
Sex differences - doener
https://darrendahly.github.io/post/2017-09-12-sex-differences/
======
stcredzero
This article is effectively a straw man. It uses an argument which isn't
directly applicable (not central to the points made by James Damore in the
Google Memo) to give an appearance of being reasonable. If you want to be more
familiar with the science James Damore was referencing, take a look at this
video of a presentation by Steven Pinker and the sources referenced therein.

[https://www.youtube.com/watch?v=9PaL5FW5src](https://www.youtube.com/watch?v=9PaL5FW5src)

The key takeaway for the Google Memo, is that James Damore was fired for
referencing mainstream science, then asking if that was relevant to Google's
hiring practices. What's more, many of his coworkers and many of my fellow
college classmates were more than willing to throw him under the bus and
impute all sorts of unsavory thoughts and emotions to Mr. Damore with no
evidence, while the Google management was willing to publicly do the same
while re-disseminating his memo in the worst way possible to encourage
misreadings of it. See also Christina Hoff Summers' video on the subject.

[https://www.youtube.com/watch?v=tu4tB9W3xFo](https://www.youtube.com/watch?v=tu4tB9W3xFo)

Steven Pinker identifies as a feminist, as does Christina Hoff Summers. Diane
Halpern certainly isn't a misogynist.

The extreme left which ascribes to Postmodernist political theories is coming
for the scientists, rationalist nerds, and Aspergers neuro-atypicals. They
want to cow everyone into agreeing to their ideologically driven Lysenkoist-
like censored science. They represent a new authoritarianism operating through
a fear of social ostracism and economic disenfranchisement. (You don't have to
take my word for it -- you can take theirs. Just pay attention to what campus
activists have been saying since about 2014.) If you believe in rational
discourse, free speech, and meritocracy, you need to courageously speak out
against these authoritarians.

(First they came for the social scientists and evolutionary biologists...)

~~~
tptacek
Can you tell me more about what you believe that Pinker video establishes?

I have generally high regard for your comments. But in this instance, I think
your claim about what happened to Damore is facially flawed. Damore didn't
simply "reference mainstream science". Whether you agree with him or not, I
don't think it's possible to defend the claim that he was fired for citations.

I'd also urge you to step back from the Damore framing of this post. I know
why it's hard to escape. But I think the author is just using Damore as an
opportunity to make a more general statistical point. Certainly, at no point
in this post does the author even mention Damore by name, _let alone advocate
for his termination_.

~~~
stcredzero
_Can you tell me more about what you believe that Pinker video establishes?_

What I say it establishes. That James Damore was referencing mainstream
science. One might reasonably conclude that his conclusions are wrong. Here is
an example:
[https://www.youtube.com/watch?v=BIRvtA2JIIA](https://www.youtube.com/watch?v=BIRvtA2JIIA)

I think all of those who concluded that he was being a misogynist have no leg
to stand on. The accusation is levied just to silence views that are not
liked.

 _I 'd also urge you to step back from the Damore framing of this post. I know
why it's hard to escape. But I think the author is just using Damore as an
opportunity to make a more general statistical point._

I don't have a problem with the article's statistical point. I think there are
all sorts of opportunities to make points here.

~~~
dieterrams
> I think all of those who concluded that he was being a misogynist have no
> leg to stand on.

I don't necessarily believe he's a misogynist, but I do think he's in denial
about the impact of sexism on gender gaps. To quote his letter:

"We need to stop assuming that gender gaps imply sexism."

The fact is that we don't have to assume. It's fairly unlikely such gaps are
_entirely_ the result of sexism. But to suggest that sexism does not play a
role in gender gaps is absurd.

Edit: To respond to similar points in the replies, yes, I'm quite aware that
you can read this sentence in the strictest logical sense as saying a gender
gap, in and of itself, does not imply sexism. This is obviously and trivially
true. But studies on evaluatory bias tell us that biases, such as and
including sexism, are in fact the norm. It is so fantastically unlikely that
they are not present among Google's interviewers / hiring committees that the
sentence, taken in the strictest sense, is making an irrelevant point.

Rhetorically, however, it serves the effect of suggesting we ought to consider
it plausible that perhaps sexism isn't at all at play in Google's hiring.
Which, again, is absurd.[1] It would be far more likely that Google's hiring
tilts sexist against _men_ than sexism not being a factor at all.

[1] Note that this has nothing to do with Google specifically, but rather with
humans generally.

