G ender differences in mathematics participation rate, mean and high-end performance, and variance in distribution of performance have been reported on numerous occasions. The reasons for these findings have been the subject of much debate. For example, the greater male variability hypothesis, originally proposed by Ellis in 1894 [42] and reiterated in 2005 by Lawrence Summers when he was president of Harvard University [48], states that variability in intellectual abilities is intrinsically greater among males. If true, it could account for the fact that all Fields medalists have been male. If gender differences in means and variances are primarily a consequence of innate, biologically determined differences between the sexes, one would expect these differences to be similar among countries regardless of their culture and to remain fairly constant across time. Such a finding would suggest that little can be done to diminish these differences. In support of this hypothesis, Machin and Pekkarinen [26] claimed that greater male variance in mathematics performance was a “robust phenomenon”, that is, observed among fifteen-year-olds in thirty-five out of the forty countries that participated in the 2003 Programme for International Student Assessment (PISA). In addition, women’s nature might include a tendency to prefer the more nurturing fields, such as nursing and teaching young children, to the more quantitative ones, such as mathematics, physics, and engineering. If so, it might not make sense to encourage and direct any but the unusual female toward studying and seeking employment in these latter fields. This viewpoint has led some folks to propose that it may be a waste of time and money to expend resources directed toward trying to increase participation of women in these mathematics-intensive fields (e.g., [5], [6], [46], [49], [50]). Alternatively, boys and girls may be born similar in their innate intellectual potential but end up displaying differences due to a variety of sociocultural factors present in their environment, for example, gender-stratification ([2]). If true, one might see differences among countries and changes over time in mathematics variances and mean performances. This gender-stratified hypothesis is consistent with several recent findings. For example, Hyde and collaborators ([20], [25]) reported that girls have now reached parity with boys in mean mathematics performance in the United States, even in high school, where a significant gap in mean performance existed in the 1970s. Likewise, both Brody and Mills ([3]) and Wai et al. ([51]) noted a drop in nonrandom samples of students under thirteen years of age, from 13:1 in the 1970s down to approximately 3:1 by the 1990s in the ratio of U.S. boys to girls scoring above 700 on the quantitative section of the college-entrance SAT examination. The percentage of Ph.D.’s in the mathematical sciences awarded to U.S. citizens who are women has increased from 6 percent in the 1960s to 30 percent in the past decade ([4], [9]). Sociocultural, legal, and educational changes that took place during this time span may account for these dramatic improvements in mathematics performance and participation by U.S. females. Gender differences in opportunities and outcomes within countries have been quantified by a variety of measures. The Gender Gap Index (GGI) is a composite, weighted measure of the gap Jonathan M. Kane is professor of mathematics and computer science at the University of Wisconsin-Whitewater. His email address is kanej@uww.edu.
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