Oh my, I'd missed that:
"Two behavioral scientists who study honesty accused of using falsified data"
https://www.npr.org/transcripts/1190568472
Amazing :masto_lol:
#behavior #behaviouralScience #fraud #data #planetMoney #DanAriely #psychology #FrancescaGino #nudge #HarvardBusinessSchool #honesty #insurance #taxes #guatemala #dmv #DataColada
#behavior #behaviouralscience #fraud #data #planetmoney #danariely #psychology #francescagino #nudge #harvardbusinessschool #honesty #insurance #taxes #guatemala #dmv #datacolada
Next was a fantastic talk by Joowon Klusowski on choice and illusion of control at #DataColada. Through a series of rigorous experiments, Klusowski takes an absolute hammer to the notion that choice causes an illusion of control, showing instead that many of the effects of choice that are observed are due to pre-existing illusions. Highly recommend https://www.youtube.com/watch?v=Z4m_4TANQj8 (5/8) #psychology #BehavioralEconomics
#datacolada #psychology #behavioraleconomics
Next was an interesting talk by Nina Mažar on providing performance feedback on organ donor registrations (with surprising results) at #DataColada https://www.youtube.com/watch?v=LhoDGrY1EEU (6/12) #psychology
Next was a great talk by Ziad Obermeyer on predicting physician error at #DataColada. This is another version of a talk that appeared on this list 7 months ago, but the discussion of this fascinating study context and the confluence of machine learning, management, and ethics, still makes it highly relevant https://www.youtube.com/watch?v=ARn4-GB6CyY (6/7) #MachineLearning #ethics
#datacolada #MachineLearning #ethics
Next was a fantastic talk by Betsy Levy Paluck on the state of prejudice reduction research at #DataColada. tldr; there is a paucity of high-quality research that measures the effect of interventions to change attitudes and behavior, meaning that we simply don't know if any of what's out there actually works. An essential discussion ensues on what that means for research moving forward. Highly recommend https://www.youtube.com/watch?v=-9qiiqmCSpI (9/10) #psychology
Next was a great talk by Ioannis Evangelidis on diminishing sensitivity in choice at #DataColada. After an introduction on sensitivity between options, Evangelidis shows through a number of experiments how people perceive value quite predictably (albeit a bit irrationally) https://www.youtube.com/watch?v=XJisLShY1C8 (5/8) #economics #psychology
#datacolada #economics #psychology
Last was an amazing talk by Sydney Scott on goal pursuit flexibility at #DataColada. Using a pair of rigorous studies, Scott shows how people tend to prefer flexible goals for themselves despite perceived lower efficacy, but will pick more rigid goals for others. Highly recommend https://www.youtube.com/watch?v=CRPS64tMcLo (10/10) #psychology
Next was a fascinating talk by Joachim Vosgerau on statistical biases and misperceptions that can come from #BigData analysis at #DataColada. Vosgerau shows that if one collects data in a non-representative way, it can lead to high levels of confidence in an extremely biased and incorrect result. Sadly, his follow up studies to try to correct perceptions of these analyses weren't able to move people to more critically evaluate large N analyses. Highly recommend https://www.youtube.com/watch?v=UJzlMFx72q4 (6/9)
[en] Cheating in Science: Harvard "Honesty Scholar" May Have Been Caught in Dishonesty
"... dishonesty can lead to creativity" - an interesting and somewhat amusing read.
The New York Times: "Questions about a widely cited paper are the latest to be raised about methods used in #behavioral research."
#ResearchHighlights #honesty #dishonesty #phacking #harking #dredging #gino #harvard #fraud #cheating #academic #datacolada
#datacolada #academic #cheating #fraud #harvard #gino #dredging #harking #phacking #dishonesty #honesty #researchhighlights #behavioral
Next was an intriguing talk by Nick Yeung on confidence, trust, and decision making at #DataColada. Yeung investigates these phenomena at a variety of levels, showing how people consistently discount other's predictions in a wide range of contexts (unless they agree with you) https://www.youtube.com/watch?v=i9xvEU6qgyY (8/9)