Results for 'Scientific explanations'

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  1. Minimal Structure Explanations, Scientific Understanding and Explanatory Depth.Daniel Kostić - 2018 - Perspectives on Science (1):48-67.
    In this paper, I outline a heuristic for thinking about the relation between explanation and understanding that can be used to capture various levels of “intimacy”, between them. I argue that the level of complexity in the structure of explanation is inversely proportional to the level of intimacy between explanation and understanding, i.e. the more complexity the less intimacy. I further argue that the level of complexity in the structure of explanation also affects the explanatory depth in a similar way (...)
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  2.  90
    The Relations Between Pedagogical and Scientific Explanations of Algorithms: Case Studies From the French Administration.Maël Pégny - manuscript
    The opacity of some recent Machine Learning (ML) techniques have raised fundamental questions on their explainability, and created a whole domain dedicated to Explainable Artificial Intelligence (XAI). However, most of the literature has been dedicated to explainability as a scientific problem dealt with typical methods of computer science, from statistics to UX. In this paper, we focus on explainability as a pedagogical problem emerging from the interaction between lay users and complex technological systems. We defend an empirical methodology based (...)
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  3. Explanations: Aesthetic and Scientific.Shen-yi Liao - 2014 - Royal Institute of Philosophy Supplement 75:127-149.
    Methodologically, philosophical aesthetics is undergoing an evolution that takes it closer to the sciences. Taking this methodological convergence as the starting point, I argue for a pragmatist and pluralist view of aesthetic explanations. To bring concreteness to discussion, I focus on vindicating genre explanations, which are explanations of aesthetic phenomena that centrally cite a work's genre classification. I show that theoretical resources that philosophers of science have developed with attention to actual scientific practice and the special (...)
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  4. Dynamical Versus Structural Explanations in Scientific Revolutions.Mauro Dorato - 2017 - Synthese 194 (7):2307-2327.
    By briefly reviewing three well-known scientific revolutions in fundamental physics (the discovery of inertia, of special relativity and of general relativity), I claim that problems that were supposed to be crying for a dynamical explanation in the old paradigm ended up receiving a structural explanation in the new one. This claim is meant to give more substance to Kuhn’s view that revolutions are accompanied by a shift in what needs to be explained, while suggesting at the same time the (...)
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  5. Mathematical Explanations and the Piecemeal Approach to Thinking About Explanation.Gabriel Târziu - 2018 - Logique Et Analyse 61 (244):457-487.
    A new trend in the philosophical literature on scientific explanation is that of starting from a case that has been somehow identified as an explanation and then proceed to bringing to light its characteristic features and to constructing an account for the type of explanation it exemplifies. A type of this approach to thinking about explanation – the piecemeal approach, as I will call it – is used, among others, by Lange (2013) and Pincock (2015) in the context of (...)
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  6. 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 (...)
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  7. 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 (...)
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  8. The Directionality of Distinctively Mathematical Explanations.Carl F. Craver & Mark Povich - 2017 - Studies in History and Philosophy of Science Part A 63:31-38.
    In “What Makes a Scientific Explanation Distinctively Mathematical?” (2013b), Lange uses several compelling examples to argue that certain explanations for natural phenomena appeal primarily to mathematical, rather than natural, facts. In such explanations, the core explanatory facts are modally stronger than facts about causation, regularity, and other natural relations. We show that Lange's account of distinctively mathematical explanation is flawed in that it fails to account for the implicit directionality in each of his examples. This inadequacy is (...)
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  9. Because Without Cause: Non-Causal Explanations in Science and Mathematics.Mark Povich & Carl F. Craver - 2018 - Philosophical Review 127 (3):422-426.
    Lange’s collection of expanded, mostly previously published essays, packed with numerous, beautiful examples of putatively non-causal explanations from biology, physics, and mathematics, challenges the increasingly ossified causal consensus about scientific explanation, and, in so doing, launches a new field of philosophic investigation. However, those who embraced causal monism about explanation have done so because appeal to causal factors sorts good from bad scientific explanations and because the explanatory force of good explanations seems to derive from (...)
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  10. Explanatory Rivals and the Ultimate Argument.Finnur Dellsén - 2015 - Theoria 82 (3):217-237.
