation or experiment generally plays no role in the discussion; this is true …. (shrink)

Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...) find that the components of a mechanism interact in complex ways involving positive and negative feedback and that the organization often exhibits highly interactive local networks linked by a few long-range connections (small-worlds organization) and power law distributions of connections. The mechanisms are themselves active systems that are perturbed by inputs but not set in motion by them. Researchers also need to look up —situate a mechanism in its context, which may be a larger mechanism that modulates its behavior. When looking down is combined with looking around and up, mechanistic research results in an integrated, multi-level perspective. (shrink)

Developmental Systems Theory (DST) emphasises the importance of non-genetic factors in development and their relevance to evolution. A common, deflationary reaction is that it has long been appreciated that non-genetic factors are causally indispensable. This paper argues that DST can be reformulated to make a more substantive claim: that the special role played by genes is also played by some (but not all) non-genetic resources. That special role is to transmit inherited representations, in the sense of Shea (2007: Biology and (...) Philosophy, 22, 313-331). Formulating DST as the claim that there are non-genetic inherited representations turns it into a striking, empirically-testable hypothesis, driving the sort of investigations that are only now beginning to appear in the scientific literature. DST’s characteristic rejection of a gene vs. environment dichotomy is preserved, but without dissolving all potentially explanatory distinctions into an interactionist causal soup, as some have alleged. (shrink)

This paper discusses three shortcomings of the current state of the debate regarding historical evidence against scientific realism. Attending to these issues will direct the debate away from over-generalising wholesale arguments.

Schaffner’s model of theory reduction has played an important role in philosophy of science and philosophy of biology. Here, the model is found to be problematic because of an internal tension. Indeed, standard antireductionist external criticisms concerning reduction functions and laws in biology do not provide a full picture of the limits of Schaffner’s model. However, despite the internal tension, his model usefully highlights the importance of regulative ideals associated with the search for derivational, and embedding, deductive relations among mathematical (...) structures in theoretical biology. A reconstructed Schaffnerian model could therefore shed light on mathematical theory development in the biological sciences and on the epistemology of mathematical practices more generally. *Received November 2006; revised March 2009. †To contact the author, please write to: Philosophy Department, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064; e‐mail: [email protected]. (shrink)

The success of a piece of behaviour is often explained by its being caused by a true representation (similarly, failure falsity). In some simple organisms, success is just survival and reproduction. Scientists explain why a piece of behaviour helped the organism to survive and reproduce by adverting to the behaviour’s having been caused by a true representation. That usage should, if possible, be vindicated by an adequate naturalistic theory of content. Teleosemantics cannot do so, when it is applied to simple (...) representing systems (Godfrey-Smith 1996). Here it is argued that the teleosemantic approach to content should therefore be modified, not abandoned, at least for simple representing systems. The new ‘infotel-semantics’ adds an input condition to the output condition offered by teleosemantics, recognising that it is constitutive of content in a simple representing system that the tokening of a representation should correlate probabilistically with the obtaining of its specific evolutionary success condition. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Philosophers of science have recently focused on the scientific activity of modeling phenomena, and explicated several of its properties, as well as the activities embedded into it. A first approach to modeling has been elaborated in terms of representing a target system: yet other epistemic functions, such as producing data or detecting phenomena, are at least as relevant. Additional useful distinctions have emerged, such as the one between phenomenological and mechanistic models. In biological sciences, besides mathematical models, models now come (...) in three forms: in vivo, in vitro and in silico. Each has been investigated separately, and many specific problems they raised have been laid out. Another relevant distinction is disciplinary: do models differ in significant ways according to the discipline involved—medicine or biology, evolutionary biology or earth science? Focusing on either this threefold distinction or the disciplinary boundaries reveals that they might not be sufficient from a philosophical perspective. On the contrary, focusing on the interaction between these various kinds of models, some interesting forms of explanation come to the fore, as is exemplified by the papers included in this issue. On the other hand, a focus on the use of models, rather than on their content, shows that the distinction between biological and medical models is theoretically sound. (shrink)

Dobzhansky argued that biology only makes sense if life on earth has a shared history. But his dictum is often reinterpreted to mean that biology only makes sense in the light of adaptation. Some philosophers of science have argued in this spirit that all work in ‘proximal’ biosciences such as anatomy, physiology and molecular biology must be framed, at least implicitly, by the selection histories of the organisms under study. Others have denied this and have proposed non-evolutionary ways in which (...) biologists can frame these investigations. This paper argues that an evolutionary perspective is indeed necessary, but that it must be a forward-looking perspective informed by a general understanding of the evolutionary process, not a backward-looking perspective informed by the specific evolutionary history of the species being studied. Interestingly, it turns out that there are aspects of proximal biology that even a creationist cannot study except in the light of a theory of their effect on future evolution. (shrink)

