We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization in order to explain (...) cognition. To a large extent, practicing cognitive neuroscientists have already accepted this shift, but philosophical theory has not fully acknowledged and appreciated its significance. As a result, the explanatory framework underlying cognitive neuroscience has remained largely implicit. We explicate this framework and demonstrate its contrast with previous approaches. (shrink)

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

Against those who identify genealogy with reductive genealogical debunking or deny it any evaluative and action-guiding significance, I argue for the following three claims: that although genealogies, true to their Enlightenment origins, tend to trace the higher to the lower, they need not reduce the higher to the lower, but can elucidate the relation between them and put us in a position to think more realistically about both relata; that if we think of genealogy’s normative significance in terms of a (...) triadic model that includes the genealogy’s addressee, we can see that in tracing the higher to the lower, a genealogy can facilitate an evaluation of the higher element, and where the lower element is some important practical need rather than some sinister motive, the genealogy can even be vindicatory; and finally, that vindicatory genealogies can offer positive guidance on how to engineer better concepts. (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)

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)

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)

In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...) computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51–62, 2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. (shrink)

The discussion presents a framework of concepts that is intended to account for the rationality of semantic change and variation, suggesting that each scientific concept consists of three components of content: 1) reference, 2) inferential role, and 3) the epistemic goal pursued with the concept’s use. I argue that in the course of history a concept can change in any of these components, and that change in the concept’s inferential role and reference can be accounted for as being rational relative (...) to the third component, the concept’s epistemic goal. This framework is illustrated and defended by application to the history of the gene concept. It is explained how the molecular gene concept grew rationally out of the classical gene concept despite a change in reference, and why the use and reference of the contemporary molecular gene concept may legitimately vary from context to context. (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.

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)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (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)

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)

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. This approach explains (...) why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

We outline three very different concepts of the gene—instrumental, nominal, and postgenomic. The instrumental gene has a critical role in the construction and interpretation of experiments in which the relationship between genotype and phenotype is explored via hybridization between organisms or directly between nucleic acid molecules. It also plays an important theoretical role in the foundations of disciplines such as quantitative genetics and population genetics. The nominal gene is a critical practical tool, allowing stable communication between bioscientists in a wide (...) range of fields grounded in well-defined sequences of nucleotides, but this concept does not embody major theoretical insights into genome structure or function. The post-genomic gene embodies the continuing project of understanding how genome structure supports genome function, but with a deflationary picture of the gene as a structural unit. This final concept of the gene poses a significant challenge to conventional assumptions about the relationship between genome structure and function, and between genotype and phenotype. (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 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)

The new mechanists and the autonomy approach both aim to account for how biological phenomena are explained. One identifies appeals to how components of a mechanism are organized so that their activities produce a phenomenon. The other directs attention towards the whole organism and focuses on how it achieves self-maintenance. This paper discusses challenges each confronts and how each could benefit from collaboration with the other: the new mechanistic framework can gain by taking into account what happens outside individual mechanisms, (...) while the autonomy approach can ground itself in biological research into how the actual components constituting an autonomous system interact and contribute in different ways to realize and maintain the system. To press the case that these two traditions should be constructively integrated we describe how three recent developments in the autonomy tradition together provide a bridge between the two traditions: (1) a framework of work and constraints, (2) a conception of function grounded in the organization of an autonomous system, and (3) a focus on control. (shrink)

There is ongoing controversy as to whether the genome is a representing system. Although it is widely recognised that DNA carries information, both correlating with and coding for various outcomes, neither of these implies that the genome has semantic properties like correctness or satisfaction conditions, In the Scope of Logic, Methodology, and the Philosophy of Sciences, Vol. II. Kluwer, Dordrecht, pp. 387–400). Here a modified version of teleosemantics is applied to the genome to show that it does indeed have semantic (...) properties – there is representation in the genome. The account differs in three respects from previous attempts to apply teleosemantics to genes. It emphasises the role of the consumer of representations. It rejects the standard assumption that genetic representation can be used to explain the course of an organism’s development. And it identifies the explanatory role played by representational properties of the genome. A striking consequence of this account is that other inheritance systems could also be representational. Thus, a version of the parity thesis is accepted. However, the criteria for being an inheritance system are demanding, so semantic properties are not ubiquitous. (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)

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)

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)

“Functional homology” appears regularly in different areas of biological research and yet it is apparently a contradiction in terms—homology concerns identity of structure regardless of form and function. I argue that despite this conceptual tension there is a legitimate conception of ‘homology of function’, which can be recovered by utilizing a distinction from pre-Darwinian physiology (use versus activity) to identify an appropriate meaning of ‘function’. This account is directly applicable to molecular developmental biology and shares a connection to the theme (...) of hierarchy in homology. I situate ‘homology of function’ within existing definitions and criteria for structural assessments of homology, and introduce a criterion of ‘organization’ for judging function homologues, which focuses on hierarchically interconnected interdependencies (similar to relative position and connection for skeletal elements in structural homology). This analysis of biological concepts has at least three broad philosophical consequences: (1) it provides the grounds for the study of behavior and psychological categories as homologues; (2) it demonstrates that philosophers who take selected effect function as primary effectively ignore large portions of comparative, structural, and experimental research, thereby misconstruing biological reasoning and knowledge; and, (3) it underwrites causal generalizations, which illuminates inferences made from model organisms in experimental biology. (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)

