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91 found
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  1. Karl Popper: Conjectures and Refutations.Danny Frederick - manuscript
  2. Three Strategies for Salvaging Epistemic Value in Deep Neural Network Modeling.Philippe Verreault-Julien - manuscript
    Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One paradoxical implication of that proposal is that epistemic value may be obtained from mere ignorance. For the less we know, then the more is epistemically possible. This chapter examines a particular class of problematic epistemically possible how-possibly explanations, viz. *epistemically opaque* how-possibly explanations. Those are how-possibly explanations justified by an epistemically opaque process. How could epistemically opaque how-possibly explanations have epistemic value if (...)
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  3. The Problem of Disjunctive Explanations.Brad Weslake - manuscript
    I present a problem for theories of explanation, concerning explanations involving disjunctive properties. The problem is particular acute for the explanatory non-fundamentalist, according to whom non-fundamental scientific explanations are sometimes superior to fundamental physical explanations. I criticise solutions to the problem due to Woodward, Strevens and Sober, and Lewis, and then defend a solution inspired by an account of non-fundamental laws recently defended by Callender and Cohen.
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  4. Beauty as a Guide to Truth: Aquinas, Fittingness, and Explanatory Virtues.Levi Durham - forthcoming - Proceedings and Addresses of the American Philosophical Association.
    Many scientists and philosophers of science think that beauty should play a role in theory selection. Physicists like Paul Dirac and Steven Weinberg explicitly claim that the ultimate explanations of the physical world must be beautiful. And philosophers of science like Peter Lipton say that we should expect the loveliest theory to also be the most likely. In this paper, I contend that these arguments from loveliness bear a striking similarity to Thomas Aquinas’ arguments from fittingness; both seem to presume (...)
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  5. Realism and the Value of Explanation.Samuel John Andrews - 2023 - Philosophical Quarterly 73 (4):1305–1314.
    Dasgupta poses a serious challenge to realism about natural properties. He argues that there is no acceptable explanation of why natural properties deserve the value realists assign to them and are consequently absent of value. In response, this paper defines and defends an alternative non-explanatory account of normativity compatible with realism. Unlike Lewis and Sider, who believe it is sufficient to defend realism solely on realist terms, I engage with the challenge on unfriendly grounds by revealing a tu quoque. Dasgupta (...)
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  6. What's the coincidence in debunking?Harjit Bhogal - 2022 - Philosophy and Phenomenological Research 107 (1):147-167.
    Many moral debunking arguments are driven by the idea that the correlation between our moral beliefs and the moral truths is a big coincidence, given a robustly realist conception of morality.One influential response is that the correlation is not a coincidence because there is a common explainer of our moral beliefs and the moral truths. For example, the reason that I believe that I should feed my child is because feeding my child helps them to survive, and natural selection instills (...)
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  7. Înțelegerea lumii cu ajutorul matematicii.Gabriel Târziu - 2022 - Iași, Romania: Editura Universităţii „Alexandru Ioan Cuza”.
    Această carte face parte dintr-un curent recent din filosofia analitică de preocupare cu rolul matematicii în știință și se vrea a fi o contribuție la discuția filosofică recentă despre valoarea explicativă a matematicii în știință și despre contribuția acesteia la înțelegerea naturii. Obiectivul principal al cărții este prezentarea unei teorii filosofice cu privire la felul în care matematica poate contribui la înțelegerea fenomenelor naturii fără a juca un rol explicativ în raport cu acestea.
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  8. Coherent Causal Control: A New Distinction within Causation.Marcel Weber - 2022 - European Journal for Philosophy of Science 12 (4):69.
    The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes (...)
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  9. String Theory, Non-Empirical Theory Assessment, and the Context of Pursuit.Frank Cabrera - 2021 - Synthese 198:3671–3699.
    In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...)
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  10. Du Châtelet on Sufficient Reason and Empirical Explanation.Aaron Wells - 2021 - Southern Journal of Philosophy 59 (4):629-655.
  11. Difference-making and deterministic chance.Harjit Bhogal - 2020 - Philosophical Studies 178 (7):2215-2235.
    Why do we value higher-level scientific explanations if, ultimately, the world is physical? An attractive answer is that physical explanations often cite facts that don’t make a difference to the event in question. I claim that to properly develop this view we need to commit to a type of deterministic chance. And in doing so, we see the theoretical utility of deterministic chance, giving us reason to accept a package of views including deterministic chance.
