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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]( - Submit your audio questions [via our website]( - Nick Brown's [blogpost]( on the video game "study" - We ran a live survey using Prolific! Go to to get $50 worth of credit for one dollar! - Spotting unlikely data in meta-analysis - How can make reviewers better at detecting errors in papers? - Using a "[Red team](" to pull apart your papers - What do lay people think _really_ happens in peer review? **Other links** - [Dan on twitter]( - [James on twitter]( - [Everything Hertz on twitter]( - [Everything Hertz on Facebook]( Music credits: [Lee Rosevere]( --------------------------------- [Support us on Patreon]( and get bonus stuff! - $1 a month or more: Monthly newsletter + Access to behind-the-scenes photos & video via the Patreon app + the the warm feeling you're supporting the show - $5 a month or more: All the stuff you get in the one dollar tier PLUS a bonus mini episode every month (extras + the bits we couldn't include in our regular episodes) --------------------------------- Buy our merch from our [online store](! We've got hats, mugs, hoodies, shirts + more ![]( --------------------------------- **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
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