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Competent and Cold: A Directed Content Analysis of Warmth and Competence Dimensions to Identify and Categorise Stereotypes of Scientists Portrayed in Meme-Based GIFs

Authors :
Fujiwara, Y.
Velasco, R. C. L.
Jones, L. K.
Hite, R. L.
Source :
International Journal of Science Education. 2022 44(4):694-715.
Publication Year :
2022

Abstract

Memes within animated graphical interchange formats (GIFs) are developed and shared by Internet users to communicate cultural ideas, symbols, or practices for a wide global audience. Among the billions of GIFs shared internationally, some portray scientists engaged in scientific work. Media and science education scholarship alike have evidenced how scientists are portrayed can influence social perceptions of science and contribute to stereotypes that deter youth's interest in and affinity to science and science occupations. To understand what social perceptions of science may manifest from new media (GIFs), the present study ascertained stereotypes using Warmth and Competence constructs from Fiske's Stereotype Content Model (SCM). The SCM utilizes high, medium, and low warmth and competence dimensions found in media-based imagery to illuminate stereotypes. Researchers coded and categorised 287 meme-based GIFs of scientists sourced the largest online GIF repository, Giphy. A directed qualitative content analysis found high-competence and low-warmth dimensions most represented within the sample that theoretically (per SCM) represent perceptions that contribute to an envious stereotype with elements of admiration and contempt. This study suggests that although there have been improvements in the portrayals of scientists in media, however, GIFs may preserve and perpetuate the trope of the competent, yet cold, scientist.

Details

Language :
English
ISSN :
0950-0693 and 1464-5289
Volume :
44
Issue :
4
Database :
ERIC
Journal :
International Journal of Science Education
Publication Type :
Academic Journal
Accession number :
EJ1350724
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1080/09500693.2022.2050560