Department of Experimental Psychology.
Department of Philosophy.
J Exp Psychol Gen. 2022 Jul;151(7):1481-1501. doi: 10.1037/xge0001151. Epub 2021 Dec 20.
What do we communicate with causal explanations? Upon being told, " because ", a person might learn that C and E both occurred, and perhaps that there is a causal relationship between and . In fact, causal explanations systematically disclose much more than this basic information. Here, we offer a communication-theoretic account of explanation that makes specific predictions about the kinds of inferences people draw from others' explanations. We test these predictions in a case study involving the role of norms and causal structure. In Experiment 1, we demonstrate that people infer the normality of a cause from an explanation when they know the underlying causal structure. In Experiment 2, we show that people infer the causal structure from an explanation if they know the normality of the cited cause. We find these patterns both for scenarios that manipulate the statistical and prescriptive normality of events. Finally, we consider how the communicative function of explanations, as highlighted in this series of experiments, may help to elucidate the distinctive roles that normality and causal structure play in causal judgment, paving the way toward a more comprehensive account of causal explanation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
我们用因果解释来交流什么？当被告知“因为”时，一个人可能会了解到 C 和 E 都发生了，也许 和 之间存在因果关系。事实上，因果解释系统地揭示了比这一基本信息更多的内容。在这里，我们提供了一种解释的通信理论解释，对人们从他人的解释中得出的推理种类做出了具体的预测。我们在一个涉及规范和因果结构作用的案例研究中检验了这些预测。在实验 1 中，我们证明了当人们知道潜在的因果结构时，他们会从一个解释中推断出原因的正常性。在实验 2 中，我们表明，如果人们知道被引用的原因是正常的，他们就会从一个解释中推断出因果结构。我们发现这些模式既适用于操纵事件统计和规范性正常性的场景，也适用于操纵事件描述性正常性的场景。最后，我们考虑了解释的交流功能如何有助于阐明正常性和因果结构在因果判断中所扮演的独特角色，为更全面的因果解释铺平了道路。（PsycInfo 数据库记录（c）2022 APA，保留所有权利）。
