Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

One thing about technical artefacts that needs to be explained is how their physical make-up, or structure, enables them to fulfil the behaviour associated with their function, or, more colloquially, how they work. In this paper I develop an account of such explanations based on the familiar notion of mechanistic explanation. To accomplish this, I outline two explanatory strategies that provide two different types of insight into an artefact’s functioning, and show how human action inevitably plays a role in artefact (...) explanation. I then use my own account to criticize other recent work on mechanistic explanation and conclude with some general implications for the philosophy of explanation.Keywords: Artefact; Technical function; Explanation; Levels of explanation; Mechanisms. (shrink)

Reasoning in Biological Discoveries brings together a series of essays, which focus on one of the most heavily debated topics of scientific discovery. Collected together and richly illustrated, Darden's essays represent a groundbreaking foray into one of the major problems facing scientists and philosophers of science. Divided into three sections, the essays focus on broad themes, notably historical and philosophical issues at play in discussions of biological mechanism; and the problem of developing and refining reasoning strategies, including interfield relations and (...) anomaly resolution. Darden summarizes the philosophy of discovery and elaborates on the role that mechanisms play in biological discovery. Throughout the book, she uses historical case studies to extract advisory reasoning strategies for discovery. Examples in genetics, molecular biology, biochemistry, immunology, neuroscience and evolutionary biology reveal the process of discovery in action. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

In the 1950s and 1960s, an interfield interaction between molecular biologists and biochemists integrated important discoveries about the mechanism of protein synthesis. This extended discovery episode reveals two general reasoning strategies for eliminating gaps in descriptions of the productive continuity of mechanisms: schema instantiation and forward chaining/backtracking. Schema instantiation involves filling roles in an overall framework for the mechanism. Forward chaining and backtracking eliminate gaps using knowledge about types of entities and their activities. Attention to mechanisms highlights salient features of (...) this historical episode while providing general reasoning strategies for mechanism discovery. (shrink)

While much of the recent literature on mechanisms has emphasized the superiority of mechanisms and mechanistic explanation over laws and nomological explanation, paradigmatic mechanisms—e.g., clocks or synapses—actually exhibit a great deal of stability in their behavior. And while mechanisms of this kind are certainly of great importance, there are many events that do not occur as a consequence of the operation of stable mechanisms. Events of natural and human history are often the consequence of causal processes that are ephemeral and (...) capricious. In this paper I shall argue that, notwithstanding their ephemeral nature, these processes deserve to be called mechanisms. Ephemeral mechanisms share important characteristics with their more stable cousins, and these shared characteristics will help us to understand connections between scientific and historical explanation. (shrink)

A variety of scientific disciplines have set as their task explaining mental activities, recognizing that in some way these activities depend upon our brain. But, until recently, the opportunities to conduct experiments directly on our brains were limited. As a result, research efforts were split between disciplines such as cognitive psychology, linguistics, and artificial intelligence that investigated behavior, while disciplines such as neuroanatomy, neurophysiology, and genetics experimented on the brains of non-human animals. In recent decades these disciplines integrated, and with (...) the advent of techniques for imaging activity in human brains, the term cognitive neuroscience has been applied to the integrated investigations of mind and brain. This book is a philosophical examination of how these disciplines continue in the mission of explaining our mental capacities. (shrink)

Analysis of the adequacy of engineering design methods, as well as analysis of the utility of concepts of function often invoked in these methods, is a neglected topic in both philosophy of technology and in engineering proper. In this paper, I present an approach—dubbed an explanationist perspective—for assessing the adequacy of function-based design methods. Engineering design is often intertwined with explanation, for instance, in reverse engineering and subsequent redesign, knowledge base-assisted designing, and diagnostic reasoning. I argue that the presented approach (...) is useful for validating function-based design methods with respect to their explanatory elements and that it supports assessment of the explanatory and design utility of “function”, and the different conceptualizations thereof, as used in such engineering design methods. I deploy two key desiderata from the explanation literature to assess the viability of function-based design methods: explanatorily relevant difference-making factors and counterfactual understanding defined in terms of what-if-things-had-been-different questions. I explicate the approach and its merits in terms of two case studies drawn from the engineering functional modeling literature: reverse engineering and redesign and malfunction analysis. I close the paper by discussing ramifications of the presented approach for the philosophy of design and the philosophy of explanation. (shrink)

