Here is the U.S., especially, we love to think the ivory tower is a meritocracy, and that the tribe of science is objective in all things — including how it treats its members. A nice little pile of data runs counter to this picture, however. A quick roundup:
- At Majikthise, Lindsay Beyerstein points us to the Nature profile of Ben Barres (subscription required). Barres had gender reassignment surgery (at age 42) in the middle of his career as a scientist — so he has some first hand knowledge of what it’s like to be a female scientist vs. what it’s like to be a male scientist. Lindsay also includes a link to a (free) Washington Post article about Barres, and this choice quote:
“By far,” Barres wrote, “the main difference I have noticed is that people who don’t know I am transgendered treat me with much more respect” than when he was a woman. “I can even complete a whole sentence without being interrupted by a man.”
- At Pandagon, Amanda Marcotte comments on the same Nature profile of Ben Barres, and connects it to the Great Algebra Flunking of 1990, a story that will make you want to build a time machine to go back and punch Amanda’s 7th grade math teacher for insisting that girls keep tidy, decorated notebooks to pass a freakig math class while boys just had to demonstrate that they could do math.
- While we’re on the subject of teachers who could use a thrashing, Leslie Madsen Brooks relates her tale of being the girl at the back of a physics class whose teacher had basically given up on the whole class. But, the student triumphs in this story (and her father gets extra points for a special dance at back-to-school-night). I think there’s a lesson here about students and parents having the courage to call shenanigans on teachers who are making lazy assumption about their students, whether they’re based on assumptions about gender or ethnicity or native ability or whatever else.
- Back to the Pandagon post, there is a beautiful comment that goes right to the question of how cultural assumptions make us think about the burden of proof in discussions of whether boys might be innately better at math and science than girls. Commenter Nancy writes:
I had an exchange of emails with Pinker over the Summers issue over a year ago.
He stopped writing back after I sent this:
———————-
“I noted that girls have increased their test scores relative to boys, in a time frame that would seem to exclude evolutionary affect. I speculated that you might then try to explain the test score improvements through nurture. I thought it was obvious why this was an example of having things both ways, but maybe not, so I’ll be more explicit – if the test scores changed in a faster-than-evolutionary time frame, why would you assume that it was nurture ameliorating the effects of nature, rather than the other way around – that the errors of nurture were fading away to allow nature to be revealed? Why is it nature when girls are failing, but nurture when they succeed? That’s what I mean by having it both ways. …”I’ve added the bold emphasis. Good stuff.
- Sciencewoman provides a number of other good women-in-science links that are worth your attention, as she regularly does.
Deeply entrenched societal assumptions are a dumb reason to lose scientific talent, and every effort ought to be made to turn students on to math and science, even the students who are going to go on to do other things with their lives. Let’s get with the program here!
Looking at college attendance and achievement currently in the US – 60% female, much better test scores and grades for women, I think that in 10 years or so we may see the exact opposite in academic disciplines – men complaining about bias and exclusion. Social issues vs ability are so obvious when turned around like that. I think think the political ramifications might be bad however – less support for academic research.
Hypothesis: The success of women in academia is reduced because academia isn’t in fact a meritocracy and women are selected against by “the system”
Prediction from hypothesis: The more objective the selection and examination procedure, the better women should perform.
Observation #1: Subjects with a higher degree of objectivity in selection procedure: mathematics, and hard sciences. Subjects with lower degree of objectivity: soft sciences, literature.
Observation #2: In academia, women are much more successful in subjects such as the soft sciences and literature than in mathematics and the hard sciences.
I see a contradiction here.
Dan P, I think what you are citing as an observation is what we’re examining as a hypothesis instead. Is it really true that math and the “hard” sciences have a greater degree of objectivity in selection?
The contradiction is your own making.
Dan P, you’re assuming there’s no bias in how the work of males and females is evaluated in mathematics and the hard sciences. But some data from the Nature article (via Amanda at Pandagon — she got ahold of the PDF) suggest that this is not the case. For instance:
And:
And, from Dr. Barres:
(Bold emphasis added.)