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  12. Explanatory Abstraction and the Goldilocks Problem: Interventionism Gets Things Just Right.Thomas Blanchard - 2020 - British Journal for the Philosophy of Science 71 (2):633-663.
    Theories of explanation need to account for a puzzling feature of our explanatory practices: the fact that we prefer explanations that are relatively abstract but only moderately so. Contra Franklin-Hall ([2016]), I argue that the interventionist account of explanation provides a natural and elegant explanation of this fact. By striking the right balance between specificity and generality, moderately abstract explanations optimally subserve what interventionists regard as the goal of explanation, namely identifying possible interventions that would have changed the explanandum.
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  13. Understanding, Truth, and Epistemic Goals.Kareem Khalifa - 2020 - Philosophy of Science 87 (5):944-956.
    Several argue that truth cannot be science’s sole epistemic goal, for it would fail to do justice to several scientific practices that advance understanding. I challenge these arguments, but only after making a small concession: science’s sole epistemic goal is not truth as such; rather, its goal is finding true answers to relevant questions. Using examples from the natural and social sciences, I then show that scientific understanding’s epistemically valuable features are either true answers to relevant questions or a means (...)
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  14. Coincidences and the Grain of Explanation.Harjit Bhogal - 2019 - Philosophy and Phenomenological Research 100 (3):677-694.
    I give an account of what makes an event a coincidence. -/- I start by critically discussing a couple of other approaches to the notion of coincidence -- particularly that of Lando (2017) -- before developing my own view. The central idea of my view is that the correct understanding of coincidences is closely related to our understanding of the correct 'level' or 'grain' of explanation. Coincidences have a kind of explanatory deficiency — if they did not have this deficiency (...)
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  15. The Diversity of Models as a Means to Better Explanations in Economics.Emrah Aydinonat - 2018 - Journal of Economic Methodology 25 (3):237-251.
    In Economics Rules, Dani Rodrik (2015) argues that what makes economics powerful despite the limitations of each and every model is its diversity of models. Rodrik suggests that the diversity of models in economics improves its explanatory capacities, but he does not fully explain how. I offer a clearer picture of how models relate to explanations of particular economic facts or events, and suggest that the diversity of models is a means to better economic explanations.
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  16. Evolutionary Debunking Arguments and Our Shared Hatred of Pain.Ben Bramble - 2017 - Journal of Ethics and Social Philosophy 12 (1):94-101.
    This article responds to an argument from Katarzyna de Ladari-Radek and Peter Singer in their article, "The Objectivity of Ethics and the Unity of Practical Reason.".
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  17. How to define levels of explanation and evaluate their indispensability.Christopher Clarke - 2017 - Synthese 194 (6).
    Some explanations in social science, psychology and biology belong to a higher level than other explanations. And higher explanations possess the virtue of abstracting away from the details of lower explanations, many philosophers argue. As a result, these higher explanations are irreplaceable. And this suggests that there are genuine higher laws or patterns involving social, psychological and biological states. I show that this ‘abstractness argument’ is really an argument schema, not a single argument. This is because the argument uses the (...)
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  18. Multi-Level Selection and the Explanatory Value of Mathematical Decompositions.Christopher Clarke - 2016 - British Journal for the Philosophy of Science 67 (4):1025-1055.
    Do multi-level selection explanations of the evolution of social traits deepen the understanding provided by single-level explanations? Central to the former is a mathematical theorem, the multi-level Price decomposition. I build a framework through which to understand the explanatory role of such non-empirical decompositions in scientific practice. Applying this general framework to the present case places two tasks on the agenda. The first task is to distinguish the various ways of suppressing within-collective variation in fitness, and moreover to evaluate their (...)
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  19. Explanatory Value and Probabilistic Reasoning: An Empirical Study.Matteo Colombo, Marie Postma & Jan Sprenger - 2016 - Proceedings of the Cognitive Science Society.
    The relation between probabilistic and explanatory reasoning is a classical topic in philosophy of science. Most philosophical analyses are concerned with the compatibility of Inference to the Best Explanation with probabilistic, Bayesian inference, and the impact of explanatory considerations on the assignment of subjective probabilities. This paper reverses the question and asks how causal and explanatory considerations are affected by probabilistic information. We investigate how probabilistic information determines the explanatory value of a hypothesis, and in which sense folk explanatory practice (...)
