Diversity and Women at NIME23

Dear NIME Community,

Thanks everyone for the amazing work towards the upcoming conference, I am making some research concerning diversity and women inclusion at NIME (and generally in electronic music) and I was wondering whether the chairs could be so kind to share, now that the selection has been completed, a few details regarding the application process with the wider community, namely numerical information that can be kept anonymous and shouldn’t be hard to extract, in short:

  • How many women have been selected as authors at NIME23?
  • What is the conversion rate, ie the relation between women applicants and women selected at NIME23?
  • How many white men whose first language is English have been selected as authors at NIME23?
  • What is the conversion rate, ie the relation between [white men && natural English speakers && applicants] and [white men && natural English speakers && selected] at NIME23?
  • How many non white men were selected as authors at NIME23?
  • What is the conversion rate, ie what is the relation between the number of applicants and the number of selected authors for non white men?

This would be enough for a first screening, although surely numbers can tell us a lot more if we look at them long enough :slight_smile:

With many thanks in advance, I am sharing this request on the forum (this is my very first post!) because I thought the quantitative info could be relevant data for the community to reflect upon.

Best wishes

Dr Eleonora Oreggia
Co-convenor Electronic Music, Computing and Technology BMus/BSc
Goldsmiths University of London

Ciao Eleonora,

Welcome to the NIME forum!

These are all very interesting questions and I’m also curious about the geographical/gender/etc distribution of the conversion rate. However, I doubt that the Chairs will be able to help you with this as CMT (the submission portal) does not collect information on gender, ethnicity, and authors’ native language. I think that trying to infer this information from authors’ names and affiliations is problematic.
We can have discussions about adding this information on the NIME 2024 submission form for statistical reasons to allow applicants to self-identify.



Hello Fabio,

Many thanks for your answer, it sounds reasonable to look into achieving this for next year. Perhaps for this year it is still possible to gather information about meta reviewers, how they are selected and whether they cover a reasonably diverse range in terms of gender and provenance.

On the other hand, the anonymous submission at NIME may not be necessary as, at least in my experience as a reviewer, in most cases even if the author’s name was hidden, it was highly possible as well as probable to recognise the identity through details contained in the paper, such as instrument’s name, location of some experiment/installations etc, and in some cases the name of courses and the academic institute where the author was teaching.

In this sense, I have often wondered whether it wouldn’t be more transparent to leave the author’s name in clear. Personally, I have refused to review some papers whose author I immediately recognised by the instrument’s name, even if I hadn’t worked with them in the past 2 years (which is the policy’s threshold) because I had studied with these people and considered them as friends.

I wonder whether this has happened to others and if the two years policy is enough to foster an impartial selection.

Best wishes

Hello everyone,

Those are two distinct, related, and equally important topics.

It is hard to access the data you mentioned as this was not requested during submission. Also, if we want to request that info (gender, first language, ethnicity, etc.), I would like to clarify to the authors why this data is needed and ensure the proper use of this information. Nevertheless, I’d love to check those statistics as well, and it could aid us in guiding initiatives to make the NIME community more diverse and inclusive.

For the blind or double-blind review process, I agree with you that in a community such as NIME, we often review papers that the authors can be easily identified, if not known at first glance. Also, open peer review is gaining traction, and the discussion is not new; check Pros and cons of open peer review | Nature Neuroscience from 1999!

I’m not sure if you are advocating for single-blind reviews or open (transparent) reviews. Still, for open reviews, students might feel intimidated or unconsciously inclined to accept the content without question when reviewing articles by established professors and researchers (the latter being also possible in a single-blind review situation). This can be especially harsh in a not-so-big community such as NIME.