Results for 'calling for explanation'

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  1.  80
    Calling for explanation: the case of the thermodynamic past state.Dan Baras & Orly Shenker - 2020 - European Journal for Philosophy of Science 10 (3):1-20.
    Philosophers of physics have long debated whether the Past State of low entropy of our universe calls for explanation. What is meant by “calls for explanation”? In this article we analyze this notion, distinguishing between several possible meanings that may be attached to it. Taking the debate around the Past State as a case study, we show how our analysis of what “calling for explanation” might mean can contribute to clarifying the debate and perhaps to settling (...)
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  2. How Can Necessary Facts Call for Explanation?Dan Baras - forthcoming - Synthese:1-18.
    While there has been much discussion about what makes some mathematical proofs more explanatory than others, and what are mathematical coincidences, in this article I explore the distinct phenomenon of mathematical facts that call for explanation. The existence of mathematical facts that call for explanation stands in tension with virtually all existing accounts of “calling for explanation”, which imply that necessary facts cannot call for explanation. In this paper I explore what theoretical revisions are needed (...)
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  3. Why Do Certain States of Affairs Call Out for Explanation? A Critique of Two Horwichian Accounts.Dan Baras - 2019 - Philosophia 47 (5):1405-1419.
    Motivated by examples, many philosophers believe that there is a significant distinction between states of affairs that are striking and therefore call for explanation and states of affairs that are not striking. This idea underlies several influential debates in metaphysics, philosophy of mathematics, normative theory, philosophy of modality, and philosophy of science but is not fully elaborated or explored. This paper aims to address this lack of clear explanation first by clarifying the epistemological issue at hand. Then it (...)
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  4. Pluralistic Ignorance in the Bystander Effect: Informational Dynamics of Unresponsive Witnesses in Situations Calling for Intervention.Rasmus Kraemmer Rendsvig - 2014 - Synthese 191 (11):2471-2498.
    The goal of the present paper is to construct a formal explication of the pluralistic ignorance explanation of the bystander effect. The social dynamics leading to inaction is presented, decomposed, and modeled using dynamic epistemic logic augmented with ‘transition rules’ able to characterize agent behavior. Three agent types are defined: First Responders who intervene given belief of accident; City Dwellers, capturing ‘apathetic urban residents’ and Hesitators, who observe others when in doubt, basing subsequent decision on social proof. It is (...)
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  5. Diagrams as Locality Aids for Explanation and Model Construction in Cell Biology.Nicholaos Jones & Olaf Wolkenhauer - 2012 - Biology and Philosophy 27 (5):705-721.
    Using as case studies two early diagrams that represent mechanisms of the cell division cycle, we aim to extend prior philosophical analyses of the roles of diagrams in scientific reasoning, and specifically their role in biological reasoning. The diagrams we discuss are, in practice, integral and indispensible elements of reasoning from experimental data about the cell division cycle to mathematical models of the cycle’s molecular mechanisms. In accordance with prior analyses, the diagrams provide functional explanations of the cell cycle and (...)
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  6. The “Positive Argument” for Constructive Empiricism and Inference to the Best Explanation.Moti Mizrahi - 2018 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 49 (3):461–466.
    In this paper, I argue that the “positive argument” for Constructive Empiricism (CE), according to which CE “makes better sense of science, and of scientific activity, than realism does” (van Fraassen 1980, 73), is an Inference to the Best Explanation (IBE). But constructive empiricists are critical of IBE, and thus they have to be critical of their own “positive argument” for CE. If my argument is sound, then constructive empiricists are in the awkward position of having to reject their (...)
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  7. The Case for Regularity in Mechanistic Causal Explanation.Holly Andersen - 2012 - Synthese 189 (3):415-432.
    How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...)
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  8. Teaching and Learning Guide For: Explanation in Mathematics: Proofs and Practice.William D'Alessandro - 2019 - Philosophy Compass 14 (11).
    This is a teaching and learning guide to accompany "Explanation in Mathematics: Proofs and Practice".
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  9. Varying the Explanatory Span: Scientific Explanation for Computer Simulations.Juan Manuel Durán - 2017 - International Studies in the Philosophy of Science 31 (1):27-45.
    This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model (...)