    Although many aspects of Inference to the Best Explanation have been extensively discussed, very little has so far been said about what it takes for a hypothesis to count as a rival explanatory hypothesis in the context of IBE. The primary aim of this article is to rectify this situation by arguing for a specific account of explanatory rivalry. On this account, explanatory rivals are complete explanations of a given explanandum. When explanatory rivals are conceived of in this way, (...)
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  11. Certainty and Explanation in Descartes’s Philosophy of Science.Finnur Dellsén - 2017 - Hopos: The Journal of the International Society for the History of Philosophy of Science 7 (2):302-327.
    This paper presents a new approach to resolving an apparent tension in Descartes’ discussion of scientific theories and explanations in the Principles of Philosophy. On the one hand, Descartes repeatedly claims that any theories presented in science must be certain and indubitable. On the other hand, Descartes himself presents an astonishing number of speculative explanations of various scientific phenomena. In response to this tension, commentators have suggested that Descartes changed his mind about scientific theories having (...)
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  12. When Mechanisms Are Not Enough: The Origin of Eukaryotes and Scientific Explanation.Roger Deulofeu & Javier Suárez - 2018 - In Alexander Christian, David Hommen, Gerhard Schurz & N. Retzlaff (eds.), Philosophy of Science. European Studies in Philosophy of Science, vol 9. Dordrecht, Netherlands: pp. 95-115.
    The appeal to mechanisms in scientific explanation is commonplace in contemporary philosophy of science. In short, mechanists argue that an explanation of a phenomenon consists of citing the mechanism that brings the phenomenon about. In this paper, we present an argument that challenges the universality of mechanistic explanation: in explanations of the contemporary features of the eukaryotic cell, biologists appeal to its symbiogenetic origin and therefore the notion of symbiogenesis plays the main explanatory role. We defend the notion (...)
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  13. Neuroscientific Kinds Through the Lens of Scientific Practice.Jacqueline Anne Sullivan - 2016 - In Catherine Kendig (ed.), Natural Kinds and Classification in Scientific Practice. Routledge. pp. 47-56.
    In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such mechanistic (...)
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  14. 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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  15. Causal Patterns and Adequate Explanations.Angela Potochnik - 2015 - Philosophical Studies 172 (5):1163-1182.
    Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several (...)
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  16. Humean Laws, Explanatory Circularity, and the Aim of Scientific Explanation.Chris Dorst - 2019 - Philosophical Studies 176 (10):2657-2679.
    One of the main challenges confronting Humean accounts of natural law is that Humean laws appear to be unable to play the explanatory role of laws in scientific practice. The worry is roughly that if the laws are just regularities in the particular matters of fact (as the Humean would have it), then they cannot also explain the particular matters of fact, on pain of circularity. Loewer (2012) has defended Humeanism, arguing that this worry only arises if we fail (...)
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  17. A Pessimistic Induction Against Scientific Antirealism.Seungbae Park - 2014 - Organon F: Medzinárodný Časopis Pre Analytickú Filozofiu 21 (1):3-21.
    There are nine antirealist explanations of the success of science in the literature. I raise difficulties against all of them except the latest one, and then construct a pessimistic induction that the latest one will turn out to be problematic because its eight forerunners turned out to be problematic. This pessimistic induction is on a par with the traditional pessimistic induction that successful present scientific theories will be revealed to be false because successful past scientific theories were (...)
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  18. Scientific Collaboration: Do Two Heads Need to Be More Than Twice Better Than One?Thomas Boyer-Kassem & Cyrille Imbert - 2015 - Philosophy of Science 82 (4):667-688.
    Epistemic accounts of scientific collaboration usually assume that, one way or another, two heads really are more than twice better than one. We show that this hypothesis is unduly strong. We present a deliberately crude model with unfavorable hypotheses. We show that, even then, when the priority rule is applied, large differences in successfulness can emerge from small differences in efficiency, with sometimes increasing marginal returns. We emphasize that success is sensitive to the structure of competing communities. Our results (...)
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  19. Extending the Argument From Unconceived Alternatives: Observations, Models, Predictions, Explanations, Methods, Instruments, Experiments, and Values.Darrell Rowbottom - 2016 - Synthese (10).
    Stanford’s argument against scientific realism focuses on theories, just as many earlier arguments from inconceivability have. However, there are possible arguments against scientific realism involving unconceived (or inconceivable) entities of different types: observations, models, predictions, explanations, methods, instruments, experiments, and values. This paper charts such arguments. In combination, they present the strongest challenge yet to scientific realism.
