Three results stand out. Ego depletion is the one effect where disclosure is near-universal: every usable top result we checked, including Wikipedia and every general-audience explainer site, mentioned the 23-lab failed replication. This is likely because the failure is so large (d = 0.04, a null result) and well-covered that it has become part of the effect's own story. Overconfidence, the planning fallacy, and the sunk cost fallacy sit at the opposite extreme, disclosed in none of the results we checked for any of the three. Per the ledger above, these three are not the same kind of gap: the planning fallacy has genuinely never been tested at large scale, overconfidence has a live methodological critique of its classic demonstration, and sunk cost actually replicated in Many Labs 1, so its 0% is a case of real, positive evidence going uncited, not a hidden weakness.

A reader searching any of these terms today would have no way to tell those three situations apart.

The broader pattern: outside of ego depletion, disclosure of replication concerns in the top search results is the exception, not the rule: under 20% for seven of the eleven effects checked, and never above 60% for any effect except ego depletion.

Methodology for this measurement

  • What we searched: the plain common name of each effect (e.g. "ego depletion willpower psychology," "anchoring effect cognitive bias"), with a second rephrased query per effect where needed to build a larger result pool, general web search.
  • What counted as a result: the top 15 organic (non-ad, non-video) results per query that were real general-audience articles, encyclopedia entries, or reference pages. Pages that could not be fetched or parsed were excluded from the denominator rather than counted as non-disclosing (marked "unreadable" and dropped), so the percentages reflect usable pages only, not all 15 slots. Sample sizes actually checked ranged from 6 to 13 usable pages per effect.
  • What counted as disclosure: any sentence anywhere on the page noting a replication failure, contested status, or a caveat that the effect is weaker, narrower, or less settled than the popular framing implies. A single disclosing sentence on an otherwise uncritical page still counted as disclosed, which is a low bar, so the low percentages above likely understate, not overstate, the real transparency gap.
  • What this does not claim: this is one search snapshot, not a tracked index; rankings and page content change, and a different query phrasing would return a different set of pages. We are not claiming these are the only or the definitive top results, only what we observed for these specific queries on the date below. Sample sizes of 6 to 13 per effect are still small enough that a single-digit swing in disclosed count meaningfully moves the percentage; treat these as directional, not precise to the decimal.
  • This measurement was revised once already: an initial pass at 4 to 9 results per effect found sunk cost fallacy at 28.6% disclosure; rerunning at a larger sample (10 usable results) found 0%. We are showing the larger, more recent sample rather than averaging the two, and flag this specifically because it is exactly the kind of small-sample instability the rest of this page argues readers should watch for.
  • When this was measured: August 2026. We plan to re-run this measurement periodically and will note the date of the most recent run here.

How to use this responsibly

Match how you cite an effect to its evidence tier: treat robust, multi-lab-replicated effects as safe to teach and design around, cite supported-with-caveats effects with their bounds rather than as universal laws, and cite contested or failed-to-replicate effects only alongside their replication failure, or leave them out of load-bearing claims entirely. Knowing a bias exists also does not mean a given "debiasing" fix works, since debiasing has its own, separately weaker evidence base.

  • Robust effects (framing, classic estimation anchoring, sunk cost) replicated in large multi-lab projects and are safe to teach and design around, while remembering effect sizes are conditional.
  • Supported / supported-with-caveats effects (confirmation bias, overconfidence, availability, loss aversion, planning fallacy) are real but should be described with their boundaries, not as iron laws - and in the planning fallacy's case, with the caveat that nobody appears to have run the large-scale replication yet.
  • Contested effects (ego depletion, dramatic social priming, incidental/irrelevant anchoring) should be cited only with the replication failure noted - or not used as load-bearing evidence at all.
  • The meta-lesson: the existence of a bias does not mean any specific intervention reliably "debiases" it. Debiasing evidence is its own, often weaker, literature.

Methodology and scope notes

  • Evidence basis: foundational papers for each effect, cross-checked against large replication efforts (Many Labs 1 and 2, Registered Replication Reports) and meta-analyses where one exists. The replication ledger records, for each effect, what kind of evidence exists (single study, meta-analysis, or multi-lab replication) and what it found - both axes are reported so a thin evidence base is never disguised as a failed one, or vice versa.
  • What we did not do: we did not run new experiments and we did not estimate any number we could not trace to a specific cited study. Where a claim about a study (a citation count, a meta-analysis' study count) could not be independently confirmed, it was cut rather than published as a guess.
  • The Open Science Collaboration (2015) 100-study project is cited for context on the replication crisis, not as direct evidence for any single row - none of these ten effects were part of that randomly sampled project.
  • "Robust" is not "unlimited." Even well-replicated biases have moderators, cultural variation, and context limits. Treat ratings as evidence strength, not universal magnitude.
  • Not individual advice. This summarises general findings about typical decision-makers; it is not personalised, clinical, financial, or legal guidance.
  • Maintenance: updated when major new replication evidence changes a rating, not on a fixed schedule.

Sources checked: the raw audit

For transparency, every page we checked for the search transparency gap measurement above is listed below, one collapsible section per row, with our verdict and the exact disclosing sentence where one was found. This is the full working, not a summary of it.

