Charles Murray

ches, so d equals –5.4 ÷ 2.9, which works out to an effect size of –1.86. This is an extremely large effect size. Most sex differences are much smaller and the distributions have much more overlap.
Note that the sign of d (negative

I also disagree with Hyde’s position that Type I errors should still be more feared than Type II errors.

We continue to learn more about the two groups. We learn that one group is more prudent, the other more happy-go-lucky; one group is more practical, the other more imaginative; and so on. In some cases, the additional traits on which the groups differ are so closely related that the new knowledge adds only a small amount to the difference; in other cases, the new information adds a lot to the degree of their difference

In assessing the various arguments for and against, three points need to be kept in mind.

Measuring personality sex differences in infancy is tough, and the instruments for doing so are not nearly as precise as instruments for older children.

The same article that reported the results for American adults on the Costa-McCrae inventory also reported them for 25 other countries.23 In 2005, McCrae and Antonio Terracciano used observer reports from 50 cultures, 22 of which had not been included in previous studies.

The largest of the negative effect sizes (i.e., higher for males) was trivially small (d = –0.05).25

Among the 70 nations with data on personality and a GII score, the five nations with the best (meaning lowest) scores on the GII were Switzerland, Denmark, the Netherlands, Sweden, and Iceland.

Kajonius published the results for a database with a more extensive (120-item) version of the FFM for 22 countries with uniformly larger sample sizes per country (at least 1,000) than the samples used by the other studies.

Or as the authors put it, “These findings imply that both economic development and gender equality exhibited an independent and significant association with gender differences in preferences.”