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  1. Joseph F. Hanna (2004). Contra Ladyman: What Really is Right with Constructive Empiricism. British Journal for the Philosophy of Science 55 (4):767-777.
    there be an objective modal distinction between the observable and the unobservable.’ My intent is to counter Ladyman's claim that the irreducibly modal character of empirical adequacy is something that is ‘really wrong with constructive empiricism’. I argue that disposition concepts refer to non-modal properties of types rather than to modal properties of tokens of those types. Solubility, for example, is an ‘occurrent’, though unobservable, property of a type of substance (involving the structure of associated atoms); and observability is, similarly, (...)
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  2. Joseph F. Hanna (2004). The Scope and Limits of Scientific Objectivity. Philosophy of Science 71 (3):339-361.
    The aim of this paper is twofold: first to sketch a framework for classifying a wide range of conceptions of scientific objectivity and second to present and defend a conception of scientific objectivity that fills a neglected niche in the resulting hierarchy of viewpoints. Roughly speaking, the proposed ideal of scientific objectivity is effectiveness in the informal but technical sense of an effective method. Science progresses when "higher levels of communicative discourse" are reached by transforming subjective judgments regarding the generation (...)
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  3. Charles R. Twardy, Kevin B. Korb, Ole Rogeberg, Cristina Bicchieri, John Duffy, Gil Tolle, P. D. Magnus, Craig Callender, Joseph F. Hanna & Paul Skokowski (2004). 1. A Criterion of Probabilistic Causation A Criterion of Probabilistic Causation (Pp. 241-262). Philosophy of Science 71 (3).
     
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  4. Joseph F. Hanna (1986). Objective Homogeneity Relativized. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:422 - 431.
    In his recent book Scientific Explanation and the Causal Structure of the World Wesley Salmon provides a detailed explanation of objective homogeneity, a concept which is central to his S-R model of explanation. 1 propose a modification of Salmon's definition which both simplifies and (in minor ways) corrects it, while at the same time generalizes it by including an important temporal factor that is missing from the original. I argue that if the world is irreducibly stochastic, then objective probabilities (determined (...)
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  5. Joseph F. Hanna (1986). Scientific Explanation and the Causal Structure of the World. Review of Metaphysics 39 (3):582-585.
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  6. Joseph F. Hanna (1984). On the Empirical Adequacy of Composite Statistical Hypotheses. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1984:73 - 80.
    According to van Fraassen's constructive empiricism, the epistemological aim of scientific theories is "to save the phenomena". Theories which achieve this aim are said to be empirically adequate. In an earlier paper a likelihood analysis of the empirical adequacy of simple statistical hypotheses was given. The present paper extends that likelihood analysis of empirical adequacy to composite statistical hypotheses. It is argued that for composite hypotheses the notion of likelihood is ambiguous. This ambiguity leads to a distinction between (...)
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  7. Joseph F. Hanna (1983). Empirical Adequacy. Philosophy of Science 50 (1):1-34.
    In his book, The Scientific Image, Bas van Fraassen argues for an anti-realist view of science according to which the sole epistemological aim of science is to "save the phenomena". As originally conceived, his constructive empiricism is strongly extensional, but in his account of the empirical adequacy of probabilistic theories, van Fraassen reluctantly abandons this extensional position, arguing that modal (intensional) notions are unavoidable in interpreting probability. I argue in this paper that van Fraassen has not presented the strongest possible (...)
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  8. Joseph F. Hanna (1982). Probabilistic Explanation and Probabilistic Causality. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:181 - 193.
    This paper argues that if the world is irreducibly stochastic, then both Salmon's S-R model of explanation and Fetzer's C-R model of explanation have the following undesirable consequence: the objective probability (associated with the model's relevance condition) of any actual macro-event is either undefined or else, if defined, it equals one--so that the event is not even a candidate for a probabilistic explanation. This result follows from the temporal ambiguity of ontic probability in an irreducibly stochastic world. It is argued (...)
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  9. Joseph F. Hanna (1981). Single Case Propensities and the Explanation of Particular Events. Synthese 48 (3):409 - 436.
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  10. Joseph F. Hanna (1978). On Transmitted Information as a Measure of Explanatory Power. Philosophy of Science 45 (4):531-562.
    This paper contrasts two information-theoretic approaches to statistical explanation: namely, (1) an analysis, which originated in my earlier research on problems of testing stochastic models of learning, based on an entropy-like measure of expected transmitted-information (and here referred to as the Expected-Information Model), and (2) the analysis, which was proposed by James Greeno (and which is closely related to Wesley Salmon's Statistical Relevance Model), based on the information-transmitted-by-a-system. The substantial differences between these analyses can be traced to the following basic (...)
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  11. Joseph F. Hanna (1969). Explanation, Prediction, Description, and Information Theory. Synthese 20 (3):308 - 334.
    The distinction between explanation and prediction has received much attention in recent literature, but the equally important distinction between explanation and description (or between prediction and description) remains blurred. This latter distinction is particularly important in the social sciences, where probabilistic models (or theories) often play dual roles as explanatory and descriptive devices. The distinction between explanation (or prediction) and description is explicated in the present paper in terms of information theory. The explanatory (or predictive) power of a probabilistic model (...)
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  12. Joseph F. Hanna (1968). An Explication of 'Explication'. Philosophy of Science 35 (1):28-44.
    It is generally agreed that the method of explication consists in replacing a vague, presystematic notion (the explicandum) with a precise notion (the explicatum) formulated in a systematic context. However, Carnap and others who have used this and related terms appear to hold inconsistent views as to what constitutes an adequate explication. The central feature of the present explication of 'explication' is the correspondence condition: permitting the explicandum to deviate from some established "ordinary-language" conventions but, at the same time, requiring (...)
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  13. Joseph F. Hanna (1966). A New Approach to the Formulation and Testing of Learning Models. Synthese 16 (3-4):344 - 380.
    It is argued that current attempts to model human learning behavior commonly fail on one of two counts: either the model assumptions are artificially restricted so as to permit the application of mathematical techniques in deriving their consequences, or else the required complex assumptions are imbedded in computer programs whose technical details obscure the theoretical content of the model. The first failing is characteristic of so-called mathematical models of learning, while the second is characteristic of computer simulation models. An approach (...)
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