The point is that you can't know whether they're rated differently (by different criteria) or actually different.
There are also lots of uncontrolled variables, such as the average woman submitting 1.4 reviews, while the average guy submitted only 1.3 reviews. This means the totals would obviously be off, even if everything were symmetric per capita, a fact not mentioned when the numbers are displayed.
Further, it's likely that the discrepancy in the number of reviews per capita submitted is a sign of some underlying sampling bias, which needs to be accounted for before we can really talk about the distribution of feedback.
I think this is a serious issue that needs addressing, but that's exactly why I feel it's important to object to bad math.
Right, and I'm not objecting to the conclusion "women in tech are described as being more aggressive than men in tech". What I'm objecting to is the logical jump from there to assuming that the difference is due to a bias in the "described" part rather than a bias in which people enter the tech field.
It's possible that there's a hiring bias, and reviews are being done fairly, but show biased results when naively studied because of the underlying bias.
This is what makes social statistics hard, and there are many faults in studies involving gender that fail to account for possible confounding effects in the data.