Some weeks ago we published some visualizations of the data of the attendants at the DHd 2016 that we take from the program of the conference. The organization of the conference liked what we did, and while speaking with them, I pointed out that I had the feeling that significantly fewer women were at the conference if compared to the Spanish DH Conference 2015 (in which the gender distribution of the speakers were more or less 50%). So the organization gave us more data about the participants, of course anonymized, and for that we are very thankful.
So, let’s start with the basic gender question. Was I supposing correctly, that there were more men than women?
Yes I was, although I would have said that the difference was going to be greater. Another aspect that one cannot presume in the conference, but that it has to be answered in the registration steps, is about the academical level. How was the proportion of predocs, Docs and Professors at the conference?
The majority of the people are bellow the PhD title (I would have expected fewer), and only around 10% are Professors. Now, let’s mixed this two kind of data and see how many women and men were in the different academical levels:
Of course both genders decrease in higher levels in total values. But what happened if we see the proportions of women and men in the different levels?
Now, that is interesting. As predocs, around 60% of the the people at the conference were men; this number goes up until 65% at the PhD level ant it increases until 70% at the Professor level. Of course the amount of female in the different groups decreases in a direct way. What a pity that we don’t have more data about the students in earlier stages of the University (Master, graduate…), because I guess (and this is only me guessing) we would see that at the beginning of their degrees, the majority of the students are women and probably at the Master level both genders represent the same proportion.
And now let’s move to the intersections between gender and places: countries and cities. How was the proportion of male and female for this countries? For this visualization I only took the countries that had more than two people at the conference for obvious reasons. The vertical axe represents the proportion of men and the horizontal the proportion of women; the size of the bubble represent the total amount of participants. For example, from USA were two people (one woman and one man):
We have already seen that the majority of the participants came from Germany, and comparing the almost 400 Germans with 2 people from USA doesn’t make much sense. So let’s go a step deeper and see how was the proportion of gender per city at the conference. For that I have only taken the cities that have more than 4 attendants. Let’s remember that the cities might have different institution and companies present at the conference, so the next visualizations don’t fit exactly the situation at the Universities.
Here we see that there were more women than men from some cities like Marburg, Düsseldorg, Paderborn, Graz or Bern. Sadly the overlaping hides some of the cities in middle and at the top left. So let’s visualizate it as bars: