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Co-author uses ChatGPT for academic writing - is it ethical?
I am writing a paper with a co-author. I spent a considerable amount of time (several months) writing a first draft of the paper. I then sent it to co-author asking them to revise the draft and add their contribution in specified sections.
The co-author returned the draft within a few days. The required parts were added and the writing was heavily edited. The style of the new document looked similarly to a few other documents that I knew were produced by ChatGPT. I asked the co-author and they admitted (quite proudly) that they used ChatGPT to assist with writing and editing of the manuscript.
I was not happy with the resulted state of the document. There were several obvious errors, which I pointed to the co-author. But also, the whole document seemed a bit weird to read. I could not really define it, but reading it gave away a feeling that the document was AI-generated. I was concerned with the possibility that there could be other mistakes in the document, which are not immediately obvious, and that it could reduce the chances for the paper to pass through the peer review process.
I shared my concerns with the co-author. They agreed to correct the mistakes I noticed. They claimed that they checked the document after it was generated, but a small number of issues possibly remained. They dismissed my argument that the writing is unnatural and weird to read, and requested to point out specific line-by-line errors, which should be corrected. They suggested that I could proofread the document and edit it again before submission, since I have concerns about its quality.
I feel that co-author did not put sufficient effort in their writing, and leans on ChatGPT, my work as a co-author, and work of peer reviewers instead. This leaves a bitter taste in my mouth, but I do not know if this behaviour is unethical or wrong in some other way which I can't quite describe.
Are my concerns valid and how is it best to communicate them to the co-author?

My first language is not English, and the same for my co-author. I appreciate that ChatGPT can correct errors in the use of English and improve grammar. I am concerned that it might introduce factual mistakes, change slight variations of meaning, or generally make the text unpleasant to read (although as a non-English speaker I find it difficult to explain why it happens).

Even if there is disagreement on the ethics, it's totally normal to be pissed if a co-author butchers your writing. Authors should be open to considering the changes suggested by someone else but that doesn't mean that if someone rewrites your paper to be worse that they get their way because they touched it second. It's also extremely rude to make changes and then expect you to fix the things they screwed up.

@BryanKrauseisonstrike The co-author agrees to correct mistakes introduced by their edits, but insists that I should point them out since I believe these errors exist. They disagree with my assessment that the writing is unnatural and suggest that I should re-write it because this notion is not something objectively measurable.

I try to look at the bright side! I reviewed numerous math papers written in bad and overly concise English, lacking any explanations or context, full of mathematical jargon that the authors - after internalizing it - apply without thought or consideration, Now I'm looking forward to reviewing math papers written in flawless and overly wordy English, larded with misleading context and pointless explanations of trivialities, and still full of mathematical jargon that ChatGPT - after internalizing it - applies without thought or consideration. Who wouldn't welcome a bit of change now and then?

The effort is in identifying the mistakes (which they expect you to do), not fixing them. They don't have an objective measure that their version is any better than your original, either. Arguably, the presence of errors you've identified is the closest thing to identifying that their work is objectively bad. If a human had made a series of edits to a paper's language, they should be able to comment on why each change was made: e.g., subject-verb agreement, run-on sentences, terminology used consistently within the manuscript and within the relevant literature, spelling correction, etc.

Related: Is it OK to generate parts of a research paper using a large language model such as ChatGPT?. Also Is it OK to use GPT-3+ to rewrite your own paper to have better English?

Call me crazy, but the fact that the co-author didn't say up front they were using ChatGPT seems like a signal they're on a tack of sneaky, duplicitous behavior.

Note that even if there were no compelling ethical argument against writing a paper via GPT, you are still within your rights to refuse co-authorship of a paper which is of poor quality and might harm your professional reputation.

Perhaps worth clarifying the level of English fluency of the various individuals, and whether this is the driver for using ChatGPT.

This coauthor sounds like a very unreasonable person who considers you beneath them. I find it hard to imagine that you have any reason to put up with this.

Related question prior to ChatGPT: Is paraphrasing my own texts using online tools is okay? Moreover, regarding "They suggested that I could proofread the document and edit it again before submission", if you've put a lot of effort into careful and precise wording already, you're probably going to have a more difficult task in proofreading and reediting the document than initially, because you now have to look for possible "not quite right" phrasings and figure out how to fix them while adhering to the various other changes made.

Out of curiosity, do you use a version control system for your paper, like Git?

Two co-authors writing a paper in English, which for neither of them is a native language, is tough, and so I can understand the desire to do better than your own capabilities and also then the belief of your co-author that ChatGPT-written material might be better "English" than his English.  But native speakers will know it isn't natural English.  Just look at all the discussion (and the ongoing strike!) over at meta.stackexchange.com on how ChatGPT written material is obviously detectable because it is unnatural.

There is another issue: the entire contents of your original paper are now part of ChatGPT's database, which means someone else could wind up with your text in their paper.  That's how ChatGPT builds its database.  So effectively the paper has been leaked, even if not in an easily identifiable media.  Although I suspect the right prompt would allow ChatGPT to produce your original paper.   For this reason many businesses, INCLUDING the big tech companies with AI products, prohibit employees from submitting any internal materials to ChatGPT.

As to the validity of ChatGPT's output, you need to verify everything it did for correctness and double-check to ensure nothing was lifted verbatim (even snippets) from a previously copywritten source.

"requested to point out specific line-by-line errors" — Have they provided specific line-by-line reasons for every edit in the document?

I have been through this experience with a co-author cheerfully butchering the English language of a manuscript we were both working on again and again and all I can say is I feel your pain.  It's incredibly frustrating, especially when I am a native English speaker and he was a non-native.

You're right to be angry at this. It is unethical and many journals expressly forbid use of ChatGPT during the preparation of manuscripts (Science and all Springer journals).
I might be reading too much into this, but since you didn't tell them straight up that it is unethical, I assume that the co-author is a superior. You could identify a journal that forbids use of ChatGPT and highlight their policy to your colleague.

how is it unethical? Can you elaborate on that? Or is your argument that it is unethical because journals expressively forbid it? Can you briefly outline their argument in that case? The general advice to point to a journal's policy, ideally the journals the paper is being written for is of course a very good point!

