Mechanistic Explanation

We provide an account of mechanistic representation and explanation that has several advantages over previous proposals. In our view, explaining mechanistically is not simply giving an explanation of a mechanism. Rather, an explanation is mechanistic because of particular relations that hold between a mechanical representation, or model, and the target of explanation. Under this interpretation, mechanistic explanation is possible even when the explanatory target is not a mechanism. We argue that taking this view is not only coherent and plausible, it (...) gives a more sophisticated view of the relationship between mechanical models and their targets. This allows us to address some ambiguities within the mechanist framework, and delivers a more intuitive way to interpret scientists' use of the term "mechanism". (shrink)

The free-energy principle claims that biological systems behave adaptively maintaining their physical integrity only if they minimize the free energy of their sensory states. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, and function of the brain, and has been called a “postulate,” a “mandatory principle,” and an “imperative.” While it might afford a theoretical foundation for understanding the complex relationship between physical environment, life, and mind, its epistemic (...) status and scope are unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanicism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. (shrink)

An adequate understanding of the ubiquitous practice of mechanistic explanation requires an account of what Craver (2007) termed “constitutive relevance.” Entities or activities are constitutively relevant to a phenomenon when they are parts of the mechanism responsible for that phenomenon. Craver’s mutual manipulability (MM) account extended Woodward’s account of manipulationist counterfactuals to analyze how interlevel experiments establish constitutive relevance. Critics of MM (e.g., Baumgartner and Gebharter 2016 and Baumgartner and Casini 2017) argue that applying Woodward’s account to this philosophical problem (...) conflates causation and constitution, thus rendering the account incoherent. These criticisms, we argue, arise from failing to distinguish the semantic, epistemic, and metaphysical aspects of the problem of constitutive relevance. In distinguishing these aspects of the problem and responding to these critics accordingly, we amend MM into a refined epistemic criterion, the “matched interlevel experiments” (MIE) account. Further, we explain how this epistemological thesis is grounded in the plausible metaphysical thesis that constitutive relevance is causal betweenness. (shrink)

I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...) to produce a phenomenon of interest. (shrink)

The idea at the core of the New Mechanical account of explanation can be summarized in the claim that explaining means showing ‘how things work’. This simple motto hints at three basic features of Mechanistic Explanation (ME): ME is an explanation-how, that implies the description of the processes underlying the phenomenon to be explained and of the entities that engage in such processes. These three elements trace a fundamental contrast with the view inherited from Hume and later from strict logical (...) empiricism (see Creath 2017), focused on epistemic and formal features of science and according to which issues concerning the kind of entities and processes that lie within a theory’s domain are extraneous to science and belong instead to ontology or metaphysics. Philosophers belonging to the new mechanical philosophy believe that the received view of scientific explanation (Hempel 2001), pivoting on the notion of law of nature, overshadows this insight. Since its origin in the 17th century, mechanical philosophy aimed to explain natural phenomena by reducing them to mechanisms. Traditional attempts to define the concept of mechanism involved the identification of a limited set of fundamental elements as, for instance, contact action, action at a distance, inertial motion (see e.g. Hesse 2005), and, more recently, transmission of a mark, or of a conserved quantity (see Frisch, this volume). The new mechanical philosophy rejects this austere characterization of mechanisms and mechanistic explanation and aim at providing a novel, philosophically rigorous explication of the concept of mechanism and of its role in scientific explanation and practice. ME has been adopted with profit in philosophy of special sciences (for instance in biomedical sciences, e.g. in the explanation of chemical transmission at synapses ((Machamer, Darden and Craver 2000), MDC henceforth); but also in social sciences, e.g. the three kinds of social mechanisms in Coleman’s analysis of Max Weber’s account of the role of the Protestant ethic in the growth of capitalism (Hedström and Swedberg 1998)), where exceptionless regularities are rarely ever found. In physics, it is generally possible to formulate explanations in law-based form, with the result that the plurality of explanatory forms might be overlooked. This should not come as a surprise, given that physics was the main inspiration for logical empiricists, and, in particular, Newtonian physics was a template for Hempel’s formulation of the covering law model. However, this situation is unfortunate, since, we will argue, knowing how things work is often part of the explanation of physical phenomena. In this chapter, we provide an introduction to the basic features of ME, with specific focus on its application to physics (section 1). The main part of the chapter is devoted to the defence of two theses: on the one hand, some domains of physics are not compatible with mechanistic reasoning and explanation (section 2); on the other hand, a comprehensive account of explanation in physics can’t dispense with ME (section 3). (shrink)

