Across the calculus sections, women outperformed men on grades.

Several recent studies have suggested that the gender gap in STEM fields is caused not by bias, but simply by different choices made by men and women. What the new research shows, Dasgupta said, is choice isn’t as simple as people think. “People assume that these choices are free choices, based on talent and interest and motivation,” Dasgupta said. “But these data suggest that the meaning of choices, of what it means to choose math or science, is more complicated. Even talented people may not choose math or science not because they don’t like it or are not good at it, but because they feel that they don’t belong.”

—Inoculation Against Stereotype by Scott Jaschik (Inside Higher Ed)

There is a common belief among some computer geek communities that women are underrepresented in STEM because we just don’t like it, and so we should celebrate differences instead of making women “miserable” by “forcing” us into careers we “don’t like”. This study would debunk that myth, if only most men in tech who discuss the topic of women in tech actually did some research on it, instead of leaving comments that make male geeks feel good about themselves and rationalize the gender imbalance in “their” field.

For other male geeks who insist that there are hard-wired brain differences in men and women, and argue that women’s brains are hard-wired against understanding math and science as well as men (instead of hard-wired against enjoying math and science), this part of the article should be emphasized:

Skeptics might wonder if some of the [gender] differences [in engagement] among students relate to how well the students know the material. The researchers checked for that and found that, across sections, women outperformed men on grades. So the data point to women losing confidence with male instructors — even if female students know the material as well as or better than their male counterparts.

Link: Inoculation Against Stereotype (Inside Higher Ed)

Women did not evolve against risk-taking and tech startups.

This is cross-posted at Geek Feminism.

There is a common idea that women are underrepresented in tech startups because we are “nurturing and not risk-taking enough by nature”, an idea often proposed and upvoted in Hacker News discussions. Roy F. Baumeister, Professor of Psychology, also argues something similar in his defense of Lawrence Summers’ hypothesis that fewer women than men have high innate ability in science. Professor Baumeister argues that men evolved to take risks, and women evolved to play it safe, because we are allegedly descendants of risk-taking men and risk-averse women.

However, there are a few problems with this explanation of why women are underrepresented among tech entrepreneurs. One problem is that top venture capitalist John Doerr consciously and deliberately invests in tech startups run by white men over women and racial minorities, and even encourages other VCs to follow his lead. Even more, it is understood that this is “the way the venture-capital industry operates”. While other industries call this “stereotyping” or “profiling”, VCs call it “pattern recognition”. In other words, there is systemic discrimination in the tech industry based on gender, as well as race and age.

Another problem with the hypothesis of female risk-aversion is that outside of the tech industry, women have been launching new businesses at twice the rate of men for three decades:

The phenomenal growth of women-owned businesses has made headlines for three decades—women consistently have been launching new enterprises at twice the rate of men, and their growth rates of employment and revenue have outpaced the economy.

If you were hacking since age 8, it means you were privileged.

Often, computer geeks who started programming at a young age brag about it, as it is a source of geeky prestige. However, most computer geeks are oblivious to the fact that your parents being able to afford a computer back in the 1980s is a product of class privilege, not your innate geekiness. Additionally, the child’s gender affects how much the parents are willing to financially invest in the child’s computer education. If parents in the 1980s think that it is unlikely their eight-year-old daughter will have a career in technology, then purchasing a computer may seem like a frivolous expense.

Because of systemic racism, class differences correlate with racial demographics. In the Racialicious post Gaming Masculinity, Latoya quotes a researcher’s exchange with an African American male computer science (CS) undergraduate:

“Me and some of my black friends were talking about the other guys in CS. Some of them have been programming since they were eight. We can’t compete with that. Now, the only thing that I have been doing since I was eight is playing basketball. I would own them on the court. I mean it wouldn’t be fair, they would just stand there and I would dominate. It is sort of like that in CS.”
– Undergraduate CS Major

Those “other guys” in CS are those white, male geeks who brag in CS newsgroups about hacking away at their Commodore 64s as young children, where successive posters reveal younger and younger ages in order to trump the previous poster. This disgusting flaunting of privilege completely demoralizes those of us who gained computer access only recently. However, CS departments—which tend to be dominated by even more privileged computer geeks of an earlier era when computers were even rarer—also assume that early computer adoption is a meritocratic measure of innate interest and ability.

Women prefer good-looking men to high-earning men.

Women prefer physically attractive men to high-earning men:

Discussing sexism in geek communities is more important than discussing gender imbalance.

Some female geeks use the discourse of increasing female representation in science, technology, engineering, and math (the “STEM” fields) as a proxy for addressing sexism in geek communities. Because countering sexism against women does not directly benefit men, some women reframe the issue of sexism by appealing to capitalist values. They argue that if women are better represented in STEM fields, it would lead to economic growth and technological innovation (and that this can be achieved through efforts to reduce gender bias).

However, this strategy backfires when male geeks interpret the movement to increase female representation in STEM fields as “social engineering”, i.e., feminists forcing women to do what we purportedly “dislike” (science, tech, engineering, and math). The subtext of this movement—which is that female geeks who love STEM topics have to endure sexism from male geeks or get out, and this is a Bad Thing^TM that needs to be fixed—is lost entirely.

Observe this Digg comment on the Bias Called Persistent Hurdle for Women in Sciences submission: