Results for 'Jon Phelan'

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  1.  77
    Who's afraid of Friedrich Nietzsche? Effective and ineffective criticisms: Phelan who's afraid of Friedrich Nietzsche?Jon Phelan - 2010 - Think 9 (26):109-118.
    When one finds a philosopher inspiring, it is all too easy to adopt an uncritical reading. This would be to treat the author as an exception. The hallmark of such arguments from reverence is that they often start with ‘As so-and-so said…’ and appear as the final statement on the matter. Friedrich Nietzsche is subject to such reverential treatment at the hand of undergraduate and A-Level devotees. I hope in the course of this brief survey to suggest some worthwhile criticisms (...)
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  2.  10
    Literature and Understanding: The Value of a Close Reading of Literary Texts.Jon Phelan - 2020 - Routledge.
    Literature and Understanding investigates the cognitive gain from literature by focussing on a reader's close analysis of a literary text. It examines the meaning of 'literature', outlines the most prominent positions in the literary cognitivism debate, explores the practice of close reading from a philosophical perspective, provides a fresh account of what we mean by 'understanding' and in so doing opens up a new area of research in the philosophy of literature. This book provides a different reply to the challenge (...)
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  3.  6
    Thomas Aquinas.Jon Phelan - 2000 - The Philosophers' Magazine 10:60-60.
  4.  14
    The Oedipus Plays of Sophocles.Jon Phelan - 2020 - Philosophical Quarterly 70 (280):655-657.
    The Oedipus Plays of Sophocles. Edited By Woodruff Paul.
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  5.  9
    A J Ayer.Jon Phelan - 2005 - The Philosophers' Magazine 30 (30):80-81.
    The desire for parsimony – to posit as few explanatory features as possible – has a rich philosophical history and is often given lots of weight in philosophical theory construction. But, as the psychologist Tania Lombrozo has demonstrated, our bias in favour of parsimony can lead us to adopt simple explanations even when it’s far more likely that a complicated explanation is correct.
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  6.  43
    "A. I. Richards": Can Artificial Intelligence Appreciate Poetry?Jon Phelan - 2021 - Philosophy and Literature 45 (1):71-87.
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  7.  3
    A J Ayer.Jon Phelan - 2005 - The Philosophers' Magazine 30:80-81.
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  8.  2
    Thomas Aquinas.Jon Phelan - 2000 - The Philosophers' Magazine 10:60-60.
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  9.  10
    Big question marks.Jack Furlong, Ion Giorgiou, Jaroslav Peregrin, Jon Phelan & Lawrence Phillips - 1999 - The Philosophers' Magazine 6:53-54.
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  10.  13
    Big question marks. [REVIEW]Jack Furlong, Ion Giorgiou, Jaroslav Peregrin, Jon Phelan & Lawrence Phillips - 1999 - The Philosophers' Magazine 6:53-54.
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  11.  20
    Literature and Understanding: The Value of a Close Reading of Literary Texts.Iris Vidmar Jovanović - 2023 - British Journal of Aesthetics 63 (3):445-448.
    Detailed, precise and ridden with excellent examples, Jon Phelan’s Literature and Understanding: The Value of a Close Reading of Literary Texts is an inviting a.
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  12.  15
    In Defence of Objective Bayesianism.Jon Williamson - 2010 - Oxford University Press.
    Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.
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  13.  27
    On the physical significance of the locality conditions in the bell arguments.Jon P. Jarrett - 1984 - Noûs 18 (4):569-589.
  14.  41
    Inquiry.Jon Barwise - 1986 - Philosophical Review 95 (3):429.
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  15.  14
    Bayesian Nets and Causality: Philosophical and Computational Foundations.Jon Williamson - 2004 - Oxford, England: Oxford University Press.
    Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
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  16.  12
    Why Frequentists and Bayesians Need Each Other.Jon Williamson - 2013 - Erkenntnis 78 (2):293-318.
    The orthodox view in statistics has it that frequentism and Bayesianism are diametrically opposed—two totally incompatible takes on the problem of statistical inference. This paper argues to the contrary that the two approaches are complementary and need to mesh if probabilistic reasoning is to be carried out correctly.
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  17.  3
    The feasibility and malleability of EBM+.Jon Williamson - 2021 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 36 (2):191-209.
