Gender Inequality In Education: Datasets And Sources

Returning to the subject of education and gender, this post is a bit more about using the data available to you to make informed decisions when running ICT4D projects. For some, these will be painfully apparent; for others, perhaps a little less so, so I am essentially writing this post for the latter group. Experts and data-savvy types, avert your eyes.

It is probably best to frame this around a particular question or conjecture, so I am going to assume that one of the potential pathways for greater employability for women in some countries and in particular greater employability in "innovative" fields is research. That essentially a good barometer for greater inclusion is the percentage of women participating in research oriented fields. This could include women in independent, private, NGO or government run research centres or think tanks, and the more humble variety where I ply my trade some of the time, higher education. The former, almost without exception worldwide, pays better than the latter. But that is besides the point (or is it?). Our real focus here is on exploring the pathways of research that I am not even sure are real. I mean I know research is real, but I am not sure it is a legitimate or accurate barometer for any sort of greater inclusion overall.

So the hypothesis I am running with here is that there have some gains in women's participation in higher education worldwide and that some of those gains might translate to greater participation in research oriented sectors. Some parts of the conjecture are supported in evidence. There has indeed been an uptick in both sexes in higher education.

Good on you, world. But clearly the problem here is that this data isn't disaggregated. We don't know how this breaks down according to gender. OECD has a good datastore for this sort of thing. Good on you, Canada.