In yesterday’s post, we discussed sex differences in achievement and ability. Few were identified. For the most part, however, this research discussed average differences. The problem with only discussing averages is that people engaged in science and math careers are far from “average” when it comes to math and science ability. Math and science professors often score in the top 1 percent — or higher — on standardized math tests.
It’s entirely possible that the top 1 percent looks very different from the average results for the population. Consider this graph of test scores from two different groups:
The vertical axis of the graph is the number of people achieving each score on the test. Even though Group 1 has a higher average score than Group 2, there are still more members of Group 2 at the top of the scale (and at the bottom). Group 2′s scores are more spread out, more variable than scores of Group 1, which means that when we focus in at the top of the scale, we find more members of Group 2, even though overall Group 1 performed better on the test.
So, is that what we find when we look at real populations? Are males like Group 2, and females like Group 1, when it comes to mathematical ability?
The Study of Mathematically Precocious Youth observed thousands academically gifted American children who took the SAT test at age 12-14, several years before the usual administration in the 11th grade. In 1983, among those who scored higher than 700 on the test, males outnumbered females by 13:1. This indeed suggests that males have a much wider distribution of scores than females at that age. Interestingly, by 2005, the ratio at that same level had dropped to 2.8:1. Either girls have gotten a lot smarter in the last 20 years, or some of the discrepancy in 1983 can be explained by social differences: different opportunities for boys and girls.
Yet there is still a large, significant sex difference in math scores at the top of the scale (there’s no difference in verbal scores). Where does this difference come from? Some evidence suggests that the brightest boys even have an advantage at kindergarten age. Some scholars have speculated that sex roles in humans evolved millions of years ago: while men were out hunting and fighting with neighboring tribes, women stayed closer to home, foraging and caring for children. Since men travelled farther than women, they required better navigation skills — similar to the visuospatial skills we discussed yesterday. The men who survived were better at navigation, and they passed this trait on to their male children. But others have argued that women needed to travel just as far in foraging. It’s certainly possible that differences in ability can be entirely explained by factors unrelated to evolution.
Sex differences in higher education
We’ve established that in the tiny slice of students with the highest math test scores, there are many more males than females. But how are these boys and girls doing when they grow up and go to college and beyond? While the overall graduation rate from college favors women, in math and science, the numbers tell a different story. The male to female ratio of science majors at MIT in the 1990s was about 1.5 to 1. Among faculty it was higher than 10 to 1. Part of the discrepancy might be due to different social conditions when MIT’s faculty was educated. Take a look at this graph:
As you can see, in every field, a larger portion of doctorates was awarded to women in 2001 than in 1980. But women still earn many fewer doctorates than men in physical science and engineering. How can we explain this lingering discrepancy?
Part of it may come down to the relationship between verbal and mathematical skills. The study of precocious youth mentioned earlier actually tracked these children until they became adults. If you take a look at their career choices at age 33, you find that the relationship between verbal and math scores in this group — all scoring in the top 1 percent — explained a lot about what fields they went into. Take a look at this graph, which relates career choices to SAT scores:
The blue line represents the point where math and verbal scores were equal. Above that line, verbal scores are better than math scores; below it, vice-versa. As you can see, people choosing the fields most dominated by men, math/computer science and engineering, tended to score much lower on the verbal SAT compared to the math SAT when they took those tests years before. And boys are much more likely than girls to score lower on verbal than math — for girls, the scores tend to be equal.
But one theme Halpern and her colleagues constantly return in their article is that the issue of women’s achievement in math and science is extremely complex. To suggest that the relationship between verbal and math test scores explains all sex differences would be vastly oversimplifying things. We’ll cover more on this important topic in tomorrow’s post.
Halpern, D.F., Benbow, C.P., Geary, D.C., Gur, R.C., Hyde, J.S., & Gernsbacher, M.A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest, 8(1), 1-51.