Overconfidence / miscalibration: 0 of 6 disclosed
Planning fallacy: 0 of 12 disclosed
Sunk cost fallacy: 0 of 10 disclosed
Anchoring, incidental/irrelevant: 1 of 9 disclosed
Availability heuristic: 2 of 12 disclosed
Anchoring, classic estimation: 2 of 11 disclosed
Framing effect: 2 of 11 disclosed
Confirmation bias: 3 of 9 disclosed
Loss aversion: 6 of 13 disclosed
  • en.wikipedia.org: disclosed. "Multiple studies have questioned the existence of loss aversion. In several studies examining the effect of losses in decision-making, no loss aversion was found under risk and uncertainty."
  • psychologytoday.com: not disclosed
  • thedecisionlab.com: not disclosed
  • ebsco.com: disclosed. "Losses can have a greater psychological impact than equivalent gains, although the strength of this effect varies across people, situations, and study designs."
  • masterclass.com: excluded, page unreadable
  • behavioraleconomics.com: disclosed. "Some researchers have questioned the robustness or even existence of loss aversion (Gal & Rucker, 2018)."
  • tutor2u.net: not disclosed
  • economicshelp.org: not disclosed
  • insidebe.com: disclosed. "Evidence seems to consistently show that loss aversion does not occur in all situations, and not in the same way in different situations."
  • nngroup.com: not disclosed
  • yukaichou.com: disclosed. "Loss aversion still exists; it is just smaller and more context-dependent than the 2.0 figure implies."
  • fiveable.me: excluded, page unreadable
  • wallstreetprep.com: not disclosed
  • psychologyfanatic.com: disclosed. "their sensitivity drops significantly or even disappears once they've experienced those gains or losses"
  • simplypsychology.org: not disclosed
Social/behavioral priming: 4 of 7 disclosed
Ego depletion: 13 of 13 disclosed
  • en.wikipedia.org: disclosed. "In 2016, a major multi-lab replication study carried out at two dozen labs across the world using a single protocol failed to find any evidence for ego depletion."
  • simplypsychology.org: disclosed. "There have both been studies to support and question the validity of ego depletion as a theory."
  • thedecisionlab.com: disclosed. "It recently came under fire when an attempt to replicate Baumeister's landmark study did not yield results in support of ego depletion."
  • psychologytoday.com: disclosed. "The first published failure to replicate the effect came out in 2004."
  • sciencedirect.com: excluded, page unreadable
  • study.com: excluded, page unreadable
  • betterhelp.com: disclosed. "The studies that supported ego depletion may have been flawed."
  • reachlink.com: disclosed. "Twenty-three laboratories across the world tested 2,141 participants using the same standardized protocol. The result was an effect size of just d=0.04."
  • scienceinsights.org: disclosed. "A major coordinated effort involving 23 laboratories and over 2,100 participants failed to replicate the effect."
  • nirandfar.com: disclosed. "Plenty of new research has found that willpower is actually not "used up" like gas in a gas tank or charge in a battery."
  • psychologyfanatic.com: disclosed. "Ego-depletion and the strength model recently have come under fire. There is scientific backing to some of the opposition."
  • teuxdeux.com: disclosed. "Studies by other orgs and researchers have either found no ego depletion effect or even gone as far as claiming publication bias"
  • psychologs.com: disclosed. "This perspective is controversial in modern psychology, as motivation plays a significant role."
  • stillmindflorida.com: disclosed. "A large-scale replication effort published in Psychological Science found limited support for the theory, sparking discussions about its reliability and broader applicability."
  • speakandregret.michaelinzlicht.com: disclosed. "24 labs from around the world and tested over 2,000 participants, all to replicate a previously published ego depletion study...And then the results came in: no effect."

Sources

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  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. View source
  • Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453-458. View source
  • Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207-232. View source
  • Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220. View source
  • Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502-517. View source
  • Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the "planning fallacy." Journal of Personality and Social Psychology, 67(3), 366-381. View source
  • Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost. Organizational Behavior and Human Decision Processes, 35(1), 124-140. View source
  • Hagger, M. S., et al. (2016). A multilab preregistered replication of the ego-depletion effect. Perspectives on Psychological Science, 11(4), 546-573. View source
  • Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. View source
  • Klein, R. A., et al. (2014). Investigating variation in replicability: A "many labs" replication project. Social Psychology, 45(3), 142-152. View source
  • Klein, R. A., et al. (2018). Many Labs 2: Investigating variation in replicability across samples and settings. Advances in Methods and Practices in Psychological Science, 1(4), 443-490. View source
  • Hart, W., Albarracín, D., Eagly, A. H., Brechan, I., Lindberg, M. J., & Merrill, L. (2009). Feeling validated versus being correct: A meta-analysis of selective exposure to information. Psychological Bulletin, 135(4), 555-588. View source
  • Zeif, N., & Yechiam, E. (2023). Loss aversion simply does not materialize for smaller losses. Judgment and Decision Making, 18, e19. View source
  • Gal, D., & Rucker, D. D. (2018). The loss of loss aversion: Will it loom larger than its gain? Journal of Consumer Psychology, 28(3), 497-516. View source
  • Doyen, S., Klein, O., Pichon, C.-L., & Cleeremans, A. (2012). Behavioral priming: It's all in the mind, but whose mind? PLOS ONE, 7(1), e29081. View source
  • Sedlmeier, P., Hertwig, R., & Gigerenzer, G. (1998). Are judgments of the positional frequencies of letters systematically biased due to availability? Journal of Experimental Psychology: Learning, Memory, and Cognition, 24(3), 754-770. View source
  • Juslin, P., Winman, A., & Olsson, H. (2000). Naive empiricism and dogmatism in confidence research: A critical examination of the hard-easy effect. Psychological Review, 107(2), 384-396. View source