It uses standardized test scores. I quote findings below. Remarks inside parentheses are mine.
"The third column in table S1, reports the estimated male/female variance ratios with standard errors in parentheses. In all but five countries (There are 41 countries) we can reject the hypothesis that the variance ratio is equal to one at 5% level. In all the countries where this hypothesis is rejected, the variance ratios are larger than one indicating that the male variance in reading is higher than the female variance."
In other words, male variance > female variance with 95% significance level in 36 countries, and no statistically significant difference in 5 countries. There is no countries where female variance > male variance with statistical significance.
There are various interpretations of this result. The usual interpretation is that there is a sex difference in variability. Another interpretation is that since variability difference is not universal (in 5 countries it is not statistically significant), variability difference is cultural. The later interpretation is argued in PNAS paper cited below.
I also found this little thing that implies that the score distributions aren't symmetric (I think):
"There is no clear pattern in the male to female ratios at the bottom 5% of the math distribution. This ratio is different from one in only 15 countries but in some countries it is larger than one and in others smaller. On the other hand, at the top 5% the ratio of boys to girls is larger than one in 35 countries with the highest estimated ratio in Korea (2.55). In these 35 countries, boys are clearly over-represented at the top end of the math distribution. The quantile differences at 5th and 95th quantiles confirm the same finding, with no clear pattern at the 5th quantile but positive and significant differences in all but five countries at the 95th quantile. "
Doing a quick test, I took some random normal numbers with variance ratio 1.4, and found that the variance ratio is not very sensitive to if I calculate it using the full sample, the bottom half or the top half. In other words, for a normal distribution the reported ratios for the 5th and 95th quantile should be the same within the errors, but this is never the case for mathematics so the scores simply aren't normal.
How do they reach this conclusion? 36 for, 5 against at 95% significance level would expected given random variation, no?
Either way, a 95% significance level by itself tells us little about how we should interpret those 5 against.
For an even more "untouchable" subject try: https://en.wikipedia.org/wiki/Race_and_intelligence
It's important to remember that high IQ and high-status positions don't correlate. High IQ is no indicator for success in live. If you actually measure people with higher societal status, you'll probably find quite a few with high IQ. But we must not interpret that in any way, because that's hindsight bias: We don't see all the high-IQ people not in high-status positions.
Psychologically, the more relevant variable for success in live is motivation.
(As a sidenote, IQ itself is by no means an objective measurement. The theories of intelligence are and were strongly influenced by the respective world views of its creators. Cattell for example, the inventor of fluid and crystallized intelligence, most probably differentiated between both as a way to explain racial differences: Everybody has crystallized intelligence, but only the white have highly developed fluid intelligence. He distanced himself from his early views a few months before his death, but the theory remained popular for many decades.)
Which is still pretty small compared to who your parents are (in terms of the upbringing offered to you and the connections it offers).
> Which is still pretty small compared to who your parents are (in terms of the upbringing offered to you and the connections it offers).
It quite looks like it, yes. That's why I prefixed that with "Psychologically". I actually had written more or less your answer after that, but then deleted it because I didn't want to derail the thread :)
https://cogsci.stackexchange.com/questions/5740/are-there-re...
That said, I think we haven't quite reached the point where we can rule out hegemony when it comes to imbalance in general.
You could go the other way and assume that it is all explained by a single trait -- give Congresspeople an IQ of 150, CEOs 160, and just assume that the trend in the chart continues and the overrepresentation of males is even higher at the further extremes.
This, however, runs into the problem that we've measured the IQs of Congresspeople and CEOs. Congresspeople are starkly average, with Representatives averaging 101 and Senators 98, so unless you believe that half of Congresspeople are below 50 and half above 150, the expectation based on this research is that more than half of Congresspeople should be women. Likewise, CEOs only average -- optimistically -- 130, where the gender split is only 46/54.
