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The discussions show enthusiastic support for using prediction markets as efficient alternatives for assessing reproducibility, with posts mentioning their effectiveness, related experiments, and potential for faster discovery, where words like 'effective,' 'fascinating,' and 'useful' underline positive perceptions and engagement with the research's implications.
Most discussions express support and recognition of the method's usefulness, indicating general agreement on the value of prediction markets in research reproducibility.
The topic attracts high interest, with mentions of prediction markets as innovative and promising tools in scientific validation.
Many posts delve into details, citing examples, related studies, and potential applications, demonstrating active engagement.
Some posts highlight the potential for prediction markets to improve research reliability and speed, suggesting moderate but meaningful impact.
@literalbanana @Meaningness prediction markets are actually pretty good at predicting what replicates and what doesn't https://t.co/dDtHAAvIqG
@arjunrajlab I recall this was tried in one of those systematic replication studies, and worked surprisingly well. I.e. people knew what was bs. Maybe this one: https://t.co/uaPMxOMyro
@sirileknes @TimoRoettger I think it could be useful! Though if you preregister your analysis plan and predictions with enough details, it should prevent your bias from affecting the results. Prediction markets are used to test if peers can predict studies' results (see e.g. https://t.co/SIopLDrKjL)
@0xNN2 yes love it! @VitalikButerin touched on it here https://t.co/kzotfrmBPk https://t.co/qnovQBJUIG https://t.co/zQw3Ss9kCa
Using prediction markets to estimate the reproducibility of scientific research https://t.co/Ezx5VXUvCe
@JProtzko A paper showing forecasters can in some cases spot stuff that won’t replicate: https://t.co/6DDeKqywn8 And a reflection by a forecaster who did well in a related study in which he describes his thinking along the lines you mention above: https://t.co/MjMT3RnXzi
Impact is often overvalued in science, with citations and prominence overshadowing quality. This video explores why nonreplicable studies are cited more than replicable ones and discusses the influence of journal…
Open Science promotes transparency and integrity using practices like preprints, preregistrations, and open software, improving research robustness in neuroscience and psychology. This series explores how these methods…
Ref: Using prediction markets to estimate the reproducibility of scientific research https://t.co/ZfAlKsmXXs
Dreber et al. (2015) reported an alternative method to examine the replicability of SBS papers: the expert-sourced prediction markets. It is effective and less time-consuming. However, it is hard to scale. https://t.co/zkHoKZgFQq
@tarunchitra https://t.co/JxyswTWfHW
@0xNN2 yes love it! @VitalikButerin touched on it here https://t.co/kzotfrmBPk https://t.co/qnovQBJUIG https://t.co/zQw3Ss9kCa
@AlanaDLevin Read a cool paper on using markets to predict the reproducibility of an academic paper: https://t.co/J2VqEzR8e7 There's actually a lot of work on predictive markets out there -- some of it is really fascinating
@JProtzko A paper showing forecasters can in some cases spot stuff that won’t replicate: https://t.co/6DDeKqywn8 And a reflection by a forecaster who did well in a related study in which he describes his thinking along the lines you mention above: https://t.co/MjMT3RnXzi
@literalbanana @Meaningness prediction markets are actually pretty good at predicting what replicates and what doesn't https://t.co/dDtHAAvIqG
@Sam_J_Street You mean more recent than the 2015 Dreber et al. experiments? https://t.co/kk2oq9Pa1o
@Professologue @wagneregger @Utopia_Rabbit @melex_sior @NathLarigaldie @Gobe_l_un @GeekNfit @HygieneMentale @Dumbsociologist @Scintigraphiste @MrSam144 @vieux_chene @AlexSamTG @lasagne42 @LanguesdeCha @YTCreateurs @KenzoNera @JaisTroian Celui-ci est plus pertinent : https://t.co/yQz3wfE7x0
