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.
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http://dx.doi.org/10.3758/bf03195937 | DOI Listing |
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