At least seven years after questions were first raised about work by a researcher at the University of Maryland Baltimore, School of Medicine, he has agreed to a three-year ban on Federal funding.
Anil Jaiswal, whose first retraction appeared in 2013, faked data in eight NIH grant applications and six papers supported by Federal grants, according to a new finding by the Office of Research Integrity (ORI). Jaiswal, the ORI said,
intentionally, knowingly, or recklessly: (a) used random blank background sections of film or empty boxes to falsely represent or fabricate western blot analyses; (b) used manipulated images to generate and report falsified data in figures; and (c) used mislabeled images to falsely report data in figures.
Jaiswal has had 22 papers retracted, with some of those taking a year or more after the university requested them, as we’ve reported based on public records requests. As part of his agreement with ORI, he said he would retract two more papers, from Cancer Research and Chemico-Biological Interactions.
Jaiswal left the University of Maryland in November 2017. Over his career, he has received some $17 million in NIH grants.
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What a laugh! 3 year ban for $17 million is worth it!
Do you get 6 year ban for $34 million?
But is it worth public humiliation on the internet? Yes, probably that too. How about being lashed by a former member of ISIS with the finely honed tip of a bamboo cane? I think that is going to be the punishment needed to stop fraud in science. Plenty of unemployed former ISIS members that the ORI can employ.
One can always debate PHS ‘sanctions’, but were ORI to get into the ‘punishment’ game it would have to use a higher standard of proof, one that would severely limit 1) its number of findings and 2) what the research community would actually learn.
If you “watch retractions” with an interest in the means for ‘correcting the literature,’ then what is significant about the last couple of ORI findings is the considerable detail and effort put into announcing what was actually found to be false. (Someone is doing a good job in investigations!)
When that happens (and unlike the secretive NSF model), interested researchers can actually use the content of an ORI finding, . . . but only if NIH-NLM still (???) links ORI findings via Comment links to PubMed search results (ORI newsletter, Sept 2011, p 3ff). I hope ORI keeps reporting detail.
“One can always debate PHS ‘sanctions’, but were ORI to get into the ‘punishment’ game it would have to use a higher standard of proof…”
The standard of proof for civil courts is “on balance of probabilities”. “Beyond all reasonable doubt is for criminal courts. The standard of proof for the ORI cases is at the level of civil courts. Civil courts can issue hefty fines.
The scientific literature will gradually become full of problematic data if the standard of proof to get something published is “on balance of probabilities”, yet the standard to remove something from the literature is “beyond all reasonable doubt”.
Actually, Not Civil Law! In the US, “Research Misconduct” involves what is called “Administrative Law‘ where the standard of proof is the minimal “preponderance of the evidence.” That translates in practice to ‘more likely than not.’
But on the broader point, are you maintaining that it is the job of an underfunded federal agency to cleanse and preserve the vital bodily fluids of academic science?
I should have added that there is nothing in a ORI PHS Finding that precludes 1) a relevant party from suing in civil court to recover funds, nor 2) the respondent being prosecuted in criminal court by other entities if that is warranted. Indeed, that has happened before. The contorted language “neither admits nor denies” in most voluntary agreements specifically recognizes that risk.
An estimated $200 billion — or the equivalent of 85 percent of global spending on research — is routinely wasted on poorly designed and redundant studies, according to meta-researchers who have analyzed inefficiencies in research. We know that as much as 30 percent of the most influential original medical research papers later turn out to be wrong or exaggerated.
These days, unfortunately there are many papers are conducted on fake data