The current antireductionist consensus rests in part on the indefensibility of the deductive-nomological model of explanation, on which classical reductionism depends. I argue that the DN model is inessential to the reductionist program and that mechanism provides a better framework for thinking about reductionism. This runs counter to the contemporary mechanists’ claim that mechanism is an alternative to reductionism. I demonstrate that mechanists are committed to reductionism, as evidenced by the historical roots of the contemporary mechanist program. This view shares (...) certain core commitments with reductionism. It is these shared commitments that constitute the essential elements of the reductionist program. (shrink)

Mechanistic explanation is at present the received view of scientific explanation. One of its central features is the idea that mechanistic explanations are both “downward looking” and “upward looking”: they explain by offering information about the internal constitution of the mechanism as well as the larger environment in which the mechanism is situated. That is, they offer both constitutive and contextual explanatory information. Adequate mechanistic explanations, on this view, accommodate the full range of explanatory factors both “above” and “below” the (...) target phenomenon. The aim of this paper is to demonstrate that mechanistic explanation cannot furnish both constitutive and contextual information simultaneously, because these are different types of explanation with distinctly different aims. Claims that they can, I argue, depend on several intertwined confusions concerning the nature of explanation. Particularly, such claims tend to conflate mechanistic and functional explanation, which I argue ought to be understood as distinct. Conflating them threatens to oversell the explanatory power of mechanisms and obscures the means by which they explain. I offer two broad reasons in favor of distinguishing mechanistic and functional explanation: the first concerns the direction of explanation of each, and the second concerns the type of questions to which these explanations offer answers. I suggest an alternative picture on which mechanistic explanation is understood as fundamentally constitutive, and according to which an adequate understanding of a phenomenon typically requires supplementing the mechanistic explanation with a functional explanation. (shrink)

A tension exists between those who do—e.g. Meyer (The British Journal for the Philosophy of Science 71:959–985, 2020 ) and Chemero ( 2011 )—and those who do not—e.g. Kaplan and Craver (Philosophy of Science 78:601–627, 2011 ) Piccinini and Craver (Synthese 183:283–311, 2011 )—afford nonmechanistic explanations a role in cognitive science. Here, I argue that one’s perspective on this matter will cohere with one’s interpretation of the tasks of cognitive science; that is, of the actions for which cognitive scientists are (...) specially fitted. To make this point concrete, I consider two tasks of cognitive science—establishing causal claims and unifying—and show how these tasks are interpreted differently by mechanists and nonmechanists respectively. I then argue that, as a result of these different interpretations, we cannot expect to resolve the tension between mechanists and nonmechanists by appeal to cognitive scientific practice. I conclude that we should give up on the debate between mechanists and nonmechanists, and search for progress elsewhere. (shrink)

Some philosophers argue that we should eschew cross-explanatory integrations of mechanistic, dynamicist, and psychological explanations in cognitive science, because, unlike integrations of mechanistic explanations, they do not deliver genuine, cognitive scientific explanations. Here I challenge this claim by comparing the theoretical virtues of both kinds of explanatory integrations. I first identify two theoretical virtues of integrations of mechanistic explanations—unification and greater qualitative parsimony—and argue that no cross-explanatory integration could have such virtues. However, I go on to argue that this is (...) only a problem for those who think that cognitive science aims to specify one fundamental structure responsible for cognition. For those who do not, cross-explanatory integration will have at least two theoretical virtues to a greater extent than integrations of mechanistic explanations: explanatory depth and applicability. I conclude that one’s views about explanatory integration in cognitive science cannot be segregated from one’s views about the explanatory task of cognitive science. (shrink)

Kaplan and Craver :601–627, 2011) and Piccinini and Craver :283–311, 2011) argue that only mechanistic explanations of cognition are genuine causal explanations, because only evidence of mechanisms reveals the causal structure of cognition. I first argue that this claim is grounded in a commitment to the mechanistic account of causality, which cannot be endorsed by a defender of causal-nonmechanistic explanations. Then, I defend the epistemic theory of causality, which holds that causal explanations are not genuine to the extent that they (...) reveal mechanistic causal structure, but, rather, to the extent that they have evidential support and yield successful prediction, explanation, and control inferences. Finally, I enact an epistemic unification of causal explanation in cognitive science, according to which both mechanistic and nonmechanistic explanations of cognition can be genuine causal explanations. (shrink)