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  10. Intelligibility is Necessary for Scientific Explanation, but Accuracy May Not Be.Mike Braverman, John Clevenger, Ian Harmon, Andrew Higgins, Zachary Horne, Joseph Spino & Jonathan Waskan - 2012 - In Naomi Miyake, David Peebles & Richard Cooper (eds.), Proceedings of the Thirty-Fourth Annual Conference of the Cognitive Science Society. Cognitive Science Society.
    Many philosophers of science believe that empirical psychology can contribute little to the philosophical investigation of explanations. They take this to be shown by the fact that certain explanations fail to elicit any relevant psychological events (e.g., familiarity, insight, intelligibility, etc.). We report results from a study suggesting that, at least among those with extensive science training, a capacity to render an event intelligible is considered a requirement for explanation. We also investigate for whom explanations must be capable of (...)
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  11. ‘Pain Always Asks for a Cause’: Nietzsche and Explanation.Matthew Bennett - 2017 - European Journal of Philosophy 25 (4):1550-1568.
    Those who have emphasised Nietzsche's naturalism have often claimed that he emulates natural scientific methods by offering causal explanations of psychological, social, and moral phenomena. In order to render Nietzsche's method consistent with his methodology, such readers of Nietzsche have also claimed that his objections to the use of causal explanations are based on a limited scepticism concerning the veracity of causal explanations. My contention is that proponents of this reading are wrong about both Nietzsche's methodology and his method. I (...)
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  12. The No‐Miracles Argument for Realism: Inference to an Unacceptable Explanation.Greg Frost‐Arnold - 2010 - Philosophy of Science 77 (1):35-58.
    I argue that a certain type of naturalist should not accept a prominent version of the no-miracles argument (NMA). First, scientists (usually) do not accept explanations whose explanans-statements neither generate novel predictions nor unify apparently disparate established claims. Second, scientific realism (as it appears in the NMA) is an explanans that makes no new predictions and fails to unify disparate established claims. Third, many proponents of the NMA explicitly adopt a naturalism that forbids philosophy of science from using any methods (...)
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  13. Plato Seeking for “One Real Explanation” in Phaedo.Mohammad Bagher Ghomi - manuscript
    This essay intends to discuss what Plato was seeking as an explanation in Phaedo. In this dialogue, we observe Socrates criticizing both the natural scientists’ explanations and Anaxagoras’ theory of Mind because they could not explain all things, firstly, in a unitary and, secondary, in a real way. Thence, we are to call what Plato is seeking as his ideal explanation in Phaedo “One Real Explanation”. He talks at least about three kinds of explanation, two of (...)
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  14. New Mechanistic Explanation and the Need for Explanatory Constraints.L. R. Franklin-Hall - 2016 - In Ken Aizawa & Carl Gillett (eds.), Scientific Composition and Metaphysical Ground. Palgrave. pp. 41-74.
    This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, I argue that (...)
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  15.  42
    Function-Theoretic Explanation and the Search for Neural Mechanisms.Frances Egan - 2017 - In Explanation and Integration in Mind and Brain Science 145-163. Oxford, UK: pp. 145-163.
    A common kind of explanation in cognitive neuroscience might be called functiontheoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes (in the system’s normal environment) the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it (...)
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  16.  14
    Respect for Subjects in the Ethics of Causal and Interpretive Social Explanation.Michael L. Frazer - forthcoming - American Political Science Review.
    Rival causal and interpretive approaches to explaining social phenomena have important ethical differences. While human actions can be explained as a result of causal mechanisms, as a meaningful choice based on reasons, or as some combination of the two, it is morally important that social scientists respect others by recognizing them as persons. Interpretive explanations directly respect their subjects in this way, while purely causal explanations do not. Yet although causal explanations are not themselves expressions of respect, they can be (...)
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  17. Is There Room for Reference Borrowing in Donnellan’s Historical Explanation Theory?Andrea Bianchi & Alessandro Bonanini - 2014 - Linguistics and Philosophy 37 (3):175-203.
    Famously, both Saul Kripke and Keith Donnellan opposed description theories and insisted on the role of history in determining the reference of a proper name token. No wonder, then, that their views on proper names have often been assimilated. By focusing on reference borrowing—an alleged phenomenon that Kripke takes to be fundamental—we argue that they should not be. In particular, we claim that according to Donnellan a proper name token never borrows its reference from preceding tokens which it is historically (...)
