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  1. Imagination and Actionability: Refections on the Future of Interdisciplinarity.Machiel Keestra - 2019 - Issues in Interdisciplinary Studies 2 (37):110-129.
    When introduced around 1925, interdisciplinarity, grounded in the notion of the unity of knowledge, was meant to reconnect the fragmented and specialized disciplines of academia. However, interdisciplinary research became more and more challenging as the plurality and heterogeneity of disciplinary perspectives and insights increased. Insisting on this divergence and diversity, Julie Thompson Klein has nonetheless contributed in important ways to convergence in interdisciplinarity with her work on the process of integration as interdisciplinarity's defining feature. Of course, she is aware that (...)
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  2. 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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  3. 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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  4. How Thought Experiments Increase Understanding.Michael T. Stuart - 2017 - In Michael T. Stuart, Yiftach 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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  5. 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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