Recent extensions of mechanistic explanation into psychology suggest that cognitive models are only explanatory insofar as they map neatly onto, and serve as scaffolding for more detailed neural models. Filling in those neural details is what these accounts take the integration of cognitive psychology and neuroscience to mean, and they take this process to be seamless. Critics of this view have given up on cognitive models possibly explaining mechanistically in the course of arguing for cognitive models having explanatory value independent (...) of how well they align with neural mechanisms. We can have things both ways, however. The problem with seamless integration accounts is their seamlessness, not that they take cognitive models to be mechanistic. A non-componential view of mechanisms allows for cognitive and neural models that cross cut one another, and for cognitive models that don’t decompose into parts. I illustrate the inadequacy of seamless accounts of integration by contrasting how “filter” models of attention in psychology and of sodium channels in neuroscience developed; by questioning whether the mappings generated by neuroimaging subtraction studies achieve integration; and by reinterpreting the evidence for cognitive models of memory having been successfully integrated with neural models. I argue that the integrations we can realistically expect are more partial, patchy, and full of loose threads than the mosaic unity Craver describes. (shrink)

Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the account is (...) still unsuccessful as it stands. Consequently, he advances a proposal for shoring up the account, which is founded on the possibility of acquiring knowledge of social mechanisms by linking together norms or practices found in a society. Key Words: causality • social mechanisms • interpretation • anthropology. (shrink)

There have been a number of attempts to apply mechanism-related concepts to the notion of extended cognition. Such accounts appeal to the idea that extended cognitive routines are realized by mechanisms that transcend some salient border or boundary. The present paper describes some of the challenges confronting the effort to develop a mechanistic account of extended cognition. In particular, it describes five problems that must be resolved if we are to make sense of the idea that extended cognition can be (...) understood via an appeal to extended mechanisms. These problems are intended to guide the philosophical effort to develop a mechanistic account of extended cognition. (shrink)

Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines, there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of (...) the social machine community. The present paper outlines an approach to understanding social machines that draws on recent work in the philosophy of science, especially work in so-called mechanical philosophy. This is what might be called a mechanistic view of social machines. According to this view, social machines are systems whose phenomena are explained via an appeal to socio-technical mechanisms. We show how this account is able to accommodate a number of existing attempts to define the social machine concept, thereby yielding an important opportunity for theoretical integration. (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.

Biological processes are often explained by identifying the underlying mechanisms that generate a phenomenon of interest. I characterize a basic account of mechanistic explanation and then present three challenges to this account, illustrated with examples from molecular biology. The basic mechanistic account is insufficient for explaining nonsequential and nonlinear dynamic processes, is insufficient for explaining the inherently stochastic nature of many biological mechanisms, and fails to give a proper framework for analyzing organization. I suggest that biological processes are best approached (...) as a multidimensional gradient—with some processes being paradigmatic cases of mechanisms and some being marginal cases. (shrink)

I argue (1) that what (ontic) New Mechanistic philosophers of science call mechanisms would be material Gestalten, and (2) that Merleau-Ponty’s engagement with Gestalt theory can help us frame a standing challenge against ontic conceptions of mechanisms. In short, until the (ontic) New Mechanist can provide us with a plausible account of the organization of mechanisms as an objective feature of mind-independent ontic structures in the world which we might discover – and no ontic Mechanist has done so – it (...) is more conservative to claim that mechanistic organization is instead a mind-dependent aspect of our epistemic strategies of mechanistic explanation. (shrink)

In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...) When every ounce of your concentration is fixed upon blasting a winged pig out of the sky, you do not question its species' ontological status. James Morrow, City of Truth (1990). (shrink)

