In line with proponents of 4E cognition, Gallagher [2019] is concerned that many cognitive phenomena are not amenable to decomposition strategies since their very nature is to be constituted extensively. By contrast the received view on causal explanation—the mechanistic account [Craver 2007]—emphasises the necessity for decomposition in explaining natural phenomena and insists on a sharp distinction between causal versus constitutive relations. I propose that removing the requirement that constitutive relations cannot also be causes helps to ease this tension between explanation (...) and Gallagher’s non-decompositional stance, per Leuridan [2012]. Further, I draw on Froese et al.’s [2013] minimal model of social cognition to argue that constitutive relations can and do act as causal difference-makers in the Woodwardian sense [Woodward 2003]. (shrink)

Mechanistic explanations are often said to explain because they reveal the causal structure of the world. Conversely, dynamical models supposedly lack explanatory power because they do not describe causal structure. The only way for dynamical models to produce causal explanations is via the 3M criterion: the model must be mapped onto a mechanism. This framing of the situation has become the received view around the viability of dynamical explanation. In this paper, I argue against this position and show that dynamical (...) models can themselves reveal causal structure and consequently produce nonmechanistic, dynamical explanations. Taking the example of cell fates from systems biology, I show how dynamical models, and specifically the attractor landscapes they describe, identify the causes of cell differentiation and explain why cells select particular fates. These dynamical features of the system better fit Woodward’s (2010, 2018) criteria of specificity and proportionality and make them the best candidate causes of cell fates than mechanisms. I also show how these causes are irreducible and inaccessible to mechanistic models, making 3M unworkable and counterproductive in this case. Dynamical models can reveal dynamical causes and thereby provide causal explanations. (shrink)

Mechanistic explanations, according to one prominent account, are derived from objective explanations (Craver 2007, 2014 ). Mechanistic standards of explanation are in turn pulled from nature, and are thereby insulated from the values of investigators, since explanation is an objectively defined achievement grounded in the causal structure of the world (Craver 2014 ). This results in the closure of mechanism’s explanatory standards—it is insulated from the values, norms and goals of investigators. I raise two problems with this position. First, it (...) relies on several ontological claims which, while plausible, fail to guarantee the objectivity of mechanistic explanatory standards to the degree of certainty required. Second, Craver’s position itself introduces a value–laden explanatory standard—the 3M requirement (Kaplan & Craver 2011 )—which undermines the closure of explanatory standards. I show how in practice mechanistic explanation is in part guided by explanatory taste, shorthand for background contextual values that influence our standards of explanation. Mechanism often has a particular pragmatically-oriented taste for control, and gerrymanders explanatory standards in order to obtain it. I conclude by arguing that objectivity, rather than being obtained through the right set of explanatory standards, is better thought of as the result of processes of intersubjective criticism, which renders visible the contextual values of communities of investigators and allows them to be controlled for (Longino 1990 ). (shrink)

Much contemporary debate on the nature of mechanisms centers on the issue of modulating negative causes. One type of negative causability, which I refer to as "causation by absence," appears difficult to incorporate into modern accounts of mechanistic explanation. This paper argues that a recent attempt to resolve this problem, proposed by Benjamin Barros, requires improvement as it overlooks the fact that not all absences qualify as sources of mechanism failure. I suggest that there are a number of additional types (...) of effects caused by absences that need to be incorporated to account for the diversity of causal connections in the biological sciences. Furthermore, it is argued that recognizing natural variability in mechanisms, such as attenuation, leads to some interesting line-drawing issues for contemporary philosophy of mechanisms. (shrink)

Proponents of evidence-based medicine have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on evidence (...) hierarchies of methodology fails to lend credence to the common practice of corroboration in medicine. I argue that the strength of evidence lies in the evidence itself, and not the methodology used to obtain that evidence. Ultimately, when it comes to evaluating the effectiveness of medical interventions, it is the evidence obtained from the methodology rather than the methodology that should establish the strength of the evidence. (shrink)

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of mechanistic reasoning where it is (...) not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences. (shrink)

It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques of (...) systems biologists as part of a broader practice of constructing and evaluating mechanism schemas. This argument is elaborated by considering the case of bacterial chemotactic networks, where some research has been interpreted as explaining phenomena by means of abstract design principles. (shrink)