It has been claimed that the intentional stance is necessary to individuate behavioral traits. This thesis, while clearly false, points to two interesting sets of problems concerning biological explanations of behavior: The first is a general in the philosophy of science: the theory-ladenness of observation. The second problem concerns the principles of trait individuation, which is a general problem in philosophy of biology. After discussing some alternatives, I show that one way of individuating the behavioral traits of an organism is (...) by a special use of the concept of biological function, as understood in an enriched causal role (not selected effect) sense. On this view, a behavioral trait is essentially a special kind of regularity, namely a regularity that is produced by some regulatory mechanism. Regulatory mechanisms always require goal states, which can only be provided by functional considerations. As an example from actual (as opposed to folk) science, I examine the case of social behavior in nematodes. I show that the attempt to explain this phenomenon actually transformed it. This supports the view that scientific explanation does not explain an explanandum phenomenon that is given prior to the explanation; rather, the explanandum is changed by the explanation. This means that there could be a plurality of stances that have some heuristic value initially, but which will be abandoned in favor of a functional characterization eventually. (shrink)

Watson and Crick’s discovery of the structure of DNA led to developments that transformed many biological sciences. But what were the relevant developments and how did they transform biology? Much of the philosophical discussion concerning this question can be organized around two opposing views: theoretical reductionism and layer-cake antireductionism. Theoretical reductionist and their anti-reductionist foes hold two assumptions in common. First, both hold that biological knowledge is structured like a layer cake, with some biological sciences, such as molecular biology cast (...) at lower levels of organization, and others, such as classical genetics, cast at higher levels. Second, both assume that scientific knowledge is structured by theory and that the productivity of scientific research depends on whether the underlying theory identifies the fundamentals upon which the phenomena to be explained and investigated depend. In the first part of this paper, I challenge these assumptions. In the second part, I show how recasting the basic theory of classical genetics made it possible to retool the methodologies of genetics. It was the investigative power of these retooled methodologies, and not the explanatory power of a gene-based theory, that transformed biology. (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)

Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...) in philosophy of science drew attention to the fact that many experimental phenomena have a ‘life of their own’: the conviction that they are real is not dependent on the theories used to characterise and explain them. I suggest that something similar can be true of descriptive phenomena, and that many homologies are phenomena of this kind. As a result the descriptive biology of form and function has a life of its own—a degree of epistemological independence from the theories that explain form and function. I also suggest that the two major ‘homology concepts’ in contemporary biology, usually seen as two competing definitions, are in reality complementary elements of the biological explanation of homology. (shrink)

We reconstruct genetic determinism as a reductionist thesis to the effect that the molecular properties of cells can be accounted for to a great extent by their genetic outfit. The non-reductionist arguments offered at this molecular level often use the relationship between structure and function as their point of departure. By contrast, we develop a non-reductionist argument that is confined to the structural characteristics of biomolecules; no appeal to functions is made. We raise two kinds of objections against the reducibility (...) claim underlying genetic determinism. First, some conceptual distinctions at the protein level cannot be captured on a genetic basis. A one-to-many relationship between DNA sequences and proteins emerges from them. Second, the relationship between genes and proteins is characterized by explanatory loops or reciprocal explanatory dependence. The presence of proteins is explained by the transcription from corresponding DNA sequences, and the latter is in turn accounted for by the action of proteins. By contrast, a reductive account requires a unidirectional explanatory dependence. (shrink)

The theory of concepts advanced in the present discussion aims at accounting for a) how a concept makes successful practice possible, and b) how a scientific concept can be subject to rational change in the course of history. To this end, I suggest that each scientific concept consists of three components of content: 1) the concept.

In this paper, rather than focusing on genes as an organising concept around which historical considerations of theory and practice in genetics are elucidated, we place genetic markers at the heart of our analysis. This reflects their central role in the subject of our account, livestock genetics concerning the domesticated pig, Sus scrofa. We define a genetic marker as a element existing in different forms in the genome, that can be identified and mapped using a variety of quantitative, classical and (...) molecular genetic techniques. The conjugation of pig genome researchers around the common object of the marker from the early-1990s allowed the distinctive theories and approaches of quantitative and molecular genetics concerning the size and distribution of gene effects to align in projects to populate genome maps. Critical to this was the nature of markers as ontologically inert, internally heterogeneous and relational. Though genes as an organising and categorising principle remained important, the particular concatenation of limitations, opportunities, and intended research goals of the pig genetics community, meant that a progressively stronger focus on the identification and mapping of markers rather than genes per se became a hallmark of the community. We therefore detail a different way of doing genetics to more gene-centred accounts. By doing so, we reveal the presence of practices, concepts and communities that would otherwise be hidden. (shrink)

