Slashdot Mirror
Crackpot Scandal In Mathematics
ocean_soul writes "It is well known among scientists that the impact factor of a scientific journal is not always a good indicator of the quality of the papers in the journal. An extreme example of this was recently uncovered in mathematics. The scandal is about one El Naschie, editor in chief of the 'scientific' journal Chaos, Solitons and Fractals, published by Elsevier. This is one of the highest impact factor journals in mathematics, but the quality of the papers in it is extremely poor. The journal has also published 322 papers with El Naschie as (co-)author, five of them in the latest issue. Like many crackpots, El Nashie has a kind of cult around him, with another journal devoted to praising his greatness. There was also a discussion about the Wikipedia entry for El Naschie, which was supposedly written by one of his followers. When it was deleted by Wikipedia, they even threatened legal actions (which never materialized)."
Yeah, you really have to be careful out there... that's why I get all my astronomy and mathematical insight (as well as web design hints) from http://www.timecube.com/
And if it ain't there, then I just look it up on wikipedia
Where's the article?
Ohhh! Right right! This is the article. Slashdot is now a primary source!
The harm, I think, is that he's not a well-enough-known crackpot; a respectable publisher (Elsevier) has given him a journal as his own private playground. This makes it more difficult for non-crackpots trying to enter the field (e.g. grad students) to sort the wheat from the chaff. It also allows other crackpots to come off as more credible by citing crackpot articles which have a veneer of respectability. Imagine if a computer science "journal" based on Hollywood's portrayal of how computers work were being published by the ACM, and you have some idea of how big a problem this is.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
In fact, the crackpotness of El Nachies' papers is obvious even to most grad students (you should read some, they are in fact rather funny). The bigger problem is that, by repeatedly citing his own articles, his journal gets a high impact factor. People who have absolutely no clue about math, like the ones who decide on the funding, conclude from the high impact factor that the papers in this journal must be of high quality.
How did El Naschie game the system?
According to Elsevier, his impact factor is 3.025, which does seem high compared to Elsevier titles like Advances in Applied Mathematics (founded by Gian-Carlo Rota, who was a respectable mathematician).
It's clear from the samples that El Naschie's articles are complete garbage, and I'm sure no respectable mathematician would want to publish in what's effectively a crackpot's vanity press. This is obviously the scientific journal version of Googlebombing.
So how did he pull this off? Is he citing himself, and if so, where?
If you want to automatically determine what constitutes a good journal purely from data, the definition is something like: is frequently cited by other good journals. Obviously, there's a circularity there. Various techniques attempt to mitigate it, but none are perfect, and indeed most are rather simplistic and easy to game. It's basically hard to distinguish, purely from citation data, a vibrant community of legitimate research from a vibrant community of crackpots.
In real life, most academics get around the circularity problem by starting with a set of "known good" journals that are determined by consensus in the field rather than algorithms (though this may sometimes be controversial). That lets them take into account more subjective things such as status of a research community (crackpots or not?). For example, as the linked article points out, the Annals of Mathematics is generally accepted as a top-quality venue for mathematics.
If you wanted, you could then construct an Annals-centric view of mathematical impact automatically by seeing how frequently other journals are cited by papers in Annals. This is what happens informally as journals gain and lose reputation: a promising new venue often first comes to a community's attention because its articles begin to be cited in "known good" journals.
But just taking all journals with no starting point, and attempting to extract from the citation graph which ones are "good" purely from the links, is doomed to failure, because there just isn't enough information in there to make the distinctions people want to make.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
The summary claims Chaos, Solitons and Fractals, has a high impact factor. The blog linked to, however, does not assert this, and I see no source for it. He does also co-edit the International Journal of Nonlinear Sciences and Numerical Simulation, which the blog asserts "flaunt its high 'impact factor'." The link to the IJNSNS praising him is broken, so I can't confirm that.
It looks to me like some crackpot got a journal. However, it doesn't seem particularly devastating. Nobody has based work on his articles purely on the basis of the "Impact Factor." I don't think anyone else is taking him seriously. At worst, libraries have paid to subscribe.
Oh, snap!
Seriously? There's a lot of high-quality CS research out there in the journals and conference papers; of course there's also a lot of crap. But I'd say most of the crap comes from wishful thinking rather than pure crackpottery. If nothing else, if you try to implement something that doesn't work, you'll know immediately -- thus CS at least potentially has a built-in reality check that pure math lacks. I rather suspect that whether or not a CS journal demands working code from its authors is a strong predictor for the quality of the articles which appear in that journal.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
This has been a fascinating case of Crackpottery. Read the blog and the subsequent replies. El Naschie seems to make it (Quantum Mechanical babble-speak) up as he goes along ,but unless you are an expert in this area, as Dr. John Baez is, it would be difficult for the casual reader to discern this. This is similar to the Bogdanov affair, another well know scientific scam. ( http://en.wikipedia.org/wiki/Bogdanov_Affair )I'm a little surprised it took this long for Slashdot to discover this one.
One other thing: One of Baez's beefs among others is that this bogus El Naschie journal is bundled with more respectable journals and Elsevier profits from the bogus science.
Glad to be of service.