The aim of this thesis is to argue in favour of the embodied music cognition paradigm, as opposed to traditional theories of musical mind. The thesis consists of three chapters. The goal of the first chapter is to examine computational music cognition, focusing on the main problem of this approach. In the second chapter, I will present and discuss Marc Leman’s EMC, that may serve as a response to the problems of the computational view of the musical mind. Although this (...) framework is interesting, it is unclear in several places. For that reason, I intend to enrich it with the references to the recent works on human mirror neuron system and enactivist views on music cognition. Given that, in the last chapter, I will answer the question, whether mental representations are necessary in music cognition. (shrink)

In this paper I analyze the process by which modelers in systems biology arrive at an adequate representation of the biological structures thought to underlie data gathered from high-throughput experiments. Contrary to views that causal claims and explanations are rare in systems biology, I argue that in many studies of gene regulatory networks modelers aim at a representation of causal structure. In addressing modeling challenges, they draw on assumptions informed by theory and pragmatic considerations in a manner that is guided (...) by an interventionist conception of causal structure. While doubts have been raised about the applicability of this notion of causality to complex biological systems, it is here seen to be an adequate guide to inquiry. (shrink)

In an instant classic paper ; 2002: 179–182) biologist Yuri Lazebnik deplores the poor effectiveness of the approach adopted by biologists to understand and “fix” biological systems. Lazebnik suggests that to remedy this state of things biologist should take inspiration from the approach used by engineers to design, understand, and troubleshoot technological systems. In the present paper I substantiate Lazebnik’s analysis by concretely showing how to apply the engineering approach to biological problems. I use an actual example of electronic circuit (...) troubleshooting to ground the thesis that, in engineering, the crucial phases of any non-trivial troubleshooting process are aimed at generating a mechanistic explanation of the functioning of the system, which makes extensive recourse to problem-driven qualitative reasoning possibly based on cognitive artifacts applied to systems that are known to have been designed for function. To show how to translate these findings into biological practice I consider a concrete example of biological model building and “troubleshooting”, aimed at the identification of a “fix” for the human immune system in presence of progressing cancer, autoimmune disease, and transplant rejection. The result is a novel immune system model—the danger model with regulatory cells— and new, original hypotheses concerning the development, prophylaxis, and therapy of these unwanted biological processes. Based on the manifest efficacy of the proposed approach, I suggest a refocusing of the activity of theoretical biologists along the engineering-inspired lines illustrated in the paper. (shrink)

Network theory is applied across the sciences to study phenomena as diverse as the spread of SARS, the topology of the cell, the structure of the Internet and job search behaviour. Underlying the study of networks is graph theory. Whether the graph represents a network of neurons, cells, friends or firms, it displays features that exclusively depend on the mathematical properties of the graph itself. However, the way in which graph theory is implemented to the modelling of networks differs significantly (...) across scientific fields. This article compares the economics variant of network theory with those of other fields. It shows how the methodology employed by economists to model networks is shaped by two explanatory desiderata: that the explanandum phenomenon is based on micro-economic foundations and that the explanation is general. (shrink)

Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.

Some psychologists aim to secure a role for psychological explanations in understanding contemporary social disparities, a concern that plays out in debates over the relevance of the Implicit Association Test. Meta-analysts disagree about the predictive validity of the IAT and about the importance of implicit attitudes in explaining racial disparities. Here, I use the IAT to articulate and explore one route to establishing the relevance of psychological attitudes with small effects: an appeal to a process of “accumulation” that aggregates small (...) effects into large harms. After characterizing mechanisms of accumulation and considering some candidate examples, I argue that such mechanisms suggest how a contemporary attitude with small effects could figure in the explanation of large disparities, but they do not vindicate the importance of such an attitude since such mechanisms are typically also determined by competing causes. I close by sketching several strategies for advancing a defense of the relevance of attitudes with small effects. (shrink)

Proponents of mechanistic explanations have recently proclaimed that all explanations in the neurosciences appeal to mechanisms. The purpose of the paper is to critically assess this statement and to develop an integrative account that connects a large range of both mechanistic and dynamical explanations. I develop and defend four theses about the relationship between dynamical and mechanistic explanations: that dynamical explanations are structurally grounded, that they are multiply realizable, possess realizing mechanisms and provide a powerful top-down heuristic. Four examples shall (...) support my points: the harmonic oscillator, the Haken–Kelso–Bunz model of bimanual coordination, the Watt governor and the Gierer–Meinhardt model of biological pattern formation. I also develop the picture of “horizontal” and “vertical” directions of explanations to illustrate the different perspectives of the dynamical and mechanistic approach as well as their potential integration by means of intersection points. (shrink)

Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...) use of this kind of information in risk assessment is heavily influenced by pragmatic factors, which have not been sufficiently taken into account in philosophical analysis. Mechanistic models are like hypothesis that have to be validated empirically. Due to their dependence on the standards of evidence, they are subject to the same pragmatic factors. Therefore, recurring to mechanistic information does not lead to closure of the methodological controversies in risk assessment. (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)

Every scientist chooses a preferred level of analysis and this choice shapes the research program, even determining what counts as evidence. This contribution revisits Marr's three levels of analysis and evaluates the prospect of making progress at each individual level. After reviewing limitations of theorizing within a level, two strategies for integration across levels are considered. One is top–down in that it attempts to build a bridge from the computational to algorithmic level. Limitations of this approach include insufficient theoretical constraint (...) at the computation level to provide a foundation for integration, and that people are suboptimal for reasons other than capacity limitations. Instead, an inside-out approach is forwarded in which all three levels of analysis are integrated via the algorithmic level. This approach maximally leverages mutual data constraints at all levels. For example, algorithmic models can be used to interpret brain imaging data, and brain imaging data can be used to select among competing models. Examples of this approach to integration are provided. This merging of levels raises questions about the relevance of Marr's tripartite view. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

Michael S. Moore defends the ideas of free will and responsibility, especially in relation to criminal law, against several challenges from neuroscience. I agree with Moore that morality and the law presuppose a commonsense understanding of humans as rational agents, who make choices and act for reasons, and that to defend moral and legal responsibility, we must show that this commonsense understanding remains viable. Unlike Moore, however, I do not think that classical compatibilism, which is based on a conditional understanding (...) of the ability to do otherwise, provides a sufficiently robust account of free will, even when it is amended as Moore suggests. I argue that free will and responsibility can be defended more robustly by observing that, at the level of agency, there can be alternative possibilities and mental causation in a stronger sense than recognized by classical compatibilism, even if physical determinism is true. Moore’s arguments could thus be strengthened by embracing this compatibilist libertarian position. At the same time, I note that, although the idea of responsibility is robustly defensible, there are independent reasons for rejecting a retributivist approach to punishment. (shrink)

The Hodgkin–Huxley (HH) model of the action potential is a theoretical pillar of modern neurobiology. In a number of recent publications, Carl Craver ([2006], [2007], [2008]) has argued that the model is explanatorily deficient because it does not reveal enough about underlying molecular mechanisms. I offer an alternative picture of the HH model, according to which it deliberately abstracts from molecular specifics. By doing so, the model explains whole-cell behaviour as the product of a mass of underlying low-level events. The (...) issue goes beyond cellular neurobiology, for the strategy of abstraction exhibited in the HH case is found in a range of biological contexts. I discuss why it has been largely neglected by advocates of the mechanist approach to explanation. 1 Introduction2 A Primer on the HH Model2.1 The basic qualitative picture2.2 The quantitative model3 Interlude: What Did Hodgkin and Huxley Think?4 Craver’s View4.1 Mechanistic explanation4.2 Sketches4.3 Craver's view: The HH model as a mechanism sketch5 An Alternative View of the HH Model5.1 Another look at the equations5.2 The discrete-gating picture5.3 The road paved by Hodgkin and Huxley5.4 Summary and comparison to Craver6 Conclusion: The HH Model and Mechanistic Explanation6.1 Sketches and abstractions6.2 Why has aggregative abstraction been overlooked? (shrink)

Reverse Inference ( RI ) is an imaging-based type of inference from brain states to mental states, which has become highly widespread in neuroscience, most especially in neuroeconomics. Recent critical studies of RI may be taken to show that, if cautiously used, RI can help achieve research goals that may be difficult to achieve by way of behavior-based procedures alone. But can RI exceed the limits of these procedures and achieve research goals that are impossible for them to achieve alone? (...) By way of answering this question we show that a conception of the mind—type identity—under which the answer is in the positive, is untenable for reasons that strongly support another conception of the mind—functionalism—under which the answer must be in the negative. On this basis we then conclude that RI cannot exceed the limits of behavior-based procedures in cognitive psychology. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

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

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is provided, which sheds light on explanatory (...) unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

