A bit more about your comment as promised.

>> There are whole fields of research devoted to the questions you're raising. As
such, it's hard to reply with anything that would do justice to them. This
isn't to say your questions aren't important, just that your lack of answers
reflects your ignorance more so than that of the researchers. I say this not
antagonistically but to suggest that it's important to understand that what
you see is not always all there is to say.

Another comment brought up the term "construct validity" and it seems to match
my concerns exactly. I am glad there is debate on that.

I study for a PhD in AI and I have similar concerns about research in my
field. For instance, in AI, research often claims to have modelled human
abilities such as "reasoning", "emotion" or "intuition". I'm personally
uncomfortable even with well-established terms like "learning" (as in "machine
learning") and "vision" (as in "machine vision")- because we don't really know
what it means to "see" or to "learn" in human terms so we shouldn't be hasty
to apply that terminology to machines.

This tendency has been criticised from the early days of the field but we seem
to have regressed in recent years, with the success of machine learning for
object classification in images and speech processing taking the field by
storm and leaving no room for careful study anymore, it seems. But that's a
conversation for another thread.

In AI, I'm worried that calling what algorithms do "attention" or "learning to
learn" etc, gives a false impression to people outside the field about the
progress of the field, and, in the end, about what we know and what we don't
know. This is certainly not advancing the science.

I think the same about psychology and studies like the ones we're discussing
here. If psychologists are happy measuring the correlations of the answers in
their questionnaires, and they call the quantities measured in this way with
names like "agreeableness" and "sensitivity"- doesn't that just give the
entirely wrong impression to people outside the field who have a very
different concept of what "agreeableness" etc means?

I say that this is "not advancing the science". You could argue that the
science is doing fine, thank you, even if lay people don't get it. But, if the
way the science is carried out creates confusion and influences real behaviour
and decisions, as studies like the ones discussed above have the potential to
do- is that really a beneficial outcome of research?

To put it plainly: as a researcher I don't aspire to create confusion, but to
bring clarity in subjects that are hard to understand. Isn't that the whole
point?

>> In the end, questions of sex differences in behavior are about sex differences
in behavior. And that's what this research addresses.

I understand this. But, my concern here is that asking people "what do you
think about sex differences in behaviour" is likely to return results tained
by ungodly amounts of cultural bias that would be impossible to disentangle
from any other results. How is this addressed in such studies? How do you
account for people answering questions about sex differences in behaviour
based on what they are used to think about sex differences in behaviour,
rather than what they actually observe?

P.S. Hey, your answer does do justice to my questions. Thanks for your
patience, again.