Geometric and featural representations in semantic concepts.

We explore the adequacy of two types of similarity representation in the context of semantic concepts. To this end, we evaluate different categorization models, assuming either a geometric or a featural representation, using categorization decisions involving familiar and unfamiliar foods and animals. The study aims to assess the optimal stimulus representation as a function of the familiarity of the stimuli. For the unfamiliar stimuli, the geometric categorization models provide the best account of the categorization data, whereas for the familiar stimuli, the featural categorization models provide the best account. This pattern of results suggests that people rely on perceptual information to assign an unfamiliar stimulus to a category but rely on more elaborate conceptual knowledge when assigning a familiar stimulus.

Dutch norm data for 13 semantic categories and 338 exemplars.

A data set is described that includes eight variables gathered for 13 common superordinate natural language categories and a representative set of 338 exemplars in Dutch. The category set contains 6 animal categories (reptiles, amphibians, mammals, birds, fish, and insects), 3 artifact categories (musical instruments, tools, and vehicles), 2 borderline artifact-natural-kind categories (vegetables and fruit), and 2 activity categories (sports and professions). In an exemplar and a feature generation task for the category nouns, frequency data were collected. For each of the 13 categories, a representative sample of 5-30 exemplars was selected. For all exemplars, feature generation frequencies, typicality ratings, pairwise similarity ratings, age-of-acquisition ratings, word frequencies, and word associations were gathered. Reliability estimates and some additional measures are presented. The full set of these norms is available in Excel format at the Psychonomic Society Web archive, www.psychonomic.org/archive/.