In this paper, I propose two theses, and then examine what the consequences of those theses are for discussions of reduction and emergence. The first thesis is that what have traditionally been seen as robust, reductions of one theory or one branch of science by another more fundamental one are a largely a myth. Although there are such reductions in the physical sciences, they are quite rare, and depend on special requirements. In the biological sciences, these prima facie sweeping reductions (...) fade away, like the body of the famous Cheshire cat, leaving only a smile.... The second thesis is that the "smiles" are fragmentary patchy explanations, and though patchy and fragmentary, they are very important, potentially Nobel-prize winning advances. To get the best grasp of these "smiles," I want to argue that, we need to return to the roots of discussions and analyses of scientific explanation more generally, and not focus mainly on reduction models, though three conditions based on earlier reduction models are retained in the present analysis. I briefly review the scientific explanation literature as it relates to reduction, and then offer my account of explanation. The account of scientific explanation I present is one I have discussed before, but in this paper I try to simplify it, and characterize it as involving field elements and a preferred causal model system abbreviated as FE and PCMS. In an important sense, this FE and PCMS analysis locates an "explanation" in a typical scientific research article. This FE and PCMS account is illustrated using a recent set of neurogenetic papers on two kinds of worm foraging behaviors: solitary and social feeding. One of the preferred model systems from a 2002 Nature article in this set is used to exemplify the FE and PCMS analysis, which is shown to have both reductive and nonreductive aspects. The paper closes with a brief discussion of how this FE and PCMS approach differs from and is congruent with Bickle's "ruthless reductionism" and the recently revived mechanistic philosophy of science of Machamer, Darden, and Craver. (shrink)

In his seminal Inference to the Best Explanation, Peter Lipton adopted a causal view of explanation and a broadly Millian view of how causal knowledge is obtained. This made his account vulnerable to critics who charged that Inference to the Best Explanation is merely a dressed-up version of Mill’s methods, which in the critics’ view do the real inductive work. Lipton advanced two arguments to protect Inference to the Best Explanation against this line of criticism: the problem of multiple differences (...) and the problem of inferred differences. Lipton claimed that these two problems show Mill’s method of difference to be largely unworkable unless it is embedded in an explanationist framework. Here I consider both arguments as well as the best Millian defense against them. Since the existing Millian defense is only partially successful, I will develop a new and improved account. As an integral part of the argument, I show that my solutions to the problems of multiple and inferred differences offer new insight into Lipton’s main case study: Ignaz Semmelweis’s discovery of the cause of childbed fever. I conclude that the method of difference can overcome Lipton’s challenges outside an explanationist framework. (shrink)

Semmelweis’s discovery of the cause of puerperal fever around the middle of the 19th century counts among the paradigm cases of scientific discovery. For several decades, philosophers of science have used the episode to illustrate, appraise and compare views of proper scientific methodology.Here I argue that the episode can be profitably reexamined in light of two cognate notions: causal reasoning and mechanisms. Semmelweis used several causal reasoning strategies both to support his own and to reject competing hypotheses. However, these strategies (...) have gone unappreciated in the existing literature. I show that a causal reasoning approach makes sense of the multitude of tables in Semmelweis’s main text, which in later editions were often abridged because they appeared redundant.Moreover, the existing literature tends to focus on Semmelweis’s clinical intervention and on the extent to which it alone confirms his theoretical conclusions. This neglects Semmelweis’s efforts to show by animal experiments that his clinical results are in agreement with a demonstrable mechanism of puerperal fever pathogenesis. I argue that the full evidential force of Semmelweis’s argument can only be appreciated if both his clinical and his laboratory investigations are taken into account. (shrink)

This article focuses on emergence in social systems. The author begins by proposing a new tool to explore the mechanisms of social emergence: multi agent–based computer simulation. He then draws on philosophy of mind to develop an account of social emergence that raises potential problems for the methodological individualism of both social mechanism and of multi agent simulation. He then draws on various complexity concepts to propose a set of criteria whereby one can determine whether a given social mechanism generates (...) emergent properties, in the sense that their explanation cannot be reduced to a mechanistic account of individuals and their interactions. This combined account helps to resolve the competing claims of methodological individualists and social realists. The author’s conclusion is that the scope of mechanistic explanation may be limited due to the extreme complexity of many social systems. Key Words: emergence • mechanism • computer simulation • methodological individualism • social realism. (shrink)