In this article, I present two conceptual problems for Craver's mutual manipulability account of constitutive relevance in mechanisms. First, constitutive relevance threatens to imply causal relevance despite Craver (and Bechtel)'s claim that they are strictly distinct. Second, if (as is intuitively appealing) parthood is defined in terms of spatio-temporal inclusion, then the mutual manipulability account is prone to counterexamples, as I show by a case of endosymbiosis. I also present a methodological problem (a case of experimental underdetermination) and formulate two (...) partial, but fallible solutions based on the notions of parthood and synchronicity. (shrink)

Mechanistic approaches are very common in the causal interpretation of biological and neuroscientific experimental work in today’s philosophy of science. In the mechanistic literature a strict distinction is often made between causal relations and constitutive relations, where the latter cannot be causal. One of the typical reasons for this strict distinction is that constitutive relations are supposedly synchronic whereas most if not all causal relations are diachronic. This strict distinction gives rise to a number of problems, however. Our end goal (...) in this paper is to argue that it should be given up, at least in the context of the biological and the psychological sciences. To that effect, we argue that constitutive relations in this context are diachronic, thus undermining the aforementioned reason. We offer two cases from scientific practice in which constitutive relations are regarded as both diachronic and causally efficacious, review three existing ways of dealing with the apparent diachronic nature of interlevel relations in mechanisms and propose a new account of diachronic, causal constitutive relevance. (shrink)

Because biologization of psychiatric constructs does not involve derivation of laws, or reduce the number of entities involved, the traditional term of ‘reduction’ should be replaced. This paper describes biologization in terms of redefinition, which involves changing the definition of terms sharing the same extension. Redefinition obtains through triangulation and calibration, that is, respectively, detection of an object from two different spots, and tweaking parameters of detection in order to optimize the picture. The unity of the different views of the (...) same object does not occur through derivation from one of them, as reduction suggests, nor does it obtain through mechanistic unity or the goal of explaining one mechanism, as the phrase ‘mosaic unity’ suggests. Instead, it depends on finding a specific angle of observation, from which linguistic consistency matches sound localization in the brain, so that all observations make sense together, just as an anamorphic picture makes clear sense only when observed from the right spot. (shrink)

There is growing evidence that plants possess abilities associated with cognition, such as decision-making, anticipation and learning. And yet, the cognitive status of plants continues to be contested. Among the threats to plant cognitive status is the ‘Representation Demarcation Challenge’ which points to the absence of a seemingly defining aspect of cognition, namely, computation over representation with non-derived content. Defenders of plant cognition may appeal to post-cognitivist perspectives, such as enactivism, which challenge the assumptions of the Representation Demarcation Challenge. This (...) points to an impasse in the debate over plant cognition as it collapses into perennial disagreements over the best way to conceptualise the very nature of cognition. I propose a path that allows us to bypass this quagmire by reconceiving the question of what is cognitive about ‘plant cognition’ in terms of a quest to map the many possible adaptive capacities and behaviours more-or-less associated with cognition, alongside their underlying processes and mechanisms. In turn, we can examine the degrees of similarity between plants and more paradigmatically cognitive creatures. The ‘piecemeal approach’ thus shifts attention away from the abstract and dichotomous question of whether plants are cognitive and towards a series of more precise questions about the many ways and extent to which plants possess features associated with cognition. Ultimately, I suggest, the value of viewing plants through a cognitive lens may lie less in determining whether they are bona fide cognitive creatures and more in guiding research into concrete abilities and their underlying causes. (shrink)

The question of whether there are laws of nature in ecology has developed substantially in the last 20 years. Many have attempted to rehabilitate ecology’s lawlike status through establishing that ecology possesses laws that robustly appear across many different ecological systems. I argue that there is still something missing, which explains why so many have been skeptical of ecology’s lawlike status. Community ecology has struggled to establish what I call a General Unificatory Theory. The lack of a GUT causes problems (...) for explanation as there are no guidelines for how to integrate the lower-level mathematical and causal models into a larger theory of how ecological assemblages are formed. I turn to a promising modern attempt to provide a unified higher-level explanation in ecology, presented by ecologist Mark Vellend, and advocate for philosophical engagement with its prospects for aiding ecological explanation. (shrink)

