Math is a girl thing!

29 August 2012 by Kris Hardies, posted in Uncategorized

Women's underrepresentation in math-intensive fields of science continues to receive a great deal of attention from both scientists and the public. Despite the accumulated scientific evidence on this topic, this remains, however, a very complex area with many yet to be resolved issues. Furthermore, myths and half-truths seem to cloud the public's understanding of this issue.

SEX DIFFERENCES IN MATH PERFORMANCE

It is easy to track down some studies that show men to be, on average, somewhat better at math than women. There are plenty of those to be found in the scientific literature. Conversely, meta-analyses (i.e., studies that combine results from different studies) show that gender differences in math (abilities, performance, etc.) are in fact close to zero (e.g., Else-Quest et al., 2010; Hyde and Linn, 2006). Furthermore, these differences are smaller at younger ages, have been getting (much) smaller over time, and are smaller in more gender equal societies.

While the gender gap in math performance is tiny at best, at the same time, there exists a widely shared belief in our society that math is a male domain, that "math is a boys thing". We of course all remember the infamous talk Larry Summers, President of Harvard University at the time being, gave in 2005. Although this talk was heavily condemned afterwards, many people (both within and outside academia) wondered if there was truth in his claims; that gender gaps in math are due to differences in intrinsic aptitude. While Summers was rightfully criticized on various grounds (scientifically speaking it didn't make too much sense what he was saying), by no means where his claims extraordinary, extreme, or different from what a lot of people (almost intuitively) think about this topic. For example, a couple of years earlier, David Gelernter, professor of computer science at Yale University, declared in an interview that "[women] must be choosing not to enter [math-intensive fields of science], presumably because they don't want to; presumably because (by and large) they don't like these fields or (on average) don't tend to excel in them, which is nearly the same thing." While such statements are clearly untrue from a scientific point of view, they accord very well with what most people believe to be true about this issue. There exists a very robust cultural belief that "math is a boy thing", which we familiarize ourselves with from a very early age. If one, for example, asks children to draw a mathematician they will, almost without exception, draw a male figure (Picker and Berry, 2000, 2001). And it has been shown that most people, (unconsciously) associate math stronger with boys than with girls, even when they do not explicitly endorse the stereotypical association between math and masculinity. (Test it here for yourself.)


GENDER STEREOTYPES AND MATH PERFORMANCE

Given the existence of the widespread cultural belief that boys are naturally more interested in and better at math than girls, it is rather unsurprising that women more often than men have a relatively negative perception of their own mathematical abilities (e.g., O'Laughlin and Brubaker, 1998; Miller and Bichsel, 2004). Such attitudes cause stress and anxiety, of which so-called "stereotype threat" is a special case. The existence of a stereotype leads to heightened performance anxiety experienced by individuals who must perform a task for which their group is thought to not be qualified (e.g., women and math). As a consequence, self-identification as "being a woman" undermines the mathematical desires, expectations, and abilities of womenbecause math is thought of as being male (Nosek et al., 2002). As it was eloquently put by Barbie (Mattel Inc., 1992) 'Math class is tough!'

