title: Influence of multiple categories on the prediction of unknown properties.
abstract: Knowing an item's category helps us predict its unknown properties. Previous studies suggest that when asked to evaluate the probability of an unknown property, people tend to consider only an item's most likely category, ignoring alternative categories. In the present study, property prediction took the form of either a probability rating or a speeded binary-choice judgment. In keeping with past findings, the subjects ignored alternative categories in their probability ratings. However, their binary-choice judgments were influenced by alternative categories. This novel finding suggests that the way in which category knowledge is used in prediction depends critically on the form of the prediction.
authors.affiliation: University of Massachusetts, Amherst, Massachusetts, USA. michael.verde@plymouth.ac.uk
authors.forename: Michael F
authors.initials: MF
authors.lastname: Verde
authors.forename: Gregory L
authors.initials: GL
authors.lastname: Murphy
authors.forename: Brian H
authors.initials: BH
authors.lastname: Ross
mesh_terms: D003071:Cognition; D006801:Humans; D011930:Reaction Time; D012660:Semantics; D014796:Visual Perception