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  20. Theories of Properties and Ontological Theory-Choice: An Essay in Metaontology.Christopher Gibilisco - 2016 - Dissertation, University of Nebraska-Lincoln
    This dissertation argues that we have no good reason to accept any one theory of properties as correct. To show this, I present three possible bases for theory-choice in the properties debate: coherence, explanatory adequacy, and explanatory value. Then I argue that none of these bases resolve the underdetermination of our choice between theories of properties. First, I argue considerations about coherence cannot resolve the underdetermination, because no traditional theory of properties is obviously incoherent. Second, I argue considerations of explanatory (...)
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  21. Probability and the Explanatory Virtues: Figure 1.Clark Glymour - 2015 - British Journal for the Philosophy of Science 66 (3):591-604.
    Recent literature in philosophy of science has addressed purported notions of explanatory virtues—‘explanatory power’, ‘unification’, and ‘coherence’. In each case, a probabilistic relation between a theory and data is said to measure the power of an explanation, or degree of unification, or degree of coherence. This essay argues that the measures do not capture cases that are paradigms of scientific explanation, that the available psychological evidence indicates that the measures do not capture judgements of explanatory power, and, finally, that the (...)
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  22. A defense of objectivism about evidential support.Brian Hedden - 2015 - Canadian Journal of Philosophy 45 (5):716-743.
    Objectivism about evidential support is the thesis that facts about the degree to which a body of evidence supports a hypothesis are objective rather than depending on subjective factors like one’s own language or epistemic values. Objectivism about evidential support is key to defending a synchronic, time-slice-centric conception of epistemic rationality, on which what you ought to believe at a time depends only on what evidence you have at that time, and not on how you were at previous times. Here, (...)
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  23. EMU defended: reply to Newman.Kareem Khalifa - 2015 - European Journal for Philosophy of Science 5 (3):377-385.
    In his “EMU and Inference,” Mark Newman European Journal for Philosophy of Science, 4:55–74, 2014 provides several interesting challenges to my explanatory model of understanding :15–37, 2012). I offer three replies to Newman’s paper. First, Newman incorrectly attributes to EMU an overly restrictive view about the role of abilities in understanding. Second, his main argument against EMU rests on this incorrect attribution, and would still face difficulties even if this attribution were correct. Third, contrary to his stated ambitions, his own, (...)
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  24. Depth and Explanation in Mathematics.Marc Lange - 2015 - Philosophia Mathematica 23 (2):196-214.
    This paper argues that in at least some cases, one proof of a given theorem is deeper than another by virtue of supplying a deeper explanation of the theorem — that is, a deeper account of why the theorem holds. There are cases of scientific depth that also involve a common abstract structure explaining a similarity between two otherwise unrelated phenomena, making their similarity no coincidence and purchasing depth by answering why questions that separate, dissimilar explanations of the two phenomena (...)
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  25. Re-orienting discussions of scientific explanation: A functional perspective.Andrea I. Woody - 2015 - Studies in History and Philosophy of Science Part A 52 (C):79-87.
  26. A normative account of the need for explanation.Zanja Yudell & Wai-Hung Wong - 2015 - Synthese 192 (9):2863-2885.
    Although explanation is a central topic in the philosophy of science, there is an important issue concerning explanation that has not been discussed much, namely, why some phenomena need an explanation while some do not. In this paper we first explain why this is an important issue, and then discuss two accounts of the need for explanation that can be gathered from the literature. We argue that both accounts are inadequate. The main purpose of the paper is, however, to offer (...)
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  27. Statistical Mechanical Imperialism.Brad Weslake - 2014 - In Alastair Wilson (ed.), Chance and Temporal Asymmetry. Oxford: Oxford University Press. pp. 241-257.
    I argue against the claim, advanced by David Albert and Barry Loewer, that all non-fundamental laws can be derived from those required to underwrite the second law of thermodynamics.
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  28. Reasoning Without the Principle of Sufficient Reason.Shieva Kleinschmidt - 2013 - In Tyron Goldschmidt (ed.), The Philosophy of Existence: Why Is There Something Rather Than Nothing? Routledge. pp. 64-79.