    The EBM+ programme is an attempt to improve the way in which present-day evidence-based medicine (EBM) assesses causal claims: according to EBM+, mechanistic studies should be scrutinised alongside association studies. This paper addresses two worries about EBM+: (i) that it is not feasible in practice, and (ii) that it is too malleable, i.e., its results depend on subjective choices that need to be made in order to implement the procedure. Several responses to these two worries are considered and evaluated. The (...)
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  18.  12
    Countable additivity and subjective probability.Jon Williamson - 1999 - British Journal for the Philosophy of Science 50 (3):401-416.
    While there are several arguments on either side, it is far from clear as to whether or not countable additivity is an acceptable axiom of subjective probability. I focus here on de Finetti's central argument against countable additivity and provide a new Dutch book proof of the principle, To argue that if we accept the Dutch book foundations of subjective probability, countable additivity is an unavoidable constraint.
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  19.  29
    A beautiful supertask.Jon Perez Laraudogoitia - 1996 - Mind 105 (417):81-83.
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  20.  68
    Calibration for epistemic causality.Jon Williamson - 2021 - Erkenntnis 86 (4):941-960.
    The epistemic theory of causality is analogous to epistemic theories of probability. Most proponents of epistemic probability would argue that one's degrees of belief should be calibrated to chances, insofar as one has evidence of chances. The question arises as to whether causal beliefs should satisfy an analogous calibration norm. In this paper, I formulate a particular version of a norm requiring calibration to chances and argue that this norm is the most fundamental evidential norm for epistemic probability. I then (...)
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  21. Objective Bayesianism, Bayesian conditionalisation and voluntarism.Jon Williamson - 2011 - Synthese 178 (1):67-85.
    Objective Bayesianism has been criticised on the grounds that objective Bayesian updating, which on a finite outcome space appeals to the maximum entropy principle, differs from Bayesian conditionalisation. The main task of this paper is to show that this objection backfires: the difference between the two forms of updating reflects negatively on Bayesian conditionalisation rather than on objective Bayesian updating. The paper also reviews some existing criticisms and justifications of conditionalisation, arguing in particular that the diachronic Dutch book justification fails (...)
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  22.  26
    The feasibility and malleability of EBM+.Jon Williamson - 2021 - Theoria. An International Journal for Theory, History and Foundations of Science 36 (2):191-209.
    The EBM+ programme is an attempt to improve the way in which present-day evidence-based medicine (EBM) assesses causal claims: according to EBM+, mechanistic studies should be scrutinised alongside association studies. This paper addresses two worries about EBM+: (i) that it is not feasible in practice, and (ii) that it is too malleable, i.e., its results depend on subjective choices that need to be made in order to implement the procedure. Several responses to these two worries are considered and evaluated. The (...)
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  23.  16
    Distinguish to Unite; or The Degrees of Knowledge.Jacques Maritain & G. P. Phelan - 1961 - Philosophy and Phenomenological Research 21 (4):581-582.
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  24.  25
    Stationary logic.Jon Barwise - 1978 - Annals of Mathematical Logic 13 (2):171.
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  25.  10
    Coronavirus, the great toilet paper panic and civilisation.Jon Stratton - 2021 - Thesis Eleven 165 (1):145-168.
    Panic buying of toilet rolls in Australia began in early March 2020. This was related to the realisation that the novel coronavirus was spreading across the country. To the general population the impact of the virus was unknown. Gradually the federal government started closing the country’s borders. The panic buying of toilet rolls was not unique to Australia. It happened across all societies that used toilet paper rather than water to clean after defecation and urination. However, research suggests that the (...)
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  26.  16
    Classical particle dynamics, indeterminism and a supertask.Jon Pérez Laraudogoitia - 1997 - British Journal for the Philosophy of Science 48 (1):49-54.
    In this paper a model in particle dynamics of a well-known supertask is constructed. As a consequence, a new and simple result about the failure of determinism of classical particle dynamics can be proved which is related to the non-existence of boundary conditions at spatial infinity. This result is much more accessible to the non-technical reader than similar ones in the scientific literature.
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  27.  9
    Egoistic and ethical orientations of university students toward work-related decisions.Jon M. Shepard & Linda S. Hartenian - 1991 - Journal of Business Ethics 10 (4):303 - 310.
