Science feels like the most reliable thing we have. The opposite of belief. But it’s a belief system itself—a ritual, with all the failure modes that rituals have. And the receipts are right there in the replication crisis. Further reading The Scientific Ritual — the article this lecture is based onProblems with p-values — the technical companion: Fisher, Neyman-Pearson, the hybrid messThe trap of scientific evidence — on the “no evidence” tension and the homeopathy/parachute paradoxEverything is ideology — science as one belief system among severalIn praise of the sage — other ways of knowing; the MD/PhD distinctionScientific fact — on what science actually doesThe value of ritual — ritual as a knowledge-production strategyMeditation — on the dinner-table meditation exampleBeyond System 1 and System 2 — on Kahneman’s dual-process frameworkThe placebo effect — on why “works for some, not for others” is a feature, not a bugGrit — positive-psychology critiqueOverengineering calming down (lecture) — the broader positive-psychology auditBias is good (lecture) — the cognitive-bias seriesLife is worse (lecture) — the previous episode; a worked example of reading a literature References The replication crisis itself Open Science Collaboration (2015), Estimating the reproducibility of psychological science, Science 349 (6251)Wikipedia: replication crisisAmerican Statistical Association: Wasserstein, Schirm & Lazar (2019), Moving to a World Beyond “p < 0.05” Statistical ritualism Gerd Gigerenzer (2018), Statistical Rituals: The Replication Delusion and How We Got There, Advances in Methods and Practices in Psychological SciencePhilip B. Stark & Andrea Saltelli (2018), Cargo-cult statistics and scientific crisis, Significance 15 (4)Andrew Gelman & Eric Loken (2014), The Statistical Crisis in Science — the “garden of forking paths” paperAndrew Gelman, Why I don’t like so-called Bayesian hypothesis testing p-values, Bayes factors, and software Wikipedia: p-value, Bayes factorRonald A. Fisher (1925), Statistical Methods for Research Workers — where the 5% threshold appears as an illustrative exampleHarold Jeffreys (1939), Theory of Probability — where the Bayes-factor thresholds (BF > 3 substantial, BF > 10 strong) come fromJASP — the open-source Bayesian statistics software with default priors Specific replication-crisis casualties Cuddy, Wilmuth & Carney (2010) original power posing paper; Carney’s later statement withdrawing supportHagger et al. (2016), A Multilab Preregistered Replication of the Ego-Depletion EffectBargh, Chen & Burrows (1996) original elderly priming paper; failed Doyen et al. (2012) replicationBrown, Sokal & Friedman (2013), The Complex Dynamics of Wishful Thinking — demolishing the 3:1 positivity ratioCarol Dweck, growth mindset — replication concerns documented in Sisk et al. (2018) and Bahník & Vranka (2017)Angela Duckworth, grit — meta-analytic critique in Credé, Tynan & Harms (2017) Books cited in the lecture Daniel Kahneman, Thinking, Fast and SlowStephen J. Gould, Adam’s Navel and Other EssaysYann Martel, Life of PiBill Mollison, Permaculture: A Designer’s Manual Other Richard Dawkins on militant atheism (TED) — the “evidence vs. faith” framingReform efforts: preregistration, open data, multi-lab replication consortia (e.g. ManyLabs)
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