Well hello there, my dear GFPs! Forgive me for I have sinned; it has been…some weeks since my last newsletter for which I can only point to the following:
the never-ending book
post-op recovery
and probably most important, a 3 week visit from Nathan’s family, including five magical nieces who I have been obviously working hard to
radicaliseok fine spoiling and that has been occupying a fair amount of my time, for which I don’t REALLY apologise as radicalising the next generation is IMPORTANT WORK, as I’m sure you will all agree.
Genius schmenius scenius
Another thing I did since I last wrote to you is to finish reading Helen Lewis’s latest foray into book writing — honestly, where does this woman find the time 😭 In the time it takes me to write one (1) book, she writes and presents approximately a thousand podcasts, writes about a gajillion incisive articles at her homebase of The Atlantic, and then just tosses out another Sunday Times bestseller without breaking a sweat.
Actually it’s worse than that since I haven’t even finished the first draft of my one (1) book (SORRY, EVERYONE…I promise I am trying to make it worth the wait!).
Anyway, in conclusion, if she weren’t a wonderful friend on top of all of that I would have to hate her. Sadly, it is one of my many burdens in life to have to admire and like her a lot — and so, on to her new book: The Genius Myth: The Dangerous Allure of Rebels, Monsters and Rule-Breakers, in which with typical wit and flair Helen uncovers the sometimes disturbing and often ridiculous history of “genius,” a concept she argues, convincingly, is artificially constructed, its borders zealously guarded by self-appointed custodians, who ensure the inclusion of those they wanted (white men) and the exclusion of those they didn’t (everyone else).
Helen (sorry, I can't refer to her as “Lewis”, it feels too weird) pours quite serious cold water on the idea that we need to put up with the nonsense that so often emanates from those we have decided are geniuses (often because they won’t stop telling us they are) in order to benefit from said genius; ponder, she suggests, the example of Elon Musk versus Tim Berners-Lee. In fact, Helen argues convincingly for the importance of “scenius” over genius — that is, that it is the environment more than the individual that really matters for human progress. Consider, she says, how many inventions have been invented by more than one person, acting entirely independently from each other — the one we remember tends to be the one who is better at self-promotion.
A treasure trove of at once disturbing and fascinating insights (come [lol] for the Nobel prize winners sperm bank; stay for the monstrous labour contract Einstein wrote for his wife to sign), The Genius Myth is available to UK GFPs here and US GFPs here; for everyone else, I’m sure translations will be forthcoming!
A half-finished revolution
As you can no doubt imagine, the examples I was most drawn to in Helen’s book concerned the artificial and deliberate exclusion of women from the rarified ranks of genius (barring them from institutions; eliding them from historical accounts; funnelling them into the unsung role of managing their genius husband) — and to add insult to injury, Helen reveals multiple instances where the guardians of genius use that deliberate elision, and its resulting lack of female representation among the ranks of documented geniuses, as proof that women are not, in fact, geniuses.
I was reminded of this classic of the bait-and switch genre this week when I read this fascinating paper which explores an under-examined but compelling explanation for women’s continued under-representation in the upper echelons of computer science: the type of research they do is systematically undervalued.
This type of systematic bias will not be unfamiliar to readers of Invisible Women, who may remember I addressed this issue when discussing how female academics are often loaded with more teaching hours (barely valued work) and pushed into taking on “‘honorary’ admin posts (“someone has to do it, but please not me” work), both of which come at the expense of their research (highly valued work).
But it turns out it’s even worse than that, because, as this paper reveals, even when female academics do get to do research (ie highly valued work), it now transpires that the type of research they are more likely to do — indeed, that women have, often with the best of intentions, been encouraged to do — is in fact, not that highly valued.
Much academic research can be broadly divided into two categories: basic or theoretical research, and applied research. Basic research examines fundamental principles, the theoretical underpinnings of how things work, while applied research “aims to create practical knowledge,” to solve real-world problems and create often inspired by real-world problems or data.” In computer science, which is the area this paper focuses on, basic research could be something like “proving the mathematical properties of algorithms,” while applied research might involve “developing algorithms to improve medical diagnoses.”
I don’t think it takes a genius (ohoho) to figure out which type of research is considered more genius-adjacent; everything we know about how genius is coded in our society suggests that it is theoretical research that will be more prestigious. And indeed that is what this paper found: when they surveyed a representative sample of faculty members they found that a professor presented as being engaged in theoretical research was considered to be more “brilliant, creative, and technically skilled” than the researcher engaged in applied research — even though they considered both applied research and theoretical research as of equal importance. (It’s worth noting here that because their sample of computer science faculty was representative they were unable to meaningfully sex analyse their data because, well, there were too few women.)
