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  1. Against Computational Perspectivalism.Dimitri Coelho Mollo - 2021 - British Journal for the Philosophy of Science 72 (4):1129-1153.
    Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a compelling alternative to perspective-independent (...)
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  • Reason, causation and compatibility with the phenomena.Basil Evangelidis - 2020 - Wilmington, Delaware, USA: Vernon Press.
    'Reason, Causation and Compatibility with the Phenomena' strives to give answers to the philosophical problem of the interplay between realism, explanation and experience. This book is a compilation of essays that recollect significant conceptions of rival terms such as determinism and freedom, reason and appearance, power and knowledge. This title discusses the progress made in epistemology and natural philosophy, especially the steps that led from the ancient theory of atomism to the modern quantum theory, and from mathematization to analytic philosophy. (...)
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  • Coherent Causal Control: A New Distinction within Causation.Marcel Weber - 2022 - European Journal for Philosophy of Science 12 (4):69.
    The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes (...)
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  • Micro-level model explanation and counterfactual constraint.Samuel Schindler - 2022 - European Journal for Philosophy of Science 12 (2):1-27.
    Relationships of counterfactual dependence have played a major role in recent debates of explanation and understanding in the philosophy of science. Usually, counterfactual dependencies have been viewed as the explanantia of explanation, i.e., the things providing explanation and understanding. Sometimes, however, counterfactual dependencies are themselves the targets of explanations in science. These kinds of explanations are the focus of this paper. I argue that “micro-level model explanations” explain the particular form of the empirical regularity underlying a counterfactual dependency by representing (...)
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  • Behavioural and heuristic models are as-if models too – and that’s ok.Ivan Moscati - forthcoming - Economics and Philosophy:1-31.
    I examine some behavioural and heuristic models of individual decision-making and argue that the diverse psychological mechanisms these models posit are too demanding to be implemented, either consciously or unconsciously, by actual decision makers. Accordingly, and contrary to what their advocates typically claim, behavioural and heuristic models are best understood as ‘as-if’ models. I then sketch a version of scientific antirealism that justifies the practice of as-if modelling in decision theory but goes beyond traditional instrumentalism. Finally, I relate my account (...)
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  • Bayesian Epistemology.Jürgen Landes - 2022 - Kriterion – Journal of Philosophy 36 (1):1-7.
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  • Towards Ideal Understanding.Mario Hubert & Federica Isabella Malfatti - 2023 - Ergo 10 (22):578-611.
    What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...)
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  • One mechanism, many models: a distributed theory of mechanistic explanation.Eric Hochstein - 2016 - Synthese 193 (5):1387-1407.
    There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual models (...)
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  • Mechanistic inquiry and scientific pursuit: The case of visual processing.Philipp Haueis & Lena Kästner - 2022 - Studies in History and Philosophy of Science Part A 93 (C):123-135.
    Why is it rational for scientists to pursue multiple models of a phenomenon at the same time? The literatures on mechanistic inquiry and scientific pursuit each develop answers to a version of this question which is rarely discussed by the other. The mechanistic literature suggests that scientists pursue different complementary models because each model provides detailed insights into different aspects of the phenomenon under investigation. The pursuit literature suggests that scientists pursue competing models because alternative models promise to solve outstanding (...)
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  • Coherence in Science: A Social Approach.Sanford C. Goldberg & Kareem Khalifa - 2022 - Philosophical Studies 179 (12):3489-3509.
    Among epistemologists, it is common to assume that insofar as coherence bears on the justification of belief, the only relevant coherence relations are those _within_ an individual subject’s web of beliefs. After clarifying this view and exploring some plausible motivations for it, we argue that this individualistic account of the epistemic relevance of coherence fails to account for central facets of scientific practice. In its place we propose a social account of coherence. According to the view we propose, a scientist (...)
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  • Neural representationalism, the Hard Problem of Content and vitiated verdicts. A reply to Hutto & Myin.Matteo Colombo - 2014 - Phenomenology and the Cognitive Sciences 13 (2):257-274.
    Colombo’s (Phenomenology and the Cognitive Sciences, 2013) plea for neural representationalism is the focus of a recent contribution to Phenomenology and Cognitive Science by Daniel D. Hutto and Erik Myin. In that paper, Hutto and Myin have tried to show that my arguments fail badly. Here, I want to respond to their critique clarifying the type of neural representationalism put forward in my (Phenomenology and the Cognitive Sciences, 2013) piece, and to take the opportunity to make a few remarks of (...)
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  • Gualtiero Piccinini: Physical Computation: A Mechanistic Account: Oxford University Press, Oxford, 2015, ix + 313, £35.00, ISBN 9780199658855.Matteo Colombo - 2016 - Minds and Machines 26 (3):307-312.
  • A new defence of doxasticism about delusions: The cognitive phenomenological defence.Peter Clutton - 2018 - Mind and Language 33 (2):198-217.
    Clinicians and cognitive scientists typically conceive of delusions as doxastic—they view delusions as beliefs. But some philosophers have countered with anti-doxastic objections: delusions cannot be beliefs because they fail the necessary conditions of belief. A common response involves meeting these objections on their own terms by accepting necessary conditions on belief but trying to blunt their force. I take a different approach by invoking a cognitive-phenomenal view of belief and jettisoning the rational/behavioural conditions. On this view, the anti-doxastic claims can (...)
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  • On the Nature of Explanations Offered by Network Science: A Perspective From and for Practicing Neuroscientists.Maxwell A. Bertolero & Danielle S. Bassett - 2020 - Topics in Cognitive Science 12 (4):1272-1293.
    Network neuroscience represents the brain as a collection of regions and inter-regional connections. Given its ability to formalize systems-level models, network neuroscience has generated unique explanations of neural function and behavior. The mechanistic status of these explanations and how they can contribute to and fit within the field of neuroscience as a whole has received careful treatment from philosophers. However, these philosophical contributions have not yet reached many neuroscientists. Here we complement formal philosophical efforts by providing an applied perspective from (...)
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