    According to Principles of Sufficient Reason, every truth (in some relevant group) has an explanation. One of the most popular defenses of Principles of Sufficient Reason has been the presupposition of reason defense, which takes endorsement of the defended PSR to play a crucial role in our theory selection. According to recent presentations of this defense, our method of theory selection often depends on the assumption that, if a given proposition is true, then it has an explanation, and this will (...)
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  29. Description, Explanation, and Explanatory Depth in Developmental Biology.Christopher H. Pearson - 2013 - In Vassilios Karakostas & Dennis Dieks (eds.), Epsa11 Perspectives and Foundational Problems in Philosophy of Science. Springer. pp. 345--356.
  30. Values and Explanation.Marek Tomecek - 2013 - Organon F: Medzinárodný Časopis Pre Analytickú Filozofiu 20:196-205.
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  31. Proportionality, contrast and explanation.Brad Weslake - 2013 - Australasian Journal of Philosophy 91 (4):785-797.
    If counterfactual dependence is sufficient for causation and if omissions can be causes, then all events have many more causes than common sense tends to recognize. This problem is standardly addressed by appeal to pragmatics. However, Carolina Sartorio [2010] has recently raised what I shall argue is a more interesting problem concerning omissions for counterfactual theories of causation—more interesting because it demands a more subtle pragmatic solution. I discuss the relationship between the idea that causes are proportional to their effects, (...)
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  32. How Can Causal Explanations Explain?Jon Williamson - 2013 - Erkenntnis 78 (2):257-275.
    The mechanistic and causal accounts of explanation are often conflated to yield a ‘causal-mechanical’ account. This paper prizes them apart and asks: if the mechanistic account is correct, how can causal explanations be explanatory? The answer to this question varies according to how causality itself is understood. It is argued that difference-making, mechanistic, dualist and inferentialist accounts of causality all struggle to yield explanatory causal explanations, but that an epistemic account of causality is more promising in this regard.
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  33. A Second Look at the Logic of Explanatory Power (with Two Novel Representation Theorems).Vincenzo Crupi & Katya Tentori - 2012 - Philosophy of Science 79 (3):365-385.
    We discuss the probabilistic analysis of explanatory power and prove a representation theorem for posterior ratio measures recently advocated by Schupbach and Sprenger. We then prove a representation theorem for an alternative class of measures that rely on the notion of relative probability distance. We end up endorsing the latter, as relative distance measures share the properties of posterior ratio measures that are genuinely appealing, while overcoming a feature that we consider undesirable. They also yield a telling result concerning formal (...)
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  34. Abstraction and Depth in Scientific Explanation. [REVIEW]Marc Lange - 2012 - Philosophy and Phenomenological Research 84 (2):483-491.
  35. Scientific Explanation between Principle and Constructive Theories.Laura Felline - 2011 - Philosophy of Science 78 (5):989-1000.
    The aim of this paper is to analyse the role that the distinction between principle and constructive theories have in the question of the explanatory power of Special Relativity. We show how the distinction breaks down at the explanatory level. We assess Harvey Brown’s (2005) claim that, as a principle theory, Special Relativity lacks of explanatory power and criticize it, as, we argue, based upon an unrealistic picture of the kind of explanations provided by principle (and constructive) theories. Finally, we (...)
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  36. An Explication of the Use of Inference to the Best Explanation.Adam Grobler - 2011 - In Dennis Dieks, Wenceslao Gonzalo, Thomas Uebel, Stephan Hartmann & Marcel Weber (eds.), Explanation, Prediction, and Confirmation. Springer. pp. 83--91.
  37. Strevens. 2009. Depth. An account of scientific explanations. [REVIEW]Federica Russo - 2011 - Theoria : An International Journal for Theory, History and Fundations of Science 26 (2):261-263.
  38. Comparing Probabilistic Measures of Explanatory Power.Jonah N. Schupbach - 2011 - Philosophy of Science 78 (5):813-829.
    Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in (...)
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  39. A case study in explanatory power: John Snow’s conclusions about the pathology and transmission of cholera.Dana Tulodziecki - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (3):306-316.
    In the mid-1800s, there was much debate about the origin or 'exciting cause' of cholera. Despite much confusion surrounding the disease, the so-called miasma theory emerged as the prevalent account about cholera's cause. Going against this mainstream view, the British physician John Snow inferred several things about cholera's origin and pathology that no one else inferred. Without observing the vibrio cholerae, however,-data unavailable to Snow and his colleagues-, there was no way of settling the question of what exactly was causing (...)
