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The One-to-One Constraint in Analogical Mapping and Inference
Daniel C Krawczyk1, Keith J Holyoak, John E Hummel
1University of California, BerkeleyUniversity of California, Los Angeles.
This study on analogical reasoning found that while people sometimes map one element to multiple others when generating comparisons, they avoid this in inferences. Multiple correspondences arise from separate, similar mappings, not single complex ones.
Area of Science:
- Cognitive Psychology
- Cognitive Science
- Psychology
Background:
- Analogical reasoning theories posit a one-to-one constraint, preventing single elements from mapping to multiple elements across analogs.
- Empirical data shows violations of this constraint during mapping generation but not during inference generation.
- Previous studies on nonisomorphic analogs are limited and methodologically flawed.
Purpose of the Study:
- To investigate the generation of mixed inferences from combining information from two potential mappings.
- To examine whether participants produce mixed inferences when presented with nonisomorphic analogs.
Main Methods:
- Participants were tasked with generating explicit mappings between analogs.
- The study aimed to elicit mixed inferences by presenting scenarios that could result from combining two mappings.
- The focus was on analyzing the nature of correspondences generated by participants.
Main Results:
- Participants generated two-to-one correspondences when explicitly asked for mappings.
- However, participants did not produce mixed inferences, even when presented with opportunities.
- Multiple correspondences were observed to stem from multiple, separate isomorphic mappings, not a single homomorphic mapping.
Conclusions:
- The one-to-one constraint in analogical reasoning appears robust during inference generation, even with nonisomorphic analogs.
- Observed multiple correspondences are likely a result of parallel isomorphic mappings rather than complex homomorphic ones.
- This suggests distinct cognitive processes underlie mapping generation versus inference in analogical reasoning.
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