Your go-to analysis of this data is that there's a grand conspiracy of misogynistic discrimination? I'm finding it really hard to imagine anyone deciding not to cite a paper on the sole basis that they saw a female name in the authorship.
Edit: You added your second sentence after I posted this (that's fine, I do the same sometimes)
And indeed, his slides agree with you. There appears to be no substantial bias towards citing recent work by women. So that doesn't really counter what I said except in the sub-case of older papers.
That sub-case could easily be explained by there being a bias towards citing older work of people considered to be the key people in a field (I would expect so), and a bias against considering women to be the key people in the field. That second bias could be explained by a bias against considering people with female names key people in the field, or it could be considered a bias against considering people with fewer papers (see data/previous arguments for this) key people in the field, or both.
This is a giant unsupported hypothesis. I don't pretend otherwise. It seems to be just as supported as the hypothesis that women are just worse at physics then men though.
https://www.cfa.harvard.edu/~srugheimer/Women_in_STEM_Resour...
Look up the Implicit Association Test for a good example of this. I've taken it, and while it wasn't exactly a shocker to me to discover that I have an unconscious bias against black people (I grew up in an area that had maybe 5 of them, and despite my very liberal upbringing, our society and culture still label black people as "other" and "dangerous"), it was eye-opening to be able to see the effect so clearly.
Psychology has too long been a field where people draw a conclusion first and then create some experiment or hypothesis to support it. It is only now with the advent of analytics that we are shedding light on this quackery.
[1] http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=22...