Does it matter here in the UK what the president of Harvard says? Larry Summers was addressing a conference in Massachusetts this year on diversifying the science and engineering workforce, when he made his now notorious remarks on women’s ability to do science and maths. Through some dubious statistical extrapolation, he suggested that innate biological differences meant men could outnumber women “at the high end” of the sciences by five to one. In other words, discrimination only played a small role in explaining the low number of female maths and science professors.
His comments provoked lots of controversy in the press and in blogs: Summers was portrayed either as a heroic speaker of unfashionable truths, or as a prejudiced apologist for a right-wing agenda. Feminists who attacked his viewpoint were accused of stifling healthy debate through a mixture of scientific ignorance and political correctness. Helena Cronin in “The Observer” and Camilla Cavendish in “The Times” were particularly scathing about the women who thought his comments were out of line. But is this just a campus war, and an American one at that?
are there things women do less well; and can we use science to “prove” it?
Well, for all that Summers’ views drew, if somewhat shakily, on academic papers, his argument both feeds into and is shaped by the gender debate which is science faction. Always lurking there in the background, it has at its heart three issues: do women and men think in the same ways; are there things women do less well; and can we use science to “prove” it? It is actually a short step from Larry Summers to John Gray (author of the “Mars and Venus” books) or to the persistent idea that women can’t read maps (see “Why Men Don’t Listen and Women Can’t Read Maps” by Allan Pease et al). I would suggest this oddly-contoured debate is characterised, wilfully or otherwise, by two sorts of misunderstanding, the second only a little bit more sophisticated than the first.
The first kind of misunderstanding simply comes from people repeating and misusing an idea often enough, until it becomes a debased version of itself. You might start off with Summers talking about scientific high-fliers at Ivy League universities, and Xie and Shauman’s sample of high school pupils (a sociological study quoted by Summers), but through a series of unwarranted extensions these comments end up being applied to things they were never meant to cover. So an idea escapes and becomes amazingly tenacious.
we’ve arrived at the fuzzy idea that women just aren’t quite as bright as men
You can see this kind of slippage at work even just in the pages of The Times. Never mind the original US context of Summers’ remarks: Andrew Sullivan ropes them into his wider generalisation that “One thing that endures across cultures and populations is a male edge at the very top of the bell curve for spatial and mathematical reasoning.” Camilla Cavendish is less careful and doesn’t make it quite clear whether she is talking about just maths, or other skills as well, when she refers to “the bell curve of ability” which “does not mean that there are no women geniuses; it just means that there seem to be more men ones.” By the time you come to Gerard Baker’s article, Summers’ comments are being used to back up the astonishing assertion that “Other research has indicated that women, whether for environmental or innate neurological reasons, are less inclined to abstract thinking.” Eh? Through a bizarre downward spiral, we’ve arrived at the fuzzy idea that women just aren’t quite as bright as men.
This sort of warped misunderstanding is irritating enough, though at least if it ends up slackly expressed like this, we can label it as an unfounded popular myth. But supposing there is no slippage and somebody quotes a study just as they have read or heard it. They might then tell us that scientific evidence proves there are important differences between men and women’s abilities, and that we’re being stupid or censorious to ignore them. There may be fewer women engineers than men, but so what? That’s not down to discrimination; it’s because women are naturally poorer at engineering.
why should I have to become an expert on neuroscience in my spare time?
One option is just to ignore it. If I think that social justice is much more than a reflex of the latest scientific consensus, then why should I have to become an expert on neuroscience in my spare time? I might also think that slavishly propping up the idea of a binary gender system is unhelpful, yet I don’t feel completely happy ignoring this sort of “evidence”. It isn’t pleasant to be criticised for being blinkered or hostile to “facts”, so if people invoke them, it is easy to feel obliged to reconsider your opinions, or to find that conversations about how women can’t manage engineering are harder to refute. In that case would it be best to keep up to date with statistics on sex discrimination, on how well girls do in maths in Iceland and the latest research on the brain? Clearly even if I thought this was a good idea, it is hugely impractical. How can most people keep on top of all the relevant technical material?
If this wasn’t enough, we still have to deal with the pressing problem that any scientific study on gender tends to be presented by some people as if it had all the force of scientific truth. I think one way to deal with it is to regard it as the second kind of misunderstanding that creeps into the gender debate: a basic category confusion between politics and science. Science tells us some things that we can generally all agree on: for example, a pedestrian is more severely injured by a fast-moving than a slow-moving car, so most people would probably accept that we need speed limits in built-up areas.
The problem comes when we move to more speculative areas such as personality or ability
The problem comes when we move away from that level of certainty to more speculative areas such as personality or ability. Here the science is less clear. As Susan Greenfield argued, why should having excellent spatial skills be decisive in making someone a good scientist? Especially as we haven’t defined what we mean by a good scientist. There are lots of other qualities that scientists need, including verbal and computational ones. And what does spatial mean anyway? There might be some evidence to show that men are better at rotating 3D objects in their head, but spatial doesn’t mean that skill alone; in fact the word is sometimes used rather vaguely to wash over a range of subjects from maths and engineering, to biology, chemistry and physics.
Perhaps most importantly of all, we don’t have hard and fast rules to explain the dynamic between people’s abilities and their environments. Instead we have certain kinds of information and disputed theories. So there are studies to show the effects of male and female hormones on the brain, studies of family backgrounds, and studies to show how embedded gender stereotypes lead to discrimination. Choosing to research any one of these things is in itself is a selection and potentially a political one.
people can end up being highly political under the guise of objectivity
Even the scientific data itself doesn’t necessarily prove what it is argued to prove.
Are pupils’ test results really a measure of ability or a measure of cultural bias, or just of how pushy their parents are? Or perhaps the results vary depending on whether girls have been told to expect to do well, or to do badly. If I get men and women to memorise a route on a map and then to recount it to me, do I really know whether I’m measuring how their brains do map-reading differently, or whether men have been taught to use compass directions and women to point out landmarks? I can certainly measure how well girls do in maths at school at any one time, and even see that it varies from country to country and from one generation to another. But in the absence of a unifying theory that explains the interplay of physical and social factors in an individual person, how do I make the results meaningful? And as soon as I theorise to make them meaningful, I step into politics. To say that Icelandic girls do well at maths is making an observation. To say that we need all-women shortlists for maths jobs, or that discrimination against women in maths has little impact is making a political statement. Science can explain some things extremely well, but is still bad at explaining how people work, and how they interact together in social systems. And so by selecting some findings and ignoring others, people can end up being highly political under the guise of objectivity.
Of course, from one perspective, this is all old hat. Echoes of the mindset that women rarely excel at maths and science resonate in the 1920 exchange between Desmond McCarthy and Virgina Woolf in the “New Statesman”, about whether women could ever make first rate artists or writers. What bothers me is the tenacity of the idea. Science is embedded in our everyday lives, whether through technology like the internet, or as a background understanding of the world. We are not likely to think of thunder storms as manifestations of divine wrath. At the same time, not many people have specialist scientific knowledge, far less over different disciplines, causing a gap between what we know and why we know it. It can be hard to resist the clout of biologically determined “facts”, but at least we can start to argue that what gives our observations meaning is as yet not science but politics.