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Comment by Andrew T. Levin

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Economist, Professor at Dartmouth College and NBER Research Associate
So rather than one complex Bayesian model with a hundred parameters in it, what we're going to do is break this question into smaller pieces. I'll call them bite-sized pieces. They're still pretty complex, but at least four smaller components where we can then systematically look at each of these.
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Bayesian analysis is the right framework for settling the COVID-19 origins question
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AI Verified Relevant: in source context, this quote is part of Levin’s explanation for why Bayesian analysis is "the way to go" for comparing the competing COVID-origin hypotheses, so it provides a clear stance signal on whether Bayesian analysis is the right framework for that 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 · 45min ago
AI Verified Relevant: in the immediately surrounding transcript, the author says Bayesian analysis is the way to compare the two COVID-origin hypotheses, and this quote explains the concrete Bayesian method he will use by breaking the question into components. That makes a supportive stance on the complete statement substantially more likely. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
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AI Verified The source context is explicit: he says, "If we really want to take seriously two competing hypotheses, then Bayesian analysis is the way to go." The quoted line about breaking the problem into smaller "bite-sized pieces" explains how to apply a Bayesian approach, not reject it, so the author is supporting Bayesian analysis as the right framework for this 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 · 44min ago
AI Verified The author is arguing within a Bayesian approach, not rejecting it: the quote says they will avoid “one complex Bayesian model” by breaking the problem into “smaller pieces.” In the source context, Levin explicitly says that for the two competing COVID-origin hypotheses, “Bayesian analysis is the way to go,” so the most likely position is support for Bayesian analysis as the proper framework here. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data?utm_source=openai)) · YouCongress gpt-5.4-2026-03-05 · 1h ago

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AI Verified The source URL contains a transcript of the Hoover event, and the exact quoted wording appears verbatim in that transcript, attributed to “Andrew Levin,” at lines 514–516. The same event page is dated July 24, 2024, and Dartmouth’s official faculty page confirms the speaker’s full professional name is Andrew T. Levin, so the attribution is correct. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 46min ago
AI Verified The quote is authentic and verbatim. The Hoover source URL contains a transcript in which the exact text appears, and it is attributed in the transcript to “Andrew Levin.” The same page identifies the event as his Hoover workshop on Wednesday, July 24, 2024. Dartmouth’s faculty page corroborates that this speaker is Andrew T. Levin. ([hoover.org](https://www.hoover.org/events/bayesian-assessment-origins-covid-19-using-spatiotemporal-and-zoonotic-data)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
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