Philosophy of Science 85 (5):819-831 (2018)
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With the ever-growing quality of observational data in astronomy, the complexity of astrophysical models has been increasing in turn. This trend raises the question: Are there still reasons to prefer simpler models if the final goal is an actual model-target comparison? I argue for two aspects in which astrophysical research may favor models having reduced complexity: first, to address the problem of determining the values of adjustable parameters and, second, to pave the way for a validation of the model based on the modeler’s understanding of the scope of the model and the critical processes on the target’s side.
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DOI | 10.1086/699696 |
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References found in this work BETA
Understanding (with) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2018 - British Journal for the Philosophy of Science 69 (4):1069-1099.
Methodological and Epistemic Differences Between Historical Science and Experimental Science.Carol E. Cleland - 2002 - Philosophy of Science 69 (3):447-451.
Understanding (With) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2016 - British Journal for the Philosophy of Science:axx005.
When Climate Models Agree: The Significance of Robust Model Predictions.Wendy S. Parker - 2011 - Philosophy of Science 78 (4):579-600.
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Citations of this work BETA
Jump Ship, Shift Gears, or Just Keep on Chugging: Assessing the Responses to Tensions Between Theory and Evidence in Contemporary Cosmology.Siska De Baerdemaeker & Nora Mills Boyd - 2020 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 72:205-216.
Cosmic Bayes. Datasets and Priors in the Hunt for Dark Energy.Michela Massimi - 2021 - European Journal for Philosophy of Science 11 (1):1-21.
The Systemic Concept of Contextual Truth.Andrzej Bielecki - 2021 - Foundations of Science 26 (4):807-824.
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