And it’s not just about subjective faculty judgments: there are objective measures of the how applied research is devalued in comparison to theoretical research: applied research is less likely to get funding, less likely to be published in top-ranked journals and conferences, and less likely to win awards — all of which will naturally affect the career prospects of people who choose applied research over theoretical research.
And who are those people? Well, they’re women of course!
Ironically, this may in part be a result of an attempt by a number of computer science courses to increase the representation of female students. As readers of Invisible Women may remember, computer science was historically an extremely female dominated domain:
In fact, women were the original ‘computers’, doing complex maths problems by hand for the military before the machine that took their name replaced them. Even after they were replaced by a machine, it took years before they were replaced by men. ENIAC, the world’s first fully functional digital computer, was unveiled in 1946, having been programmed by six women. During the 1940s and 50s, women remained the dominant sex in programming, and in 1967 Cosmopolitan magazine published ‘The Computer Girls’, an article encouraging women into programming. ‘It’s just like planning a dinner,’ explained computing pioneer Grace Hopper. ‘You have to plan ahead and schedule everything so that it’s ready when you need it. Programming requires patience and the ability to handle detail. Women are ‘naturals’ at computer programming.’ (IW, p105)
But as employers gradually realised that the computing these women were doing was not low-skilled clerical work they had assumed (the circular reasoning being that if women were doing it it couldn’t be all that difficult), it stopped being associated with women and planning dinner and instead became associated with men and being too clever and important to plan dinner. As a result, female representation in computer science nose-dived and has never really recovered — until in the past decade or so, universities have started to successfully increase the number of female students signing up for computer science courses by emphasising the subject’ practical applications.
Universities have successfully increased women’s participation in computer science by highlighting its applications. When universities introduced interdisciplinary CS+X programs – combining computing with fields like anthropology, biology, or music – the number of women students grew significantly. These programs appeal to students who want to apply their coding and algorithm-building skills to solving real-world problems rather than pursuing computing for its own sake. (Source)
All of this is great for the university’s diversity stats, not to mention for humankind over all since more equal representation means a greater likelihood that subsequent research will serve us all — but it appears as if it may have been less good for the future careers of the female students in question.
Still, those who encouraged female computer scientists into a devalued area of research can comfort themselves by remembering that any female-dominated domain tends to be devalued. As we’ve just explored, when computer science was female-dominated it was considered low-status, and this is a trend that has been observed in multiple areas: as the number of women in a profession increases, its prestige (and wages) decrease. All of which means that rather than women having been encouraged into a devalued area of research, applied research may be devalued precisely because it’s female-dominated.
These irrational (de)value judgements are to the detriment of us all. I don’t know about you but I quite like it when the brightest minds are brought to bear on real world problems; framing this kind of work as somehow less skilled, less creative and less important than work that remains in the theoretical realm is hardly going to attract those minds.
They are also a useful reminder that feminism is a half-finished revolution. We have been really quite successful when it comes to giving women access to domains that have previously been jealously guarded (often through legal structures) as exclusively male. We have proven that a woman can be “as good as a man” in any number of fields. But we have progressed very little when it comes to recognising the value in domains that have been traditionally coded as female — and this is the result. This almost exclusively one-way progress has arguably — ironically — reified the positioning of masculinity as aspirational and femininity as something to transcend. And until we change that, half-finished is exactly what this revolution will remain.
So you want to be a writer…
Good news! Rachel Hewitt, who is not only a bestselling and prize-winning writer, but has also taught creative writing at universities for a decade, has recently launched a six-week online course on her substack!
You can check it out and sign up here:
Poppy pic of the week
That’s it! Until next time, my dear GFPs….xoxoxo
Thanks for another great newsletter. The Genius Myth is definitely on my TBR as I loved Difficult Women. I could also recommend 12 bytes by Jeanette Winterson when it comes to computer science and it's development. I have always worked for myself in computer science, but I've definitely had instances where I've been patronised in emails about something I was more all over than the person I was talking to, and I do wonder if it would have been different if I'd signed off to 'Matt' instead of 'Mandy' it would be different. It is so important to get more women in the tech world solving problems that affect women (just as a small example - it probably doesn't occur to men how much pockets are a thing). My friend ran an outreach programme to get more working class kids on a tech courses, but in the end they found that they only had boys applying. When he questioned the leaders of the course it turned out that they had only advertised in the computer science department, rather than going out to where the girls were. When I was a kid, I didn't know computer science was an option. I hope it is better now
The Code Girls about the WWII code-workers is a great examination along similar lines (code calculation evolved into computer coding). It was initially thought of by the US Army as rote but necessary work that was needed to give the girls something to o do so they wouldn't sleep around.