How does biology explain the low numbers of women in computer science? Hint: it doesn't.

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

more share options
Embed For WordPress.com

Without related presentations

13 comments

Comments 1 - 10 of 13 previous next Post a comment

+ Victor Yodaiken 3 weeks ago
It’s obviously cultural - if only because the percentage of women in the field dropped radically in the 1980s when it was 'professionalized' and didn’t depend on pure ability anymore.
+ Terri Oda 1 month ago
letsbeefriends: *laugh* You’re seriously arguing about what one pixel means in a presentation whose curves I mostly drew by hand in Open Office? This is meant to be more like a sketch that a teacher draws on a chalkboard -- a useful learning tool for visualization of the problem, not a precise instrument of data-display. Don’t bother fussing over pixels!
+ letsbeefriends 1 month ago
how can you make your argument on the second graph? anyone who knows math knows that you can manipulate the range and precision of the graph to make the curves be as much close or apart as they want. each pixel could be 1 or 100 IQ points (or whatever they used to measure this, hopefully not IQ points).
+ Amanda Wilson 1 month ago
great i do agree that there is a shortage of women taking up computing(im in last year at uni and there are very few of us) however there now appears to be wider problem with peope taking up CS and its not just the women, since 2001 numbers is the UK have been steadily falling for computing courses, there are projects out there trying to encourage people so hopefully these will start to have an impact on the next generation of computer scientists!!!
+ Terri Oda 1 month ago
Don: I was just teasing you about the title of the book: Any tome that claims to represent ’The truth’ seems a little optimistic/overzealous at this stage, where there is little consensus and people fear publishing certain types of research for fear of appearing sexist.

Mike: The ability usually cited by people offering this theory is usually determined by tests similar to (or the same as) those used by IQ tests. Those tests have their own very interesting biases (for example, did you know that IQ tests have been shown to heavily penalize immigrants?) and some research has implied that they are not very good predictors of future success in careers. I didn’t want to touch issues of what ability means in this heavily simplified explanation, but if you’re interested, it’s a fascinating area of study.

Carlos: If I could explain it, I’d probably be a rich woman. And also in totally the wrong field, since this is absolutely unrelated to my day-job unless you count my own demographic information.
+ Carlos Z 1 month ago
Interesting topic. What does explain it?
I am an engineer with both a masters in engineering and one in business and I saw the same 'few females' in engineering syndrome as you mentioned in your presentation. The very strange thing was that during the MBA the same kind of phenomena was seen in majors.... most females went to marketing and communications as a major while finance and strategy was plagues with males...
+ Don Schmincke 1 month ago
Wow! Terri, thanks for opening up an interesting topic. I didn’t think I’d be spending time on this but I like your sense of passion on the topic and Gregory’s terrific statistical contributions. Just to clarify what we’ve learned so far in our research:

1) You mentioned 'I’m not a psychologist, a biologist, a sociologist, an anthropologist, etc. but I’ve read a lot of theories over the years and I don’t think a single one of them is likely to be the entire truth, so I’m immediately suspicious of your book. ;) ---- I agree that no one theory explains it. That’s why we’ve referenced over 300 publications from dozens of scientific disciplines. Many are referenced in the 'suspicious' book. You may take exception but your debate isn’t with me but with the scientists at Oxford, Cambridge, Harvard, and many others (incidentally most of our research was supplied by female scientists).

2) Together there is a pattern - nature’s design makes sense. We broke into separate genders for a reason. We alter female fetuses to become male for a reason. And it works. That’s why the neural patterns, neuropeptide levels, hormonal levels, brain configurations, and other genetically triggered differences between males and females are there. It drives how each gender perceives, relates, and communicates with the world. Many scientists believe this multitude, not one, of changes contributes to the differences in interests, aptitudes, skills, etc. for most, not all, of each gender.

3)What caused all the background 'who’s better in what?' arguments? I was shocked to find out one scientific theory - agriculture. The ability to produce more calories per acre stopped the genetic-team from being necessary. Now both genders were force to operate together according to this theory. There may be something here. With the extra calories we could now have 'extra' to support politicians, philosophers, engineers, . . . and computer scientists. I think this has merit as a theory. Why? Because you, Gregory, and I are spending time on this website versus looking for food. LOL!
+ Gregory Maxwell 1 month ago
I updated my analysis to also show the impact of difference in the standard deviation, as well. It’s quite considerable.

My argument is quite emphatically not /just/ that there are multiple factors: The core of it is that when you select from the better performers you magnify whatever difference exists between men and women greatly. Even if math skils are the only factor, with the cited 0.15sd difference in the mean if you’re picking students from the top percentile of the general population you’ve accounted for roughly half your gender bias on the basis of a single skill-set alone and without factoring in any difference in the variance of male and female performance.

But I wouldn’t be so foolish to claim that this explained everything even if the numbers worked out right: Skills differences don’t have to be biological in origin.

If I were trying to pin it on biological origin I’d look at factors such as brain mass (~0.8xσ greater in men; which isn’t enough to explain the differences because brain mass is only weakly correlated to intellectual performance) or Don’s glucose consumption. I also expect interest to be a bigger factor than raw skill, but like skill interest may or may not have biological origins.

I guess I misunderstood the position you were taking: If you were saying that a difference of 0.15sd isn’t enough to make a single skill non-trivial factor, I can’t agree. But does it explain it entirely? No, not by itself.

