The narrative on gender bias

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:

From gender bias to media bias? A thread on how our study looking at adult perceptions of children's pain got misconstrued. A reminder of the importance of taking media coverage with a grain of salt, reading original studies when possible, and guarding against confirmation bias. pic.twitter.com/m0sn8WKlnc

— Brian D. Earp (@briandavidearp) February 20, 2019

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 science¹ 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).

When media outlets get science reporting this wrong due to narratives biasing interpretation of data, don't be surprised when there's going to be skepticism over other science (e.g. climate change), economics, or politics.

— Rabbi Josh Yuter (@JYuter) February 21, 2019