Causal inference and the hierarchical structure of experience

Samuel G.B. Johnson, Frank C. Keil

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Children and adults make rich causal inferences about the physical and social world, even in novel situations where they cannot rely on prior knowledge of causal mechanisms. We propose that this capacity is supported in part by constraints provided by event structure-the cognitive organization of experience into discrete events that are hierarchically organized. These event-structured causal inferences are guided by a level-matching principle, with events conceptualized at one level of an event hierarchy causally matched to other events at that same level, and a boundary-blocking principle, with events causally matched to other events that are parts of the same superordinate event. These principles are used to constrain inferences about plausible causal candidates in unfamiliar situations, both in diagnosing causes (Experiment 1) and predicting effects (Experiment 2). The results could not be explained by construal level (Experiment 3) or similarity-matching (Experiment 4), and were robust across a variety of physical and social causal systems. Taken together, these experiments demonstrate a novel way in which noncausal information we extract from the environment can help to constrain inferences about causal structure.

Original languageEnglish
Pages (from-to)2223-2241
Number of pages19
JournalJournal of Experimental Psychology: General
Volume143
Issue number6
DOIs
Publication statusPublished - 1 Dec 2014

Keywords

  • Causal reasoning
  • Event representation
  • Explanation
  • Prediction
  • Time

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology(all)
  • Developmental Neuroscience

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