@FrankHopkins it is unethical because it is plagiarism. The co-author did not actually author the text but is presenting it as though it were their work.

@terdononstrike that is arguable as no other person wrote the text and you would need to consider translation tools unethical then for the same reason. But if that is the stance of the author of this answer, it would make the standpoint/argument of the answer more clear if they added it. I.e. we don't need to discuss in the comments whether it is ethical, my main point for the improvement of the answer is that the answer does not include its reasoning for it being unethical - as that is part of the question and imho context depending and in general still in open debate that would be essential.

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I'm not sure using ChatGPT to write papers is necessarily unethical (assuming proper citation). I wouldn't recommend it and many journals have explicitly banned it from the author list - though this is generally based on the argument that AI cannot fulfill all authorship criteria. I think it can become unethical if one tries to pass of AI-generated work as their own.
I think editing papers with ChatGPT is even more of a grey area. There are already plenty of editing companies that provide lower cost services that rely on AI. How is using a tool like ChatGPT to rework a paper you wrote any less ethical than paying for an editing service (whether that service uses humans or their own AI).
With that being said, your co-author doesn't actually sound like they are contributing to the writing. Instead they are shifting the work onto you. I don't think using ChatGPT in and of itself is the issue. The issue is that they are trying to take a shortcut and claim credit. Assuming they have contributed in other ways you could consider letting them know you expect more direct contribution to the writing. Or perhaps say that while ChatGPT is a powerful tool, their contribution to the manuscript must be their own. Finally you can always just express to them what you have said here, that you don't like the results of the AI edited/generated writing.
The nuclear option (which might be appropriate if they have not contributed otherwise) is to tell them editing with ChatGPT is not sufficient for authorship. And thus, if they wish to remain and author, they must make their own unique contributions.

You can cite ChatGPT, but ChatGPT can't cite its sources.

@LukeSawczak you can feed chatgpt with bullet points it needs to formulate to a full fledged text and then insert the citations you got those factual bullet points from at the right places saving yourself the writing bits.

Good points about the general question of whether chatGPT is ethical. If it is generally unethical, then are non-native speakers also not allowed to generate their initial paper draft with a translation engine from a draft in their own language? And why do we accept the use of computers in writing a paper? Shouldn't an author write down every letter with their ink-dripping feather? It obviously depends a bit on how the tool is used, as a support tool or just to generate the whole paper from two sentences.

@FrankHopkins As my late great-uncle Brian said in his British accent, "Tha'... is no' a guarantee!" What it fills in between the headings can easily come from diverse, plagiarized sources. Citing the questions you asked doesn't mean you've cited the answers you've been given. As for the more significant differences between LLMs and other technological aids, I can't do better than mention my talk to the ACSE of Ontario in April: https://www.youtube.com/watch?v=GbF0WxiZzts

I'm not advocating for using ChatGPT to generate large sections of text. I'm not convinced it's impossible to do so ethically, but I would not try. I still don't think it's any different from existing editing services (especially since they already are starting to incorporate AI and LLM into their workflow). While your talk was interesting I don't think it's all the applicable...

@FrankHopkins using a computer for writing a paper does not cause any difference in the information conveyed in the text. Written by pen and later typed by somebody else, you would get exactly the same thing. For a translation tool, it's already not exact (and indeed a machine-translated paper should at least be double-checked by a bilingual human) but at least shouldn't have really extra information. But translating bullet points into prose actually requires filling in gaps, because bullet points are incomplete (else why not just write papers in bullet point form and leave it this way?)

@sErISaNo Thanks for checking it out -- not directly applicable to writing/editing except to argue that there is no production of knowledge (as there should be in publishing). Editing well is in my mind vaguely possible to boost with AI, even if a bad idea, but for writing meaningfully it's not possible.

@leftaroundabout obviously both aren't identical, but it seems to me there is an inherent feeling others need to do stuff manually because that's how we did it for aeons. I keep saying by the way that of course you need to proofread whatever AI spits out, same as with translations. The part where it helps is generate a nice text with full sentences that flows, is easy to read and perhaps adds details that one might need to correct. Going from bullet points to written out text costs time, that is why in some cases I'd rather have the AI do a first draft on which I can iterate.

@FrankHopkins the time it takes for the translation from bullet points to prose should be pretty insignificant though, compared to the time to come up with the original ideas / doing the research. And it's a good opportunity for re-visiting your thoughts and reconsidering the general structure. If you find yourself (as an experienced English speaker) spending too much time fleshing out bullet points, it's an indication you're writing too much boilerplate content, which is in itself ethically dubious.

@LukeSawczak Scottish accent.  British accent doesn't really mean anything as there are multiple countries contained in Great Britain.  It's like saying someone speaks Arabic with an Arab accent.

@Tom True. But being unable to specify where in Britain his accent was from (not Scotland, but somewhere else with glottal stop for final /t/), I went for the general and hoped it'd be understood!

@leftaroundabout lot's of things that one automates are overall negligible, but a) they add up and b) they free mental capacity so you don't have to switch thinking modes. Quite a few people have big issues with starting from scratch. I often would take an old paper as a template and then adjust, it'd be awesome not to worry about that step. Beyond that, just because something doesn't seem useful to you and your work process it isn't unethical or a problem for the output. This goes from "it's unethical" to "I don't see the point, so it's unethical".

@FrankHopkins I'm all for automation, but ChatGPT isn't an automation tool. An automation tool is one that does something in a well-defined manner which you would otherwise have had to do yourself. If something goes wrong with automation, you can step back and look where the problem happened, and change the procedure. ChatGPT meanwhile does tasks that are at best vaguely specified, and even when the results are useful then nobody knows how it actually did it. Or: useful results are actually an amalganation of other peoples' work, and that should be properly attributed which ChatGPT doesn't do.

@leftaroundabout all those points are valid regarding how AI operates (this kind of), but in this context I feel them totally misplaced. I'd worry for things like AI driving my car but here you have a safe gate where you can manually check and understand the output before it is anywhere else applied. When you start writing you don't have a fixed text in mind either, so that the automation does automate that process of writing "some text".  there is no "determinism" in my automation definition, it's just that some task I would need to do myself is done by magic, err a machine.

