We answer a listener question on identifying red flags for errors in papers. Is there a way to better equip peer-reviewers for spotting errors and suspicious data?
More details and links...
We answer an audio question from Kim Mitchell (https://twitter.com/academicswrite).
Submit your audio questions via our website (https://everythinghertz.com/audio-question)
Nick Brown's blogpost (http://steamtraen.blogspot.com/2020/04/some-issues-in-recent-gaming-research.html) on the video game "study"
We ran a live survey using Prolific! Go to prolific.com/everythinghertz to get $50 worth of credit for $1
Spotting unlikely data in meta-analysis
How can make reviewers better at detecting errors in papers?
Using a "Red team (https://en.wikipedia.org/wiki/Red_team)" to pull apart your papers
What do lay people think really happens in peer review?
Other links
- Dan on twitter (www.twitter.com/dsquintana)
- James on twitter (www.twitter.com/jamesheathers)
- Everything Hertz on twitter (www.twitter.com/hertzpodcast)
- Everything Hertz on Facebook (www.facebook.com/everythinghertzpodcast/)
Music credits: Lee Rosevere (freemusicarchive.org/music/Lee_Rosevere/)
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Cite this episode
Quintana, D.S., Heathers, J.A.J. (Hosts). (2020, June 15) "110: Red flags for errors in papers", Everything Hertz [Audio podcast], DOI: 10.17605/OSF.IO/VTYNG