    An onslaught of ethically questionable actions by top government, business, and religious leaders during the 1980s has brought the issue of ethics in decision making to the forefront of public consciousness. This study examines the ethical orientation of university students in four decision-making situations. The dependent variable — ethical orientation toward work-related decisions — is measured through student responses to questions following four work-related vignettes. Possible responses to each vignette are structured to permit categorization of respondents into two broad orientations: (...)
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  28.  13
    Mechanistic theories of causality.Jon Williamson - unknown
    After introducing a range of mechanistic theories of causality and some of the problems they face, I argue that while there is a decisive case against a purely mechanistic analysis, a viable theory of causality must incorporate mechanisms as an ingredient. I describe one way of providing an analysis of causality which reaps the rewards of the mechanistic approach without succumbing to its pitfalls.
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  29.  15
    A Bayesian Account of Establishing.Jon Williamson - 2022 - British Journal for the Philosophy of Science 73 (4):903-925.
    When a proposition is established, it can be taken as evidence for other propositions. Can the Bayesian theory of rational belief and action provide an account of establishing? I argue that it can, but only if the Bayesian is willing to endorse objective constraints on both probabilities and utilities, and willing to deny that it is rationally permissible to defer wholesale to expert opinion. I develop a new account of deference that accommodates this latter requirement.
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  30.  30
    Scientific Methodologies in Medieval Islam.Jon McGinnis - 2003 - Journal of the History of Philosophy 41 (3):307-327.
    : The present study considers Ibn Sînâ's (Lat. Avicenna) account of induction (istiqra') and experimentation (tajriba). For Ibn Sînâ induction purportedly provided the absolute, necessary and certain first principles of a science. Ibn Sînâ criticized induction, arguing that it can neither guarantee the necessity nor provide the primitiveness required of first principles. In it place, Ibn Sînâ developed a theory of experimentation, which avoids the pitfalls of induction by not providing absolute, but conditional, necessary and certain first principles. The theory (...)
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  31. From Bayesian epistemology to inductive logic.Jon Williamson - 2013 - Journal of Applied Logic 11 (4):468-486.
    Inductive logic admits a variety of semantics (Haenni et al., 2011, Part 1). This paper develops semantics based on the norms of Bayesian epistemology (Williamson, 2010, Chapter 7). §1 introduces the semantics and then, in §2, the paper explores methods for drawing inferences in the resulting logic and compares the methods of this paper with the methods of Barnett and Paris (2008). §3 then evaluates this Bayesian inductive logic in the light of four traditional critiques of inductive logic, arguing (i) (...)
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  32.  5
    Gods Inside.Michael R. Rose & John P. Phelan - 2009-09-10 - In Russell Blackford & Udo Schüklenk (eds.), 50 Voices of Disbelief. Wiley‐Blackwell. pp. 279–287.
    This chapter contains sections titled: The Gods Problem The Evolution of Free Will Is Our Starting Point So Gods Evolved Gods Are Hidden Inside Us The Godless Must Walk the Earth Gods Must Be Made Manifest Religion Mediates Between Free Will and Gods Living in Harmony With Our Actual Gods.
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  33.  51
    Justifying the Principle of Indifference.Jon Williamson - forthcoming - European Journal for the Philosophy of Science.
    This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to minimise worst-case expected inaccuracy. The question arises as to which interpretation is preferable. I show that the epistemic argument contradicts Evidentialism and suggest that the relative plausibility (...)
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  34.  27
    Conditional beliefs aren’t conditional probabilities.Jon Williamson - unknown
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  35.  9
    An objective Bayesian account of confirmation.Jon Williamson - 2011 - In Dennis Dieks, Wenceslao Gonzalo, Thomas Uebel, Stephan Hartmann & Marcel Weber (eds.), Explanation, Prediction, and Confirmation. Springer. pp. 53--81.
  36.  88
    Objective Bayesianism with predicate languages.Jon Williamson - 2008 - Synthese 163 (3):341-356.
    Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objective Bayesianism to first-order logical languages. It is argued that the objective Bayesian should choose a probability function, from all those that satisfy constraints imposed by background knowledge, that is closest to a particular frequency-induced probability function which generalises the λ = 0 function of Carnap’s continuum of inductive methods.
