Harvard Teaching Hospital Seeks Retraction of 6 Papers by Top Researchers
wsj.com
wsj.com
I have a HLS lawyerbro that absolutely attests to this theory. "You hear that? That's `pride` fuckin'with'ya."
One thing that should be setting off alarm bells now is how often these scandals in the last couple of years have involved people who are in very high-level administrative positions at these institutions. Not only because of the values that might be instilled downward in the future, but also what it says about what has been valued already to reach those positions.
I have seen and heard stuff like this routinely that never makes the press. Not everyone in academics is corrupt, but the rot is prevalent enough that it's pretty systemic at this point and affects everyone. I think sometimes people don't even realize what they're suggesting sometimes, it's so common.
I have a theory that as some indicator of success deviates from a normal tail, there's more likely to be corruption or luck involved. The incentives just don't work the other way. But I'm biased based on my experiences, which reflect one domain of modern society.
And/or abuse, coercion, and exploitation of others.
Crazy that Nature published a article highlighting fraud concerns about Nature's own publications, but Nature has no plans to reduce that fraud.
The general public often think that academia is merit-based with the smartest being rewarded, but as you know it's a more complicated picture than that. You're not alone in your thinking; I'm pretty sure everyone in academia recognizes the problems. It's just that enough people benefit from the current incentive structures that the occasional scandal isn't enough for academics to reassess the predominant paradigm.
Just dismissing everything as "welp, that's just hierarchical power structures" is dumb.
Larger systems do require some degree of it, yes. But the ones that have more hierarchy and where it is more rigid, inevitably end up with more of this kind of thing.
Or to put it differently, the unquenched desires of acquisition, rivalry, vanity, and power lead people to do things they oughtn't
The flip side of this is most societies’ model citizens are highly compliant, possibly even supplicant. Entire categories of rudeness are, in essence, about not challenging authority and convention.
For a sector/area/industry that deals with "hard facts" and Science, it's "surprising" how much of these groups and institutions run on prestige, greed and ego.
We are talking about institutions run by these people who have annual budgets of BILLIONS of dollars, sometimes I feel most people view these schools and institutions like just one step above their local high-school, nothing is further from the truth.
When thinking about it more, I think that is also highly likely. It many of these cases the most "famous" author is the last one on the paper, but is the first to be highlighted in the media. That is, oftentimes the work was just done in their labs but they did little more than review. But there is such pressure for those toiling in the labs to make a "big" splash that it's not hard to think that some small number of them would be willing to cheat. This line from the original blog post (https://forbetterscience.com/2024/01/02/dana-farberications-...) reporting on the findings is telling:
> “You should reach out to Dr. Hidde Ploegh- the first author, Dr. Boaz Tirosh was in his laboratory.”
> Well Laurie, it’s your paper, if you care about it being correct, you could very well reach out yourself!
While I agree that Laurie Glimcher should be very concerned about any research misconduct done under her authorship, I think it's premature to get out the pitchforks when there are potentially many levels of indirection here.
To be clear, I'm not saying any of the authors get a free pass, but different authors have vastly different levels of culpability.
What would be the evidence of deceit you’d expect to find here? A video of a monologue by the evil villain disclosing their intention to deceive readers because they believe no one will reproduce their analysis before they get their promotion?
Agreed that de-anonymizing will become trivial. This will be a problem not only for bad actors in research, journalism, creative writing, etc., but for internet commenters who believed they'd done due diligence to remain anonymous, and even for research participants who'd expected anonymity when signing their consent forms. We're rushing headlong into even stranger days!
Academic fraud seems to be self-correcting as we have seen by the numerous reports of fraud and withdrawn papers; as a rule, the players express shame and remorse. Nonacademic fraud doesn't exhibit these characteristics and sometimes seems to be proud of the fraud.
Presumably the same can be done for tabular data and genomic or "omics" data. At the very least statistical techniques can be used. I imagine high throughput imaging modalities will be the main target.
That being said the only way the -omics data will have utility is via AI models which are trained on some task... which present their own problems..
You don't need a language model. The effort is in collecting and chopping the data to find snippets to compare. NNs can help with that.
Newer fraud will probably use generative diffusion AIs to make "realistic western plots" on demand .. there's probably a paper in that!
The higher the stakes, the lower the standards.
https://forbetterscience.com/2024/01/02/dana-farberications-...
The icing on the cake is when these frauds retract their papers, NOTHING happens to them. Nothing.
Still, some things are worth researching, but finding out what's true (or true-ish) will take a lot of time. Don't trusting findings that haven't been reproduced, stay skeptical of theories that hinge on a far-reaching interpretation of the data, and downright ignore publications with surprising claims. It's not nice, but it's realistic.
> "For more than 150 trials, Carlisle got access to anonymized individual participant data (IPD). By studying the IPD spreadsheets, he judged that 44% of these trials contained at least some flawed data: impossible statistics, incorrect calculations or duplicated numbers or figures, for instance. And in 26% of the papers had problems that were so widespread that the trial was impossible to trust, he judged — either because the authors were incompetent, or because they had faked the data."