Hilariously, this paper does NOT conclude what antimaskers and antivaxxers think it does, quotes cherry picked by #COVID19 contrarians and antimaskers notwithstanding. 1/https://twitter.com/commieleejones/status/1391754136031477760 …
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Hilariously, one prominent #COVID19 crank loved the paper—loved it!—at first. 3/https://twitter.com/MLevitt_NP2013/status/1392805311434477570 …
Then @MLevitt_NP2013 actually read the paper. Suddenly he didn't like it so much. (He was cited as a negative example of antimaskers.) This lead him, a Nobel laureate, to "punch down" and despicably attack the lead author, a graduate student. 4/https://twitter.com/MLevitt_NP2013/status/1393600374108418048?s=20 …
This just goes to show that reading the whole 18-page paper, rather than just the abstract and the quotes carefully cherry picked by antimaskers and antivaxxers, easily demonstrates that the paper does not at all say that antimaskers have a more rigorous approach to data. 5/
Rather, it shows that using the tools of data analysis and science does NOT inoculate one from quackery and crankery, an important lesson. 6/
Another important lesson is that more data and media literacy is not the primary way out of the #COVID19 bad science and pseudoscience infodemic. Antimaskers have a high degree of data literacy (of a sort, as the authors put it) and use it to spread doubt about public health. 7/7
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