In this paper I argue that historiography employs causal narrative explanations just as other historical sciences such as evolutionary biology or paleontology do. There is a logic of explanation common to all these sciences that centers on causal explanation of unique and unrepeatable events. The explanandum of historiography can further be understood as mechanism in the sense developed by Stuart Glennan and others in recent years. However, causal explanation is not the only way historiography relates to the past. Arthur Danto (...) has given us the theoretical tools to differentiate between causal narratives and conceptual colligations, with both playing a pivotal role in historiography even though Danto himself has not expressed that thought clearly. (shrink)

What kinds of norms constrain mechanistic discovery and explanation? In the mechanistic literature, the norms for good explanations are directly derived from answers to the metaphysical question of what explanations are. Prominent mechanistic accounts thus emphasize either ontic or epistemic norms. Still, mechanistic philosophers on both sides agree that there is no sharp distinction between the processes of discovery and explanation. Thus, it seems reasonable to expect that ontic and epistemic accounts of explanation will be accompanied by ontic and epistemic (...) accounts of discovery, respectively. As we will show here, however, recent discovery accounts implicitly rely on both ontic and epistemic norms to characterize the discovery process. In this paper, we develop an account that makes explicit that, and how, ontic and epistemic norms work together throughout the discovery process. By describing mechanism discovery as a process of pattern recognition we demonstrate that scientists have to develop epistemic activities to distinguish a pattern from its background. Furthermore, they have to determine which epistemic activities successfully describe how the pattern is implemented by identifying the pattern’s components. Our approach reveals that ontic and epistemic norms are equally important in mechanism discovery. (shrink)

In this paper, we defend a novel, multidimensional account of representational unification, which we distinguish from integration. The dimensions of unity are simplicity, generality and scope, non-monstrosity, and systematization. In our account, unification is a graded property. The account is used to investigate the issue of how research traditions contribute to representational unification, focusing on embodied cognition in cognitive science. Embodied cognition contributes to unification even if it fails to offer a grand unification of cognitive science. The study of this (...) failure shows that unification, contrary to what defenders of mechanistic explanation claim, is an important mechanistic virtue of research traditions. (shrink)

Philosophers of psychology debate, among other things, which psychological models, if any, are (or provide) mechanistic explanations. This should seem a little strange given that there is rough consensus on the following two claims: 1) a mechanism is an organized collection of entities and activities that produces, underlies, or maintains a phenomenon, and 2) a mechanistic explanation describes, represents, or provides information about the mechanism producing, underlying, or maintaining the phenomenon to be explained (i.e. the explanandum phenomenon) (Bechtel and Abrahamsen (...) 2005; Craver 2007). If there is a rough consensus on what mechanisms are and that mechanistic explanations describe, represent, or provide information about them, then how is there no consensus on which psychological models are (or provide) mechanistic explanations? Surely the psychological models that are mechanistic explanations are the models that describe, represent, or provide information about mechanisms. That is true, of course; the trouble arises when determining what exactly that involves. Philosophical disagreement over which psychological models are mechanistic explanations is often disagreement about what it means to describe, represent, or provide information about a mechanism, among other things (Hochstein 2016; Levy 2013). In addition, one's position in this debate depends on a host of other seemingly arcane metaphysical issues, such as the nature of mechanisms, computational and functional properties (Piccinini 2016), and realization (Piccinini and Maley 2014), as well as the relation between models, methodologies, and explanations (Craver 2014; Levy 2013; Zednik 2015). Although I inevitably advocate a position, my primary aim in this chapter is to spell out all these relationships and canvas the positions that have been taken (or could be taken) with respect to mechanistic explanation in psychology, using dynamical systems models and cognitive models (or functional analyses) as examples. (shrink)