@leftaroundabout from my point of view most criticism I've seen go against bad usage of AI tools, not really against AI tools themselves. e.g., assuming you just have the tool write a paper out of a couple sentences you hand it and then hand the paper in like that -> I agree that is unethical because the tool is not properly used; and I agree OP's colleague acts unethical by misusing the AI tool and not respecting OP by simply rewriting a complete section (exception: they are advisor and OP inexperienced undergrad). anyway, I think we're past improving the answer, so thx for the exchange^^

@FrankHopkins I see it quite the other way around: AI-driving-my-car is ok as long as it's statistically safer as my human driving. I don't really care how the driving happens after all, it's just a means to get to a destination. But writing is not just a means to get to a destination. The whole point of writing is to facilitate human understanding. That's subverted if a tool which nobody understands sits in the middle of the process.

...And if you say the particular job the tool does is unimportant, "just bullet points" - well, let's get rid of the job entirely then! There's a point to be made that papers aren't the best way to convey research, IMO a combination of well-typed and well-documented source code with interactive/video presentations may be the future. But if we don't do it with tools we understand, then we're on a slippery slope indeed where more and more of the research will be done by ever-smarter AIs until we don't understand anything at all.

@leftaroundabout okay that last bit is funny; that basically means anyone but a handful of CS scientists are on unethical footing, because most scientists won't be able to tell you how the PC they write their paper with works. They can check that the output matches what they wanted to say though. Which is exactly the same as (properly used) AI text generation. you have to check and understand what it provides you upon your input. If that distinction doesn't get across, well, I guess I should give AI a chance to formulate it as my manual approaches seem to fail. ;) Anyway, good night or day.

I share your distaste for your coauthors use of ChatGPT, but I would not go as far as to say that any use of ChatGPT for academic writing is unethical. The following, however, is deeply disrespectful:

They dismissed my argument that the writing is unnatural and weird to read, and requested to point out specific line-by-line errors, which should be corrected. They suggested that I could proofread the document and edit it again before submission, since I have concerns about its quality.

Your coauthor has made far-reaching changes to your draft, changing the tone and flow of the text, and introducing enough obvious errors to raise serious concerns on your side. It seems that your coauthor has not pointed out any specific line-by-line errors to you, and they have not proofread the document themselves. To follow through on the parallel with your coauthors own words above; they seem to have no concerns about quality.
This attitude is deeply disrespectful. It shows that your coauthor has little regard for your work and does not value your time and efforts at all. A respectful yet effective way to point this out is to simply return their request to them. A message along the following lines should do, perhaps with some fluff depending on culture:

Thanks coauthor for going over my draft, and for addressing my concerns about the quality of your version of the draft. I've proofread it and edited it again, see the attachement. If you find any more errors or room for improvement, please point this out specifically line-by-line.

Of course you attach your original draft.

Well I wouldn't call the response " A respectful yet effective way" it's passive aggressive and escalates the situation. Is it appropriate, perhaps. But respectful, not really, certainly not diplomatic. That might still fit, since the other person was not respectful either with their rewrite... but then you might word is as "An equally non-respectful way" ;) I upvoted, but imho it should be clear that this "opens the battle", even if not completely direct.

@FrankHopkins I completely disagree with you. OP has the right to ask his/her coauthor to reach a certain quality standard if they are going to work together. You are not rude by asking someone to do properly their job (or, at least, to make a serious effort to contribute).

@Amelian it's not about pushing back but how.

The "respectful yet effective way to point this out" is more akin to "the nuclear option". Depending on OP's relationship with coauthor, this could easily make things worse.

Many journals now allow the use of ChatGPT as a writing tool, similarly to grammar checkers or paid services, provided you leave a notice in the manuscript. Many journals have got text snippets on their website.
It depends on the journal. Many require a disclaimer similar to:

ChatGPT has been used in the writing for the purpose of [....]. The authors take full responsibility of the output.

With regards to your co-author, the main problems are:

Lack of proofreading
despite ChatGPT being very error prone at this point
no concern that ChatGPT's writing style is grammatically correct but very unnatural and sterile
altogether, lack of effort in the project

Your co-author is too lazy to put in his own time into the project and too dumb to use ChatGPT appropriately, thus having a negative impact on the project. Don't work with him or her.
Life advice: who misbehaves once will also misbehave again, and you should axe them as soon as you can.

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The title ("ethical") and the question are slightly divergent.
Personally, I think the issue is not so much ethics as long as the source (ChatGPT) is mentioned. However, given that the latter, in turn, does not cite its sources, clearly the acceptable ethics around use of the bot is still evolving.
"I could not really define it" - that, in my opinion, is the real crux of the problem. ChatGPT generates a strangely synthetic text, a bit too smooth to be true, while possibly introducing hard-to-find errors.
Now, I, for myself, very much do not like having my text substantially altered without good reason, because while writing it, I form a model of what I want to say and, if it's well structured, when revising for errors, I need only to fix the minor errors that remain to adjust. A complete rewrite forces me to re-read the text as if it is new, as if it comes from a third party, in other words, it is possibly even more work than writing it myself. Of course, when you collaborate, that's what you have to do, but if it is text that you wrote yourself and when it is your duty to write that section, that's a real nuisance.
I usually also will not rewrite other people's sections. I will comment and make suggestions, but try not to reformulate complete sections (maybe I would individual sentences - but not the full structure of thinking).
Perhaps the best analogy is code. It is easier to understand one's own code and understand why it works (or it may fail) than to try to understand someone else's. Sure, someone else may spot subtle bugs etc., but the overall structure - in general - is best understood by the author and best not changed without consulting the latter.
In short, your gut feeling is perfectly justified. The co-author took a text where you spent time and effort making it understandable and mangled it through an intransparent process. Now, they dump on you the effort to make sure that this mangled result is correct, while ripping out all mental support scaffold that you built while writing. This is not on. It is like auto-reorganizing your desktop without asking you and without good reason.
This is unethical, simply, because it is creating unnecessary work for you. It's just not a good collegiate behaviour and shirking off their duty to quality, accuracy, reliability and correctness of results.
How to communicate: tell your colleague that you spent a lot of time getting your contribution of the paper right, and do not have the capacity redoing the work effectively from scratch, by trying to sort out all mistakes that the bot introduced unnecessarily. If they decide to write their part via bot, you need to read it as if it comes from a third party and check meticulously for errors. That they expect a line-by-line pointing out of errors is a sign that they do not take your time seriously or they do not understand how the bot works. You need to decide if you push back to remove the errors or, after the second "review" round, say, "now you fix this". I have done that with code development - after having been told for the 4th or 5th time that my library contained the bug in a software we developed, and it wasn't, I told the colleague, "no, the bug is in yours, please fix it".
This is not really ok, and you can warn them that you have to declare the ChatGPT contribution (you may be found out anyway, there are checkers for this now, so hiding that fact is not an option, in case they should contemplate it) which may affect the paper's acceptance.
If they dismiss your issues, you need to consider the option of splitting the paper if that is at all possible.

