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The Ontic Account of Scientific Explanation

In Marie I. Kaiser, Oliver R. Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the Special Sciences: The Case of Biology and History. Springer Verlag. pp. 27-52 (2014)

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  1. Mathematical Explanation: A Contextual Approach.Sven Delarivière, Joachim Frans & Bart Van Kerkhove - 2017 - Journal of Indian Council of Philosophical Research 34 (2):309-329.
    PurposeIn this article, we aim to present and defend a contextual approach to mathematical explanation.MethodTo do this, we introduce an epistemic reading of mathematical explanation.ResultsThe epistemic reading not only clarifies the link between mathematical explanation and mathematical understanding, but also allows us to explicate some contextual factors governing explanation. We then show how several accounts of mathematical explanation can be read in this approach.ConclusionThe contextual approach defended here clears up the notion of explanation and pushes us towards a pluralist vision (...)
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  • Viewing-as explanations and ontic dependence.William D’Alessandro - 2020 - Philosophical Studies 177 (3):769-792.
    According to a widespread view in metaphysics and philosophy of science, all explanations involve relations of ontic dependence between the items appearing in the explanandum and the items appearing in the explanans. I argue that a family of mathematical cases, which I call “viewing-as explanations”, are incompatible with the Dependence Thesis. These cases, I claim, feature genuine explanations that aren’t supported by ontic dependence relations. Hence the thesis isn’t true in general. The first part of the paper defends this claim (...)
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  • Idealization and the Ontic Conception: A Reply to Bokulich.Carl F. Craver - 2019 - The Monist 102 (4):525-530.
    In a recent issue of The Monist, Alisa Bokulich argues that those who embrace an ontic conception of scientific explanation are committed to rejecting an explanatory role for idealized, i.e., deliberately false, models. Her argument is based on an inaccurate characterization of the ontic view. Indeed, her positive view of idealization embraces rather than opposes the ontic conception. Because Bokulich is not alone in this misunderstanding, an effort to diagnose and correct it might prevent scholars from talking past one another (...)
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  • Are More Details Better? On the Norms of Completeness for Mechanistic Explanations.Carl F. Craver & David M. Kaplan - 2020 - British Journal for the Philosophy of Science 71 (1):287-319.
    Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...)
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  • Systems biology and the integration of mechanistic explanation and mathematical explanation.Ingo Brigandt - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical (...)
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  • Representing and Explaining: The Eikonic Conception of Scientific Explanation.Alisa Bokulich - 2018 - Philosophy of Science (5):793-805.
    The ontic conception of explanation, according to which explanations are "full-bodied things in the world," is fundamentally misguided. I argue instead for what I call the eikonic conception, according to which explanations are the product of an epistemic activity involving representations of the phenomena to be explained. What is explained in the first instance is a particular conceptualization of the explanandum phenomenon, contextualized within a given research program or explanatory project. I conclude that this eikonic conception has a number of (...)
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  • Fiction As a Vehicle for Truth: Moving Beyond the Ontic Conception.Alisa Bokulich - 2016 - The Monist 99 (3):260-279.
    Despite widespread evidence that fictional models play an explanatory role in science, resistance remains to the idea that fictions can explain. A central source of this resistance is a particular view about what explanations are, namely, the ontic conception of explanation. According to the ontic conception, explanations just are the concrete entities in the world. I argue this conception is ultimately incoherent and that even a weaker version of the ontic conception fails. Fictional models can succeed in offering genuine explanations (...)
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  • New Mechanistic Philosophy and the Scientific Prospects of Code Biology.Majid Davoody Beni - 2019 - Biosemiotics 12 (2):197-211.
    Marcello Barbieri has presented code biology as an alternative to the Peircean approach to biosemiotics. Some critics questioned the viability of code biology on grounds that Barbieri’s conception of science is limited. It has been argued that code biology’s mechanistic tendency is the cause of the allegedly limited conception of science. In this paper, I evaluate the scientific viability of the code model from the perspective of scientific realism in the philosophy of science. To be more precise, I draw on (...)
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  • Dosis sola facit venenum: reconceptualising biological realism.Majid D. Beni - 2022 - Biology and Philosophy 37 (6):1-18.
    Richard Levins’s (Am Sci 54(4):421–431, 1966) paper sets a landmark for the significance of scientific model-making in biology. Colombo and Palacios (Biol Philos 36(5):1–26. 10.1007/s10539-021-09818-x, 2021) have recently built their critique of the explanatory power of the Free Energy Principle on Levins’s insight into the relationship between generality, realism, and precision. This paper addresses the issue of the plausibility of biological explanations that are grounded in the Free Energy Principle (FEP) and deals with the question of the realist fortitude of (...)
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  • Psychology and Neuroscience: The Distinctness Question.Brice Bantegnie - 2022 - Erkenntnis 87 (4):1753-1772.
    In a recent paper, Gualtiero Piccinini and Carl Craver have argued that psychology is not distinct from neuroscience. Many have argued that Piccinini and Craver’s argument is unsuccessful. However, none of these authors have questioned the appropriateness of Piccinini and Craver’s argument for their key premise—that functional analyses are mechanism sketches. My first and main goal in this paper is to show that Piccinini and Craver offer normative considerations in support of what is a descriptive premise and to provide some (...)
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  • Recent Work in The Philosophy of Biology.Christopher J. Austin - 2017 - Analysis 77 (2):412-432.
