> Compared to double-blind reviewers, we saw about a 22% decrease in the odds that a single-blind reviewer would give a female-authored paper a favorable review, but due to the smaller count of female-authored papers this result was not statistically significant. In an extended version of our paper, we consider our study as well as a range of other studies in the literature and perform a “meta-analysis” of all these results. From this larger pool of observations, the combined results do show a significant finding for the gender effect.

This sounds like p-hacking. They're testing for significance, and when that fails, use the same data again along with other data to achieve significance. Am I mistaken?