In this article, we discuss the issue of context-dependence of mechanism-based explanation in the social sciences. The different ways in which the context-dependence and context-independence of mechanism-based explanation have been understood in the social sciences are often motivated by different and apparently incompatible understandings of what explanatory mechanisms are. Instead, we suggest that the different varieties of context-dependence are best seen as corresponding to different research goals. Rather than conflicting with one another, these goals are complementary to each other and (...) therefore pave the way to a methodologically more cooperative approach to mechanism-based explanation in the social sciences. (shrink)

This paper proposes an integrated-structure notion of interlevel emergence, from a dynamic relational ontological perspective. First, I will argue that only the individualist essentialism of atomistic metaphysics can block the possibility of interlevel emergence. Then I will show that we can make sense of emergence by recognizing the formation of structures of transformative and interdependent causal relations in the generation and development of a particular class of mereological complexes called integrated systems. Finally, I shall argue that even though the emergent (...) structural attributes of such systems are not micro-determined nor micro-reducible, they can still be accounted for by an interlevel integrative neo-mechanistic form of explanation. (shrink)

This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism for countering (...) heat shock—the heat shock response (HSR) system—in Escherichia coli (E. coli) bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation. (shrink)

Winner of the 2020 Essay Competition of the International Social Ontology Society. -/- Ian Hacking uses the looping effect to describe how classificatory practices in the human sciences interact with the classified people. While arguably this interaction renders the affected human kinds unstable and hence different from natural kinds, realists argue that also some prototypical natural kinds are interactive and human kinds in general are stable enough to support explanations and predictions. I defend a more fine-grained realist interpretation of interactive (...) human kinds by arguing for an explanatory domain account of the looping effect. First, I argue that knowledge of the feedback mechanisms that mediate the looping effect can supplement, and help to identify, the applicability domain over which a kind and its property variations are stably explainable. Second, by applying this account to cross-cultural case studies of psychiatric disorders, I distinguish between congruent feedback mechanisms that explain matches between classifications and kinds, and incongruent feedback mecha- nisms that explain mismatches. For example, congruent mechanisms maintain Western auditory experiences in schizophrenia, whereas exporting diagnostic labels inflicts incongruence by influencing local experiences. Knowledge of the mechanisms can strengthen explanatory domains, and thereby facilitate classificatory adjustments and possible interventions on psychiatric disorders. (shrink)

William Gilbert’s 1600 book, De magnete, greatly influenced early modern natural philosophy. The book describes an impressive array of physical experiments, but it also advances a metaphysical view at odds with the soon to emerge mechanical philosophy. That view was animism. I distinguish two kinds of animism – Aristotelian and Platonic – and argue that Gilbert was an Aristotelian animist. Taking Robert Boyle as an example, I then show that early modern arguments against animism were often effective only against Platonic (...) animism. In fact, unacknowledged traces of Aristotelian animism can be found in Boyle’s mechanical account of nature. This was Gilbert’s legacy. (shrink)

While ideal interventions are acknowledged by many as valuable tools for the analysis of causation, recent discussions have shown that, since there are no ideal interventions on upper-level phenomena that non-reductively supervene on their underlying mechanisms, interventions cannot—contrary to a popular opinion—ground an informative analysis of constitution. This has led some to abandon the project of analyzing constitution in interventionist terms. By contrast, this paper defines the notion of a horizontally surgical intervention, and argues that, when combined with some innocuous (...) metaphysical principles about the relation between upper and lower levels of mechanisms, that notion delivers a sufficient condition for constitution. This, in turn, strengthens the case for an interventionist analysis of constitution. (shrink)

