A Primer on Gender and Science
Written by Abhilash // September 28, 2010 // Science & Technology // 16 Comments
(This is a guest post by Jessica Hanzlik. Jessica completed a MSc in Particle Physics and a MSc in Comparative Social Policy at the University of Oxford, where she was a Rhodes Scholar.)
This post will be too US/Western Europe-centric as most of my expertise, if one may call it that, lies in how the topic of ‘gender and science’ or ‘women in science’ manifests itself in those areas of the world. I am particularly interested in peoples’ perspectives on similarities and differences for India. I’ll provide citations for many of the interesting studies which have been done relating to this topic, and if you don’t have access to the articles then email me ([email protected]) and I’m happy to send you a pdf of the relevant articles.
I. Introduction
I grew up with a science-teacher mother and grandmother, so it wasn’t until I began studying physics at university that I realised that not everyone, and in fact, a very small minority of women, thought that becoming a scientist was a natural career choice. Shortly after I began to question why less than twenty percent of my classmates were female and why only three of Ohio State University’s sixty physics professors were women, Larry Summers, then-president of Harvard and now-economic advisor to President Obama, controversially brought national attention to this question writ large at a conference on diversifying the science and engineering workforce. He theorised, among other hypotheses, that the under-representation of women in the top levels of academia (for, you see, the gender disparity that I noticed in my small world was a strikingly-apt microcosm of the larger academic world as well) is due to a ‘different availability of aptitude at the high end’.
What, precisely, did he mean by that statement? Well, suppose the distribution of ‘aptitude’, as measured by, for example, IQ or SAT scores, among men fits a Bell curve with mean mu-m and variation sigma-m, and the distribution of the same aptitude among women fits a different Bell curve, with mean mu-w and variation sigma-w. Then, one can imagine a world in which the means of each distribution are equal, but the widths of the distributions are different. If the Bell curve for men is flatter than that of women, then this hypothetical world would have more of both very low performing men and very high performing men than the equivalent of women. This situation might, for example, explain why many more men than women are diagnosed with autism, and it might also explain why many more men than women become scientists. This idea is called the ‘greater male variance’ theory, and it would imply that the gaping gender disparity in the sciences is the expected consequence of natural variation in aptitude and ability among men and women.
II. Evidence
Larry Summers was not the first person to come up with the idea of greater male variance (which is one of the reasons his statements at this conference caused an uproar, eventually leading to a vote of no-confidence by the Harvard faculty and removing him from the presidency). Researchers have tested the hypothesis in a variety of ways. One of the most recent studies, ‘Gender, culture, and mathematics performance’ finds that in the US, girls and boys have the same mean score on a standardised mathematics exam, but as the greater male variance predicts, more boys than girls score above the top percentiles. However, and more significantly, they find that the ratio of boys to girls scoring in the top percentiles has changed not only over time, with the ratio decreasing rapidly as time increased, but that the ratio is not consistent among different ethnic groups within the US nor is it consistent cross-nationally. The researchers thus conclude that the gender gap is ‘largely an artefact of changeable sociocultural factors, not immutable, innate biological differences between the sexes’. (Hyde J. et al)
III. Social implications
While biologists have been unable to explain the gender gap in the sciences, sociologists have been much more successful at this goal. Before we get to some of the more interesting results from sociology, I need to clarify one more point. Although I didn’t realise it at the time, my anec-data — that twenty percent of my physics classmates were women and FIVE percent of my physics professors were women — is representative of two types of gender gaps in the sciences. The first order effect is, of course, that much less that half of physical science students are women. The second order effect is that at every level of the science career trajectory, from undergraduate student to graduate student to post-doc to assistant professor to full professor, the proportion of women drops. Perhaps this drop is a historical artefact; if thirty years ago, only five percent of science students were women, then we would expect that today, only five percent of full professors are women. It turns out that the second-order gap is not a historical artefact. As they move up the science career ladder, women drop out disproportionately at every step, an effect known as the ‘leaky pipeline’.
