Introduction to Intelligence

How do we talk, or not talk, about intelligence?

In January 2005, the President of Harvard University, Lawrence H. Summers, sparked an uproar during a presentation at an economic conference on women and minorities in the science and engineering workforce. During his talk, Summers proposed three reasons why there are so few women with careers in math, physics, chemistry, and biology. One explanation was that it might be due to discrimination against women in these fields, and a second was that it might be a result of women’s preference for raising families rather than for competing in academia. However, Summers also argued that women might be less genetically capable of performing science and mathematics — that they may have less “intrinsic aptitude” than men do.

Summers’s comments on genetics set off a flurry of responses. One of the conference participants, a biologist at the Massachusetts Institute of Technology, walked out on the talk, and other participants said that they were deeply offended. Summers replied that he was only putting forward hypotheses based on the scholarly work assembled for the conference and that research has shown that genetics have been found to be very important in many domains compared with environmental factors. As an example, he mentioned autism, which was once believed to be a result of parenting but is now known to be primarily genetic in origin.

The controversy did not stop with the conference. Many Harvard faculty members were horrified that a prominent person could even consider the possibility that mathematical skills were determined by genetics, and the controversy and protests that followed the speech led to a first-ever faculty vote for a motion expressing a lack of confidence in a Harvard president. Summers resigned his position, in large part as a result of the controversy, in 2006 (Goldin, Goldin, & Foulkes, 2005).

Researchers at the University of Western Ontario in Canada (Vingilis-Jaremko & Vingilis, 2006), while conducting a meta-analysis of three decades of research on gender differences in performance and participation within the science, technology, engineering, and math (STEM) areas, stated: “clearly, gender stereotypic messages and priming can have negative effects. Unfortunately, gender stereotypic messages are widespread in the 21st century. Much work has yet to be done” (p. 6).

Yet, the 2010 Pan-Canadian Assessment Program (PCAP) from the Council of Ministers of Education in Canada shows that in studying 32,000 Grade 8 students from across Canada, female Grade 8 students outperformed their male counterparts on reading and science, with no significant difference between the two genders in math skills. Researchers believe that the cultural shift to making math and science more gender-neutral may be an influencing factor. Girls scored better than boys in both science and reading. Researchers hypothesised that boys appear to believe that reading and writing is a feminine act and are therefore reluctant to engage fully in these subject areas. Stereotype threat (the lowering of performance on tasks when reminded of the participant’s race, gender or age or the reduction in performance of individuals who belong to negatively stereotyped groups) seems to apply to both genders (Council of Ministers of Education Canada, 2011). In discussing intelligence in the rest of this chapter, we should keep in mind these issues as they have a direct impact on how we interpret the data.