You realize, of course, that the only reason I was able to use a computer analogy is that we're talking about pure math. If we had been talking about CS, I'd have had to go with a car analogy right off the bat.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
And it gets worse when money becomes involved. Pseudoscientists and crackpots often try to find "investors" for their schemes, and even a layman who performs due diligence can be fooled when publishers like Elsevier become enablers for pseudoscience. When the paper shows up in an INSPEC or Web of Science search, how is the person being scammed supposed to know that the paper isn't really legitimate?
Many "free energy" scam artists already have patents for their nonsensical inventions, thanks to the laxity of the USPTO. It'll get worse unless these "pseudo-journals" are exposed and publicized to the greater science and engineering community, as well as the public at large. I had never heard of El Naschie before today, because I'm not a mathematician; thanks to this article, more people like me will now keep an eye out for his future "work".
Much like anyone with a working knowledge of CS probably has the ability to verify the CS research, math is a rather logical science which is often pretty easy to verify. Sure sure, there are things that are hard to confirm based on the amount of calculations that must be performed and irrational numbers and all that (infinity is a bitch to test), but those things exist in CS as well.
Its silly to some how imply they are vastly different from each other, they are in fact almost identical to each other.
Persistent Volume manager for Kubernetes - https://github.com/dwimsey/openshift-pvmanager
Alas, something I discovered to my sorrow over the years is that sufficiently specialized math is indistinguishable from gobbledygook (and vice versa).
Researchers in just about every field build on layers of other researchers' work. There simply isn't time to go back and verify every result in the reference tree of every article you site -- if you did that, you'd never get any original work done! Creating code that compiles and executes properly doesn't guarantee that everything you've based that code on is correct, of course, but it's a good sign. I'm not aware of any equivalent reality check in pure math. Now, I know relatively little about the field (applied CS and statistics is my game, specifically bioinformatics) so I'll happily accept a correction on this point.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
Yea, I read through a bit of the cited paper and got a few good laughs out of it. Maybe he's being published more for the humorous aspect of it all than for the actual information.
Perhaps it's an experiment: He's a mathematician. Now he's just demonstrating how the Impact Factor is a poor metric, and will soon present a superior measure that correctly ranks the journal poorly. ;)
ASCII stupid question, get a stupid ANSI
People used to say about a mathematician or physicist that "what he is doing is so important that only a few people in the world can understand what he is talking about."
In a few cases it was actually true.
Also, there were mathematicians who believed that the highest form of mathematics was work that had no practical application. There was a story that the inventor of matrix theory expressed pride that he had invented a form of mathematics with absolutely no practical use. Little did he know how extensively his work could be used. He would have been appalled.
There still seems to be a feeling that the less people are able to understand a paper in a math journal, the more important the paper is likely to be.
At one time I was a subscriber to the Annals of Mathematical Statistics. Papers in math journals usually assume that you know every paper previously written by the author and the others in the field. There is often very little introductory material and no tutorial material in these papers. Even if you have a general understanding of the topic, you can't follow the papers because they are written very concisely, and assume that nothing needs to be explained if it was ever published anywhere else. You may have to backtrack for years of someone's papers and still not be able to understand the paper you are trying to read.
This is probably a combined consequence of "publish or perish" in academia and page limits in journals. It is often hard to tell if a given paper makes any sense or is useful.
I guess you could call it job security through obscurity.
Excluding references to the same journal is too harsh a criterion, since a lot of high quality papers get published in high quality journals. What should be perhaps excluded, though, is self-citation (whether to your own articles in the same or a different journal). Also, papers published in a journal by a journal editor shouldn't count.
First, assume a perfectly spherical car of uniform density...
Mart
"I know I will be modded down for this": where's the option '-1, Asking for it'?
Elsevier, just like other large commercial publishers of scientific journals, offers libraries a significant discount if they subscribe to their whole catalog.
By including crappy, useless and inexpensive (for them) journals, they can siphon more money out of universities and into the pockets of their shareholders, as is their god-given duty as capitalists.
I guess that the way to test this would be to get a non-existent paper listed in Physics Abstracts, and cited in one or two major papers, and then see how many subsequent papers simply add the citation to their own list.
Eric Baird
which is why academic publishing is seriously screwed up. the public pays taxes to fund most academic research, but then researchers have to pay journal publishers in order to get their papers published. and in return, the publishers retain the copyright to all public research, keeping it out of the hands of the tax payers who funded it (and charging Universities up the ass to have access to their own research).
people used to justify this commingling of academia with commercial interests by the peer-review process involved in journal publication, but the peer-review process provided by academic journals clearly isn't working here. at this point, it would be far better for Universities to publish their own research papers, allowing public research to be made freely available to students, researchers, and anyone else who might be interested in it.
research papers could be published in online databases where they would be archived for easy public access. it's easy enough for independent writers to self-publish and distribute their writings online. so it should be no problem for Universities to do the same. the peer-review process of papers submitted for publication could be handled either by the University itself, or different Universities could get together and form an agreement whereupon they would review one another's papers for free. this would keep academic research purely non-commercial and eliminate potential conflicts of interest.
eliminating/bypassing commercial publishing houses would also mean that societally beneficial projects like Google Book Search wouldn't be stonewalled by greed-driven publishers, and public good could be placed before corporate interests for once. Wikipedia is nice and all, but serious research would greatly benefit from all academic research being made freely available in a searchable online database for all to access. after all, public research isn't very useful if no one has access to it.