Let’s turn now to some fascinating sociological research on this topic.
The ‘stereotype threat’ is a phenomenon discovered by sociologists in which a minority group, e.g., women with regard to mathematical ability, risks being judged by a negative stereotype about their group. The existence and force of the stereotype threat is demonstrated in the study ‘Stereotype threat and women’s math performance.’ For this research, scientists recruited mathematically-qualified men and women. In round one, they were given either easy or hard math tests. Women under-performed men on the difficult but not the easy test. In round two, participants were explicitly told that the test did not measure gender differences in performance, and consequently, women did not under-perform men on identical tests. In round three, participants were reminded of the stereotype that women are worse than men at mathematics, and subsequently women performed substantially worse. (Spencer, SJ et al.; Stereotype threat and women’s math performance)
Even if women and men do not subconsciously maintain negative stereotypes about women’s mathematical or scientific ability, other research suggests that further barriers exist to women’s ability to advance their scientific career. When identical CVs are presented to reviewers, the gender of the name at the top of the CV influences reviewers’ assessment of the applicant’s accomplishments and abilities, with male names being rated as more highly qualified than women’s in some situations. (Steinpreis, R et al. The impact of gender on the review of the curricula vitae of job applicants and tenure candidates)
In auditions for prestigious orchestra positions, blind auditions, in which applicants play behind a screen concealing their identity, women are 50 percent more likely to advance from the preliminary rounds than they are in open auditions. Obviously I’m not suggesting that musicians and scientists face identical barriers and difficulties, but the two fields, each demanding years of focused work, are more similar than they are different.
IV. Conclusions
This issue matters both because the current state of affairs is unfair, and because it indicates that we are currently neglecting half of our pool of potential scientists. We have some really big problems to solve in the next few decades and it seems foolish to ignore a very large group of people who have the intelligence to contribute ideas and solutions.
Fixing the problem won’t happen overnight, but small changes can make big differences. We now know that explicitly telling women that there is not a gender gap in scientific/mathematical ability significantly increases their aptitude. Mentoring young women provides them with successful role models. Role models can be either male or female — the encouragement and support are what matters. It seems to me that by making the science world into a more fair and just place, the quality of science produced by scientists can only increase, and that, one hopes, is good for everyone.
16 Comments on "A Primer on Gender and Science"
Jessica,
Many thanks for your excellent post. The studies you cite are very revealing.
In relation to the second order effect you have described (which you call the leaky pipeline), I think there is another factor at play apart from the cause you have outlined (which is -the negative stereotype operating at every stage of promotion).
This other factor arises because of the disproportionate demands (of course the demands are disproportionate partially becasue of biology and mostly becasue of society) made on women in the context of raising a family. This has been the cause cited for a similarly leaky pipeline in the corporate world, where women are usually the high performers at younger associate levels but rarely make it to the senior Manager/Partner levels. Women are the objects of covert prejudice when it comes to promotions/bonuses because of the competing claims on their time and the perception that they will not be able to give a 100 per cent to the job.
Of course, this is nothing novel, it has been stated a million times before. But while, the factor of negative stereotype is simple to tackle in that it merely needs correction of an unequivocal social wrong, correcting this other factor may not be as simple or straight forward.
Subra
Hi Subra,
I totally agree with you about the structural issues in, at the least, the American academy. It’s pretty clear that academia was designed with the ideal male worker in mind, someone who’d have a partner at home to take care of the life stuff so that he could spend his time professing.
As you say, in business as in academia, women are effectively forced to choose between work and family, since it is even more difficult for women than men to balance child-bearing and child-rearing and the tenure clock, given the biological restrictions on when women can physically have children.
Probably what’ll change the structural problems is men realizing that a work-life balance is a good thing, because as you point out, at the moment it’s still considered a women’s issue, this question of children and tenure/career ladder. How to get men to advocate for change is something to think about.
The sociology experiments are definitely quite revealing.
The ‘stereotype threat’ is definitely there, and it needs to be actively combated.
