ERIC Number: EJ1080380
Record Type: Journal
Publication Date: 2015-Nov
Abstractor: As Provided
An Exemplar-Model Account of Feature Inference from Uncertain Categorizations
Nosofsky, Robert M.
Journal of Experimental Psychology: Learning, Memory, and Cognition, v41 n6 p1929-1941 Nov 2015
In a highly systematic literature, researchers have investigated the manner in which people make feature inferences in paradigms involving uncertain categorizations (e.g., Griffiths, Hayes, & Newell, 2012; Murphy & Ross, 1994, 2007, 2010a). Although researchers have discussed the implications of the results for models of categorization and inference, an explicit formal model that accounts for the full gamut of results has not been evaluated. Building on previous proposals, in this theoretical note I consider the predictions from an exemplar model of categorization in which the inferred category label becomes a new feature of the objects. The model predicts a priori, a wide range of robust results that have been documented in this literature and can also be used to interpret effects of experimental manipulations that modulate these results. The model appears to be an excellent candidate for understanding the manner in which specific exemplar information and category inferences are combined to generate inferences about new features of objects.
Descriptors: Models, Classification, Inferences, Cognitive Psychology, Experimental Psychology, Observation, Probability, Visual Stimuli, Equations (Mathematics), Correlation, Simulation
American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: firstname.lastname@example.org; Web site: http://www.apa.org
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Sponsor: US Air Force (DOD), Office of Scientific Research (AFOSR)
Authoring Institution: N/A
Grant or Contract Numbers: FA95501410307