I explore a type of computational social simulation known as artificial societies. Artificial society simulations are dynamic models of real-world social phenomena. I explore the role that these simulations play in social explanation, by situating these simulations within contemporary philosophical work on explanation and on models. Many contemporary philosophers have argued that models provide causal explanations in science, and that models are necessary mediators between theory and data. I argue that artificial society simulations provide causal mechanistic explanations. I conclude that (...) in their current form, these simulations are based on methodologically individualist assumptions that could limit their potential scope of social explanation. (shrink)

Biological sciences have strived to adopt the conceptual framework of physics and have become increasingly quantitatively oriented, aiming to refute the assertion that biology appears unquantifiable, unpredictable, and messy. But despite all effort, biology is characterized by a paucity of quantitative statements with universal applications. Nonetheless, many biological disciplines—most notably molecular biology—have experienced an ascendancy over the last 50 years. The underlying core concepts and ideas permeate and inform many neighboring disciplines. This surprising success is probably not so much attributable (...) to mathematical and statistical approaches in molecular biology, but rather to the preponderance of qualitative approaches, especially visualization. Visualizations can be afforded by quantitative research, but usually they rely on both, quantitative and qualitative research. I claim the following three features to be responsible for the unceasing zeal for using visualizations: visual representations facilitate reasoning, images can be cognitively processed in a “fast” manner, and abstractions of visual representations prompt conceptual advances. In summary, visualizations have largely contributed to the success of molecular biology by conveying its concepts to other disciplines, and at the same time, eclipsing mere quantitative approaches. However, visualizations also bear the risk of misinterpretation when traversing neighboring disciplines and even more so when pervading nonscientific domains. (shrink)

Powers are properties defined by what they do. The focus of the large majority of the powers literature has been mainly put on explicating the (multifaceted) results of the production of a power in certain (multifaceted) initial conditions: but all this causal complexity is bound to be—and, in fact, it has proved to be—quite difficult to handle. In this paper we take a different approach by focusing on the very activity of producing those multifaceted manifestations themselves. In this paper, we (...) propose an original account of what the essence of a power consists in which stems from a radical reconceptualisation of power-causation according to which counterfactuals are to be explained away by powers, and not vice-versa. We call this approach the dynamical operator account of powers. According to this account, the causal role of powers consists in their ensuring that the ontological transition from a stimulus S to a manifestation M happens. Powers thus have a dynamical essence which consists in the fundamental activity of generating the counterfactuals typically associated with them. We show that if one conceptualises this functional activity as the metaphysical fulcrum around which counterfactual-based causation revolves, one is granted not only an improved methodology to individuate powers but also a better understanding of their knowability, modality and directedness. (shrink)

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman’s account of minimal model explanations and that it demonstrates (...) how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated. (shrink)

According to mainstream philosophical views causal explanation in biology and neuroscience is mechanistic. As the term ‘mechanism’ gets regular use in these fields it is unsurprising that philosophers consider it important to scientific explanation. What is surprising is that they consider it the only causal term of importance. This paper provides an analysis of a new causal concept—it examines the cascade concept in science and the causal structure it refers to. I argue that this concept is importantly different from the (...) notion of mechanism and that this difference matters for our understanding of causation and explanation in science. (shrink)

In the last two decades few topics in philosophy of science have received as much attention as mechanistic explanation. A significant motivation for these accounts is that scientists frequently use the term “mechanism” in their explanations of biological phenomena. While scientists appeal to a variety of causal concepts in their explanations, many philosophers argue or assume that all of these concepts are well understood with the single notion of mechanism. This reveals a significant problem with mainstream mechanistic accounts– although philosophers (...) use the term “mechanism” interchangeably with other causal concepts, this is not something that scientists always do. This paper analyses two causal concepts in biology–the notions of “mechanism” and “pathway”–and how they figure in biological explanation. I argue that these concepts have unique features, that they are associated with distinct strategies of causal investigation, and that they figure in importantly different types of explanation. (shrink)

The experimental interventions that provide evidence of causal relations are notably similar to those that provide evidence of constitutive relevance relations. In the first two sections, I show that this similarity creates a tension: there is an inconsistent triad between Woodward’s popular interventionist theory of causation, Craver’s mutual manipulability account of constitutive relevance in mechanisms, and a variety of arguments for the incoherence of inter-level causation. I argue for an interpretation of the views in which the tension is merely apparent. (...) I propose to explain inter-level relations without inter-level causation by appealing to the notion of fat-handed interventions, and an argument against inter-level causation which dissolves the problem. (shrink)

Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance of the (...) mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. (shrink)

ABSTRACTMeasurements of environmental toxicity from long-term exposure to oil contamination have delivered inaccurate and contradictory results regarding the potential harms for humans and ecosyste...