: The long dispute between incompatibilists and compatibilists is further exemplified in the discussion between Sam Harris and Daniel Dennett. In this article I try to add to the discussion by outlining a concept of free will linked to five operating conditions and proposing its operationalization and quantification. The idea is to empirically and pragmatically define free will as we need it for moral blame and legal liability, while separating it from the debate on global determinism, local determinism, automatisms and (...) priming phenomena on a psychological level. This is made possible by weakening the claims of determinisms and psychological automatisms, based on the latest research, and by giving a well-outlined definition of free will as I want to defend it. Keywords: Compatibilism; Daniel Dennett; Free Will Quantification; Global Determinism; Local Determinism Un approccio pragmatico ed empirico al libero arbitrio Riassunto: La lunga disputa tra incompatibilisti e compatibilisti trova un’esemplificazione nel dibattito tra Sam Harris e Daniel Dennett. In questo articolo cerco di contribuire alla discussione delineando un concetto di libero arbitrio legato a cinque condizioni operative e proponendo la sua operazionalizzazione e quantificazione. L’idea è di definire empiricamente e pragmaticamente il libero arbitrio di cui abbiamo bisogno per trattare di colpa morale e di responsabilità legale, separandolo dal dibattito su determinismo globale, determinismo locale, automatismi e fenomeni di innesco a livello psicologico. Ciò è reso possibile indebolendo le pretese di determinismi e automatismi psicologici, che si basano su recenti ricerche empiriche, e dando una precisa definizione di libero arbitrio per come voglio difenderlo. Parole chiave: Compatibilismo; Daniel Dennett; Quantificazione del libero arbitrio; Determinismo globale; Determinismo locale. (shrink)

Embodied, embedded, enactive, and extended theorists do not typically focus on the ontological frameworks in which they develop their theories. One exception is 4E theories that embrace New Mechanism. In this paper, we endorse the New Mechanist’s general turn to ontology, but argue that their ontology is not the best on the market for 4E theories. Instead, we advocate for a different ontology: causal powers realism. Causal powers realism posits that psychological manifestations are the product of mental powers, and that (...) mental powers are empirically-discoverable features of individuals that account for the causal work those individuals do. We contend that causal powers realism provides a unifying framework for the central commitments of 4E theories, as well as additional resources for theorizing in a 4E framework. And while New Mechanism offers some of these resources as well, we argue that causal powers realism is ultimately the better of the two. (shrink)

Philosophical and scientific investigations of the proprietary aspects of self—mineness or mental ownership—often presuppose that searching for unique constituents is a productive strategy. But there seem not to be any unique constituents. Here, it is argued that the “self-specificity” paradigm, which emphasizes subjective perspective, fails. Previously, it was argued that mode of access also fails to explain mineness. Fortunately, these failures, when leavened by other findings (those that exhibit varieties and vagaries of mineness), intimate an approach better suited to searching (...) for an explanation. Having an alternative in hand, one that shows promise of achieving explanatory adequacy, provides an additional reason to suspend the search for unique constituents. In short, a negative and a positive thesis are developed: we should cease looking for unique constituents and should seek to explain mineness in accord with the model developed here. This model rejects attempts to explain the phenomenon in terms of either a narrative or a minimal sense of self; it seeks to explain at a “molecular” level, one that appeals to multiple, interacting dimensions. The molecular-level model allows for the possibility that subjective perspective is distinct from a stark perspective (one that does not imply mineness). It proposes that the confounding of tacit expectations plays an important role in explaining mental ownership and its complement, disownership. But the confounding of tacit expectations is not sufficient. Because we are able to be aware of the existence of mental states that do not belong to self, we require a mechanism for determining degree of self-relatedness. One such mechanism is proposed here, and it is shown how this mechanism can be integrated into a general model of mental ownership. In the spirit of suggesting how this model might be able to help resolve outstanding problems, the question as to whether inserted thoughts belong to the patient who reports them is also considered. (shrink)

The Brain and the Meaning of Life Paul Thagard Princeton: Princeton University Press, 2010 274 pages, ISBN: 9780691142722 (hbk): $29.95 This paper criticizes central arguments in Paul Thagard's The Brain and the Meaning of Life, concluding, contrary to Thagard, that there is very little that we can learn from brain research about the meaning of life. The paper offers a critical review of Thagard's argument against nihilism and his argument that it is love, work, and play, rather than other activities, (...) that make life meaningful. Moreover, the paper argues that the rich neurological information Thagard presents throughout the book does not contribute at all to his arguments and, more generally, that neurological research is irrelevant also to almost all other aspects of meaning of life research. (shrink)

