Two types of typicality: Rethinking the role of statistical typicality in ordinary causal attributions

Justin Sytsma, Jonathan Livengood, David Rose

Research output: Contribution to journalArticlepeer-review

Abstract

Recent work on the role of norms in the use of causal language by ordinary people has led to a consensus among several researchers: The consensus position is that causal attributions are sensitive to both statistical norms and prescriptive norms. But what is a statistical norm? We argue that there are at least two types that should be distinguished-agent-level statistical norms and population-level statistical norms. We then suggest an alternative account of ordinary causal attributions about agents (the responsibility view), noting that this view motivates divergent predictions about the effect of information about each of the two types of statistical norms noted. Further, these predictions run counter to those made by the consensus position. With this set-up in place, we present the results of a series of new experimental studies testing our predictions. The results are in line with the responsibility view, while indicating that the consensus position is seriously mistaken.

Original languageEnglish (US)
Pages (from-to)814-820
Number of pages7
JournalStudies in History and Philosophy of Science Part C :Studies in History and Philosophy of Biological and Biomedical Sciences
Volume43
Issue number4
DOIs
StatePublished - Dec 2012

Keywords

  • Ordinary causal attributions
  • Prescriptive norms
  • Responsibility
  • Statistical norms

ASJC Scopus subject areas

  • History
  • History and Philosophy of Science

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