A Manifesto to Cite 50/50

I recently came across Women Also Know Stuff. I think it is a great initiative that helps to slowly combat systemic and structural inequality. They point to many female scientists in most social sciences and I wondered whether I could find a similar program in computer science. The answer was no because apparently we first need to get women into computer science. I would still love to see #WomenAlsoKnowComputerScience on twitter, alas the search results are empty. It is not that I don’t know great female compute scientist but maybe they lack exposition which makes it all the more harder to convince women to join the field.

What I thought could help would be a larger exposition in scientific citations. I will need to go a bit off-topic to explain my thinking but bare with me. Citations produce scale-free networks (Klemm & Eguiluz, 2002).

Comparison of a random network and a scale-free network. The scale free network shows super connecting nodes in grey. Taken from wikipedia.

That means that a few super-connected nodes (so-called hubs) take up almost all the citation. In general, if we as scientists need a citation to underline a concept, we are much more likely to end up citing such a super-connected node. What that means is that highly cited scientists will get even more cited and less cited scientists remain so. That is even if their science was better. Network effects (or economies of scales) ensure that not necessarily the best science is cited the most, but usually the one preserving the status quo (Wang, Veugelers, & Stephan, 2017). But the effect is even stronger than that. The big names (not only the citations) dominate the field to such an extend that alternative explanations favored by other scientists are locked out of the discussion until such a star departs from the field (Azoulay, Fons-Rosen, & Zivin, 2015).

So where does that leave us with citing female scientists? They are at a triple-disadvantage:

  1. They have been structurally excluded from the discipline
  2. They (usually) don’t have a big name so their citation counts don’t increase
  3. As there are no role models young women may not take up the field

However, and this is what I would like to stress most, it is not the quality of their research. Now, if citations are usually not awarded for merit only but mainly due to structural reasons, why not use them to start shifting the scales today such that in some day in the future women are equally represented in this field (and in many others) such as the statistical distribution of people would predict.

The Manifesto to Cite 50/50

Making a citation to underline a concept does not require us to only cite that one citation that we always use. We can vary whom we cite and we can choose to cite female scientists as well.

  • Citing a female scientist does not cost us anything in our career but it may help build those careers that eventually will bring equality.
  • Citing a female scientist when we only have male scientists at our hand makes us critically reflect our own field and possibly help us to engage with research more deeply to find female scientists.

We probably won’t reach a 50/50 quota any time soon in our citation lists but maybe we can start climbing towards it. I admit I am not there yet and I haven’t done this for any publication I produced yet, but I am of a mind to change this. Maybe you would like to contribute as well? Change is hard and so my first goal is to have at around 50% of publications having a female co-author (though first author would be preferable). I am sure I will fail miserably to reach that goal in the next few publications I make. But yesterday I sat down and tried to find a few women in the field that I could cite and it was surprising how relevant their research was and shocking how I barely heard of any of them (except those who despite the odds managed to become a big name of their own). I think that in the long-term this practice will also make me a better and more engaged scholar that (at least sometimes) manages to look beyond the in-group in which my work is circulating.

Computer Science and more

Now I know I specifically focused on computer science but probably such an attempt should not be confined to one discipline. It should be a truly interdisciplinary endeavor.

Azoulay, P., Fons-Rosen, C., & Zivin, J. S. G. (2015). Does science advance one funeral at a time? National Bureau of Economic Research.
Klemm, K., & Eguiluz, V. M. (2002 NaN). Highly clustered scale-free networks. Physical Review E. APS.
Wang, J., Veugelers, R., & Stephan, P. (2017 NaN). Bias against novelty in science: A cautionary tale for users of bibliometric indicators. Research Policy. Elsevier.