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Diversion of attention in everyday concept learning: Identification in the service of use

机译:在日常概念学习中转移注意力:在使用服务中进行识别

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摘要

Many people tend to believe that natural categories have perfectly predictive defining features. They do not easily accept the family resemblance view that the features characteristic of a category are not individually sufficient to predict the category. However, common category-learning tasks do not produce this simpler-than-it-is belief. If there is no simple classification principle in a task, the participants know that fact and can report it. We argue that most category-learning tasks in which family resemblance categories are used fail to produce the everyday simpler-than-it-is belief because they encourage analysis of identification criteria during training. To simulate the learning occurring in many natural circumstances, we developed a procedure in which participants' analytic activity is diverted from the way in which the stimuli are identified to the use to which the stimuli will be put. Finally, we discuss the prevalence of this diverted analysis in everyday categorization.
机译:许多人倾向于认为自然类别具有完全可预测的定义特征。他们不容易接受家庭相似的观点,即类别的特征不足以单独预测该类别。但是,常见的类别学习任务不会产生这种比其简单的信念。如果任务中没有简单的分类原则,则参与者知道该事实并可以报告该事实。我们认为,大多数使用家庭相似类别的类别学习任务未能产生日常的简单观念,因为它们鼓励在培训过程中分析识别标准。为了模拟在许多自然条件下发生的学习,我们开发了一种程序,在该程序中,参与者的分析活动从识别刺激的方式转移到将其用于刺激的用途。最后,我们讨论了这种分类分析在日常分类中的普遍性。

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