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  18. The Case for the Comparator Model as an Explanation of the Sense of Agency and its Breakdowns.Glenn Carruthers - 2012 - Consciousness and Cognition 21 (1):30-45.
    I compare Frith and colleagues’ influential comparator account of how the sense of agency is elicited to the multifactorial weighting model advocated by Synofzik and colleagues. I defend the comparator model from the common objection that the actual sensory consequences of action are not needed to elicit the sense of agency. I examine the comparator model’s ability to explain the performance of healthy subjects and those suffering from delusions of alien control on various self-attribution tasks. It transpires that the comparator (...)
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  19.  18
    Towards a Biological Explanation of Sin in Walter M. Miller, Jr.'s “A Canticle for Leibowitz”.Christopher Ketcham - 2020 - Journal of Science Fiction and Philosophy 3:1-25.
    Walter M. Miller, Jr.’s 1959 novel A Canticle for Leibowitz is on one level a theological reflection on the human propensity to sin. Not coincidentally, the story is located in an Albertinian abbey in the former American southwest six hundred years after a nuclear holocaust, recounting three separate historical periods over the following twelve hundred years: a dark age, a scientific renaissance, and finally a time of technological achievement where a second nuclear holocaust is imminent. Miller asks the question of (...)
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  20. Disagreement, Correctness, and the Evidence for Metaethical Absolutism.Gunnar Björnsson - 2015 - In Russ Shafer-Landau (ed.), Oxford Studies in Metaethics: Volume 8. Oxford University Press.
    Metaethical absolutism is the view that moral concepts have non-relative satisfaction conditions that are constant across judges and their particular beliefs, attitudes, and cultural embedding. If it is correct, there is an important sense in which parties of moral disputes are concerned to get the same things right, such that their disputes can be settled by the facts. If it is not correct, as various forms of relativism and non-cognitivism imply, such coordination of concerns will be limited. The most influential (...)
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  21. Inductions, Red Herrings, and the Best Explanation for the Mixed Record of Science.P. D. Magnus - 2010 - British Journal for the Philosophy of Science 61 (4):803-819.
    Kyle Stanford has recently claimed to offer a new challenge to scientific realism. Taking his inspiration from the familiar Pessimistic Induction (PI), Stanford proposes a New Induction (NI). Contra Anjan Chakravartty’s suggestion that the NI is a ‘red herring’, I argue that it reveals something deep and important about science. The Problem of Unconceived Alternatives, which lies at the heart of the NI, yields a richer anti-realism than the PI. It explains why science falls short when it falls short, and (...)
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  22. Refusing to Endorse. A Must Explanation for Pejoratives.Carlo Penco - 2018 - In Annalisa Coliva, Paolo Leonardi & Sebastiano Moruzzi (eds.), Eva Picardi on Language, Analysis and History. London: Palgrave. pp. 219-239.
    In her analysis of pejoratives, Eva Picardi rejects a too sharp separation between descriptive and expressive content. I reconstruct some of her arguments, endorsing Eva’s criticism of Williamson’s analysis of Dummett and developing a suggestion by Manuel Garcia Carpintero on a speech act analysis of pejoratives. Eva’s main concern is accounting for our instinctive refusal to endorse an assertion containing pejoratives because it suggests a picture of reality we do not share. Her stance might be further developed claiming that uses (...)
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  23. A Unified Explanation of Quantum Phenomena? The Case for the Peer‐to‐Peer Simulation Hypothesis as an Interdisciplinary Research Program.Marcus Arvan - 2014 - Philosophical Forum 45 (4):433-446.
    In my 2013 article, “A New Theory of Free Will”, I argued that several serious hypotheses in philosophy and modern physics jointly entail that our reality is structurally identical to a peer-to-peer (P2P) networked computer simulation. The present paper outlines how quantum phenomena emerge naturally from the computational structure of a P2P simulation. §1 explains the P2P Hypothesis. §2 then sketches how the structure of any P2P simulation realizes quantum superposition and wave-function collapse (§2.1.), quantum indeterminacy (§2.2.), wave-particle duality (§2.3.), (...)
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  24. An Explanation for Normal and Anomalous Drawing Ability and Some Implications for Research on Perception and Imagery.Jennifer A. McMahon - 2006 - Visual Arts Research 28 (1):38-52.