There are already several good answers regarding whether your concerns about your co-author's behavior are valid (they are), so I will focus on the second part of the question:

[...] how is it best to communicate them to the co-author?

Your co-author used ChatGPT without telling you, later admitted to using it after you asked them about it, and yet seems to still be under the impression that lightly edited AI-generated documents are indistinguishable from quality writing by a human. They are not: the fact that you took sufficient issue with the writing  that it prompted a discussion about your collaborator's use of AI tools is strong evidence of the contrary, and something I would emphasize. If you found the writing bad, other readers are likely to find the writing bad. If your collaborator cannot see the difference, that's a failure on their part, and a sign they should definitely not use ChatGPT in the way they do, because they currently do not have the skills to transform the output of ChatGPT to the point it would be considered good academic writing.
Your co-author might then say that of course, ChatGPT's output needs some additional polishing to meet the quality standards of good published research and properly reflect the ideas of the human authors, and it is merely a tool to get a quick draft and/or some ideas. There, I would make the following points:

Some people might get to a good document faster by editing a first draft generated by ChatGPT, some people might find it slow and painful work to modify the output of a Large Language Model to the point that it's no longer the AI's writing. Even if one thinks ChatGPT is a great help in their writing, one cannot expect that it's the case for other people, and should ponder whether that's how their co-authors work best and whether they're wasting their co-authors' time.
Hiding how a document was generated is bad behavior in a collaboration. In the same way that one might not spend as much time checking grammar if one's co-author is a native English speaker, one does not proofread an AI-generated document in the same manner as one written by a human. In other situations, for example more time-constrained ones, you could have just blindly trusted that your collaborator did a good job, and ended up sending a bad manuscript to an editor. Your document might also get flagged for plagiarism because ChatGPT gave similar looking text to several of its users, or copied stuff almost verbatim from the internet.

Do: ask ChatGPT to find grammar mistakes in a text, or to suggest synonyms and alternative ways to convey some ideas, and use its output to improve your writing. Don't: ask it to produce several pages of output at once, edit 10% of it, and send that to your collaborator without disclosing that's how the document was produced.

Since it feels like an AI-generated text and contains obvious errors, it suggests to me that the co-authors just copy pasted the ChatGPT output, which seems like a terrible practice. From what you wrote, it seems that they might have even copied pasted the whole document. That honestly seems unethical to me, as it suggests that they would have tried to publish something that they are aware might not be true or might have been plagiarized. So I would say that your concerns are definitely valid. So if I were you, I would definitely not cooperate with them ever again. As to how to communicate it... The only thing that I can think of, that might end in a positive outcome, is to find a native English speaking person, who can identify the obviously AI-generated parts, and who can verbalize, why they feel off. Otherwise I am afraid you will have to either bite the bullet in some way, or to be very blunt with the co-authors and force them to put the effort in.
That being said, I find the opposition to ANY use of ChatGPT for academic writing in the answers/comments bizarre. People seem to act as if you have to put what ChatGPT generates exactly the way it is generated, even if it is wrong or feels wrong.

I would argue that using ChatGPT is unethical (plagiarism) or inaccurate (often just lies). I think if ChatGPT is used it definitely has to be cited.

In my opinion usage of GPT is scientific misconduct. The core of science is citing the source of information correctly, so that it can be tracked back and put into context - and errors can be found.
As of now, if you let GPT make statements on your behalf there is not way for you to figure out (and thus you can not cite it correctly) if a certain statement/fact is actually derived specifically from a reference (even if you ask gpt to give these) or if that is actually only a reflection of what chat gpt typically would find referenced to statements relating that topic. So that means that in the core you make it completely impossible to trace back "your" logic and reasoning to it's original sources.
As a side effect there is no way for your coauthor to tell (without reading the citations) if that referenced paper actually says what is implicitly or explicitly stated or if gpt just found it typical to mention that one.
My recommendation: revert you paper to the state which you gave your coauthor, go to the supervisor/principal investigator or person representing the project and ask them about rewriting the paper without relying on contributions from said coauthor. If the coauthor is part of an institution, address the issue to the appropriate office there.

Neither myself nor my co-author are at the stage of our career when we have supervisors, but your answer might be helpful for a PhD student in a similar situation.

For most topics the risk that gpt generates enough text that is a copy of a source to count as plagiarism is about the same of you generating a text that looks like a copy of a source and counts as plagiarism. If a concept summary is complex enough to need a source for the underlying concept, you need to manually add that if you write it yourself as well. Can you back up that general statement that gpt specifically comes with a higher risk than a text you write from memory a bit by any references? ^^

@FrankHopkins: If you manage your sources properly, you can assure that. And yes, i would expect that i manage sources relevant to a central argument in my paper carefully.

@Sascha if you do that, then you can insert it into the relevant generated parts as well. My point here is that there is a difference between unsupervised AI generated stuff (directly submit what you have an AI generate) vs. supervised generated text (you use AI as a tool for e.g. a draft of a section). Your answer doesn't distinguish between how you use AI based tools, but is universal, so I asked for something backing up those arguments in their generality or alternatively putting them into some more specific context.

