What's different between female STEM workers and those in other professions?

Many studies of women in STEM use men as a referent group to women: how do women compare to men in CS with regard to retention, attitudes, discrimination, etc? While there's certainly benefit to using men as a referent group (and it's far, far better than no referent group at all), there's a threat to validity that we tend to overlook when studying women in CS: how much of what we see is an artifact of CS culture versus that of our wider society?

Triangulation using different referent groups is a good way to get around this issue. I've talked before about differences between women in CS vs. other STEM fields, differences between women in CS between different cultures, and differences over time/generations. But in every one of these posts, I've really only looked at scientists.

Glass et al's "What's So Special about STEM? A Comparison of Women's Retention in STEM and Professional Occupations" addresses another angle: what's different for women in STEM vs. women in other professional occupations? After all, women are more likely than men to leave other professional occupations such as business, medicine and law [1]. And in all these fields, substantial problems remain at the top: women may make up a substantial proportion of workers, but a tiny minority of those running the show.

The Glass et al Paper

To make the comparison of STEM women and non-STEM women, the Glass et al paper uses longitudinal data from the National Longitudinal Survey of Youth 1979. The longitudinal approach is a strength of the paper. A weakness, however, is that the women participating are a single generational cohort who entered the workforce in the late 80s/90s: "second generation" per my previous post.

Overall, Glass et al found that women in STEM jobs had more in common with women in non-STEM professional jobs -- and that "few differences in job characteristics emerge" overall. This is a rather important finding -- it means that if we work carefully, we can often generalize findings about women in the general workforce to women in the STEM workforce.

I say "carefully" since there were a few differences that they found. Here's what's unique to STEM women:

1. Women who are married to fellow STEM workers are nearly 100% more likely to stay in their STEM jobs than women married to non-STEM workers.
2. A higher education does not increase a STEM woman's likelihood of staying in a STEM career. In other occupations, such as medicine or law, the more advanced degrees a woman has, the more likely she'll stay in the field. Glass et al attribute to this to the type of work done by those with MSc/PhDs: the more education you need to do the job, the more likely it'll be isolating and in a "noxious" work environment for women.
3. Unlike non-STEM women who leave their jobs to stay at home, when STEM women leave their jobs, they overwhelmingly do so to fill non-STEM jobs, rather than to stay at home permanently. Switching to management explains almost a quarter of these job departures.

Those three differences aside, everything they looked at turned out to be the same for both STEM women and non-STEM women.

Similarities between female STEM and non-STEM workers

For both women in STEM jobs and women in professional non-STEM jobs, the following things are positively correlated with the retention of women in the workplace: Higher pay, job commitment, higher reported job satisfaction, longer time working in that career, and the presence of parental leave.

Sociologists have documented the "Work-Family Narrative" -- the cultural narrative that women leave (or struggle with) their jobs because they can't balance work and family. They've similarly documented that the majority of workplace interventions to improve the status of women focus on this narrative.

Yet, what Glass et al found is that primary propellant of women out of the workforce -- both STEM and non-STEM -- is not childcare. Nor is it lack of confidence or lack of training -- or lack of "leaning in".

The primary propellants are dissatisfaction with pay and promotion prospects. There's a ton of sociology papers out there finding similar results. Childcare might be the catalyst for acting on that dissatisfaction, but it's not the underlying cause.

This dissatisfaction is linked to a number of sources of inequality, such as being left out of the "boys networks", subconscious biases against women, open prejudice about the competence of women, and sexual harassment. Correspondence studies of women in STEM and other professional domains have consistently found that women are less likely to be thought worth of a promotion as an equally qualified man, less worthy of a higher salary, and less likable overall. And there's evidence that men in our society are promoted based on potential -- while women are promoted based on past accomplishments. This sort of unintentional, de facto discrimination is not unique to STEM.

The Work-Family Narrative as a Social Defense

The paper I linked to about the "Work-Family Narrative" -- by Padravic and Ely -- presents a rather compelling argument that the reason that people focus on this narrative is because it is an unconscious social defense. The Work-Family Narrative gives a way of thinking about the problems facing women in the professional workplace that doesn't involve coming to terms with discrimination and systematic problems in the workforce.

Padravic and Ely also argue that this narrative similarly allows people to keep their cultural stereotypes in tact: women are the caregivers, men are the workers -- and so women have a hard time in the workforce because they must balance their position as caregiver. I've noted before that our brains are wired to keep cultural stereotypes in tact.

Discrimination is an ugly thing to talk about. I don't blame people for shying away from it. But it needs to be tackled to change the numbers of women in the workforce -- whether it be STEM or other fields. And it's important to compare STEM to the rest of society -- we need to know what's a STEM problem and what's even more systematic.