True Lies: Realism, Robustness, and Models

Philosophy of Science 78 (5):1177-1188 (2011)
  Copy   BIBTEX

Abstract

In this essay, I argue that uneliminated idealizations pose a serious problem for scientific realism. I consider one method for “de-idealizing” models—robustness analysis. However, I argue that unless idealizations are eliminated from an idealized theory and robustness analysis need not do that, scientists are not justified in believing that the theory is true. I consider one example of modeling from the biological sciences that exemplifies the problem.

Other Versions

No versions found

Links

PhilArchive

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Idealizations and Partitions: A Defense of Robustness Analysis.Gareth P. Fuller & Armin W. Schulz - 2021 - European Journal for Philosophy of Science 11 (4):1-15.
Credentialed Fictions and Robustness Analysis.Gareth Fuller - 2022 - Southwest Philosophy Review 38 (1):135-143.
Robustness analysis and tractability in modeling.Chiara Lisciandra - 2017 - European Journal for Philosophy of Science 7 (1):79-95.
Robustness and reality.Markus I. Eronen - 2015 - Synthese 192 (12):3961-3977.
Robustness and sensitivity of biological models.Jani Raerinne - 2013 - Philosophical Studies 166 (2):285-303.
The Volterra Principle Generalized.Tim Räz - 2017 - Philosophy of Science 84 (4):737-760.
Robust realism for the life sciences.Markus I. Eronen - 2019 - Synthese 196 (6):2341-2354.

Analytics

Added to PP
2012-01-07

Downloads
238 (#171,852)

6 months
10 (#1,169,684)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Jay Odenbaugh
Lewis & Clark College

References found in this work

The strategy of model building in population biology.Richard Levins - 1966 - American Scientist 54 (4):421–431.
Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.

Add more references