~~~
Banthum
Read your quote. It just means that just because there is a gender gap, we
cannot simply assumed there must be sexism.

It is not a statement about a specific case, but a general point on
rationality.

And it is undeniably true in the general sense.

This means that if someone wants to convince us there is sexism in a specific
case, they must demonstrate that specifically, not just note a lopsided gender
ratio and assume the mechanism.

~~~
xelxebar
While we're on the rational point, I personally take inspiration from Bayes
Law---A gender gap is _weak_ evidence for sexist practices. All else equal,
sexists worlds are more likely to produce gender gaps than non-sexist ones.

To me, part of the trickiness of the entire "equality" discussions is that we
don't have clear, "correct" distributions of variable X for demographic Y.

Pure egalitarianism is iffy, because given any distribution, we can
manufacture a demographic that is "underrepresented", so it's not at all clear
that flat equality across "reasonable" demographics is even logically sound.

I kind of piggy backed off your comment there and ran in a bit of a different
direction. Hope you don't mind.

------
haberman
> The apparent [appeal] of this message wasn’t limited to chauvinist TechBros.
> Many “moderate” commentators also seemed quite impressed. After all, the
> memo wasn’t arguing that all men, or even most of them, are better suited
> than women for tech jobs. That would be ridiculous! But since the existence
> of sex differences in some traits is scientifically uncontroversial, some
> supporters of the Google Memo claimed the scientific high-ground. “You see?
> We aren’t sexist or biased”, they proclaimed. “This is just science.” And
> you can’t hate on science.

The tone of this introduction doesn't inspire confidence that the author is
truth-seeking without agenda.

> Remember, a 1 SD shift is a pretty big one (e.g. a difference of 3 inches
> for height), so not suprisingly, the evidence seems to suggest that the 10%
> increase in the mean is the more realistic scenario for most variables where
> differences seem to exist.

Several times he references the Stevens/Haidt results, but doesn't seem to
acknowledge this finding from Stevens/Haidt
([https://heterodoxacademy.org/2017/08/10/the-google-memo-
what...](https://heterodoxacademy.org/2017/08/10/the-google-memo-what-does-
the-research-say-about-gender-differences/)):

> Gender differences in _interest and enjoyment_ of math, coding, and highly
> “systemizing” activities are large. The difference on traits related to
> preferences for “people vs. things” is found consistently and is very large,
> with some effect sizes exceeding 1.0. (See especially the meta-analyses by
> Su and her colleagues, and also see this review paper by Ceci & Williams,
> 2015).

~~~
naasking
> Several times he references the Stevens/Haidt results, but doesn't seem to
> acknowledge this finding from Stevens/Haidt
> ([https://heterodoxacademy.org/2017/08/10/the-google-memo-
> what...](https://heterodoxacademy.org/2017/08/10/the-google-memo-what...)):

Excellent citation. I think it overreaches a little in attributing the
position that women don't _perform_ as well as men at software engineering,
ie. they label many claims red which people have attributed to Damore, but he
didn't make those claims; I believe Damore said the exact opposite actually,
that women absolutely can perform at the same level, but that women simply
aren't _interested_ in CS careers. Your cite covers this in the conclusions,
so it's pretty fair overall.

