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  1. How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  • Feminist Perspectivism: A Revised Standpoint Theory.Chevan Lindsay - unknown
    The heart of this thesis is an examination into the relevant differences between Nietzsche’s perspectivism and standpoint theory. Briefly, both standpoint theory and perspectivism have been subjected to various charges that dissolve into two major ones, which are worthy of additional scrutiny: the charges of essentialism and incoherence. My overall argument in thesis is that standpoint theory, in spite of recent feminist defense, is still susceptible to these charges, and this proves counterproductive to its aims of combatting marginalization. Moreover, I (...)
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  • Science and Values: A philosophical perspective on the justifiability of evidence based policymaking.Osman Dede - 2021 - Dissertation, Erasmus Institute for Philosophy and Economics
    Science is widely regarded as the most reliable epistemic source of providing knowledge about the world. Policymakers intend to make purposeful changes in the world. The practice of policymakers relying on scientific experts to make informed decisions about which policies to implement is called Evidence Based Policymaking. This thesis provides a perspective from the philosophy of science in order to discuss the justifiability of Evidence Based Policymaking (EBP) with respect to broadly democratic and liberal values. Justifying EBP with broadly democratic (...)
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  • How to Assess the Epistemic Wrongness of Sponsorship Bias? The Case of Manufactured Certainty.Jon Leefmann - 2021 - Frontiers In 6 (Article 599909):1-13.
    Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently (...)
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  • Conditionals, Causal Claims and Objectivity.Michał Sikorski - 2020 - Dissertation, Università di Torino
    In my thesis, I develop two distinct themes. The first part of my thesis is devoted to indicative conditionals and approaching them from an empirically informed perspective. In the second part, I am developing classical topics of philosophy of science, specifically, scientific objectivity and the role of values in science, in connection to recent methodological developments, revolving around the Replication Crisis.
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  • A Critical Evaluation of Value-Free Science Based on the Induction Risk Argument.Gholam Hossien Javadpoor - 2020 - Journal of Philosophical Theological Research 22 (2):73-95.
    One of the most important issues in the philosophy of science in recent decades is to assess the permissibility of the involvement of background and non-scientific factors in science and to place them next to evidence or to involve them in the process of weighing evidence. Proponents of the value-free science ideal have considered any intervention of this kind as a blow to the objectivity of science and slipping in the process of science. One of the important arguments in criticizing (...)
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  • Drug Labels and Reproductive Health: How Values and Gender Norms Shape Regulatory Science at the FDA.Christopher ChoGlueck - 2019 - Dissertation, Indiana University
    The US Food and Drug Administration (FDA) is fraught with controversies over the role of values and politics in regulatory science, especially with drugs in the realm of reproductive health. Philosophers and science studies scholars have investigated the ways in which social context shapes medical knowledge through value judgments, and feminist scholars and activists have criticized sexism and injustice in reproductive medicine. Nonetheless, there has been no systematic study of values and gender norms in FDA drug regulation. I focus on (...)
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  • Robustness, Diversity of Evidence, and Probabilistic Independence.Jonah N. Schupbach - 2015 - In Mäki, Ruphy, Schurz & Votsis (eds.), Recent Developments in the Philosophy of Science: EPSA13 Helsinki. Springer. pp. 305-316.
    In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...)
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  • Neutralité scientifique.Marc-Kevin Daoust - 2018 - Encyclopédie Philosophique.
    Un biologiste fait une découverte incompatible avec des conceptions religieuses de la vie bonne. En classe, un professeur d'université profite de son exposé magistral pour faire la promotion d'une idéologie politique. Un fonds de recherche des sciences sociales refuse de financer un projet visant à résoudre le problème de la sous-représentation des femmes en politique, affirmant qu'une telle recherche n'est pas scientifique. Tous ces exemples témoignent de l'interaction constante entre, d'une part, l'enseignement et la recherche scientifique, et d'autre part, les (...)
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  • Value management and model pluralism in climate science.Julie Jebeile & Michel Crucifix - 2021 - Studies in History and Philosophy of Science Part A 88 (August 2021):120-127.
    Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered (...)
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