Given my experience in science, I have observed that because of a large number of reasons, women tend to under perform, and the lack of role models worsens the situation, making survival and motivation difficult for women in their careers.
On another note, I have observed a tech-phobia among many women I have worked with. This is slightly troubling, but this phobia definitely exists and is quite sharp in many cases, where women are either unwilling or unable to do sophisticated technical work, deal with machinery and arrive at working models. There are less women in science, but even lesser women in engineering and technology, so women need to themselves make sure that they gain in crucial technology skills and fight this tech phobia.
Sumeet, my understanding is that tech phobia is pretty common among both genders. May be 2% of males and 1% of females really enjoy basking in new technology — but the majority of both males and females try to steer clear of it (the same is true of most of the things we are discussing here — we’re comparing small minorities of male populations with small minorities of female populations).
I don’t see why you claim that women “need to” do something as a category. If you’re claiming that technophobic individuals need to overcome their technophobia, that’s a different claim. With a few exceptions (such as Jessica here) most women, like most men, are more concerned about their individual selves than with trying to improve the collective status of their gender group. And I think that’s as it should be. I’m more than a tad unhappy if a woman who goes into mathematics (or engineering, for that matter) in order to “prove” to the world that women can do mathematics — particularly if she isn’t that talented or interested in the area.
Jessica, I have many issues with the assertions you make.
You say: “While biologists have been unable to explain the gender gap in the sciences, sociologists have been much more successful at this goal.” I could say, “While scientists have been unable to convincingly explain the origins of life, religious theories have been much more successful at this goal.” While it’s perhaps a bit unfair to compare sociology with religion, the point remains: the standard of “proof” needed for sociological theories is considerably less than the standard of proof generally needed for biological, genetic explanations. To say that sociologists have come up with theories is very different from saying that they have demonstrated successfully that their theories account for a significant fraction of existing gender disparities.
Now, here is my understanding of the biological evidence so far. (Numbers are from the United States). First, both cognitive abilities and character traits are known to be substantially heritable, with heritability higher for cognitive traits (narrow and broad heritabilities about 50% and 75% respectively). See, for instance, Bouchard et al’s Minnesotta twins reared apart study. Moreover, the non-heritable component of cognitive traits is largely considered “within family”, i.e., when you control for genes, being raised in a family has very little impact on cognitive abilities as measured by IQ tests — though it has more of an impact on life outcomes. This non-heritable component is termed “nonshared environment” or “unique environment” and I don’t think anybody really know what nonshared environment comprises or how t manipulate it to increase cognitive traits.
Now, coming to the subject of gender differences. Recent IQ studies have shown that (in the US and UK) males on average have a slightly higher mean IQ than females but that this difference starts manifesting itself only after the age of fifteen. (The difference would be between 0.1 and 0.3 standard deviation, so pretty useless for the purpose of judging individuals). If these studies are correct (and there are question marks because earlier studies showed no IQ differences) then IQ would, like height, be something where the male “advantage” really starts manifesting itself only in late teenage years.
Less controversially, though, IQ test have shown that females have a stronger verbal performance than males and males are stronger on visuo-spatial skills — i.e., there are different “profiles.” This may be due to biological or sociological factors or a combination, though to the best of my knowledge, there are no popular stereotypes of strong male visuo-spatial skills or strong female verbal skills. There is, however, some evidence that biology explains at least part of the difference: female verbal skills vary with the menstrual cycle and have been correlated with hormone levels.
I’ll continue in the next comment, since this one is getting too long.
Hi Vipul,
Thanks for your contributions.
If you’ll take a look at ‘Gender, culture, and mathematics performance’ by Hyde and Mertz, you’ll see that they engage with this idea that biological factors are the major determinants of the gender gap in mathematics. They take representative numbers for variations in the means and spreads of male and female ability distribution curves and calculate what that would look like for the proportion of male to female mathematicians. They find that even assuming that there does exist greater male variance (an assumption they don’t actually believe based on cross-cultural analyses) then they still cannot explain the lack of women. For biological variation to explain the current male:female ratio, these professionals would all have to have been four standard deviations above the mean.
