Poster found here.
The original compute-ers, people who operated computing machines, were mostly women. At that period of history, most typists were women and their skills seemed to transfer from that job to the next. As late as the second half of the 1960s, women were seen as naturals for working with computers. As Grace Hopper explained in a 1967 Cosmopolitan article:
It’s just like planning dinner. You have to plan ahead and schedule everything so it’s ready when you need it. Programming requires patience and the ability to handle detail. Women are “naturals” at computer programming.
But then, this happened:
Computer programming was masculinized.
The folks at NPR, who made the chart, interviewed information studies professor Jane Margolis. She interviewed hundreds of computer science majors in the 1990s, right after women started dropping out of the field. She found that having a personal computer as a kid was a strong predictor of choosing the major, and that parents were much more likely to buy a PC for their sons than they were for their daughters.
This may have been related to the advertising at the time. From NPR:
These early personal computers weren’t much more than toys. You could play pong or simple shooting games, maybe do some word processing. And these toys were marketed almostentirely to men and boys. This idea that computers are for boys became a narrative.
By the 1990s, students in introductory computer science classes were expected to have some experience with computers. The professors assumed so, inadvertently punishing students who hadn’t been so lucky, disproportionately women.
So it sounds like that’s at least part of the story.Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.
Source: Hirsute History.
Have a scholar we should commemorate? Send us a cool pic and we will!
In statistics, a little star next to a coefficient generally means that the result is statistically significant at the p<.05 level. In English, this means that there is only a 1 in 20 chance that the finding just popped up by pure random chance. In sociology, that’s generally considered good enough to conclude that the finding is “real.”
If one investigates a lot of relationships, however, this way of deciding which ones to claim as real has an obvious pitfall. If you look at 20 possible but false relationships, chances are that one of them will be statistically significant by chance alone. Do enough fishing in a dead lake, in other words, and you’ll inevitably pull up some garbage.
Thanks xkcd, for making this funny:Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.
Anthropologist John Ziker decided to try to find out. With his collaborators — Matt Genuchi, Kathryn Demps, and David — Nolin Ziker recruited a non-random sample of 16 professors at Boise State University and scheduled interviews with them every other day for 14 days. In each interview, they reported how they spent their time the previous day. In total, he collected data for 166 days.
It’s a small, non-random sample at just one university, but here’s what he discovered.
All ranks worked over 40 hours a week (average of 61 hours/week) and all ranks put in a substantial number of hours over the weekends:
Professors, then, worked 51 hours during the official workweek and then, in addition, put in ten hours over the weekend.
What were they doing those days? Research, teaching, and service are the three pillars of an academic workload and they dominated professors’ time. They used weekends, in particular, to catch up on the first two. The suspension of the business of the university over the weekend gave them a chance to do the other two big parts of their job.
This chart breaks down the proportion of time they spend on different activities more clearly. Ziker is surprised by the amount of time faculty spend in meetings and I’m particularly impressed by the amount of time they spend on email. Most professors will probably note, with chagrin, the little bars for primary research and manuscript writing.
This was just a first phase, so we can look forward to more data in the future. In the meantime, I’ll add this data to my preferred answer when asked what I do all day:Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.