Current philosophical theorizing about technical functions is mainly focused on specifying conditions under which agents are justified in ascribing functions to technical artifacts. Yet, assessing the precise explanatory relevance of such function ascriptions is, by and large, a neglected topic in the philosophy of technical artifacts and technical functions. We assess the explanatory utility of ascriptions of technical functions in the following three explanation-seeking contexts: why was artifact x produced?, why does artifact x not have the expected capacity to ϕ?, (...) how does artifact x realize its capacity to ϕ? We argue that while function ascriptions serve a mere heuristic role in the first context, they have substantial explanatory leverage in the second and third context. In addition, we assess the relevance of function ascriptions in the context of engineering redesign. Here, function ascriptions also play a relevant role: they enable normative statements of the sort that component b functions better than component a. We unpack these claims by considering philosophical theories of technical functions, in particular the ICE theory, and engineering work on function ascription and explanation. We close the paper by relating our analysis to current debates on the explanatory power of mechanistic vis-à-vis functional explanations. (shrink)

Craver claims that mechanistic explanation is ontic, while Bechtel claims that it is epistemic. While this distinction between ontic and epistemic explanation originates with Salmon, the ideas have changed in the modern debate on mechanistic explanation, where the frame of the debate is changing. I will explore what Bechtel and Craver’s claims mean, and argue that good mechanistic explanations must satisfy both ontic and epistemic normative constraints on what is a good explanation. I will argue for ontic constraints by drawing (...) on Craver’s work in Sect. 2.1, and argue for epistemic constraints by drawing on Bechtel’s work in Sect. 2.2. Along the way, I will argue that Bechtel and Craver actually agree with this claim. I argue that we should not take either kind of constraints to be fundamental, in Sect. 3, and close in Sect. 4 by considering what remains at stake in making a distinction between ontic and epistemic constraints on mechanistic explanation. I suggest that we should not concentrate on either kind of constraint, to the neglect of the other, arguing for the importance of seeing the relationship as one of integration. (shrink)

Proponents of mechanistic explanation all acknowledge the importance of organization. But they have also tended to emphasize specificity with respect to parts and operations in mechanisms. We argue that in understanding one important mode of organization—patterns of causal connectivity—a successful explanatory strategy abstracts from the specifics of the mechanism and invokes tools such as those of graph theory to explain how mechanisms with a particular mode of connectivity will behave. We discuss the connection between organization, abstraction, and mechanistic explanation and (...) illustrate our claims by looking at an example from recent research on so-called network motifs. (shrink)

The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, many of whom have (...) assimilated their conception of explanation to the ontic conception. (shrink)

In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the (...) actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Craver's continuum of ?how-possibly,? to ?how-plausibly,? to ?how-actually? models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanism's activities, not its entities. This point is illustrated with two examples of functional models. (shrink)

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.

By contrasting three general conceptions of scientific explanation, this paper seeks to clarify the explanandum and to exhibit the fundamental philosophical issues involved in the project of explicating scientific explanation. The three conceptions--epistemic, modal, and ontic--have both historical and contemporary importance. In the context of Laplacian determinism, they do not seem importantly distinct, but in the context of irreducibly statistical explanations, the three are seen to diverge sharply. The paper argues for a causal/mechanical version of the ontic conception, and concludes (...) by exhibiting some striking consequences of this approach. (shrink)

There are two general approaches to characterising biological functions. One originates with Cummins. According to this approach, the function of a part of a system is just its causal contribution to some specified activity of the system. Call this the ‘C-function’ concept. The other approach ties the function of a trait to some aspect of its evolutionary significance. Call this the ‘E-function’ concept. According to the latter view, a trait's function is determined by the forces of natural selection. The C-function (...) and E-function concepts are clearly quite different, but there is an important relation between them which heretofore has gone unnoticed. The purpose of this paper is to outline that relation.This is not the first paper to discuss the relation of C-function and E-function. Previous attempts all follow either one of two strategies. The first proposes that the two concepts are ‘unified.’ The other proposes that they are radically distinct and apply to wholly different fields within biology. (shrink)

This paper is about mechanisms and models, and how they interact. In part, it is a response to recent discussion in philosophy of biology regarding whether natural selection is a mechanism. We suggest that this debate is indicative of a more general problem that occurs when scientists produce mechanistic models of populations and their behaviour. We can make sense of claims that there are mechanisms that drive population-level phenomena such as macroeconomics, natural selection, ecology, and epidemiology. But talk of mechanisms (...) and mechanistic explanation evokes objects with well-defined and localisable parts which interact in discrete ways, while models of populations include parts and interactions that are neither local nor discrete in any actual populations. This apparent tension can be resolved by carefully distinguishing between the properties of a model and those of the system it represents. To this end, we provide an analysis that recognises the flexible relationship between a mechanistic model and its target system. In turn, this reveals a surprising feature of mechanistic representation and explanation: it can occur even when there is a mismatch between the mechanism of the model and that of its target. Our analysis reframes the debate, providing an alternative way to interpret scientists’ mechanism-talk , which initially motivated the issue. We suggest that the relevant question is not whether any population-level phenomenon such as natural selection is a mechanism, but whether it can be usefully modelled as though it were a particular type of mechanism. (shrink)

