[TOS] how broad a mandate?

[Greg Wilson]

Thanks to everyone who responded to my question about whether material on 
the gender imbalance in computing as a whole, and the even greater 
imbalance in open source, ought to be included in a course of this kind.
I've done a lecture like this in my CSC301 "Intro to Software Engineering" 
course for the last two years, and I'd welcome your thoughts on whether 
you think it would be a good starting point.

I begin by telling student that according to Statistics Canada, Chinese 
Canadians make up about 3.5% of the population. Our Computer Science 
classes, however, are usually 30-40% ethnic Chinese. I then ask whether 
anyone believes that "proves" that Chinese brains are better wired at 
birth for programming than other brains.  The answer, of course, is "no" 
(although there's always one guy in the class who will say "yes" as a 
joke).

I then point out that Afro-Caribbean students are much rarer in our CS 
classes than they are in Toronto as a whole; again, nobody will blame that 
on genetics.  The third step is to pull up statistics about women in 
computing and ask whether *that* is nature or nurture, then go into the 
rest of the talk below.  I haven't (yet) added material specific to open 
source; I'd welcome ideas about how to do so.

Thanks,
Greg

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Some Statistics

Figure: Science and Engineering Degrees 1985--2004

Figure: Computer Science Degrees 1985--2004

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Why Is This In A Software Engineering Course?

    * The world is not run by technologists
      * It's run by people who can argue well about things people really care about
      * If you want to run things, you'd better learn how to do this
    * Anomalies point to new understanding
      * Asking "why" is the beginning of knowledge
    * And yes, I personally think we can and should do better
      * "Philosophers have only interpreted the world; the point, however, is to change it."

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A Few Things to Keep In Mind

    * Asimov's Other Law (rephrased): In the time it takes to refute one piece of BS, someone can spout ten more
      * Meticulous argument usually isn't stirring
      * Drowning an opponent in specious (def: plausible but false) claims is a good tactic, but rarely leads to truth
    * Every bell curve has two ends
      * So there will almost always be examples of people who succeeded despite X, or failed despite Y
      * To be true, a general claim must therefore be based on data, not anecdotes
        * And yes, you can prove anything with statistics...
        * ...but you can tell any lie you want to in English, too
    * An attack upon one of your beliefs is not necessarily an attack upon you as a person
      * Conversely, *ad hominem* attacks are fallacious (though often effective)
    * Crass is not automatically funny
      * And cynical is not automatically smart
    * We too are wrong about something
      * By modern definitions, most of our grandparents were racist homophobes
      * By our grandchildren's definitions, we will be splodgeous flibulators

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Start With Academia

    * The gender ratio in North American high school math and science classes is roughly even
    * But the gender ratio among university professors in those fields is five to one
    * Why?
      * Are men intrinsically better at math?
      * Is there discrimination of some kind?

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An Informed Argument

These quotations are taken from *Why Aren't More Women in Science?*

[Alpha] The spread of abilities among men is greater than the
spread among women, i.e., the male bell curve is flatter and wider
than the female bell curve.  This is why the male:female ratio in
students scoring 700 or more on the SAT-M (the math portion of the
Standardized Achievement Test) is 13:1.  It's therefore not surprising
that men outnumber women in numerate disciplines.

[Beta] That 13:1 ratio comes from 1983.  By 2005, the ratio was
only 4:1.  What's more, the differences in ability between American
students and those in Europe and Japan are greater than those between
the genders.  Surely that's proof that socialization is responsible?

[Alpha] Not necessarily.  Women tend to outperform men on tests
of verbal fluency, arithmetic calculation, perceptual speed, and
memory for spatial locations.  Men, on the other hand, tend to do
better at verbal analogies, mathematical word problems, and mental
rotation (i.e., the ability to look at several pictures of 3D objects,
and figure out whether they represent the same thing from different
angles or not). If you statistically subtract the influence of
rotational ability from SAT-M scores, it eliminates the sex
differences.  Being able to see things in 3D must therefore be
important to mathematical thinking, and men just happen to be better
at it.

[Beta] But excelling in science, as in any career, requires
single-minded dedication: according to E.O. Wilson, you need forty
hours a week for teaching and administration, twenty on top of that
for basic research, and another twenty to do really important
research.  What's more, you need to put in these hours when you're in
your twenties and thirties, which also happens to be the time most
people start families, or start caring for elderly parents.  In our
society, these burdens fall disproportionately on women.  The end
result is about as fair as telling athletes who are just about to
enter the major leagues that they have to cut their training time in
half.

[Alpha] Hang on---the fact that more women than men devote
themselves to family is a choice.  There's lots of research showing
that on average, men tend to prefer working with "things", while
women prefer working with "people".  What if society's expectations
simply reflect people's preferences?  You don't have to shift the mean
of a bell curve very far to have a dramatic effect on numbers in the
upper tail.

[Beta] All right, let's talk about shifting the mean.  Research
by Dweck and others has shown that if students---both male and
female---believe that something is a "gift", i.e., that people are
either born good at it or not, then they are less likely to do well at
it, because the first time they hit a setback, they conclude that they
"just don't have the gene".  If, on the other hand, they are told
that mastery of the ability has been proven to depend only on hard
work, they will, on average, do better.  Couple that with societal
stereotypes, like Barbie dolls saying, "Math is hard," and it's easy
to see why women are underrepresented at the upper levels of math,
science, and engineering.

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Unlocking the Clubhouse

    * [CITATION] describes a multi-year project at Carnegie-Mellon to investigate:
      * Why so few women went into CS
      * Why the dropout rate among women was higher than among men
        * Despite the fact that their grades were usually slightly higher
      * What (if anything) could be done to change those facts
    * Conclusion 1: people are conditioned in many small ways to believe that computers are "boy's things"
      * Advertising is a multi-billion dollar industry because it works
        * "Like water on stone..."
      * Most families put the computer in the boy's room because "he's the one who uses it most"
        * Which becomes a self-fulling prophecy
      * Women in programming teams disproportionately likely to "wind up" doing documentation and testing
        * "It is apparent to anyone who actually knows them that most Chinese prefer to be given work that is intellectually undemanding."
    * Conclusion 2: the "who needs a social life?" ethos drives many people away
      * Not just women: three quarters of students of both genders believe that they do not fit the stereotype of a computer science students
      * So bright people who want to make a positive impact on the world go elsewhere
        * Question: are the 200:1 gender ratio and user unfriendliness of open source both reflections of this?
      * Network effects can work against you, too...
        * Many unmarried women wear rings at conferences in self-defence
        * And eventually stop going anyway
    * Conclusion 3: this can be changed
      * High school outreach: "as the twig is bent, so grows the tree"
      * Connecting CS with the real world
      * Results:
        * Female undegraduate enrolment at CMU rose by more than a factor of four
        * Dropout rates decreased significantly
        * For *both* genders