In Chapter 6, professor Lubinski and Benbow state their own opinions about why fewer women are in the science field. They use a lot of graphs to explain three main points: sex difference in cognitive ability, in interests and in willingness to work long hours. However, all the sex differences they talked about are truly caused by gender schema which they didn’t mention in their passage and the statistics in the passage cannot show the differences they talked about.

The authors use the IQ Score Band to illustrate that men’s scores have higher variability, thus causing more men at the top. However, if there are more men have higher IQ, then no matter in which field, more men than women are at the top. But in some field such as nursing and education, there are more brilliant women than men (Chapter 2). Also, the Mental Survey itself needs to be questioned, just as the SAT-M test (Chapter 4). As mentioned in Chapter 4, men and women may not have cognitive difference, but they show different aptitude for mathematics, which means women are good at solving some kinds of problems in math while men are good at others. So if the Survey is not good enough to eliminate the difference in aptitude, men and women may show difference in this test. So we cannot conclude from the IQ Score Band that men are more talented in science.

In order to illustrate that there are more men in science field, the professors show that people who are more gifted in science are more likely to study in science. This statement is based on the previous conclusion that men are more talented in science, which has been proved deficient, so the statement is not proper. The true reason that leads to more men in science is gender schema. From Chapter 1, girls who know their gender are more likely to perform badly than girls who do not recognize their gender. In Chapter 6, from the two graphs about the favorite high school and college courses, we can see that as the age increasing, the percentage of women in math and science is decreasing rapidly, which shows that girls are more affected by the gender schema when they realizing it as they grown up.

The authors state that women and men have sex difference in interests. In fact, women are not truly less interest but are influenced by gender schema. In Chapter 4, the knowledge of a person’s gender influences faculty members’ assessment of women. When judging women’s honors, people always think that women don’t pay as many efforts as men, and even think that women don’t do the work by themselves (Steinpreis, Anders and Ritzke, 1999). Because of this bias which means that they have to pay more efforts to overcome the accumulated disadvantages, fewer women choose to work in science and math. So the gender schema forces them to choose jobs outside of science, and this has no relation about interests. In Chapter 6, the study made by Webb, Lubinski, and Benbow (2002), which the authors use to prove the sex difference in interests, is a great example of my point.

The authors talk about the difference in willingness to work long hours and show that women are more willing to work less. This is, in fact, caused by the gender schema. As in Chapter 4, men and women may have equal desires for work, but they face unequal chances and difficulties of realizing both desires. This discourages them from choosing careers in math and science. In the picture 1 of Figure 6.5 in passage, we can see that the typical work hours for women are less than men, which definitely shows the gender schema in workplace. So the less willing to work long hours showed in picture 2 is truly caused by the gender schema in workplace but not the sex difference in willingness to work long.

Although the authors believe that sex difference causes an overrepresentation of males in STEM fields, I believe, the true reason is gender schema. We cannot conclude that there is no sex difference in science field, but before we talks about the sex differences which are innate, we should eliminate the outer reason—the gender schema.

Reference:

Why Aren’t More Women in Science? (Chapter 1 to Chapter 6) 

                                                by Stephen J. Ceci and Wendy M. Williams