Scott Alexander on Bayesian analysis is the right framewor…

Scott Alexander

Author and psychiatrist

Saar brought up an interesting point halfway through the debate: you should rarely see high Bayes factors on both sides of an argument.

AI Verified source (Mar 28, 2024)

3mo ago

Policy proposals and claims

Bayesian analysis is the right framework for settling the COVID-19 origins question

votes Against

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AI Verified Relevant: in context, this is a methodological point about applying Bayes factors to the COVID-origins lab-leak vs. zoonosis debate, and the article uses that discussion to evaluate whether direct Bayesian/Rootclaim-style analysis can resolve the question. The surrounding section explains the point with COVID-origin examples, and the article later explicitly discusses whether this Bayesian approach works for settling the dispute, so a determinate stance on the complete statement is substantially more likely. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

AI Verified ai_verified because the quote is a methodological claim about weighing Bayes factors in the COVID-origins debate itself, so it is directly about using Bayesian analysis to resolve that question. In source context, the article treats this point as part of its extended assessment of whether Bayesian/Rootclaim-style analysis can handle COVID origins, including later discussion that explicit Bayesian analysis here may not work well for humans on this problem. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

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AI Verified The quote treats Saar’s Bayes-factor argument as an “interesting” and “good point,” but the source context is overall skeptical that formal Bayesian analysis is the right way to settle this case: the author says nobody really does full Bayes on “fuzzy real-world problems,” is “unsure that it’s a good strategy for a human,” and concludes Rootclaim’s direct approach “doesn’t work.” So the author’s overall position is more against than for the statement. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

AI Verified The quote is a criticism of Bayesian use here: if both sides generate very large Bayes factors, that suggests the analysts may have "bungled" the model rather than found a decisive framework. In the article’s broader context, the author says directly applying Bayes to this kind of COVID-origins question "doesn’t work" because the evidence is too hard to quantify, so his overall stance is against. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim?hide_intro_popup=true)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

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AI Verified Verified: the supplied Astral Codex Ten post is authored by Scott Alexander and dated 2024-03-28, and it contains the quote verbatim: "Saar brought up an interesting point halfway through the debate: you should rarely see high Bayes factors on both sides of an argument." The stored author, date, content, and source URL all match. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

AI Verified The quote appears verbatim on the cited Astral Codex Ten post: “Saar brought up an interesting point halfway through the debate: you should rarely see high Bayes factors on both sides of an argument.” The same page lists the post title, author as Scott Alexander, and date as Mar 28, 2024, so the stored quote, attribution, date, and source URL are correct. ([astralcodexten.com](https://www.astralcodexten.com/p/practically-a-book-review-rootclaim)) · YouCongress gpt-5.4-2026-03-05 · 3mo ago

replying to Scott Alexander