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Causal Attributions and Corpus Analysis

Sytsma, Justin and Bluhm, Roland and Willemsen, Pascale and Reuter, Kevin (2018) Causal Attributions and Corpus Analysis. [Preprint]

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Abstract

Although philosophers have often held that causation is a purely descriptive notion, a growing body of experimental work on ordinary causal attributions using questionnaire methods indicates that it is heavily influenced by normative information. These results have been the subject of sceptical challenges. Additionally, those who find the results compelling have disagreed about how best to explain them. In this chapter, we help resolve these debates by using a new set of tools to investigate ordinary causal attributions—the methods of corpus linguistics. We apply both more qualitative corpus analysis techniques and the more purely quantitative methods of distributional semantics to four target questions: (a) Can corpus analysis provide independent support for the thesis that ordinary causal attributions are sensitive to normative information? (b) Does the evidence coming from corpus analysis support the contention that outcome valence matters for ordinary causal attributions? (c) Are ordinary causal attributions similar to responsibility attributions? (d) Are causal attributions of philosophers different from causal attributions we find in corpora of more ordinary language? We argue that the results of our analyses support a positive answer to each of these questions.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Sytsma, Justin
Bluhm, Roland
Willemsen, Pascale
Reuter, Kevin
Additional Information: To appear in Methodological Advances in Experimental Philosophy, edited by Eugen Fischer and published by Bloomsbury Press.
Keywords: Corpus Analysis, Distributional Semantics, Causation, Causal Attributions, Responsibility, Injunctive Norms
Subjects: General Issues > Causation
Specific Sciences > Cognitive Science
Depositing User: Justin Sytsma
Date Deposited: 05 Jul 2018 08:37
Last Modified: 10 Jul 2018 21:36
Item ID: 14848
Subjects: General Issues > Causation
Specific Sciences > Cognitive Science
Date: 4 July 2018
URI: http://philsci-archive.pitt.edu/id/eprint/14848

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