Philosophical discussions on causal inference in medicine are stuck in dyadic camps, each defending one kind of evidence or method rather than another as best support for causal hypotheses. Whereas Evidence Based Medicine advocates the use of Randomised Controlled Trials and systematic reviews of RCTs as gold standard, philosophers of science emphasise the importance of mechanisms and their distinctive informational contribution to causal inference and assessment. Some have suggested the adoption of a pluralistic approach to causal inference, and an inductive (...) rather than hypothetico-deductive inferential paradigm. However, these proposals deliver no clear guidelines about how such plurality of evidence sources should jointly justify hypotheses of causal associations. We here develop such guidelines by first giving a philosophical analysis of the underpinnings of Hill’s viewpoints on causality. We then put forward an evidence-amalgamation framework adopting a Bayesian net approach to model causal inference in pharmacology for the assessment of harms. Our framework accommodates a number of intuitions already expressed in the literature concerning the EBM vs. pluralist debate on causal inference, evidence hierarchies, causal holism, relevance, and reliability. (shrink)

Although there has been much recent discussion on mechanisms in philosophy of science and social theory, no shared understanding of the crucial concept itself has emerged. In this paper, a distinction between two core concepts of mechanism is made on the basis that the concepts correspond to two different research strategies: the concept of mechanism as a componential causal system is associated with the heuristic of functional decomposition and spatial localization and the concept of mechanism as an abstract form of (...) interaction is associated with the strategy of abstraction and simple models. The causal facts assumed and the theoretical consequences entailed by an explanation with a given mechanism differ according to which concept of mechanism is in use. Research strategies associated with mechanism concepts also involve characteristic biases that should be taken into account when using them, especially in new areas of application. (shrink)

Mechanisms are often characterized as causal structures and the interventionist account of causation is then used to characterize what it is to be a causal structure. The associated modularity constraint on causal structures has evoked criticism against using the theory as an account of mechanisms, since many mechanisms seem to violate modularity. This paper answers to this criticism by making a distinction between a causal system and a causal structure. It makes sense to ask what the modularity properties of a (...) given causal structure are, but not whether a causal system is modular tout court. The counter-examples to the interventionist account are systems in which a particular structure is modular in variables, but not in parameters. A failure of parameter-modularity does not by itself threaten the interventionist interpretation of the structure and the possibility of causally explaining with that structure, but it does mean that knowledge of the structure is not sufficient to constitutively explain system-level properties of the embedding system. (shrink)

This paper aims to provide Humean metaphysics for the interventionist theory of causation. This is done by appealing to the hierarchical picture of causal relations as being realized by mechanisms, which in turn are identified with lower-level causal structures. The modal content of invariances at the lowest level of this hierarchy, at which mechanisms are reduced to strict natural laws, is then explained in terms of projectivism based on the best-system view of laws.

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

Advocates of the New Mechanicism in philosophy of science argue that scientific explanation often consists in describing mechanisms responsible for natural phenomena. Despite its successes, one might think that this approach does not square with the ontological strictures of quantum mechanics. New Mechanists suppose that mechanisms are composed of objects with definite properties, which are interconnected via local causal interactions. Quantum mechanics calls these suppositions into question. Since mechanisms are hierarchical it appears that even macroscopic mechanisms must supervene on a (...) set of “objects” that behave non-classically. In this paper we argue, in part by appeal to the theory of quantum decoherence, that the universal validity of quantum mechanics does not undermine neo-mechanistic ontological and explanatory claims as they occur within in classical domains. Additionally, we argue that by relaxation of certain classical assumptions, mechanistic explanatory strategies can sometimes be carried over into the quantum domain. (shrink)

Volume 32, Issue 1, March 2019, Page 69-72.

Recent findings in different areas of psychology and cognitive science have brought the unconscious mind back to center stage. However, the unconscious mind worry remains: What renders unconscious phenomena mental? I suggest a new strategy for answering this question, which rests on the idea that categorizing unconscious phenomena as “mental” should be scientifically useful relative to the explanatory research goals. I argue that this is the case if by categorizing an unconscious phenomenon as “mental” one picks out explanatorily relevant similarities (...) to a corresponding paradigmatically mental conscious phenomenon. Explanatory relevance is spelled out in terms of mechanistic norms. (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)