In 1937, John Dewey delivered a lecture to the College of Physicians in Saint Louis. His clear message was that in the practice of medicine it does not suffice for physicians to treat just the body, or to look to just the body for the mechanism of disease. Emphasizing the relational nature of organism-environment, he argued that the physician must treat the whole patient and must therefore consider the environment of the patient. It makes no sense, he suggested, to provide (...) medicine to address a problem with the patient's lungs and then to send him back into the coal mine. As he put it: "We must observe and understand internal processes and their interactions from the standpoint of their interactions with what is... (shrink)

Cartwright et al. in European Journal for Philosophy of Science, 10 and the new mechanists agree that regular behaviors described in cp laws are generated by mechanisms. However, there is disagreement with regard to the two questions that Cartwright at al. ask: the epistemological question and the ontological question. Most importantly, Cartwright et al. argue that the explanation involved is a CL-explanation, while the new mechanists insist that mechanistic explanation and CL-explanation are competitors. In this reply, I will highlight some (...) worries regarding Cartwright et al.’s analysis of the relationship between mechanisms and cp laws and I will provide alternative answers to the two questions in line with the new mechanistic approach. (shrink)

Many authors have turned their attention to the notion of constitution to determine whether the hypothesis of extended cognition (EC) is true. One common strategy is to make sense of constitution in terms of the new mechanists’ mutual manipulability account (MM). In this paper I will show that MM is insufficient. The Challenge of Trivial Extendedness arises due to the fact that mechanisms for cognitive behaviors are extended in a way that should not count as verifying EC. This challenge can (...) be met by adding a necessary condition: cognitive constituents satisfy MM and they are what I call behavior unspecific. (shrink)

Recent research in philosophy of science has shown that scientists rely on a plurality of strategies to develop successful explanations of different types of phenomena. In the case of biology, most of these strategies go far beyond the traditional and reductionistic models of scientific explanation that have proven so successful in the fundamental sciences. Concretely, in the last two decades, philosophers of science have discovered the existence of at least two different types of scientific explanation at work in the biological (...) sciences, namely: mechanistic and structural explanations. Despite the growing evidence about the radically different nature of these two types of explanation, no inquiry has been conducted to date to determine the ontological reasons that might underlie these differences, nor the way in which these types of explanations can be systematically related with each other. Here, we aim to cover this gap by connecting this plurality of research strategies with the existence of emergent levels of reality. We argue that the existence of these different—and apparently incompatible—explanatory strategies to account for biological phenomena derives from the existence of “ontological jumps” in nature, which generate different regimes of causation that in turn demand the development of different explanatory frameworks. We identify two of these strategies—mechanistic modelling and network modelling—and connect them to the existence of two ontological regimes of causation. Finally, we relate them with each other in a systematic way. In this vein, our paper provides an ontological justification for the plurality of explanatory strategies that we see in the life sciences. (shrink)

Some proponents of mechanistic explanation downplay the significance of how-possibly explanations. We argue that developing accounts of mechanisms that could explain a phenomenon is an important aspect of scientific reasoning, one that involves imagination. Although appeals to imagination may seem to obscure the process of reasoning, we illustrate how, by examining diagrams we can gain insights into the construction of mechanistic explanations.

Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with reference (...) to the debate over realism about physical computation and computationalism. A welcome exception is Dewhurst’s ([2018]) recent analysis of computational individuation under the mechanistic framework. He rejects the idea of appealing to semantic properties for determining the computational identity of a physical system. But Dewhurst seems to be too quick to pay the price of giving up the notion of computational equivalence. We aim to show that the mechanist need not pay this price. The mechanistic framework can, in principle, preserve the idea of computational equivalence even between two different enough kinds of physical systems, say, electrical and hydraulic ones. (shrink)

One of Stuart Glennan's most prominent contributions to the new mechanist debate consists in his reductive analysis of higher-level causation in terms of mechanisms (Glennan, 1996). In this paper I employ the causal Bayes net framework to reconstruct his analysis. This allows for specifying general assumptions which have to be satis ed to get Glennan's approach working. I show that once these assumptions are in place, they imply (against the background of the causal Bayes net machinery) that higher-level causation indeed (...) reduces to interactions between component parts of mechanisms. I also briefly discuss the plausibility of these assumptions and some consequences for the mechanism debate. (shrink)