These, it seems to me, say that the assumptions present in your prediction need to be unpacked a little to ensure that there really is the “objectivity” you’re assuming in assessing success in math and “hard sciences”.
Dan P’s observation #2 relies on the objectivity of the sciences – which is exactly the thing he’s trying to investigate in making his hypothesis.
Hypothesis: The success of women in academia is reduced because some aspect of the examination system selects against them.
Prediction from hypothesis: Under controlled conditions where the examiner knows nothing about the identity of the candidate the performance should be fairly equal between the sexes.
Am I onto something here?
Dan P. I don’t see where you get Observation #1 from at all (and I was in the physical sciences for a good 12 years or so). Faculty selection is all about whether the selection committee thinks you’ve got what it takes etc. — not whether your latest theorem was mistake-free. A lack of objectivity about what you need to have in order to have what it takes is just as prevalent there as in the social sciences.
(Plus: hard sciences vs. soft sciences – what does this mean? If you mean physical sciences vs. biological sciences or natural sciences vs. social sciences then I think that each of these communicates more information)
Thomas has it, but the experiment he sketches has yet to be performed. Barres’ is not a great dataset; see Lindsay’s comments to her own entry for the reasons.
Actually, I belive that the experiement proposed by tom s. has been done, only not in the sciences: rather in hiring for symphony orchestras.
I’m definitely interested in understanding the nature of and reasons for gender inequality in academia, but I find the individual stories you’ve posted to be largely unhelpful. There’s no way to know if these stories are representative of common behavior or are merely outstanding circumstances. I’ve never noticed behavior similar to that described in the stories in the classrooms and academic departments I’ve been in, but am starting to wonder if I’ve been incredibly oblivious.
Michael, there are quite a few women (myself included) who have noticed such behaviors in our classrooms and academic departments. The individual stories aren’t data points from carefully controlled studies, but they may well be reasons to question the assumptions that there aren’t forces at work here beyond a sorting of people according to their talents and interests.
I’d be quite happy to have some more carefully controlled studies to draw on here, but there still seems to be resistance to the idea that there might be something (other than “innate abilities” or what have you) to study here.
yes, Michael, you’ve been oblivious. It’s not just you, though, a lot men and women are oblivious to the little things. When you look at all of the individual stories together, you will find that women have many of the same stories – including having men finish their sentences, or having a statement ignored until it is repeated by a male, or being left out of the group social life. Frequently women in male dominated environments are so isolated from each other that they don’t even know how universal their experiences are. Any one of those stories can be rationalized away. When you look at them all, you have to conclude that something systemic is going on.
This happens every day in every field, not just science. Just last week I was at a UPS store, and this man was wanting to send something to his son overseas, and all he had was an APO address. The clerk (female) told him that UPS could not ship to APO addresses. He insisted it was a US Army address and they had to ship it. She repeated that UPS can only ship to residential or business street addresses, not PO Boxes or APO or Navy FPO addresses. He repeated the address and asked how much it would be. She repeated, adding that he needed to go to the post office. He repeated. I intervened and explained the same thing; he ignored me and insisted that the clerk take his package and quit refusing to support the troops. She kept her cool. A man who had come into the store to stand in line behind me heard a round of the exchange and said, ‘Hey, UPS doesn’t do APO, man. They never have.’ The guy said, ‘Oh. Really? Should I just mail it, then?’ ‘Yep.’ ‘Okay, thanks.’
Some guy off the street was accepted at once, but not the clerk. Or me. Why?
I have to think it was because we were women.
I’m not at all surprised to hear that it happens in science classes or labs or any place else at all where people are.
The orchestra audition system works because your selection is based on a single performance where your identity can easily be hidden behind a screen. Contrast that to the way academic job searches are conducted. Your CV is full of identifying information…even if we were to delete the applicant’s name from the paper citations, it would be trivially simple to find out their identity by a web search. So, given that there will likely be several more decades of concious or unconscious bias against women in academic sciences, does somebody have a proposal for gender-blind job applications? (And let’s not even worry about the interview stage yet.)
