While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship positions, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.
The bare outline of our procedure is not revolutionary:
There are a couple of points that I think are particularly interesting though. The first is that, if the senior author of the paper is female, women are much better represented at all other positions. Computational biology is still worse than biology as a whole, but the bio representation jumps to nearly 50%, and the computational biology jumps to 40%.
Paradoxically, I think that the most encouraging news comes from a graph that shows the lowest female representation. Pubmed data only allowed us to compare biology and computational biology, but what about computer science? For this, we turned to the arXiv - a preprint server for quantitative fields. We can’t really compare this directly to the data from pubmed, but they do have a “quatitative biology” section.
There, quantitative biology has better representation than computer science. It’s still abysmal, don’t get me wrong, but it suggests that maybe, just maybe, biology might be used as an inroads to get more women into computational and quantitative techniques.
This gets at the question I’m most interested in - we know represenation is bad, but is there a way to improve it? These data aren’t conclussive by any means, but they suggest there’s a reason to try.
Now I just need to get a job where someone will let me experiment on (with?) undergrads…