
Men’s and Women’s Brains Appear to Age Differently - bootload
http://nymag.com/scienceofus/2015/11/there-are-gender-differences-in-how-brains-age.html
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cm2187
It's a courageous study in the current environment. Is it even legal in the US
to suggest there could be an intellectual difference between sexes, even at a
certain age?

It reminds me of this
[https://en.wikipedia.org/wiki/Lysenkoism](https://en.wikipedia.org/wiki/Lysenkoism)

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hajile
You mean like when Lawrence Summers was forced to resign from Harvard because
he said that (well-known) differences in IQ distribution _might_ have an
impact on the number of women in STEM, but more research was needed (and
fighting against sexism should also continue).

He was completely right with his information. The bell curve for male IQ is
much shallower resulting in men greatly outnumbering women both at the top and
the bottom of the IQ chart (note: that doesn't mean that a man with the same
IQ as a woman is smarter, just that there are more men with higher IQs).

The idea that abstract logic, spatial reasoning, and pattern recognition (what
IQ indicates) are primary components in being good at STEM is well-known too.
The one idea definitely implies the other and stating that causal implication
shouldn't be a crime.

Nobody stepped forward to disprove the science. They simply screamed sexism.
They didn't care that he had even said that fighting the sexist component was
also important. They didn't care that he had said the science might be
disproven. They only cared that they didn't like the idea no matter if it was
true or not.

History is filled with ideologues hurting and killing men of science for ideas
we now know to be true. Freedom to research, study, and publish those studies
without being threatened or harmed is paramount. If there's a problem, then
fight the science -- not the scientist.

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GFK_of_xmaspast
There was a big followup article in the "Notices of the American Mathematical
Society" that actually looked at the numbers and concluded Summers was not
supported by the data.

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hajile
Here are the only two articles I can find mentioning Larry Summers

[http://www.ams.org/notices/200810/fea-
gallian.pdf](http://www.ams.org/notices/200810/fea-gallian.pdf)
[http://www.ams.org/notices/201201/rtx120100010p.pdf](http://www.ams.org/notices/201201/rtx120100010p.pdf)

They do not address the question of IQ in any meaningful way. They only seek
to show that women can succeed in mathematics. Summers in no way said that
women could not succeed in math (or any other STEM field). The question of IQ
has more to do with _potential candidates_ rather than success of those
candidates.

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danbruc
Why does this get so much attention? Men and women are obviously different in
a lot of ways, why should the brain be an exception? Discovering that there
are no differences would be an astonishing result, the opposite is what one
should expect.

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RightWingRabble
Because the official feminist line is there are no physical differences in the
brain of men and women. Extra attention is needed to overcome the rhetoric.

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mkrfox
I want to see a study like this on nonbinary and agender people.

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omginternets
Gender theory is by-and-large a sociological theory, not a scientific one.
It's extraordinarily difficult -- from an epistemological point of view -- to
produce strong evidence for the claim that gender is orthogonal to sex.

What this means, in practice, is that the selection criteria will be vague,
which in turn is likely to produce massively varying results from study to
study.

I see why you're interested in this, but I think you're basing your hypotheses
on a false premise: namely that gender theory is hard science.

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mkrfox
I didn't state any hypotheses or claim gender is easily tackled by science. I
expressed an interest.

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tdkl
What would be the point of the results, if they aren't scientific ? Except who
would pay for them and their agenda.

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mkrfox
"Hard to tackle by science" is not the same as "not scientific." Confounding
variables are notoriously hard to control for in social science, but people
manage to find useful information when they go in without agendas.

~~~
omginternets
You've missed my point: my claim is that your study is necessarily non-
scientific, given the epistemological problem associated with gender/sex
orthogonality.

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known
Unlike men, women's brain is horizontally wired and good at multitasking.
[http://www.webmd.com/balance/features/how-male-female-
brains...](http://www.webmd.com/balance/features/how-male-female-brains-
differ?page=2&print=true)

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nv-vn
The findings are interesting, however I don't think that such a small sample
can be used to make any conclusive assumptions and I think that these findings
should be taken with a grain of salt. Since all these studies tend to have
quite small sample sizes, it is quite likely that they will contradict past
studies of similar sizes.

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omginternets
n=50 (closer to 100 with the control group) is massive for a brain-imaging
study.

More to the point: statistical power matters, which is only indirectly related
to sample size. I mean no disrespect, but this kind of criticism usually
betrays ignorance of statistics and scientific methodology.

Do you suspect the study is under-powered? If so, why?

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nv-vn
>n=50 (closer to 100 with the control group) is massive for a brain-imaging
study.

The problem I see with it being a small group is not necessarily that the
results are inaccurate because of size/lack of statistical power, but more so
because of the fact that a lot of variables will not show up in a small
sample. For example, it is possible that certain diseases that they found to
be more common in one sex than the other are only more common in caucasians
and the same relationship does not occur with other races (since this happened
in Hungary, it is very unlikely that non-white people were a part of this
study). The numbers determined here probably apply very well to people in
Hungary but they might be very different from what we'd find in the United
States or in India, for example.

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omginternets
What you're describing is an epiphenomenon, and increasing the sample size
won't fix this. In fact, increasing the sample-size (i.e. over-powering a
study) _increases_ the propensity for spurious correlation.

This may well be an epiphenomenon, but that's why reproductibility (not
statistical significance) is the gold-standard of science.

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tomp
> In fact, increasing the sample-size (i.e. over-powering a study) increases
> the propensity for spurious correlation.

Huh? If there aren't just 2 kinds of brain, but instead 30 different kinds,
then a study with 300 brains is much more likely to catch all 30 kinds of
brains than a study with just 50 brains.

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omginternets
So you're worried about a representative sample?

This is -- again -- only indirectly related to sample size. If the sample was
randomly selected and the statistical power is great enough, then any
correlation it's missing is marginal; this is a feature, not a bug!

You're not entirely wrong insofar as brain-imagery studies rarely conduct
random samples, but increasing your sample size won't fix that.