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  40. Dalton’s Chemical Atoms versus Duhem’s Chemical Equivalents.Karen R. Zwier - 2011 - Philosophy of Science 78 (5):842-853.
    Paul Needham has claimed in several recent papers that Dalton’s chemical atomism was not explanatory. I respond to his criticism of Dalton by arguing that explanation admits of degrees and that under a view that allows for a spectrum of explanatory value, it is possible to see ample worth in Dalton’s atomistic explanations. Furthermore, I argue that even Duhem, who rejected atomism, acknowledged the explanatory worth of Dalton’s atomism.
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  41. Causal Modeling, Explanation and Severe Testing.Clark Glymour, Deborah G. Mayo & Aris Spanos - 2010 - In Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science. Cambridge University Press. pp. 331-375.
  42. Levels of explanation reconceived.Angela Potochnik - 2010 - Philosophy of Science 77 (1):59-72.
    A common argument against explanatory reductionism is that higher‐level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher‐level explanations are more general than their lower‐level alternatives or that higher‐level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different (...)
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  43. Explanatory independence and epistemic interdependence: A case study of the optimality approach.Angela Potochnik - 2010 - British Journal for the Philosophy of Science 61 (1):213-233.
    The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case (...)
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  44. Explanatory Depth.Brad Weslake - 2010 - Philosophy of Science 77 (2):273-294.
    I defend an account of explanatory depth according to which explanations in the non-fundamental sciences can be deeper than explanations in fundamental physics.
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  45. Under What Conditions Can Formal Models of Social Action Claim Explanatory Power?Nathalie Bulle - 2009 - International Studies in the Philosophy of Science 23 (1):47-64.
    This paper's purpose is to set forth the conditions of explanation in the domain of formal modelling of social action. Explanation is defined as an adequate account of the underlying factors bringing about a phenomenon. The modelling of a social phenomenon can claim explanatory value in this sense if the following two conditions are fulfilled. (1) The generative mechanisms involved translate the effects of real factors abstracted from their phenomenal context, not those of purely ideal ones. (2) The explanatory hypotheses, (...)
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  46. Reintroducing prediction to explanation.Heather E. Douglas - 2009 - Philosophy of Science 76 (4):444-463.
    Although prediction has been largely absent from discussions of explanation for the past 40 years, theories of explanation can gain much from a reintroduction. I review the history that divorced prediction from explanation, examine the proliferation of models of explanation that followed, and argue that accounts of explanation have been impoverished by the neglect of prediction. Instead of a revival of the symmetry thesis, I suggest that explanation should be understood as a cognitive tool that assists us in generating new (...)
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  47. Is self-explanation always better? the effects of adding self-explanation prompts to an english grammar tutor.Ruth Wylie, Kenneth R. Koedinger & Teruko Mitamura - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 1300--1305.
  48. The Illusion of Depth of Understanding in Science.Petri Ylikoski - 2009 - In Henk De Regt, Sabina Leonelli & Kai Eigner (eds.), Scientific Understanding: Philosophical Perspectives. University of Pittsburgh Press. pp. 100--119.
    In this chapter I will employ a well-known scientific research heuristic that studies how something works by focusing on circumstances in which it does not work. Rather than trying to describe what scientific understanding would ideally look like, I will try to learn something about it by observing mundane cases where understanding is partly illusory. My main thesis is that scientists are prone to the illusion of depth of understanding (IDU), and as a consequence they sometimes overestimate the detail, coherence, (...)
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  49. Explanatory inquiry and the need for explanation.Stephen R. Grimm - 2008 - British Journal for the Philosophy of Science 59 (3):481-497.
    Explanatory inquiry characteristically begins with a certain puzzlement about the world. But why do certain situations elicit our puzzlement while others leave us, in some epistemically relevant sense, cold? Moreover, what exactly is involved in the move from a state of puzzlement to a state where one's puzzlement is satisfied? In this paper I try to answer both of these questions. I also suggest ways in which our account of scientific rationality might benefit from having a better sense of the (...)
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  50. Abduction and inference to the Best Explanation.Valeriano Iranzo García - 2007 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 22 (3):339-346.
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