@FrankHopkins: The question was about the use of chatgpt. Obviously a careful redaction process reduces the risk of accidentally making statements without attribution to the right sources. Investigating why ChatGPT made a certain statement is impossible since ChatGPT (by it's own statement) has no direct input from peer-reviewed articles. This means that it's not clear where a statement like "qubit type x is known for it's long decoherence time" is based upon. And for me the correct scientific way in not to later identify a potential (most likely) reference but the one which the author used .

@Sascha okay, to me it doesn't matter whether you can ask chatgpt where its quotes come from, it is your text in the end and if you're a domain expert you can verify and enhance it. So if the author had a single source to base their knowledge on they can add it and if they didn't they might find their primary source know that they learned something (though ideally at that stage they should know the material about which they ask the AI to write, but hey, different people different approaches). Anyway, maybe add that reasoning to the answer. I personally think it's logically flawed/assumes

@Sascha a certain usage and ideal way to work that isn't necessarily universal, but it would imho make the answer more clear in general. Especially the first sentence is very universal and to me the rest does not seem to back up that universal statement, so maybe you can add parts of the discussion here to set that in context. Anyway, have a neat day.

Using GPT to write papers is completely unacceptable. This doesn't mean using it at all is bad- I use GPT literally every day for things like Python questions, debugging, or translating code to do a certain thing.
However, every single word in my papers is written by me or by coworkers. So, you're totally correct to be upset with them, that's NOT how this works. Every word on the page needs to be your own, not GPT's.
Edit: because passing another entity's words as your own is plagiarism.

This answer doesn't seem to contain any reasoning, just personal opinion.

I disagree. @Sneftel either way, the reason is because it's plagiarism, passing off another entity's words off as your own. If a student uses GPT to write large swaths of a paper, it ceases to become their own contribution. This isn't "opinion", this is just how plagiarism works.

So in your opinion, if the author acknowledges the use of ChatGPT, there's no problem because there's no plagiarism?

I strongly agree with this answer... :)  Especially the wording "passing [off] another entity's words as your own is plagiarism" :)

@Sneftel No, you seemed to miss my point about "large swaths". As academics, we quote and cite things all the time, sometimes at great length. However, at some point this has bearing on the originality of ones own work. For example, if a history student literally quoted books for 90 percent (say) of their term paper, this is plagiarism, even if they cite everything correctly. In other words, they are not mutually exclusive ideas. A work can be unoriginal but not plagiarized, can be both, or can be one or the other. Specifics matter.

I don't see any ethical issues in using ChatGPT or some other automated systems to help write a paper. Just make sure that the publication target allows it eg see https://academia.stackexchange.com/a/193049/452 and if you generate large chunks you may also want to check for plagiarism.
If you are unhappy about your coauthor's work quality, that's a different issue.

ChatGPT is a great tool but it only reproduces existing content or combines it in an unvalidated manner: It should, hence, generally be avoided when writing original articles. If not scientists, whoelse will in the future deliver original human content for tools such as ChatGPT? So, I'm so glad to see that journals and (in the meanwhile) many other organisations begin to ban it and related tools. However, it should be said, outside science, ChatGPT will become incredibly useful. But within science, ChatGPT must be very harshly regulated to the ultimate utmost ... by any means.

@Mario the human validates. Introduction and related work often don't have much novel content.

Difficult point, perhaps. In my field, CS, an introduction is often quite concise and actually quite rapidly written. Perhaps in other fields, it might help, in my context, not so much I guess. Anyway, if you start allowing it here and there, where do you stop? My concern can be summarised by the term "contamination". Contaminated content looses "truth" value if you will, much in the sense of a gain in entropy, which usually is not so cool.

@Mario This "contamination" idea seems based on a weird assumption of what it would be used for. you don't let it generate science, you let it formulate your science and use it to help express yourself faster.

@Btw. especially in CS I would feel it could be very helpful, e.g. if you want to generate an example program, or structure something with a bit more complex Latex, you don't need to know how to do so completely yourself or look it up - you generate something with the AI and then adjust it where needed.

@Mario So AI-generated articles on the ethics of using AI to write articles would be fine? Science journals aren't the only ones who expect original content. I don't know why you'd think original content creation was peculiar to only scientific disciplines. Even outside academia, do we really not care about originality in novels, say? Or poetry?

Ok, @FrankHopkins, I appreciate your points. In my own field, generating and formulating science is not so well separable. I'm doing logic and maths stuff, so, the main method of generating science in my context is writing up my thoughts. And it seems vastly unnatural to me let a tool such as ChatGPT interfere with that quite inseparable process. However, using ChatGPT like a pocket calculator outside my research seems highly useful. Anyway, perhaps I'm speaking for a quite narrow group of people here.

Dear @cfr, it was not my intention to exclude creative domains like the ones you mentioned. I fully support the regulation of ChatGPT there as well, in principle, whenever it is important (for whatever reason) that one can rely on the artefacts under consideration being actually generated by humans.

@ctr It's weird to automatically assume "written by AI" = no novelty. You can give an AI engine bullet points of what your article should say, that are all novel. You can create a story with characters not existing before and let AI hash out the textual details. That is novelty. Now, ideally - with the current level of AI - the text is curated too and just taken as a first draft, because it likely will read...dry in my experience, but this equation of "man-written=novelty, ai-generated text=no novelty in what the text says" seems totally illogical to me. Man still drives the content.

@Mario I also totally agree that there are areas/tasks where it's a totally misplaced tool, especially in its current form. There is currently from my pov just two a bit extreme sides, one that wants to apply shiny new tool to everything and one that wants to see it banned from everything and talks it down all the time. Both seem to fuel each other, e.g. because a lot of the hypers don't really understand its limits and the other way around people jump on examples where it produced "crap" and overgeneralize. My point is just that the ethicality cannot be judged that universally that easily.

