Hundreds of extreme self-citing scientists revealed in new database

Another example, my advisor doesn't like git. While writing papers I and my collaborators use git but send an email copy to my advisor. Clearly he's going to be on the paper because he's my advisor but you'll see zero commits from him.

I think it's just too easy to think that technology solves this in a trivial way. It's complicated. You have people from different eras working on things. And this is in a CS program, mind you. In different fields it gets much worse very quick.

Side note: go look at papers from top tier universities. You'll notice that they frequently cite colleagues at their University. Is this because they are gaming the system? Is it because they are doing the most related research (which is VERY common for a single University to work close)? Or is it a combination. In all likelihood it's a combination because citations matter. The h index is used in your performance because this is meant to be how impactful your paper is, but the system can definitely be manipulated (and likely isn't happening for malicious reasons nor necessarily unethical reasons)

Answering questions about your past papers; looking over someone else's proposed methodology; or cleaning up an internal tool into one you can share are all great tasks for advancing the field, but none of them bolster a CV, earn grants, or help you get tenure. If you want credit for them, you usually have to commit lots more time to the task, like running a formal discussion, becoming an author, or polishing the tool into an OSS contribution. All too often, the result is siloed projects and work abandoned as soon as it's published. (How many papers offering some novel twist on priming or ego depletion could have been turned into replication-and-extension if past authors had been involved?)

Especially in astronomy, with large projects and lots of non-PhD team members, this makes so much sense. (I believe something similar may happen at LIGO - if not formally then at least in practice?) If work is going to be judged by authorship, it's only fair to recognize that at a certain point the groundwork and floating aid people give is comparably valuable to the act of writing up some chunk of the text.

There are other factors at play too, that are harder for me to pin down. Funding models are a big problem, but there's something related to attention-seeking or metrification at play too. Some of this has probably always been around, but in talking to older colleagues I get the sense that things are much more splashy and fad-driven than they used to be, with much greater pressure to produce in volume. A colleague explained that when it's that much easier to write and publish a paper, there's more of an expectation that you do more of them, even though the idea development time isn't any shorter.

This is also one of the arguments against promoters of so-called "term limits" for congressmen and others; imagine this kind of churn in priorities occurring with major and minor public works projects!

We don't have to wonder too much - we can already see it at the state level with governorships changing; one recent large change of this kind is with California's high-speed rail system. For all of it's "boondoggle-ry" and problems, I don't think the way it's been "axed" lately will be of help to completing it. In fact, it might just be a self-fulfilling prophecy for its opponents.

That's only one example; I'm sure others in other states could be easily found as well if one were to look. Ultimately, that kind of thing would only get worse with term limits on representatives to Congress, because federal funding for such large scale projects is needed - and that would end up likely in flux, and ultimately scuttle projects that depend on steady funding to be completed.

One could argue that individual state projects should only be funded by the state itself, but that notion of state self-sufficiency went out with the end of the Civil War. I also tend to wonder if - under a term-limited system - such a thing as the interstate highway system could have ever been built. It doesn't seem likely.

There seem to be some authors and author groups who rely almost entirely on self-citation for impact factor, allowing them to get by with irrelevant or unchecked work. It might be possible to detect that with a metric like self-citation or high author-placement self-citation as a fraction of overall citations.

But overall, it seems like this metric should be limited to exploratory use. There are wholly legitimate cases of frequent self-citation, like mathemeticians pioneering a new technique, or astronomy research groups which cite a large support team and product many sequential findings. Discerning an apparent citation-mill like Vel Tech R&D from a legitimate research group like the LSST requires thought, not just statistics.

Meanwhile, the most egregious self-citers are usually doing something else wrong too. Robert Sternberg wasn't just self-citing, he was reusing large amounts of text without acknowledgement, and abusing his journal editorship to publish his own works without peer review. The Vel Tech author in the article seems to be citing his own past works which are irrelevant beyond vaguely falling in the same field, and the enormous range in his work (from food chain models to neurobiology to machine learning to fusion reactors) makes me suspect it's either inaccurate or insignificant.

Ioannidis is damn good at what he does, and was far too sensible to broadly condemn high self-citation researchers. But it would be a real shame to see self-citation rate blindly added to university standards the way citations and impact factor were. The lesson here is that reducing academic impact to statistical measures of papers doesn't work, not that we need some more statistical measures.

Publish? What and where exactly?

That's a strawman. The answer you were looking for is, "I don't know". I don't know either.