Dan’s syllogism is correct — note that he didn’t claim that physics & math were 100% objective, utterly free of bias. He just claimed that they were more objective than the touchy-feely departments like English. Since we’re comparing representation in the hard vs soft departments, absolute levels of bias don’t matter, just the ratio — assuming there’s strong bias in academia, it must be easier to get away with in squishier domains, and therefore the prediction is that the distance from gender parity in English departments should be greater than the distance from parity in Math departments. As observed already, that’s the opposite of the true pattern.
Not to put too fine a point on it — but would patriarchs really allow women to achieve parity in law school, business school, medical school, and to become professional lawyers, managers, and doctors — and yet strive to keep them from doing math research? Under the bias hypothesis, we would expect the opposite, since the professions are more central to the power structure than nerdy research institutes — in fact, this is exactly what the picture looked like when there really was real bias: back in the early 20th C, there was a greater proportion of female Nobelists & other top scientists compared to today, yet you couldn’t find a single female doctor, lawyer, or manager.
Obvious conclusion: young girls w/ sufficient brains, personality, & whatever else you need to be a top scientist, would rather pursue careers in the pragmatic professions rather than conduct abstract research.
Agnostic, you could find a female doctor if you happened to run into my great grandmother, who got her medical degree in 1894. She went to med school after being widowed — she had kids to support.
Agnostic, is there a difference in hiring practices between “squishy” disciples and hard sciences in academia that I’m unaware of? I haven’t done job search, but as far as I can tell the proceedures are roughly the same. I haven’t heard of candidates being locked in rooms and forced to solve equations and perform experiments with the winner determined by objective criteria. I’ve heard of resumes and interviews and so forth. And, as has been mentioned, according to research the average female is 2.5 times more qualified than the average male hired for a comperable position, and according to other studies hiring committees sent the information of candidates with identical, average level qualifications were far more likely to positively access the male applicants in terms of teaching experience, publications, etc. and far more likely to negatively access the identically credentialed female. We’re not talking about some sort of cabal, we’re talking about individuals with hiring power who have been conditioned to believe that women are less capable than men and who tend more often than not to act accordingly, sometimes consciously, sometimes not.
Obvious conclusion: young girls w/ sufficient brains, personality, & whatever else you need to be a top scientist, would rather pursue careers in fields where they’re less likely to face discrimination and disdain–or at least where such treatment isn’t as likely to be rationalized or celebrated with paeans to females’ genetic inferiority and/or inability to recognize “real” bias.
One point not being made so far is that it’s not so much that women are turned away from science or intellectual pursuit in general. It’s that the ‘hard’ sciences are specifically closed to women. The ‘soft’ sciences are the ones women are most likely to be pushed into, because they are ‘easier’.
Dan, your datapoint simply is wrong.
Maths and hard sciences obviously do do better then softer sciences.
I study physics, there are 10-15% female undergrads, PhD and Postdocs, and about 10% female professors.
While I’m sure there is bias I do believe it is a lot less in a science where you can prove your results are correct.
Point in case, my friend in psychology. They have 95% female undergard, yet by the time you come to the professor level this number has dropped to zero.
Conclusion (vaguely corroborated by the anecdotal data): The major biases are introduced much before the university system can add biases on top.
As there are equal amounts of male and female undergrad students these days, but the distribution of students is skewed toward female/soft male/hard science, yet at the professor level the skew becomes much lower, it has to be that the soft sciences have stronger bias.
(Incidentally, the fact that we have equally many male and female students makes it rather absurd for departments with excess male student body to try to get closer to 50/50 as long as the departments with excess female student body don’t do the same)
Janet, you will find today’s front page story in the Boston Globe about an eminent but jealous old man of science getting some serious heat at MIT for allegedly turning away a superior female candidate to work in his laboratory at MIT. It has all the peanut shells and smell of elephant poop to make you sure the male chauvinist circus has recently decamped … if that is what you want to find.
