We have translated an article by psychologist Guido Corradi published in the Spanish site Politikon. You can follow him via twitter in @GuidoBCor or read him in Rasgo Latente.

**By Guido Corradi**

Link to original text: http://politikon.es/2015/06/23/genero-y-aptitud-numerica/

23rd of June, 2015

The proportion of men choosing a technical degree is higher than that of women. Is this, perhaps, because girls might have lower mathematical aptitude owing to different evolutionary roles? Today, despite the latest scientific findings, many myths and erroneous beliefs remain accepted as true by both society and by a segment of the scientific community. As Elizabeth Spelke (2005) points out, some ideas which may sound plausible but must be questioned are: a) Men possess higher mathematical aptitude due to higher spatial abilities; b) From their youth, men are more focused on objects; and c) The higher variance in male cognitive ability explains why there are more men in the upper deciles. As we’ll see, these arguments make for plausible-sounding narratives, even though they are far from having a solid empirical basis. While it is true that there are gender differences, these do not affect mathematical skills. What’s critical is the social context in which mathematical aptitude emerges, as reflected in differences among countries in cross-section, or over time.

What is the evolutionary origin of the capabilities that allow us to use numbers? Thirty thousand years ago, humans were using pieces of bones to represent quantities. Twenty five thousand years later, the first symbolic representation of quantities –numbers– appear. Nowadays, children learn complex mathematical concepts (verbalization of quantities, subtraction, addition, number representation) in their childhood. Mathematics took thousands of years to develop; yet it doesn’t take many years for children to acquire a great knowledge of it. The basic ability of distinguishing quantities, for example, is present in animals as removed from humans as fish. However, as far as we know, we don’t have evidence they can even learn to multiply. From experimental evidence, the ability to manipulate quantities is based on the ability to track moving objects and on the intuitive discrimination of quantities. Both capacities arose in response to evolutionary pressures, but today we humans employ them in a different way.

With this we can weave a pop evolutionary psychology just-so story: boys evolved to hunt, and that’s why their mathematical ability – related to spatial perception- is superior, and from there emerges their superiority in mathematics that in turn leads to a greater number of them pursuing technical skills. But nothing could be farther from the truth. Even though there exists sexual dimorphisms (for example, in spatial navigation), mental rotation and linguistic capacities, there are no sexual differences in the basic mechanism with which numerical cognition operates.

Further, mathematical ability depends on many factors that interact beyond the basic mechanisms outlined previously. Mathematical thinking includes numerical cognition, but that’s not the only factor. Mathematical thinking — which is to say, the ability to operate with, work with, and represent numbers — is an amalgam of simpler skills like numerosity perception. But without the use of language, this capability, even if it already exists, cannot completely develop to full potential. Since mathematical ability is a composite of many other abilities, it’s not farfetched to think that sexual differences can compensate one another through the variability of different underlying abilities. In simpler terms: a higher level of one of these abilities can compensate a deficit in one of the others.

Another idea defending the male advantage over women in mathematical aptitude is the Baron-Cohen hypothesis: that boys become systematizers because they are focused on objects and mechanisms. That early focus would lead them to a better comprehension of abstract mathematical systems. However, if we follow the empirical evidence for this hypothesis, we only find a work by Connellan (2000). There are some points to be noted about this study. The norm in psychology is, we cannot arrive at *big conclusions* unless we have not only results but also revisions and meta-analysis of results. Because it is very easy to take conclusions out of context and go beyond what the data justify. In Connelan’s paper, a big leap is made from talking about baby sight fixation to talking about early male object preference. When this same experimental paradigm is used in adults, no differences are found.

According to the literature, neither spatial navigation skills, nor differences in the variability of cognitive ability, nor the hypothesis of male systematization offer evidence for gender differences in mathematical aptitude which can also explain the differences in the choice of degree leading to technical careers. There are no differences in the basic abilities underlying mathematical aptitude.

And what when we investigate the results of these cognitive abilities? When reviewing a meta-analysis of sexual differences in PISA and TIMMS we see that they depend more on the context they are measured in than on gender itself. Certainly, there is considerable variability among nations which explains gender differences in test scores in terms of differences in social status and women’s welfare.

More recent studies (Lindberg, et al. 2010) support the hypothesis that there are no differences in mathematical aptitude. It has to be mentioned that since measurement of the gap began, gender disparity in mathematical achievement has been decreasing. In a seminal meta-analysis by Hyde (1990) this tendency is observed. When we include more recent work such as the previously cited, we can confirm it. In other words, without a substantial change in human biology, we are achieving important changes in the results of both genders.

When we talk about so important a topic as the gender gap in technical degrees, the debate should center perhaps on social factors, evaluator prejudice, class competitiveness, or motivation. No more effort is required in the dubious sexual differences in mathematical aptitude.

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