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  20. On Structural Accounts of Model-Explanations.Martin King - 2016 - Synthese 193 (9):2761-2778.
    The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems with maintaining that (...)
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  21.  81
    Cartesian Certainty, Realism and Scientific Inference.Manuel Barrantes - forthcoming - In Jorge Secada & C. Wee (eds.), The Cartesian Mind.
    In the Principles, Descartes explains several observable phenomena showing that they are caused by special arrangements of unobservable microparticles. Despite these microparticles being unobservable, many passages suggest that he was very confident that these explanations were correct. In other passages, however, Descartes points out that these explanations merely hold the status of ‘suppositions’ or ‘conjectures’ that could be wrong. The aim of this chapter is to clarify this apparent conflict. I argue that the possibility of natural explanations (...)
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  22.  97
    The Causal Economy Approach to Scientific Explanation.Laura Franklin-Hall - forthcoming - Minnesota Studies in the Philosophy of Science.
    This paper sketches a causal account of scientific explanation designed to sustain the judgment that high-level, detail-sparse explanations—particularly those offered in biology—can be at least as explanatorily valuable as lower-level counterparts. The motivating idea is that complete explanations maximize causal economy: they cite those aspects of an event’s causal run-up that offer the biggest-bang-for-your-buck, by costing less (in virtue of being abstract) and delivering more (in virtue making the event stable or robust).
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  23.  51
    Explanations and candidate explanations in physics.Martin King - 2020 - European Journal for Philosophy of Science 10 (1):1-17.
    There has been a growing trend to include non-causal models in accounts of scientific explanation. A worry addressed in this paper is that without a higher threshold for explanation there are no tools for distinguishing between models that provide genuine explanations and those that provide merely potential explanations. To remedy this, a condition is introduced that extends a veridicality requirement to models that are empirically underdetermined, highly-idealised, or otherwise non-causal. This condition is applied to models of electroweak (...)
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  24. Modeling and Inferring in Science.Emiliano Ippoliti, Thomas Nickles & Fabio Sterpetti - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Springer. pp. 1-9.
    Science continually contributes new models and rethinks old ones. The way inferences are made is constantly being re-evaluated. The practice and achievements of science are both shaped by this process, so it is important to understand how models and inferences are made. But, despite the relevance of models and inference in scientific practice, these concepts still remain contro-versial in many respects. The attempt to understand the ways models and infer-ences are made basically opens two roads. The first one is (...)
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  25. The Rationality of Scientific Discovery Part 1: The Traditional Rationality Problem.Nicholas Maxwell - 1974 - Philosophy of Science 41 (2):123--53.
    The basic task of the essay is to exhibit science as a rational enterprise. I argue that in order to do this we need to change quite fundamentally our whole conception of science. Today it is rather generally taken for granted that a precondition for science to be rational is that in science we do not make substantial assumptions about the world, or about the phenomena we are investigating, which are held permanently immune from empirical appraisal. According to this standard (...)
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  26. Humean Scientific Explanation.Elizabeth Miller - 2015 - Philosophical Studies 172 (5):1311-1332.
    In a recent paper, Barry Loewer attempts to defend Humeanism about laws of nature from a charge that Humean laws are not adequately explanatory. Central to his defense is a distinction between metaphysical and scientific explanations: even if Humeans cannot offer further metaphysical explanations of particular features of their “mosaic,” that does not preclude them from offering scientific explanations of these features. According to Marc Lange, however, Loewer’s distinction is of no avail. Defending a transitivity (...)
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  27. 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 (...)
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  28. Scientific Explanation: Putting Communication First.Angela Potochnik - 2016 - Philosophy of Science 83 (5):721-732.
    Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative (...)
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  29. There May Yet Be Non-Causal Explanations.Finnur Dellsén - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (2):377-384.
    There are many putative counterexamples to the view that all scientific explanations are causal explanations. Using a new theory of what it is to be a causal explanation, Bradford Skow has recently argued that several of the putative counterexamples fail to be non-causal. This paper defends some of the counterexamples by showing how Skow’s argument relies on an overly permissive theory of causal explanations.
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  30. Explaining the Success of a Scientific Theory.Timothy D. Lyons - 2003 - Philosophy of Science 70 (5):891-901.