According to the new mechanistic approach, an acting entity is at a lower mechanistic level than another acting entity if and only if the former is a component in the mechanism for the latter. Craver and Bechtel :547–563, 2007. doi:10.1007/s10539-006-9028-8) argue that a consequence of this view is that there cannot be causal interactions between acting entities at different mechanistic levels. Their main reason seems to be what I will call the Metaphysical Argument: things at different levels of a mechanism (...) are related as part and whole; wholes and their parts cannot be related as cause and effect; hence, interlevel causation in mechanisms is impossible. I will analyze this argument in more detail and show under which conditions it is valid. This analysis will reveal that interlevel causation in mechanisms is indeed possible, if we take seriously the idea that the relata of the mechanistic level relation are acting entities and accept a slightly modified notion of a mechanistic level that is highly plausible in the light of the first clarification. (shrink)

The relationship between topological explanation and mechanistic explanation is unclear. Most philosophers agree that at least some topological explanations are mechanistic explanations. The crucial question is how to make sense of this claim. Zednik (Philos Psychol 32(1):23–51, 2019) argues that topological explanations are mechanistic if they (i) describe mechanism sketches that (ii) pick out organizational properties of mechanisms. While we agree with Zednik’s conclusion, we critically discuss Zednik’s account and show that it fails as a general account of how and (...) when topological explanations are mechanistic. First, if topological explanations were just mechanism sketches, this implies that they could be enriched by replacing topological terms with mechanistic detail. This, however, conflicts how topological explanations are used in scientific practice. Second, Zednik’s account fails to show how topological properties can be organizational properties of mechanisms that have a place in mechanistic explanation. The core issue is that Zednik’s account ignores that topological properties often are _global_ properties while mechanistic explanantia refer to _local_ properties. We demonstrate how these problems can be solved by a recent account of mechanistic completeness (Craver and Kaplan in Br J Philos Sci 71(1):287–319, 2020; Kohár and Krickel in Calzavarini and Viola (eds) Neural mechanisms—new challenges in the philosophy of neuroscience, Springer, New York, 2021) and use a multilayer network model of Alzheimer’s Disease to illustrate this. (shrink)

In the last couple of years a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the questions what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences sometimes take a form of the question what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue of what they are explanatory. These questions raise further issues about (...) counterfactuals, modality, and explanatory asymmetries: i.e., do mathematical and non-causal explanations support... (shrink)

In this paper, I argue that the newly developed network approach in neuroscience and biology provides a basis for formulating a unique type of realization, which I call topological realization. Some of its features and its relation to one of the dominant paradigms of realization and explanation in sciences, i.e. the mechanistic one, are already being discussed in the literature. But the detailed features of topological realization, its explanatory power and its relation to another prominent view of realization, namely the (...) semantic one, have not yet been discussed. I argue that topological realization is distinct from mechanistic and semantic ones because the realization base in this framework is not based on local realisers, regardless of the scale but on global realizers. In mechanistic approach, the realization base is always at the local level, in both ontic and epistemic accounts. The explanatory power of realization relation in mechanistic approach comes directly from the realization relation-either by showing how a model is mapped onto a mechanism, or by describing some ontic relations that are explanatory in themselves. Similarly, the semantic approach requires that concepts at different scales logically satisfy microphysical descriptions, which are at the local level. In topological framework the realization base can be found at different scales, but whatever the scale the realization base is global, within that scale, and not local. Furthermore, topological realization enables us to answer the “why” questions, which according to Polger 2010 make it explanatory. The explanatoriness of topological realization stems from understanding mathematical consequences of different topologies, not from the mere fact that a system realizes them. (shrink)

The philosophical literature on scientific explanation in neuroscience has been dominated by the idea of mechanisms. The mechanist philosophers often claim that neuroscience is in the business of finding mechanisms. This view has been challenged in numerous ways by showing that there are other successful and widespread explanatory strategies in neuroscience. However, the empirical evidence for all these claims was hitherto lacking. Empirical evidence about the pervasiveness and uses of various explanatory strategies in neuroscience is particularly needed because examples and (...) case studies that are used to illustrate philosophical claims so far tend to be hand-picked. The risk of confirmation bias is therefore considerable: when looking for white swans, all one finds is that swans are white. The more systematic quantitative and qualitative bibliometric study of a large body of relevant literature that we present in this paper can put such claims into perspective. Using bibliometric tools, we identify the typical linguistic patterns used in the alleged mechanistic, dynamical, and topological explanations in the literature, their preponderance and how they change over time. Our findings show abundant use of mechanistic language, but also the presence of a significant neuroscience literature using topological and dynamical explanatory language, which grows over time and increasingly differentiates from each other and from mechanistic explanations. (shrink)