    The biological sciences have always proven a fertile ground for philosophical analysis, one from which has grown a rich tradition stemming from Aristotle and flowering with Darwin. And although contemporary philosophy is increasingly becoming conceptually entwined with the study of the empirical sciences with the data of the latter now being regularly utilised in the establishment and defence of the frameworks of the former, a practice especially prominent in the philosophy of physics, the development of that tradition hasn’t received the (...)
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  • Naturalism Meets the Personal Level: How Mixed Modelling Flattens the Mind.Robert D. Rupert - manuscript
    In this essay, it is argued that naturalism of an even moderate sort speaks strongly against a certain widely held thesis about the human mental (and cognitive) architecture: that it is divided into two distinct levels, the personal and the subpersonal, about the former of which we gain knowledge in a manner that effectively insulates such knowledge from the results of scientific research. -/- An empirically motivated alternative is proposed, according to which the architecture is, so to speak, flattened from (...)
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  • How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  • Mechanistic Levels, Reduction, and Emergence.Mark Povich & Carl F. Craver - 2017 - In Stuart Glennan & Phyllis McKay Illari (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy. Routledge. pp. 185-97.
    We sketch the mechanistic approach to levels, contrast it with other senses of “level,” and explore some of its metaphysical implications. This perspective allows us to articulate what it means for things to be at different levels, to distinguish mechanistic levels from realization relations, and to describe the structure of multilevel explanations, the evidence by which they are evaluated, and the scientific unity that results from them. This approach is not intended to solve all metaphysical problems surrounding physicalism. Yet it (...)
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  • Open-Ended Control vs. Closed-Ended Control: Limits of Mechanistic Explanation.Jason Winning - manuscript
    Some recent discussions of mechanistic explanation have focused on control operations. But control is often associated with teleological or normative-sounding concepts like goals and set-points, prompting the question: Does an explanation that refers to parts or mechanisms “controlling” each other thereby fail to be mechanistic? In this paper I introduce and explain a distinction between what I call open-ended and closed-ended control operations. I then argue that explanations that enlist control operations to do explanatory work can count as mechanistic only (...)
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  • Neo-Quinean and neo-Aristotelian metaontology : on explanation, theory choice, and the viability of ontological inquiry.Micheál Vincent Lacey - unknown
    This thesis is an exercise in comparative metaontology. I am centrally concerned with how one might choose between competing metaontological theories. To make my project tractable, I compare two contemporary metaontological approaches dominant in the literature: neo-Quineanism and neo-Aristotelianism. Peter van Inwagen, a representative of N-Q, claims that ontological inquiry should be conducted in the quantifier-variable idiom of first-order predicate logic; to know what exists, or what a theory says exists, we read our commitments off the regimented sentences that we (...)
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  • Reconciling New Mechanism and Psychological Explanation: A Pragmatic Approach.Michael De Vivo - unknown
    Recently, Gualtiero Piccinini and Carl Craver have argued that functional analyses in psychology lack explanatory autonomy from explanations in neuroscience. In this thesis I argue against this claim by motivating and defending a pragmatic-epistemic conception of autonomous psychological explanation. I argue that this conception of autonomy need not require that functional analyses be distinct in kind from neural-mechanistic explanations. I use the framework of Bas van Fraassen’s Pragmatic Theory of Explanation to show that explanations in psychology and neuroscience can be (...)
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  • Integrating Philosophy of Understanding with the Cognitive Sciences.Kareem Khalifa, Farhan Islam, J. P. Gamboa, Daniel Wilkenfeld & Daniel Kostić - 2022 - Frontiers in Systems Neuroscience 16.
    We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.
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  • Prediction and Topological Models in Neuroscience.Bryce Gessell, Matthew Stanley, Benjamin Geib & Felipe De Brigard - forthcoming - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New challenges in the philosophy of neuroscience. Springer.
    In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...)
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  • Mathematics and the world: explanation and representation.John-Hamish Heron - 2017 - Dissertation, King’s College London
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  • The Meta-Explanatory Question.L. R. Franklin-Hall - manuscript
    Philosophical theories of explanation characterize the difference between correct and incorrect explanations. While remaining neutral as to which of these ‘first-order’ theories is right, this paper asks the ‘meta-explanatory’ question: is the difference between correct and incorrect explanation real, i.e., objective or mind-independent? After offering a framework for distinguishing realist from anti-realist views, I sketch three distinct paths to explanatory anti-realism.
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  • Psychoneural Isomorphism: From Metaphysics to Robustness.Alfredo Vernazzani - 2020 - In Marco Viola & Fabrizio Calzavarini (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    At the beginning of the 20th century, Gestalt psychologists put forward the concept of psychoneural isomorphism, which was meant to replace Fechner’s obscure notion of psychophysical parallelism and provide a heuristics that may facilitate the search for the neural correlates of the mind. However, the concept has generated much confusion in the debate, and today its role is still unclear. In this contribution, I will attempt a little conceptual spadework in clarifying the concept of psychoneural isomorphism, focusing exclusively on conscious (...)
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  • Re-re-reconciling the epistemic and ontic views of explanation: a reply to Wright and van Eck.Benjamin Sheredos - manuscript
    In a recent article published in Ergo and entitled "Ontic explanation is either ontic or explanatory, but not both," Cory Wright and Dingmar van Eck have sought to undermine any ontic approach to explanation, providing three arguments to show that an epistemic approach is "the only game in town." I show that each of their arguments is straightforwardly question-begging. For brevity, I make my counter-arguments by showing how the claims of Sheredos (2016)-whom Wright & van Eck cite as an ally-undermine (...)
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