Volume 9, Number 2, Article 10, Pages 1-8 doi:10.1167/9.2.10 http://journalofvision.org/9/2/10/ ISSN 1534-7362
Uncovering gender discrimination cues in a realistic setting
Nicolas Dupuis-Roy
Département de Psychologie, Université de Montréal, Montréal, QC, Canada
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Isabelle Fortin
Département de Psychologie, Université de Montréal, Montréal, QC, Canada
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Daniel Fiset
Département de Psychologie, Université de Montréal, Montréal, QC, Canada
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Frédéric Gosselin
Département de Psychologie, Université de Montréal, Montréal, QC, Canada
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Abstract

Which face cues do we use for gender discrimination? Few studies have tried to answer this question and the few that have tried typically used only a small set of grayscale stimuli, often distorted and presented a large number of times. Here, we reassessed the importance of facial cues for gender discrimination in a more realistic setting. We applied Bubbles—a technique that minimizes bias toward specific facial features and does not necessitate the distortion of stimuli—to a set of 300 color photographs of Caucasian faces, each presented only once to 30 participants. Results show that the region of the eyes and the eyebrows—probably in the light-dark channel—is the most important facial cue for accurate gender discrimination; and that the mouth region is driving fast correct responses (but not fast incorrect responses)—the gender discrimination information in the mouth region is concentrated in the red-green color channel. Together, these results suggest that, when color is informative in the mouth region, humans use it and respond rapidly; and, when it's not informative, they have to rely on the more robust but more sluggish luminance information in the eye-eyebrow region.

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History
Received September 28, 2008; published February 10, 2009
Citation
Dupuis-Roy, N., Fortin, I., Fiset, D., & Gosselin, F. (2009). Uncovering gender discrimination cues in a realistic setting. Journal of Vision, 9(2):10, 1-8, http://journalofvision.org/9/2/10/, doi:10.1167/9.2.10.
Keywords
gender discrimination, color vision, bubbles, classification image, face perception
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