That’s not the case at all. Being at the leading edge of research should mean that you are creating new knowledge. That doesn’t imply that people cannot understand it. This expectation that laypeople cannot possibly understand science is one of the reasons so many papers are written so densely and obtusely. “They” can’t understand it anyway, right?

Feynman said if he couldn’t explain it to freshmen he didn’t understand it himself.

It's about the question of resource allocation. Pretty much every subfield of academia is a net consumer of resources, i.e. someone outside of that subfield is funneling resources to it. That someone - no matter if it's a university, or some foundation, or a gov't agency, or a philantrophist - needs to make a decision on how to allocate resources. And, in general, they honestly want to make a good, informed decision on which projects and researchers to support; but nonetheless they have to make a decision according to some criteria. So there's no choice of "no metric", there will always be a metric and we can only argue that it should be better. And the answer to "why anybody would willingly submit themselves to that" is that duh, you don't get a choice - you can suggest a better method to fulfil their goals of allocating resources in a way that is (also in their opinion) fair and objective; but you can't get around the fact that scientists are generally funded by nonscientists. And they need(or want) to make decisions.

They could delegate that, but that doesn't solve the question about the criteria - if they delegate that to universities, they still have to decide on how to allocate between departments; if they delegate that to scientist councils uniting all the departments in the country working on some subfield, they have to decide on how to allocate between the different organizations. So no matter what, you have to compare not only quality of similar scientists, but also of dissimilar scientists working in different (sub)fields. And delegation doesn't absolve you from responsibility, so if the money is (or looks!) wasted, then that's a failure - so when you delegate, you want to require them to use objective criteria. Which is hard - I could tell you which researchers in my subfield are doing excellent work and which are useless; but if I had to justify these decisions, to demonstrate why they're not just my bias because of politics/liking certain methods/gender/ethnicity/etc then it would actually be tricky; and I think that I'd actually reach out for these metrics. And I'm quite certain that the metrics (for the people that I have in mind) would agree with my subjective opinion; on average, the great research gets cited much more and is in higher-ranking venues; while the lousy stuff gets no citations apart from the author's only grad student.

Also, there's a lack of trust (IMHO not totally unwarranted). You could get a bunch of experts who are qualified to evaluate who gets what amount of resources, you can't rely on them actually doing so - if we take spiders as a totally random example, in general you're qualified to distinguish which spider research is good and which is useless only if you actually work on spider research, most likely in one of these teams - and the expected result is nepotism, allocating resources based on purely (intra-field) political reasons. And who'd decide on how to split resources between spider research and bird research? Do you expect the spider guys and bird guys to reach a consensus? Or would it go to whatever field the dean is in? This is a big problem even currently, and a big part of why the metrics are being gamed - but at least metrics are something that require effort to game and can't be gamed totally; if we'd do away with them, then we'd be left with absolutely arbitrary political allocation, which would be even worse.

So at the end of the day "they" need some way to transform the only reasonable source of truth - actual peer-review - to something that "non-peers" can use to judge what the the aggregate of that peer review says. That need is IMHO not negotiable, I really believe that they do actually need it - they don't want to do resource allocation totally arbitrarily, they want to do it well, they need (because of external pressures) objectivity and accountability, and currently this (journal rankings, bibliometerics, etc) is the best what we have suggested to summarize the results of that peer review.

If I had to write a law draft for a better process of allocating resources, what should be written in it?

An insightful study that's replicable (but has not yet been) is valuable. A lousy study that's been replicated five times (not because it's interesting, but because it was easy to do, and the replicators knew that they'd be rewarded for replicating anything) is not valuable.

A metric that says "number of studies" is IMHO even more arbitrary, more gameable, and more detached from actual value than citation count - which does have some notion that your study actually matters to other poeple; that it was worth writing that paper because someone read it.

Or, I dunno, paleontology or sociology or other stuff.

You trust in people, in consistency of physical laws, in coherency of your own mind, in constancy of temporal flow, in so many things because - as the Pyrrhonist refrains - nothing is certain, not even this.

Today, most scientists go for the popular topics and whatever is on the government research plan to get funding.* Whenever the wind changes direction they change their topics because they need that funding.

*: This might seem to contradict with the statement that most scientists work on nice topics. But only on the surface. In order to get published you have to do something novel. So, you choose a popular topic and then research a rather unpopular side aspect on it like how a specific chemical behaves when applied to the popular topic. If you're successful you publish and continue. Citations come later or they don't but the next round of funding comes with publishing. After a few years without many citations you move on to the next thing.

On government plans often you need to publish and then it's done. The citations only matter long-term if at all. Most scientists don't achieve anything of greater value. They are happy if they can publish at all. If the institute has a few scientists with a high citation count it carries all the rest of them.

