Abstract
| Original language | English |
|---|---|
| Journal | Political Psychology |
| Publication status | Submitted - 2019 |
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Leading or Cheery-leading : the Gender Gap in Political Smiles. / Koo, Se Jin.
In: Political Psychology, 2019.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Leading or Cheery-leading
T2 - the Gender Gap in Political Smiles
AU - Koo, Se Jin
PY - 2019
Y1 - 2019
N2 - The socially-ascribed devaluation of women’s status persists in many countries across varying levels of development and democracy. In these various settings, women are often assumed to make others feel comfortable by, for instance, smiling. However, the empirical evidence supporting the operation of gender stereotypes in political spheres is inconclusive. To fill this gap, this study addresses the questions of (1) whether women candidates smile more than their male peers and (2) whether smiling equally helps female and male candidates win elections. For the purposes of this study, a biometric artificial intelligence (AI) application detecting facial emotions in images is used to measure smiles. The results demonstrate that female candidates smile more than male candidates in elections and that women are more incentivized to smile, especially when they run an electoral race with many competing candidates, suggesting that the role of gender stereotypes in elections grows as the information cost increases.
AB - The socially-ascribed devaluation of women’s status persists in many countries across varying levels of development and democracy. In these various settings, women are often assumed to make others feel comfortable by, for instance, smiling. However, the empirical evidence supporting the operation of gender stereotypes in political spheres is inconclusive. To fill this gap, this study addresses the questions of (1) whether women candidates smile more than their male peers and (2) whether smiling equally helps female and male candidates win elections. For the purposes of this study, a biometric artificial intelligence (AI) application detecting facial emotions in images is used to measure smiles. The results demonstrate that female candidates smile more than male candidates in elections and that women are more incentivized to smile, especially when they run an electoral race with many competing candidates, suggesting that the role of gender stereotypes in elections grows as the information cost increases.
M3 - Article
JO - Political Psychology
JF - Political Psychology
SN - 0162-895X
ER -