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acquisition analyses Average absolute deviation C-L procedure C-L training C-L/Profile calculated in terms Category B 1100 category information category instances category learning category member category representation category-level information category-level representation category-level usage central tendency Concept-Learning Confidence Ratings Context Independent cue context model control conditions dissertation effect experiment experimental conditions experimental hypothesis Experimental Psychology Feature Sortings Condition feature-value four characteristics independent cue model initials Instance Identification Accuracies instance variability instance-level and category-level instance-level encoding instance-level information instance-level representation internal representation learner Medin old profiles P-A training P-A/Profile similarity ratings Paired-Associates parameter Patrick Dwyer Profile Feature Sortings profiles are calculated prototypic instance prototypic patterns representation of categories respective categories i.e. RETURN key Second Test Similarity Ratings Condition squared deviations subjects Table Test of Category training instances training procedure training profiles Training/Profile Feature Sortings Training/Profile Similarity Ratings transfer profiles Type of Training Type of Usage University of California Usage Task values variable