Seriously, I’d be interested in your comments though I think there is more to the story than the Globe can tell at this point and more is needed for sound opinions to crystalize.
I’ll be blogging it today. [what, after all, have I to do with sound opinions?]
As a 35 year veteran of the computing trade, I ran into the works and the stories of Lynn Conway before and after the sex change. HE was brilliant but had his career at IBM was destroyed and was near sucide. SHE fought for and eventually regained much of the acceptance that her incredible talent was due. Put that story up along side Barres’ and see what can be concluded.
There were female lawyers before the late 20th century. They just weren’t given employment opportunities that men were until very late in the game. Sandra Day O’Connor graduated 2nd of her class in Stanford Law, which as now was one of the schools you could count on one hand among the very top. Her best job offer from a law firm was as a legal secretary. In another case, a woman could only join a firm to handle her own husband’s business but no one else’s.
The bias in hiring is still out there in the legal profession. Some hiring partners openly bemoan that they lose female associates to the mommy track. They don’t talk so much about the male associates who bail because of the monomania of “the firm is my entire life” which is standardly demanded. The denial about the second makes their belief in the first seem reasonable.
I posted on the Boston Globe article that greensmile mentions here.. In an interesting twist, note that Ben Barres (of the Nature article) plays a prominent role! A correction: the woman was not offered a position in the eminent scientist’s lab. She was offered a faculty position in a neighboring Center. She decided not to take the job due to the eminent scientist’s apparent desire to create a hostile enviroment for her as she started her own lab.
For women to enter any field that has historically been dominated by men, a great deal of perserverance is required. If women have been more successful in law and medicine than in the hard sciences, perhaps it is due in part to the strong incentives in place for women to pursue those careers, as well as the existence of a well-defined program to follow to obtain professional certification and obtain a job. In contrast, the hard sciences are marked by a very long apprenticeship period (4-8 years of grad school, followed by 2-4 years of postdoc) before a scientist can hope to obtain a semi-permanent (tenure-track) job. At each step of the way, from undergrad to grad to postdoc to assistant professor to tenure, the numbers are winnowed down, so that no one can be assured in advance of getting a job at the end of the track. While some jobs exist outside of academia for those trained in sciences, physical scientists in particular must often “reshape” themselves as computer programmers or the like to qualify. In return they give up any advantage accrued by their long years of experience, as they struggle to compete for jobs with computer science BS graduates.
As others have said, while scientific knowledge may be objective, hiring and tenure committees are not– nor is what they value. And even on supposedly objective exams, there is a well-documented effect of “stereotype threat” (see my post here) whereby test-takers performance can be strongly affected by stereotypes held about their abilities.
While we’re on the subject of teachers who could use a thrashing, Leslie Madsen Brooks relates her tale of being the girl at the back of a physics class whose teacher had basically given up on the whole class. But, the student triumphs in this story (and her father gets extra points for a special dance at back-to-school-night). I think there’s a lesson here about students and parents having the courage to call shenanigans on teachers who are making lazy assumption about their students, whether they’re based on assumptions about gender or ethnicity or native ability or whatever else.
On the other hand, I remember from my high school years that girls were often using their gender as a tool to be excused from learning physics or math (mostly the first). Something along the line of “but why do you expect me to learn this, prof? I’m a girl!”
I would even dare to say that many women find gender discrimination outrageous *only* when it works to their disadvantage.
Roman, such women and girls clearly ought to be called out on nonsense like that.
That gender stereotyping reinforces sloth is just one more reason to give it the heave-ho. (I’m not saying people can’t be lazy, but they ought to be upfront about being lazy rather than blaming it on something else.)
I wish I’d returned here earlier because I find the responses to my comments interesting. In particular, fh’s claim that my #1 is borne out but that #2 is wrong. (If someone shows me I’m wrong, that interesting right?) #2 should be easy to settle by looking at data for relatives numbers of people at various levels inn various subjects. Where do I find such data?