@Professologue @wagneregger @Utopia_Rabbit @melex_sior @NathLarigaldie @Gobe_l_un @GeekNfit @HygieneMentale @Dumbsociologist @Scintigraphiste @MrSam144 @vieux_chene @AlexSamTG @lasagne42 @LanguesdeCha @YTCreateurs @KenzoNera @JaisTroian Et ici : https://t.co/yQz3wfE7x0
@sirileknes @TimoRoettger I think it could be useful! Though if you preregister your analysis plan and predictions with enough details, it should prevent your bias from affecting the results. Prediction markets are used to test if peers can predict studies' results (see e.g. https://t.co/SIopLDrKjL)
Even better is if we had a betting market on key COVID hypotheses, we could discover the truth faster and observe the market’s implied probability of each hypotheses being true. https://t.co/IAc0PqPsFP
RT @slinnarsson: @arjunrajlab I recall this was tried in one of those systematic replication studies, and worked surprisingly well. I.e. pe…
@arjunrajlab I recall this was tried in one of those systematic replication studies, and worked surprisingly well. I.e. people knew what was bs. Maybe this one: https://t.co/uaPMxOMyro
Using prediction markets to estimate the reproducibility of scientific research https://t.co/bsJSACHQYB
RT @gaodawei: Using prediction markets to estimate the reproducibility of scientific research https://t.co/Ezx5VXUvCe
Using prediction markets to estimate the reproducibility of scientific research https://t.co/Ezx5VXUvCe
Using prediction markets to estimate the reproducibility of scientific research. @StatModeling @bahniks @R__INDEX http://andrewgelman.com/2015/11/09/using-prediction-markets-to-estimate-the-reproducibility-of-scientific-research/
10.1073/pnas.1516179112. 30. Benjamin, D, et al. Redefine statistical significance. Nat. Hum. Behav. 1 (2017). DOI: 10.1038/s41562-017-0189-z. 31. Jeffreys, H ...
1516179112/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1516179112. PNAS Early Edition | 1 of 5.
https://www.pnas.org/doi/10.1073/pnas.2402315121 New study. Does ... 1516179112.abstract) and summary news stories in Atlantic (http://www.
https://www.pnas.org/doi/10.1073/pnas.1516179112. Eu mesmo fiz um desses estudos. Então, o sistema pelo menos meio que funciona. O que ...
... pnas.org/doi/10.1073/pnas. 1313495110 http://www.unm.edu/~mbeb ... 1516179112.abstract) and summary news stories in Atlantic (http://www.
... 1516179112.abstract) and summary news stories in Atlantic (http://www. ... 10.1073/pnas. 2120668119 About the project: https://replications ...
org/content/early/2015/11/04/1516179112. abstract ... org/replication-2022pnas119-43/ The original study: https://doi.org/10.1073/pnas.
https://www.pnas.org/doi/10.1073/pnas. 2402315121 New study. Does ... 1516179112.abstract) and summary news stories in Atlantic (http://www.
org/replication-2022pnas119-43/ The original study: https://doi.org/10.1073/pnas. ... org/content/early/2015/11/04/1516179112. abstract ...
DOI: 10.1073/pnas.1516179112. Available from: http://www.pnas.org/content/112/50/15343. Referências. American Statistical Association releases ...
DOI: 10.1073/pnas.1516179112. Available from: http://www.pnas.org/content/112/50/15343. Referências. American Statistical Association releases ...
org/replication-2022pnas119-43/ The original study: https://doi.org/10.1073/pnas. ... org/content/early/2015/11/04/1516179112. abstract ...
Medline doi:10.1073/pnas.1516179112. 27. J. Wolfers, E. Zitzewitz, Interpreting Prediction Market Prices as Probabilities. (Working Paper No ...
org/replication-2022pnas119-43/ The original study: https://doi.org/10.1073/pnas. ... org/content/early/2015/11/04/1516179112. abstract ...
... pnas.org/cgi/doi/10.1073/pnas.1516179112. Journal information: Proceedings of the National Academy of Sciences. Provided by Harvard University.
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