Keywords: gender bias in STEM, Williams and Ceci, Moss-Racusin, gender blind, gender bias stem evaluation, gender blind hiring
Why Brilliant Girls Tend to Favor Non-STEM Careers
"Much of the “evidence” cited in support of discrimination does not actually demonstrate discrimination. For example, some gender gaps in funding and in graduate admissions have been conclusively shown to result, not from discrimination, but from the fact that women disproportionately apply in more competitive fields...
Lo and behold, there is not “pervasive evidence of” a gender gap in graduate enrollments, though there is a gap in some STEM fields. Completely consistent with the work by Su et al and by Wang et al, in nearly all fields that are about people, not only is there no gap disadvantaging women, there are actually more women than men! (Health, education, social and behavioral sciences, public administration, arts and humanities, and even biological sciences). The same report found that, overall, across all fields, the "gap" is in the "wrong" direction: 57 percent of enrollees in graduate programs are women.
Even if there is discrimination against women in these fields, it is not preventing women from entering those fields in droves. (Indeed, the logic of “gap = discrimination”—a logic I have repeatedly rejected but which runs rampant throughout the social sciences and general public—would have us believe there is widespread discrimination against men in most fields now)...
The list of social science victim groups is so long, that, most likely, almost all of us have been the target of discrimination or hostility at some point in our lives, rendering the question of whether some groups are more victimized than others muddier than it seems.
However equivocal the evidence for “bias” in the present may be as an explanation for the gender gap in STEM fields, there is ample evidence of bias. Scientific bias! Social scientists clearly "prefer" bias explanations over other, deeply important, scientifically rigorous, social developmental evidence...
The Moss-Racusin study [Ed: showing men are favored for a laboratory manager position] is, by conventional standards, the weakest of the studies. Its sample size is a fraction of that of the others. It studies a relatively minor situation (hiring lab managers). It was a single study (Su et al is a meta-analysis of scores of studies; Williams and Ceci reported five separate studies). In contrast to Wang et al, it only studied an event at a single time point; it did not follow people’s career trajectories.
This does not make Moss-Racusin et al a “bad” study; it is merely weaker on virtually all important scientific grounds than the others...
And yet, look at the citation counts. Others are citing the Moss-Racusin et al study out the wazoo. Now, Wang et al and Williams and Ceci came out later, so probably the most useful column is the last. Since 2015, the weaker Moss-Racusin study has been cited 50% more often than the other three combined! That means there are probably more papers citing the Moss-Racusin et al study and completely ignoring the other three, than there are papers citing even one of the other three! What kind of "science" are we, that so many "scientists" can get away with so systematically ignoring relevant data in our scientific journals?...
And that, gentle reader, is a gigantic scientific bias. It might even be beyond bias. Some might call it an “obsession” with discrimination and bias so severe that it is blinding many in our field to major findings regarding gender differences that contribute to preferences for different types of fields."
In other words, scientists prefer a weak study that allegedly demonstrates gender bias against women, rather than stronger ones that show why gender bias against women is unlikely (this exact same paper about hiring lab managers got thrown to me as an example of gender bias, and I got accused of cherry picking even though I had cited multiple studies including meta-analyses, against this one, single, solitary, relatively low powered study)
The Sticking Point: Why Men Still Outnumber Women in Science
"Back in 2005, you might have been forgiven for thinking that the gender wars were largely a thing of the past. The extreme blank slate view of earlier decades was losing its foothold as evolutionary psychology, neuroscience, and common sense steadily eroded the Nurture-Only explanation of sex differences. The political correctness that peaked in the 1990s seemed to have relaxed to the point where you could discuss differences between the sexes without fear of the sky falling on your head. Sure, there were still some gender radicals out there. But they no longer had the kind of sway they had in earlier decades.
Or so one might have thought. But 2005 was the year we learned that there were still limits to what you can say about sex differences, and severe consequences for stepping over the line. For 2005 was the year that Lawrence Summers, then president of Harvard University, was invited to give a speech at a Harvard conference on Diversifying the Science and Engineering Workforce...
One conference attendee, Nancy Hopkins, was so upset she stumbled out of the room, dizzy and nauseous...
A public debate staged soon after Summers' gaffe. The debaters were Harvard psychologists Steven Pinker and Elizabeth Spelke. Spelke argued that the sex difference is 100% nurture; Pinker argued that nature and nurture both contribute, but focused on possible biological contributions...
Our commitment to the moral principle (“don’t discriminate”) should not be made dependent on the outcome of the empirical question. Otherwise, notes Pinker, if it turns out men and women aren’t biologically identical, we’ll then have to conclude that discriminating on the basis of sex is OK after all…or we'll have to suppress the facts. Neither of these options is desirable. And nor is either necessary...
