Gender and Race

Hysteria Trumps Academic Freedom
 by Doreen Kimura

Larry Summers was the president of Harvard University, who resigned soon after he gave a talk partly concerned with the representation of women in the sciences.  He was severely criticized for suggesting that the under representation of women may be due to innate differences in intellectual talents.  This would appear to be an empirical claim, but many feminists regarded it as an unconscionable  expression of sexism.

Doreen Kimura is a leading researcher in the area of cognitive sex difference, and she dismisses the feminist reaction as unscientific. and embarrassing to serious women scientists.

Men and women do differ in their intellectual talents, and if by "innate" we mean influenced or determined before birth, then some of these differences are indeed innate. Differentiation between the sexes depends heavily on the difference between them in levels of sex hormones early in prenatal life. These hormone levels determine not only the physical differences, but also strongly influence many behaviours into  adulthood. Those behaviours include the intellectual or cognitive pattern, hormonal influences being especially well documented for certain  kinds of spatial ability, like being able to mentally rotate or manipulate visual objects.

Men are, on average, better on such spatial tasks and on mathematical reasoning tasks than are women. Women, in contrast are better, on average, on tasks requiring verbal memory (recalling word material), and also in recalling the position of objects presented in an array. There are many other less striking differences. 
       
Mathematical reasoning ability is especially important for physical sciences like physics and engineering, and since many more men than women score at the high end of math aptitude tests, it is reasonable to expect that more men will go into those professions. Note that boys and girls may not differ in their grades on math tests in school, but the same boys still excel on math aptitude tests, where the items are less rehearsed.

Kimura is careful to point out that these are statistical generalizations, and that individuals vary remarkably.  So admitting these differences in no way supports discriminatory social policy.  It only means that we should not be surprised, nor necessarily concerned that women and men are not found in equal numbers in the various scientific professions.

 Women, Science and Gender
 by Cathy Young

Cathy Young is similarly critical of a recent report from the National Academies, ``Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering," which concludes that differential representation is not due to innate differences, but rather to gender bias and sexism.  
Part of the report’s evidence for sexist bias is that “single women scientists and engineers [were] 16 percent more likely than single men to be in tenure track jobs five years after the PhD, while married women with children were 45 percent less likely than married men with children to be in tenure track positions."
This is actually pretty interesting, but Young thinks it isn’t clear that this reflects anything more than the preferences of women in marital relationships.

Under-representation or Misrepresentation?
by Doreen Kimura

In this article, Kimura gives us a more refined look at the biological basis of the cognitive sex differences noted earlier.  Specifically:

1)   Prenatal androgen levels are almost certainly a major factor in the level of adult spatial ability. 
2)  Cogntive sex differences present very early in life, before major differences in life experience 
3)  Cognitive sex differences present across cultures that vary in social pressures to conform to a gender norm. 
4)  Cogntive sex differences are apparently uninfluenced by systematic training in adulthood. While both sexes benefit by short-term intensive training on spatial tasks, men’s and women’s scores do not converge (Baenninger & Newcombe, 1989). 
5) Cognitive sex differences are reflected in other species. For example, male rats are superior to female rats in learning spatial mazes, and these sex differences can be reversed by hormonal manipulation in early postnatal life (Williams & Meck, 1993).
Kimura is critical of the social scientist tendency to prefer environmental explanations above all.  For example: 
There have been studies showing that adults who engage in spatially demanding activities also generally engaged in such activities in childhood, that is, that the two are related (Newcombe, Bandura & Taylor, 1983). The usual, and problematic, interpretation by most social scientists is that the childhood experience determined the adult pattern.         
Kimura points out that this explanation has no greater empirical plausibility that the view that the aptitudes are what cause the activities.  Furthermore, she notes:
The participants selected for Benbow’s (1988) studies of mathematically precocious youth (SMPY) have consistently shown a greater number of males. Even within this select group of boys and girls the average scores of boys are higher. The ratio of boys to girls at the high end of the distribution of scores is about ten to one. In the Putnam competition, open to all undergraduates in North America, what data we have suggests a huge preponderance of males who get the higher scores, even correcting for the larger numbers of male applicants. 
Kimura also thinks that institutional discrimination is a very weak explanation of the differential representation in technical fields:
In mathematical, physical and computer sciences, men overwhelmingly receive the bulk of doctorates, with women ranging from 20-23%. In engineering, the picture is even more uneven, with women receiving barely 15% of doctorates. However, in biological sciences, women received 43.5% of the doctorates in the most recent numbers available (Statistics Canada, 2001). Data from the United States are remarkably similar—in recent years women earned 46% of the doctorates in biological sciences, but only 18% of those in physics (National Science Foundation, n.d.).
Her point is that biology is also a traditionally male-dominated discipline, yet there are more than twice as many women going into biology as physics or engineering.
As in the previous article, Kimura concludes that while it is likely that there are innate differences between men and women regarding mathematical aptitude, there is too much overlap to let this fact influence policy:
We are, however, speaking of average differences, and given the substantial overlap between men and women on all cognitive functions, using sex to determine quotas of admission to any program would be mistaken. There will be women who make outstanding engineers, as there are men who will make outstanding nurses. Not discriminating on the basis of sex is a double-edged sword, however, and requires that we accept the probability of differential representation of the sexes over a wide variety of activities. 

