Alignment with gender stereotypes predicts success in tech
Existing research and policy often focus on building women’s technical skills—or at least their confidence in their technical skills—necessary to succeed in tech jobs. However, new research conducted by scholars at the Clayman Institute finds the cultural image of tech as a space for coding-obsessed, geeky guys contributes more powerfully to significant gender gaps in tech.
The Silicon Valley tech universe is notorious for its toxic, masculine culture to such an extent that the term “brogrammer” has emerged as a way to characterize how the tech culture alienates women employees and potential job candidates. As venture capitalist Jenn Wei reflected in an article at the Washington Post, “When most people think of the average tech entrepreneur, the pale guy who codes while playing World of Warcraft in his gadget-filled basement pops up.” While, of course, women can be tech geeks too, these cultures often make women feel like they don’t fit in. Women hold only 24% of jobs in STEM fields, and while 40% of men with STEM degrees work in STEM jobs, only 26% of women do.
According to a wealth of academic research, gender stereotypes impede women’s entry and persistence in STEM fields by affecting women’s performance, self-assessments of ability, sense of belonging, and ultimately their interest in pursuing STEM majors and careers. But current change efforts often focus on young women entering the pipeline. Therefore, such efforts run the risk of assuming that stereotypes have less influence on women further in their careers.
Using a sample of approximately 1,800 tech workers from seven firms in Silicon Valley, drawn from a survey conducted jointly by the Clayman Institute and the Anita Borg Institute for Women and Technology, we asked whether stereotypes continue to have a negative effect on women once they are on the job. Are women working in tech careers less likely than men to believe they align with the stereotypical image of a successful tech worker? If so, how do these beliefs affect work outcomes like identification with the tech field, perceptions of supervisor treatment, and plans to switch career fields?
We defined two types of alignment: skill and cultural. Skill alignment refers to the extent to which tech employees believe they possess the skills of a successful tech worker, whereas cultural alignment measures the extent to which tech employees believe they match the attributes of a successful tech worker. By comparing each employee’s self-ratings to their ratings of successful tech workers, we generated scales of alignment. The cultural scale included traits such as “geeky,” “obsessive,” and “assertive,” and the skill scale included descriptors like “highly mathematical” and “analytical.”
We find men are more likely than women to believe they have the traits and skills of a successful tech worker. While 56% of the men in our sample align culturally, only 37% of women do. This is particularly shocking given that the women in our sample are all currently working in tech jobs, yet fewer than half believe they have the cultural traits of a successful tech worker. On the skill dimension, the gender difference is statistically significant but smaller: 66% of men report skill alignment, compared to 53% of women.
Furthermore, we also find these gender gaps in alignment predict important work outcomes. Having positive skill alignment significantly impacts the extent to which employees identify with the tech profession; those who believe they have the skills to be successful are also more likely to identify with the tech profession. Cultural alignment similarly has a significant impact on identification with the tech profession, but it also impacts the extent to which employees identify with their companies, believe their supervisors value their opinions and assign them high-visibility projects, and, importantly, their plans to switch career fields in the next 12 months.
Because women are less likely than men to believe they match the cultural image of successful tech workers, they are less likely to identify with the tech field, less likely to report positive supervisor treatment, and more likely to consider switching career fields. We also find senior-level women tend to report less stereotypical views of successful tech workers compared to early career women, even though their views of themselves stay largely the same. Therefore, it may be easier to change the images surrounding tech rather than changing women’s images of themselves.
Simply getting more women to enter STEM fields, while helpful, will not solve the gender problem. Our findings suggest that if tech companies could improve their cultural environments, they could retain more women. Because, as long as cultural stereotypes continue to make women feel like they don’t fit in, women will be less likely to identify with their professions and more likely to leave tech jobs in higher numbers than men.
One encouraging example of positive change occurred at Carnegie Mellon, which increased the percentage of women majoring in computer science from 7% to 42% in five years. Among other changes, Carnegie Mellon transformed the cultural image of computer science at their university through concerted training and outreach efforts. While it may be hard to change widely shared cultural stereotypes, it’s possible for organizations to change the images that are present in their local environments. For example, experiments by Sapna Cheryan and colleagues demonstrate the significant effect room decorations, such as wall posters, can have on women’s interest in computer science.
Companies can engage in efforts such as emphasizing the real-world impacts of their work, featuring women engineers as role models, and presenting multiple pathways to success. Companies can also use more inclusive language in their job descriptions, performance evaluations, and company values.
By making the image of success more inclusive, we can hopefully do more than put women into tech jobs—we can keep them there and enable them to advance.