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Comparing race, gender, age, and career categories in recognizing and grouping tasks
Author(s) -
Jingjing Song,
Lin Li
Publication year - 2020
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.9156
Subject(s) - categorization , race (biology) , perception , task (project management) , psychology , social psychology , computer science , artificial intelligence , gender studies , sociology , management , neuroscience , economics
The purpose of our research was to compare how participants weighed age, gender, race, and career categories in recognizing and grouping tasks. In Study 1, we used a category recognition task to compare participants’ speeds in recognizing information from different categories. The results showed that participants recognized the gender information most quickly, followed by career, race, and age information. In Study 2, a categorization task was used to compare participants’ category preferences. The results showed that the career category had the greatest weight, and the gender category had the lowest weight. Two targets who had different career identities were more possible considered as belonging to different groups than two targets with different gender, race or age identities. Our results have implications in understanding the weight of different categories, with gender and career category are the most important category that affects perception and evaluation.

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