Acknowledge Your Looks To Grab Male-Dominated Jobs

NEW YORK: For attractive women who apply for male-dominated jobs, acknowledging their looks and appearances can put brakes on the male bias against them, says a research. Past research shows physical beauty can be detrimental to women applying for masculine jobs.
But the new study is the first to provide a method for curtailing such prejudice against attractive women. Researchers from the University of Colorado Boulder in the US identified two main types of sexism that cause people to mentally disqualify women from masculine jobs.
"While 'benevolent sexism' causes men to see women as incapable and in need of protection from job difficulties, 'hostile sexism' causes them to see women as violators of gender roles, encroaching on job turf that's rightfully male," explained lead study author Stefanie Johnson, assistant professor of management and entrepreneurship.
For the study, 355 participants were divided into three groups. Each group looked at fictitious applications for a construction job opening.
"The raters who received the application of the attractive woman, who had acknowledged her appearance or sex, gave higher marks than those who received the application of the attractive woman who hadn't acknowledged either," Johnson added. The findings revealed two underlying types of sexism at play in the interview.
"If you score higher on 'hostile sexism' and the beautiful female applicant acknowledges her appearance and sex, you rate her less negatively - you still might hate her for being there but a little less. If you are a 'benevolent sexist' and she acknowledges, you rate her more positively," Johnson commented.
Another issue they explored during the study was unattractive women who acknowledge their looks when applying for masculine jobs, said Johnson.
There was no benefit to the acknowledgment, they found. "In fact, it made the situation worse. They received lower ratings," Johnson pointed out. The paper was published in the journal Organizational Behavior and Human Decision Processes.

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