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  1. Rethinking objectivity: Nozick's neglected third option.Alison Wylie - 2000 - International Studies in the Philosophy of Science 14 (1):5 – 9.
  • Resolving the Raven Paradox: Simple Random Sampling, Stratified Random Sampling, and Inference to Best Explanation.Barry Ward - 2022 - Philosophy of Science 89 (2):360-377.
    Simple random sampling resolutions of the raven paradox relevantly diverge from scientific practice. We develop a stratified random sampling model, yielding a better fit and apparently rehabilitating simple random sampling as a legitimate idealization. However, neither accommodates a second concern, the objection from potential bias. We develop a third model that crucially invokes causal considerations, yielding a novel resolution that handles both concerns. This approach resembles Inference to the Best Explanation (IBE) and relates the generalization’s confirmation to confirmation of an (...)
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  • Hempel's Raven paradox: A lacuna in the standard bayesian solution.Peter B. M. Vranas - 2004 - British Journal for the Philosophy of Science 55 (3):545-560.
    According to Hempel's paradox, evidence (E) that an object is a nonblack nonraven confirms the hypothesis (H) that every raven is black. According to the standard Bayesian solution, E does confirm H but only to a minute degree. This solution relies on the almost never explicitly defended assumption that the probability of H should not be affected by evidence that an object is nonblack. I argue that this assumption is implausible, and I propose a way out for Bayesians. Introduction Hempel's (...)
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  • Missing systems and the face value practice.Martin Thomson-Jones - 2010 - Synthese 172 (2):283-299.
    Call a bit of scientific discourse a description of a missing system when (i) it has the surface appearance of an accurate description of an actual, concrete system (or kind of system) from the domain of inquiry, but (ii) there are no actual, concrete systems in the world around us fitting the description it contains, and (iii) that fact is recognised from the outset by competent practitioners of the scientific discipline in question. Scientific textbooks, classroom lectures, and journal articles abound (...)
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  • Inscriptionalism and intensionality.David Parsons - 2013 - Philosophia 41 (2):567-585.
    Intensional contexts are typically characterised by an apparent failure of either (A) the principle of the inter-substitution of co-referring terms salva veritate, or (B) existential generalisation. The difficulties which are seen to occur do so in contexts involving either modality or the propositional attitudes. In this paper attempts are made to determine whether or not Scheffler’s inscriptional analysis can provide a viable means of accounting for the problems which are thought to occur in intensional contexts. Somewhat unexpectedly, little effort has (...)
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  • Inductive systematization: Definition and a critical survey.Ilkka Niiniluoto - 1972 - Synthese 25 (1-2):25 - 81.
    In 1958, to refute the argument known as the theoretician's dilemma, Hempel suggested that theoretical terms might be logically indispensable for inductive systematization of observational statements. This thesis, in some form or another, has later been supported by Scheffler, Lehrer, and Tuomela, and opposed by Bohnert, Hooker, Stegmüller, and Cornman. In this paper, a critical survey of this discussion is given. Several different putative definitions of the crucial notion inductive systematization achieved by a theory are discussed by reference to the (...)
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  • An agent-based conception of models and scientific representation.Ronald N. Giere - 2010 - Synthese 172 (2):269–281.
    I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of models. (...)
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  • The paradox of confirmation.Branden Fitelson - 2006 - Philosophy Compass 1 (1):95–113.
    Hempel first introduced the paradox of confirmation in (Hempel 1937). Since then, a very extensive literature on the paradox has evolved (Vranas 2004). Much of this literature can be seen as responding to Hempel’s subsequent discussions and analyses of the paradox in (Hempel 1945). Recently, it was noted that Hempel’s intuitive (and plausible) resolution of the paradox was inconsistent with his official theory of confirmation (Fitelson & Hawthorne 2006). In this article, we will try to explain how this inconsistency affects (...)
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  • Progressive and degenerative journals: on the growth and appraisal of knowledge in scholarly publishing.Daniel J. Dunleavy - 2022 - European Journal for Philosophy of Science 12 (4):1-27.
    Despite continued attention, finding adequate criteria for distinguishing “good” from “bad” scholarly journals remains an elusive goal. In this essay, I propose a solution informed by the work of Imre Lakatos and his methodology of scientific research programmes (MSRP). I begin by reviewing several notable attempts at appraising journal quality – focusing primarily on the impact factor and development of journal blacklists and whitelists. In doing so, I note their limitations and link their overarching goals to those found within the (...)
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  • A Comparative Treatment of the Paradox of Confirmation.Ram-Prasad Chakravarthi - 2002 - Journal of Indian Philosophy 30 (4):339-358.
  • Mauricio Suárez (ed.): Fictions in Science. Philosophical Essays on Modeling and Idealization. [REVIEW]Jordi Cat - 2012 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 43 (1):187-194.
  • Reconstructing Arguments: Formalization and Reflective Equilibrium.Georg Brun - 2014 - History of Philosophy & Logical Analysis 17 (1):94-129.
    Traditional logical reconstruction of arguments aims at assessing the validity of ordinary language arguments. It involves several tasks: extracting argumentations from texts, breaking up complex argumentations into individual arguments, framing arguments in standard form, as well as formalizing arguments and showing their validity with the help of a logical formalism. These tasks are guided by a multitude of partly antagonistic goals, they interact in various feedback loops, and they are intertwined with the development of theories of valid inference and adequate (...)
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  • Relevance and Verification.Ben Blumson - 2021 - Philosophical Quarterly 71 (3):457-480.
    A. J. Ayer’s empiricist criterion of meaning was supposed to have sorted all statements into nonsense on the one hand, and tautologies or genuinely factual statements on the other. Unfortunately for Ayer, it follows from classical logic that his criterion is trivial—it classifies all statements as either tautologies or genuinely factual, but none as nonsense. However, in this paper, I argue that Ayer’s criterion of meaning can be defended from classical proofs of its triviality by the adoption of a relevant (...)
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  • Ontologias para a Modelagem Multiagente de Sistemas Complexos em Ciências Cognitivas.Leonardo Lana de Carvalho, Franck Varenne & Elayne de Moura Bragra - 2014 - Ciências and Cognição 19 (1):58-75.
    Cognitive sciences as an interdisciplinary field, involving scientific disciplines (such as computer science, linguistics, psychology, neuroscience, economics, etc.), philosophical disciplines (philosophy of language, philosophy of mind, analytic philosophy, etc.) and engineering (notably knowledge engineering), have a vast theoretical and practical content, some even conflicting. In this interdisciplinary context and on computational modeling, ontologies play a crucial role in communication between disciplines and also in a process of innovation of theories, models and experiments in cognitive sciences. We propose a model for (...)
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