When it comes to determining the race of a stranger, our minds see more than skin color. That's the conclusion of a study co-authored by UCI sociologist
Andrew Penner, which was really quite simple when it came to the research. Viewers were shown images of the same man in business attire and a janitor's uniform. Photos of a different man were added to the mix, as were those of women. Above the photos were boxes marked “white” and “black” so the viewers could assign the race of each person shown. You can imagine what the National Institutes of Health and the National
Science Foundation-funded research found.
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Tracking the movements of each viewer's mouse as it selected the race of
the model, the researchers discovered that, initially, those in the
business clothing were most often perceived to be white, while those in
the janitor uniforms were usually ranked as black, despite the person in
the respective photos being the same person of the same race.
Keep
in mind that the person being tested may have ultimately chosen the
correct race of the model. What the researchers were after was that
initial assumption. The pattern grew more pronounced as faces became
more racially
ambiguous, the study concluded.
“Together, the findings show how stereotypes interact with physical cues
to shape person categorization, and suggest that social and contextual
factors guide the perception of race,” reads the abstract of the study “Looking the Part,” which was posted Sept. 26 on PLos ONE.
Penner's co-authors were psychology graduate student Jonathan B. Freeman, and Matthias Scheutz, computer science associate
professor at Tufts University; Nalini Ambady, psychology professor,
and Aliya Saperstein, sociology assistant professor, at Stanford.
OC Weekly Editor-in-Chief Matt Coker has been engaging, enraging and entertaining readers of newspapers, magazines and websites for decades. He spent the first 13 years of his career in journalism at daily newspapers before “graduating” to OC Weekly in 1995 as the alternative newsweekly’s first calendar editor.
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