@Mario + I agree there is risk of misuse, but, perhaps that also helps to improve actual quality control^^ From my pov, it does not make sense to prohibit tools in such a general way in this context, as it typically depends on how they are used regarding whether they produce something of scientific value. I'd rather prefer to have clear quality requirements/checks independent on the tooling used to generate the paper/contribution (and yes, a paper generated by AI out of thin air should fail those and be ethically shunned, for quality reasons). Anyway, guess we're past improving the answer^^

Fully agreed, Frank. Reading your comments, I see we are pretty much on the same side. It'll have to be seen how regulation and quality control can play together fruitfully.


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Submitting a paper that contains the researcher name to a conference that employs double blind reviewing
Me and my co-researchers are submitting a paper regarding speech recognition to a conference that is held by the university where we study. In this study, we, strictly for the purpose of trolling, included our co-researchers name into the dictionary for speech recognition. Curiously, the performance of the speech recognition at recognizing the researcher's name has generated interesting insight for analysis. The analysis works by breaking down the phonetic of the researcher's name. The usage of the researcher's name is crucial since the researcher's name provides the best example.
Unfortunately, the conference that we're submitting to employs a double-blind peer reviewing system and my researcher whose name we used is widely known in the university for his achievements and trolling so it's very likely the reviewer knows him.
Is there anything I can do to mitigate this besides submitting to a different conference?

can you not find a single other word that generates the same effect?

It is hard to see how it would be obvious to a reviewer that the researcher whose name is used is also an author. In this case there should be no issue about reviewing.
But, you could also inform the conference chair and ask for advice there.
In some similar cases it might be possible to obfuscate the name for review purposes, but your description indicates that isn't possible here. But, you might need to change a few phrases if they make the relationship explicit. And note, also, that the final version is normally a bit different from the reviewed version. Reviewers themselves often suggest changes.

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Applying to Ph.D. as M.S. student but failing to complete M.S. after admission
I'm currently studying for a qualifying exam required by my M.S. program to get the degree and have also applied to continue onto a Ph.D. elsewhere (all of this in the U.S). This situation got me curious about a weird edge case:
What is likely to happen if I get accepted to a Ph.D. program, but later find out I have failed my qual/will not receive the M.S. degree?
I realize that no answer to this will be universally applicable, but the reason I ask is because I already have a B.S (what most of my fellow applicants have) and they don't necessarily know that my M.S requires a qual in the first place (so admissions decisions were probably made taking into account my coursework, etc.). So, on the one hand, it seems like even supposing I didn't receive the M.S. I am still an applicant with the same credentials as my fellow applicants + two years of additional grad level coursework + 2 years of MS project + 2 years of Research on top of these other things. On the other hand they accepted me expecting another degree which I don't have.
I'm not too worried about this personally and intend to pass, but I was curious since it is a real possibility for me (most people get 2 or more chances at the quals, but since I am changing fields a bit I wanted to take certain classes to help in Ph.D. admissions during my first year and ended up with only one shot).
It would be nice if this got answered as generally as possible for future worriers, but if more specificity is needed I did a math undergrad/M.S. and applied to Comp. Sci. for PhD. Also, the M.S. was not done to bolster my record but instead just because I found funding and got more time to explore before jumping onto the PhD "treadmill" as some of my professors have described it (meaning, my undergrad would have made me a good math applicant with research experiences, 3.6+ GPA, strong letters, from a respected school, etc. should I have decided to apply straight out of it).
Anyhow sorry this got long, I was just trying to walk the line between keeping it general and making it unanswerable haha. (Also, as a little aside, I can retake it late in the summer but it'd be a pain travel/housing wise).
tl;dr
Accepted into PhD while in a MS elsewhere, but failed exam required for MS (all in USA). What happens?

I would say it depends on the offer/acceptance letter you receive. I know someone who was accepted to a PhD program while doing an MSc, but whose funding (scholarship) depended on him getting a certain final grade on his MSc. I can imagine situations where that is not the case, and where you are accepted to a PhD regardless of what happens with your studies before the PhD program begins.

The answer is simple: you lose your Ph.D slot.
When you are accepted in a Ph.D program and still need to finish the M.S the acceptance is conditional. You need to finish successful the M.S before the date stipulated by the Ph.D program.
This case is always foreseen and the rules are published in the call.

This still applies even if the requirement for entrance is a B.S and not a M.S? (i.e I'm asking if you're answering this assuming the PhD program requires their students come in with a MS like some other fields and/or countries vs. you're answering this knowing the MS isn't required but knowing that I am in the MS and applying means it became required for me unofficially)

This is very specific, it would require to consult the rules of the call. However, if they took into account your posible M.S title as something that put you ahead of other candidates, they could require you to finish the M.S even if the program accept B.S candidates.

Thanks for the answers! This uncertainty/poorly informed questions is in part because I have no idea what level of detail these calls usually will contain, etc. (When I applied to my MS I was already in the dept. and knew people so it was very casual)

It boils down to two possibilities:

you have been granted conditional access (you can access only if you complete M.Sc);
you have been granted unconditional access (you do not need your M.Sc to access the Ph.D).

Please note that a M.Sc is not necessarily a prerequisite to a PhD, as well as a person can become a professor at university without having a PhD (increasingly rarer nowadays, country dependent, but still possible). It all depends on the local/regional/national regulations.

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Is there a reason a TA and a professor may have to travel together?
I don't work in academia but I'm working on a screenplay set in that world. I was wondering if there might be a reason for a TA and a professor to travel together for work. If the professor were attending an academic conference, would it be normal for the TA to go with? Thanks!

Often the TA is the professor's student, in which case they will often attend conferences together.

A teaching assistant? Not unless it's a pedagogy conference. A research assistant, maybe.

@aeismail The TAs of my courses are also PhD students of mine, so indeed we frequently go to conferences together.

@MassimoOrtolano: Yes, but they're not going to the conference because they're your TA.

Thank you for the responses, everyone! Is there a reason why students attend conferences with you? In the case of my screenplay, the professor is teaching a creative writing class and the TA is her student.

Why set your screenplay in an unfamiliar environment?

The closest bond is between a student and his or her thesis advisor.  I had some great conversations with my advisor while driving him to the airport.  Does that count as travel?

