A recent PNAS article entitled "Heavy use of equations impedes communication among biologists" has caught considerable attention.
In my view, the problem is not so much with their observation (equation denser papers tend to collect fewer citations) as with their main conclusion:
"To maximize the scientific impact of their work, biologists should consider reducing the equation density in the main text of their theoretical articles."
These type of observational analyses (i.e. *not* randomised
experiments) are prone to confounding factors---a problem I am keenly aware of, as it almost ruined two years of my work.
Although the authors have controlled for a few confounders (article length, journal), there could well be other important ones.
For instance, it is well known that math papers have in general much lower citation rates than biological papers. So it might well be that articles on more mathematical topics tend to get fewer citations in general---regardless of the number of equation.
Because of this, I'd caution against dropping
equations in the hope of boosting one's citation count.
For what it's worth, my own anecdotal experience has been that math formulas can be appreciated if they are accompanied by intuitive explanations about their rationals. Ideally, the text should make sense to both mathphobes skipping over the equations and mathphiles skipping over prose!
Thanks to Hannes Röst for bringing this article to my attention.
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