I've been keeping an eye on Brian Earp's work for years, as he's got a very nuanced approach to things. Recently one of the papers that he was first author on, Gender Bias in Pediatric Pain Assessment, got picked up by quite a few prominent media outlets who consistently misreported the paper's results to fit the politically narrative. Here's a thread he put together on how to better interpret the results:
I think he's appropriately cynical, as per this recent update that if the study had found the opposite results those too would likely have be interpreted also to fit the narrative - and thought more about how certain elements of current theory might be unfalsifiable.
A few years back Earp authored The unbearable asymmetry of bullshit, which looks at how activists can push false narratives in science so I don't think he's exactly been caught off guard that certain things might have been distorted. (I do sort of wonder if he's come to regret having earlier referred a journalist to that boring predictable ideologue Kate Manne though).
It seems to be a bad week for the New York Times's credibility. In another article asserting sexism it seems that a study which is likely fraudulent / non-existant was cited. It was soon acknowledged by the journalist who wrote the piece as a solid critique but a number of days later now the article still remains uncorrected. (EDIT: the journalist in question has now mentioned a correction though my cached copy still shows the error). (It's been a pretty bad week in general for politically correct narratives re: sexism - i.e. someone looking into research on whether blind auditions improved the hiring of female musicians - perhaps the most commonly-cited paper I've heard suggesting that blinding people to the identity of those they're evaluating - found that the figures supposedly supporting this were at least ambiguous and in part in conflict with the narrative).
