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Guilt by association and honor by association: The role of acquired equivalence

Overview of attention for article published in Psychonomic Bulletin & Review, December 2012
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Title
Guilt by association and honor by association: The role of acquired equivalence
Published in
Psychonomic Bulletin & Review, December 2012
DOI 10.3758/s13423-012-0346-3
Pubmed ID
Authors

Mikaël Molet, Jessica P. Stagner, Holly C. Miller, Thierry Kosinski, Thomas R. Zentall

Abstract

Guilt by association and honor by association are two types of judgments that suggest that a negative or positive quality of a person or object can transfer to another person or object, merely by co-occurrence. Most examples have been demonstrated under conditions of direct associations. Here, we provide experimental evidence of guilt by association and honor by association via indirect associations. We show that participants may treat two individuals alike if they have been separately paired with a common event using an acquired-equivalence paradigm. Our findings suggest that association fallacies can be examined using a paradigm originally developed for research with nonhuman animals and based on a representation mediation account.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Student > Bachelor 5 15%
Professor 4 12%
Student > Master 4 12%
Researcher 3 9%
Other 6 18%
Unknown 7 21%
Readers by discipline Count As %
Psychology 12 35%
Business, Management and Accounting 2 6%
Arts and Humanities 2 6%
Medicine and Dentistry 2 6%
Economics, Econometrics and Finance 2 6%
Other 3 9%
Unknown 11 32%