Last month, neuroscientist Dario Maestripieri committed a faux pas after visiting a conference of his fellow neuroscientists. On his Facebook page, he left the following statement about his female colleagues:

My impression of the Conference of the Society for Neuroscience in New Orleans. There are thousands of people at the conference and an unusually high concentration of unattractive women. The super model types are completely absent. What is going on? Are unattractive women particularly attracted to neuroscience? Are beautiful women particularly uninterested in the brain? No offense to anyone..

An uproar over this ensued. Despite the furor, Meastripieri’s comment actually sounds like a fairly sound empirical observation. Nonetheless, his comments have not sit well with certain individuals:

It’s almost like people have something invested in denying the existence of gender bias among scientists, the phenomenon of a chilly climate in scientific professions, or even the possibility that Dario Maestripieri’s Facebook post was maybe not the first observable piece of sexism a working scientist put out there for the world to see.

The thing is, that denial is also the denial of the actual lived experience of a hell of a lot of women in science (and in other fields — I’ve been sexually harassed in both of the disciplines to which I’ve belonged).

I can’t pretend to speak for everyone who calls out sexism like Maestripieri’s, so I’ll speak for myself. Here’s what I want:

1. I want to shine a bright light on all the sexist behaviors, big or small, so the folks who have managed not to notice them so far start noticing them, and so that they stop assuming their colleagues who point them out and complain about them are making a big deal out of nothing.
2. I want the exposure of the sexist behaviors to push others in the community to take a stand on whether they’re cool with these behaviors or would rather these behaviors stop. If you know about it and you don’t think it’s worth talking about, I want to know that about you — it tells me something about you that might be useful for me to know as I choose my interactions.
3. I want the people whose sexist behaviors are being called out to feel deeply uncomfortable — at least as uncomfortable as their colleagues (and students) who are women have felt in the presence of these behaviors.
4. I want people who voice their objections to sexist behaviors to have their exercise of free speech (in calling out the behaviors) be just as vigorously defended as the free speech rights of the people spouting sexist nonsense.
5. I want the sexist behavior to stop so scientists who happen to be women can concentrate on the business of doing science (rather than responding to sexist behavior, swallowing their rage, etc.)

Women: also people! Just like men, but with different genitals! And women who are neurobiologists probably have literally tens of thousands of priorities in their lives that outrank “appealing to Professor Dario Maestripieri’s boner.” Or anyone’s boner, really!

You’ll notice in this criticism of Maestripieri that no one is claiming that his observations are factually incorrect. I’ll wager that they’ll be few that do, if any. Of course, that would involve first accepting that attractiveness is an objectively quantifiable trait, and many in the politically correct crowd haven’t come to terms with this fact, despite the abundance evidence for such.

It probably doesn’t help that Maestripieri’s research focuses on gender and attractiveness. Back in March, this is what he wrote on his blog at Psychology Today (where all the racist, sexist pigs seem to congregate):

I fly frequently and at some point I began to notice that the passengers who sit in F/B class seem better-looking than those sitting in Economy (E). This applies to individuals of both genders and of any age, including children and people in their 70s. A few times, as I boarded a plane and walked to reach my seat in the last row I mentally assigned an attractiveness score, from 1 to 10, to the people sitting in F/B class and calculated an average. Then I did the same for some random people sitting in the middle of the E class. Every time I did this, the average score for the people in the F/B class turned out to be higher than the average score for the people in the E class, which means that I rated the F/B people as being more attractive. My observations and mental calculations, of course, cannot be considered scientific data by any stretch of imagination. I encourage all of you—the readers of this blog—to do the same observations next time you fly and send me your average attractiveness scores for the F/B and the E passengers. When I have enough reports, I will run a statistical analysis and we will all publish our results in Science magazine (or more likely, I will write another blog about it).

In short, it seems that Maestripieri’s comments are reflective of something he does all the time; they are his observation about the attractiveness (perceived by him) of individuals encountered in different settings.