According to Philip Kitcher, scientific unification is achieved via the derivation of numerous scientific statements from economies of argument schemata. I demonstrate that the unification of selection phenomena across domains in which it is claimed to occur--evolutionary biology, immunology and, speculatively, neurobiology--is unattainable on Kitcher's view. I then introduce an alternative method for rendering the desired unification based on the concept of a mechanism schema. I conclude that the gain in unification provided by the alternative account suggests that Kitcher's view (...) is defective. (shrink)

Persistence theories of causation – such as transference theory, conserved-quantity theory, and Douglas Ehring's theory – attempt to analyzecausation in terms of some persisting entityconnecting cause and effect. While mostpersistence accounts are intended as empiricaltheories, this article develops a persistenceanalysis of the concept of causation. The basic idea is that the central concept ofdirect causation can be analyzed in terms ofproperty acquisition. The analysis cohereswith our ordinary causal judgments andprovides a straightforward explanation of thedirection of causation. It also explains whybackwards (...) causation is conceptually problematic. (shrink)

This article argues that empirical social scientists can be freed from having to account for “micro-to-macro transitions.” The article shows, in opposition to the (still) dominant perspective based on Coleman’s macro-micro-macro model, that no micro-macro transitions or mechanisms connect the individual level to the macro level in empirical social science. Rather, when considering that social macro entities and properties are micro manifest rather than macro manifest, it becomes clear that the micro-macro move in empirical social science is purely conceptual or (...) analytical. (shrink)

How are scientific explanations possible in ecology, given that there do not appear to be many—if any—ecological laws? To answer this question, I present and defend an account of scientific causal explanation in which ecological generalizations are explanatory if they are invariant rather than lawlike. An invariant generalization continues to hold or be valid under a special change—called an intervention—that changes the value of its variables. According to this account, causes are difference-makers that can be intervened upon to manipulate or (...) control their effects. I apply the account to ecological generalizations to show that invariance under interventions as a criterion of explanatory relevance provides interesting interpretations for the explanatory status of many ecological generalizations. Thus, I argue that there could be causal explanations in ecology by generalizations that are not, in a strict sense, laws. I also address the issue of mechanistic explanations in ecology by arguing that invariance and modularity constitute such explanations. (shrink)

Philosophers of science have examined The Theory of Island Biogeography by Robert MacArthur and E. O. Wilson (1967) mainly due to its important contribution to modeling in ecology, but they have not examined it as a representative case of ecological explanation. In this paper, I scrutinize the type of explanation used in this paradigmatic work of ecology. I describe the philosophy of science of MacArthur and Wilson and show that it is mechanistic. Based on this account and in light of (...) contributions to the mechanistic conception of explanation due to Craver (2007), and Bechtel and Richardson (1993), I argue that MacArthur and Wilson use a mechanistic approach to explain the species-area relationship. In light of this examination, I formulate a normative account of mechanistic explanation in ecology. Furthermore, I argue that it offers a basis for methodological unification of ecology and solves a dispute on the nature of ecology. Lastly, I show that proposals for a new paradigm of biogeography appear to maintain the norms of mechanistic explanation implicit in The Theory of Island Biogeography. (shrink)

: Among the current philosophical accounts of causation two are the most prominent. The first is James Woodward's interventionist counterfactual approach; the second is the mechanistic approach advocated by Peter Machamer, Lindley Darden, Carl Craver, Jim Bogen and Stuart Glennan. Thecounterfactual approach takes it that causes make a difference to their effects, where this difference-making is cashed out in terms of actual and counterfactual interventions. The mechanistic approach takes it that two events are causally related if and only if there (...) is a mechanism that connects them. In this paper I examine them both in some detail. After pointing out some important problems that both approaches face, I argue that there is a sense in which the counterfactual approach is more basic than the mechanistic one in that a proper account of mechanisms depends on counterfactuals while counterfactuals need not be supported (or depend on) mechanisms. Nonetheless, I also argue that if both approaches work in tandem in practice, they can offer us a better understanding of aspects of Hume's secret connexion and hence a glimpse of it. (shrink)

