Department of Psychology, California State University San Bernardino, 5500 University Parkway, San Bernardino, CA 92407-2397, United States.
Cognition. 2019 Sep;190:1-19. doi: 10.1016/j.cognition.2019.04.009. Epub 2019 Apr 22.
Similarity has long been regarded as a major determinant of human categorization. Surprisingly, much research has shown that when people are asked to construct their own categories they rarely do so on the basis of overall similarity, instead categorizing on the basis of a single feature or dimension of the objects. This article reports five experiments that manipulate the proportion of parts shared by two structurally alignable objects to determine whether similarity would have a graded effect on free categorization. Increasing the proportion of shared features increased both the rated similarity of a given pair of objects and the probability of assigning them to the same category. Interestingly, the shape of the two similarity functions differed, with rated similarity increasing linearly with the proportion of shared features while the probability of assigning the objects to the same category increased superlinearly (exponentially). This difference is discussed in terms of Shepard's (1987) model of generalization, which predicts that any monotonic increase in perceived similarity will result in an exponential increase in the probability of generalization. Overall, these results provide a strong demonstration of similarity-based free categorization, and the particular form of that relationship provides useful information regarding the underlying cognitive processes involved.
相似性长期以来一直被视为人类分类的主要决定因素。令人惊讶的是，大量研究表明，当人们被要求自行构建类别时，他们很少基于整体相似性进行分类，而是基于对象的单个特征或维度进行分类。本文报告了五项实验，这些实验操纵了两个结构上可对齐的物体之间共享部分的比例，以确定相似性是否会对自由分类产生渐变效应。共享特征比例的增加提高了给定的一对物体的评级相似性，并增加了将它们分配到同一类别的概率。有趣的是，这两个相似性函数的形状不同，评定相似性与共享特征的比例呈线性关系，而将物体分配到同一类别的概率呈超线性（指数）增加。根据 Shepard（1987）的泛化模型，讨论了这种差异，该模型预测，感知相似性的任何单调增加都会导致泛化概率的指数增加。总的来说，这些结果有力地证明了基于相似性的自由分类，而这种关系的特殊形式提供了有关所涉及的潜在认知过程的有用信息。
