Will sex differences never end? Sometimes they seem to go one way, sometimes the other, with the gaps closing or staying resolutely the same, but this is the March of Science, as different schools contend, and as new results are added to the old. We should be glad that researchers delve into these matters, particularly in times when sex differences are considered somehow dangerous, and apt to cause offence, public disorder, and a rending of the very fabric of society, as when a diaphanous blouse is torn from a lady’s breast by a brutish leering lout. I digress. I may not have got the hang of current sensibilities.
Anyway, back to “tilt”. I find this a relatively new concept, but perhaps it is more succinct than the former description “verbal-performance discrepancy”. Which way do the fair sex incline: to matters verbal or mathematical? Verbal, it would seem, and all the more so as you go up the ability spectrum.
Sex differences in ability tilt in the right tail of cognitive abilities: A 35-year examination Jonathan Wai, Jaret Hodges, Matthew C. Makel. https://doi.org/10.1016/j.intell.2018.02.003 Intelligence, Volume 67, March–April 2018, Pages 76–83
The authors highlight the following findings:
Sex differences in math-verbal ability tilt in the right tail were examined across 35 years.
Sample included >2 million gifted adolescents across multiple measures in the U.S. and India.
Ability tilt favored males for math > verbal and females for verbal > math.
Sex differences in ability tilt remained fairly stable over time and replicated across measures.
Trends should be monitored given their potential to impact future workforce trends.
Sex differences in cognitive ability level and cognitive ability pattern or tilt (e.g., math > verbal) have been linked to educational and occupational outcomes in STEM and other fields. The present study examines cognitive ability tilt across the last 35 years in 2,053,265 academically talented students in the U.S. (SAT, ACT, EXPLORE) and 7119 students in India (ASSET) who were in the top 5% of cognitive ability, populations that largely feed high level STEM and other occupations. Across all measures and samples, sex differences in ability tilt were uncovered, favoring males for math > verbal and favoring females for verbal > math. As ability tilt increased, sex differences in ability tilt appeared to increase. Additionally, sex differences in tilt increased as ability selectivity increased. Broadly, sex differences in ability tilt remained fairly stable over time, were consistent across most measures, and replicated across the U.S. and India. Such trends should be carefully monitored given their potential to impact future workforce trends.
Before going further, I should digress to sing the praises of Gerd Gigerenzer. Whereas Kahneman and Tversky concentrated on puzzles which many have found contrived, Gigerenzer concentrated on actual, everyday problems with interpreting statistics. Here is an example. We can all guess those people in the top 1% of intelligence are 1 in 100 intellects, but what does 0.01% mean? It “feels like” 1 in a 1000, but is in fact 1 in 10,000. As Gigerenzer says, don’t mix decimals with percentages. They are different tribes. Confusing. Instead, use natural frequencies. In a town of 10,000 people there will be 100 people who are in the top 1% of the population, but only one person who is 1 in 10,000. That is the level that Benbow and Lubinski studied. Eminent minds, Galton called them.
So, skipping a thousand words, here is the pictorial summary, which shows that sex differences increase as ability tilt increases:
To my eye, starting from the bottom for all students, these violin plots show the following: women are almost perfectly balanced between verbal and mathematical ability, but men incline towards being better at maths than at verbal tasks. Men are more likely to calculate. This relatively slight difference might be the source of contrary imaginations, and some exasperated arguments.
At the higher intellectual level of the top 1 in a 100 of the population both men and women incline more to mathematical thinking, but men predominate more.
At the eminent level of the top 1 in 10,000 of the population, men outnumber women by about 2.5.
The authors caution:
It should be noted it is likely that the magnitude of the selectivity level moderator (top 5%, top 1%, top 0.01%) is underestimated. In the analysis, the ratio of male to females was skewed toward males. This skew increased as selectivity increased. This unbalanced design can lead to the true effect being greater than what is reported. In other words, it is possible that the magnitude of tilt is greater than what is reported.
Of course, the top mathematicians will be even brighter, say 1 in 1,000,000. They will be mostly men.
The paper is rightly restrained in its conclusions, but this stable result is a causal component in the observed sex differences in STEM studies and subsequent occupations. Sex differences in preferences for occupations are mentioned, but are not part of this study. India, which is far less favourable to women’s careers, shows the same trend. Probably, men take to maths more than do women, and at the brightest levels that general trend is accentuated. The current study may under-estimate the male advantage.