As your citation explains, in societies with greater gender equality, women
have so many other choice of careers that CS just isn't an attractive option.
Perhaps it's not attractive for reasons that can be changed, but those reasons
should be investigated, not simply assumed to be driven by sexism.

~~~
yellowapple
Hell, for all we know those reasons for disinterest might actually stem from
sexism in some form or other. If that's the case, then that's where we need to
be focusing our attention as a society rather than trying to extrapolate from
the end result (employee gender ratios) alone.

------
bArray
I've made the point more times than I care to mention, put simply there are
two ways to think about the problem. The first is that men are dominating STEM
fields. The second is that women are dominating non-STEM fields.

IMO, the latter is _mostly_ true. Less males are attending Western
Universities than females, yet there is absolutely no push what-so-ever to fix
this. Nobody cares about the lack of men in subjects such as Art or English
Literature and certainly no initiative exists to even begin to correct this.
Nobody is trying to push women into the lower 5% of jobs. Brick layers,
plumbers, electricians - all well paying jobs - where is the push to get women
into those?

There are fundamental differences in the sexes which favour men for some jobs.
For example, millions of years of evolution means that when you take a random
pack of dogs, a group of apes or a gathering of humans and allow them to
discover natural social order - almost always the leader will be male. Whether
we want to accept it or not, we are still just highly functioning animals.

Probably the most concerning, despicable, disgusting act of them all is a
"recognition of women in... award" ( _rarely_ recognition of men of course),
or the manipulation of wages to equal the "pay gap", or biasing employment,
etc. To me, it says "we know women can't compete, therefore we're biasing the
end result to make the outcome equal". It's like first-wave feminism meant
nothing, what was the fight for equal opportunity even about if you only go on
to bias towards equal outcome anyway?

The point: Equal opportunity > Equal outcome

~~~
naasking
> Nobody is trying to push women into the lower 5% of jobs. Brick layers,
> plumbers, electricians - all well paying jobs - where is the push to get
> women into those?

Because these jobs don't address the power imbalance between men and women in
our society. Lawyers and doctors are highly respected careers that influence
the direction of society. Lots of women pushed into this field. Politics also
needs more women, as should be obvious given how much states and Congress
tries to control women's health care options.

Computer science is increasingly pervading every facet of our existence, and
so having gender parity ensures female concerns are equally represented as
this field evolves.

~~~
bArray
>Because these jobs don't address the power imbalance between men and women in
our society.

The "power imbalance" should be represented in all areas, surely? You can't
just have the icing on the cake. And I think you've hit the nail on the head,
this isn't about equality, this is about control, particularly money and
power.

>Lawyers and doctors are highly respected careers that influence the direction
of society.

And have begun to dominate these fields now (although I can't find a source of
that I would be happy to quote).

>Lots of women pushed into this field.

I'm not sure there has been a significant struggle for a long time.

>Politics also needs more women, as should be obvious given how much states
and Congress tries to control women's health care options.

I wouldn't say the main problem with Congress is that there is a lack of
women, I think it's very existence is it's largest issue.

>having gender parity ensures female concerns are equally represented as this
field evolves

"female concerns" sounds like a terribly generic term, you'll have to be more
specific and explain how these concerns override the need for women
representation (not necessarily women by the way, just a person who fairly
represents them) in politics. My thinking is that tech for the most part is
completely genderless, it's simply the application of Science. Most control is
tech can be or has been completely overridden by law.

But in general, I think (without being rude and wanting a genuine reply) that
you've missed my point with regards to the lower 5% of jobs. My point is that
instead of making STEM fields artificially more difficult to get into for men,
another option is to make other fields more attractive. Social care for
example is horrendously dominated by women, yet of massive importance to
society - they are struggling to recruit due to social stigma, yet little is
being done to address this.

------
xupybd
I think one thing the author needs to look at is the number of females trying
to enter this field. When I was studying there was only one female in all of
my computer science related papers. But loads and loads in the papers that
overlapped with the chemical engineers. Many of the female chemical engineers
did a lot better than the bulk of the CS students even when the assignments
involved coding. But it seemed that most of the Engineers performed better
than the CS students

I don't think it's that females aren't good at or don't have natural abilities
equal to men when it comes to programming but for what ever reason (that I
don't care to speculate on) programming is not an attractive career option to
many of them.

So I think this point is a little off

>>At this point, anyone already familiar with the normal distribution is
probably having a sensible chuckle. This is because while Google might be
selective in their hiring practices, they aren’t +4 SD selective.

Because there is just a much smaller number (at least in my experience) of
female developers. So if one company is 50-50 male to female they would have a
disproportionate number of the total population of female developers.

------
JamesBarney
17% of google devs are women 18% of cs majors are women.

This isn't a google problem, no need to talk about variances.

[http://splinternews.com/survey-says-92-percent-of-
software-d...](http://splinternews.com/survey-says-92-percent-of-software-
developers-are-men-1793846921)

[https://www.ncwit.org/infographic/3435](https://www.ncwit.org/infographic/3435)

