Female Programmers

„If your image of a computer programmer is a young man, there’s a good reason: It’s true. Recently, many big tech companies revealed how few of their female employees worked in programming and technical jobs. Google had some of the highest rates: 17 percent of its technical staff is female. It wasn’t always this way. Decades ago, it was women who pioneered computer programming — but too often, that’s a part of history that even the smartest people don’t know,“ explains NPR’s Laura Sydell.

In an interview on All Tech Considered, Walter Isaacson, the author of „The Innovators: How a Group of Hackers, Geniuses and Geeks Created the Digital Revolution,“ describes how the women who pioneered the computer revolution have often been left out of the story. In his book, he shares many of their stories, including that of Ada Lovelace, who is widely considered the world’s first computer programmer; Grace Hopper, the inventor of the first compiler and the COBOL programming language; and the female mathematicians who developed programs for the world’s first general-purpose computer, the ENIAC.

„When they have been written out of the history, you don’t have great role models,“ says Isaacson. „But when you learn about the women who programmed ENIAC or Grace Hopper or Ada Lovelace … it happened to my daughter. She read about all these people when she was in high school, and she became a math and computer science geek.“

To listen to Sydell’s interview on NPR, visit http://n.pr/1dK3ZfB — you can also learn more about Isaacson’s book „The Innovators“ at http://amzn.to/1NLLGAO

To introduce children to the woman who invented the first computer program — Ada Lovelace — there are several excellent picture books about her: “Ada Byron Lovelace and the Thinking Machine” for ages 5 to 9 (http://www.amightygirl.com/ada-lovelace-thinking-machine), „Ada Lovelace, Poet of Science“ for ages 5 to 9 (http://www.amightygirl.com/ada-lovelace-poet-of-science), and „Ada’s Ideas” for ages 6 to 9 (http://www.amightygirl.com/ada-s-ideas)

There is also a new early chapter book about the six women who programmed ENIAC, the first programmable computer, for ages 6 to 8 at http://www.amightygirl.com/women-who-launched-the-computer-age

For a fun way to introduce your Mighty Girl to programming, check out the new game „Code and Go Robot Mouse,“ for ages 5 to 9 at http://www.amightygirl.com/code-and-go-mouse

Another excellent way introduce kids to programming is via new DIY systems that allow you to build real programmable computers on your own such as the „Raspberry Pi Ultimate Set“ for ages 9 and up (http://www.amightygirl.com/raspberry-pi-ultimate-set) and „Piper: Craft A Computer Kit“ for ages 7 and up (http://www.amightygirl.com/piper-craft-a-computer-kit)

We Like You a Lot, Ms. Scientist, But We’d Rather Hire the Guy

A recently released study, “Science Faculty’s Subtle Gender Biases Favor Male Students,” shows compelling evidence for unconscious gender bias among faculty, specifically in some natural and biological science fields.

The researchers asked a national sample of 127 biology, physics and chemistry professors to evaluate the application materials of an undergrad science student who applied for a lab manager position, a job they saw as a gateway to other opportunities.

Everyone was given the same materials, but half the applicants were given the first name Jennifer and half were called John. The participants were told the student would be given feedback based on their evaluations.

The results are sobering. There was a significant difference in the average competence, hireability and mentoring ratings by gender. Professors who thought they were evaluating a female applicant saw a less-qualified candidate than professors who were evaluating the identical application materials but thought it was from a man:

So not only was there a gap in perceived competence and fit for the position, but professors were less willing to engage in the type of mentoring that can help students gain both skills and confidence in their abilities—which can be especially important for under-represented groups.

And despite what you might expect, female professors were just as likely to do this as male professors were. Just thinking an applicant was female seems to have touched off an unconscious bias that led them to see female candidates negatively and to be less willing to spend time mentoring them. Professors’ age, tenure status and discipline didn’t make a difference, either.

The professors were also asked to recommend a starting salary. Again there was a significant difference. The average suggested beginning salary for the male candidate was $30,238, while for the female student it was $26,507:

The authors point out that these findings are especially noteworthy because, unlike many studies of gender bias that use college students or people who have never had to make the type of hiring or mentoring decisions they’re being asked to engage in for the study, this sample was made up of scientists who are active in their fields, regularly working with students.

Interestingly, when asked how much they liked the candidate, those evaluating the female student gave a higher score than those assigned the male student. But this didn’t translate into seeing the female candidate as competent. The study authors argue that this is strong evidence for subtle gender bias. The professors didn’t express dislike or hostility toward a female candidate. In fact, they tended to actively like her. But as the researchers explained,

… despite expressing warmth toward emerging female scientists, faculty members of both genders appear to be affected by enduring cultural stereotypes about women’s lack of science competence that translate into biases in student evaluation and mentoring.

This study implies that women in the natural and biological sciences (and yes, surely other fields too) still face prejudices that can impact the opportunities they are given to work closely with professors, as well as limiting their access to jobs and starting them out at a lower salary. These factors can snowball over time, creating larger and larger gaps in career achievements and income as men capitalize on opportunities while women find it impossible to catch up.

via Ms.Magazine