Department of Psychology, Albert-Ludwigs University Freiburg.
J Exp Psychol Learn Mem Cogn. 2019 Dec;45(12):2188-2208. doi: 10.1037/xlm0000706. Epub 2019 Apr 18.
We consider the proposition that reasoners represent causal conditionals such as "if John studies hard, he will do well in the test" as a causal model in which the antecedent (John studies hard) is a potential cause of the consequent (John does well in the test). Some studies suggest that reasoners ignore alternative causes of the consequent in predictive judgments. Similarly, reasoners may not fully consider alternative causes in diagnostic judgments either. We tested these assumptions in a comparison of 2 causal models with and without alternative causes. In Experiments 1 and 2, only the model with alternative causes tended to overestimate predictive and diagnostic judgments. In Experiment 3, we tested whether the causal models account for the participants' judgments of the probability of the conditional. However, neither model's predictions were accurate. Based on the assumption that probability judgments only follow ordinal relations, we tested qualitative, rather than quantitative predictions of the causal models in Experiments 4 and 5. Participants provided predictive and diagnostic judgments for causal scenarios they observed in the experiments. The results suggest that reasoners consider alternative causes. Finally, in Experiment 6, participants considered pairs of causal conditionals, matched in causal power but differing in the probability of alternative causes. On average, participants preferred to bet on the predictive conclusions of those conditionals that had a higher probability of alternative causes. Because of the uncertain metric properties of probability judgments, we conclude that reasoners likely consider alternative causes in predictive and diagnostic judgments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
我们认为,推理者将“如果约翰努力学习,他在考试中会表现出色”这样的因果条件句表示为因果模型,其中前提(约翰努力学习)是后果(约翰在考试中表现出色)的潜在原因。一些研究表明,推理者在预测判断中忽略了后果的其他原因。同样,推理者在诊断判断中也可能没有充分考虑其他原因。我们通过比较有和没有替代原因的 2 个因果模型来检验这些假设。在实验 1 和实验 2 中,只有具有替代原因的模型往往会过高估计预测和诊断判断。在实验 3 中,我们测试了因果模型是否可以解释参与者对条件概率的判断。然而,两个模型的预测都不准确。基于概率判断仅遵循序关系的假设,我们在实验 4 和实验 5 中测试了因果模型的定性而非定量预测。参与者对他们在实验中观察到的因果场景提供了预测和诊断判断。结果表明,推理者会考虑替代原因。最后,在实验 6 中,参与者考虑了配对的因果条件句,这些条件句在因果力上匹配,但在替代原因的概率上有所不同。平均而言,参与者更愿意在那些具有更高替代原因概率的条件句的预测结论上打赌。由于概率判断的不确定度量属性,我们得出结论,推理者可能会在预测和诊断判断中考虑替代原因。(PsycINFO 数据库记录(c)2019 APA,保留所有权利)。