Abstract
AbstractHere I critically assess an argument put forward by Kuorikoski et al. (Br J Philos Sci, 61(3):541–567, 2010) for the epistemic import of model-based robustness analysis. I show that this argument is not sound since the sort of probabilistic independence on which it relies is unfeasible. By revising the notion of probabilistic independence imposed on the models’ results, I introduce a prima-facie more plausible argument. However, despite this prima-facie plausibility, I show that even this new argument is unsound in most if not all cases of model-based robustness analysis. This I do to demonstrate that the epistemic import of model-based robust analysis cannot be satisfactorily defended on the basis of probabilistic independence.
Publisher
Springer Science and Business Media LLC
Subject
General Social Sciences,Philosophy
Reference26 articles.
1. Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford: Oxford University Press.
2. Cartwright, N. (1989). Nature’s capacities and their measurement. Clarendon Press.
3. Cartwright, N. (1991). Replicability, reproducibility, and robustness: Comments on Harry Collins. History of Political Economy, 23(1), 143–155.
4. Fitelson, B. (2001). A Bayesian account of independent evidence with applications. Philosophy of Science, 68(S3), S123–S140.
5. Frigg, R., & Hartmann, S. (2020). Models in science. In The Stanford encyclopedia of philosophy, edited by E. N. Zalta, Spring 2020. Metaphysics Research Lab, Stanford University.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献