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

Gebharter has proposed using one of the best known Bayesian network causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this article is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in (...) the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions. (shrink)

Alexander Gebharter has recently proposed to use Bayesian network causal discovery methods to identify the constitutive dependencies that underwrite mechanistic explanations. The proposal depends on using the assumptions of the causal Bayesian network framework to implicitly define mechanistic constitution as a kind of deterministic direct causal dependence. The aim of this paper is twofold. In the first half, we argue that Gebharter’s proposal incurs severe conceptual problems. In the second half, we present an alternative way to bring Bayesian network tools (...) to bear on the issue of understanding mechanistic constitution. More precisely, our proposal interprets constitution as the relation explaining why a target phenomenon has its characteristic causal role in terms of the causal roles of some of its spatiotemporal parts---where the notion of causal role is probabilistically understood. (shrink)

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

Some New Mechanists have proposed that claims of compositional relations are justified by combining the results of top-down and bottom-up interlevel interventions. But what do scientists do when they can perform, say, a cellular intervention, but not a subcellular detection? In such cases, paired interlevel interventions are unavailable. We propose that scientists use abduction and we illustrate its use through a case study of the ionic theory of resting and action potentials.

Within contemporary philosophy of perception, it is commonly claimed that flavour experiences are paradigmatic examples of multimodal perceptual experiences. In fact, virtually any sensory system, including vision and audition, is believed to influence how we experience flavours. However, there is a strong intuition, often expressed in these works, that not all of these sensory systems make an equal contribution to the phenomenology of flavour experiences. More specifically, it seems that the activities of some sensory systems are constitutive for flavour perception (...) while others merely influence how we experience flavours. This paper aims to answer the question regarding the constitutive factors of flavour perception in a twofold way. First, a theoretical framework is developed, relying on debates regarding constitutivity in analytic metaphysics and philosophy of science, which defines the stronger and weaker senses in which the activities of sensory systems may be constitutive for flavour perception. Second, relying on empirical results in flavour science, the constitutive status of activities related to distinct sensory systems in the context of flavour perception is investigated. (shrink)

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

Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as a (...) general approach to analogical inference and argue that these problems can be avoided by supplementing Bayesian update with Jeffrey conditionalization. (shrink)

An epistemic account of constitutive relevance lists the criteria by which scientists can identify the components of mechanisms in empirical practice. Three prominent claims from Craver form a promising basis for an account. First, constitutive relevance is established by means of interlevel experiments. Second, interlevel experiments are executions of interventions. Third, there is no interlevel causation between a mechanism and its components. Currently, no account on offer respects all three claims. I offer my causal situationist account of constitutive relevance that (...) respects the claims. By situating a part of a mechanism on the causal chain between the mechanism’s input and output, components can be identified with interventions, without the interventions suggesting interlevel causation. The causal situationist account is the only account on offer so far that clearly fits within Craver’s framework. (shrink)

This paper discusses two challenges for a Boolean method for establishing constitutive regularity statements which, according to the regularity theory of mechanistic constitution, form the core of any mechanistic explanation in neuroscience. After presenting the regularity definition for the constitution relation and a methodology for constitutive inference, the paper discusses the problem of full variation of tested mechanistic factors and the problem of informational redundancy. A solution is offered for each problem. The first requires some adjustments to the original theory (...) by introducing the technical notion of a set of types satisfying independent instantiability. The second one is resolved by demonstrating that the problem of informational redundancy is based on a confusion that fails to challenge the theory. It is concluded that the methodology of constitutive inference is consistent and plausible with respect to actual practice in neuroscience. (shrink)

In contemporary philosophy of science, the consensus view seems to be that scientific explanations describe mechanisms responsible for the phenomena to be explained. Two kinds of explanatory relevance figure in mechanistic accounts of explanation: causal and constitutive. Following prominent accounts, it seems natural to analyze both these relations in terms of systematic interventions into some factor X with respect to another factor Y. However, such interventions are tailored to uncover causal relations only. Construing the constitutive relationship between parts and wholes (...) in terms of interventions thus raises metaphysical, conceptual, and epistemological questions. We here review the barriers that intervention-based inquiry into mechanisms encounters and consider some solutions. (shrink)

One reason for the popularity of Craver’s mutual manipulability account of constitutive relevance is that it seems to make good sense of the experimental practices and constitutive reasoning in the life sciences. Two recent papers propose a theoretical alternative to in light of several important conceptual objections. Their alternative approach, the no de-coupling account, conceives of constitution as a dependence relation that once postulated provides the best explanation of the impossibility of breaking the common cause coupling of a macro-level mechanism (...) and its micro-level components. This entails an abductive view of constitutive inference. Proponents of the NDC or abductive account recognize that their discussion leaves open a big question concerning the practical dimension of the notion of constitutive relevanssssce: Is it possible to faithfully reconstruct constitutional reasoning in science in terms of a failure to de-couple, via interlevel experiments, phenomena from their mechanistic constituents? Focusing on the field of memory and long-term potential research, this article argues that the abductive account provides a more adequate description of interlevel experiments in neuroscience. We also suggest that the account highlights some significant practical recommendations of how to interpret the findings of interlevel experiments. 1Introduction 2Mutual Manipulability and Constitutive Relevance 2.1Constitutive relevance through an interventionist lens 2.2Mutual manipulability: A methodological application 3Trouble for the Mutual Manipulability Account 4The Abductive Account of Constitution 5The Abductive Account: A Methodological Application 5.1Long-term potential and memory experiments 5.2A comparative summary 6Conclusions. (shrink)

