Philosophy of Science 81 (1):31-59 (2014)

Authors
Roman Frigg
London School of Economics
Seamus Bradley
London School of Economics (PhD)
Abstract
The sensitive dependence on initial conditions associated with nonlinear models imposes limitations on the models’ predictive power. We draw attention to an additional limitation than has been underappreciated, namely, structural model error. A model has SME if the model dynamics differ from the dynamics in the target system. If a nonlinear model has only the slightest SME, then its ability to generate decision-relevant predictions is compromised. Given a perfect model, we can take the effects of SDIC into account by substituting probabilistic predictions for point predictions. This route is foreclosed in the case of SME, which puts us in a worse epistemic situation than SDIC.
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DOI 10.1086/674416
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References found in this work BETA

In Defence of Objective Bayesianism.Jon Williamson - 2010 - Oxford University Press.
On Indeterminate Probabilities.Isaac Levi - 1974 - Journal of Philosophy 71 (13):391-418.
On Indeterminate Probabilities.Isaac Levi - 1978 - In A. Hooker, J. J. Leach & E. F. McClennen (eds.), Journal of Philosophy. D. Reidel. pp. 233--261.

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Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Lorenzo Magnani & Tommaso Wayne Bertolotti (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.

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