A unified quantitative approach to modeling subjects ' identification and categorization of multidimensional perceptual stimuli is proposed and tested. Two subjects identified and categorized the same set of perceptually confusable stimuli varying on separable dimensions. The identification data were modeled using Sbepard's (1957) multidimensional scaling-choice framework. This framework was then extended to model the subjects ' categorization performance. The categorization model, which generalizes the context theory of classification developed by Medin and Schaffer (1978), assumes that subjects store category exemplars in memory. Classification decisions are based on the similarity of stimuli to the stored exemplars. It is assumed that the same multidimensional perceptual representation underlies performance in both the identification and Categorization paradigms. However, because of the influence of selective attention, similarity relationships change systematically across the two paradigms. Some support was gained for the hypothesis that subjects distribute attention among component dimensions so as to optimize categorization performance. Evidence was also obtained that subjects may have augmented their category representations with inferred exemplars. Implications of the results for theories of multidimensional scaling and categorization are discussed.

Experiments were conducted in which Ss made classification, recognition, and similarity judgments for 34 schematic faces. A multidimensional scaling (MDS) solution for the faces was derived on the basis of the similarity judgments. This MDS solution was then used in conjunction with an exemplar-similarity model to accurately predict Ss ' classification and recognition judgments. Evidence was provided that Ss allocated attention to the psychological dimensions differentially for classification and recognition. The distribution of attention came close to the ideal-observer distribution for classification, and some tendencies in that direction were observed for recognition. Evidence was also provided for interactive effects of individual exemplar frequencies and similarities on classification and recognition, in accord with the predictions of the exemplar model. Unexpectedly, however, the frequency effects appeared to be larger for classification than for recognition. The purpose of this study was to provide tests of a model for relating perceptual classification performance and oldnew recognition memory. The model under investigation is the context theory of classification proposed by Medin and

This article is based on a doctoral dissertation submitted to the University of California, Santa Barbara, by W. Todd Maddox. Partial support was provided by National Science Foundation Grants BNS88-19403, DBS92-09411, and SBR-9514331 and by an Arizona State University Faculty-Grant-in-Aid

In 2 sets of experiments, the authors investigated the basis for old-item distinctiveness effects in perceptual recognition, whereby distinctive old items are recognized with higher probability than are typical old items. In Experiment 1, distinctive old items were defined as those lying in isolated regions of a continuous-dimension similarity space. In this case, any beneficial effects of distinctiveness were absent or small, regardless of the structure of the test list used to assess recognition memory. In Experiment 2, distinctive items were defined as those objects containing certain discrete, individuating features. In this case, large old-item distinctive effects were observed, with the nature of the effects being modulated by the structure of the test lists. A hybrid-similarity exemplar model, combining elements of continuous-dimension distance and discrete-feature matching, was used to account for these distinctiveness effects in the recognition data. According to global-activation models of old–new recognition memory, observers make recognition judgments on the basis of the overall familiarity of test objects. Presentation of a test object is assumed to give rise to a global activation of information stored in memory. The greater this global activation, the greater is the sense of familiarity associated with the object, and so the greater is the probability with which an observer judges the object to be old