    Scientific realists have claimed that the posit that our theories are (approximately) true provides the best or the only explanation for their success . In response, I revive two non-realists explanations. I show that realists, in discarding them, have either misconstrued the phenomena to be explained or mischaracterized the relationship between these explanations and their own. I contend nonetheless that these non-realist competitors, as well as their realist counterparts, should be rejected; for none of them succeed in (...)
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  31. 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 (...)
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  32. Scientific Explanation and Moral Explanation.Uri D. Leibowitz - 2011 - Noûs 45 (3):472-503.
    Moral philosophers are, among other things, in the business of constructing moral theories. And moral theories are, among other things, supposed to explain moral phenomena. Consequently, one’s views about the nature of moral explanation will influence the kinds of moral theories one is willing to countenance. Many moral philosophers are (explicitly or implicitly) committed to a deductive model of explanation. As I see it, this commitment lies at the heart of the current debate between moral particularists and moral generalists. In (...)
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  33. Judging Mechanistic Neuroscience: A Preliminary Conceptual-Analytic Framework for Evaluating Scientific Evidence in the Courtroom.Jacqueline Anne Sullivan & Emily Baron - 2018 - Psychology, Crime and Law (00):00-00.
    The use of neuroscientific evidence in criminal trials has been steadily increasing. Despite progress made in recent decades in understanding the mechanisms of psychological and behavioral functioning, neuroscience is still in an early stage of development and its potential for influencing legal decision-making is highly contentious. Scholars disagree about whether or how neuroscientific evidence might impact prescriptions of criminal culpability, particularly in instances in which evidence of an accused’s history of mental illness or brain abnormality is offered to support a (...)
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  34. A Critique of Popper's Views on Scientific Method.Nicholas Maxwell - 1972 - Philosophy of Science 39 (2):131-152.
    This paper considers objections to Popper's views on scientific method. It is argued that criticism of Popper's views, developed by Kuhn, Feyerabend, and Lakatos, are not too damaging, although they do require that Popper's views be modified somewhat. It is argued that a much more serious criticism is that Popper has failed to provide us with any reason for holding that the methodological rules he advocates give us a better hope of realizing the aims of science than any other (...)
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  35.  61
    Surrealism Is Not an Alternative to Scientific Realism.Seungbae Park - 2019 - Logos and Episteme: An International Journal of Epistemology 10 (4):379–393.
    Surrealism holds that observables behave as if T were true, whereas scientific realism holds that T is true. Surrealism and scientific realism give different explanations of why T is empirically adequate. According to surrealism, T is empirically adequate because observables behave as if it were true. According to scientific realism, T is empirically adequate because it is true. I argue that the surrealist explanation merely clarifies the concept of empirical adequacy, whereas the realist explanation makes an (...)
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  36.  24
    Perspectivalism in the Development of Scientific Observer-Relativity.Lydia Patton - 2019 - In Martin Kusch, Katherina Kinzel, Johannes Steizinger & Niels Jacob Wildschut (eds.), The Emergence of Relativism. New York: Routledge. pp. 63-78.
    Hermann von Helmholtz allows for not only physiological facts and psychological inferences, but also perspectival reasoning, to influence perceptual experience and knowledge gained from perception. But Helmholtz also defends a version of the view according to which there can be a kind of “perspectival truth” revealed in scientific research and investigation. Helmholtz argues that the relationships between subjective and objective, real and actual, actual and illusory, must be analyzed scientifically, within experience. There is no standpoint outside experience from which (...)
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  37. 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 the causes (...)
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  38.  83
    Functional Analyses, Mechanistic Explanations, and Explanatory Tradeoffs.Sergio Daniel Barberis - 2013 - Journal of Cognitive Science 14:229-251.
    Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, we must (...)
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  39. Paradigmatic Explanations: Strauss's Dangerous Idea.Gregory W. Dawes - 2007 - Louvain Studies 32 (1-2):67-80.
    David Friedrich Strauss is best known for his mythical interpretation of the Gospel narratives. He opposed both the supernaturalists (who regarded the Gospel stories as reliable) and the rationalists (who offered natural explanations of purportedly supernatural events). His mythical interpretation suggests that many of the stories about Jesus were woven out of pre-existing messianic beliefs and expectations. Picking up this suggestion, I argue that the Gospel writers thought paradigmatically rather than historically. A paradigmatic explanation assimilates the event-to-be- explained to (...)
