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Michael T. Stuart [9]Michael Stuart [2]
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Michael T. Stuart
University of Geneva
  1. Towards a Dual Process Epistemology of Imagination.Michael T. Stuart - 2019 - Synthese:1-22.
    Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative processes (...)
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  2.  28
    The Material Theory of Induction and the Epistemology of Thought Experiments.Michael T. Stuart - forthcoming - Studies in History and Philosophy of Science Part A.
    John D. Norton is responsible for a number of influential views in contemporary philosophy of science. This paper will discuss two of them. The material theory of induction claims that inductive arguments are ultimately justified by their material features, not their formal features. Thus, while a deductive argument can be valid irrespective of the content of the propositions that make up the argument, an inductive argument about, say, apples, will be justified (or not) depending on facts about apples. The argument (...)
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  3. How Thought Experiments Increase Understanding.Michael T. Stuart - 2017 - In Michael T. Stuart, Yiftach J. H. Fehige & James Robert Brown (eds.), The Routledge Companion to Thought Experiments. London: Routledge. pp. 526-544.
    We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways (...)
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  4.  40
    Imagination: A Sine Qua Non of Science.Michael T. Stuart - 2017 - Croatian Journal of Philosophy (49):9-32.
    What role does the imagination play in scientific progress? After examining several studies in cognitive science, I argue that one thing the imagination does is help to increase scientific understanding, which is itself indispensable for scientific progress. Then, I sketch a transcendental justification of the role of imagination in this process.
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  5. Peeking Inside the Black Box: A New Kind of Scientific Visualization.Michael T. Stuart & Nancy J. Nersessian - 2018 - Minds and Machines 29 (1):87-107.
    Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...)
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  6. Thought Experiments: State of the Art.Michael T. Stuart, Yiftach Fehige & James R. Brown - 2018 - In Michael T. Stuart, Yiftach J. H. Fehige & James Robert Brown (eds.), The Routledge Companion to Thought Experiments. London, UK: Routledge. pp. 1-28.
    This is the introduction to the Routledge Companion to Thought Experiments.
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  7. The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms.Michael Stuart - 2019 - In Mark Addis, Fernand Gobet & Peter Sozou (eds.), Scientific Discovery in the Social Sciences. Springer Verlag.
    When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from (...)
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  8. Philosophical Conceptual Analysis as an Experimental Method.Michael T. Stuart - 2015 - In Thomas Gamerschlag, Doris Gerland, Rainer Osswald & Wiebke Petersen (eds.), Meaning, Frames, and Conceptual Representation. Düsseldorf University Press. pp. 267-292.
    Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...)
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  9.  73
    Everyday Scientific Imagination: A Qualitative Study of the Uses, Norms, and Pedagogy of Imagination in Science.Michael Stuart - 2019 - Science & Education 28 (6-7):711-730.
    Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination in problem-solving. (...)
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  10. The Content-Dependence of Imaginative Resistance.Hanna Kim, Markus Kneer & Michael T. Stuart - 2018 - In Florian Cova & Sébastien Réhault (eds.), Advances in Experimental Philosophy of Aesthetics. London: Bloomsbury. pp. 143-166.
    An observation of Hume’s has received a lot of attention over the last decade and a half: Although we can standardly imagine the most implausible scenarios, we encounter resistance when imagining propositions at odds with established moral (or perhaps more generally evaluative) convictions. The literature is ripe with ‘solutions’ to this so-called ‘Puzzle of Imaginative Resistance’. Few, however, question the plausibility of the empirical assumption at the heart of the puzzle. In this paper, we explore empirically whether the difficulty we (...)
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  11. REVIEW: James R. Brown, Laboratory of the Mind. [REVIEW]Michael T. Stuart - 2012 - Spontaneous Generations 6 (1):237-241.
    Originally published in 1991, The Laboratory of the Mind: Thought Experiments in the Natural Sciences, is the first monograph to identify and address some of the many interesting questions that pertain to thought experiments. While the putative aim of the book is to explore the nature of thought experimental evidence, it has another important purpose which concerns the crucial role thought experiments play in Brown’s Platonic master argument.In that argument, Brown argues against naturalism and empiricism (Brown 2012), for mathematical Platonism (...)
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