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Comment by Scott Alexander

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Either way, you’re accepting that a 1-in-10,000 freak coincidence happened. Isn’t it more likely you’ve bungled your analysis?
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 In context, this line appears in the article’s discussion of Bayes factors in the COVID-origins debate, specifically arguing that if both sides generate extreme 1-in-10,000 evidence, that likely indicates a bungled probabilistic model rather than a clean resolution. That is directly about using Bayesian analysis to settle the COVID-19 origins question, and it provides enough methodological signal that a stance on the complete statement is determinable. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified In context, this quote is part of the article’s discussion of Bayesian math in the COVID-origins debate: it argues that getting extreme Bayes-factor-style evidence on both sides is a sign the analysis may be mis-specified or error-prone. That is directly about whether Bayesian analysis is an appropriate framework for settling the COVID-19 origins question, and it makes a skeptical stance on that complete statement substantially more likely. ([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 treats extreme Bayes factors on both sides as evidence the model is probably wrong — "you've bungled your analysis" — and the article says full Bayesian reasoning on fuzzy real-world problems is too hard and that Rootclaim-style analysis "doesn't work." That implies opposition to Bayesian analysis as the practical way to settle COVID origins. ([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 treats competing Bayes factors as a sign the analysis is probably wrong — "more likely you’ve bungled your analysis" — and the article’s context says Scott supports Bayes in principle but not "full Bayesian reasoning on fuzzy real-world problems," concluding Rootclaim-style explicit Bayesian analysis on COVID origins "doesn’t work." ([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 supplied URL is fetchable and opens to an Astral Codex Ten post titled "Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate," credited to Scott Alexander and dated Mar 28, 2024 (lines 7, 13-15). The exact quoted sentence appears verbatim at lines 324-331, so the quote is authentic and correctly attributed. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified Verified: the exact quote appears verbatim in Scott Alexander’s Astral Codex Ten post “Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate,” and the page credits Scott Alexander as the author and dates it March 28, 2024. The quote appears in the article’s “The Math: Double Coincidences” section on the supplied URL. ([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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