It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so. Although agreeing with the spirit of this proposal, we argue that the underlying conception of mechanistic evidence as evidence that is different in kind from correlational, difference-making or statistical evidence, does not correctly capture the role that information about (...) mechanisms should play in evidence-based policy. We offer an alternative account of mechanistic evidence as information concerning the causal pathway connecting the policy intervention to its outcome. Not only can this be analyzed as evidence of difference-making, it is also to be found at any level and is obtainable by a broad range of methods, both experimental and observational. Using behavioral policy as an illustration, we draw the implications of this revised understanding of mechanistic evidence for debates concerning policy extrapolation, evidence hierarchies, and evidence integration. (shrink)

Is there a field of social intelligence? Many various disciplines approach the subject and it may only seem natural to suppose that different fields of study aim at explaining different phenomena; in other words, there is no special field of study of social intelligence. In this paper, I argue for an opposite claim. Namely, there is a way to integrate research on social intelligence, as long as one accepts the mechanistic account to explanation. Mechanistic integration of different explanations, however, comes (...) at a cost: mechanism requires explanatory models to be fairly complete and realistic, and this does not seem to be the case for many models concerning social intelligence, especially models of economical behavior. Such models need either be made more realistic, or they would not count as contributing to the same field. I stress that the focus on integration does not lead to ruthless reductionism; on the contrary, mechanistic explanations are best understood as explanatorily pluralistic. (shrink)

The focus of this special issue of Theory & Psychology is on explanatory mechanisms in psychology, especially on problems of particular prominence for psychological science such as theoretical integration and unification. Proponents of the framework of mechanistic explanation claim, in short, that satisfactory explanations in psychology and related fields are causal. They stress the importance of explaining phenomena by describing mechanisms that are responsible for them, in particular by elucidating how the organization of component parts and operations in mechanisms gives (...) rise to phenomena in certain conditions. We hope for cross-pollination between philosophical approaches to explanation and experimental psychology, which could offer methodological guidance, in particular where mechanism discovery and theoretical integration are at issue. Contributions in this issue pertain to theoretical integration and unification of psychology as well as the growing importance of causal mechanistic explanations in psychological science. (shrink)

An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s (forthcoming) deductive-mathematical account, because it is modelled on the deductive-nomological account, is unlikely to satisfy these desiderata. I provide a counterfactual account of DME, the Narrow (...) Ontic Counterfactual Account (NOCA), that can satisfy all three desiderata. NOCA appeals to ontic considerations to account for explanatory asymmetry and ground the relevant counterfactuals. NOCA provides a unification of the causal and the non-causal, the ontic and the modal, by identifying a common core that all explanations share and in virtue of which they are explanatory. (shrink)

In this paper we defend the view that mechanisms are underpinned by networks of difference-making relations. First, we distinguish and criticise two different kinds of arguments in favour of an activity-based understanding of mechanism: Glennan’s metaphysics- first approach and Illari and Williamson’s science-first approach. Second, we present an alternative difference-making view of mechanism and illustrate it by looking at the history of the case of scurvy prevention. We use the case of scurvy to argue that evidence for a mechanism just (...) is evidence for difference-making relations. (shrink)

The emergence of large-scale social media systems, such as Wikipedia, Facebook, and Twitter, has given rise to a new multi-disciplinary effort based around the concept of social machines. For the most part, this research effort has limited its attention to the study of Web-based systems. It has also, perhaps unsurprisingly, tended to highlight the social scientific relevance of such systems. The present paper seeks to expand the scope of the social machine research effort to encompass the Internet of Things. One (...) advantage of this expansion is that it helps to reveal some of the links between the science of social machines and the sciences of the mind. A second advantage is that it furthers our conceptual understanding of social machines and supports the quest to derive a philosophically-robust definition of the term “social machine.” The results of the present analysis suggest that social machines are best conceived as systems in which a combination of social and technological elements play a role in the mechanistic realization of system-level phenomena. The analysis also highlights the relevance of cognitive science and the philosophy of mind to our general understanding of systems that transcend the cyber, physical, and social domains. (shrink)

I propose a metaphysical theory of mechanisms based on the notion of causation. In particular, I use causation to formulate existence, identity, and parthood conditions for mechanisms. These conditions provide a sound metaphysical basis for accounts of mechanistic explanation, mechanistic organization, and for more restrictive theories of mechanisms.

