Where are all of the "binders full of women"?

Like Mitt Romney in Tuesday night's debate, we were wondering, where are the "binders full of women" applying to work at FloatingSheep?

So, in typical FloatingSheep style, we found a very talented woman to make a map.  Montse Compa, the Humboldt State University student that produced a map of Big Bird tweets during the last presidential debate, helped us answer this question:

So, despite the many memes devoted to binders full of women and the news coverage of these "viral" memes, there are no women actually in binders. Women live in the material world. But just as Mitt Romney is able to represent women as being in binders, there are plenty of women (and people who like women) on Twitter producing counter-representations, as UK Geography grad student Ryan Cooper discovered with this map of tweets referencing the latest presidential debate screw-up.

SheepCamp 2012: Monica Stephens on the Gender Biases of the Geoweb

Monica Stephens' talk is titled Guns, Germans and Strip Clubs, and focuses on the gender bias within the geoweb and how it falls short of the rhetoric of inclusiveness that surrounds Web 2.0 applications. She looks specifically at the case of how "childcare" was not approved as map category within OpenStreetMap.

SheepCamp 2012, Monica Stephens from UK College of Arts & Sciences on Vimeo.

Monica's website: https://sites.google.com/a/email.arizona.edu/stephens/
On Twitter: @geographiliac

Wikipedia Demographics

We've written a fair amount about the geographic and linguistic clusters of Wikipedia authors but were reminded today (via New York Times "Room for Debate" forum") that there are plenty of other clusters along social and economic dimensions. Last year a survey of Wikipedia users was conducted which highlights some interesting fissures within the user group.



One of the most provocative findings (and the one highlighted by the New York Times forum) is that less than 15 percent of the regular contributors to Wikipedia are women. This really grabs one's attention but a closer look at the data report (see also here and here) makes us wonder if this figure accurately reflects the Wikipedia community. Some of the questions are:

• What was the sampling method used? Nothing is listed in the reports.
• What is the bias in the sample? For example, Russia and Russian speakers are the largest language and country groups represented in the survey even though the Russian section of Wikipedia is only the 8th largest linguistic group. (English, German, French, Italian, Polish, Japanese and Spanish are all larger).
• Did women have a lower participation rate then men in the survey? There were three times as many male respondents as female respondents. Does this accurately reflect the makeup of the Wikipedia audience? Given the unexpected results for language and country, it is not clear if there might be gender bias as well.
  

All this said, we find the question of an imbalance in gender participation very intriguing and important. We just don't know if the survey methods used are such that we can be confident in the magnitude of the highlighted differences. Anyone who can shed some light on this would be more than welcome to comment.