@aeismail Ha, yes, of course.

@GregF: It's unlikely that you'd even have a TA in a creative writing course. The reason for attending the conference would usually be to present one's one research. You'd be better off with a discipline that does field work—then it's much more likely to have the student travel with the advisor.

@PatriciaShanahan: Because screenplays set in a film-industry environment become boring quite quickly?

In most cases, a teaching assistant would not have any reason to travel with their professor, since their responsibilities are around teaching. Perhaps if the class was an expedition for field work in an archaeological department or something (I think I have heard of a department doing this), but then it would have all of the students as well.
A research assistant, on the other hand, will often travel to a conference with their advisor, if they have a paper or poster to present. Thus, to me, the most likely case for a teaching assistant traveling with a professor is if they are also supervised in research by that same professor.

Many TAs are also RAs or otherwise engaged in research. These are not mutually exclusive.

@Thomas That is the point of my second paragraph. In the US, at least, TA and RA are typically descriptions of the means of financial support for a student.  When dealing with graduate students, all are typically engaged in research, but not necessarily with a professor that they are TAing for.  Undergraduate TAs, of course, might not be doing any research at all.

Some undergrads do do research. I once filled in for a week when both the professor and undergrad TA of a course were at a conference.

@Thomas Again, I am unsure what you are disagreeing with in my statements: "undergraduate TAs might not be doing research" also implies that many might be doing research.  The point is that it is the research relationship that typically leads to joint travel, not the teaching relationship.

This could happen when the course is not taught at the home university. For example, a collegue of mine taught a course as part of an international exchange program focussing on mobility of teachers rather than mobility of students. He took his TAs with him. I have attended a summer school where people from across the world taught courses. Again they tended to take their TAs with them. This happens in real live, but it is definately not the rule. So I am a bit worried that this may look a bit too contrived in a screen play. As others have already mentioned, traveling with an RA would be much more likely.

In my graduate school in engineering I was aware of an especially poorly-funded group where the professor (70-80 y.o.) and 2-4 research assistant students (all 27-35 y.o.) would drive from east coast to Cincinnati in same car for conference and ALL SHARED THE SAME HOTEL ROOM (2 beds)! quelle horreur! Although the professor liked creeping on female students all persons involved were hetero cis males so no funnie business here, just a humiliating level of frugality.

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Technique for teaching "unlearning"?
How should one go about trying to teach students to "unlearn" a previous skill/principle they believe is correct but is actually wrong?
Hypothetically speaking as a really basic situation, if your student was adamant that the formula for the area of a rectangle is 2*l + 2*w, even though you tried to explain that is instead the formula for the perimeter, and explained to them the definition of area vs. perimeter, but they are overly confident that they are right, how can you gently guide them to the right direction? What is best practice?

Ask the students to draw a 1 m^2 (or whatever unit length/area is common to them) square on the board and explain why they do as they do and then ask them to calculate its area. Clearly they should arrive at the same result both times. That should give you a foundation for evaluating their logical skills and maybe start turning their minds.

Apart from the answer I gave below, your example might indicate a confusion between area and perimeter. I think I would try taking it out of the abstract, by letting them calculate how long it would take to walk around a polygon and many small tiles it would take to cover a floor, or something to that effect.

As a physicist I'd ask them to write the measurement units (dimensionality analysis). An area will never be given in distance units.

I've tracked down a research paper on this very mathematical issue, which apparently has been stumping people since Plato:
De Bock, D., Van Dooren, W., Janssens, D., & Verschaffel, L. (2002). Improper use of linear reasoning: An in-depth study of the nature and the irresistibility of secondary school students' errors. Educational Studies in Mathematics, 50(3), 311-334.
and
http://en.wikipedia.org/wiki/Meno%27s_slave
To generalize, it is advantageous to try the following in order to create "cognitive conflict" in the student's own mind:

Recognize that students' "fast thinking" (in a Kahneman sense) will be their first response. Requiring them to slow down and justify their answer will be frustrating and painful for them.
Create an environment where the student is comfortable changing their answer. No attacks in front of an audience of their peers, etc.
Give examples of "what other students answered," perhaps in the form of a table that shows many people chose the linear response, while others recognized area increases as the cube of length. This reduces shame at their own answer and may increase interest about why another answer was so often chosen.
Give examples of the reasoning of correct students, and ask the incorrect student to justify their disagreement.
I would recommend giving the student time to think, and then asking them to discuss it again another day.

thanks for the suggestions! I will definitely implement them. Hopefully this will bring some improvement. Thanks for the book tip too; I will be adding Kahneman's book to my reading list.

@Lisa, You might find this video helpful in avoiding firm commitment to incorrect answers. It asks students "what do you notice" before allowing them to solve a problem. http://youtu.be/WFvYZDR4OeY

"area increases as the cube of length."  cube should be square.

I these cases the direct approach is seldom constructive. It's tempting to start constructing logical examples that show they must be wrong, but this is much more a matter of psychology than of logic.
Basically, the stronger you argue, the harder they will dig their heels in. With your example you may actually force a situation where they have no other way out than to admit that they're wrong, but in most scenarios they'll find a way to stick to their guns, and the more you push the issue, the harder it becomes to admit they were wrong all along.
So the trick here is small commitments. Don't ask them to accept the whole thing in one go, but get them to accept a small part of it, something they can agree on without admitting defeat. Then just stand back and let them come round on their own.
My favourite example of this principle is trying to convince a rabid anti-Apple consumer to buy an apple laptop instead of a regular PC. If you argue on quality of hardware, or value for money, or user experience, it won't do you any good (regardless of whether those are valid arguments). What you should do is buy them something very cheap and tiny, like an iPod nano, for their birthday. Once they commit to that, the anti-Apple stance is no longer a point of principle, but they're somewhere in the grey area, free to move around.
It's all about breaking down the principled stance and the ties to their pride. Only once you've got rid of that should you come in with the logical arguments.

@Peter thanks for the suggestion! Great Apple metaphor too (coming from someone who switched from Android/PC to Apple). I will try this out.  Given the example, what would you say is a small enough commitment?

