btrmt. lectures

The Scientific Ritual


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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 on
  • Problems with
  • p-values — the technical companion: Fisher, Neyman-Pearson, the
    hybrid mess
  • The trap
  • of scientific evidence — on the “no evidence” tension and the
    homeopathy/parachute paradox
  • Everything
  • is ideology — science as one belief system among several
  • In praise of the
  • sage — other ways of knowing; the MD/PhD distinction
  • Scientific
  • fact — on what science actually does
  • The value of
  • ritual — ritual as a knowledge-production strategy
  • Meditation — on the
  • dinner-table meditation example
  • Beyond
  • System 1 and System 2 — on Kahneman’s dual-process framework
  • The placebo
  • effect — on why “works for some, not for others” is a feature, not a
    bug
  • Grit
  • positive-psychology critique
  • Overengineering
  • calming down (lecture) — the broader positive-psychology audit
  • Bias is good
  • (lecture) — the cognitive-bias series
  • Life 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
    • crisis
    • American 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 Science
      • Philip 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”
        paper
      • Andrew Gelman, Why
      • I don’t like so-called Bayesian hypothesis testing
        p-values, Bayes factors,
        and software
        • Wikipedia: p-value, Bayes factor
        • Ronald A. Fisher (1925), Statistical Methods for Research
        • Workers — where the 5% threshold appears as an illustrative
          example
        • Harold Jeffreys (1939), Theory of Probability — where the
        • Bayes-factor thresholds (BF > 3 substantial, BF > 10 strong) come
          from
        • JASP — 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 support
          • Hagger et al. (2016), A
          • Multilab Preregistered Replication of the Ego-Depletion Effect
          • Bargh, Chen & Burrows (1996) original elderly
          • priming paper; failed Doyen
            et al. (2012) replication
          • Brown, Sokal & Friedman (2013), The Complex
          • Dynamics of Wishful Thinking — demolishing the 3:1
            positivity ratio
          • Carol 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 Slow
            • Stephen J. Gould, Adam’s
            • Navel and Other Essays
            • Yann Martel, Life of
            • Pi
            • Bill Mollison, Permaculture: A Designer’s Manual
            • Other
              • Richard
              • Dawkins on militant atheism (TED) — the “evidence vs. faith”
                framing
              • Reform efforts: preregistration, open data, multi-lab replication consortia
              • (e.g. ManyLabs)
                ...more
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                btrmt. lecturesBy Dorian Minors