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Hurricanes Were Kinda Sexist Until 1979

With Hurricane Sandy, which you might know better as the Frankenstorm, pounding the East Coast, it got us thinking about the weird practice of naming hurricanes after people. It was odder still in the not-too-distant past, since from 1954 to 1979, hurricanes only received ladies’ names.

The practice started with the advent of the National Weather Service (which was then called the National Weather Bureau). The service was started by military meteorologists (yes, that’s a thing) after the end of World War II. They named them after the military phonetic alphabet (Alpha, Bravo, Charlie, etc.). Needless to say, that was a bit boring and repetitive, so the NWS adopted an older, informal practice among meteorologists to name storms the same way people name their cars, boats, guitars, and guns — after women.

It took years of complaining by influential feminists to get the National Weather Service to play fair, since, as it turns out, a lot of women didn’t really like being compared to devastating natural disasters.

But weirder still than the whole idea of giving a unique identity to a giant pocket of low air pressure with high winds whirling around it is the fact that the most devastating hurricanes get their names “retired.” Yes, just as you’ll never see another Chicago Bulls player don the number 23, we’ll never get hit by another hurricane named Katrina or Isabel.

And that’s really weird, right? It’s like we want to honor certain storms as “all-time greats.” I’ve got this weird mental image of jerseys hung in the rafters of the National Weather Service offices.

Sexist-Proving Scientists Prove Scientists Sexist

A comic on Rosalind Franklin from Kate Beaton's webcomic "Hark! A Vagrant"

Source: Hark! A Vagrant

The fact that women aren’t paid as fairly as men isn’t news to anyone. But this is the first time I’ve seen that stat approached as a highly controlled purely scientific study, and directed at the very people conducting the study.

A group of researchers at Yale conducted a double-blind study that sent out identical application materials for entry-level academic science jobs. The catch? The applications were randomly given a male or female name. You can read the full published paper here. (It’s only six pages, so it is readable for the curious.)

The end results were biased. Really, really biased. On a scale of 1-5 in the categories of competence, hireability, and mentoring, women were consistently rated about 0.7 points lower then men. The “hiring” scientists were also asked to offer a starting salary to the applicants. The women were offered an average of $26.5K. The men were offered a little over $30K.

Marie Curie must be turning over in her radioactive grave.

I’m sure you could probably do this study with any industry and get more or less the same results. But the reason this study is worth a blog post is (a) the whole scientists using science against other scientists thing has a bit of an ouroboros feel to it and (b) there is already such a strong stereotype against women in math and science. This study suggests that stereotype might be a self-fulfilling prophesy. If women are rated lower and paid less, there will be fewer female scientists considered eligible candidates and more female scientists who look elsewhere for a field where it is easier to thrive unimpeded. From the study’s conclusions:

To the extent that faculty gender bias impedes women’s full participation in science, it may undercut not only academic meritocracy, but also the expansion of the scientific workforce needed for the next decade’s advancement of national competitiveness.

It’s not worth giving the individual scientists any grief about this. Like so many things, the problem is social and institutional, not individual. Note that the study found no discernible difference between male and female hiring academics. The women displayed the same bias. How can that be?

Once again, it’s a self-fulfilling prophesy. Female scientist reads application from another woman, is subconsciously aware of the stereotype and subtly adheres to it, despite better judgment at a higher processing level. Or it might be explained by a type of subconscious stereotype threat. (Here’s a good NPR article on the topic.)  Female scientist reads application from another woman, is actively aware of the stereotype, and judges more critically to prove that she has no bias one way or the other. With both explanations, the end result is the same.

That’s the sad/confusing part. Being aware of a problem is the right first step towards fixing it, but perhaps awareness subtly contributes to the problem too.

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