Generalization from a case study is a perennial issue in the methodology of the social sciences. The case study is one of the most important research designs in many social scientific fields, but no shared understanding exists of the epistemic import of case studies. This article suggests that the idea of mechanism-based theorizing provides a fruitful basis for understanding how case studies contribute to a general understanding of social phenomena. This approach is illustrated with a re- construction of Espeland and (...) Sauder's case study of the effects of rankings on US legal education. On the basis of the reconstruction, it is argued that, at least with respect to sociology, the idea of mechanism-based theorizing captures many of the generalizable elements of case studies. (shrink)

While ideal interventions are acknowledged by many as valuable tools for the analysis of causation, recent discussions have shown that, since there are no ideal interventions on upper-level phenomena that non-reductively supervene on their underlying mechanisms, interventions cannot—contrary to a popular opinion—ground an informative analysis of constitution. This has led some to abandon the project of analyzing constitution in interventionist terms. By contrast, this paper defines the notion of a horizontally surgical intervention, and argues that, when combined with some innocuous (...) metaphysical principles about the relation between upper and lower levels of mechanisms, that notion delivers a sufficient condition for constitution. This, in turn, strengthens the case for an interventionist analysis of constitution. (shrink)

Philosophical discussions of systems biology have enriched the notion of mechanistic explanation by pointing to the role of mathematical modeling. However, such accounts still focus on explanation in terms of tracking a mechanism's operation across time (by means of mental or computational simulation). My contention is that there are explanations of molecular systems where the explanatory understanding does not consist in tracking a mechanism's operation and productive continuity. I make this case by a discussion of bifurcation analysis in dynamical systems, (...) articulating the distinctive way in which explanatory understanding is provided, especially about the reversibility or irreversibility of molecular processes. (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)

We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction (...) strategies serve various aims, including prediction and control, that are central to understanding the epistemic diversity of systems biology. (shrink)

The appeal to mechanisms in scientific explanation is commonplace in contemporary philosophy of science. In short, mechanists argue that an explanation of a phenomenon consists of citing the mechanism that brings the phenomenon about. In this paper, we present an argument that challenges the universality of mechanistic explanation: in explanations of the contemporary features of the eukaryotic cell, biologists appeal to its symbiogenetic origin and therefore the notion of symbiogenesis plays the main explanatory role. We defend the notion that symbiogenesis (...) is non-mechanistic in nature and that any attempt to explain some of the contemporary features of the eukaryotic cell mechanistically turns out to be at least insufficient and sometimes fails to address the question that is asked. Finally, we suggest that symbiogenesis is better understood as a pragmatic scientific law and present an alternative non-mechanistic model of scientific explanation. In the model we present, the use of scientific laws is supposed to be a minimal requirement of all scientific explanations, since the purpose of a scientific explanation is to make phenomena expectable. Therefore, this model would help to understand biologists’ appeal to the notion of symbiosis and thus is shown to be better, for the case under examination, than the mechanistic alternative. (shrink)

This paper investigates the relationship between structural explanation and the New Mechanistic account of explanation. The aim of this paper is twofold: firstly, to argue that some phenomena in the domain of fundamental physics, although mechanically brute, are structurally explained; and secondly, by elaborating on the contrast between SE and mechanistic explanation to better clarify some features of SE. Finally, this paper will argue that, notwithstanding their apparently antithetical character, SE and ME can be reconciled within a unified account of (...) general scientific explanation. (shrink)

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...) noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive “patches” of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain’s capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus. (shrink)

I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation of chemotaxis (...) in Escherichia coli—I argue that each strategy invokes a different combination of abstraction types and that each targets its abstractions to different mechanistic details. (shrink)

