In honor of International Women’s Day, Coursera released an analysis of gender equality in education which I began as an intern last summer, using their unique dataset which includes data for millions of women around the world.
Studying statistics has made me very interested in gender issues, and the reason is simple. If you're a statistician, studying gender is like kicking a puppy down the stairs: an unfairly easy way to see something interesting. And, depending on the dataset and the cuteness of the puppy, very depressing. It’s hard not to get angry when you see the numbers scroll down your screen, laying out basic inequities in black and white [1].
So it was an honor to work on this project with Tom and the other members of the data analytics team: even though I was the only girl on the team, they never made feel that way. If we ever do achieve gender parity, it will be in part because of guys like them -- and also because of the equally intimidating women Coursera’s managed to hire. On Friday night Tom and I were trying to finish up this analysis in Coursera’s offices, and it was getting near 10 and the lights kept turning off so we were coding in the dark and eating tortilla chips and seaweed for dinner [2]. And I was hunched over on the floor trying to debug my code and thinking, huh, I look really cool right now.
But then I realized: I was happy. This is what I want to be doing.
With thanks to Nick Eriksson, Jacob Steinhardt, and Nat Roth for insights and edits, and to everyone at Coursera.
With thanks to Nick Eriksson, Jacob Steinhardt, and Nat Roth for insights and edits, and to everyone at Coursera.
Notes:
[1] There are, of course, many other factors -- race and age being two -- which reliably produce profound differences between people, and these are also important to study. Unfortunately, these traits are often harder to infer: in many datasets, you can figure out someone’s gender from their name, but you can’t really do that for race and age.
[2] To avoid giving a false impression: this is not how people at Coursera usually work. In fact, everyone else I saw at the office was there for the company’s weekly happy hour.