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Health Care

Florida Judge Makes Inconvenient Student-Masking Data Disappear

( igoriss/Getty Images)

In the COVID era of debate, appeals to authority have gone viral. I recently mentioned one example: Politifact rated “false” the claim that student-masking “lacks a well-grounded scientific justification.” One might assume that Politifact cited data showing that masks on students slow viral spread, improve health outcomes, and have minimal effect on learning and socialization. Nope! All it could do was appeal to the authority of the CDC and like-minded researchers who offered such ringing endorsements as, “Mechanistically, it is a little hard to believe masking would not have some effect.”

Last week, as part of his ruling against Florida governor Ron DeSantis’s mask-optional policy, a state judge engaged in perhaps the most egregious appeal to authority I have seen so far. By way of background, the governor’s order banning mask mandates had cited “a Brown University study [that] analyzed COVID-19 data for schools in Florida and found no correlation with mask mandates.” That is indeed what the study found. Keep that in mind.

The Brown University study’s lead author Emily Oster and her co-authors did include several disclaimers in their paper about the limitations of observational studies — e.g., “we cannot make strong causal claims,” “we [could] not control for community mitigation practices,” and so on. That’s all fine. Everyone agrees that a randomized controlled trial would be more definitive, but for now this is the best we have.

The authors went too far, however, when they suggested in their summary that students should wear masks anyway:

We would emphasize that in general this [other] literature suggests in-person school can be operated safely with appropriate mitigation, which typically includes universal masking. It would be premature to draw any alternative conclusions about this question based on this preliminary data.

This implicit endorsement of masking may or may not be justified based on other evidence, but it indisputably does not follow from the data analysis in their paper. The authors’ remarks here are analogous to “dicta” in a judicial opinion — side observations that are not part of the actual holding.

Now back to that Florida judge. In his decision, he uses the authors’ dicta not merely to cast doubt on their findings, but to deny that their findings even exist! He delivered his opinion orally, so the text is choppy, but here is the relevant part:

This study doesn’t say masking is not effective. In fact, it recommends universal masking. . . . [DeSantis] said that [the Brown report] had analyzed Covid data and found no correlation with mask mandates. If that’s true, why did the Brown report recommend that universal masking was still the way to go?

Now I don’t say that the governor has time enough to read a report that’s that thick, but his advisors do. So the statement in the executive order is just incorrect. That study does not find “no correlation” with mask mandates.

Remember, “no correlation” is exactly what the study found. However, this judge believes that appeals to authority are so powerful that they can make data disappear. Because the authors added some side comments about how they still favor masking, the judge literally cannot believe that their data analysis tends to support the opposite position. In this legal proceeding, the word of the authorities trumps actual evidence.

The danger here is underappreciated. Prior to COVID, there had been a movement to “democratize” science in the sense that data and code-sharing should be the norm, and that working papers could receive informal peer review from just about anyone on the Internet. The point was to avoid having a priestly class that could make unquestioned pronouncements about The Science. Now the priestly class is back with a vengeance. People who disagree with the public-health establishment are widely censored, “but the CDC says . . .” has become a mic-dropping argument, and judges are so enamored with expert authority that they cannot even comprehend the existence of contrary data.

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