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William Peden
Lingnan University
  1.  41
    Explanatory Reasoning in the Material Theory of Induction.William Peden - forthcoming - Metascience:1-7.
    In his recent book, John Norton has created a theory of inference to the best explanation, within the context of his "material theory of induction". I apply it to the problem of scientific explanations that are false: if we want the theories in our explanations to be true, then why do historians and scientists often say that false theories explained phenomena? I also defend Norton's theory against some possible objections.
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  2. Probability and Arguments: Keynes’s Legacy.William Peden - 2021 - Cambridge Journal of Economics 45 (5):933–950.
    John Maynard Keynes’s A Treatise on Probability is the seminal text for the logical interpretation of probability. According to his analysis, probabilities are evidential relations between a hypothesis and some evidence, just like the relations of deductive logic. While some philosophers had suggested similar ideas prior to Keynes, it was not until his Treatise that the logical interpretation of probability was advocated in a clear, systematic and rigorous way. I trace Keynes’s influence in the philosophy of probability through a heterogeneous (...)
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  3.  40
    Prisoners of Prophecy: Freedom and Foreknowledge in the Dune Series.William Peden - forthcoming - In Dune and Philosophy: Mind, Monads and Muad’Dib.
    In the Dune Series, Frank Herbert explores the idea of prophecy. To be prescient seems to be empowered, but is this true? Can knowing the future trap us? Does knowledge of the future constrict our sense of being free agents? -/- These questions have also been explored by decision theorists and philosophers of action. Thus, this chapter provides an introduction to these fields aimed at fans of the Dune series. -/- I explain the Prisoner's Dilemma and how foreknowledge can trap (...)
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  4. Statistical Significance Testing in Economics.William Peden & Jan Sprenger - 2021 - In Conrad Heilmann & Julian Reiss (eds.), The Routledge Handbook of the Philosophy of Economics.
    The origins of testing scientific models with statistical techniques go back to 18th century mathematics. However, the modern theory of statistical testing was primarily developed through the work of Sir R.A. Fisher, Jerzy Neyman, and Egon Pearson in the inter-war period. Some of Fisher's papers on testing were published in economics journals (Fisher, 1923, 1935) and exerted a notable influence on the discipline. The development of econometrics and the rise of quantitative economic models in the mid-20th century made statistical significance (...)
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  5.  27
    Incentives for Research Effort: An Evolutionary Model of Publication Markets with Double-Blind and Open Review.Mantas Radzvilas, Francesco De Pretis, William Peden, Daniele Tortoli & Barbara Osimani - forthcoming - Computational Economics:1-44.
    Contemporary debates about scientific institutions and practice feature many proposed reforms. Most of these require increased efforts from scientists. But how do scientists’ incentives for effort interact? How can scientific institutions encourage scientists to invest effort in research? We explore these questions using a game-theoretic model of publication markets. We employ a base game between authors and reviewers, before assessing some of its tendencies by means of analysis and simulations. We compare how the effort expenditures of these groups interact in (...)
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  6. Evidentialism, Inertia, and Imprecise Probability.William Peden - forthcoming - The British Journal for the Philosophy of Science:1-23.
    Evidentialists say that a necessary condition of sound epistemic reasoning is that our beliefs reflect only our evidence. This thesis arguably conflicts with standard Bayesianism, due to the importance of prior probabilities in the latter. Some evidentialists have responded by modelling belief-states using imprecise probabilities (Joyce 2005). However, Roger White (2010) and Aron Vallinder (2018) argue that this Imprecise Bayesianism is incompatible with evidentialism due to “inertia”, where Imprecise Bayesian agents become stuck in a state of ambivalence towards hypotheses. Additionally, (...)
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  7.  94
    Does the Dome Defeat the Material Theory of Induction?William Peden - forthcoming - Erkenntnis:1-20.
    According to John D. Norton's Material Theory of Induction, all inductive inferences are justified by local facts, rather than their formal features or some grand principles of nature's uniformity. Recently, Richard Dawid (2015) has offered a challenge to this theory: in an adaptation of Norton's own celebrated "Dome" thought experiment, it seems that there are certain inductions that are intuitively reasonable, but which do not have any local facts that could serve to justify them in accordance with Norton's requirements. Dawid's (...)
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  8. Imprecise Probability and the Measurement of Keynes's "Weight of Arguments".William Peden - 2018 - IfCoLog Journal of Logics and Their Applications 5 (4):677-708.
    Many philosophers argue that Keynes’s concept of the “weight of arguments” is an important aspect of argument appraisal. The weight of an argument is the quantity of relevant evidence cited in the premises. However, this dimension of argumentation does not have a received method for formalisation. Kyburg has suggested a measure of weight that uses the degree of imprecision in his system of “Evidential Probability” to quantify weight. I develop and defend this approach to measuring weight. I illustrate the usefulness (...)
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  9.  41
    Report on "Bayes By the Sea".William Peden - 2019 - The Reasoner 13 (10):3-4.
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