Causal Attributions and Corpus Analysis

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: Can corpus analysis provide independent support for the thesis that ordinary causal attributions are sensitive to normative information? Does the evidence coming from corpus analysis support the contention that outcome valence matters for ordinary causal attributions? Are ordinary causal attributions similar to responsibility attributions? 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.