Carol recommended that I read Same Difference by Rosalind Barnett and Caryl Rivers for more thoughts on gender and culture and the differences between them. I haven't finished the book yet, but even in the first few pages, the book gave some really great ways to think about gender and culture. It's very well written and enjoyable to read, and definitely a great resource for this research project. It has proved to be very insightful and I'm not even all the way through!
Barnett and Rivers write, "We begin with the premise - which we support throughout the book - that people's behavior is determined more by situation than by gender." (p. 5) I think that this statement is the very essence of what we're trying to get at when we ask the difference between gender and culture. Culture is everything that surrounds you, and affects you - gender is only the set of stereotypes or cultural norms placed upon you depending on whether you are a man or a woman. Clearly culture is so much more than gender and it makes sense that people are affected more culture than gender.
They go onto explain the following, which I feel is consistent with our view on culture and gender:
"In the past, gender was all-important. Whether you were male or female determined your role in society: the way you behaved and the work you did. Under these circumstances, it's easy to assume that the reason men and women were doing different kinds of work was biological. If you look around a community and see only women weaving and only men tilling the soil, you are apt to conclude that the "cause" of this difference is that women are suited for weaving and men for tilling. But that conclusion would be wrong. Being female doesn't automatically give you a talent for weaving. Rigid cultural norms, not biology, are operating here. As gender roles loosen - as they have done in the developed world - women's and men's behavior reflects many forces: their gender, their individual talents and preferences, their personalities, and the situations in which they find themselves." (p. 5,6)
As I mentioned in a previous post, my grandfather grew up thinking that French was the man's language and English the language of women because that's how it was at home. Barnett and Rivers bring up the same idea, people learn things by what they see around them. No wonder people think that women can't do computer science - they've grown up with books, films, television, family, friends, and teachers telling them that nerdy, white guys are computer scientists.
This idea - that culture not gender is responsible for women's low representation in computer science - is supported throughout many other papers. Women in Computer Science: NO SHORTAGE HERE! by Mazliza Othman and Rodziah Latih, An Expanding Pipeline: Gender in Mauritius by Adams, Bauer, and Baichoo, and Gender Gap in Computer Science Does Not Exist in One Former Soviet Union Republic: Results of a Study by Gharibyan and Gunsaulus are all papers about the gender divide in CS in other countries. In these countries (Malaysia, Mauritius, and Armenia, respectively) there's a pretty even balance of women and men in CS. And of the reasons is that in these countries there aren't these "rigid cultural norms" - these stereotypes of who can do computer science.
Othman and Latih write, "While the lack of female role models or mentors in the field has been cited as a demotivating factor for female students in the U.S. and Europe, this is not a problem for Malaysian females. The dean of Faculty of CS & IT at the University of Malaya was a woman, and three out four department heads are currently women. Of the faculty lecturers, 61% are female as are 73% of the Ph.D. holders. Nine out of 12 associate professors are females. At Universiti Kebangsaan Malaysia, 66% of the lecturers at the Faculty of Technology and Information Science are female as are 40% of Ph.D. holders. Given this scenario, female students associated with these two faculties are clearly not lacking female mentors or role models, and are assured that pursuing a career in CS/IT is a normal, indeed, unremarkable option." (p. 4)
In Malaysia, where you grow up seeing women in CS, you grow up not even thinking that you wouldn't fit in or belong in CS. If you see lots of people like you doing CS, why shouldn't you be able to? And this is something that is missing in the United States. And it's a self-fulfilling prophecy. If women don't go into CS because there are no women in CS (and consequently they think they won't fit in), then there won't be a high percentage of women in CS, so more women won't go into CS!
It is very difficult to avoid falling into the trap of thinking that "women are suited for weaving and men for tilling." Unfortunately, a lot of researchers do fall into this trap. One of the most important distinctions in statistics is "correlation vs. causation." Just because it happens that there are fewer women in computer science, does not mean that women aren't in CS because they are women. Margolis and Fisher, Carol Gilligan (discussed at length in Gender Differences), and many other researchers mistake correlation for causation.