Wang, Yafeng (2022) Feature Dependence: A Method for Reconstructing Actual Causes in Engineering Failure Investigations. Studies in History and Philosophy of Science, 96. pp. 100-111. ISSN 00393681
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Abstract
Engineering failure investigations seek to reconstruct the actual causes of major engineering failures. The investigators need to establish the existence of certain past events and the actual causal relationships that these events bear to the failures in question. In this paper, I examine one method for reconstructing the actual causes of failure events, which I call "feature dependence". The basic idea of feature dependence is that some features of an event are informative about the features of its causes; therefore, the investigators can use the features of a known failure event to reconstruct details of its causes. I make explicit the structure of feature dependence and the evidential basis of its key premises, and show how feature dependence works in the investigation of the American Airlines Flight 191 accident.
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Item Type: | Published Article or Volume | ||||||
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Additional Information: | This is a preprint (the final draft before the peer review). Please cite the published Version: Wang, Y. (2022). Feature Dependence: A Method for Reconstructing Actual Causes in Engineering Failure Investigations. Studies in History and Philosophy of Science, 96:100-111. | ||||||
Keywords: | Actual Causation, Causal Reasoning, Historical Reconstruction, Features, Engineering Failure Investigations | ||||||
Subjects: | General Issues > Causation Specific Sciences > Engineering |
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Depositing User: | Yafeng Wang | ||||||
Date Deposited: | 31 Mar 2024 05:31 | ||||||
Last Modified: | 31 Mar 2024 05:31 | ||||||
Item ID: | 23248 | ||||||
Journal or Publication Title: | Studies in History and Philosophy of Science | ||||||
Publisher: | Elsevier | ||||||
Official URL: | https://www.sciencedirect.com/science/article/abs/... | ||||||
DOI or Unique Handle: | https://doi.org/10.1016/j.shpsa.2022.09.005 | ||||||
Subjects: | General Issues > Causation Specific Sciences > Engineering |
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Date: | 30 September 2022 | ||||||
Page Range: | pp. 100-111 | ||||||
Volume: | 96 | ||||||
ISSN: | 00393681 | ||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/23248 |
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