采用學習―測試二階段實驗范式,對比了類別標簽與類別特征在類別特征推理中的極化效應。研究結果表明,在類別標簽組,標簽匹配項目上的特征推理分數顯著高于標簽不匹配項目上的特征推理分數;在特征標簽組,標簽匹配項目上的特征推理分數與標簽不匹配項目上的特征推理分數之間差異不顯著。類別標簽組的失匹配分數顯著高于特征標簽組。即在類別特征推理任務中,類別標簽的極化效應顯著高于類別特征的極化效應,因此,類別標簽與類別特征存在本質差異,類別標簽在類別特征推理中起主導作用。而且,本研究還發現,高前提概率條件下的特征推理分數都顯著高于低前提概率條件下的特征推理分數,所以,前提概率也影響類別特征推理任務。

Categorization and inference are two important functions of category knowledge,besides categorization,category-based feature inference is an important application of category knowledge.Categorization is to infer an item′s category label when its feature value is known,while inference is to infer an item′s one or few unknown feature value when its category label is known.Category label is a symbol on behalf of category membership,while category feature is a symbol representing a feature of an item.This study aimed to contrast the polarization effect between category label and feature label in category-based feature inference.The experiments used learning-test two phase paradigm and a 2(type of category label:category and feature) ×2(matching type of label:matching and non-matching) × 2(basal probability:high and low)experimental design.The results of the experiment showed that:1) The polarization effect of category label was significantly higher than the one of feature label.2) Category label was different from category feature essentially.3) The basal probability affected the category-based feature inference.In summary,this study showed that category label is essentially different from category feature.And this study had a new finding that the basal probability did affect the category-based feature inference.