I don’t think that anywhere close to the vast majority of scientists come from that part of the Bell curve.
Thus I stand by my assertion that biology does not explain the gender gap nearly as well as sociology does.
Jessica,
Thanks for the response. Unfortunately, another of my comments is in the moderation queue right now, Abhilash will have to approve it because it contains hyperlinks. I will just repeat the gist here: a large number of academic professions in in the US have female domination at least till the grad school level. I am hard pressed to attribute this to discrimination against males. The more likely explanation seems to be profile differences in both abilitis and interests. Both biology and society affect these differences
I will get back to you after a more careful study Hyde et al
Stepping back a bit, let’s note that as the number of people graduating from college increases, the proportion of women increases. In the United States and most developed countries, and even in Iran (?) and many developing countries, women already make up more than half of the people completing college degrees, so much so that many colleges are considering affirmative action for males so that their female students (see here for a bunch of links). The latest numbers from the Council of Graduate Studies in the US (see http://blog.american.com/?p=19710 ) shows that women earn slightly more than 50% of all doctoral degrees. Many fields in the humanities and social sciences are heavily female-dominated.
Note that even if you find the variance differences unconvincing, profile differences tend to explain a lot of the difference between disciplines. (The leaky pipeline is a different issue). Those disciplines that rely more heavily on visuo-spatial skills are also the ones with lower female representation. The social sciences and humanities, which are more “verbal”, are also the ones where women are seen a lot more.
More importantly, though, why is it a problem at all? If you (I don’t mean you specifically here — generic you) don’t think it is a problem that males are “under-represented” in political science graduate programs, why do you think it is a problem that women are under-represented in particle physics research programs?
One argument I’ve heard is that different genders bring different perspectives to the table, and domination by a single gender leads to a biased or narrow perspective in the subject. But then why focus attention so much on STEM (science, technology, engineering, and mathematics)? Is the argument that the bias or lack of gender balance is significantly more harmful in STEM fields than in other fields? Or is it that, as Robin Hanson said:
“I notice that women are said to look good in male-style clothes (e.g., suits), far more than men are said to look good in female-style clothes (e.g., dresses). Women also earn more respect succeeding at male-dominated professions than men earn by succeeding at female-dominated professions.
The general pattern in all three cases is that we seem to respect women doing well at what mostly men do far more than we respect men doing well at what mostly women do. For better or worse, male abilities seem to more define which abilities count most for high status. Doesn’t seem fair to women, but there it is.”
Hi again Vipul,
I think you’ve made an incredibly important point here about masculine activities defining what’s important to society. For the record, yes, I think that the teaching profession and the poli sci programs and the humanities graduate schools would all benefit from an influx of men and their particular ways of looking at the world. I think the same thing is true about any form diversity — racial, cultural, sexual identity, etc.
But to answer your question about why focus on the STEM professions explicitly, for me, it’s partly personal in that I love math and science and want as many other people as possible to feel the same way, and it’s also partly driven by my feeling that it’s extra important for the STEM fields to be as fair and objective as possible. It’s probably a bias on my part that I think that science can be, and generally is, a powerful driver of social progress. And, in order for science to be at its best, it needs to continuously move toward fulfilling its own ideals of objectivity.
On to the “leaky pipeline”. As you and many others have said, more and more women drop out of academic careers because they want (or are pressured) to take up the burdens and joys of motherhood. My guess is that this is the dominant reason for the leaky pipeline. In the United States, unmarried women have generally earned more and progressed faster in their careers than unmarried men — and this has been true for quite some time.
If my surmise is correct, then the issue is almost entirely one of personal choices: (i) the decision of women (and men) to marry, (ii) the decision to have (or, in rare cases, adopt) children, and (iii) the negotiation process between marriage/domestic partners (one woman and one man in case of a monogamous heterosexual couple) on the sharing of household and earning responsibilities.
Of course, social conditions constraint personal choices to quite an extent, but these aren’t discipline-specific or academia-specific social conditions, as far as I can see.