~~~
fulafel
Are both of those US-only figures? Google is a multinational company. If the
"all cs majors" figure is US and the Google 17% is global, then they are not
comparable. If you want a global conclusion you should include weighted CS
grads % from Google campus countries, if you want a US-only conclusion you
need some way to exclude devs from non-US Google campuses.

~~~
JamesBarney
[https://www.usatoday.com/story/tech/2014/05/28/google-
releas...](https://www.usatoday.com/story/tech/2014/05/28/google-releases-
employee-diversity-figures/9697049/)

This says it's an international number but it also puts the % of female CS
grads in the U.S. at 12%.

Other ways it might be off include that women who get CS degrees enter non-
development positions at higher rates(Project managers, business analysts,
etc) and drop out of the industry at higher rates(I've heard).

------
naasking
> The differences in means is what the Google Memo seems to focus on

No it doesn't. "Mean" isn't used in this way even once in the whole memo. The
only indirect reference to means differences are two sample graphs that Damore
only uses to explicitly label judgement based on means as _fundamentally
incorrect_ because it ignores significant overlap between groups. The greater
male variability hypothesis is the only correct way to interpret the memo.

Further, this article's conclusion doesn't follow from the facts as presented.
It's literally asserting, "I can't fathom the existence a gender-specific
difference of 4SD, therefore it doesn't exist and so such a difference can't
explain our observations". Didn't you miss a step where you have to actually
demonstrate that this difference actually doesn't exist before you can dismiss
it?

Certainly we can debate how _reasonable_ such a distribution might be given
what we know about gender-specific variability of other traits, but we
absolutely can't dismiss it out of hand.

Consider, for instance, that "hiring at Google" isn't the _first time_ this
variability comes into play, but instead the _Nth time_ , where N is fairly
large. If people tend to pursue things they're naturally good at, and such
variability will obviously influence what genders will be naturally inclined
to pursue, on average, then this acts as a compounding filter over a decade
where students are first exposed to computer science.

Consider the distribution characterizing "people's net worth". The variability
in people's ability to make and save money isn't that broad, but including
compounding effects of interest on debt and investments, even these small
differences will yield _huge_ variability in your net worth on your death bed.

------
nemo1618
>Starting again from the standard normal, adding 0.10 SD to the male mean
would lead to a 1.2 to 1 male to female ratio (at ≥1.5SD); but adding a full
SD would give almost 5:1. Remember, a 1 SD shift is a pretty big one (e.g. a
difference of 3 inches for height), so not suprisingly, the evidence seems to
suggest that the 10% increase in the mean is the more realistic scenario for
most variables where differences seem to exist.

The average male is about 6 inches taller than the average female. If a >1SD
difference is possible in height, why not other areas? Or am I missing
something here?

