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  1. Defending Deployment Realism against Alleged Counterexamples.Mario Alai - 2014 - In Guido Bonino, Greg Jesson & Javier Cumpa (eds.), Defending Realism: Ontological and Epistemological Investigations. Boston: De Gruyter. pp. 265-290.
    Criticisms à la Laudan can block the “no miracles” argument for the (approximate) truth of whole theories. Realists have thus retrenched, arguing that at least the individual claims deployed in the derivation of novel predictions should be considered (approximately) true. But for Lyons (2002) there are historical counterexamples even to this weaker “deployment” realism: he lists a number of novel predictions supposedly derived from (radically) false claims. But if so, those successes would seem unexplainable, even by Lyons’ “modest surrealism” or (...)
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  • Inductivist Strategies for Scientific Realism.Valeriano Iranzo - 2012 - Poznan Studies in the Philosophy of the Sciences and the Humanities 101 (1):241-268.
    Philip Kitcher has developed a sort of inductivist-reliabilist justification for scientific realism. After distinguishing his argument from a well-known abductivist one (the "no-miracles" argument), I will argue that Kitcher's proposal cannot adequately meet the antirealist challenge. Firstly, it begs the question against the antirealists; secondly, it can hardly support a plausible - piecemeal - scientific realism. I will explore an alternative inductivist approach that exploits correlations between theoretical properties and empirical success. On my view, its prospects for avoiding the aforementioned (...)
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  • Editorial.[author unknown] - 2017 - Editorial 9 (44):1-4.
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  • Scientific prediction and the underdetermination of scientific theory building.Richard Dawid - unknown
    According to the no miracles argument, scientific realism provides the only satisfactory explanation of the predictive success of science. It is argued in the present article that a different explanatory strategy, based on the posit of limitations to the underdetermination of scientific theory building by the available empirical data, offers a more convincing understanding of scientific success.
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