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Using agreement probability to study differences in types of concepts and conceptualizers
Enrique Canessa1,2, Sergio E Chaigneau3,4, Sebastián Moreno5
1Center for Cognition Research (CINCO), School of Psychology, Universidad Adolfo Ibáñez, Av. Presidente Errázuriz 3328, Las Condes, Santiago, Chile. ecanessa@uai.cl.
Behavior Research Methods
|December 5, 2022
Summary
Agreement probability (p(a)) measures concept homogeneity. Concrete concepts show higher agreement than abstract ones, with visual experience influencing concrete concept descriptions in sighted versus blind individuals.
Area of Science:
- Cognitive Psychology
- Linguistics
- Neuroscience
Background:
- The Property Listing Task (PLT) elicits concept descriptions.
- Agreement probability (p(a)) quantifies homogeneity in PLT data.
- Understanding concept differences (concrete vs. abstract) across populations is crucial.
Purpose of the Study:
- To analyze differences between concrete and abstract concepts in sighted and blind populations using p(a).
- To investigate the influence of visual/perceptual information on concept representation.
- To evaluate the utility of p(a) for concept classification.
Main Methods:
- Utilized agreement probability (p(a)) as a homogeneity measure.
- Applied p(a) to analyze property lists from sighted and blind participants for concrete and abstract concepts.
- Assessed the statistical significance of differences in p(a) between groups.
Main Results:
- Concrete concepts exhibited higher homogeneity (p(a)) than abstract concepts in both sighted and blind groups.
- Concrete concepts were less homogeneous in the blind group compared to the sighted group.
- No statistically significant difference in homogeneity was found for abstract concepts between sighted and blind individuals.
Conclusions:
- p(a) effectively differentiates between concrete and abstract concepts.
- Visual/perceptual information significantly influences the homogeneity of concrete concept descriptions.
- Abstract concepts, relying on social/linguistic input, show similar homogeneity across sighted and blind populations.
- p(a) is a valuable tool for analyzing PLT data and studying concept representation.
Keywords:
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