saturnfan wrote:Yes, if you are going to make claims, surprisingly enough, you need to back them up.
I'm sorry, but the original claim is yours. You claimed that women are underrepresented because men are better suited to it. That is
your claim.
Is about half, more or less than 50%? And Malaysia was the only country listed specifically about computer science. This equates to women being far more represented in the computer sciences across the globe?
Seriously. If you cannot at least argue with what I actually say, why bother at all?
http://psi.sagepub.com/content/8/1/1.abstract
Thank you for an excellent piece of shoddy science.
I quote:
Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science.
If this were absolutely true, then why aren't men outperforming women on standardized math exams anymore?
Our analysis shows that, for grades 2 to 11, the general population no longer
shows a gender difference in math skills, consistent with the gender similarities hypothesis (19). There is evidence of slightly greater male variability in scores, although the causes remain unexplained. Gender differences in math performance, even among high scorers, are insufficient to explain lopsided gender patterns in participation in some STEM fields. An unexpected finding was that state assessments designed to meet NCLB requirements fail to test complex problem-solving of the kind needed for success in STEM careers, a lacuna that should be fixed.
Hyde et al. (2008) "Gender Similarities Characterize Math Performance"
Science.
Current research published in a premiere academic journal.
You might wonder about post-secondary education tests?
Proponents of what has been termed the Gender Similarities Hypothesis (GSH) have typically relied on meta-analyses as well as the generation of nonsignificant tests of mean differences to support their argument that the genders are more similar than they are different. In the present article, we argue that alternative statistical methodologies, such as tests of equivalence, can provide more accurate (yet equally rigorous) tests of these hypotheses and therefore might serve to complement, challenge, and/or extend findings from meta-analyses. To demonstrate and test the usefulness of such procedures, we examined Scholastic Aptitude Test–Math (SAT-M) data to determine the degree of similarity between genders in the historically gender-stereotyped field of mathematics. Consistent with previous findings, our results suggest that men and women performed similarly on the SAT-M for every year that we examined (1996–2009). Importantly, our statistical approach provides a greater opportunity to open a dialogue on theoretical issues surrounding what does and what should constitute a meaningful difference in intelligence and achievement. As we note in the discussion, it remains important to consider whether even very small but consistent gender differences in mean test performance could reflect stereotype threat in the testing environment and/or gender biases in the test itself that would be important to address.
Ball et al. (2013) "Beyond Gender Differences Using Tests of Equivalence to Evaluate Gender Similarities."
Psychology of Women Quarterly.
And one more on national differences:
Abstract:
About 70% of more than half a million Implicit Association Tests completed by citizens of 34 countries revealed expected implicit stereotypes associating science with males more than with females. We discovered that nation-level implicit stereotypes predicted nation-level sex differences in 8th-grade science and mathematics achievement. Self-reported stereotypes did not provide additional predictive validity of the achievement gap. We suggest that implicit stereotypes and sex differences in science participation and performance are mutually reinforcing, contributing to the persistent gender gap in science engagement.
Discussion:
We found that a national indicator of implicit gender–science stereotyping was related to nations’ sex differences in science and math achievement...The mean level of implicit stereotyping among national citizens, regardless of age or gender, predicted the sex differences in TIMSS performance among the 8th graders of that nation from 2003 and 1999...Rather, a more likely cause of the relation is that both the 8th grade test takers and the diverse IAT participants of a given country are influenced by the same socio-cultural context. That social context embodies the reciprocal influence of stereotyped science = male associations and sex differences in engagement in science and mathematics. This significant relationship persisted even after accounting for a general indicator of societal gender inequality, the GGI. Thus, the relation between implicit gender–science stereotypes and science and math achievement gaps is specific to science and math domains, and not simply a consequence of generalized national gender inequality.
Nosek et al. (2009). "National differences in gender–science stereotypes predict national sex differences in science and math achievement."
PNAS.
I don't see how anyone can have that level of faith in that article. I imagine that line of inquiry won't last.
