Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.
Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.
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DOI:
10.1111/cogs.12213
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发表时间:
2015-09
影响因子:
2.5
通讯作者:
Ahn WK
中科院分区:
文献类型:
--
作者:
Johnson SG;Ahn WK
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 used causal transitivity—the inference 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 4–5).
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