If You Don’t Like People, Then You’re Not a Woman, and Other Theories on Why Young Women Don’t Consider Tech Jobs

I hope I look back on this post in 10 years and ironically fist-bump my fellow lady coders.
Publish date:
August 4, 2011
career, stereotypes, women

Newsflash: There are many, many more men in the technology industry than women.

From the tippy-top of companies down to the entry-level coding jobs, the women are just hard to find. No, this disparity isn't actually news -- it's one of the mostdebatedtopics on tech blogs all over the Internet. Just this year, the percentage of new Computer Science and Computer Engineering graduates showed a continuation of the dismally low 20-year trend.

(Source: Computing Research Association) That’s 13.8% of undergraduate CS degrees, which is a 7.25 Males to 1 Female ratio, right in line with the sea of dark suits on the C-SPAN channel: the US Congress, where 76 of 541 members (14%) are female.

A lot of companies are flabbergasted by the issue and genuinely want to hire more women. But instead of wondering offensively where the hell their female applicants are, they’re thinking through the problem and asking industry leaders to understand the issue. It’s that 7.25:1 ratio, man. There are literally so few women in the field that it’s ridiculous to ask questions like “Where are all the women in startups?” or “Why Aren’t More Women in C-Level Positions?”.

Employers, I’d really like there to be more female applicants, too, but there literally aren’t enough of them to go around. And of course, not all of that tiny 13.8% pie slice goes into the workforce -- some women go to grad school, some decide not to use their degree, and some decide to start a family right away. In fact, I’ve never seen a ratio as low as 7.25 males to 1 female ratio at my jobs. Somewhere in the 10:1 range feels likely.

But there could be some good news on the horizon.

True Child, an organization that researches gender norms (awesome!), recently released a report called “Why Girls Opt Out,” attempting to explain why young girls have a strong aversion to Science, Technology, Engineering, and Math (STEM). After reviewing the numbers and interviewing young girls, its concludes that young girls equate math to masculinity, and girls at that age want to do everything in their power to be seen as feminine and normal.

True Child states very plainly that the logical equation in girls’ heads must be Math = Masculine, Me = Female, therefore, Math != Me. I think STEM fields seem masculine not because of their subject matter, but because they’re not social in nature, where women are, by definition, told to be social.

If we go to the other extreme and think about fields that have equal or a majority of women (literature, biology, history, politics, psychology), these fields speak the natural language of people: actions, thoughts, wants, desires, and needs. Subjects removed from what it means to be a person, like physics problems, chemical equations and software code, are fundamentally abstract. They're full of symbols, trusted theoretical systems, and things we never heard of as children. It’s a completely foreign system that you need to learn on faith in order to use it, and it’s probably very hard for young girls to see the social benefit to its investment.

I've came up with a theory last year, which is an amalgamation of other research conclusions, personal accounts and my own experiences. It's called: "If You Don't Like People, then You Are Not a Woman," and it's based on these two assumptions:

1. If you work in tech, then you don’t like people.

Seventies, 80s, and 90s Hollywood stained our culture to stereotype people who work in technology as socially inept (think "Revenge of the Nerds," "Office Space," "Pi," and every single movie with a person hovering over a terminal). Career propaganda works. Know anyone who went into the military after seeing "Top Gun" or any of the other hundreds of movies depicting infallable character, leadership, strength and intelligence?

2. If you don’t like people, then you are not a woman.

Don’t believe me? Think about it, and please try to refute this statement. I've thought around every single angle, and I can't beat it; It's obligatory, and true. We are trained to be social animals, and, when we are not well-liked, well what the hell are we?! We send the Christmas cards, we organize the birthday parties, we take care of our sick family members, we wish newlyweds luck, we write on each other’s Facebook walls when we have big announcements. A woman is not a woman if she is not social.

Therefore, if you work in tech, you are not a woman.

Simple theory, and it starts with the kids, just like the TrueChild study says: Most young girls aren’t taught to explore a breadth of career opportunities to understand how STEM studies turn into jobs that help people.

Luckily, this is changing in the medical and chemical areas. In the year 2010, Medical school graduates were 48 percent female, which speaks volumes. Soon-to-be-Dr. Reavey cleared up what it's like for female researchers here on xojane, and lots of kids today know that scientists tell jokes, talk to people, and, most importantly, solve problems. (Thank you, Sesame Street, for Beaker and Bunsen.) All of these messages towards young girls teach them that even though biology and chemistry are difficult, and sometimes too abstract to understand, the end-result of their studies has an incredible social utility, so they stick it out and keep working on it.

But coders? No, we like to portray them as autistic. Take AOL's marketing pitch for their new Editions iPad app. I spared this guy's face from yesterday’s screenshot out of my own embarrassment for him.

There are so many detrimental stereotypes in this short marketing pitch that I have to list them with bullets:

  • AOL thinks their first typical user of the app is a coder, implying that coders are the early adopters who are the hardest-to-win-over. Whatever. 1
  • This person "laughs in the face of algorithms", to which I immediately laugh in the face of such a statement. 2 → He is intimidating, controlling, poweful.
  • He "can easily log 14-hour days writing code". → He is a robot.
  • He can't remember appointment dates. → He is not a compassionate human.
  • This guy can't even shave or put on a collared shirt for a photo shoot. → He does not interface with other humanoids on a regular basis.

Right? Wrong. This guy is probably a perfectly normal person who codes for a living, which actually means he mentors his coworkers every now and then, asks his fellow designers or project managers questions for more insight on what's he working on and delegates ideas to other people on how to improve things like ALGORITHMS. Nobody works in a vacuum in tech; that is a complete myth.

For our young girls, it’s all about the perception that tech is a social industry. I think movies like The Social Network are helping to slightly alter our earlier dork-cinema-wave. 3 If Zooey Deschanel were to star in an Ada Lovelace flick as rumored, we would be able to walk into any Computer Science lecture hall and see a bunch of smart chicas hunched over some pastel-colored terminals in the next 10 years!

Do me a favor. If you know any impressionable youths, girls or boys, pull them aside and read all the outstanding benefits about working in tech. Need talking points? See Twitter Engineer Lisa Phillips' outstanding blog post with a bulleted-point list for a refresher. Tell your young impressionable youths about what it means to work, and what solving problems means for other people and exactly how normal all your coder friends are (relatively speaking). Remind them what it means to a person in the technology industry.

Until then, I’m going to have to keep blogging about this.

1 Not true -- they’re the most likely to have access through connections they have in the industry, and they’re the most likely to give an app free press because many of them have their own blogs and tweet.

2 Algorithms aren't some three-headed beast that sits in front of the dungeon of knowledge. You don't laugh at algorithms; you plan new or improve existing ones. Waiting in line at the grocery store is an algorithm. The circulation of clean and dirty trays in a cafeteria is an algorithm. The order in which you shower, get dressed, put on makeup, eat breakfast, and leave the house in the morning is an algorithm. It's just a careful execution of events.

3 Sure, I could do without the scantily-clad females during the coding session scenes, but that overdramatization of how many females were in Mark Z's coding class at Harvard actually does help! Movie directors, please keep adding more female bodies in lecture halls than the 7.25:1 ratio I mentioned before!