We're assuming that men dominate the tails of the intelligence distribution. So the real question is, does being in the top 1-2 percentile make you much more likely to succeed in so called high-status positions compared to 'only' being in the top 5-7 percentile.
;-)
> negative stereotypes raise inhibiting doubts and high-pressure anxieties in a test-taker's mind... even passing reminders that someone belongs to one group or another, such as a group stereotyped as inferior in academics, can wreak havoc with test performance.
http://www.apa.org/research/action/stereotype.aspx
http://www.npr.org/2012/07/12/156664337/stereotype-threat-wh...
http://steinhardt.nyu.edu/news/2008/1/29/Stereotype_Threat_A...
Intuitively it made much sense for me when I was in high school and trying to figure out the world.
People perceive high, even extreme intelligence as some beneficial trait, but I don't think that's how we should look at things. Evolution does not care about men as much as it does about women. Man can be far from being best fit for raising children and still forward his genes to next generation. Women need to be much more optimized, stable. Too high or too low intelligence is a neurological flaw in men that makes them worse parents from evolutionary perspective but they can get away with it. Women can't.
It might change after many generations of society that takes care of children of deranged or disinterested mothers. Having extra copy of X chromosome sure does help with stability but there are many examples in biology where simple obvious mechanism are overruled by special contraptions forced by evolution to result in the opposite of what simple logic would dictate.
This would seem to predict that men show less variance than women in whether or not they forward their genes. They actually show more.
Why would too high intelligence make someone a worse parent?
The GP is arguing that men have the luxury to propagate their genes even if they do not make good parents, while women have to be a good parent in order to make their offspring survive to adulthood.
> This would seem to predict that men show less variance than women in whether or not they forward their genes
Not necessarily. Ratio of variance of whether women and men forward their genes is influenced with many factors. Extreme men can have less variance then equally extreme women, but average women can have less variance because there is very few extreme women. Also what I'm referring to is about times that shaped modern day men and women. Child of extreme woman had very small chances of surviving back then. Child of extreme man would have had better chances.
> Why would too high intelligence make someone a worse parent?
I'd want to back that up with something solid but only things that come to my mind are anecdotes of absent minded geniuses, emotional volatility associated with intelligence, social misalignment that could get a person in serious trouble (Archimedes?) or simply loosing interest in own 'plain' children.
https://en.wikipedia.org/wiki/Sex_differences_in_intelligenc... says it's controversial near the top. But the citation is a single paper which disagrees, and the rest of the article seems to support the hypothesis.
edit: removed "unpublished"
http://www.pnas.org/content/106/22/8801.long
I think that some ideas gain traction because they fit well into people's narrative, even when the evidence is not yet strong enough for real trust in them.
1. How does that correlation disprove it? It's entirely consistent with one common cause for all inequalities.
2. "Mean gender gap" is for people who did school-related tests, mainly PISA, not the general population. If the greater variability is true there will be much more severely mentally retarded males unable to even read. Depending on the size of the effect, the different mean could in fact confirm the hypothesis (that the mean is the same but std is greater).
3. No analysis whether the distribution of countries' result is consistent with greater variability for the whole human population. Especially jarring when they mention Iceland, a country so small that there are many individual schools elsewhere with more students than they have.
>These findings challenge the Greater Male Variability Hypothesis, which, if valid, should hold for all representative populations, regardless of ethnicity or nationality.
4. That's an entirely unwarranted assumption (in addition to 3). Are Asian-Americans in particular really representative of a general Asian population (with an American culture)? What about brain drain? The more recent the immigration, the harder it's to get in; simplifying for the sake of an example, if you only allow those with a X234 mutation in a B5 DNA location, don't be surprised when there's zero variability in a B5 location.
Even without a filter, why should the standard deviation in math skills be identical between genetically different populations? The identical variability should be true for the X-chromosome in general, not math-skills in particular.
https://docs.google.com/file/d/0B7DMQCP3v6SZQUw1MnNWbXBUV3M/