Now, it's possible that in a particular case, paper B assumes the correctness of a result in paper A and depends on it. But that isn't going to be the case with most references.
Imagine you're reading a research paper, and each citation of a retracted paper has a bright red indicator.
Cites of papers that cite retracted papers get orange. Higher degrees of separation might get Yellow.
Would that, plus recalculating the citation graph points system, implement the "cascading deletes" you had in mind?
It could be trivial feature of hypertext, like we arguably should be using already. (Or one could even kludge it into viewers for the anachronistic PDF.)
I think a better method would be for someone to look over each paper that cites a retracted paper, see which parts of it depend on the retracted data, and cut and/or modify those parts (perhaps highlight in red) to show they were invalidated. Then if there’s a lot of or particularly important cut or modified parts, do this for the papers that cite the modified paper, and so on.
This may also be tedious. But you can have people who aren’t the original authors do it (ideally people who like to look for retracted data), and you can pay them full-time for it. Then the researchers who work full-time reading papers and writing new ones can dedicate much less their time questioning the legitimacy of what they read and amending what they’ve written long ago.
Of course, some papers pretty much have to be cited, because they're obviously very relevant, and you just have to risk an annoying red mark appearing in your paper if that mandatory citation is ever retracted.
But citations that are more discretionary or political, in some subfields (e.g., you know someone from that PI's lab is going to be a reviewer), if you think their pettiness might be matched by the sloppiness/sketchiness of their work, then maybe you don't give them that citation, after all.
If this means everyone in a field has incentive for citations to become lower-risk for this embarrassing taint, then maybe that field starts taking misconduct and reviewing more seriously.
I wonder if you could assign a citation tree score to each first-level citation.
For example, I cite papers A,B,C,D. Paper A cites papers 1,2,3,4. Paper 1 cites a retracted paper, plus 3 good ones.
We could say "Paper 1" was 0.75, or 75% 'truthy'. "Paper A" would be 3x good + 1x 075% = 3.75/4 = 93.7% truthy, and so on.
Basically, the deeper in the tree that the retracted paper is, the less impact it propagates forth.
Maybe you could multiply each citation by it's impact factor at the top level paper.
At the top level, you'd see:
Paper A = 93.7% truthy, impact factor 100 -> 93.7 / 100 pts
Paper B = 100% truthy, IPF 10 -> 10/10 pts
Paper C = 3/4 pts
Paper D = 1/1 pts
Total = 107 / 115 pts = 93% truthy citation list
If a paper has an outsized impact factor, it gets weighted more heavily, since presumably the community has put more stock in it.
I don't think "number of citations" typically make this distinction?
Also for some papers the citation doesn't really matter, and you can exclude the entire thing without really affecting the paper.
Regardless, this seems like a nice idea on the face of it, but practically I foresee a lot of potential problems if done "non-negotiably".
Maybe negative citations could be categorized separately by the authors and not count towards the cited paper's citation count and be ignored for cascading citations.
If the citation doesn't materially affect the paper, the author can re-publish it with that removed.
This paper is 22 years old. Some authors have retired. Some are dead.
I really think that at the very least it needs a quick sniff test. Which is boring uninteresting work and with 4,500 citations that will take some effort, but that's why we pay the journals big bucks. Otherwise it's just going to be the academic variant of the Scunthorpe problem.
And/or do something more fine-grained than a binary retraction, such as adding in a clear warning that a citation was retracted and telling readers to double-check that citation specifically.
So now if you want to cite come paper you have to decide which papers you'd die and live with, and consequently your paper prestige will be dependent on how many other papers want to die and live with yours.
https://en.wikipedia.org/wiki/Nofollow
although the incentives will be more confusing.
There's an argument to be made that citing something to disagree with it should increase its prestige but not its credibility (to the extent that those can be separated): you're agreeing that it's important.
>Therefore, MSC-based bone regeneration is considered an optimal approach [53]. [0]
>MSC-subtypes were originally considered to contain pluripotent developmental capabilities (79,80). [1]
Both these examples give a single passing mention of the article. It makes no sense for thousands of researchers to go out and remove these citations. Realisticly you can't expect people to perform every experiment they read before they cite it. Meanwhile there has been a lot of development in this field despite the retracted paper.
[0] https://www.mdpi.com/2073-4409/8/8/886
[1] https://www.tandfonline.com/doi/full/10.3402/jev.v4.30087
If an experiment or analysis is reliant on the correctness of a retracted paper, then shouldn't it need to be redone? In principle this seems reasonable to me—is there something I'm missing?
EDIT: Maybe I misunderstood... is your point that the criterion of "cites a retracted paper" is too vague on its own to warrant redoing all downstream experiments?
I think, personally, it's unrealistic to expect every researcher who mentions anything that has an electron in it (aka most things) to need to recreate the double slit experiment. Or, to harvest the stem cells themselves instead of buying them from trusted suppliers. Yes I do as I type this out see more that if more re-experimenting was done it would help detect fraud. But crucially, it really doesn't matter what an electron is to people determining that stems cells are in humans. The "non-negotiably" is what worries me. There should be some negotiation to say "hey your paper uses this debunked article. You have x days to find another, proven paper that supports the argument, or remove the argument entirely, or we'll retract your paper as well." I think that's valid. Especially since the fraud here wouldn't be impacting the author using the bad paper (most of the time, I would imagine) but rather the ones writing the paper. I would hesitate to believe that people faking such crucial, potentially lifesaving research care that some nobody they'll never meet might be upset their paper doesn't make it.
I think really what I'd like to see instead is more checking done at the peer review stage. To me that's the whole point of the journal. I'm biased on this having been rejected during the peer review stage and disliking how expensive journal articles can get, but at the end of the day, that's the point of them. They should be doing everything in their power to ensure that the research is accurate. And if we can't trust that, what's the point to the journals at all? May as well just go on blogs or something.
One would hope that if some work really did materially depend on a bogus paper, then they would discover the error sooner rather than later.
How many papers entirely depend on the accuracy of one cited experiment (even if the experiment is replicated)?
The idea of punishing third parties for a citation is weird. If I quote somebody who lied, I'm at fault? Seriously?
If you cite something that turns out to be garbage, I'd imagine the procedure would be to remove the citation and to remove anything in the paper that depends on it, and to resubmit. If your paper falls apart without it, then it should be binned.
Science papers are novel contributions of data, and sometimes of purely computational methods. A data paper will stand on its own. A method paper will usually (or at least should) operate across multiple data sets to compare performance, or if only on a single dataset it's gonna to be a very well tested dataset.
If MNist turns out to be retracted, would we have to remove all the papers that used it over their years? That's about as deep as a citation can get into being fundamental and integral to a paper. And even in that case nearly any paper operating in that dataset will also be using other datasets. Sure, ignore a paper that only evaluates on a single retracted dataset, but why even bother retracting, as the paper would be ignored anyway, because what significant paper would use a single benchmark?
But 99.9% of citations have less bearing on a paper than being a fundamental dataset used to evaluate the claims in the paper. And those citations are inherently well-tested work product already.
So if people actually care about science, they would never even propose such a scheme. They would bother to at least understand what a citation was first.
No, absolutely not, that's pure fallacy.
There might be some small subset of citations that work like a mathematical proof, but how many of these 4500 citations could you find that operate that way?
And even then, you're just weakening the result, not throwing it out entirely: instead of a proof of X that cites a proof of Y, you have a proof that Y implies X.