    The aim of this paper is to draw the attention of those conducting research on imagery to the different kinds of visual information deployed by expert drawers compared to non-expert drawers. To demonstrate this difference I draw upon the cognitive science literature on vision and imagery to distinguish between three different ways that visual phenomena can be represented in memory: structural descriptions, denotative descriptions, and configural descriptions. Research suggests that perception and imagery deploy the same mental processes and that the (...)
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  25.  33
    Art Historical Explanation Of Paintings And The Need For An Aesthetics Of Agency.Daniel Davies - 2004 - Postgraduate Journal of Aesthetics 1 (3):86-98.
    Why should a person, and in the context of this conference particularly an art historian, take seriously the notion of the aesthetic, its discovery and/or rediscovery? Aesthetics might after all be considered at best something of a distraction from bread and butter historical and sociological analysis, and at worst entirely incompatible with it. Pursuing the line further it might be urged that, since on the one hand aesthetics is about 'how things appear'—i.e. is subject to individual predilection, taste and feeling—and (...)
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  26. Philosophical Intuition and the Need for an Explanation.Alexander S. Harper - manuscript
    Traditionally, intuitions about cases have been taken as strong evidence for a philosophical position. I argue that intuitions about concept deployment have epistemic value while intuitions about matters of fact have none. I argue this by use of the explanationist criterion which contends that S is justified in believing only those propositions which are part of the best explanation of S’s making the judgements she makes. This criterion accords with scientific practice. Bealer suggests, as a defence of intuition, that (...)
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  27. Between Probability and Certainty: What Justifies Belief.Martin Smith - 2016 - Oxford University Press UK.
    This book explores a question central to philosophy--namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In this book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it--roughly, one's evidence must make the falsity of that proposition (...)
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  28. The Formulation of Disjunctivism About Φ-Ing for a Reason.J. J. Cunningham - 2019 - Philosophical Quarterly 69 (275):235-257.
    We can contrast rationalising explanations of the form S φs because p with those of the form S φs because S believes that p. According the Common Kind View, the two sorts of explanation are the same. The Disjunctive View denies this. This paper sets out to elucidate the sense in which the Common Kind Theorist asserts, but the Disjunctivist denies, that the two explanations are the same. I suggest that, in the light of the distinction between kinds of (...)
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  29. Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In P. Braillard & C. Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations (...)
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  30.  82
    Proof, Explanation, and Justification in Mathematical Practice.Moti Mizrahi - forthcoming - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie:1-18.
    In this paper, I propose that applying the methods of data science to “the problem of whether mathematical explanations occur within mathematics itself” (Mancosu 2018) might be a fruitful way to shed new light on the problem. By carefully selecting indicator words for explanation and justification, and then systematically searching for these indicators in databases of scholarly works in mathematics, we can get an idea of how mathematicians use these terms in mathematical practice and with what frequency. The results (...)
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  31. Was Ist Ein Vollkommener Syllogismus des Aristoteles?Theodor Ebert - 1995 - Archiv für Geschichte der Philosophie 77 (3):221-247.
    This paper (1) criticizes Patzig's explanation of Aristotle's reason for calling his first figure syllogisms perfect syllogisms, i.e. the transitivity relation: it can only be used for Barbara, not for the other three moods. The paper offers (2) an alternative interpretation: It is only in the case of the (perfect) first figure moods that we can move from the subject term of the minor premiss, taken to be a predicate of an individual, to the predicate term of the (...)
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  32.  50
    Miracles, Trust, and Ennui in Barnes’ Predictivism.P. D. Magnus - 2011 - Logos and Episteme 2 (1):103-114.
    Eric Barnes’ The Paradox of Predictivism is concerned primarily with two facts: predictivism and pluralism. In the middle part of the book, he peers through these two lenses at the tired realist scarecrow of the no-miracles argument. He attempts to reanimate this weatherworn realist argument, contra suggestions by people like me that it should be abandoned. In this paper, I want to get clear on Barnes’ contribution to the debate. He focuses on what he calls the miraculous endorsement argument, which (...)
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  33. The Ontic Account of Scientific Explanation.Carl F. Craver - 2014 - 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.
    According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of (...)
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  34. Assessing the Resurrection Hypothesis: Problems with Craig's Inference to the Best Explanation.Robert Greg Cavin & Carlos A. Colombetti - 2019 - European Journal for Philosophy of Religion 11 (2):205-228.
