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推理仅仅是伪装下的概率推理吗?

Is inferential reasoning just probabilistic reasoning in disguise?

作者信息

Markovits Henry, Handley Simon

机构信息

Centre for Thinking and Language, Psychology Department, University of Plymouth, Plymouth, England.

出版信息

Mem Cognit. 2005 Oct;33(7):1315-23. doi: 10.3758/bf03193231.

Abstract

Oaksford, Chater, and Larkin (2000) have suggested that people actually use everyday probabilistic reasoning when making deductive inferences. In two studies, we explicitly compared probabilistic and deductive reasoning with identical if-then conditional premises with concrete content. In the first, adults were given causal premises with one strongly associated antecedent and were asked to make standard deductive inferences or to judge the probabilities of conclusions. In the second, reasoners were given scenarios presenting a causal relation with zero to three potential alternative antecedents. The participants responded to each set of problems under both deductive and probabilistic instructions. The results show that deductive and probabilistic inferences are not isomorphic. Probabilistic inferences can model deductive responses only using a limited, very high threshold model, which is equivalent to a simple retrieval model. These results provide a clearer understanding of the relations between probabilistic and deductive inferences and the limitations of trying to consider these two forms of inference as having a single underlying process.

摘要

奥克斯福德、查特和拉金(2000)提出,人们在进行演绎推理时实际上运用的是日常概率推理。在两项研究中,我们明确地对具有相同具体内容的“如果……那么……”条件前提的概率推理和演绎推理进行了比较。在第一项研究中,向成年人提供具有一个强相关前提的因果前提,并要求他们进行标准演绎推理或判断结论的概率。在第二项研究中,向推理者呈现具有零至三个潜在替代前提的因果关系情景。参与者在演绎和概率两种指导下对每组问题做出反应。结果表明,演绎推理和概率推理并非同构。概率推理只能使用有限的、非常高的阈值模型来模拟演绎反应,该模型等同于一个简单的检索模型。这些结果更清楚地揭示了概率推理和演绎推理之间的关系,以及试图将这两种推理形式视为具有单一潜在过程的局限性。

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