With respect to the leaky pipeline, of course people have the agency to ‘choose’ what they do with their lives, whether it be parenting or researching. However, if the structure of the job is such that it disproportionally encourages women to self-select out over men (since women are physically burdened by pregnancy in a way men aren’t, AND because society as you say places more of the care-giving expectations on women), then the job itself is biased. Science as a field wants to be as un-biased as possible; that’s the whole point of the profession. If the scientific profession is biased, then that bears examining, especially given that one of the ideals to which science, and scientists aspire is objectivity.
Jessica, thanks for your responses. I think I’ve got a lot to still say and perhaps I will write a blog post on this in the future, but for now, I’ll stick to the most important points.
First, I don’t see this as biology versus sociology. Things could be part-biology and part-sociology. The “sociology” part could be part parenting, part broad society, part the domain- or discipline-specific sociology. I am convinced by the current evidence that there are biological factors as well as social factors that affect individuals’ abilities and choices, and that many of these factors have different gender profiles. The question is largely about the details.
One possibility is that there is a biologically determined equilibrium range (my guess would be females between 30% and 45% of high-end STEM jobs — and about 40-60% for the non-high-end jobs) and in a reasonably equal society, the proportion would fall within that range. The fact that some societies have a proportion significantly below that range indicates that other factors are depressing female performance in relative terms — factors that are probably most likely sociological in nature. This is the possibility that I currently subscribe to. I see no reason why that equilibrium range should naturally center at 50% — I expect it to be skewed to one side in some cases and to the other side in other cases.
Second, I think your concern with STEM fields (setting aside the gender issue) is a little misdirected, because these fields are already pretty heavily populated. I do think that a knowledge and understanding of mathematics is very important for people, and that a better number sense is very useful, but I don’t think that a lot more people should *become* mathematicians or engineers or technologists. I especially don’t think that standards should be lowered or dumbed down to try to attract more people (whether male or female) into majoring in these subjects.
It’s true that people at the high end of innovation often need a lot of specific knowledge of mathematics-intensive subjects, but these form a very small fraction of the population — and cognitive abilities as well as character traits such as conscientiousness and perseverance, which are largely determined by genes and early childhood environment, already cut off a large fraction of the population from even attempting this kind of high end innovation. For most other people, it may be a good idea to encourage them to learn their high school math more carefully, but that is very different from trying to push them into mathematics.
Third, do efforts to push women into STEM fields bear fruit? Probably to some extent. But the women who are being pushed into these fields are, for the most part, not women who would have gone uneducated in the absence of such a push. Most of them would be talented, academically or commercially inclined women who would probably have gone into business, medicine, law, or other parts of academia (such as political science). This may be a good thing if the “advertising” of science to the women who change their minds is done honestly — but it could be a bad thing if false ideas of science are implanted in the women’s minds to try to attract them to it. In any case, from a societal point of view, I see no reason to believe that we need fewer doctors and more engineers.
Fourth, the stereotype threat theory is a fascinating one. But to the best of my knowledge, most of the evidence in favor of it shows how stereotype threats can make performance gaps wider than the baseline level, not how performance gaps can be narrowed relative to their baseline levels. More importantly, though, the stereotype threat story doesn’t fit my own personal experience with seeing women in mathematics. In the freshman calculus classes I have taught, my female students who start finding their college mathematics much harder than their school mathematics don’t say, “I knew it, women can’t do math.” They say something like, “This can’t be happening” or “the instructor is terrible” or “the instructor is making things too hard” or “I am having a bad time” — just like my male students. The main reason why equally talented female students do less mathematics courses, at least in the groups of non-math majors that I’ve interacted with, is that females are much more likely to have their sights set on medical school where grades matter a lot more for admissions, so hard mathematics courses are a luxury they think they cannot afford. Of course, my samples aren’t representative, but this is just food for thought.
Thanks for the post Jessica and the discussion that followed. It has been enlightening.
Poste vraiment intéressant
Trackbacks for this post