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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
A formal ideal-based account of typicality
Wouter Voorspoels1, Wolf Vanpaemel, Gert Storms
1University of Leuven, Leuven, Belgium. wouter.voorspoels@psy.kuleuven.be
Psychonomic Bulletin & Review
|June 30, 2011
Summary
The ideal dimension model (IDM) better explains category typicality than exemplar or prototype models. This suggests abstract ideals, not just specific examples, represent natural language concepts.
Area of Science:
- Cognitive Psychology
- Computational Linguistics
- Cognitive Science
Background:
- Traditional models represent categories using exemplars or prototypes.
- Barsalou proposed categories can be represented by abstract ideals.
Purpose of the Study:
- To develop and test the ideal dimension model (IDM) for natural language concepts.
- To compare the IDM's performance against exemplar and prototype models.
- To investigate how abstract representations influence category typicality.
Main Methods:
- Developed the ideal dimension model (IDM).
- Tested the IDM on typicality gradients for 11 superordinate natural language concepts.
- Employed Bayesian model evaluation to contrast the IDM with exemplar and prototype models.
Main Results:
- The IDM demonstrated superior goodness of fit and generalizability compared to exemplar and prototype models.
- The IDM effectively captured the typicality gradient for natural language concepts.
- Findings challenge the dominance of exemplar-based category representations.
Conclusions:
- Superordinate natural language categories can be represented by abstract ideal representations.
- The ideal dimension model offers a more effective account of category typicality.
- Cognitive models should consider abstract summary representations for conceptual categorization.
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