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  1. Logical reasoning and domain specificity: A critique of the social exchange theory of reasoning.Paul Sheldon Davies, James H. Fetzer & Thomas R. Foster - 1995 - Biology and Philosophy 10 (1):1-37.
    The social exchange theory of reasoning, which is championed by Leda Cosmides and John Tooby, falls under the general rubric “evolutionary psychology” and asserts that human reasoning is governed by content-dependent, domain-specific, evolutionarily-derived algorithms. According to Cosmides and Tooby, the presumptive existence of what they call “cheater-detection” algorithms disconfirms the claim that we reason via general-purpose mechanisms or via inductively acquired principles. We contend that the Cosmides/Tooby arguments in favor of domain-specific algorithms or evolutionarily-derived mechanisms fail and that the notion (...)
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  • Probability in GRW theory.Roman Frigg & Carl Hoefer - 2007 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 38 (2):371-389.
    GRW Theory postulates a stochastic mechanism assuring that every so often the wave function of a quantum system is `hit', which leaves it in a localised state. How are we to interpret the probabilities built into this mechanism? GRW theory is a firmly realist proposal and it is therefore clear that these probabilities are objective probabilities (i.e. chances). A discussion of the major theories of chance leads us to the conclusion that GRW probabilities can be understood only as either single (...)
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  • The causal and unification approaches to explanation unified—causally.Michael Strevens - 2004 - Noûs 38 (1):154–176.
    The two major modern accounts of explanation are the causal and unification accounts. My aim in this paper is to provide a kind of unification of the causal and the unification accounts, by using the central technical apparatus of the unification account to solve a central problem faced by the causal account, namely, the problem of determining which parts of a causal network are explanatorily relevant to the occurrence of an explanandum. The end product of my investigation is a causal (...)
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  • Why are there no objective values?Gebhard Geiger - 1995 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 26 (1):35-62.
    Using the mathematical frameworks of economic preference ranking, subjective probability, and rational learning through empirical evidence, the epistemological implications of teleological ethical intuitionism are pointed out to the extent to which the latter is based on cognitivist and objectivist concepts of value. The notions of objective value and objective norm are critically analysed with reference to epistemological criteria of intersubjectively shared valuative experience. It is concluded that one cannot meaningfully postulate general material theories of morality that could be tested, confirmed (...)
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  • General causation.David Sapire - 1991 - Synthese 86 (3):321 - 347.
    This paper outlines a general theory of efficient causation, a theory that deals in a unified way with traditional or deterministic, indeterministic, probabilistic, and other causal concepts. Theorists like Lewis, Salmon, and Suppes have attempted to broaden our causal perspective by reductively analysing causal notions in other terms. By contrast, the present theory rests in the first place on a non-reductive analysis of traditional causal concepts — into formal or structural components, on the one hand, and a physical or metaphysical (...)
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  • Evolution and atheism: Has Griffin reconciled science and religion?James H. Fetzer - 2011 - Synthese 178 (2):381 - 396.
    The distinguished theologian, David Ray Griffin, has advanced a set of thirteen theses intended to characterize (what he calls) "Neo-Darwinism" and which he contrasts with "Intelligent Design". Griffin maintains that Neo-Darwinism is "atheistic" in forgoing a creator but suggests that, by adopting a more modest scientific naturalism and embracing a more naturalistic theology, it is possible to find "a third way" that reconciles religion and science. The considerations adduced here suggest that Griffin has promised more than he can deliver. On (...)
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  • Did Pearson reject the Neyman-Pearson philosophy of statistics?Deborah G. Mayo - 1992 - Synthese 90 (2):233 - 262.
    I document some of the main evidence showing that E. S. Pearson rejected the key features of the behavioral-decision philosophy that became associated with the Neyman-Pearson Theory of statistics (NPT). I argue that NPT principles arose not out of behavioral aims, where the concern is solely with behaving correctly sufficiently often in some long run, but out of the epistemological aim of learning about causes of experimental results (e.g., distinguishing genuine from spurious effects). The view Pearson did hold gives a (...)
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  • Behavioristic, evidentialist, and learning models of statistical testing.Deborah G. Mayo - 1985 - Philosophy of Science 52 (4):493-516.
    While orthodox (Neyman-Pearson) statistical tests enjoy widespread use in science, the philosophical controversy over their appropriateness for obtaining scientific knowledge remains unresolved. I shall suggest an explanation and a resolution of this controversy. The source of the controversy, I argue, is that orthodox tests are typically interpreted as rules for making optimal decisions as to how to behave--where optimality is measured by the frequency of errors the test would commit in a long series of trials. Most philosophers of statistics, however, (...)
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  • Ontological aspects of information modeling.Robert L. Ashenhurst - 1996 - Minds and Machines 6 (3):287-394.
    Information modeling (also known as conceptual modeling or semantic data modeling) may be characterized as the formulation of a model in which information aspects of objective and subjective reality are presented (the application), independent of datasets and processes by which they may be realized (the system).A methodology for information modeling should incorporate a number of concepts which have appeared in the literature, but should also be formulated in terms of constructs which are understandable to and expressible by the system user (...)
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  • A theory of objective chance.John F. Phillips - 2005 - Pacific Philosophical Quarterly 86 (2):267–283.
    Objective probability, or objective chance, is the probability of some event occurring in the future independent of what anyone thinks. This paper presents and defends a theory of objective chance. I develop an informal analysis of objective chance, taking the common sense picture underlying our talk about the likelihood of future events as our starting point. A formal semantics is introduced, and I argue that the theory presented satisfies certain criteria of adequacy for a theory of probability.
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