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  40. A Biological Alternative to Moral Explanations.Joseph Millum - 2008 - Southern Journal of Philosophy 46 (3):385-407.
    Some moral realists claim that moral facts are a species of natural fact, amenable to scientific investigation. They argue that these moral facts are needed in the best explanations of certain phenomena and that this is evidence that they are real. In this paper I present part of a biological account of the function of morality. The account allows the identification of a plausible natural kind that could play the explanatory role that a moral kind would play in (...)
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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 propose (...)
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  42. Realism and the Limits of Explanatory Reasoning.Juha Saatsi - 2018 - In The Routledge Handbook of Scientific Realism. London: Routledge. pp. 200-211.
    This chapter examines issues surrounding inference to the best explanation, its justification, and its role in different arguments for scientific realism, as well as more general issues concerning explanations’ ontological commitments. Defending the reliability of inference to the best explanation has been a central plank in various realist arguments, and realists have drawn various ontological conclusions from the premise that a given scientific explanation best explains some phenomenon. This chapter stresses the importance of thinking carefully about the (...)
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  43. Realism and Explanatory Perspectivism.Juha Saatsi - forthcoming - In Michela Massimi & C. D. McCoy (eds.), Understanding Perspectivism: Scientific Challenges and Methodological Prospects. New York: Routledge.
    This chapter defends a (minimal) realist conception of progress in scientific understanding in the face of the ubiquitous plurality of perspectives in science. The argument turns on the counterfactual-dependence framework of explanation and understanding, which is illustrated and evidenced with reference to different explanations of the rainbow.
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  44.  23
    Estructuralismo, ficcionalismo, y la aplicabilidad de las matemáticas en ciencia.Manuel Barrantes - 2019 - Areté. Revista de Filosofía 31 (1):7-34.
    “Structuralism, Fictionalism, and the Applicability of Mathematics in Science”. This article has two objectives. The first one is to review some of the most important questions in the contemporary philosophy of mathematics: What is the nature of mathematical objects? How do we acquire knowledge about these objects? Should mathematical statements be interpreted differently than ordinary ones? And, finally, how can we explain the applicability of mathematics in science? The debate that guides these reflections is the one between mathematical realism and (...)
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  45. 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 models (...)
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  46. 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 (...)
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  47.  23
    A Teoria da Demonstração Científica de Aristóteles em Segundos Analíticos 1.2-9 e 1.13.Davi Bastos - 2020 - Archai: Revista de Estudos Sobre as Origens Do Pensamento Ocidental 30:e03021.
    I defend an interpretation of Aristotle’s Posterior Analytics Book I which distinguishes between two projects in different passages of that work: (i) to explain what a given science is and (ii) to explain what properly scientific knowledge is. I present Aristotle’s theory in answer to ii, with special attention to his definition of scientific knowledge in 71b9-12 and showing how this is developed on chapters I.2-9 and I.13 into a solid Theory of Scientific Demonstration. The main point (...)
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  48. Crossing the Milvian Bridge: When Do Evolutionary Explanations of Belief Debunk Belief?Paul E. Griffiths & John S. Wilkins - 2015 - In Phillip R. Sloan, Gerald McKenny & Kathleen Eggleson (eds.), Darwin in the Twenty-First Century: Nature, Humanity, and God. University of Notre Dame Press. pp. 201-231.
    Ever since Darwin people have worried about the sceptical implications of evolution. If our minds are products of evolution like those of other animals, why suppose that the beliefs they produce are true, rather than merely useful? In this chapter we apply this argument to beliefs in three different domains: morality, religion, and science. We identify replies to evolutionary scepticism that work in some domains but not in others. The simplest reply to evolutionary scepticism is that the truth of beliefs (...)
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  49. Explaining the Behaviour of Random Ecological Networks: The Stability of the Microbiome as a Case of Integrative Pluralism.Roger Deulofeu, Javier Suárez & Alberto Pérez-Cervera - forthcoming - Synthese:1-23.
    Explaining the behaviour of ecosystems is one of the key challenges for the biological sciences. Since 2000, new-mechanicism has been the main model to account for the nature of scientific explanation in biology. The universality of the new-mechanist view in biology has been however put into question due to the existence of explanations that account for some biological phenomena in terms of their mathematical properties (mathematical explanations). Supporters of mathematical explanation have argued that the explanation of the (...)
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  50. 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 (...)
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