Do you think this is a good argument?  

Sex Differences in Math and Science
 by Elizabeth Spelke

Elizabeth Spelke is a Harvard psychologist who was one of the most outspoken critics of Larry Summers.  She believes that the research supports the view that men and women have equal talents for mathematics and science.

In this paper she examines three theories that would account for differential adult aptitudes in terms of innate cognitive abilities.

1.  Males and females are predisposed from birth to learn about different things.

Parents of boys and girls will often note that the boys are more mechanically inclined from an early age, whereas the girls are more interested in people.  This view received support from a study by Conellan (2000), who recorded the length of time that male and female infants would spend gazing at an inanimate vs. an animate object.   Males were a great deal more likely to pay visual attention to an inanimate object than females.

Spelke is critical of this on methodological grounds.  She notes that Conellan’s results have not been replicated, and that other causal factors were not ruled out, such as color, movement, etc.  She also notes that it is highly problematic to extrapolate such differences to adulthood.  Other studies have found that girls develop mechanical aptitudes more quickly than boys (e.g., female infants understand more quickly than males that an object travels farther when hit by a larger object.)  But this doesn’t mean than female adults have a better intuitive grasp of physics.

2.  Better command of specific cognitive systems is genetically determined.

Spelke here argues that the reported observed differences in male and female aptitudes are highly oversimplified.  She says that it is common to report (as Kimura does0 that women excel in verbal tasks and men excel at spatial ones.  However, the truth is quite a bit more complicated.  She says:

Girls and women tend to excel on tests of verbal fluency, arithmetic calculation, and memory for the spatial location of object.  Boys and men tend to excel on tests of verbal analogies, mathematical word problems, and memory for the geometric configuration of an environment.  She emphasizes as well that the meta-analyses show that the differences, while real, are very small.

Spelke does not deny that there are innate cognitive sex differences, but she emphasizes that the differences are best understood as differences in problem-solving strategies.  These strategies produce differential results depending on the kind of data set the subjects are using.  The selection of data sets that favor male cognitive strategies is what Spelke believes accounts for the differential results on SAT math aptitude tests.  (She notes that in the history of the SAT, classes of questions have been eliminated when girls have done better than boys.)

In support of the discrimination thesis, she notes that the gender gap has closed in high school calculus classes, that girls get better grades, and that the SAT-M consistently underpredicts that performance.  (In other words, she holds that the results of the SAT-M do not make sense in light of girls performance in high school.)

3.  Males show greater variability in mathematical talent, so that there are more males that are very highly adept at math than females.

Spelke argues again that this belief is also the result of poor sampling procedures.