Hence, it is no surprise that it is well documented that women underestimate their mathematical performances (Spencer et al., 1999). It also explains why Asian women score better on tests that try to capture mathematical abilities when they identify themselves in the first place as "Asian" compared to when they identify themselves in the first place as "women" (Shih et al., 1999). Stereotypes influence the self-image and the behavior of stereotyped individuals. So the mathematical expectations, preferences, and performances of women are influenced by their implicit stereotyping as women ('I am female thus math is not for me'). In sum, the existence of the stereotype image that women and mathematics do not accord very well undermines (unconsciously) women' desire to pursue outstanding mathematical performances (Kiefer and Sekaquaptewa, 2007). Accordingly, it appears that sex differences in math achievement are uniquely related to a nation's average implicit stereotyping (Nosek et al., 2009) beyond the mere influence of generalized national gender inequality (i.e., the gender gap in math is smaller in countries with a more gender-equal culture [Guiso et al., 2008]). Moreover, since beliefs about math and women are widespread believed in society women see their ideas and stereotypes about women and math being confirmed, reinforced, and stimulated by their environments. Teachers, for example, ascribe mathematical excellence of girls rather to "effort" while they ascribe the mathematical excellence of boys rather to "talent" (Hamilton, 2008). Such different approach is, of course, not without consequences because effort is, by definition, restricted to certain limits, while talent is not. So, it is hardly surprising that the math performances of women are negatively influenced when they are told that sex differences in math performances are caused by genetic differences while there is no effect when women are told that such differences are due to experiential causes (Dar-Nimrod and Heine, 2006). Men are therefore more than women stimulated to further develop their mathematical abilities, resulting in a vicious stimulus-response-cycle (causing the gender gap in math to widen as individuals grow older).

So while the recent initiative of the European Union, Science: It's a girl thing!, is by all means a small step towards resolving women's underrepresentation in math-intensive fields, it could nevertheless prove to be an important step. Changing our cultural attitudes towards science (and the combination of women and math) will prove to be a necessary first step to obtain gender equality. Importantly, as a recent study by Kane and Mertz (2012) shows: not only is the gender gap in math absent in more gender equal countries, overall math achievement is also higher in such countries!

References

  • Dar-Nimrod, I. and Heine, S. J. (2006) Exposure to Scientific Theories Affects Women's Math Performance. Science, 314(5798): 435.
  • Else-Quest, N. M., J. S. Hyde and M. C. Linn (2010) Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin, 136(1): 103.
  • Gelernter, D. (1999) Women and science at Yale. The Weekly Standard, June 21, pp. 11-12
  • Guiso, L. et al. (2008) Culture, Gender, and Math. Science, 320(5880): 1164-1165.
  • Hamilton, C. (2008) Cognition and sex differences. Basingstoke, Palgrave Macmilla.
  • Hyde, J. S. and M. C. Linn (2006) Gender Similarities in Mathematics and Science. Science, 314(5799):599–600.
  • Kane, J. M. and J. E. Mertz (2012) Debunking Myths about Gender and Mathematics Performance. Notices of the American Mathematical Society, 59(1): 10-21.
  • Kiefer, A. K. and D. Sekaquaptewa (2007) Implicit stereotypes and women's math performance: How implicit gender-math stereotypes influence women's susceptibility to stereotype threat. Journal of Experimental Social Psychology, 43: 825–832.
  • Miller, H. and J. Bichsel (2004) Anxiety, working memory, gender, and math performance. Personality and Individual Differences, 37(3): 591-606.
  • Nosek, B. A. et al. (2009) National differences in gender-science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences of the USA, 106(26): 10593–10597.
  • Nosek, B. A., M. R. Banaji and A. G. Greenwald (2002) Math = Male, Me = Female, Therefore Math ≠ Me. Journal of Personality and Social Psychology, 83(1): 44-59.
  • O'Laughlin, E. M. and B. S. Brubaker (1998) Use of landmarks in cognitive mapping: Gender differences in self report versus performance. Personality and Individual Differences, 24(5): 595-601.
  • Picker, S. H. and J. S. Berry (2000) Investigating pupils' images of mathematicians. Educational Studies in Mathematics, 43(1): 65–94.
  • Picker, S. H. and J. S. Berry (2001) Your students' images of mathematicians and mathematics. Mathematics Teaching in the Middle School, 7(4): 202–208.
  • Shih, M., T. L. Pittinsky and N. Ambady (1999) Stereotype Susceptibility: Identity Salience and Shifts in Quantitative Performance. Psychological Science, 10(1): 80-83.
  • Spencer, S., Cl. Steele and D. Quinn (1999) Stereotype Threat and Women's Math Performance. Journal of Experimental Social Psychology, 35(1): 4-28.

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