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Making mechanism interesting

Synthese 195 (1):11-33 (2018)

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  1. Metaphysical Causal Pluralism: What Are New Mechanists Pluralistic About?Michał Oleksowicz - forthcoming - Philosophia:1-22.
    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 (...)
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  • Mechanistic and topological explanations: an introduction.Daniel Kostić - 2018 - Synthese 195 (1).
    In the last 20 years or so, since the publication of a seminal paper by Watts and Strogatz :440–442, 1998), an interest in topological explanations has spread like a wild fire over many areas of science, e.g. ecology, evolutionary biology, medicine, and cognitive neuroscience. The topological approach is still very young by all standards, and even within special sciences it still doesn’t have a single methodological programme that is applicable across all areas of science. That is why this special issue (...)
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  • Scale Dependency and Downward Causation in Biology.Sara Green - 2018 - Philosophy of Science 85 (5):998-1011.
    This paper argues that scale-dependence of physical and biological processes offers resistance to reductionism and has implications that support a specific kind of downward causation. I demonstrate how insights from multiscale modeling can provide a concrete mathematical interpretation of downward causation as boundary conditions for models used to represent processes at lower scales. The autonomy and role of macroscale parameters and higher-level constraints are illustrated through examples of multiscale modeling in physics, developmental biology, and systems biology. Drawing on these examples, (...)
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  • Putting History Back into Mechanisms.Justin Garson - 2023 - British Journal for the Philosophy of Science 74 (4):921-940.
    Mechanisms, in the prominent biological sense of the term, are historical entities. That is, whether or not something is a mechanism for something depends on its history. Put differently, while your spontaneously-generated molecule-for-molecule double has a heart, and its heart pumps blood around its body, its heart does not have a mechanism for pumping, since it does not have the right history. My argument for this claim is that mechanisms have proper functions; proper functions are historical entities; so, mechanisms are (...)
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  • A Defence of Functional Kinds: Multiple Realisability and Explanatory Counterfactuals.Gareth Fuller - 2022 - International Studies in the Philosophy of Science 35 (2):119-133.
    In this paper, I defend an updated account of functional kinds, initially presented by Daniel Weiskopf, from the criticism that functional kinds will not qualify as scientific kinds. An important part of Weiskopf’s account is that functional kinds are multiply realisable. The criticisms I consider avoid discussion of multiple realisability. Instead, it is argued that functional kinds carry inferior counterfactual profiles when compared to other accounts of kinds. I respond to this charge by arguing that this criticism fails to take (...)
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  • Flat mechanisms: a reductionist approach to levels in mechanistic explanations.Peter Fazekas - 2022 - Philosophical Studies 179 (7):2303-2321.
    The mechanistic framework traditionally comes bundled with a multi-level view. Some ascribe ontological weight to these levels, whereas others claim that characterising a higher-level entity and the corresponding lower-level mechanism are only different descriptions of the same thing. The goal of this paper is to develop a consistent metaphysical picture that can underly the latter position. According to this flat view, wholes and their parts are embedded in the same network of interacting units. The flat view preserves the original virtues (...)
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  • Are Higher Mechanistic Levels Causally Autonomous?Peter Fazekas & Gergely Kertesz - 2019 - Philosophy of Science 86 (5):847-857.
    This article provides a detailed analysis and explores the prospects of the arguments for higher-level causal autonomy available for the proponents of the mechanistic framework. Three different arguments are distinguished. After clarifying previously raised worries with regard to the first two arguments, the article focuses on the newest version of the third argument that has recently been revived by William Bechtel. By using Bechtel’s own case study, it is shown that not even reference to constraints can establish the causal autonomy (...)
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  • Molecular pathways and the contextual explanation of molecular functions.Giovanni Boniolo & Raffaella Campaner - 2018 - Biology and Philosophy 33 (3-4):24.
    Much of the recent philosophical debate on causation and causal explanation in the biological and biomedical sciences has focused on the notion of mechanism. Mechanisms, their nature and epistemic roles have been tackled by a range of so-called neo-mechanistic theories, and widely discussed. Without denying the merits of this approach, our paper aims to show how lately it has failed to give proper credit to processes, which are central to the field, especially of contemporary molecular biology. Processes can be summed (...)
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  • Explicating Top-­‐Down Causation Using Networks and Dynamics.William Bechtel - 2017 - Philosophy of Science 84 (2):253-274.
    In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and Bechtel defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and causation as solely an intra-level relation. Craver and Bechtel, however, provided insufficient specification as to when entities constitute a higher-level mechanism. In this paper I appeal to graph-theoretic representations of networks that are now widely employed in systems biology and neuroscience to (...)
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