Evaluating competing theories via a common language of qualitative verdicts

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Abstract

Kuhn (The essential tension—Selected studies in scientific tradition and change, 1977) claimed that several algorithms can be defended to select the best theory based on epistemic values such as simplicity, accuracy, and fruitfulness. In a recent paper, Okasha (Mind 129(477):83–115, 2011) argued that no theory choice algorithm exists which satisfies a set of intuitively compelling conditions that Arrow (Social choice and individual values, 1963) had proposed for a consistent aggregation of individual preference orderings. In this paper, we put forward a solution to avoid this impossibility result. Based on previous work by Gaertner and Xu (Mathematical Social Sciences 63:193–196, 2012), we suggest to view the theory choice problem in a cardinal context and to use a general scoring function defined over a set of qualitative verdicts for every epistemic value. This aggregation method yields a complete and transitive ranking and the rule satisfies all Arrovian conditions appropriately reformulated within a cardinal setting. We also propose methods that capture the aggregation across different scientists.

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Gaertner, W., & Wüthrich, N. (2016). Evaluating competing theories via a common language of qualitative verdicts. Synthese, 193(10), 3293–3309. https://doi.org/10.1007/s11229-015-0929-4

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