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Comment by Scott Alexander

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I was following along at home, and I definitely bungled this point; I had some high Bayes factors on both sides. I adjusted some of them downward based on Saar’s good point, but how far should we take it?
AI Verified source (Mar 28, 2024)
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Policy proposals and claims
Bayesian analysis is the right framework for settling the COVID-19 origins question
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AI Verified The quote is directly about applying Bayesian factors to competing COVID-origin hypotheses, and in context it is presented as part of the article’s evaluation of whether this Bayesian approach can handle the question. The surrounding section says the author had to revise Bayes factors because the method seemed bungled, and the article later concludes that directly applying Bayes to this problem "doesn’t work" because the evidence is too hard to quantify, so a negative stance on the complete statement is substantially more likely than the alternatives. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified The quote is directly about using Bayes factors to assess COVID-origins evidence, so it is on the same issue as the statement. In source context, the author presents this as part of a broader discussion that full Bayesian analysis on fuzzy real-world problems is hard, easy to bungle, and perhaps not a good human strategy here, which makes a determinate stance on the complete statement—at least skeptical/abstaining rather than straightforward endorsement—substantially more likely. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim?hide_intro_popup=true)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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AI Verified The quote itself is skeptical about Bayes settling this issue: he says he had "high Bayes factors on both sides" and asks "how far should we take it?" In the article’s broader context, he says full Bayesian treatment of fuzzy real-world problems is too hard, and concludes that Rootclaim’s direct Bayesian approach for COVID-origins-type questions "doesn’t work." So he most likely opposes the statement, even though he is generally pro-Bayesian reasoning in the abstract. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified Against: the quote says he "definitely bungled" the Bayes-factor point and asks "how far should we take it?", which implies doubt that Bayesian analysis straightforwardly settles this question; in the article’s broader context, he also says Rootclaim-style direct Bayesian analysis of COVID origins "doesn’t work" because the evidence is too hard to quantify. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago

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AI Verified The quote appears verbatim in the Astral Codex Ten post “Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate,” and the page byline credits Scott Alexander with the date Mar 28, 2024. The exact sentence appears in the source text, so the quote is authentic, correctly attributed, and present at the provided source URL; the stored author, date, content, and source are consistent with the source. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified The quote is authentic. The fetchable Astral Codex Ten page for "Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate" lists Scott Alexander as the author and Mar 28, 2024 as the publication date, and the exact quoted sentence appears verbatim in the article body at lines 331-333. No correction is needed. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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