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  1. Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
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  • Rethinking Ethnography for Philosophy of Science.Nancy J. Nersessian & Miles MacLeod - 2022 - Philosophy of Science 89 (4):721-741.
    We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks: to identify the benefits of an ethnographic approach in philosophy of science and to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography that mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and (...)
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  • The applicability of mathematics in computational systems biology and its experimental relations.Miles MacLeod - 2021 - European Journal for Philosophy of Science 11 (3):1-21.
    In 1966 Richard Levins argued that applications of mathematics to population biology faced various constraints which forced mathematical modelers to trade-off at least one of realism, precision, or generality in their approach. Much traditional mathematical modeling in biology has prioritized generality and precision in the place of realism through strategies of idealization and simplification. This has at times created tensions with experimental biologists. The past 20 years however has seen an explosion in mathematical modeling of biological systems with the rise (...)
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  • Steel and bone: mesoscale modeling and middle-out strategies in physics and biology.Robert W. Batterman & Sara Green - 2020 - Synthese 199 (1-2):1159-1184.
    Mesoscale modeling is often considered merely as a practical strategy used when information on lower-scale details is lacking, or when there is a need to make models cognitively or computationally tractable. Without dismissing the importance of practical constraints for modeling choices, we argue that mesoscale models should not just be considered as abbreviations or placeholders for more “complete” models. Because many systems exhibit different behaviors at various spatial and temporal scales, bottom-up approaches are almost always doomed to fail. Mesoscale models (...)
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  • Gluing life together. Computer simulation in the life sciences: an introduction.Janina Wellmann - 2018 - History and Philosophy of the Life Sciences 40 (4):70.
    Over the course of the last three decades, computer simulations have become a major tool of doing science and engaging with the world, not least in an effort to predict and intervene in a future to come. Born in the context of the Second World War and the discipline of physics, simulations have long spread into most diverse fields of enquiry and technological application. This paper introduces a topical collection focussing on simulations in the life sciences. Echoing the current state (...)
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  • Micro-foundations and Methodology: A Complexity-Based Reconceptualization of the Debate.Nadia Ruiz & Armin W. Schulz - 2023 - British Journal for the Philosophy of Science 74 (2):359-379.
    In a number of very influential publications, Epstein and Hoover (among other authors) have recently argued that a thoroughly micro-foundationalist approach towards economics is unconvincing for metaphysical reasons. However, as we show in this article, this metaphysical/social ontological approach to the debate fails to resolve the status of micro-foundations in the practice of economic modelling. To overcome this, we argue that endogenizing a model—that is, providing micro-foundations for it—correlates with making that model more complex. Specifically, we show that models with (...)
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  • Mesoscopic modeling as a cognitive strategy for handling complex biological systems.Miles MacLeod & Nancy J. Nersessian - 2019 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 78:101201.
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  • Model-Based Inferences in Modeling of Complex Systems.Miles MacLeod - 2020 - Topoi 39 (4):915-925.
    Modelers are tackling ever more complex systems with the aid of computation. Model-based inferences can play a key role in their ability to handle complexity and produce reliable or informative models. We study here the role of model-based inference in the modern field of computational systems biology. We illustrate how these inferences operate and analyze the material and theoretical bases or conditions underlying their effectiveness. Our investigation reiterates the significance and centrality of model-based reasoning in day-to-day problem-solving practices, and the (...)
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