From Claire Moore-Cantwell

Below are some graphs of gender data collected at AMP 2016, by Jesse Zymet and Eric Bakovic. Note that unlike previous reports of this type, participants are broken down by gender, but also by whether they are a student or a professor. Post-docs and early-career linguists in visiting positions were counted in the ‘student’ category, although this choice does not change the numbers much.

To start off, I would like to point out that these graphs do not contain information about racial minorities, because phonology (and linguistics in general) is still overwhelmingly white. The fact that there are not enough racial minorities at our conferences to even include in the tallies is a serious problem with our field that should not be forgotten about.

Preregistered participants at AMP 2016, which were about 90% of total registrants, consisted of 59 male and 56 female participants. 72 participants were students and 43 were faculty. (Thanks to Karen Jesney for these numbers!)

Overall, AMP 2016 had a fairly balanced set of presenters (“Talkers”), though male presenters were slightly in the majority. These numbers include the invited speakers: two male and one female.

Questions came more from faculty than from students by a small margin, and more from men than from women by a much larger margin.

Note that the difference between men and women was greater among students than among faculty (a difference of 18% vs. 9%), and the difference between students and faculty was greater among women than among men (10% vs. 4%).

Below is the number of questions from each demographic, broken down by talk. Talks are arranged from left to right in order of occurrence in the conference, and speaker characteristics are notated below each bar.

Note that this graph does not contain information about the order of questions asked for each talk. That information is represented in the graphs below. First, let’s consider the transitional probabilities between faculty and students:

‘S’ indicated students, and ‘P’ indicated faculty (‘professors’). The probability inside each circle indicates how likely that category is to begin the questioning. Each arrow indicates the transition probability (or forward bigram probability) between two categories of questioner. For example, after a student asked a question, there was a 53% chance that a faculty member would ask a question and a 47% chance that another student would ask a question.

Interestingly, students are much more likely than faculty to begin a question period, but faculty end up asking more questions. This graph yields some insight into why: After a student asks a question, students and faculty members are about equally likely to ask the next question. However, after a faculty member asks a question, there is only a 29% chance that a student will then ask a question. Once the floor transitions to a faculty member, it tends to stay with other faculty members rather than transitioning back to students.

There are a couple of possible reasons for this dynamic – first, it might be explicitly encouraged via actual exhortations for students to talk first and faculty to hold back. I don’t remember this actually happening at AMP, but a second possibility is that the group implicitly follows this ‘rule’ simply because it’s common in linguistics, and the group generally believes in it. Yet another possibility is that students ask the first question more often just because there are more students in the audience.

Below is a similar graph illustrating question asking dynamics among the two genders for which data was gathered.

Men and women are nearly equally likely to ask the first question, with only a slight advantage for men. However, after a woman asks a question the next questioner is more likely to be a man than another woman. On the other hand, after a man asks a question, the probability that a woman will ask the next question is quite low.

Finally, here is a graph illustrating the ‘flow’ of questioning between all four groups.

The same general flow of floor time towards faculty and towards men that the previous two graphs showed can be seen in this graph as well. Additionally, this graph reveals that the transition of floor time between female students and female faculty looks somehwat different than the transition of floor time between male students and faculty. For both genders, after a student asks a question the probability that the next question comes from a student of the same gender or a faculty member of the same gender is about equal. After a female student asks a question, female faculty members and other female students are about equally likely to ask the next question, and the same is true for male audience members. However, after a faculty member asks a question, the probability that the next question will be from a male student is much higher (29% after male faculty, and 14% after female faculty) than the probability that a female student will ask a question (0% after female faculty, and a mere 8% after male faculty).

I didn’t pay very close attention to attendee status (prof/postdoc/grad/undergrad), but there was definitely some skewing there, too. There was only one female senior prof in attendance at any point, and only on the first day; by contrast, there were 6 total relatively senior male profs in attendance (one came only for the morning of the first day, and another came only for the afternoon of the second day). There was one junior female prof and there were two junior male profs. The rest was a mix of postdocs, grads, and undergrads; I don’t know the exact breakdown, but I’d say there were more female undergrads than male undergrads and that otherwise it was close to half and half.

The conference was a regional one, with a friendly crowd and relatively informal atmosphere, and it was fairly gender balanced when I sampled the attendees towards the end of Day 1. (The missing data point is my own talk, for which I forgot to take down Q&A notes.)

