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Personally, I Don’t Want To Be One Of The Boys…

July 30th, 2008 · 8 Comments
Discrimination · Gender

Normally I don’t like to just parrot content from other blogs, but Alex Tabarrok on Marginal Revolution does such a good job of summarizing the latest talk on gender differences and math ability that I had to include it here. Basically, the research shows that males, while having the same mean in terms of math ability, have a higher variance in ability than females. This means that you get more outliers (on both ends of the spectrum) that are male. (This is fair to say in absolute numbers do to the roughly 1:1 ratio of males to females in the population.) If you believe that a supremely high (read, off the charts) math ability is a significant driver of a career such as, oh I don’t know, physics or math professor, it wouldn’t be surprising that there are more males than females in these professions.

That in itself is nothing particularly new or surprising. What is a bit suprising is that, again quoting MR, “Now the study authors clearly wanted to downplay this finding so they wrote things like ‘our analyses show greater male variability, although the discrepancy in variances is not large.'” This is surprising, and frustrating for that matter, because the study was published in the July 2008 issue of Science, which is from what I can tell a respected academic publication. Isn’t one of the perks of academia the fact that researchers can be objective in reporting their findings (and in fact, one could argue, are obligated to do so) rather than have to couch results in politically correct terms? Alex goes on in his post to explain that this “not large” discrepancy actually makes a big difference for the tail ends of the distribution, so the downplaying is not particularly justified.

Anyway, enough of quoting others…my (probably unpopular) question is why is it so damn important for women to be like men in this regard? I am in no way anti-feminist, but the desire to “prove” equality rather than try to objectively understand similarities and differences truly perplexes me. What perplexes me even more is I’ll bet that no one ever got hung (hanged?) in effigy (or fired, for that matter) for saying that, I don’t know, the top male runners can run faster than the top female runners, even though this, too, is mainly a matter of innate ability. Or, to give a more direct analogy, why aren’t people trying really hard to understand why there are more female librarians than male ones? Maybe there are more hyper-organized females in the upper tail of that distribution? My guess is that the attention would shift if librarians were brought to a level of compensation and prestige equivalent to that of university science professors.

It seems as though the real impetus for a lot of this research is to try to make the argument that women are discriminated against in at least some parts of the science and engineering disciplines, or that they are somehow discouraged from pursuing their true love for the quantitative early in life. (If we rule out innate differences, discrimination must be the explanation, right? I’ll come back to this below.) Unfortunately, the authors of this research end up grasping at questionable straws rather than admitting that the statistical evidence is not what they want it to be. Isn’t it a bit odd that researchers appear to want to find evidence for a discrimination situation? Personally, I would prefer that people of my type are not discriminated against, thank you very much. My guess is that the discrimination situation is more palatable, since we can “fix” that problem through policy, whereas it’s really difficult to make people innately smarter. Come to think of it though, the U.S. isn’t really stellar at writing anti-discrimination laws or at teaching math. Hm.

It’s not the greatest outcome from an equity perspective if females overall end up consistently sorting into lower paying and lower prestige occupations, but, given that the trend is for women to be more educated on average than men, I doubt that the sorting issue is a severe concern going forward. (See the CPS data for details.) For example, of 25-34 year olds in the U.S., .75% of women as compared to .56% of men hold doctoral degrees, and that trend persists down the academic food chain:
masters degree or higher: men 7.1%, women 9.4% (though men have more professional degrees, which could tip wages in their favor)
bachelor’s degree or higher: men 28%, women 34% (men also show a decreasing trend in this rate)
If we see education as a proxy for intelligence (which we can’t really do, but go with me here), the .56% and the .75 are roughly consistent with the idea that those holding doctorates are about 3 standard deviations away from the mean in that regard, with females actually appearing to have a fatter tail. While this doesn’t get at mathematical ability specifically, it just shows that in the aggregate it must be the case, if men outnumber women in the upper ranks of science and engineering, that women are more (academically) accomplished than men in other areas that are not being studied as fervently.

I’m almost done, I swear. My last point is, despite the outcome on the intelligence/ability debate, there are explanations for the observed occupational data that have little, if anything, to do with discrimination. A couple of my favorites:
— Preferences. Even if nobody primed them with said toys, it is still likely the case that, on average, more boys than girls would like trucks, and more girls than boys would like dolls. (Psychologists, please correct me if I am wrong- that’s what the comments feature is for.) Why is it so hard to believe that similar preference patterns exist for things like career selection? Note that this doesn’t even have to do with the idea of females choosing careers for their flexibility aspects.
— Competitiveness, or rather taste for competition. Economists Muriel Niederle and Lise Vesterlund argue that “women as a group dislike competition more than men, even if they are of the same ability. If women seek to avoid competition, then they may be less successful in obtaining promotions and more lucrative jobs.” Okay, so I suppose that this should technically go under the “preferences” category. I also find it interesting that these reseachers also find that men improve their performance more in competitive environments than do women, and this could also explain the skew of promotions and status towards men, since promotions and the like can be thought of as winning a competitive tournament against one’s coworkers. (To relate this to the example at hand, academia is more competitive than it seems from the outside, especially in the sciences, and in a lot of ways it resembles a winner-take-all environment.)

