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

Autor/inn/en	Johnson, Samuel G. B.; Ahn, Woo-kyoung
Titel	Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment
Quelle	In: Cognitive Science, 39 (2015) 7, S.1468-1503 (36 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0364-0213
DOI	10.1111/cogs.12213
Schlagwörter	Cognitive Processes; Decision Making; Attribution Theory; Networks; Semantics; Memory; Correlation; Testing + Suchen Sie Ihr Suchwort? Cognitive process; Kognitiver Prozess; Decision-making; Entscheidungsfindung; Semantik; Gedächtnis; Korrelation; Testdurchführung; Testen
Abstract	Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make "transitive" judgments about causal chains by inferring, given "A causes B" and "B causes C," that "A causes C." Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1-3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5). (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01