The past two decades have witnessed an increase in interest in social mechanisms and mechanistic explanations of social macro-phenomena. This paper addresses the question of what the components of social mechanisms in mechanistic explanations of social macro-phenomena must be. Analytical sociology’s initial position and the main new proposals by analytical sociologists are discussed. It is argued that all of them are faced with outstanding difficulties. Subsequently, a minimal requirement regarding the components of social mechanisms is introduced. It is held that (...) a component of a social mechanism in a mechanistic explanation of a social macro-phenomenon must not have the explanandum phenomenon as a part of it. (shrink)

In this paper, we address the question whether a mechanistic approach can account for evolutionary causes. The last decade has seen a major attempt to account for natural selection as a mechanism. Nevertheless, we stress the relevance of broadening the debate by including the other evolutionary causes inside the mechanistic approach, in order to be a legitimate conceptual framework on the same footing as other approaches to evolutionary theory. We analyse the current debate on natural selection as a mechanism, and (...) extend it to the rest of the evolutionary causes. We focus on three approaches that we call the stochastic view, the functional view, and the minimalist view. We argue that all of them are unable to account for evolutionary causes as mechanisms. It is concluded that the current mechanistic proposals cannot be accepted as a common framework for evolutionary causes. Finally, we outline some guidelines and requirements that any mechanistic proposal should meet in order to be applied to evolutionary theory. (shrink)

Proponents of the predictive processing (PP) framework often claim that one of the framework’s significant virtues is its unificatory power. What is supposedly unified are predictive processes in the mind, and these are explained in virtue of a common prediction error-minimisation (PEM) schema. In this paper, I argue against the claim that PP currently converges towards a unified explanation of cognitive processes. Although the notion of PEM systematically relates a set of posits such as ‘efficiency’ and ‘hierarchical coding’ into a (...) unified conceptual schema, neither the frameworks’ algorithmic specifications nor its hypotheses about their implementations in the brain are clearly unified. I propose a novel way to understand the fruitfulness of the research program in light of a set of research heuristics that are partly shared with those common to Bayesian reverse engineering. An interesting consequence of this proposal is that pluralism is at least as important as unification to promote the positive development of the predictive mind. (shrink)

While loneliness has been linked to various mental and physical health problems, the sense in which loneliness is a cause of these conditions has so far attracted little philosophical attention. This paper aims to fill this gap by analyzing research on health effects of loneliness and therapeutic interventions through current approaches to causality. To deal with the problem of causality between psychological, social, and biological variables, the paper endorses a biopsychosocial model of health and disease. I will investigate how three (...) main approaches to causality used in psychiatry and public health apply to loneliness: interventionism, mechanisms, and dispositional theories. Interventionism can specify whether loneliness causes specific effects, or whether a treatment works, incorporating results from randomized controlled trials. Mechanisms help explain how loneliness brings about negative health effects, spelling out psychological processes involved in lonely social cognition. Dispositional approaches help stress particular features of loneliness connected to negative social interactions, such as defensiveness. I will conclude by showing that previous research alongside emerging approaches to health effects of loneliness lend themselves to analysis in terms of the causal models under discussion. (shrink)

Book Review: De Regt, H. W. Understanding Scientific Understanding. New York: Oxford University Press, 2017.