There's countless numbers of scientists that made great strides working on topics others deemed rediculous. Heck, many of the Nobel prize winners were ridiculed by their colleagues as borderline wack-jobs at the time they were working on their research. Even after winning the prize, some still were with their later work (Crick's search for consciousness comes to mind, and why it would be so worthless a search does not).

If anything, the hubris of the scientific community would be as deafening as the pseudo-science BS and hold back progress just as much if not more except for one key thing: the scientific method.

Luckily, we have a process by which crackpots get differentiated from geniuses. So let's not leave $20 on the ground assuming others would have picked it up, especially when that $20 represents collective progress for the entire species.

This is nothing like tech startups, where you have tons of people sharing a relatively small problem space (creating tech tools companies want).

Consider for a moment: there are well over 350,000 different species of beetles. Theres just too much to study and too few people doing the work to expect there to always be a plethora of external research to draw upon.

Acquiring knowledge (I should say 'beliefs about valid knowledge') and brainstorming (and certainly collaboration and getting an advisor to adopt you) appear to be social activities, as much as purely logical and analytic activities.

Social activities like this, for social or herd creatures, are subject to flock or swarming patterns.

Maybe all the brilliant people are swarming around a locus of interest? It's certainly a good way to have the population explore the ins and outs of a, well, locus of interest. It's also a good way to have a loner get shunned by wandering off and poking at an uninteresting pile of dung.

I guess my point is: why not both? (Mathematically, statistically, egotistically, I know the idea that I am the foolish one is almost certainly more likely to be the case)

It seems like PhD candidates work on peripheral elements of their sponsor/tutor/professor's work, of that professor at some point is going to make a significant step then one of those PhDs will be along for the ride; not necessarily the genius one.

At the time, chytrids were about as obscure as a topic in science can be. Though fungi compose an entire organismal kingdom, on a level with plants or animals, mycology was and largely still is an esoteric field. Plant biologists are practically primetime television stars compared to mycologists. Only a handful of people had even heard of chytrids, and fewer still studied them. There was no inkling back then of the great significance they would later hold.

Longcore happened to know about chytrids because her mentor at the University of Michigan, the great mycologist Fred Sparrow, had studied them. Much yet remained to be learned—just in the course of her doctoral studies, Longcore identified three new species and a new genus—and to someone with a voracious interest in nature, chytrids were appealing. Their evolutionary origins date back 600 million years; though predominantly aquatic, they can be found in just about every moisture-rich environment; their spores propel themselves through water with flagella closely resembling the tails of sperm. Never mind that studying chytrids was, to use Joyce’s own word, “useless,” at least by the usual standards of utility. Chytrids were interesting.

The university gave Joyce an office and a microscope. She went to work: collecting chytrids from ponds and bogs and soils, teaching herself to grow them in cultures, describing them in painstaking detail, mapping their evolutionary trees. She published regularly in mycological journals, adding crumbs to the vast storehouse of human knowledge.

And so it might have continued but for a strange happening at the National Zoo in Washington, D.C., where poison blue dart frogs started dying for no evident reason. The zoo’s pathologists, Don Nichol and Allan Pessier, were baffled. They also happened to notice something odd growing on the dead frogs. A fungus, they suspected, probably aquatic in origin, though not one they recognized. An internet search turned up Longcore as someone who might have some ideas. They sent her a sample which she promptly cultured and characterized as a new genus and species of chytrid: Batrachochytrium dendrobatidis, she named it, or Bd for short.

That particular chytrid would prove to cause a disease more devastating than, as best as scientists can tell, any other in the story of life on Earth. After Longcore’s initial characterization, she and Nichol and Pessier proceeded to show that frogs exposed to Bd died. Other scientists soon linked Bd and its disease, dubbed chytridiomycosis, to massive, inexplicable die-offs of amphibians in Costa Rica, Australia, and the western United States. No disease had ever been known to cause a species to go extinct; as of this writing, chytridiomycosis has driven dozens to extinction, threatens hundreds more, and has been found in more than 500 species.

Almost overnight Longcore went from obscurity to the scientific center of an amphibian apocalypse. “Had I not been studying the ‘useless’ chytrids,” she says, “we wouldn’t have known how to deal with them.” Her research has been crucial—not only the initial characterization, but also her understanding of the systematics and classification of chytrids, which helped provide a conceptual scaffold for questions about Bd: Where did it come from? What made it so strange and so terrible? Why does it affect some species differently than others?

Imagine how many inventions we would have missed if all inventors had shared your mindset.