Fraudulent Publishing in the Mathematical Sciences
arxiv.org
arxiv.org
I know for a fact that the number of fake-journals exploded once the Govt. of India decided to use this for promotions.
It's a bit sad really: in the classical world both these countries spent inordinate amount of time on the questions of epistemology (India esp.). Now reduced to mimicking some silly thing that vaguely tracks knowledge-production even in the best case in the West.
Has this always been an issue in academia, or is this an increasing or new phenomenon? It seems as if there is a widespread need to take shortcuts and boost your h-index. Is there a better way to determine the impact of research and to encourage researchers to not feel so pressed to output and boost their citations? Why is it like this today?
Academic mathematics, from what I've seen, seems incredibly competitive and stressful (to be fair, so does competition math from a young age), perhaps because the only career for many mathematicians (outside a topics with applications such as but not limited to number theory, probability, and combinatorics) is academia. Does this play into what this article talks about?
I think some of this has to do with... resentment? You're this incredibly smart person, you worked really hard, and no one values you. No one wants to pay you big bucks, no one outside a tiny group knows your name even if you make important contributions to the field. Meanwhile, all the dumb people are getting ahead. It's easy to get depressed, and equally easy to decide that if life is unfair, it's OK to cheat to win.
Add to this the academic culture where, frankly, there are fewer incentives to address misbehavior and where many jobs are for life... and the nature of the field, which makes cheating is easy (as outlined in the article)... and you have an explosive mix.
The introduction of this article [1] gives an insight on the metric used in the Middle Ages. Essentially, to keep his position in a university, a researcher could win public debates by solving problems nobody else could solve. This led researchers to keep their work secret. Some researchers even got angry about having their work published, even with proper credit.
What that means is that researchers become much more risk averse, and and stay in their research area even if they believe it is not the most interesting/imapactfull. You just can't afford to not publish for several years, to e.g. investigate a novel research direction, because without the publications it becomes much much harder to secure funding in the future.
The demand for novel knowledge is always high. It is the supply that is short.
That’s why we hang around on HN hoping for something novel of true interest. You get a good find every once in a long while.
And I completely GP, having been in or in contact with academic research since the late 90's, there has been a very strong shift from a culture where the faculty had means for independent research, and were trusted to find their own direction, to the system we have today where a research project has much tighter overlook and reporting than most corporate projects.
A professor with a 4-5 person group will typically need two staggered pipelines of 4-5year funding projects to run risk free. In the EU it is virtually impossible to get funding for projects that do not involve multiple countries, so you need to set up and nurture partnerships for each project. Coordination the application process for these consortia is a major hassle and often outsourced at a rate of 50kEUR + win bonus. And you of course need to run multiple applications to make sure to get anything. When I talked to mentors about joining academia around 2010, the most common response was "don't".
[0]: https://en.wikipedia.org/wiki/New_public_management [1]: https://en.wikipedia.org/wiki/Financialization
Its important to note that somehow we see the erosion of families, infractures and institutions everywhere but we never talk about the giant f'ing elephant in the room.
Math is particularly susceptible to this because there are few legitimate publications and citation counts are low. If you are a medical researcher you can publish fake medical papers but more easily become “high impact” on leaderboards (scaled by subject) by adding math topics to your subjects/keywords.
It's hard, specially if you have to compare people of different areas (like algebra vs calculus) that have different threshold for what is a paper worthily result and each community has a different size and different length of review time.
Solution 1) Just count the papers! Each one is 1 point. You can finish before lunch.
Solution 2) Add some metrics like citations (that favor big areas and areas that like to add many citations). Add impact index (that has the same problem). How do you count self citations and citation rings?
Solution 3) Cherry pick some good journals, but ensure the classification committee is not just making a list of the journals they publish in. Filter the citations, or add some weight according to the classification.
Solution 4) Give the chair of the department a golden crown and pretend s/he is the queen/king and can do whatever they like. It may work, but there are BDFL and nepotist idiots. Now try scaling it for a country.
Solution 5) RTFA. Nah. It's too hard. Assume you have 5 candidates and they have 5 papers in the last 5 years (or some other arbitrary threshold). You need like two weeks to read a paper, more if it's not in you area, perhaps you can skim it in 1 or 2 days, but it's not easy to have an accurate understanding of how interesting is the result and how much impact it has in the community. (How do you evaluate if it's a interesting new result, or just a hard stupid calculation?) You can distribute the process of reading the papers, but now you have the problem of merging the opinion of different people. (Are your 3/5 stars the same that my 3/5 stars?)
My favorites from that table:
- “fuzzy logic” becomes “fluffy rationale”
- “spectral analysis” becomes “phantom examinations”
- “big data” becomes “enormous information”
It really is a terrible thing, though I can understand how some researchers feel trapped in a system that gives them little if any alternative if they wish to be employed the next year. Not just one thing needs to be changed to fix it.
Not anymore :(
The problem of AI generated papers is much more serious, although not happening on the same scale (yet!).
My take: I’ve published in well-regarded mathematical journals and the culture is definitely hard to explain to people outside of math. For example, it took more than two years to get my key graduate paper published in Foundations of Computational Mathematics, a highly regarded journal. The paper currently has over 100 citations, which (last I checked) is a couple times higher than the average citation count for the journal. In short, it’s a great, impactful work for a graduate student. But in a field like cell biology, this would be considered a pretty weak showing.
Given the long timelines and low citation counts, it’s not surprising that it’s so easy to manipulate the numbers. It is kinda ironic that mathematicians have this issue with numbers though.
The now-standard bibliometrics were not designed by statisticians :-)
It is what we could call the “zone of occasional poor practice”. Included are actions like
I think this is more common in computer science papers. I see this all the time, where 5- 10 authors will collaborate on a short paper, then collaborate on each other's papers in such a way that the effort is minimized and publishing count and citation count is maximized. .
Everybody in the field cite that paper going forward, giving it a massive impact factor, making impact factor useless. Do this occasionally, randomly, do it in niche sub fields, everybody who goes to a conference put their name on the paper “we had a nice time at <conference> this year.”
I mean, it is something everybody hates, right? There’s no point in preserving it.
On the individual level, there's another tricky problem, which is that very few individuals could figure out an alternative performance metric that beats the established one, no matter how gamified the established one is.