Är kvinnor sämre på matematik?

"... under de senaste fem åren gjorts mycket forskning på området. Bilden är splittrad. Somliga forskare har funnit att män har större varians oavsett vilket land eller vilken kultur man undersöker. Det skulle i så fall kunna tolkas som ett stöd för Pär Ströms påstående: den större manliga variansen är biologiskt, snarare än kulturellt, betingad. Andra forskare har dock funnit motsatta resultat: det eventuella överskottet av högpresterande män beror på tid och plats, vilket motsäger att det skulle handla om biologiska skillnader. I synnerhet verkar det som om överskottet av mycket matematiskt begåvade pojkar minskar eller rent av försvinner i samhällen som kännetecknas av hög jämlikhet mellan könen.

Tanken att män uppvisar större variabilitet (i både positiv och negativ mening) är fascinerande och tycks ha funnits under lång tid. Men att detta skulle vara ett entydigt biologiskt faktum, vilket Pär Ström påstår, är inte allmänt accepterat bland forskarna. Angående idén om mäns överlägsna matematiska förmåga i toppen av intelligensfördelningen finns det en intressant studie som visar hur lätt kvinnors och mäns testresultat kan manipuleras att anpassa sig till samhällets förväntningar. I studien lät man kvinnor och män lösa ett matematiskt problem rörande s k spatial rotation – vanligtvis sinnebilden för manlig överprestation. Det visade sig att om man före testet påpekade för försökspersonerna att det inte finns några genusskillnader så blev testresultatet i stort sett detsamma för kvinnorna som för männen. Detta antyder att även de mest vedertagna könsskillnaderna kan vara socialt konstruerade."

"Recent evidence for hypothesis are mixed and inconsistent and some researchers conclude, that even if males are more variable, the difference is too small to explain alone the lack of women in STEM fields.[3]
...

"Modern studies

The results seem to vary based on the type of problem, but some recent studies have found that the variability hypothesis is true for parts of IQ tests, with more men falling at the extremes of the spectrum. In contrast, one meta-analysis found that males were slightly better at progressive matrices, while women actually had more variability. In general different studies show different results. For example, males are more variable in mathematical and spatial abilities in some of Western societies, but in some other, the women are more variable. Recent studies also suggest, that greater male variability decreased in time and disappears at countries with more gender equal cultures."

Apropå den spatiala förmågan finns ett intressant stycke i https://www.apa.org/pubs/journals/releases/amp-67-2-130.pdf:

"Sex differences favoring males in mental rotation, which is the ability to imagine what an object would look like if it were rotated, can be found in infants as young as three months of age (Quinn & Liben, 2008). Although this very early difference suggests a strong biological basis for the large sex differences in mental rotation, there is also strong evidence for a large sociocultural/learning contribution. For example, when female and male college students were trained with computer games that required use of spatial visualization, this intervention reduced the gap between male and female performance, though it was not completely eliminated (Feng, Spence, & Pratt, 2007). Likewise, when male and female college students were primed with positive stereotypes (“I’m a student from a selective college”) before taking an object rotation task, the gender gap in performance was nearly eliminated. When gender was primed before the test, the gender gap widened (Mc- Glone & Aronson, 2006)."

"..."Gender Brain Myth #3: Men are naturally better at math"

But perhaps the most damning myth, which has even been espoused by a former president of Harvard, is that men are innately better at math and women are naturally better at verbal tasks. The logic is that gendered differences in math and verbal scores on standardized tests must result from intrinsic, biological differences in the brains of women and men. According to Parvizi, this logic is flawed: “Differences seen in cognitive tests do not necessarily provide direct evidence that those differences are in fact innate.”

If not inherent abilities, what can explain the differences in test scores? Evidence shows that test scores are not immune to social factors. Extensive empirical research on stereotype threat has demonstrated that if a person is exposed to a negative stereotype about a group to which they belong (e.g. women, Asians, African-Americans), they will then perform worse on tasks related to the stereotype. A striking example comes from a study on Asian-American women. When reminded of being Asian (which invokes stereotypes of high math ability) they scored higher than the control group (which was not reminded of their race or gender) on a math test. However, when Asian-American women were reminded of being female (which invokes stereotypes of poor math performance), they scored lower on the math test than the control group.

In this manner, social factors can greatly influence test performance. “Consequently, we are not in a position to draw any conclusions regarding sex differences in the brain and their relationship to differential cognitive abilities,” concluded Parvizi, “as we have yet to establish beyond a reasonable doubt that there are indeed real differences in ability.”"

A third observation from Figure 3—indeed, the one that is most visually striking—is that the AMC curve turns sharply downward at very high scores that striking—is that the AMC curve turns sharply downward at very high scores that represent the percentiles above those that the SAT can measure. The percent represent the percentiles above those that the SAT can measure. The percent female falls to 14 percent for students in the 99 female falls to 14 percent for students in the 99 th th percentile of the U.S. AMC 12 percentile of the U.S. AMC 12 population (1,112 students with scores of 114 or higher) and 10 percent (a 9 to 1 population (1,112 students with scores of 114 or higher) and 10 percent (a 9 to 1 male–female ratio) in the 99.9 male–female ratio) in the 99.9 th th percentile (a population of 206 students with percentile (a population of 206 students with scores of 130.5 or higher). The top 46 scorers were all male. At these extreme score ranges, it becomes increasingly implausible that gender-related selection into score ranges, it becomes increasingly implausible that gender-related selection into taking the AMC could account for much of the effect: why would girls capable of taking the AMC could account for much of the effect: why would girls capable of scoring 130 or higher be only one-quarter as likely to take the test as boys who scoring 130 or higher be only one-quarter as likely to take the test as boys who would do this well? Indeed, the knowledge and problem-solving skills needed to get would do this well? Indeed, the knowledge and problem-solving skills needed to get a 130 are suffi ciently high so that we feel that almost all students (male or female) a 130 are suffi ciently high so that we feel that almost all students (male or female) who have acquired such skills are probably taking the AMC 12, making gender- who have acquired such skills are probably taking the AMC 12, making gender- related selection nonexistent (for measurements of what the gender composition related selection nonexistent (for measurements of what the gender composition of high scorers would be under universal administration). of high scorers would be under universal administration