On Square Pegs and Reasearcher Bias: Women in Engineering
I originally started this article with the intention of simply razzing eWeek.com for printing the latest in an endless series of articles asking why there aren't more women in IT/Computing/Engineering/Whatever.
But I think the topic has achieved such a broad level of mindshare that it deserves closer examination. A Google search today on the quoted term "why aren't there more women" returns over 16,000 hits - and you find that people are asking this question about science, engineering, rock and roll, blogging, gaming, advertising... the list gets quite long.
It's a reasonable question to ask for any of these fields, but I'm going to suggest that in nearly every case, the following inquiry is so severely biased as to make any conclusions useless.
An Unbiased Description
Let me give you an example of the kind of bias I'm talking about. Scientific American published Girls Equal Boys At Math in their 60-second web section while I was working on this post. The title refers to the results of a highly publicized study by Janet S. Hyde in Science. She took a look at current data in US primary education and concluded that boys and girls have parity in math achievement.
This type of news makes us all feel good - we don't want to hear that half of our children are getting short-changed on their education. But naturally, a study like this can't just stand on its own. The SciAm folks editorialize with:
From any angle, girls measured up to boys. Still, there’s a lack of women in the highest levels of professional math, engineering and physics. Some have said that’s because of an innate difference in math ability. But the new research shows that that explanation just doesn’t add up.
You don't have to be an expert in semantics to see the issue: the authors are hung up on the notion that if there aren't an equal number of women in these fields, we are doing something wrong. And really, they must be pretty concerned about it if we leap from a study on primary school math all the way to job discrimination in a host of fields.
If you read the literature of the last 30 years on this topic, you'll find a lot of the same explanations for the shortage of women in Science, Technology, Engineering, and Math (STEM). Proposed problems include:
- Problems in the education of girls and women - boys get more attention, girls need a different teaching style, higher education shortcomings, etc.
- Bias in education and/or society and/or family - girls hear the message about expected career choices.
- Lack of role models and mentors, leading to a chicken and egg problem.
- Direct bias against women in hiring and selection processes.
- Women find the workplace dominated by geeky men to be hostile.
The list goes on, and of course, most of it springs from anecdotal evidence - people poll their personal experience and suppose they have a unique view of the problem.
What Would Occam Do?
The scientific method is undoubtedly the greatest thing since sliced bread, but it is not without its problems. One of them is that researchers working on a problem are basically free to create hypotheses as they wish. The scientific method tells them how to test a hypothesis, but it has a lot less to say about how to form one.
In the case of our Women In STEM problem, every researcher in the world is free to start off with the inherent bias that something is wrong if women are not equally represented in these fields.
But what if we apply Occam's razor to the problem? Our interpretation of Occam's razor says to look for the simplest solution first. And that's just what Joshua Rosenbloom, an economist at the University of Kansas decided to do.
Follow the Money
Joshua found himself wondering why the National Science Foundation was spending $19M/year "to encourage mentoring programs, gender-bias workshops, and cooperative work environments" for women when nobody really knew why woman were actually dodging these nice jobs in the sciences.
So he decided to study the problem, and he did something remarkable. He asked women why they made the career choices they did. The results, as reported in this Boston Globe article, were interesting:
Rosenbloom and his colleagues used a standard personality-inventory test to measure people's preferences for different kinds of work. In general, Rosenbloom's study found, men and women who enjoyed the explicit manipulation of tools or machines were more likely to choose IT careers - and it was mostly men who scored high in this area. Meanwhile, people who enjoyed working with others were less likely to choose IT careers. Women, on average, were more likely to score high in this arena.
Personal preference, Rosenbloom and his group concluded, was the single largest determinative factor in whether women went into IT. They calculated that preference accounted for about two-thirds of the gender imbalance in the field.
Another study reported on in the same article came to some similar conclusions regarding self-selection in the workplace, and finished with what I consider the money quote:
"It's the opposite of what we'd expect," says Pinker. "You'd think the more family-friendly policies, and richer the economy, the more women should behave like men, but it's the opposite. I think with economic opportunity comes choices, comes freedom."
What Does It All Mean?
So what do we learn from this?
First, there are probably some differences between men and women that are either intrinsic or so endemic as to seem intrinsic. (Ask any well-meaning parent who has given their 5-year old son a Barbie doll only too see it instantly turned into a gun or cudgel.)
Second, when looking at a problem like this, try to find a simple way to do some analysis without injecting your personal ideas about how things ought to be.
Finally, does this mean we shouldn't try to attract more women into these careers? Of course not. It's still going to be a worthwhile exercise to ensure that our workplaces are attractive to all applicants, not just one gender. And any business can use more skilled workers. Eliminating half the pool at the door would be a shame.
But at the same time, we shouldn't be spending either dollars or angst trying to solve a problem that might not exist. And it's just possible that the lack of Women in Engineering is not a problem - it may be a free labor market working exactly the way we want it to.