Category coherence and category-based property induction
Category coherence and category-based property induction
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DOI：
10.1016/s0010-0277(03)00167-7
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发表时间：
2004-03-01
期刊：
影响因子：
3.4
通讯作者：
Hastie, R
中科院分区：
文献类型：
--
作者：
Rehder, B;Hastie, R
人类对象类别的一个重要属性是它们定义了新观察到的属性被推广到的样本集。我们操纵了与新类别相关的因果知识，并评估了属性归纳的强度。我们发现，特征间因果关系为类别提供的理论连贯性增强了归纳预测。然而，这种效果取决于具有待投影谓词的范例体现或满足其类别的因果律的程度。也就是说，支持归纳概括的连贯性是单个类别成员而不是类别的属性。此外，我们发现一个范例的一致性是由它的类别成员程度来调节的。这些结果是通过各种因果网络拓扑和类别（包括生物类别、非生物自然类别和人工制品）获得的。 (C) 2003 Elsevier B.V. 保留所有权利。
One important property of human object categories is that they define the sets of exemplars to which newly observed properties are generalized. We manipulated the causal knowledge associated with novel categories and assessed the resulting strength of property inductions. We found that the theoretical coherence afforded to a category by inter-feature causal relationships strengthened inductive projections. However, this effect depended on the degree to which the exemplar with the to-be-projected predicate manifested or satisfied its category's causal laws. That is, the coherence that supports inductive generalizations is a property of individual category members rather than categories. Moreover, we found that an exemplar's coherence was mediated by its degree of category membership. These results were obtained across a variety of causal network topologies and kinds of categories, including biological kinds, non-living natural kinds, and artifacts. (C) 2003 Elsevier B.V. All rights reserved.