We’ve had a surge of self-help articles and books telling women how to navigate a biased system. But, fifty years after sex discrimination was first made illegal, shouldn’t the focus be on how to stop the bias in the first place?
In this two-part series, I’ll first discuss how implicit biases harm women in the workplace and then cover some of the steps we can take to reduce bias.
Identifying the Problem
Many male managers believe that the glass ceiling has been shattered. This opinion, however, is not shared by their female counterparts, who know from experience that sex discrimination is alive and well in the workplace. While overt discrimination has been on the decline for the past half-century, subtle forms of discrimination are still pervasive. This is especially true in high-level jobs where criteria for advancement are more subjective. Even well-meaning executives make judgments and take actions that reflect stereotypes and implicit attitudes that disadvantage female candidates for promotion.
In the past 20 years, there has been an explosion of research about what has come to be called cognitive or implicit bias. It all begins with the research proving that even the best-intentioned people harbor biases. This is true of men and woman of all ages and races; no one is immune. It’s not that we set out to judge women or minorities more harshly or treat them less favorably. What happens instead is that our internalized stereotypes and assumptions about certain groups of people end up influencing our judgments and evaluations without us realizing it.
As psychologist Virginia Valian has explained in her book Why So Slow? The Advancement of Women,
“A woman does not walk into the room with the same status as an equivalent man, because she is less likely than a man to be viewed as a serious professional.”
People hold gendered expectations, and women who don’t meet them are viewed as less capable. For example, if asked to visualize a computer programmer, for example, one will likely think of a man (probably “geeky” and younger); someone who doesn’t fit that image will then be at a disadvantage as people wonder if she’s “as good.”
When a man succeeds, his success is seen as confirmation of his innate ability, whereas a woman’s success is often attributed to luck or simplicity of the task. When she fails, however, her failure is seen as reflection of her (lack of) ability.
It gets even more complicated when assessing leadership, particularly in jobs that are perceived as masculine. Male leaders may be judged better than female leaders who are equally effective, but who lead with a less aggressive style. Attitudes about proper gender roles positively affect performance evaluations for leaders who conform to gender norms, and negatively affect performance evaluations of women who are engaged in nontraditional employment.
Gender norms can produce a double-bind effect. In some work environments women must speak more (or louder) than men if they want to get their ideas noticed, but when they do, they are derided as pushy. In problem-solving situations social scientists have observed that women get more negative facial expressions from both male and female peers, and are perceived less positively than men, even when they follow the same script as males.
Even “neutral” evaluators can be affected. When observing a woman struggling to be heard by others, receiving negative facial expressions, and having her points ignored, outside evaluators may attribute the reaction of peers to the woman’s lesser ability, or to her bossiness, rather than to gender bias. Professor Valian describes how people who would never endorse overt “statements such as, ‘Women do not command respect from their subordinates,’ may nevertheless feel comfortable saying, ‘Lee does not command respect from her subordinates.’ The latter comment is just a ‘fact’ about Lee, arrived at through impartial and fair observation.”
While each such instance on its own may be considered inconsequential, over the course of a woman’s career, they combine to undermine career success.
Subtle biases can lead to huge differences in how people are treated based on their perceived sex. In a 2012 study, Yale-based researchers sought to explore differences in how science faculty from large research universities rate applications for a lab manager position based on the perceived sex of the applicant. They sent 127 volunteer professors from six research institutions the application of an undergraduate science student who had applied for a lab manager position. Each of the professors received the same materials, except that some were randomly assigned the name of a female student while others were assigned a male name. They were asked to rate the student’s competence and hireability, as well as the amount of salary and mentoring they would offer the student.
The results were startling:
- — The female student was deemed less competent (on a 5-point scale as with the other measures in this study, rated 3.33 by male faculty and 3.32 by female faculty as compared to the male rated 4.01 and 4.1).
- — The female student was deemed less hirable (rated 2.96 by male faculty and 2.84 by female faculty as compared to the male rated 3.74 and 3.92).
- — The female student was offered a mean starting salary of $26,507.94 as compared to $30,238.10 offered to the male student.
- — The female student was offered less mentoring (a rating of 4.0 by male faculty and 3.91 by female faculty as compared to the male rated 4.74 and 4.73).
- — The female student was evaluated as being more likeable, but that did not translate into positive perceptions of her competence of benefits in terms of a job offer, a higher salary, or more mentoring.
These results were consistent across gender, age, scientific discipline, and tenure status. The researchers concluded that faculty gender bias, unconscious and unintended, impedes women’s full participation in science.
Similar effects were observed in another study that focused on race. In a study targeting the legal profession, researchers enlisted five law partners to draft a memo on trade secret issues that would be presented as if written by a third-year litigation associate. They deliberately inserted 22 errors (including spelling, grammar, technical writing, factual, and analytical errors). Sixty law firm partners of different backgrounds were recruited to participate in a “writing analysis study,” and asked to review the legal memo written by “Thomas Meyer.” Half were told that the author was a white associate and half were told he was black.
Stark differences resulted in the assessments:
- — On average, partners found 2.9 of the 7 spelling grammar in white Thomas’s memo as compared to 5.8 of the errors in African-American Thomas’s memo.
- — Partners found an average of 4.1 of the 6 technical writing errors in white Thomas’s memo as compared to 4.9 in African-American Thomas’s memo.
- — Partners found an average of 3.2 of the 5 errors in facts in white Thomas’s memo as compared to 3.9 in African-American Thomas’s memo.
- — Partners provided 11 edits or comments on formatting for white Thomas while making 29 for African-American Thomas.
- — Partners described white Thomas as someone who “has potential” with “good analytical skills” and a “generally good writer but needs to work on. . . .”
- — They described African-American Thomas as follows: “needs lots of work,” “can’t believe he went to NYU,” and “average at best.”
- — These biases were found across the spectrum of sex, race, and other traits.
The authors’ analysis is on point:
“When expecting to find fewer errors, we find fewer errors. When expecting to find more errors, we find more errors. That is unconscious confirmation bias. Our evaluators unconsciously found more of the errors in the “African American” Thomas Meyer’s memo, but the final rating process was a conscious and unbiased analysis based on the number of errors found. When partners say that they are evaluating assignments without bias, they are probably right in believing that there is no bias in the assessment of the errors found; however, if there is bias in the finding of the errors, even a fair final analysis cannot, and will not, result in a fair result.”
So what do we do? First, we must stop pretending to be sex blind, color blind, or blind to any other differences. Despite our best intentions, we are not. In fact, research has shown that people who most value fairness and objectivity are particularly likely to fall prey to biases, in part because they are not on guard against them.
This is not an easy task. Fifty years after the enactment of the Civil Rights Act of 1964, we can all agree that intentionally discriminating against someone because of her sex or race is an act that is morally reprehensible as well as illegal. But can we equally embrace the lesson learned from years of social science research into implicit bias – that we all harbor biases? Unless and until individuals and organizations are willing to grapple with this uncomfortable truth, we will be unable to dismantle these hidden barriers head on.