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  37.  15
    The evolving landscape of imprinted genes in humans and mice: Conflict among alleles, genes, tissues, and kin.Jon F. Wilkins, Francisco Úbeda & Jeremy Van Cleve - 2016 - Bioessays 38 (5):482-489.
    Three recent genome‐wide studies in mice and humans have produced the most definitive map to date of genomic imprinting (gene expression that depends on parental origin) by incorporating multiple tissue types and developmental stages. Here, we explore the results of these studies in light of the kinship theory of genomic imprinting, which predicts that imprinting evolves due to differential genetic relatedness between maternal and paternal relatives. The studies produce a list of imprinted genes with around 120–180 in mice and ∼100 (...)
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  38.  7
    Hanf Numbers for Fragments of L ∞ω.Jon Barwise & Kenneth Kunen - 1984 - Journal of Symbolic Logic 49 (1):315-315.
  39.  14
    Nothing happens here: Songs about Perth.Jon Stratton & Adam Trainer - 2016 - Thesis Eleven 135 (1):34-50.
    This essay examines Perth as portrayed through the lyrics of popular songs written by people who grew up in the city. These lyrics tend to reproduce the dominant myths about the city: that it is isolated, that it is self-satisfied, that little happens there. Perth became the focus of song lyrics during the late 1970s time of punk with titles such as ‘Arsehole of the Universe’ and ‘Perth Is a Culture Shock’. Even the Eurogliders’ 1984 hit, ‘Heaven Must Be There’, (...)
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  40.  8
    Where do we stand on maximal entropy?Jon Williamson - unknown
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  41.  28
    Evidential Pluralism and Explainable AI.Jon Williamson - unknown
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  42. Recursive Bayesian Nets for Prediction, Explanation and Control in Cancer Science.Jon Williamson - unknown
    this paper we argue that the formalism can also be applied to modelling the hierarchical structure of physical mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations are vital for prediction, explanation and control respectively, a recursive Bayesian net can be applied to all these tasks. We show how a Recursive Bayesian Net can be used to model mechanisms in cancer science. (...)
     
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  43.  7
    Probabilistic logic.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 57.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  44.  6
    Probability.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 80.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  45.  8
    Richard Jeffrey.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 129.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  46. Clouded judgments? The role of virtual weather in word valence evaluations.Francisco Rocabado & Jon Andoni Duñabeitia - forthcoming - Cognition and Emotion.
    Exploring the dynamic interface of environmental psychology and psycholinguistics, this investigation delves into how simulated weather conditions – sunny versus rainy – affect emotional perceptions of linguistic stimuli within a Virtual Reality (VR) framework. Participants assessed words’ emotional valence being exposed to these distinct environmental simulations. Contrary to expectations, we found that while rainy conditions modestly prolonged response times, they did not significantly alter the emotional valence attributed to words. Our study shows that weather can affect emotional cognition, but intrinsic (...)
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  47.  9
    Aristotle, eubulides and the sorites.Jon Moline - 1969 - Mind 78 (311):393-407.
  48.  10
    Infinitary Logic and Admissible Sets.Jon Barwise - 1971 - Journal of Symbolic Logic 36 (1):156-157.
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  49. Why look at causality in the sciences? A manifesto.Jon Williamson - unknown
    This introduction to the volume begins with a manifesto that puts forward two theses: first, that the sciences are the best place to turn in order to understand causality; second, that scientifically-informed philosophical investigation can bring something to the sciences too. Next, the chapter goes through the various parts of the volume, drawing out relevant background and themes of the chapters in those parts. Finally, the chapter discusses the progeny of the papers and identifies some next steps for research into (...)
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  50.  22
    Unlimited associative learning and consciousness: further support and some caveats about a link to stress.Jon Mallatt - 2021 - Biology and Philosophy 36 (2):1-6.
    Birch, Ginsburg, and Jablonka, in an article in this issue of Biology and Philosophy, provided a much-needed condensation of their well-reasoned theory of Unlimited Associative Learning. This theory compellingly identifies the conscious animals and the time when the evolutionary transition to consciousness was completed. The authors convincingly explained their use of UAL as a “transition marker,” identified two more features by which UAL can be recognized, showed how UAL’s learning features relate to consciousness, and how investigating consciousness is analogous to (...)
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