title: Distinguishing genuine from spurious causes: a coherence hypothesis.
abstract: Two opposing views have been proposed to explain how people distinguish genuine causes from spurious ones: the power view and the covariational view. This paper notes two phenomena that challenge both views. First, even when 1) there is no innate specific causal knowledge about a regularity (so that the power view does not apply) and 2) covariation cannot be computed while controlling for alternative causes (so that the covariation view should not apply), people are still able to systematically judge whether a regularity is causal. Second, when an alternative cause explains the effect, a spurious cause is judged to be spurious with greater confidence than otherwise (in both cases, no causal mechanism underlies the spurious cause). To fill the gap left by the traditional views, this paper proposes a new integration of these views. According to the coherence hypothesis, although a genuine cause and a spurious one may both covary with an effect in a way that does not imply causality at some level of abstraction, the categories to which these candidate causes belong covary with the effect differently at a more abstract level: one covariation implies causality; the other does not. Given this superordinate knowledge, the causal judgments of a reasoner who seeks to explain as much as possible with as few causal rules as possible will exhibit the properties that challenge the traditional views. Two experiments tested and supported the coherence hypothesis. Both experiments involved candidate causes that covary with an effect without implying causality at some level, manipulating whether covariation that implies causality has been acquired at a more abstract level. The experiments differed on whether an alternative cause explains the effect.
authors.affiliation: National Taiwan University, Taipei, Taiwan. ywlien@cc.ntu.edu.tw
authors.forename: Y
authors.initials: Y
authors.lastname: Lien
authors.forename: P W
authors.initials: PW
authors.lastname: Cheng
mesh_terms: D003071:Cognition; D003463:Cues; D006801:Humans; D007600:Judgment; D015203:Reproducibility of Results