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Discussion
Our overall result was consistent with elements of the variability hypothesis: female students’ grades were less variable than those of male students, but in contrast to expectations,
the greatest difference in variability occurred in non-STEM subjects. Average female grades were also higher than males, corroborating the findings of Voyer and Voyer (Fig.
2). Gender differences in grade variability of school pupils was unaffected by their age, weakly affected by the year of study, and most strongly affected by whether or not the subject was STEM.
From grade one onward, we found that girls’ grades were less variable than those of boys. Across the last 80 years, the variability in school grades has slightly decreased for both boys and girls (albeit slightly faster for girls). This decline might reflect increased student performance, or greater reluctance to fail students, i.e. grade inflation. These scenarios assume that there is a ceiling effect on grades, whereby variance is reduced because weaker students are shifted upwards, whereas the highest performing students are bumped up against the ‘ceiling’ of the highest possible grade awarded on the grading scale. Although we do not see strong evidence for a ceiling effect in our dataset (Supplementary Fig.
5), below we discuss how the ceiling affect could underestimate the magnitude of gender differences in variability.
Contrary to our expectations (Fig.
1), and those of many others,
the gender difference in variability was smaller for STEM than non-STEM subjects (Fig.
2). When the small gender gap in grade variability is combined with the small gender difference in mean grades, it indicates that
in STEM subjects, the distributions of girls’ and boys’ grades are more similar than in non-STEM subjects (Fig.
3). One possible explanation is that boys’ are more affected by the ceiling affect in STEM than non-STEM. For example, if a grading scale cannot distinguish between students in the top 1% or top 0.1%, and if there exists a male skew in the top 0.1% only in STEM but non in non-STEM, then gender differences in variance would be underestimated in STEM. Wai et al.
22 tried to get around this ceiling effect by analysing seventh-grade test scores explicitly designed to differentiate between exceptional students. They found a female:male ratio of 0.25 in the top 1% of students in STEM subjects, which is more imbalanced than our data suggests (Fig.
3c). While this finding is intriguing, it should be noted that STEM careers are not restricted to the exceptionally talented (although fields that subscribe to the belief that talent is important for success tend to employ fewer women). Therefore, while our data does not preclude a gender gap among the exceptionally talented, it nevertheless indicates a practical similarity in girls’ and boys’ academic achievements, which are likely to provide an imperfect but valid measure of the ability to pursue STEM (Fig.
3).
Because students’ grades impact their academic self-concept and predict their future educational attainment (e.g. refs.
1,
5), we might therefore predict roughly equal participation of men and women in STEM careers. However,
the equivalence of girls’ and boys’ performance in STEM subjects in school does not translate into equivalent participation in STEM later in life. Is this because grades are not measuring the abilities required to succeed in STEM? Or does the relative advantage girls have over boys in non-STEM subjects at school lead them to rationally favour career choices with fewer competitors? We consider each of these questions in turn.
We analysed school grades, where girls show a well-established advantage over boys, whereas most previous tests of gender differences in variability have focussed on test scores
18,
19,
23. To explore whether the smaller variability difference in STEM compared to non-STEM is confined to school grades, we performed a supplementary analysis of a large international dataset of standardised test scores of 15-year-olds (see Supplementary Note
2 for details). This supplementary analysis found gender differences in variance that were consistent across subjects; girls’ test scores were more consistent than boys, with equivalent gender differences in non-STEM and STEM subjects (Supplementary Fig. 11). However, girls only showed a mean advantage in non-STEM. Therefore, it appears that the mean differences between test scores and grades are caused by shifts in the position of girls’ and boys’ distributions, rather than changes in the shape of distributions in STEM compared to non-STEM (girls’ distributions of both grades and test scores are narrower than boys’ distributions, but the difference is not more pronounced in STEM).
If girls perceive they have fewer competitors in non-STEM subjects because, on average, fewer boys perform better than girls, this might lead to a preference for non-STEM over STEM careers.
Gender differences in expectations of success can arise due to backlash effects against individuals who defy the stereotype of their gender, and/or due to gender differences in ‘abilities tilt’ (having comparatively high ability in one discipline compared to another). Women in male-dominated pursuits, including STEM, face a paradox: if they conform to gender stereotypes, they might be perceived as less competent, but if they defy gender stereotypes and perform ‘like a man’, then their progress can be halted by ‘backlash’ from both men and women
13,
41. Furthermore, analyses of test scores have revealed that girls are more likely than boys to show an abilities tilt in the direction favouring non-STEM subjects (i.e. receive higher scores in non-STEM compared to STEM). Our data are consistent with girls showing an ability tilt in the direction of non-STEM subjects, although we cannot compare individual student grades (Supplementary Table 11). Intriguingly, there is evidence that
balanced high-achieving students—who possess the potential to succeed in disparate fields—prefer non-STEM careers, and that girls are more likely to be balanced than boys, at least among high achievers. A female skew towards balanced abilities could be a manifestation of them showing lower levels of between-discipline variability (i.e. greater consistency across disciplines). Gender differences in between-discipline variability, rather than within-discipline variability, is an interesting avenue for future research.
A girl’s answer to the question of ‘what do you want to be when you grow up?’ will be shaped by her own beliefs about gender, and the collective beliefs of the society she is raised in. While our results support the variability hypotheses, we have shown that the magnitude of the gender gap in STEM grades is small, and only becomes male-skewed at the very top of the distribution (Fig.
3). Therefore, by the time a girl graduates, she is just as likely as a boy to have earned high enough grades to pursue a career in STEM. When she evaluates her options, however, the STEM path is trod by more male competitors than non-STEM, and presents additional internal and external threats due to her and societies’ gendered beliefs (stereotype threat and backlash effects). To increase recruitment of girls into STEM, this path should be made more attractive for them. A future study could estimate how male-skewed we would expect STEM careers to be based solely on gender differences in academic achievement, by quantifying the academic grades of current STEM employees. Our study focussed on gender differences in academic achievement, but understanding gender differences in any trait would be improved by simultaneously comparing gender differences in mean and in variability.
Lisäksi voimme varmaan huomioida sen seikan, että naisten asema ja mahdollisuudet eivät ole tänä päivänäkään hyvät kuin osassa maailmaa, sivistyneimmissä länsimaissa.
