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Why Are Gender Stereotypes So Difficult to Combat at Work?

Why Are Gender Stereotypes So Difficult to Combat at Work?

Here's what we learned from a failed gender equality training, and how workplaces can support women better.

 

The cops were concerned. They had investigated diversity in their large UK force and discovered that when female officers and staff reflected on their time being pregnant, only 39% felt supported by their managers.

My colleagues and I on the Behavioral Insights Team were tasked with creating a more supportive environment for those female employees, in collaboration with the police. This would entail, in part, improving how managers communicated with and supported their female employees: Of the 44 percent of women who were transferred to a different job after announcing their pregnancy, only half were consulted about it, and only 33 percent reported having a conversation with their line managers about maintaining contact throughout pregnancy.

We hypothesised that stereotyping, prejudice, and bias were at work. Perhaps managers assumed that their female subordinates needed to be shielded from the outside world, or that pregnancy would derail women's career ambitions.

We reasoned that changing our perspective would be beneficial. Imagining what other people are feeling and thinking is what perspective taking is all about. In lab studies, it improved communication, decreased stereotyping and prejudice, and increased empathy. We reasoned that it could do the same for the police force.

We created a 15-minute online perspective-taking task for line managers, asking them to imagine what it would be like to be pregnant. Managers first completed a short writing exercise designed to boost their self-efficacy by recalling a situation in which they overcame challenges to help another person. The managers were then given a brief description and picture of a pregnant police officer named Anna and asked to write a few sentences about her life as they imagined it, including her experiences at work and with other people. Finally, managers were encouraged to write down a few specific things they could do the following week to better support or communicate with their female employees.

The results surprised us. We found no positive impact in a randomised controlled trial of over 3,500 police managers. In fact, line managers who completed the perspective-taking task performed slightly worse in hypothetical scenarios asking how they would support female employees.

But perhaps we shouldn't have been so surprised: Gender stereotypes are notoriously sticky, in part because we are often unaware that we hold them, and they can influence impressions and judgments outside of conscious awareness. This means that even when someone genuinely believes they are treating men and women equally, stereotype-based biases can creep in. Gender stereotypes are also sticky because, despite progress in many areas of gender equality, such as universal suffrage and education, stereotypes persist in areas such as media and entertainment.

Changing people's conscious and unconscious beliefs about women is difficult, and programmes to do so have had limited success. This is supported by research on diversity and unconscious bias training: Trainings are mostly ineffective at changing behaviour and can even backfire, especially when they are mandatory and participants resent being sent to the course. Diversity trainings may also fail if they give the impression that the organisation has now resolved its diversity issues.

Similar mechanisms could have been at work in our study, explaining why our intervention was ineffective. Perhaps the line managers simply did not know how to be more supportive, even if they wanted to. Future interventions should provide specific tools for behaviour change, as well as organisational support to ensure that the new behaviours are maintained.

Despite these obstacles, there is hope. However, eliminating stereotypes in our heads will not provide a solution. Instead, according to behavioural economist Iris Bohnet, it will come from changing the stereotypes and biases within our systems, such as hiring and selection in organisations or how we assess students in schools.

Consider the hiring process. This is a system that consistently disadvantages women, as evidenced by the low number of women in senior positions. My colleagues on the Behavioral Insights Team recently launched Applied, a hiring platform designed to eliminate bias from hiring decisions. It does so by removing a candidate's name or other background markers that may affect a candidate's likelihood of being invited to an interview.

"Gender stereotypes are notoriously sticky, in part because we are frequently unaware that we hold them."
Dr. Tiina Likki

Performance reviews, for example, are ripe for debiasing. For example, using data from a large service organisation (the type of organisation is not specified in the research), MIT professor Emilio Castilla discovered that identical ratings in performance reviews were more likely to lead to a promotion for men than women (a phenomenon known as performance reward bias).

The first step that any organisation can take is to examine the data on its employees. Investigate gender differences in work allocation, development opportunities, salary and bonuses, and promotions and retention at each grade level. Where are the gaps? Why? Many employers in the United Kingdom have recently started looking at their data as a result of the new legal requirement to publicly report their gender pay gap, a measure that reflects the difference in hourly wages between men and women across all grades.

Once an organisation has identified potential systemic biases, it can begin to apply behavioural science. But that's only the beginning: any organisation must continue to monitor the original data, evaluate interventions, and set measurable goals for change.

Furthermore, when solutions fail, we must openly broadcast those failures. We can only get a sense of what truly works to improve gender parity if we show when initiatives have gone wrong or turned out to be a poor investment. I look forward to continuing to solve this problem and promise to keep sharing my failures—and successes—along the way.

This article was originally published on the Behavioral Scientist. Read the original article.