There was at least one interesting observation to note. We started out with a pretty decent gender balance in the Q&A’s, with female question askers going first in both of the first two talks. Then, before the third talk, there was an announcement that explicitly asked graduate students to ask questions. I think many of the faculty took this to mean that we should allow graduate students to ask the first questions before jumping in. While this did definitely increase graduate student participation, which is a good thing, it has an interesting unintended consequence: the gender of the question askers started to skew towards male. In fact, throughout the entire conference, not a single female graduate student asked a question.

I suspect this effect might be due in part to reasons discussed before, in Joe’s post and comments, which is that women–especially young female academics–want to make certain that they have a really good question before asking, which takes longer and so they are less comfortable going first. At the beginning of the second day of talks, I specifically approached a dissertation-stage female graduate student to encourage her to ask questions, and she confirmed this anxiety.

Suggestions for how one might encourage more gender balance in graduate student questions would be greatly appreciated. I tried to take the direct approach in asking a specific student to participate, thinking that personal encouragement would boost confidence in the student, but I worry that in fact my intervention hurt rather than helped the situation (e.g., promoted more anxiety). I think it may also be good for students to see other female participants asking questions, but most of the female faculty (myself included) held back to allow graduate students to ask questions–seems like it’s a delicate balance to find.

[One final observation, from Eric Bakovic upon seeing this data is that “women speakers were overwhelmingly questioned by males, while questions for male speakers appear more balanced.”]

From Joe Pater.

My impression is that women are relatively well-represented in phonology, maybe more so than in other sub-disciplines of linguistics. A little piece of encouraging data on this comes from the 2015 Annual Meeting on Phonology, in which 18/27, or 66%, of the authors of oral presentations , including plenaries but not tutorials, were women (I was unable to identify the gender of one author). I’d be very interested if anyone has any better data on the representation of women in phonology, especially with respect to semantics, syntax and phonetics.

I also have the impression that women are under-represented in phonological discussion, that is, in question periods and other discussions at conferences, and I suspect this is part of a much broader phenomenon. A piece of data on this also comes from AMP 2015. Kie Zuraw kept track of the gender of question askers for 16 of the talks (all but the first two). 74/103 = 77% of the questions were asked by men, even though the audience was about equally balanced between men and women. Zuraw’s observations replicate previous observations by Stephanie Shih from the Computational Phonology and Morphology Workshop held July 11 2015 at the LSA Summer Institute, in which the audience was roughly gender balanced, but the question takers skewed male. Inspired by Shih and Zuraw’s observations, I kept track of the gender of question takers at the LSA Phonology: Learning and Learnability session January 7th, 2016, and got 26/29 = 90% male questioners, with what looked again to be a roughly gender balanced audience.

These results are not surprising – I think they are just confirming what we’ve all informally observed in conferences and elsewhere (though I have to say that I was surprised at how skewed my own count was). There is undoubtedly a complex set of conscious and unconscious biases underlying our behavior that’s producing this distribution, and presumably there is a literature in some field that has studied related phenomena. My current thinking is that there are some pretty obvious conscious decisions we can each make to change this distribution, and that simply talking about this phenomenon and raising awareness of it may well help to get a better representation of women in phonological and other academic discussion. I do hope this situation changes, because I’d very much to like to hear more of my female colleagues’ thoughts after talks.

Thanks to Ellen Broselow, Jenny Culbertson, Claire Moore-Cantwell, Magda Oiry, Stephanie Shih and Kie Zuraw for discussion.

Update Jan. 10th: Thanks to someone who prefers to remain anonymous for the following graph, which shows we still have some work to do in terms of representation of women as invited speakers. The ns in the graph are the total number of speakers.

Update Jan. 12th Sharon Peperkamp has shared “data for 53 conferences between 1993 and 2013, for a total of almost 300 invited and more than 2000 selected speakers, with 37% invited vs. 49% selected women”. It’s great to see that women are indeed well represented in phonology in general, and this makes it even clearer that we have work to do on the invited speaker numbers. Sharon has also contributed this plot of percentages over time.

The spreadsheet is available here, if anyone would like to further analyze it, make figures, or continue to keep track of the numbers. If someone wants to volunteer to coordinate this effort, please e-mail me, and I’ll put that information here. As Rachel Walker has pointed out to me, conferences could also keep track of diversity statistics themselves – apparently she’ll be bringing this up with the AMP board. If this happens, we could keep a consolidated public record here.