The topic of disease mechanisms is of clinical importance, as our understanding of such mechanisms plays an important role in how we approach devising treatments for disease. In this paper, I critique an argument made by Mauro Nervi, in which he asserts that pathology is often better viewed in the context of distinct theoretical mechanisms. I use this critique as a starting point to argue that viewing pathology as a broken-normal, malfunctioning mechanism is more therapeutically practical and more relevant to (...) clinical drug design, than creating a theoretical separation of pathology from physiology. (shrink)

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

In this paper, we compare the mechanisms of protein synthesis and natural selection. We identify three core elements of mechanistic explanation: functional individuation, hierarchical nestedness or decomposition, and organization. These are now well understood elements of mechanistic explanation in fields such as protein synthesis, and widely accepted in the mechanisms literature. But Skipper and Millstein have argued that natural selection is neither decomposable nor organized. This would mean that much of the current mechanisms literature does not apply to the mechanism (...) of natural selection.We take each element of mechanistic explanation in turn. Having appreciated the importance of functional individuation, we show how decomposition and organization should be better understood in these terms. We thereby show that mechanistic explanation by protein synthesis and natural selection are more closely analogous than they appear—both possess all three of these core elements of a mechanism widely recognized in the mechanisms literature. (shrink)

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.

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

The most recent resurgence of philosophical attention to the so-called ‘functional talk' in the sciences can be summarized in terms of the following questions: (Q1) What kind of restrictions, and in particular, what kind of evolutionary restrictions as well as to what extent, is involved in functional ascriptions? (Q2) How can we account for the explanatory import of function-ascribing statements? This paper addresses these questions through a modified version of Cummins' functional analysis. The modification in question is concerned with phylogenetical (...) restrictions on causal role functions, and it stems from an analysis of some primary areas in molecular biology. I examine how evolutionary consideration affects the so-called ‘function-analytical explanatory strategy' (Cummins [1975] 1998, 2002). Finally, I argue that the neo-functional analysis here proposed accounts for a certain convergence between the main rival theories of biological function. ‡I wish to thank David Davies, Eva Jablonka, Thomas Reydon, and Marcel Weber for their helpful comments. †To contact the author, please write to: Department of Philosophy, University of Rijeka, Omladinska 14, 51000 Rijeka, Croatia; e-mail: [email protected]. (shrink)

The most recent resurgence of philosophical attention to the so-called ‘functional talk’ in the sciences can be summarized in terms of the following questions: (Q1) What kind of restrictions, and in particular, what kind of evolutionary restrictions as well as to what extent, are involved in functional ascriptions? (Q2) How can we account for the explanatory import of function-ascribing statements? This paper addresses these questions on the basis of a modified version of Cummins’ functional analysis. The modification in question is (...) concerned with phylogenetical restrictions on causal role functions, and it stems from an analysis of some primary areas in molecular biology. I examine how evolutionary consideration affects the so-called “function-analytical explanatory strategy” (Cummins [1975] 1998, 2002). Finally, I argue that the neo-functional analysis here proposed accounts for a certain convergence between the main rival theories of biological function. (shrink)

The two major modern accounts of explanation are the causal and unification accounts. My aim in this paper is to provide a kind of unification of the causal and the unification accounts, by using the central technical apparatus of the unification account to solve a central problem faced by the causal account, namely, the problem of determining which parts of a causal network are explanatorily relevant to the occurrence of an explanandum. The end product of my investigation is a causal (...) account of explanation that has many of the advantages of the unification account. (shrink)

A biochemical pathway is a sequence of chemical reactions in a biological organism. Such pathways specify mechanisms that explain how cells carry out their major functions by means of molecules and reactions that produce regular changes. Many diseases can be explained by defects in pathways, and new treatments often involve finding drugs that correct those defects. This paper presents explanation schemas and treatment strategies that characterize how thinking about pathways contributes to biomedical discovery. It discusses the significance of pathways for (...) understanding the nature of diseases, explanations, and theories. (shrink)

Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions-according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system-captures one important sense of "function" in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explanation. The synthesis produces an analysis of specifically mechanistic role functions, one that uses the characteristic (...) active, spatial, temporal, and hierarchical organization of mechanisms to add precision and content to Cummins' original suggestion. This synthesis also shows why the discovery of role functions is a scientific achievement. Discovering a role function (i) contributes to the interlevel integration of multilevel mechanisms, and (ii) provides a unique, contextual variety of causal/mechanical explanation. (shrink)

We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...) causes can be translated into mechanistically mediated effects, the posited relationship is intelligible and should raise no special philosophical objections. When they cannot, they are suspect. (shrink)

Cognitive psychologists, like biologists, frequently describe mechanisms when explaining phenomena. Unlike biologists, who can often trace material transformations to identify operations, psychologists face a more daunting task in identifying operations that transform information. Behavior provides little guidance as to the nature of the operations involved. While not itself revealing the operations, identification of brain areas involved in psychological mechanisms can help constrain attempts to characterize the operations. In current memory research, evidence that the same brain areas are involved in what (...) are often taken to be different memory phenomena or in other cognitive phenomena is playing such a heuristic function. †To contact the author, please write to: Department of Philosophy, 0119, University of California, San Diego, La Jolla, CA 92093‐0119; e‐mail: [email protected]. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather than (...) reduce them, as well as the different ways in which mechanisms are discovered. Finally, we offer a more detailed example of an important psychological phenomenon for which mechanistic explanation has provided the main source of scientific understanding. (shrink)

I defend the historical definition of "function" originally given in my Language, Thought and Other Biological Categories (1984a). The definition was not offered in the spirit of conceptual analysis but is more akin to a theoretical definition of "function". A major theme is that nonhistorical analyses of "function" fail to deal adequately with items that are not capable of performing their functions.

An effect is typically explained by citing a cause, but not any cause will do. The oxygen and the spark were both causes of the fire, but normally only the spark explains it. What then distinguishes explanatory from unexplanatory causes? One might attempt to characterise this distinction in terms of intrinsic features of the causes. For example, some causes are changes while others are standing conditions, and one might claim that only the changes explain. Both the spark and the oxygen (...) are causes of the fire, but only the spark is a change, and perhaps this is the reason only the spark explains. On the other hand, one might attempt to characterise the distinction between explanatory and unexplanatory causes in terms of the relation between cause and effect. For example, only some causes are sufficient for their effects, and perhaps only sufficient causes explain. There is, however, an elementary feature of the distinction between explanatory and unexplanatory causes that neither an intrinsic nor a relational approach are well-suited to capture. This is the so-called `interest-relativity' of explanation: the very same cause may be explanatory for one person but not for another. When there is a famine in India, an Indian peasant may explain this by citing the drought, while a member of the World Health Organization may instead cite the failure of the Indian government to stock adequate reserves of food (Hart and Honore, 1985, pp. (shrink)

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

Abstract While agreeing that dynamical models play a major role in cognitive science, we reject Stepp, Chemero, and Turvey's contention that they constitute an alternative to mechanistic explanations. We review several problems dynamical models face as putative explanations when they are not grounded in mechanisms. Further, we argue that the opposition of dynamical models and mechanisms is a false one and that those dynamical models that characterize the operations of mechanisms overcome these problems. By briefly considering examples involving the generation (...) of action potentials and circadian rhythms, we show how decomposing a mechanism and modeling its dynamics are complementary endeavors. (shrink)

Mechanisms are a way of explaining how biological phenomena work rather than why single elements of biological systems are there. However, mechanisms are usually described as physiological entities, and little or no attention is paid to malfunction as an independent theoretical concept. On the other hand, malfunction is the main focus of interest of applied sciences such as medicine. In this paper I argue that malfunctions are parts of pathological mechanisms, which should be considered separate theoretical entities, conceptually having a (...) priority over physiological sequences. While pathological mechanisms can be described in terms of a Cummins-like mechanistic explanation, they show some unnoticed peculiarities when compared to physiological ones. Some features of pathological mechanisms are considered, such as outcome variability, ambivalence and dependence on a range. (shrink)

Between 1940 and 1970 pioneers in the new field of cell biology discovered the operative parts of cells and their contributions to cell life. They offered mechanistic accounts that explained cellular phenomena by identifying the relevant parts of cells, the biochemical operations they performed, and the way in which these parts and operations were organised to accomplish important functions. Cell biology was a revolutionary science but in this book it also provides fuel for yet another revolution, one that focuses on (...) the very conception of science itself. Laws have traditionally been regarded as the primary vehicle of explanation, but in the emerging philosophy of science it is mechanisms that do the explanatory work. Bechtel emphasises how mechanisms were discovered, focusing especially on the way in which new instruments made these inquiries possible. He also describes how new journals and societies provided institutional structure to this new enterprise. (shrink)