Furthermore, the statistical discrimination explanation doesn’t even make sense. According to Wikipedia, statistical discrimination occurs when individuals from different groups are treated unequally because these groups, on average, differ in behavior. (Statistical discrimination is basically a fancy synonym for stereotyping.) Therefore, the incentive to discriminate in this way comes about when there is a lack of information on the measure of interest. In the hiring market for science and engineering professionals, there are plenty of available measures that proxy an individual’s intelligence and ability, so there is little reason to resort to statistical discrimination based on gender in this context.

Ok, I am going to play with my Barbies now.

Tags: Discrimination · Gender

8 responses so far ↓

  • 1 Paula Hall // Jul 30, 2008 at 4:44 pm

    Never could understand why people were getting their panties in a bunch over this — I mean, stats ain’t people. Your analogy to different physical capabilities is very apt. I suspect the intellectuals and activists most upset by this have massive inferiority complexes.

  • 2 econgirl // Jul 31, 2008 at 5:49 pm

    Thanks to Paula for reminding me about a particularly funny comic. I have noticed in the past that, at least in terms of math ability, women are much more likely to be subject to stereotypes than men.

  • 3 Dan L. // Aug 5, 2008 at 8:27 pm

    I take issue with quite a lot of this post. I don’t know where to start, so I’ll just go in order:

    1. Your analogy with athletes is a dumb one. (I don’t mean to be insulting, but it’s really beneath you.) There are obviously innate differences between males and females. No one denies this. There certainly exist differences between actual males and females. No one denies this either. The only matter up for debate is which of the actual differences are primarily caused by innate differences. Running faster is a simple consequence of being taller and have bigger muscles, so it’s clear that innate differences are important here. Mathematical reasoning is a complicated procedure carried out by the brain, and unlike height, it’s not so obvious which innate ingredients are needed for math genius, and neuroscience certainly doesn’t currently understand to what extent these ingredients are different in males and females.

    2. The librarians comment is also dumb. It’s akin to saying that maybe women are better than men at cleaning toilets.

    3. You write about discrimination, for example, “Isn’t it a bit odd that researchers appear to want to find evidence for a discrimination situation?” Actually, I don’t believe that the Science article even used the word discrimination. You’re attacking a straw man. Very few people are out to prove that discrimination is the dominant force keeping women out of mathematical fields (although it seems likely that non-overt discrimination is at least one of many contributing factors). The point being made is that the gender gap is primarily due to social factors rather than innate ones. It’s a consequence of the way our society is constructed. (Considering that most aspects of our lives are consequences of the way our society is constructed, why should this be surprising?)

    4. You write, “In the hiring market for science and engineering professionals, there are plenty of available measures that proxy an individual’s intelligence and ability, so there is little reason to resort to statistical discrimination based on gender in this context.” But those measures are extremely subjective, so biases (usually unintentional) tend to have much more influence. For example, a famous psychological experiment showed that people rating job candidates on the strength of their resumes rated resumes with male names higher than identical resumes with female names. Again, going back to 3, I’m not saying that “statistical discrimination” is the driving force, but it does exist.

    5. Critics like Tabarrok are just as guilty as the writers of the Science article at ignoring inconvenient facts. While boys apparently outperformed the girls at top end, the study also showed that more Asian girls were the in the top 1% than Asian boys, which would again indicate that perhaps the measured differences are primarily due to cultural factors rather than biological ones.

    6. You criticize the scientific integrity of the authors of the Science article, but I’d like to point out that this *is* education research, not exactly the gold standard of rigorous scientific thought. But as long as one can rely on the processing of the data, the study certainly has value.

    7. How come you never respond to any of my comments? I’m starting to get the feeling that you want me to go away. 🙁

  • 4 Meryl // Mar 7, 2009 at 11:16 am

    Honey, maybe she never responds to your comments because you appear to be attacking purely for the sake of attacking. Each of the things you say above is either patently untrue/ignorant or misses the point!

  • 5 Eash // Mar 12, 2009 at 11:48 am

    Thank you Meryl, I wouldn’t liken being a librarian to cleaning toilets.

  • 6 Bags // Mar 13, 2009 at 10:54 pm

    I believe a reason you may have overlooked with regards to why women do not have as high of levels of employment in high-tech, math intensive fields is the difference between the time men and women spend during child raising. When a woman becomes pregnant and needs to care for a newborn, this usually will force her out of the labor market, while the father of the child will not leave his job. This time out of the labor market will create several differences between men and women of the same age. First, the woman who leaves the labor market to raise a child, will have less work experience than a comparable man, and hence will have less on the job training. Also, the time spent away from the labor market will depreciate the value of the female’s human capital, which will mean that she probably earn lower wages when she returns to the labor market. Lastly, this discontinous labor participation means that the female will have a shorter expected working life. This will lead her to have less incentive to pursue on the job training. All that being said, women are more likely to pursue careers where they won’t experience as much human capital depreciation if they have to leave the labor force to raise a child. In high tech, math intensive fields, technology and ideas are constantly evolving and taking time out of the labor force to raise a child will result in a much larger amount of human capital depreciation compared with a job that does not change as much in the time the woman would be out of the market. This is one of the reasons why there are less women in these kinds of jobs and also why there is a pay gap between genders in these fields. I remember reading all of this in a paper that, I think, was written by Blau, Ferber, and Winkler but it’s been a little while so I’m not certain about that.

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