We discuss two influential views of unification: mutual information unification (MIU) and common origin unification (COU). We propose a simple probabilistic measure for COU and compare it with Myrvold’s (2003, 2017) probabilistic measure for MIU. We then explore how well these two measures perform in simple causal settings. After highlighting several deficiencies, we propose causal constraints for both measures. A comparison with explanatory power shows that the causal version of COU is one step ahead in simple causal settings. However, slightly (...) increasing the complexity of the underlying causal structure shows that both measures can easily disagree with explanatory power. The upshot of this is that even sophisticated causally constrained measures for unification ultimately fail to track explanatory relevance. This shows that unification and explanation are not as closely related as many philosophers thought. (shrink)

In this paper we develop an analysis of dispositions by means of causal Bayes nets. In particular, we analyze dispositions as cause-effect structures that increase the probability of the manifestation when the stimulus is brought about by intervention in certain circumstances. We then highlight several advantages of our analysis and how it can handle problems arising for classical analyses of dispositions such as masks, mimickers, and finks.

Strong notions of free will are closely connected to the possibility to do otherwise as well as to an agent’s ability to causally influence her environment via her decisions controlling her actions. In this paper we employ techniques from the causal modeling literature to investigate whether a notion of free will subscribing to one or both of these requirements is compatible with naturalistic views of the world such as non-reductive physicalism to the background of determinism and indeterminism. We argue that (...) from a causal modeler’s perspective the only possibility to get both requirements consists in subscribing to reductive physicalism and indeterminism. (shrink)

An important question for the causal modeling approach is how to integrate non‐causal dependence relations such as asymmetric supervenience into the approach. The most prominent proposal to that effect (due to Gebharter) is to treat those dependence relationships as formally analogous to causal relationships. We argue that this proposal neglects some crucial differences between causal and non‐causal dependencies, and that in the context of causal modeling non‐causal dependence relationships should be represented as mutual dependence relationships. We develop a new kind (...) of model – “hybrid models” ‐ based on this suggestion, and formulate a set of axioms for those models. Our formalism has important implications for Kim's exclusion problem: whereas Gebharter's framework vindicates Kim's causal exclusion objection against nonreductive physicalism, our framework has no such implication, and can help non‐reductive physicalists vindicate the efficacy of high‐level properties. A further benefit of our formalism is that it yields a natural and plausible way of thinking about interventions in multi‐level contexts. (shrink)

Strong notions of free will are closely connected to the possibility to do otherwise as well as to an agent’s ability to causally influence her environment via her decisions controlling her actions. In this paper we employ techniques from the causal modeling literature to investigate whether a notion of free will subscribing to one or both of these requirements is compatible with naturalistic views of the world such as non-reductive physicalism to the background of determinism and indeterminism. We argue that (...) from a causal modeler’s perspective the only possibility to get both requirements consists in subscribing to reductive physicalism and indeterminism. (shrink)

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

Causal Bayes nets (CBNs) can be used to model causal relationships up to whole mechanisms. Though modelling mechanisms with CBNs comes with many advantages, CBNs might fail to adequately represent some biological mechanisms because—as Kaiser (2016) pointed out—they have problems with capturing relevant spatial and structural information. In this paper we propose a hybrid approach for modelling mechanisms that combines CBNs and cellular automata. Our approach can incorporate spatial and structural information while, at the same time, it comes with all (...) the merits of a CBN representation of mechanisms. (shrink)

This paper discusses the relevance of models for cognitive science that integrate mechanistic and computational aspects. Its main hypothesis is that a model of a cognitive system is satisfactory and explanatory to the extent that it bridges phenomena at multiple mechanistic levels, such that at least several of these mechanistic levels are shown to implement computational processes. The relevant parts of the computation must be mapped onto distinguishable entities and activities of the mechanism. The ideal is contrasted with two other (...) accounts of modeling in cognitive science. The first has been presented by David Marr in combination with a distinction of “levels of computation”. The second builds on a hierarchy of “mechanistic levels” in the sense of Carl Craver. It is argued that neither of the two accounts secures satisfactory explanations of cognitive systems. The mechanistic-computational ideal can be thought of as resulting from a fusion of Marr’s and Craver’s ideals. It is defended as adequate and plausible in light of scientific practice, and certain metaphysical background assumptions are discussed. (shrink)

Cartwright (Synthese 121(1/2):3–27, 1999a; The dappled world, Cambridge University Press, Cambridge, 1999b) attacked the view that causal relations conform to the Markov condition by providing a counterexample in which a common cause does not screen off its effects: the prominent chemical factory. In this paper we suggest a new way to handle counterexamples to Markov causation such as the chemical factory. We argue that Cartwright’s as well as similar scenarios feature a certain kind of non-causal dependence that kicks in once (...) the common cause occurs. We then develop a representation of this specific kind of non-causal dependence that allows for modeling the problematic scenarios in such a way that the Markov condition is not violated anymore. (shrink)