Research about Gender in the STEM Workplace: An Annotated Bibliography

January 8, 2015 at 8:37 am 2 comments

Below is just a bit of a really terrific annotated bibliography about gender in the STEM workplace — including a lot on computer science.  Great resource!

Science Faculty’s Subtle Gender Biases Favor Male Students by Corinne A. Moss-Racusina et al. In a study with 127 science faculty at research-intensive universities, candidates with identical resumes were more likely to be offered a job and paid more if their name was “John” instead of “Jennifer.” The gender of the faculty participating did not impact the outcome.

How Stereotypes Impair Women’s Careers in Science by Ernesto Reuben et al.Men are much more likely than women to be hired for a math task, even when equally qualified. This happens regardless of the gender of the hiring manager.

Measuring the Glass Ceiling Effect: An Assessment of Discrimination in Academia by Katherine Weisshaar. In computer science, men are significantly more likely to earn tenure than women with the same research productivity. [From a summary]

A Study on the Status of Women Faculty in Science at MIT by the Committee on Women Faculty. Reveals significant differences in terms of the distribution of resources and rewards to faculty by gender.

via Slow Searching: Research about Gender in the STEM Workplace.

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On Nerd Entitlement: Those who feel underprivileged are now the privileged STEM: Closing the Gender Gap | Pearson

2 Comments Add your own

  • 1. Tequoia  |  January 9, 2015 at 12:05 am

    This is what is called “Bayesian” statistics, Mark, if you’ve never heard of it.

    All these studies that send out a bunch of cvs are done by social scientists with a remarkable lack of understanding of basic empiricism. They fail to control for the most reasonable possibility that among names like “Emily Baker,” DeGubrius Muhammed,” and “Piccolo Luffy” some are more clearly recognizable as fictional people that don’t exist. This effect is probably getting even stronger now in the days of increasing mass social media. In an ideal world, after all, the expected result might be that exactly zero fictional people who don’t exist, having no background, not to be found on social media, get offered any phone calls or interviews or anything, and we’re just measuring the extent to which reality doesn’t match up to that standard.

    These studies clearly lack the proper control group – the real control group has to be fictional people who don’t exist. Find one study that even understands that; I don’t think there are any because the authors involved are too inept or corrupt. It’s ironic because a positive result, even if any authors flew under the radar with p-hacking and whatnot, would bring them a lot of fame and allow them to trumpet their personal careers to the skies, but incompetence is probably at least as strong a factor as motivated bias against other fields by the social scientists.

    If you don’t know what responses you get to a control group of clearly fictional people then you have nowhere to stand on in the first place, nothing to attempt to contrast statistically significant results to.

    In a sense it doesn’t really explain anything to see what responses test subjects have to “Emily Baker” and “DeGubrius Muhammed” when you don’t have a control group that is not based on any noticeable human racial, ethnic, or gender group, the “Piccolo Luffys” of the world. It doesn’t reject the null hypothesis that people are correctly discriminating along a continuum of determining that fictional people who don’t exist are in fact such.

    There still is the ethical issue that the explosion of these types of studies wastes people’s time and hurt actual job and academic candidates but all the people in social science fields need to be told to manage to do one single study with proper controls, blindedness, preregistration and so on.

  • 2. oh2bwise  |  January 9, 2015 at 10:20 am

    While this is an interesting an important contribution to the literature, it perpetuates the myth of sex = gender when this is simply not true anymore. Further, it invisiblizes all of those individuals who are transgender-identified and who work in the STEM disciplines. I would argue that you are missing an important and very intelligent group of individuals and that the literature in this field needs to correct its terminology and be far more inclusive when future research is initiated.


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