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Comment by Andrew T. Levin

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Economist, Professor at Dartmouth College and NBER Research Associate
And the marginal likelihood means under each hypothesis, what's the probability that we would observe the pandemic starting in Wuhan.
AI Verified source (Jul 24, 2024)
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Bayesian analysis is the right framework for settling the COVID-19 origins question
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AI Verified Relevant: on the Hoover source page, this quote appears in a presentation specifically devoted to "A Bayesian Assessment" of COVID-19 origins, and the speaker uses it to explain a core Bayesian step—comparing the marginal likelihood of observing the outbreak in Wuhan under each hypothesis. In context, that makes a stance on the statement substantially more likely and determinable. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified Relevant: in the source context, Levin argues Bayesian analysis is the appropriate way to compare the two COVID-origin hypotheses, and this quote explains a core Bayesian step—evaluating the likelihood of observing the outbreak start in Wuhan under each hypothesis—so it substantially signals support for Bayesian analysis as the framework for resolving the origins question. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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AI Verified The quote is part of Levin’s explanation of the Bayesian method (“the marginal likelihood means...”), and the source page makes his stance explicit: Bayesian analysis is “good for evaluating two competing hypotheses” and, for the COVID-origins question, “the way to go.” ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified The quote frames the issue as comparing, "under each hypothesis," the probability of observing Wuhan as the start, which is a Bayesian setup. In the source context Levin makes the stance explicit, saying Bayesian analysis is "good for evaluating two competing hypotheses" and that for COVID origins, "Bayesian analysis is the way to go"; "settling" is a mild inference from that broader endorsement of the framework. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago

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AI Verified Verified: the Hoover Institution event page for the July 24, 2024 seminar includes this exact sentence in its transcript at lines 518-519, and it appears within Andrew Levin’s uninterrupted remarks; Bob Hall speaks only at the next line, confirming the attribution and that the source URL contains the quote. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
AI Verified Verified: the Hoover transcript page for the July 24, 2024 event contains the exact sentence verbatim at transcript lines 518–519, and the transcript is attributed to “Andrew Levin,” i.e. the speaker in that section. An authoritative NBER profile gives his full canonical name as Andrew T. Levin, so the stored author is consistent, and the event date on the Hoover page is July 24, 2024. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 2h ago
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