he research on research: how often findings replicate, why they sometimes do not, and what has changed. Every DOI checked against Crossref. Notes are our summaries, not quotations. Start with Rosenthal and the Open Science Collaboration.

1. Pfungst (1911). Clever Hans (the Horse of Mr. von Osten), trans. C. L. Rahn. New York: Henry Holt. German original 1907. Free edition at Project Gutenberg. www.gutenberg.org/ebooks/33936
   Not metascience by name, but the first famous case of an effect disappearing under controls: when the questioner did not know the answer, the horse did not either. The free scan is linked. Used in: Clever Hans  archive
2. Rosenthal (1979). The file drawer problem and tolerance for null results. Psychological Bulletin. doi:10.1037/0033-2909.86.3.638
   Names the file drawer problem and gives a way to estimate how many unpublished null studies it would take to cancel a published effect. Used in: replication
3. Ioannidis (2005). Why Most Published Research Findings Are False. PLoS Medicine. doi:10.1371/journal.pmed.0020124
   Argues from a simple model that under common conditions most published significant findings are false. Its assumptions are debated; its influence is not. Used in: replication
4. Bem (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. Journal of Personality and Social Psychology. doi:10.1037/a0021524
   Nine experiments reporting evidence for precognition using standard methods. Its main legacy was to make people ask what the standard methods were worth. Used in: replication
5. Simmons, Nelson & Simonsohn (2011). False-Positive Psychology. Psychological Science. doi:10.1177/0956797611417632
   Shows how undisclosed flexibility in data collection and analysis inflates false positives, and proposes disclosure rules. Short, funny and essential. Used in: replication
6. Button et al. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience. doi:10.1038/nrn3475
   Estimates that typical neuroscience studies are badly underpowered, and explains why that also inflates the effects that are found. Used in: replication
7. Open Science Collaboration (2015). Estimating the reproducibility of psychological science. Science. doi:10.1126/science.aac4716
   One hundred replications of published psychology studies: about a third reached significance, with effects about half the original size. The reference point for everything since. Used in: replication
8. Camerer et al. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour. doi:10.1038/s41562-018-0399-z
   Replications of social-science experiments from Nature and Science, with prediction markets that forecast which would replicate rather well. Used in: replication
9. Klein et al. (2018). Many Labs 2: Investigating Variation in Replicability Across Samples and Settings. Advances in Methods and Practices in Psychological Science. doi:10.1177/2515245918810225
   Many Labs 2: each finding run in many labs and countries at once. About half replicated, and effects that held varied surprisingly little across sites. Used in: replication
10. Nosek et al. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1708274114
    The case for preregistration: separating hypothesis-testing from exploration, and how to do it in practice. Used in: replication

see also

	replication — the area page
	measurement — what changes when somebody looks
	annotated: human–AI interaction