139 research outputs found

    Progress by Enlightenment: Fact or Fiction?

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    Optimistic realism about scientific progress

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    Scientific realists use the "no miracle argument" to show that the empirical and pragmatic success of science is an indicator of the ability of scientific theories to give true or truthlike representations of unobservable reality. While antirealists define scientific progress in terms of empirical success or practical problem-solving, realists characterize progress by using some truth-related criteria. This paper defends the definition of scientific progress as increasing truthlikeness or verisimilitude. Antirealists have tried to rebut realism with the "pessimistic metainduction", but critical realists turn this argument into an optimistic view about progressive science.Peer reviewe

    Queries of Pragmatic Realism

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    Henrik Rydenfelt, Heikki J. Koskinen & Mats Bergman (eds.), Limits of Pragmatism and Challenges of TheodicyPeer reviewe

    Structural rules for Abduction

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    Approaching probabilistic laws

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    In the general problem of verisimilitude, we try to define the distance of a statement from a target, which is an informative truth about some domain of investigation. For example, the target can be a state description, a structure description, or a constituent of a first-order language (Sect. 1). In the problem of legisimilitude, the target is a deterministic or universal law, which can be expressed by a nomic constituent or a quantitative function involving the operators of physical necessity and possibility (Sect. 2). The special case of legisimilitude, where the target is a probabilistic law (Sect. 3), has been discussed by Roger Rosenkrantz (Synthese, 1980) and Ilkka Niiniluoto (Truthlikeness, 1987, Ch. 11.5). Their basic proposal is to measure the distance between two probabilistic laws by the Kullback-Leibler notion of divergence, which is a semimetric on the space of probability measures. This idea can be applied to probabilistic laws of coexistence and laws of succession, and the examples may involve discrete or continuous state spaces (Sect. 3). In this paper, these earlier studies are elaborated in four directions (Sect. 4). First, even though deterministic laws are limiting cases of probabilistic laws, the target-sensitivity of truthlikeness measures implies that the legisimilitude of probabilistic laws is not easily reducible to the deterministic case. Secondly, the Jensen-Shannon divergence is applied to mixed probabilistic laws which entail some universal laws. Thirdly, a new class of distance measures between probability distributions is proposed, so that their horizontal differences are taken into account in addition to vertical ones (Sect. 5). Fourthly, a solution is given for the epistemic problem of estimating degrees of probabilistic legisimilitude on the basis of empirical evidence (Sect. 6).Peer reviewe

    Yliopistojen rehtorien neuvostolle virallinen asema

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    Unification and confirmation

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    According to the traditional requirement, formulated by William Whewell in his account of the “consilience of inductions” in 1840, a scientific hypothesis should have unifying power in the sense that it explains and predicts several mutually independent phenomena. Variants of this notion of consilience or unification include deductive, inductive, and approximate systematization. Inference from surprising phenomena to their theoretical explanations was called abduction by Charles Peirce. As a unifying theory is independently testable by new kinds of phenomena, it should also receive confirmation from its empirical success. The study of the prospects of probabilistic Bayesianism to motivate this kind of criterion for abductive confirmation is shown to lead to two quite distinct conceptions of unification.; De acuerdo con un requisito tradicional, formulado por William Whewell en su explicación de la "consiliencia de las inducciones" en 1840, una hipótesis científica debería tener poder unificador, en el sentido de que explique y prediga varios fenómenos mutuamente independientes. Las variantes de esta noción de consiliencia o unificación incluyen la sistematización deductiva, inductiva y aproximada. Charles Peirce llamó abducción a la inferencia que va de fenómenos sorprendentes hasta sus explicaciones teóricas. Puesto que una teoría unificadora puede contrastarse independientemente a partir de nuevas clases de fenómenos, también debería recibir confirmación a partir de su éxito empírico. Se muestra que el estudio de las perspectivas del bayesianismo probabilístico para motivar este tipo de criterio para la confirmación abductiva conduce a dos concepciones distintas de la unificación, vinculación (linking up) y anulación (screening off), y en ambos casos puede observarse que la teoría unificadora recibe apoyo probabilístico a partir de fenómenos empíricos

    Social Aspects of Scientific Knowledge

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    published online 2018-07-12From its inception in 1987 social epistemology has been divided into analytic (ASE) and critical (CSE) approaches, represented by Alvin I. Goldman and Steve Fuller, respectively. In this paper, the agendas and some basic ideas of ASE and CSE are compared and assessed by bringing into the discussion also other participants of the debates on the social aspects of scientific knowledge-among them Raimo Tuomela, Philip Kitcher and Helen Longino. The six topics to be analyzed include individual and collective epistemic agents; the notion of scientific community; realism and constructivism; truth-seeking communities; epistemic and social values; science, experts, and democracy.Peer reviewe

    Vassend on Verisimilitude and Counterfactual Probabilities

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    Olav Benjamin Vassend proposes two solutions to the "interpretive problem" of assigning nonzero probabilities to hypotheses that are known to be false. He argues that the verisimilitude interpretation (probability expresses the degree of belief that the hypothesis is closest to the truth) and the counterfactual interpretation (probability is conditional on a false supposition) are equivalent. While Vassend's intuition about these two solutions is basically correct, the technical details of his treatment need elaboration and correction. Appropriate tools for combining verisimilitude and Bayesian probabilities can be found in my Truthlikeness.Peer reviewe
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