Frauen in der Wissenschaft und die biologischen Faktoren

Ein interessanter Aufsatz behandelt Unterschiede in der Wissenschaft zwischen Männern und Frauen und die dabei zugrunde liegenden biologischen Faktoren (via):

Beispielsweise spielen eben verschiedene Ausprägungen von Fähigkeiten im Schnitt eine Rolle:

Dabei wird dargestellt, dass Männer gerade im Bereich räumliches Denken besser abschneiden und dies eine gerade in vielen Naturwissenschaften ein Vorteil ist

A variety of differences between the sexes in cognitive and temperamental traits almost certainly affect occupational distributions.17 Scientific fields like physics, mathematics, and engineering require very high levels of both mathematical and spatial ability, and males predominate at the highest levels of both. For example, among perfect scorers on the mathematics portion of the SAT, the ratio of males to females is about three to one.18 Even that statistic is misleading, however, as the “ceiling effect” of the SAT is substantial. That is, there are relatively large numbers of test-takers who receive perfect scores (around 5,000 per year), so the SAT fails to discriminate well at the very high end. When the SAT is given to seventh-graders, however, the ceiling effect is less pronounced, so that the sex ratio among those who score over 760 is approximately seven boys for each girl.19 Although spatial ability is not typically screened for in admission to science programs, it is an important predictor of success in scientific fields.20 Males outperform females on most spatial tasks, with three-dimensional mental rotation showing the largest and most reliable sex difference.21 A review of mental-rotation studies found that the male mean exceeded the female mean by approximately twothirds of a standard deviation, and in many studies, it approached or exceeded a full standard deviation.22 Because males tend to be more variable than females on most traits, even if males and females scored the same on average, there would be more males at the extreme high end (and at the low end, as well). A higher male mean combined with greater male variability means that the sex ratio at the extreme high end of the distribution is especially skewed. There is sometimes a tendency to view the gifted as a relatively homogeneous group, but they are actually highly diverse in ability. For example, in a typical IQ test with a mean of 100 and a standard deviation of 15, the ability range of the top 1%—the extreme right tail of the distribution—is as broad as the range from the bottom 2% to the top 2%. The middle 96% of the range runs from about 66 to 134, while the top 1% ranges from about 135 to over 200.23 Males especially outnumber females in the top quarter of the top 1% of mathematical ability. Although one might suppose that there is a point of diminishing returns beyond which additional ability has no payoff, that does not appear to be the case in science. For example, Camilla Benbow and David Lubinski have found significant differences between those individuals in the top and bottom quarters of the top 1% on measures such as earning a degree in science, level of college attended, grade-point average, and intensity of involvement in math and science.24 Indeed, individuals in the top quarter of the top 1% are four times as likely as individuals in the bottom quarter of the top 1% to earn math-science Ph.Ds.25 Thus, it is simply erroneous to assert, as 79 signatories to a letter to Science magazine did, that “there is little evidence that those scoring at the very top of the range in standardized tests are likely to have more successful careers in the sciences.”26 On the contrary, as Wai, Lubinski and Benbow put it, these data “falsify the idea that after a certain point more ability does not matter” and show that “[m]ore ability always seems to matter.”27

Dagegen haben anscheinend Frauen im sprachlichen Bereich Vorteile, wobei sich hier eine höhere Variabilität der Männer auswirkt:

In contrast to the better performance of males on tests of mathematical and spatial ability, females tend to outperform males on a number of measures of verbal ability, including spelling, grammar, and verbal memory. In fact, in broad samples, the female advantage in verbal abilities exceeds the male advantage in mathematical ability. In 1996, for example, male eleventh-graders scored at about the same level as female eighth-graders on the National Assessment of Educational Progress (NAEP).28 In more select samples, however, the female verbal advantage often declines or disappears, because of greater male variability. Males consistently outscore females on the verbal portion of the SAT, for example, though by only a small margin.29 On the other hand, on the ACT, which tends to focus on curriculum-based knowledge rather than on the verbal reasoning emphasized by the SAT, girls outperform boys.30 The lower male mean for verbal ability, coupled with greater male variability, translates into a substantial disproportion of males at the very lowest levels of verbal ability.

Auch anderer Motivationen sind anders:

Apart from cognitive differences, the sexes also differ in temperament and personality. On most measures of direct competitiveness, for example, males score higher than females.32 Competition tends to be a more positive experience for males, and adding a competitive element to a task increases the intrinsic motivation of males but does not do so for females.33 The perception that an academic program is competitive tends to result in improved performance by males but decreased performance by females.34 Relatedly, males also engage more than females in dominance behaviors—that is, behaviors intended to achieve or maintain a position of high relative status—in order to obtain power, influence, or resources.35 The sexes also vary in risk preference, with males exhibiting a greater preference for both physical and nonphysical risks. Indeed, sex is the variable most predictive of the extent of participation in high-risk recreation.36 Men are also disproportionately represented in physically risky employment, as reflected in the fact that over 90% of all workplace deaths in the U.S. are males.37 Commenting on their study of female executives, Margaret Hennig and Anne Jardim observed that “men see risk as loss or gain; winning or losing; danger or opportunity,” while “women see risk as entirely negative. It is loss, danger, injury, ruin, hurt.”38 Females also tend to exhibit more nurturing behavior than males, both inside and outside the family. The greater female interest in infants—present from childhood39—increases at puberty.40 The more social orientation of females is reflected in a consistently found sex difference in “object versus person” orientation, with females tending to be more “person-oriented” and males tending to be more “object-oriented.”

Also verschiedene Motivationen, insbesondere was Konkurrenz, Risikobereitschaft und Versorgen angeht.

Das wirkt sich dann auch bei der Arbeitsstelle aus:

Sex differences are consistently found on measures of occupational interest such as the Strong Interest Inventory and the Self-Directed Search, which measure occupationally relevant aspects of personality. Men tend to score higher on the “Realistic” (enjoying building and outdoor work and working with “things”) and “Investigative” dimensions (interested in abstract problems and understanding the physical world), and women score higher on the “Artistic” (enjoying creating or experiencing art, music, and writing) and “Social” dimensions (enjoy interacting with people, helping, and instructing).42 35

Klassische Unterschiede also