Here's my current (contrarian) dicta on how to identify credible science in a world where most apparent results don't replicate. (1/n)
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Testing the validity of experimental methods is underrated. As in Feynman's Cargo Cult Science essay. http://calteches.library.caltech.edu/51/2/CargoCult.htm … (2/n)
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Big effect sizes >> small but statistically significant effects. (3/n)
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Experimental results >> correlational results. (4/n)
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Diverse or weird animal models >> only standard animal models. (5/n)
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Old (pre-1980's) studies get bonus points for credibility. (6/n)
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Simple hypotheses >> conjunctive hypotheses. (e.g. "something in this organ causes this effect" is more likely than "this specific protein causes this effect"). (7/n)
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Evidence from fields like agriculture, where there's a competitive industry that doesn't get much publicity, gets bonus credibility points. (8/n)
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Evidence from multiple different scientific fields, especially if it includes evolutionary biology as well as molecular biology, gets bonus credibility points. (9/n)
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Accidental discoveries, and phenomena that emerge from unbiased/global screens or general-purpose datasets, get bonus credibility points. (10/n)
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Basically all these heuristics are attempts to compensate for motivated cognition and persuasive rhetoric. "I know you're trying to sell me on this claim, so I want evidence that's as independent of your opinion as possible." (11/n)
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