How Gender Stereotypes Influence Emerging Career Aspirations

Posted by Sarah on November 24, 2010 · 6 mins read

I have just finished watching Shelly Correl’s talk on How Gender Stereotypes Influence Emerging Career Aspirations, a video filled with really great research to back up what I have been thinking about of late. I don’t want to summarise too much, I would say go and watch it, but for the main highlights…

Shelly is a professor of Sociology at Stamford University. She chose to research the affect of gender stereotypes on students choosing their careers, especially as they make decisions to enter Science Technology Engineering or Maths (STEM) subjects. She conducted numerous controlled experiments to find out how stereotypes influence the performance of tasks and also the subject’s self assessment of their ability to do the task. She found that when the subjects were primed with negative stereotypes prior, even when it was a simple as filling in demographic information, they performed worse that subjects who were not primed. Even more interesting, was subjects that were primed with positive stereotypes prior to the tasks performed better than the control group.

Another study conducted at Stamford compared the self assessment of male and female students who were equal in terms of grades and marks on tests. She found that the girls were more likely to underrate their ability than the boys were. She further showed that a person’s belief in their ability was a strong contributing factor for determining if they would pursue careers where that ability was needed. She therefore concluded that as girls underrate their ability in areas like maths and science, they don’t gravitate to subjects like AP Calculus in senior grades. She also showed that the opposite effect encouraged more girls into those subjects.

There is often outcry around attracting more women to STEM that either women are not capable or that they have no interested in these subjects. She brilliantly debunked these myths. The first by showing the bell curve of men vs women SAT maths scores, and proved that there was no significant difference between the two curves and the second myth by displaying a graph which showed a rise (trending upward) in the percentage of women represented in physics courses from 1977 to 2006, corresponding to a lot of time, money and effort spent by the National Science Foundation to encouraging women into these fields which indicates that it is working and that something can be done to make women more interested (good news for us).

She argues that there are four basic principals of how gender stereotypes affect people:

  • Stereotypic biases often occur out of awareness
  • Biases are more extreme in uncertain settings - when people don’t know what to do, gender stereotypes fill in the gaps
  • The impact of stereotypes change when beliefs in the local setting change
  • Stereotypes also bias the standards gatekeepers use to assess competence

This last point is interesting and she showed a few studies to support this point:

  • Experimental study of the evaluation of engineering internship application finds that women are judged by a harsher standard
  • Experimental study of the evaluation of police chief candidates find that evaluations change criteria when evaluating women vs men
  • Study of student evaluation of professors show female professors judged more harshly
  • Women leaders experience a double bind - when they wish to prove that they belong, they come across assertive and are not liked
  • Since stereotypes affect judgements of others we must change gender beliefs that are operating in an organisation not just change individual women’s beliefs. Therefore we need to fix organisations rather than fixing women.

So, what can be done? Shelley suggests three ways:

Control the message: what are the gender beliefs that are operating in the organisation? How does the organisation present itself? e.g. Carnie Mellon changed the way people saw computer science away from just geek which led in an increase in the percentage of women from 7% to 42%. In another study, two videos were shown to elite female maths students at Stamford about further education in maths; one video showed images with a balanced proportion of male and female engineers, and the other had an unbalanced group of mainly men - apart from the images the videos were identical. They found that the women who watched the balanced video had a more positive effect that the women who saw the unbalanced video, but even more interestingly there was a physical reaction to the unbalanced video, one which sociologists also see when people feel like they don’t belong.

Make performance standards clearer and communicate them clearly. Teach tacit knowledge. e.g. when female students dropped out of engineering courses they were asked their reason, which was in the majority that their grades were too low. However, these students were achieving higher grades than men that stayed in the course. By making the performance standards explicit, the students could have seen that their grades were satisfactory for the course and that low grades did not indicate failure in the course.

Hold gatekeepers accountable for gender disparities. It is important to keep thinking about how our policies and procedures affect career relevant decisions.

It was a great presentation, and she finished with three things that individuals can do - understand how stereotypes might affect your own career decision making; realize that negative feedback is common and productive; and promote organisation change.