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Notes -
As some background for people, scientific labs usually have a three-level structure:
Looking over the academic investigation, it seems like a classic fudge: the PI says the data was compiled by a graduate student who never formalised it and took the original creation methodology with them when they left (entirely possible). The writer (a graduate student) is in hiding and refused to talk to the committee but gave various unconvincing reasons in writing why the false database can't be theirs (e.g. their database was a different file format). A bunch of graduate students were involved with the project, and their papers also seem to be dodgy in various ways.
Quoting the investigation committee:
Most likely explanation is that it's some combination of graduate students signing up to work with a prestigious PI, being put under huge pressure to produce results, and taking the low road rather than destroying their career. By the sounds of it, the data was passed around enough times that nobody was sure where it came from, and so didn't consider themselves to be doing anything more fraudulent then trusting their colleagues. It's entirely possible that the PI didn't know - or didn't want to know - that this was happening. His name is on most of the papers but that's standard for a PI and doesn't prove he did anything except fund the work.
Should the PI be punished, in the absence of positive evidence they did something wrong? Possibly. Probably, even. I can certainly see the argument for it and it might help. But at some point you have to do something to make academia less soul-destroying, otherwise it's like beating a horse and then killing it when it kicks.
You can of course control all of this to some extent by regulating how work is done and how data is handled, and in the last twenty years we mostly do. A big part of what the PI is getting dinged for in the original report is not following the appropriate guidelines. But academic labs aren't big pharmaceutical companies with lots of money to spend on compliance, so research output takes a big hit when this regulation becomes strict.
Secret data but more importantly secret code (any programs, algorithms, statistical techniques, data cleaning, etc.), would never cut it in the professional world. If you're a data scientist or a product manager proposing a change to a company's business processes you need to have your work in source control and reviewable by other people. There's no reason academics can't do the same. Make the PI responsible by default unless they can show fraud in the work their underling did. If they didn't review their underling's work then the PI is fully responsible. This would have the added benefit that researchers would learn useful skills (how to present work for review) for working in industry.
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Perhaps that should change, and perhaps one of the ways we could make it change would be to penalize the names on the papers for fraudulent work.
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