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基于类别的预测:不确定性和特征关联的影响

Category-based predictions: influence of uncertainty and feature associations.

作者信息

Ross B H, Murphy G L

机构信息

Department of Psychology, University of Illinois, Urbana 61801, USA.

出版信息

J Exp Psychol Learn Mem Cogn. 1996 May;22(3):736-53.

PMID:8656154
Abstract

Four experiments examined how people make inductive inferences using categories. Subjects read stories in which 2 categories were mentioned as possible identities of an object. The less likely category was varied to determine if people were using it, as well as the most likely category, in making predictions about the object. Experiment 1 showed that even when categorization uncertainty was emphasized, subjects used only 1 category as the basis for their prediction. Experiments 2-4 examined whether people would use multiple categories for making predictions when the feature to be predicted was associated to the less likely category. Multiple categories were used in this case, but only in limited circumstances; furthermore, using multiple categories in 1 prediction did not cause subjects to use them for subsequent predictions. The results increase the understanding of how categories are used in inductive inference.

摘要

四项实验研究了人们如何使用类别进行归纳推理。受试者阅读一些故事,其中提到了两个类别作为一个物体可能的身份。改变可能性较小的类别,以确定人们在对该物体进行预测时是否会使用它以及可能性最大的类别。实验1表明,即使强调了分类的不确定性,受试者也只使用一个类别作为预测的基础。实验2至4研究了当要预测的特征与可能性较小的类别相关联时,人们是否会使用多个类别进行预测。在这种情况下会使用多个类别,但仅限于有限的情况;此外,在一次预测中使用多个类别并不会导致受试者在后续预测中也使用它们。这些结果增进了我们对类别在归纳推理中如何被使用的理解。

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