Notes Spelke, there are no sex differences in any of these basic mathematical competencies among infants or young children. Any differences appear only later. This, she argues, contradicts the idea that the differences trace to biology. It suggests instead that they emerge only once the forces of socialization sink their claws into us.
Unfortunately, the conclusion doesn't necessarily follow. The fact that sex differences are absent in infancy doesn't rule out a genetic explanation. Many sex differences emerge only at puberty. Indeed, that’s an important part of the definition of puberty. Furthermore, when we look closely, the usual explanations for the math differences—stereotype threat, math anxiety, Barbie dolls that say "Maths class is tough!"—are difficult to sustain. If girls are led to believe that they’re worse than boys at math, why do they get better grades in math class at school? If stereotype threat and math anxiety undermine their test-taking abilities, why does this happen on tests of some skills but not others? Is there a stereotype that girls are better at mathematical calculation but that boys are better at mathematical reasoning? Probably not...
Lesbians have spatial abilities comparable to those of straight men, and gay men have verbal abilities comparable to those of straight women...
The greater variability of males than females is not unique to humans. It’s found in many species and for many traits. In other species, we don’t hesitate to attribute the pattern to biology. When we find the same pattern in humans, shouldn’t we attribute it to the same cause, rather than to an entirely unique cause that coincidentally replicates the pattern we see in other animals?...
Bias and sexism presumably exist in all fields, but this hasn't stopped a flood of women going into prestigious non-STEM fields, such as law, medicine, and veterinary science...
In 2004-2005, only 20% of applications for faculty positions in mathematics were from women; however, 28% of the candidates interviewed were women, and 32% of those offered jobs were women. This is the opposite of what we’d expect if anti-female bias were pervasive in STEM departments.
At the very least, people in the bias-and-barriers camp should concede that the evidence is inconclusive. But this in itself suggests that any bias must be relatively weak—after all, if there were strong and pervasive bias, we would presumably have unambiguous evidence of it by now."
I didn't know even in 2005 liberals got so offended they got physically sick.
This is a good illustration of how those who say biological factors play a part always acknowledge social ones, but their opponents insist on tabula rasa.
And also of how the cliched response of "stereotype threat" is problematic
Contra Grant On Exaggerated Differences
(this is a response to the Business School Professor in Organisational Psychology who dismissed the Google "anti diversity" memo)
"Suppose I wanted to convince you that men and women had physically identical bodies. I run studies on things like number of arms, number of kidneys, size of the pancreas, caliber of the aorta, whether the brain is in the head or the chest, et cetera. 90% of these come back identical – in fact, the only ones that don’t are a few outliers like “breast size” or “number of penises”. I conclude that men and women are mostly physically similar. I can even make a statistic like “men and women are physically the same in 78% of traits”...
Galpin investigated the percent of women in computer classes all around the world. Her number of 26% for the US is slightly higher than I usually hear, probably because it’s older (the percent women in computing has actually gone down over time!). The least sexist countries I can think of – Sweden, New Zealand, Canada, etc – all have somewhere around the same number (30%, 20%, and 24%, respectively). The most sexist countries do extremely well on this metric! The highest numbers on the chart are all from non-Western, non-First-World countries that do middling-to-poor on the Gender Development Index: Thailand with 55%, Guyana with 54%, Malaysia with 51%, Iran with 41%, Zimbabwe with 41%, and Mexico with 39%. Needless to say, Zimbabwe is not exactly famous for its deep commitment to gender equality...
In the year 1850, women were locked out of almost every major field, with a few exceptions like nursing and teaching... everyone says [Ed: about engineering] “Aha! I bet it’s because of negative stereotypes!”
This makes no sense. There were negative stereotypes about everything! Somebody has to explain why the equal and greater negative stereotypes against women in law, medicine, etc were completely powerless, yet for some reason the negative stereotypes in engineering were the ones that took hold and prevented women from succeeding there...
The same patterns apply through pretty much every First World country...
Whenever I ask this question, I get something like “engineering and computer science are two of the highest-paying, highest-status jobs, so of course men would try to keep women out of them, in order to maintain their supremacy”. But I notice that doctors and lawyers are also pretty high-paying, high-status jobs, and that nothing of the sort happened there. And that when people aren’t using engineering/programming’s high status to justify their beliefs about gender stereotypes in it, they’re ruthlessly making fun of engineers and programmers, whether it’s watching Big Bang Theory or reading Dilbert or just going on about “pocket protectors”.
Meanwhile, men make up only 10% of nurses, only 20% of new veterinarians, only 25% of new psychologists, about 25% of new paediatricians, about 26% of forensic scientists, about 28% of medical managers, and 42% of new biologists.