    The hypothesis that God supernaturally raised Jesus from the dead is argued by William Lane Craig to be the best explanation for the empty tomb and postmortem appearances of Jesus because it satisfies seven criteria of adequacy better than rival naturalistic hypotheses. We identify problems with Craig’s criteria-based approach and show, most significantly, that the Resurrection hypothesis fails to fulfill any but the first of his criteria—especially explanatory scope and plausibility.
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  35. Does IBE Require a ‘Model’ of Explanation?Frank Cabrera - 2017 - British Journal for the Philosophy of Science 71 (2):727-750.
    In this article, I consider an important challenge to the popular theory of scientific inference commonly known as ‘inference to the best explanation’, one that has received scant attention.1 1 The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival (...)
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  36.  82
    Metaphysical Explanations and the Counterfactual Theory of Explanation.Stefan Roski - forthcoming - Philosophical Studies.
    According to an increasingly popular view among philosophers of science, both causal and non-causal explanations can be accounted for by a single theory: the counterfactual theory of explanation. A kind of non-causal explanation that has gained much attention recently but that this theory seems unable to account for are grounding explanations. Reutlinger (2017) has argued that, despite these appearances to the contrary, such explanations are covered by his version of the counterfactual theory. His idea is supported by recent (...)
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  37. Searching for Noncausal Explanations in a Sea of Causes.Alisa Bokulich - 2018 - In Alexander Reutlinger & Juha Saatsi (eds.), Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations. Oxford University Press.
    In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining (...)
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  38. Beyond Explanation: Understanding as Dependency Modeling.Finnur Dellsén - 2018 - British Journal for the Philosophy of Science.
    This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding (...)
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  39. What Constitutes an Explanation in Biology?Angela Potochnik - forthcoming - In Kostas Kampourakis & Tobias Uller (eds.), Philosophy of Science for Biologists. Cambridge, UK: Cambridge University Press.
    One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely shared philosophical views about scientific explanation. But this discussion also reflects what I think is important for philosophers and biologists alike to appreciate about successful scientific explanations, so some points will be controversial, at least among philosophers. I make three main points: (1) (...)
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  40. Equilibrium Explanation as Structural Non-Mechanistic Explanation: The Case Long-Term Bacterial Persistence in Human Hosts.Javier Suárez & Roger Deulofeu - 2019 - Teorema: International Journal of Philosophy 3 (38):95-120.
    Philippe Huneman has recently questioned the widespread application of mechanistic models of scientific explanation based on the existence of structural explanations, i.e. explanations that account for the phenomenon to be explained in virtue of the mathematical properties of the system where the phenomenon obtains, rather than in terms of the mechanisms that causally produce the phenomenon. Structural explanations are very diverse, including cases like explanations in terms of bowtie structures, in terms of the topological properties of the system, or (...)
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  41. Minimal Models and the Generalized Ontic Conception of Scientific Explanation.Mark Povich - 2018 - British Journal for the Philosophy of Science 69 (1):117-137.
    Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) they (...)
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  42. Presume It Not: True Causes in the Search for the Basis of Heredity.Aaron Novick & Raphael Scholl - 2017 - British Journal for the Philosophy of Science (1):axy001.
    Kyle Stanford has recently given substance to the problem of unconceived alternatives, which challenges the reliability of inference to the best explanation (IBE) in remote domains of nature. Conjoined with the view that IBE is the central inferential tool at our disposal in investigating these domains, the problem of unconceived alternatives leads to scientific anti-realism. We argue that, at least within the biological community, scientists are now and have long been aware of the dangers of IBE. We re-analyze the (...)
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  43. The Narrow Ontic Counterfactual Account of Distinctively Mathematical Explanation.Mark Povich - 2019 - British Journal for the Philosophy of Science:axz008.
    An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s (forthcoming) deductive-mathematical account, because it is modelled on the deductive-nomological account, is unlikely to satisfy these desiderata. I provide a counterfactual account of DME, (...)
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  44. A Regularist Approach to Mechanistic Type-Level Explanation.Beate Krickel - 2017 - British Journal for the Philosophy of Science (4):00-00.
    Most defenders of the new mechanistic approach accept ontic constraints for successful scientific explanation (Illari 2013; Craver 2014). The minimal claim is that scientific explanations have objective truthmakers, namely mechanisms that exist in the physical world independently of any observer and that cause or constitute the phenomena-to- be-explained. How can this idea be applied to type-level explanations? Many authors at least implicitly assume that in order for mechanisms to be the truthmakers of type-level explanation they need to be (...)
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  45. Introduction: Scientific Explanation Beyond Causation.Alexander Reutlinger & Juha Saatsi - 2017 - In Alexander Reutlinger & Juha Saatsi (eds.), Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations. Oxford: Oxford University Press.
    This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). -/- Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about (...)
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  46. Explanation, Confirmation, and Hempel's Paradox.William Roche - 2017 - In Kevin McCain & Ted Poston (eds.), Best explanations: New essays on inference to the best explanation. Oxford: Oxford University Press. pp. 219-241.
    Hempel’s Converse Consequence Condition (CCC), Entailment Condition (EC), and Special Consequence Condition (SCC) have some prima facie plausibility when taken individually. Hempel, though, shows that they have no plausibility when taken together, for together they entail that E confirms H for any propositions E and H. This is “Hempel’s paradox”. It turns out that Hempel’s argument would fail if one or more of CCC, EC, and SCC were modified in terms of explanation. This opens up the possibility that Hempel’s (...)
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  47. Biological Explanation.Angela Potochnik - 2013 - In Kostas Kampourakis (ed.), The Philosophy of Biology: A Companion for Educators. Springer. pp. 49-65.
    One of the central aims of science is explanation: scientists seek to uncover why things happen the way they do. This chapter addresses what kinds of explanations are formulated in biology, how explanatory aims influence other features of the field of biology, and the implications of all of this for biology education. Philosophical treatments of scientific explanation have been both complicated and enriched by attention to explanatory strategies in biology. Most basically, whereas traditional philosophy of science based (...) on derivation from scientific laws, there are many biological explanations in which laws play little or no role. Instead, the field of biology is a natural place to turn for support for the idea that causal information is explanatory. Biology has also been used to motivate mechanistic accounts of explanation, as well as criticisms of that approach. Ultimately, the most pressing issue about explanation in biology may be how to account for the wide range of explanatory styles encountered in the field. This issue is crucial, for the aims of biological explanation influence a variety of other features of the field of biology. Explanatory aims account for the continued neglect of some central causal factors, a neglect that would otherwise be mysterious. This is linked to the persistent use of models like evolutionary game theory and population genetic models, models that are simplified to the point of unreality. These explanatory aims also offer a way to interpret many biologists’ total commitment to one or another methodological approach, and the intense disagreements that result. In my view, such debates are better understood as arising not from different theoretical commitments, but commitments to different explanatory projects. Biology education would thus be enriched by attending to approaches to biological explanation, as well as the unexpected ways that these explanatory aims influence other features of biology. I suggest five lessons for teaching about explanation in biology that follow from the considerations of this chapter. (shrink)
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  48.  32
    Using Corpus Linguistics to Investigate Mathematical Explanation.Juan Pablo Mejía Ramos, Lara Alcock, Kristen Lew, Paolo Rago, Chris Sangwin & Matthew Inglis - 2019 - In Eugen Fischer & Mark Curtis (eds.), Methodological Advances in Experimental Philosophy. London: Bloomsbury Academic. pp. 239–263.
    In this chapter we use methods of corpus linguistics to investigate the ways in which mathematicians describe their work as explanatory in their research papers. We analyse use of the words explain/explanation (and various related words and expressions) in a large corpus of texts containing research papers in mathematics and in physical sciences, comparing this with their use in corpora of general, day-to-day English. We find that although mathematicians do use this family of words, such use is considerably less (...)
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  49. 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 (...)
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  50. Inference to the Best Explanation Made Incoherent.Nevin Climenhaga - 2017 - Journal of Philosophy 114 (5):251-273.
    Defenders of Inference to the Best Explanation claim that explanatory factors should play an important role in empirical inference. They disagree, however, about how exactly to formulate this role. In particular, they disagree about whether to formulate IBE as an inference rule for full beliefs or for degrees of belief, as well as how a rule for degrees of belief should relate to Bayesianism. In this essay I advance a new argument against non-Bayesian versions of IBE. My argument focuses (...)
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