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Workplace Bias

November 17, 2019

Sometimes it’s hard to be a woman . . .

Tammy Wynette

Women in the workplace walk a tightrope between being perceived as too bossy or too weak. The same behaviors are labeled differently for male leaders and female leaders. A male leader who shouts, speaks over others, and ignores opposing viewpoints may command respect. A female leader who does the same, asserting opinions in meetings and disagreeing in group discussions, may be called “aggressive”. These differing leadership labels are powerful—and they trickle down to all levels of employment. The even can impact employment decisions.

Who would you choose to promote? Someone who is described in their performance evaluations as analytical or as compassionate? Who would you fire if you are downsizing? Someone perceived as arrogant or as inept?

Performance Evaluations

Research shows that language in performance evaluations is applied differently to men and women. A recent study of a military dataset of more than 4,000 participants and 81,000 evaluations examined objective and subjective performance measures. It included a list of 89 positive and negative leadership qualities.

The researchers found no gender differences in objective measures (e.g., grades, fitness scores, class standing). However, the subjective evaluations were different. Although there was no gender difference in the number of positive attributes assigned, women were assigned significantly more negative attributes.

The most commonly used positive term to describe men was analytical, while for women it was compassionate. The most commonly used negative term to describe men was arrogant, while for women, it was inept. The researchers found statistically significant gender differences in how often these terms were used when describing men and women — even though men’s and women’s performances were the same by more objective measures.


Evaluating the terminology used in performance measures is important. Instead of concentrating on subjective measurements, focus instead on objective measurements. As with any potential biases, bringing awareness to the issue is the first step.

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