title: Why do we SLIP to the basic level? Computational constraints and their implementation.
abstract: The authors introduce a new measure of basic-level performance (strategy length and internal practicability; SLIP). SLIP implements 2 computational constraints on the organization of categories in a taxonomy: the minimum number of feature tests required to place the input in a category (strategy length) and the ease with which these tests are performed (internal practicability). The predictive power of SLIP is compared with that of 4 other basic-level measures: context model, category feature possession, category utility, and compression measure, drawing data from other empirical work, and 3 new experiments testing the validity of the computational constraints of SLIP using computer-synthesized 3-dimensional artificial objects.
authors.affiliation: Department of Psychology, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, Scotland. frederic.gosselin@umontreal.ca
authors.forename: F
authors.initials: F
authors.lastname: Gosselin
authors.forename: P G
authors.initials: PG
authors.lastname: Schyns
mesh_terms: D000328:Adult; D003210:Concept Formation; D003867:Depth Perception; D004193:Discrimination Learning; D005260:Female; D006801:Humans; D008297:Male; D011939:Mental Recall; D010364:Pattern Recognition, Visual; D011340:Problem Solving; D011601:Psychophysics; D011930:Reaction Time