Two main uses of categories are classification and feature inference, and category labels have been widely shown to play a dominant role in feature inference. However, the nature of this influence is unclear, and we evaluate two contrasting hypotheses formalized as mathematical models: the label special-mechanism hypothesis and the label super-salience hypothesis. The special-mechanism hypothesis is that category labels, unlike other features, trigger inference decision making in reference to the category prototypes. This results in a tendency for prototype-compatible inferences because the labels trigger a special mechanism rather than because of any influences they have on similarity evaluation. The super-salience hypothesis assumes that ...
A number of studies have contrasted classification and inference, using a variety of stimuli and tes...
had criterial features and that category membership could be determined by logical rules for the com...
The curse of dimensionality, which has been widely studied in statistics and machine learning, occur...
Two main uses of categories are classification and feature inference, and category labels have been ...
Cognition in FluxAre labels cues to category membership or simply highly salient features? This ques...
Categories have at least two main functions: classification of instances and feature inference. Clas...
The ability to make inferences about the properties of a category instance based on knowledge of its...
Labels are one source of our judgments. By assigning labels to objects, we not only create reference...
Cognition in FluxWe explore whether social context affects how labels (relative to other features) a...
When objects carry the same or different label(s), our perception of the similarity of the objects c...
Three studies examined how task demands that impact on attention to typical or atypical category fea...
This thesis examined how task demands shape the category representations formed through classificati...
Category-based feature generalisations are affected by similarity relationships between objects and ...
Category-based feature generalisations are affected by similarity relationships between objects and ...
We explore whether social context affects how labels (relative to other features) affect category le...
A number of studies have contrasted classification and inference, using a variety of stimuli and tes...
had criterial features and that category membership could be determined by logical rules for the com...
The curse of dimensionality, which has been widely studied in statistics and machine learning, occur...
Two main uses of categories are classification and feature inference, and category labels have been ...
Cognition in FluxAre labels cues to category membership or simply highly salient features? This ques...
Categories have at least two main functions: classification of instances and feature inference. Clas...
The ability to make inferences about the properties of a category instance based on knowledge of its...
Labels are one source of our judgments. By assigning labels to objects, we not only create reference...
Cognition in FluxWe explore whether social context affects how labels (relative to other features) a...
When objects carry the same or different label(s), our perception of the similarity of the objects c...
Three studies examined how task demands that impact on attention to typical or atypical category fea...
This thesis examined how task demands shape the category representations formed through classificati...
Category-based feature generalisations are affected by similarity relationships between objects and ...
Category-based feature generalisations are affected by similarity relationships between objects and ...
We explore whether social context affects how labels (relative to other features) affect category le...
A number of studies have contrasted classification and inference, using a variety of stimuli and tes...
had criterial features and that category membership could be determined by logical rules for the com...
The curse of dimensionality, which has been widely studied in statistics and machine learning, occur...