We characterize access to empirical objects in biology from a theoretical perspective. Unlike objects in current physical theories, biological objects are the result of a history and their variations continue to generate a history. This property is the starting point of our concept of measurement. We argue that biological measurement is relative to a natural history which is shared by the different objects subjected to the measurement and is more or less constrained by biologists. We call symmetrization the theoretical and (...) often concrete operation which leads to considering biological objects as equivalent in a measurement. Last, we use our notion of measurement to analyze research strategies. Some strategies aim to bring biology closer to the epistemology of physical theories, by studying objects as similar as possible, while others build on biological diversity. (shrink)

This paper is about conceptual engineering. Specifically, it discusses a common objection to CE, which I call the Discontinuity Objection. According to the Discontinuity Objection, CE leads to problematic discontinuities in subject and/or inquiry – making it philosophically uninteresting or irrelevant. I argue that a conceptual engineer can dismiss the Discontinuity Objection by showing that the pre-engineering concept persists through the proposed changes. In other words, the Discontinuity Objection does not apply if the proposal involves identity-preserving changes. Two existing views (...) on identity-preserving changes are considered and rejected. I then argue that an identity-preserving conceptual change is one that allows the concept to continue to perform its function. A concept’s function is its job, its point and purpose, its role in a conceptual repertoire. In a slogan: Preserve a concept’s function, and you preserve the concept itself; preserve the concept, and you preserve the subject. The paper concludes by discussing some implications of this view. (shrink)

Waters’s (2007) actual difference making and Weber’s (2013, 2017) biological normality approaches to causal selection have received many criticisms, some of which miss their target. Disagreement about whether Waters’s and Weber’s views succeed in providing criteria that uniquely singles out the gene as explanatorily significant in biology has led philosophers to overlook a prior problem. Before one can address whether Waters’s and Weber’s views successfully account for the explanatory significance of genes, one must ask whether either view satisfactorily meets the (...) necessary conditions for causal selection in the first place. An adequate defense of causal selection must meet two desiderata. First, there must be an explanatory property that sets some causes apart from others. Second, the property identified must be one that is recognized by biologists as relevant to their domain(s) of inquiry. I argue that both fall short of meeting the second condition. I demonstrate this by showing how many of the biological technologies crucial to experimentation do not fit either view very well. I offer a more adequate proposal that accommodates non-actual and artificial causal variables. A consequence of my view is the following: When analyzing the causal selection practices of biologists, philosophers should consider the explanatory targets relevant to a research program – including ones whose explanans must appeal to biological technologies. I then explain how this proposal can inform the existing debate between Weber (2017) and Griffiths et al. (2015). (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

This article describes contrasting ideas for a set of topics in epidemiological thinking. The premise underlying this contribution to the special edition is that researchers develop their epidemiological thinking over time through interactions with other researchers who have a variety of in-practice commitments, such as to kinds of cases and methods of analysis, and not simply to a philosophical framework for explanation. I encourage discussants from philosophy and epidemiology to draw purposefully from across a range of topics and contrasting positions, (...) and thereby pursue critical thinking in the sense of understanding ideas and practices better when we examine them in relation to alternatives. After an initial topic concerning practices for developing epidemiological literacy, a number of conceptual steps follow—the characterization of the very phenomena we might be concerned with, the scope and challenges of the field of epidemiology, the formulation of categories—before linking associations, predictions, causes and interventions and examining the confounding of purported links. Building on that conceptual basis, the remaining topics consist of issues or angles of analysis related to the complexities of inequalities within and between populations, context, and changes over the life course. The organization of topics derives from a graduate course that I teach that aims for epidemiological literacy, not technical ability in statistical formulas and data analysis, and shares the underlying premise and critical thinking goals of this article. During the topic-by-topic description, some assertions about explanation and intervention emerge, notably, that epidemiological–philosophical discussion about causality often leaves unclear or unexamined whether a modifiable factor shown to have been associated with a difference in the data from past observations should be thought of as factor that, when modified, would generate that difference going forward. The article concludes with a “Limitations of this Study” section that teases out different kinds of description–prescription relationship that are implied in undertaking philosophy of epidemiology and identifies some other considerations that are implied but not emphasized by this article. (shrink)

Ongoing empirical discoveries in molecular biology have generated novel conceptual challenges and perspectives. Philosophers of biology have reacted to these trends when investigating the practice of molecular biology and contributed to scientific debates on methodological and conceptual matters. This article reviews some major philosophical issues in molecular biology. First, philosophical accounts of mechanistic explanation yield a notion of explanation in the context of molecular biology that does not have to rely on laws of nature and comports well with molecular discovery. (...) Second, reductionism continues to be debated and increasingly be rejected by scientists. Philosophers have likewise moved away from reduction toward integration across fields or integrative explanations covering several levels of organization. Third, although the gene concept has undergone substantial transformation and even fragmentation, it still enjoys widespread use by molecular biologists, which has prompted philosophers to understand the empirical reasons for this. At the same time, it has been argued the notion of ‘genetic information’ is largely an empty metaphor, which generates the illusion of explanatory understanding without offering an adequate explanation of molecular and developmental mechanisms. (shrink)

The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.

Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...) articulate norms of completeness for mechanistic explanations that have no such unwanted implications. _1_ Introduction _2_ A Balancing Act: When Do Details Matter? _3_ The Norms of Causal Explanation _4_ The Norms of Constitutive Explanation _5_ Salmon-Completeness _6_ From More Details to More Relevant Details _7_ Non-explanatory Virtues of Abstraction _8_ From Explanatory Models to Explanatory Knowledge _9_ Mechanistic Completeness Reconsidered _10_ Conclusion. (shrink)

Over the last 20 years, several philosophers have developed a new approach to biological functions, the organizational approach. This is not a single theory but a family of theories based on the idea that a trait token can acquire a function by virtue of the way it contributes to a complex, organized system and thereby to its own continued persistence as a token. I argue that the organizational approach faces a serious liberality objection. I examine three different ways organizational theorists (...) have tried to avoid that objection and show how they fail. (shrink)

I present and defend the generalized selected effects theory (GSE) of function. According to GSE, the function of a trait consists in the activity that contributed to its bearer’s differential reproduction, or differential retention, within a population. Unlike the traditional selected effects (SE) theory, it does not require that the functional trait helped its bearer reproduce; differential retention is enough. Although the core theory has been presented previously, I go significantly beyond those presentations by providing a new argument for GSE (...) and defending it from a recent objection. I also sketch its implications for teleosemantics and philosophy of medicine. (shrink)

I distinguish two forms of pluralism about biological functions, between-discipline pluralism and within-discipline pluralism. Between-discipline pluralism holds that different theories of function are appropriate for different subdisciplines of biology and psychology. I provide reasons for rejecting this view. Instead, I recommend within-discipline pluralism, which emphasizes the plurality of function concepts at play within any given subdiscipline of biology and psychology.

John Searle has argued that functions owe their existence to the value that we put into life and survival. In this paper, I will provide a critique of Searle’s argument concerning the ontology of functions. I rely on a standard analysis of functional predicates as relating not only a biological entity, an activity that constitutes the function of this entity and a type of system but also a goal state. A functional attribution without specification of such a goal state has (...) no truth-value. But if completed with a goal state, functional attributions understood as four-place relations attain a truth-value. The truth conditions of all attributions of function involve a dependence claim of the goal state on the function bearer’s activity. The nature of this dependence may differ; I consider five different possibilities: causality, mechanistic constitution, mereology, supervenience and metaphysical grounding. If these dependency relations are objective, Searle’s central ontological thesis fails. What he ought to have said is that our valuing survival or other goal states may be the reason why biology seeks functional knowledge, but this has nothing to do with ontology. I will show further that Searle also raised an interesting challenge concerning the relationship of functional and causal truths, but it does not threaten the objectivity of functions either. At best, it could show that functional vocabulary is eliminable. However, I will show that functional vocabulary is not so eliminable. (shrink)

The Realist that investigates questions of ontology by appeal to the quantificational structure of language assumes that the semantics for the privileged language of ontology is externalist. I argue that such a language cannot be (some variant of) a natural language, as some Realists propose. The flexibility exhibited by natural language expressions noted by Chomsky and others cannot obviously be characterized by the rigid models available to the externalist. If natural languages are hostile to externalist treatments, then the meanings of (...) natural language expressions serve as poor guides for ontological investigation, insofar as their meanings will fail to determine the referents of their constituents. This undermines the Realist’s use of natural languages to settle disputes in metaphysics. (shrink)

In this article we examine the “phenotype” concept in light of recent technological advances in Genome-Wide Association Studies . By observing the technology and its presuppositions, we put forward the thesis that at least in this case genotype and phenotype are effectively coidentifled one by means of the other. We suggest that the coidentiflcation of genotype-phenotype couples in expression-based GWAS also indicates a conceptual dependence, which we call “co-deñnition.” We note that viewing these terms as codeflned runs against possible expectations, (...) viz., that genotypes and phenotypes could ultimately be expressed independently from one another. In addition, the co-definition of genotypes and phenotypes in this context emphasizes the correlative character of both genotypes and phenotypes in GWAS. (shrink)