~~~
klodolph
[deleted]

~~~
Smaug123
Is it? Have I just really badly misunderstood?

> Starting again from the standard normal, adding 0.10 SD _to the male mean_
> would lead to a 1.2 to 1 male to female ratio (at ≥1.5SD); but adding a full
> SD would give almost 5:1 [emphasis mine]

------
AnthonyMouse
> So what happens if we instead say that Google recruits from the mere mortals
> with Techiness scores ≥ 2SD, which is still the top 5% of all people? That
> ratio drops to 1.5 to 1. Despite my enjoyment of Google’s products, I have a
> hard time believing they are even this selective

Being a software developer _at all_ is ~2.5% of the US population (and even
less internationally).

Moreover, if the variability hypothesis is true then the entire point is that
1SD for men will be larger in absolute terms than 1SD for women.

~~~
tptacek
First, the baseline isn't the total US population. We're not surprised that
toddlers and retired World War 2 veterans aren't software developers. You're
looking for the percentage of the labor market, which, of course, is higher.

Second, what you're pointing out is orthogonal to the question. The _premise_
of the question is that there aren't many women software developers; the
dispute between the memo and Dahly is _why_ that is.

Third, if you bring international labor into this, you muddy the issue even
more, because female participation in the software development market is
sharply higher in some major overseas markets.

I don't follow your second sentence.

~~~
AnthonyMouse
> First, the baseline isn't the total US population. We're not surprised that
> toddlers and retired World War 2 veterans aren't software developers. You're
> looking for the percentage of the labor market, which, of course, is higher.

~2.5% is the percentage of the US employed workforce.

> Second, what you're pointing out is orthogonal to the question. The
> _premise_ of the question is that there aren't many women software
> developers; the dispute between the memo and Dahly is _why_ that is.

The argument is that Google would not be excluding >95% of people, but 97.5%
aren't even software developers.

> Third, if you bring international labor into this, you muddy the issue even
> more, because female participation in the software development market is
> sharply higher in some major overseas markets.

But why would a US employer hire foreign employees from those markets and not
the world market overall?

> I don't follow your second sentence.

The complaint is that four standard deviations is a lot, but it's not actually
four because the size of a standard deviation is not the same.

------
klodolph
A major problem with this kind of armchair analysis is that in practice
variables are only ever approximately normal, and the differences are most
noticeable in the tail.

Taleb's book The Black Swan talks about this phenomenon, but I can't recommend
the book--it's basically one chapter's worth of material stretched over 400
pages.

~~~
tptacek
Darren Dahly is a biostatistician and lecturer at University College Cork. I
don't think you get to dismiss his analysis as "armchair".

~~~
klodolph
"Armchair" in this case means "without looking at the data". We're making
hypotheses about the tail of a distribution based on the assumption that the
distribution is normal, rather than looking at the data. It's still a problem
with the argument, no matter who makes it.

It _sounds like_ you're saying that it's more important to know the identity
of the person making the argument than the content of the argument itself?

------
TheCoreh
> We will further assume that the distribution of Techiness is sex-specific;
> and that those sex-differences exist at birth and aren’t the result of later
> social or environmental factors.

That's a really strong assumption, and one that even the author of the
"Diversity memo" didn't make, IIRC. In fact it would make sense to assume the
exact opposite: Whatever the differences of "initial state" may be, they will
compound over time in a "feedback loop".

Another issue: "techiness" isn't the only or even the main factor considered
when hiring employees. If you consider this vaguely defined variable a
function of several other variables, some not related to technology at all
(e.g. cooperation, willingness to work at a major corporation, to work long
hours, alma mater, other job opportunities, etc) you're left with basically no
way of estimating if the standard deviation differences between males and
females are, say, 1.5x or 4x.

The author also didn't combine simultaneously changes in mean and standard
deviation on his analysis, and didn't consider the possibility that the traits
might fit a different curve (e.g. Tracy-Widom)

------
yellowapple
Yet another article that misses Damore's point.

Damore's hypothesis is not about ability or qualification. It's about
_interest_. The paper claims that women are underrepresented in the tech
sector simply because they're less interested in tech than men, not because
they're less qualified or capable.

I disagree with that hypothesis, sure (quite a bit of anecdotal evidence among
coworkers and family/friends actually suggests the opposite, and I don't think
Damore adequately isolated supposed biological factors from potential
socioeconomic factors), but I at least bothered to read the paper before
blabbing about it on the Internet.

------
dnautics
> So what happens if we instead say that Google recruits from the mere mortals
> with Techiness scores ≥ 2SD, which is still the top 5% of all people?

Does anyone have any idea of what the selectivity at google hiring is? How
many people do they reject for each person they hire? Also using this number
would have to roughly take into account that the distributions are supposed to
be "over all people" whereas the hiring pool is self-selected. Simply by being
able to get python to print "hello world" you're probably already in the top
15% of "all people".

I am also curious about modeling this where the median of population A is
LOWER than population B but variance differences and selectivity pushes
selection for population A higher. (to wit: I think, and the scientific
evidence supports me, that men are generally dumber than women)

