Literature DB >> 25347533

Causal inference and the hierarchical structure of experience.

Samuel G B Johnson1, Frank C Keil1.   

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. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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Year:  2014        PMID: 25347533      PMCID: PMC4244254          DOI: 10.1037/a0038192

Source DB:  PubMed          Journal:  J Exp Psychol Gen        ISSN: 0022-1015


  39 in total

1.  Distinguishing genuine from spurious causes: a coherence hypothesis.

Authors:  Y Lien; P W Cheng
Journal:  Cogn Psychol       Date:  2000-03       Impact factor: 3.468

Review 2.  Spontaneous inferences, implicit impressions, and implicit theories.

Authors:  James S Uleman; S Adil Saribay; Celia M Gonzalez
Journal:  Annu Rev Psychol       Date:  2008       Impact factor: 24.137

Review 3.  Property transmission: an explanatory account of the role of similarity information in causal inference.

Authors:  Peter A White
Journal:  Psychol Bull       Date:  2009-09       Impact factor: 17.737

4.  A causal model theory of the meaning of cause, enable, and prevent.

Authors:  Steven Sloman; Aron K Barbey; Jared M Hotaling
Journal:  Cogn Sci       Date:  2009-01

5.  Objects, parts, and categories.

Authors:  B Tversky; K Hemenway
Journal:  J Exp Psychol Gen       Date:  1984-06

6.  Pragmatic reasoning schemas.

Authors:  P W Cheng; K J Holyoak
Journal:  Cogn Psychol       Date:  1985-10       Impact factor: 3.468

7.  Perceiving, remembering, and communicating structure in events.

Authors:  J M Zacks; B Tversky; G Iyer
Journal:  J Exp Psychol Gen       Date:  2001-03

8.  Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.

Authors:  Samuel G B Johnson; Woo-kyoung Ahn
Journal:  Cogn Sci       Date:  2015-01-03

9.  Representing causation.

Authors:  Phillip Wolff
Journal:  J Exp Psychol Gen       Date:  2007-02

10.  Segmentation in reading and film comprehension.

Authors:  Jeffrey M Zacks; Nicole K Speer; Jeremy R Reynolds
Journal:  J Exp Psychol Gen       Date:  2009-05
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  3 in total

1.  Memory accessibility shapes explanation: Testing key claims of the inherence heuristic account.

Authors:  Larisa J Hussak; Andrei Cimpian
Journal:  Mem Cognit       Date:  2018-01

2.  Causal reasoning without mechanism.

Authors:  Selma Dündar-Coecke; Gideon Goldin; Steven A Sloman
Journal:  PLoS One       Date:  2022-05-13       Impact factor: 3.752

3.  Adapting to an Uncertain World: Cognitive Capacity and Causal Reasoning with Ambiguous Observations.

Authors:  Yiyun Shou; Michael Smithson
Journal:  PLoS One       Date:  2015-10-15       Impact factor: 3.240

  3 in total

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