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  1. Modelling Beyond Application: Epistemic and Non-Epistemic Values in Modern Science.Ekaterina Svetlova - 2014 - International Studies in the Philosophy of Science 28 (1):79-98.
    In recent years, philosophers of science have begun to realize that the clear separation of the creation of models in academia and the application of models outside science is not possible. When these philosophers address hybrid contexts in which science is entwined with policy, business, and other realms of society, these often practically oriented realms no longer represent ‘the surroundings’ of science but rather are considered an essential part of it. I argue—and demonstrate empirically—that the judgement of a theory or (...)
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  • The Unreasonable Destructiveness of Political Correctness in Philosophy.Manuel Doria - 2017 - Philosophies 2 (3):17.
    I submit that epistemic progress in key areas of contemporary academic philosophy has been compromised by politically correct ideology. First, guided by an evolutionary account of ideology, results from social and cognitive psychology and formal philosophical methods, I expose evidence for political bias in contemporary Western academia and sketch a formalization for the contents of beliefs from the PC worldview taken to be of core importance, the theory of social oppression and the thesis of anthropological mental egalitarianism. Then, aided by (...)
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  • Modeling for Fairness: A Rawlsian Approach.Sven Diekmann & Sjoerd D. Zwart - 2014 - Studies in History and Philosophy of Science Part A 46:46-53.
    In this paper we introduce the overlapping design consensus for the construction of models in design and the related value judgments. The overlapping design consensus is inspired by Rawls’ overlapping consensus. The overlapping design consensus is a well-informed, mutual agreement among all stakeholders based on fairness. Fairness is respected if all stakeholders’ interests are given due and equal attention. For reaching such fair agreement, we apply Rawls’ original position and reflective equilibrium to modeling. We argue that by striving for the (...)
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