In case anyone hasn’t read it, the Datacolada article demonstrating Ariely committed fraud is a great read and extremely convincing.
https://www.gofundme.com/f/uhbka-support-data-coladas-legal-...
In early August 2023, Professor Gino filed a lawsuit for defamation against Harvard University, and against Leif, Joe, and Uri personally, claiming 25 million dollars in damages. Defending oneself in court is time-consuming and expensive regardless of the merits of the lawsuit – as First Amendment lawyer Ken White put it to Vox , “The process is the punishment.” Targets of scientific criticism can thus use the legal system to silence their critics.
At present, Leif, Joe, and Uri do not have pro bono representation. The lawyers they’ve spoken to currently estimate that their defense could cost anywhere between $50,000 and $600,000 (depending on how far the lawsuit progresses). Their employers have so far only agreed to pay part of the legal fees. Defending science requires defending legitimate scientific criticism against legal bullying.
Edit: I initially wrote that they met their GoFundMe goal of $350,000, which is true. However, I’m not sure why they set their goal to only $350k when they mention that legal costs could skyrocket to $600,000 which they have not met
Evidence of fraud in an influential field experiment about dishonesty - https://news.ycombinator.com/item?id=28210642 - Aug 2021 (51 comments)
(Lots more related links at https://news.ycombinator.com/item?id=37719476)
The insurance company confirmed the data Arielly represents he got is not the data they sent. Arielly is a fraud.
Dan Arielly is a curious figure to give this sort of benefit of doubt.
This data was so shoddily faked that I have a hard time believing someone did this with an intention to deceive. Uniform distribution with a hard cutoff at 50K??
Faking data realistically is almost as hard as getting it honestly. I know, I “expanded the data pool” for my eight grade science project.
Do an easy experiment once correctly, then again with falsified data. Present the results side-by-side. Ask people if they can tell you which is which. Present have a bit on what sort of statistics could catch your faked data set.
In my defense I would have run more tests had I started when I should have :)
Your suggestion only works in the simulated science, like school projects where you are retracing the footsteps of past successful scientists, to verify an already known result. There putting in more work will reveal that effect more and cleaner, because your teacher already knew how the thing works in the first place. This is totally unlike real science where we confront the frontier of the unknown.
My teachers warned against this and told us they would catch us if we tried.
It's just so laughably faked it's not even funny.
There was a similar case a while ago in spider biology: https://www.nature.com/articles/d41586-022-02156-2
Pruitt had several influential spider biology papers out and when others failed to replicate and dug into the Supplementary Data, they also found lazy patterns.
>When Laskowski dug into data sets that Pruitt had provided for the study, she was shocked to find stretches of data that seemed to have been duplicated, to represent findings for multiple spiders. This questionable data helped to bolster a long-unproven theory that repeated social interactions in a group of spiders cause individuals to behave predictably.
So yeah, who knows how much scientific fraud there actually is; I haven't seen a case of fraud where the data was convincingly faked, which means that these cases are hard to detect or hard to prove.