This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic tools for (...) the improvement of empirically-riven work in the debates about mechanistic explanation of ecological phenomena. (shrink)

My topic is the confluence of two recently active philosophical research programs. One research program concerns the metaphysics of realization. The other research program concerns scientific explanation in terms of mechanisms. In this paper I introduce a distinction between descriptive and explanatory approaches to realization. I then use this distinction to argue that a well-known account of realization, due to Carl Gillett, is incompatible with a well-known account of mechanistic explanation, due to Peter Machamer, Lindley Darden, and Carl Craver (MDC, (...) Philos Sci 57: 1-25, 2000). This is surprising, not least of which because Gillett has cited MDC's work as evidence that his account of realization is the right way to think about realization in the sciences. (shrink)

This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...) It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr’s theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop. (shrink)

Sometimes instances of perceived causation turn out to lack causal relata. The reasons may vary. Causation may display itself as prevention, or as omission, and in some cases causation occurs within such complex environments that few of the things we associate with causes and effects are true of them, etc. But even then, there may be causal explanations to be had. This suggests that the explanatory power of causal reports have other sources than the relation between cause and effect. In (...) this paper it is argued that the causal mechanisms we allude to in explanations have relevant determinables other than the traditionally acknowledged ones. The traditional but in this aspect mistaken view of causation is to be blamed. Discernability, complexity of manifestation, originality, and even stability have often been overlooked. We know, that, in fact, heat is a constant attendant of flame; but what is the connexion between them, we have no room so much as to conjecture or imagine. (Hume 1777, VII. 2, 64). (shrink)

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it (...) is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life. (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)

The homeostatic property cluster theory is widely influential for its ability to account for many natural-kind terms in the life sciences. However, the notion of homeostatic mechanism has never been fully explicated. In 2009, Carl Craver interpreted the notion in the sense articulated in discussions on mechanistic explanation and pointed out that the HPC account equipped with such notion invites interest-relativity. In this paper, we analyze two recent refinements on HPC: one that avoids any reference to the causes of the (...) clustering of properties and one that replaces homeostatic mechanisms with causal networks represented by causal graphs. We argue that the former is too slender to account for some inductive inference in science and the latter, thicker account invites interest-relativity, as the original HPC does. This suggests that human interest will be an un-eliminative part of a satisfactory account of natural kindness. We conclude by discussing the implication of interest-relativity to the naturalness, reality, or objectivity of kinds and indicating an overlooked aspect of natural kinds that requires further studies. (shrink)

Although the literature on the issue of pluralism within the philosophy of science is very extensive, this paper focuses on the metaphysical causal pluralism that emerges from the new mechanistic discussion on causality. The main aim is to situate the new mechanistic views on causation within the account of varieties of causal pluralism framed by Psillos ( 2009 ). Paying attention to his taxonomy of metaphysical views on causation (i.e., the straightjacket view, the functional view, the two-concept view, the agnostic (...) view and the atheist view) will help clarify differences in opinion and, at the same time, make it possible to elucidate the main metaphysical theses present within the new mechanistic debate. Special attention is given to S. Glennan’s theory of causation, since it is unique in offering an overall metaphysical view of the issue. It is also argued that mechanists are not “atheists” on causation: while all of them are causal realists, most mechanists are “agnostic” on causation, with a few exceptions such as S. Glennan, P. Machamer and J. Bogen. (shrink)

This paper discusses the prospect of the "new social history" guided by the recent work of Charles Tilly on the methodology of social and historical explanation. Tilly advocates explanation by mechanisms as the alternative to the covering law explanation. Tilly's proposals are considered to be the attempt to reshape the practices of social and historical explanation following the example set by the explanatory practices of molecular biology, neurobiology, and other recent "success stories" in the life sciences. Recent work in the (...) philosophy of science on these practices by Peter Machamer, Lindley Darden, Carl Craver and others is used as the foil to disclose the difficulties of Tilly's project. Most important among them is the dilemma of specification: if diagrams (standard forms of the representation of mechanisms) are intended as representations of robust causal processes, they cannot be specific enough to provide complete mechanism schemata, and are bound to remain mechanism sketches. If mechanism sketches are elaborated in detail by tracing particular causal processes, they provide representations of fragile causal processes, which cannot be considered as mechanisms comparable to those in advanced life and other special sciences. Tilly's work on the explanation of mechanisms can be considered as symptomatic for the recent trend to visualize the forms of historical representation. As far as diagrams seem to be able to communicate stories in a direct way (without narrative discourse), this trend is a challenge for the theory of historical representation. The new theories of scientific explanation focusing on the explanatory practices of the life sciences can provide examples and be the source of inspiration for the work on the theory of historical and social explanation, going beyond the confines of the received framework of the covering law model of explanation. (shrink)