In this case this is about women in the field of neuroscience. In terms of gender ratios, it seems (of new Ph.Ds anyway) that the number of men and women in field is roughly equal. But are these women typically less attractive?

Here is a quick Google image search montage:

(also as a teenager):
These are culled from an image search of “female neuroscientists”. I selected all the White females I could find and verify as being neuroscientists. Whenever possible, I tried to find images of the older scientists as younger women, to remove age as a factor as much as possible. Clicking on each image leads to its source and usually a bio of the researcher pictured.

What we see is a fairly good mix of attractiveness, ranging from quite attractive to considerably less so. This appears to be contrary to Maestripieri’s reported experience. One clear pattern does seem to emerge here, however: the younger neuroscientists seem to be systematically more attractive than their elder colleagues. This seems to be true even when somewhat controlling for present age, as can be seen from the youthful photos of the old timers.

If this pattern is indeed real, then why is this so? There are only two fundamental explanations: either women entering the field are more attractive than they once were (a cohort effect) or women remaining in the field (or achieve some level of prominence) tend to be those who are significantly less attractive. I will leave it to others to distinguish which operates here, or if this pattern is indeed real. If the former is the case, perhaps it is a sign that attempts to get women into the sciences has been successful, and may now have more appeal to a broader range of women (including the more attractive ones).

Here’s another interesting experiment. See if you can pick out which of these women are in the sciences from those who are non-scientists (typically in business). Try to guess each before clicking on the link below:

These are from ChipChick’s The Top 13 Women Who Impacted Technology in 2010, which includes a mix of women in business and/or the sciences. In this instance, there is a fairly distinctive pattern of the scientists looking systematically different (and less attractive) from the businesswomen (interestingly, their 2011 choices of top women does not display this pattern as egregiously; maybe they were called on the pattern from the previous year and tried to even it out.) This is suggest that perhaps it’s not that intelligent people, overall, are less attractive, but perhaps that there is some selective filter towards those becoming researchers, or one for those finding success in business (such as, as Half Sigma suggested, sleeping one’s way up the corporate ladder—”the executive couch”, so to speak). If women in business are selected for attractiveness as well as ability, this may explain the deviation between the “first class” club and the neuroscientists noted by Maestripieri. Only more research can determine this.

In my personal experience, I’ve noted I can fairly accurately estimate how intelligent someone is just by looking at them (at least, whether they are on the right, middle, or left parts of the bell curve), which was the focus of several studies discussed by a Slate article earlier this year. The key thing is that unintelligent, average, and high intelligent people have a distinctive “look” about them, which Half Sigma also noted. While there are often tells, such as glasses, smart people still none the less stand out in their own way (as do other types of people). Overall, as noted by Satoshi Kanazawa, there is a positive association with attractiveness and intelligence, but I have noted that it appears that the most intelligent people are not, as a group, the most attractive (just see here and here). Indeed, Kanazawa’s data showed that those rated 5 out of 5 on the attractiveness scale had a mean IQ of only 100.7, vs 94.2 for those rated 1 out of 5 (the numbers cited in his blog post probably underestimates the correlation due to the fact that it’s not separated by race). The very attractive do not appear to be overly intelligent, and as the Slate piece noted, the standard deviation in intelligence is higher for the unattractive (which means that they are more spread along the bell curve).

I believe that this can likely be explained by genetic load. Attractiveness may signify that an individual possesses a low level of genetic load, (which detracts from appearance and intelligence) but not necessarily a high amount of genes for intelligence. Indeed, some genes for intelligence may have a negative impact on appearance (smarter people tend to have larger foreheads, for example, which may not necessarily be flattering for the individual who possesses it), and if intelligence was under recent and fairly intense selection (which appears to be the case in medieval northern Eurasia), many individuals could have gotten by because of their smarts despite their looks. Recent and intense selection tends to select for “sub-optimal” genes for the trait under selection, as “quick-fixes” are favored, with superior, “long-term” solutions taking more time to evolve.