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)

Computer simulations and experiments share many important features. One way of explaining the similarities is to say that computer simulations just are experiments. This claim is quite popular in the literature. The aim of this paper is to argue against the claim and to develop an alternative explanation of why computer simulations resemble experiments. To this purpose, experiment is characterized in terms of an intervention on a system and of the observation of the reaction. Thus, if computer simulations are experiments, (...) either the computer hardware or the target system must be intervened on and observed. I argue against the first option using the non-observation argument, among others. The second option is excluded by e.g. the over-control argument, which stresses epistemological differences between experiments and simulations. To account for the similarities between experiments and computer simulations, I propose to say that computer simulations can model possible experiments and do in fact often do so. (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)

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)

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)

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)

In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...) the nature of the ENCODE project, the relevant notion of function and the claim that most of our genome is junk. We argue that evolutionary accounts of function presuppose functions as ‘causal roles’, and that selection is but a useful proxy for relevant functions, which might well be unsuitable to biomedical research. Taking a closer look at the discovery process in which ENCODE participates, we argue that ENCODE’s strategy of biochemical signatures successfully identified activities of DNA elements with an eye towards causal roles of interest to biomedical research. We argue that ENCODE’s controversial claim of functionality should be interpreted as saying that 80 % of the genome is engaging in relevant biochemical activities and is very likely to have a causal role in phenomena deemed relevant to biomedical research. Finally, we discuss ambiguities in the meaning of junk DNA and in one of the main arguments raised for its prevalence, and we evaluate the impact of ENCODE’s results on the claim that most of our genome is junk. (shrink)

Amalgamating evidence of different kinds for the same hypothesis into an overall confirmation is analogous, I argue, to amalgamating individuals’ preferences into a group preference. The latter faces well-known impossibility theorems, most famously “Arrow’s Theorem”. Once the analogy between amalgamating evidence and amalgamating preferences is tight, it is obvious that amalgamating evidence might face a theorem similar to Arrow’s. I prove that this is so, and end by discussing the plausibility of the axioms required for the theorem.

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)

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)

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

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 discovery of RNA interference in 1998 has made a lasting impact on biological research. Identifying the regulatory role of small RNAs changed the modes of molecular biological inquiry as well as biologists' understanding of genetic regulation. This article examines the early years of small RNA biology's success story. I query which factors had to come together so that small RNA research came into life in the blink of an eye. I primarily look at scientific repertoires as facilitators of rapid (...) scientific change. I show that for a short period of time, between the years 1998 and 2002, different model organism communities, investigative strategies, technological innovations, and research interests could be successfully aligned to take small RNA research off the ground. I discuss how the keystone discoveries were situated in specific experimental traditions and what strategies were employed to establish these discoveries as more general phenomena. Providing thus a practice-based approach of rapid scientific change, I ask how to relate the change in propositional bits of scientific knowledge with changes in scientific practice. (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)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (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)

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 notion of biological function is fraught with difficulties—intrinsically and irremediably so, we argue. The physiological practice of functional ascription originates from a time when organisms were thought to be designed and remained largely unchanged since. In a secularized worldview, this creates a paradox which accounts of functions as selected effect attempt to resolve. This attempt, we argue, misses its target in physiology and it brings problems of its own. Instead, we propose that a better solution to the conundrum of (...) biological functions is to abandon the notion altogether, a prospect not only less daunting than it appears, but arguably the natural continuation of the naturalisation of biology. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

Model organisms are central to contemporary biology and studies of embryogenesis in particular. Biologists utilize only a small number of species to experimentally elucidate the phenomena and mechanisms of development. Critics have questioned whether these experimental models are good representatives of their targets because of the inherent biases involved in their selection (e.g., rapid development and short generation time). A standard response is that the manipulative molecular techniques available for experimental analysis mitigate, if not counterbalance, this concern. But the most (...) powerful investigative techniques and molecular methods are applicable to single-celled organisms (‘microbes’). Why not use unicellular rather than multicellular model organisms, which are the standard for developmental biology? To claim that microbes are not good representatives takes us back to the original criticism leveled against model organisms. Using empirical case studies of microbes modeling ontogeny, we break out of this circle of reasoning by showing: (a) that the criterion of representation is more complex than earlier discussions have emphasized; and, (b) that different aspects of manipulability are comparable in importance to representation when deciding if a model organism is a good model. These aspects of manipulability harbor the prospect of enhancing representation. The result is a better understanding of how developmental biologists conceptualize research using experimental models and suggestions for underappreciated avenues of inquiry using microbes. More generally, it demonstrates how the practical aspects of experimental biology must be scrutinized in order to understand the associated scientific reasoning. (shrink)