And absolutely— My position does support that any kind of small bias can have a large effect, so long as you’re either combining influencing factors or selecting people with high (or low) amounts of that characteristic. Skills biases, interest biases, social factors (such as outright discrimination), and biological characteristics can all have unexpectedly large contributions to gender bias in this model.
+ Mike Roberts 1 month ago
What is missing is the explanation for the horizontal axis of the graph: 'ability.' This is something that is very difficult to measure and very dependent upon how it is defined. Are we defining ability as the proven capability to perform certain activities, or are we talking about the potential to perform those acts? The latter would be more accurate, but phenomenally hard to measure. Either way, we are questioning ability based upon what criteria? Is this a measure of the ability to perform well in school and on math tests? If so, up to what level: high school, college, graduate? Is this the ability to use math in concrete and practical applications and which applications are tested: calculus, geometry, statistics?

I completely agree that Computer Science has little in common with mathematics much to my chagrin. This used to be the case because CS fell under no other program and math was the closest cousin. My college’s program was still based on this antique, historical view of the field which left me with what was essentially a math degree with programmed tacked on to it.
+ Terri Oda 1 month ago
Also, a lot of people have asked ’isn’t the curve a bit flatter for men than for women?’

The answer is yes, in the real world the curves aren’t identical, but the differences are at the extreme ends (there are more incredibly gifted and incredibly stupid men). Because the differences largely affect the ’tails’ of the distribution, they affect so few individuals that they don’t have a huge impact on the end results. More precise graphs would have complicated the explanation with very little benefit, and when you’re trying to fit into a handful of slides, every word counts!

Since I was aiming for a simple explanation, I went with simplified graphs.

Comments 1 - 10 of 13 previous next

Notes on slide 1

18 Favorites

Mark Matienzo, Applications Developer at The New York Public Library, favorited this 2 weeks ago
Selena Deckelmann, Software Engineer at End Point, favorited this 2 weeks ago
Tags math womenintech biology
Paul Stalenhoef, Software Devloper at Everest, favorited this 3 weeks ago
Tags separate tags by comma
Jen McCabe , Chief Patient Advocate, International healthcare consultant and blogger, Nexthealth.NL organizer and Health 2.0 analyst at Organized Wisdom, Health Management Rx, Health 2.0 , favorited this 1 month ago
Aquafornia at Aquafornia, favorited this 1 month ago
Sarah Allen, Software Developer favorited this 1 month ago
Eleanor McHugh, Freelance Reality Consultant at Games With Brains, favorited this 1 month ago
Guilherme Zühlke O'Connor, Web Developer at Yahoo London, favorited this 1 month ago
monad favorited this 1 month ago
Tags gender
Simon Law, Drunken Master at Akoha, favorited this 1 month ago
Amanda Wilson, Student at home, favorited this 1 month ago
Patricia Araque at Ellas 2.0/ Atalaya Formación, favorited this 1 month ago
Brianna Laugher, Software developer at ToggleText, favorited this 1 month ago
Claudine Chionh, Research Assistant at University of Melbourne, favorited this 1 month ago
Tags computing women mathematics
Kate Carruthers, Consultant at Sydney, favorited this 1 month ago

How does biology explain the low numbers of women in computer science? Hint: it doesn't. - Presentation Transcript

How does biology explain the low numbers of women in computer science? Hint: It doesn't.
My name is Terri. I'm a mathematician.
I'm also female .
Nowadays, I work as a computer scientist. There aren't that many women in CS.
People like to say this is due to biological differences in math ability between men and women.
Turns out, people really suck at math.
Let me explain.
People claim the biological differences go like this: Rawr! I eat calculus for lunch! Math is hard. Let's go shopping! Men Women Rawr! I eat calculus for lunch! Math is hard. Let's go shopping! Men Women
That's not how it works Rawr! I eat calculus for lunch! Math is hard. Let's go shopping! Men Women Rawr! I eat calculus for lunch! Math is hard. Let's go shopping! Men Women
Ability graphs look more like this: Most normal people fall somewhere near the middle Only a few geniuses Ability # of people
When they hear men have higher math scores than women, people guess math is like this: Ability # of people Men Women
Which could explain why computer science is around 75% male... Ability # of people Men Women Must be at least this tall to write computer code
...except that it's a lie. Lies, damned lies, and statistics, eh?
First, CS doesn't require that much math ability. When I was an undergrad, we drew the graph like this: Trees Computer Science Majors Slime Mould Moose Math majors
Heh.
But degree rivalry aside, I've been teaching CS for 7 years. You only need moderate math skills to code. Ability # of people Level needed to code
So that'd be something like this... Old Graph: Very few women New Graph: Lots more women Ability # of people Men Women Must be at least this tall to write computer code Dotted line is average for both genders
Except... Remember how I said the graph is a lie?
Ability # of people Men Women
The population difference looks more like this: Ability # of people Men Women
Don't believe me? Here's the graph from a paper on the subject. Hyde, J; Fennema, E; Lamon, S. “Gender differences in mathematics performance: A meta-analysis.” Psychological Bulletin. Vol 107(2), Mar 1990, 139-155.
So if we put that line back in... We should have nearly 50% women Ability # of people Men Women You must be approximately this tall to write code
Therefore, Biological differences do not account for the gender disparity in computer science. They can't. They just aren't that significant. Not even close.
Also... You know who really sucks at math? People who think biology explains why there aren't more women in CS.
Now you know. Thanks for listening.
This presentation was created by Terri Oda And is released under a Creative Commons Attribution-Share Alike license: If you want to use it in other ways, just ask: [email_address] Or email to let me know you liked it!