Constitutive mechanistic explanations are said to refer to mechanisms that constitute the phenomenon-to-be-explained. The most prominent approach of how to understand this constitution relation is Carl Craver’s mutual manipulability approach to constitutive relevance. Recently, the mutual manipulability approach has come under attack (Leuridan 2012; Baumgartner and Gebharter 2015; Romero 2015; Harinen 2014; Casini and Baumgartner 2016). Roughly, it is argued that this approach is inconsistent because it is spelled out in terms of interventionism (which is an approach to causation), whereas (...) constitutive relevance is said to be a non-causal relation. In this paper, I will discuss a strategy of how to resolve this inconsistency, so-called fat-handedness approaches (Baumgartner and Gebharter 2015; Casini and Baumgartner 2016; Romero 2015). I will argue that these approaches are problematic. I will present a novel suggestion of how to consistently define constitutive relevance in terms of interventionism. My approach is based on a causal interpretation of mutual manipulability, where manipulability is interpreted as a causal relation between the mechanism’s components and temporal parts of the phenomenon. (shrink)

Current debates about the integration of traditional and academic ecological knowledge struggle with a dilemma of division and assimilation. On the one hand, the emphasis on differences between traditional and academic perspectives has been criticized as creating an artificial divide that brands TEK as “non-scientific” and contributes to its marginalization. On the other hand, there has been increased concern about inadequate assimilation of Indigenous and other traditional perspectives into scientific practices that disregards the holistic nature and values of TEK. The (...) aim of this article is to develop a practice-based account of the epistemic relations between TEK and AEK that avoids both horns of the dilemma. While relations between TEK and AEK are often described in terms of the “holistic” nature of the former and the “mechanistic” character of the latter, we argue that a simple holism–mechanism divide misrepresents the epistemic resources of both TEK and AEK. Based on the literature on mechanistic explanations in philosophy of science, we argue that holders of TEK are perfectly capable of identifying mechanisms that underlie ecological phenomena while AEK often relies on non-mechanistic strategies of dealing with ecological complexity. Instead of generic characterizations of knowledge systems as either mechanistic or holistic, we propose to approach epistemic relations between knowledge systems by analyzing their heuristics in practice. (shrink)

In this paper, we argue that several recent ‘wide’ perspectives on cognition (embodied, embedded, extended, enactive, and distributed) are only partially relevant to the study of cognition. While these wide accounts override traditional methodological individualism, the study of cognition has already progressed beyond these proposed perspectives towards building integrated explanations of the mechanisms involved, including not only internal submechanisms but also interactions with others, groups, cognitive artifacts, and their environment. The claim is substantiated with reference to recent developments in the (...) study of “mindreading” and debates on emotions. We claim that the current practice in cognitive (neuro)science has undergone, in effect, a silent mechanistic revolution, and has turned from initial binary oppositions and abstract proposals towards the integration of wide perspectives with the rest of the cognitive (neuro)sciences. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...) to save the standard mechanistic view of computation—it trivialises the appeal to mechanism, and thus makes the account collapse into a purely functional view. I claim, however, that the objection can be put to rest once the account is appropriately amended: computational individuation is indeed functional, while mechanistic explanation plays a role in accounting for computational implementation. Since individuation and implementation are crucial elements in a satisfying account of computation in physical systems, mechanism keeps its central importance in the theory of concrete computation. Finally, I argue that my version of the mechanistic view helps to provide a convincing reply to a powerful objection against non-semantic theories of concrete computation: the argument from the multiplicity of computations. (shrink)

Mechanisms are organized collections of objects and activities that underlie certain phenomena/behaviours. In this article, I shall argue that the organizations of mechanisms should be thought of as external relations, namely, as relations that do not entirely depend on their relata’s existence, nor on their natures, nor on their intrinsic properties. After having introduced in the first two sections mechanisms and the ontology of relations, I shall analyse the organizations of mechanisms along four different dimensions: spatial, temporal, causal and hierarchical. (...) I shall demonstrate that each dimension requires that organizations be taken as external relations. Finally, in the last section, I shall anticipate and reply to two objections. (shrink)