Her work is critical of various pillars of gender science, and most definitely does not refrain from tackling the "Greater Male Variability" hypothesis that gets so much mileage these days. One such excerpt:
> In a Science study of over 7 million United States schoolchildren, Janet Hyde and her team found that across grade levels and states, boys were modestly more variable than girls. Yet when they looked at the data from Minnesota state assessments of eleventh graders to see how many boys and girls scored above the 95th and 99th percentile (that is, scored better than 95 percent, or 99 percent, of their peers) an interesting pattern emerged. Among white children there were, respectively, about one-and-a-half and two boys for every girl. But among Asian American kids, the pattern was different. At the 95th percentile boys’ advantage was less, and at the 99th percentile there were more girls than boys.[15] Start to look in other countries and you find further evidence that sex differences in variability are, well, variable. Luigi Guiso’s cross-cultural Science study also found that, like the gender gap in mean scores, the ratio of males to females at the high end of performance is something that changes from country to country. While in the majority of the forty countries studied there were indeed more boys than girls at the 95th and 99th percentiles, in “in some countries females are equally or more variable, or are as likely as boys to make it into the 95th percentile.“
> (Penner 2008; Machin & Pekkarinen 2008). These latter authors stress the strong pattern of greater male variability, but the boy/girl ratio (shown in parentheses) at the top 5 percent of maths ability was more-or-less equal in Indonesia (0.91), Thailand (0.92), Iceland (1.04) and the UK (1.08). Penner found greater female variability in the Netherlands, Germany and Lithuania. For useful discussion of these data, see (Hyde & Mertz, 2009)."
This analysis ignores both the (1) base rate, and (2) practice effect. The problem with using gender-neutral percentiles is that the proportion of males and females may not be 1:1. So, even if the percentage of women in the 99th percentile is higher than that of men, men could actually be more likely to be in the 99th percentile than women.
That is, they found p(women | 99th) / p(men | 99th) whereas they're claiming they found p(99th | women) / p(99th | men).
Regarding the second, it could be that the women were studying more, and thus not represent a genetic trait. In order to settle whether differences are genetic, you would have to compare performance from the same amount of effort.
I'm interested to see how the research continues in the future. It seems there is a lot of taboo around the subject, and I hope that doesn't dissuade scientific debate.
> Regarding the second, it could be that the women were studying more, and thus not represent a genetic trait. In order to settle whether differences are genetic, you would have to compare performance from the same amount of effort.
I think this is an important objection, but you stop far shy of its true implication. If just studying more would skew the results, then you cannot reasonably say that the method used has any significant power to detect the influence genetic traits.
What is tested in a standardised test is arguably the combined effect of societal environment and genes, and considering that the field of the interaction between gene expression and the host environment (Epigenetics) is only just starting, even the genetic component might not be some static contribution.
> In a Science study of over 7 million United States schoolchildren, Janet Hyde and her team found that across grade levels and states, boys were modestly more variable than girls. Yet when they looked at the data from Minnesota state assessments of eleventh graders to see how many boys and girls scored above the 95th and 99th percentile (that is, scored better than 95 percent, or 99 percent, of their peers) an interesting pattern emerged. Among white children there were, respectively, about one-and-a-half and two boys for every girl. But among Asian American kids, the pattern was different. At the 95th percentile boys’ advantage was less, and at the 99th percentile there were more girls than boys.[15] Start to look in other countries and you find further evidence that sex differences in variability are, well, variable. Luigi Guiso’s cross-cultural Science study also found that, like the gender gap in mean scores, the ratio of males to females at the high end of performance is something that changes from country to country. While in the majority of the forty countries studied there were indeed more boys than girls at the 95th and 99th percentiles, in “in some countries females are equally or more variable, or are as likely as boys to make it into the 95th percentile.“
> (Penner 2008; Machin & Pekkarinen 2008). These latter authors stress the strong pattern of greater male variability, but the boy/girl ratio (shown in parentheses) at the top 5 percent of maths ability was more-or-less equal in Indonesia (0.91), Thailand (0.92), Iceland (1.04) and the UK (1.08). Penner found greater female variability in the Netherlands, Germany and Lithuania. For useful discussion of these data, see (Hyde & Mertz, 2009)."