~~~
trhway
> I think, and the scientific evidence supports me, that men are generally
> dumber than women

and given that the programming is a pretty dumb job, a blue-collar job of the
21st century ('S' in CS isn't a real science), i think we have the
explanation.

------
suneilp
> Science is a tool for explaining what we observe. There is almost always
> more than one plausible explantion for any observation, and so it’s the job
> of the scientist to pit these against each other and see which comes out on
> top.

That is such a crude way to go about things.

It's been suggested before that there are larger influences from society on
how men and women should act and live their lives. I still believe that. I
don't think we've made a lot of progress on gender issues. A lot of them still
lurk under the surface and the PC culture shields them and prevents discovery
and resolution.

~~~
david38
A lot from when? In the 80s, a woman couldn't get a credit card w/o her
husband co-signing. That's a pretty huge access to money they previously
didn't have.

------
singularity2001
sorry for the lazy reading but why does he center both normal distributions at
0? is there no scientific proof for increased 'techiness' in males? and how
does he come to the conclusion that "they don’t seem to be the dominant
factor."?

~~~
Smaug123
Near the end of the post, the author considers what happens when the means of
the two distributions are different. "They don't seem to be the dominant
factor" because in order to fully generate the observed ratio of male/female
employment at Google using only the "general techiness factor", one needs to
hypothesise implausibly large differences in the underlying distributions of
techiness.

~~~
naasking
> in order to fully generate the observed ratio of male/female employment at
> Google using only the "general techiness factor", one needs to hypothesise
> implausibly large differences in the underlying distributions of techiness.

Except it's only implausible if you assume the conclusion. The implausibility
is literally summoned from the aether, because it's certainly not based on any
empirical facts.

------
njarboe
"This is because while Google might be selective in their hiring practices,
they aren’t +4 SD selective. This is because, given a normal distribution, we
only expect 0.000032% of observations to have a score ≥ 4 SDs above the mean."

Maybe there is something I don't understand but 4 sigma is .006334% so > 4SD
would be 0.003167%.

"This percentage equates to just 273 New Yorkers, 30 people from San
Francisco, or just 11 thousand people in the entire United States, the 3rd
most populous country on earth."

0.000032% of 320 million would be 102 people.

~~~
itsdrewmiller
Drop the "%" and it all makes sense.

------
imtringued
The article is too google centric. It's believable that google is hiring a
significant chunk of the top 0.3% of the US population because they pay
incredibly high salaries (300k+).

It would make more sense to look at average companies that don't have the
resources to hire from the right side of the normal distribution. If they have
a 4 to 1 ratio where a 1.5 to 1 ratio was expected that means the differing
distribution is one of the less significant possible factors out of many.

------
he0001
Even if I think the Author have a point, isn't the assumption of Googles
hiring practices flawed since they are making an selection of an already
biased selection, meaning hiring from the top tech institutions in the world?