Note that many of these imbalances are even more lopsided than the imbalance favoring men in technology, and that many of these jobs earn much more than the average programmer. For example, the average computer programmer only makes about $80,000; the average veterinarian makes about $88,000, and the average pediatrician makes a whopping $170,000...
Might young women be avoiding computers because they’ve absorbed stereotypes telling them that they’re not smart enough, or that they’re “only for boys”? No. As per Shashaani 1997, “[undergraduate] females strongly agreed with the statement ‘females have as much ability as males when learning to use computers’, and strongly disagreed with the statement ‘studying about computers is more important for men than for women’. On a scale of 1-5, where 5 represents complete certainty in gender equality in computer skills, and 1 completely certainty in inequality, the average woman chooses 4.2; the average male 4.03. This seems to have been true since the very beginning of the age of personal computers: Smith 1986 finds that “there were no significant differences between males and females in their attitudes of efficacy or sense of confidence in ability to use the computer, contrary to expectation…females [showed] stronger beliefs in equity of ability and competencies in use of the computer.” This is a very consistent result [Ed: This is empirical evidence against the chestnut that women are told they are incompetent with computers, have no confidence etc]...
Might girls be worried not by stereotypes about computers themselves, but by stereotypes that girls are bad at math and so can’t succeed in the math-heavy world of computer science? No. About 45% of college math majors are women, compared to (again) only 20% of computer science majors. Undergraduate mathematics itself more-or-less shows gender parity. This can’t be an explanation for the computer results.
Might sexist parents be buying computers for their sons but not their daughters, giving boys a leg up in learning computer skills? In the 80s and 90s, everybody was certain that this was the cause of the gap. Newspapers would tell lurid (and entirely hypothetical) stories of girls sitting down to use a computer when suddenly a boy would show up, push her away, and demand it all to himself. But move forward a few decades and now young girls are more likely to own computers than young boys – with little change in the high school computer interest numbers. So that isn’t it either...
One subgroup of women does not display these gender differences at any age. These are women with congenital adrenal hyperplasia, a condition that gives them a more typically-male hormone balance...
I mentioned that about 50% of medical students were female, but this masks a lot of variation. There are wide differences in doctor gender by medical specialty... A privilege-based theory fails – there’s not much of a tendency for women to be restricted to less prestigious and lower-paying fields – Ob/Gyn (mostly female) is extremely lucrative, and internal medicine (mostly male) is pretty low-paying for a medical job.
But the people/thing theory above does extremely well! Pediatrics is babies/children, Psychiatry is people/talking (and of course women are disproportionately child psychiatrists), OB/GYN is babies (though admittedly this probably owes a lot to patients being more comfortable with female gynecologists) and family medicine is people/talking/babies/children.
Meanwhile, Radiology is machines and no patient contact, Anaesthesiology is also machines and no patient contact, Emergency Medicine is danger, and Surgery is machines, danger, and no patient contact.
Here’s another fun thing you can do with this theory: understand why women are so well represented in college math classes. Women are around 20% of CS majors, physics majors, engineering majors, etc – but almost half of math majors! This should be shocking. Aren’t we constantly told that women are bombarded with stereotypes about math being for men? Isn’t the archetypal example of children learning gender roles that Barbie doll that said “Math is hard, let’s go shopping?” And yet women’s representation in undergraduate math classes is really quite good.
I was totally confused by this for a while until a commenter directed me to the data on what people actually do with math degrees. The answer is mostly: they become math teachers. They work in elementary schools and high schools, with people.
Then all those future math teachers leave for the schools after undergrad, and so math grad school ends up with pretty much the same male-tilted gender balance as CS, physics, and engineering grad school...
Silicon Valley was supposed to be better than this. It was supposed to be the life of the mind, where people who were interested in the mysteries of computation and cognition could get together and make the world better for everybody. Now it’s degenerated into this giant hatefest of everybody writing long screeds calling everyone else Nazis and demanding violence against them. Where if someone disagrees with the consensus, it’s just taken as a matter of course that we need to hunt them down, deny them of the cloak of anonymity, fire them, and blacklist them so they can never get a job again. Where the idea that we shouldn’t be a surveillance society where we carefully watch our coworkers for signs of sexism so we can report them to the authorities is exactly the sort of thing you get reported to the authorities if people see you saying...
This is the world we’ve built. Where making people live in fear is a feature, not a bug."
Comment: "My impression is that there were lots of women in CS in 1980 for the same reason there were lots of Jews in banking in 1800: they were banned from doing anything else. Computer programming was originally considered sort of a natural outgrowth of being a secretary (remember, 77% of data entry specialists are still female today, probably because it’s also considered a natural outgrowth of being a secretary). Women had lots of opportunity in it, and a lot of women who couldn’t break into other professions naturally went into it"