The smaller the better I'd say. It really depends on the scenario. I'd try to find small commitments by creating concrete and specific examples and stayiong away from the connection to the abstract. Really anything that they can agree to without agreeing to the main point. In your example, you might talk about a bathroom floor and how many tiles you need to cover it versus how much caulk you need to line the edges. After they've worked that out, you can slowly let them draw their own conclusions.


text:
Review paper very similar to mine
I have published a review paper a few years ago in an important journal which was recently (last month) cited by a review paper related to the topic (published in another journal).
However, a significant part of that new paper (basically an entire section of a few pages) is extremely similar to my paper. It is not copy/paste, but very close. There are several sentences that are almost alike and even match my writing style and line of reasoning, which I consider paraphrasing plagiarism. On top of that, there is a table which was copy/pasted exactly as in my paper.
I feel that my work is not acknowledged and I feel that the authors are publishing this information as it was collected and critically analyzed by them. It took me months of reading and cross checking dozens (if not hundreds) of papers to be able to make the review and summary of that information with confidence and with a critical view.
The authors of this new paper do cite my work as a reference here and there, but they present all that information as collected from their own sources.
I just feel that this is not fair and honest, but maybe it's just my feelings and maybe are not doing anything wrong ...
Can you tell me if I have reasons to act on this, and how should I proceed to get my work acknowledged properly?

They certainly did something wrong (plagiarism) but how you should react is up to you based on your opinion.  What do you want to achieve?

@AnonymousPhysicist I favor knowledge transfer above other things, and the information they used fits well in their paper and will certainly benefit the reader. However, I also put honesty above other things. So, I don't mind they leave the text as is, as long as my work is acknowledged properly - that's what I want.

Have you contacted the editor/publisher of the journal in which the other article appeared? They may not approve, but may not have known.

@WolfgangBangerth I didn't act on it in any way yet (apart from this post). I was unsure what would be the best approach to this.

You need to edit the question to say "How should I proceed to get my work acknowledged properly?"  assuming that is what you want.

First I would suggest you ask someone fairly experienced to read both papers - yours and the new one - to check whether an independent person feels that they are similar. In many disciplines, review papers have a very formalised structure. This means that they all look fairly similar to each other and tables (for example) may be essentially identical.
You could also look at the specific sentences that you feel are being duplicated and also look at another review on a closely related topic. Are there also very similar sentences in that third review? This will give you an idea of whether the similarity is simply because of the requirements of reviews (such as methodology statements about the key terms being searched).
If you still feel that the review is plagiarising, then you can contact publishers and editors as suggested in the other answers. However, I urge you to be sure first as this is a serious accusation and it is risky to rely on only your own judgement of similarity.

Other answers ae great and I will follow their advice, but I specially agree with the suggestion to involve an independent third party to evaluate it first

You could consider contacting the editor of the journal that published your paper. Presumably you transferred the copyright to the journal. They have a vested interest in protecting their copyright. They may be able to request the other journal make a correction on your behalf

You could trace the similarities sentence by sentence, give reasons for your doubts, and post your evaluation on PubPeer.
If you deem such a public evaluation to be too far-reaching for now, there may be another venue. Some countries have established institutional bodies for scientific integrity to whom you could delegate your matter. An independent commission will then look into it and assess your claims. Such an evaluation may contain more expertise and add greater legitimacy to your judgement. Ask your national Academy of Sciences.


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Are politicians attempting to destroy tenure?
Apparently, Iowa's politicians intend to enrich the tenure experience by annual gladiatorial games at state schools, regardless of tenure:

those being evaluated below some threshold shall be terminated, and
after (1), the 5 remaining lowest scoring professors will be put to a public student vote, and the one with the least student support shall be terminated.

The source looks legit - blog of the AAUP. I'm not sure if this is enacted, or proposed (I think proposed). I'm also not entirely sure how to link this to an answerable question fit for Academia.SE, but maybe:

Is this a joke I didn't get, or is it true?
Is it part of a broader wave?
Does this contradict any case law, or is being fought already somehow; or will professors just have to live with it?

If this is true, and stands in Iowa, to be worried for the US at large one just has to look at how quality of life legislation spread like a wild fire once enacted in one place.

Full text of the bill as proposed by Mark Chelgren.

When student evaluations of teaching allow open comments, they often revel sexist, racist, and homophobic attitudes. While I am not a lawyer, terminating someone for potentially "protected" reasons, is likely illegal.

To be fair, that's pretty much how politicians get to keep / lose their jobs. Though it seems like a rather bad idea to apply that system to academia...

@Moriarty The difference as you know is that politicians try to determine what to do whereas academics try to determine what is true. Representative democracy may work for the former, but certainly not the latter. If 70% of the population doesn't believe in smoking, you can outlaw it. If 70% of the population doesn't believe in evolution, it doesn't do any good to pretend it is false.

This is a particularly cynical interpretation of democratisation of universities.

Interestingly, Senate File 64 always seems to die: https://legiscan.com/IA/research/SF64.

@user6726: I admit ignorance: what is "in recess" wrt to suggested legislation? Temporary suspension of discussion? I've only ever heard the term wrt politicians ("after the recess, senate...")

I don't know what that means there: I was referring to the amusing fact that when the same number was used in the previous 3 general assemblies, it died in subcommittee. Oh, I found the mouse-over -- it means the session is in recess.

@gnometorule It means the Iowa Senate is in recess right now, so the bill's not being worked on at the moment.

Yikes. The language of the bill is very (scaringly) vague. "Criteria" and "rating system." Conservative politicians are en masse pushing for MOOCs and a dismantling of the higher education system. It's started a bit in Canada and many professors I have close relationships with are incredibly worried about the future of academia in Canada. The vague language makes it seem like the rating system and criteria could be influenced heavily from the outside. (Do you teach evolution? That's a paddlin'.) I have known a few professors who honestly did not deserve tenure but the vast majority...

... work hard and are very committed to their craft as researchers and teachers. At the primary school level, I understand addressing the issue of tenure. There are many, many horrible teachers who hardly understand their subject material. That is not an easily corrected issue as it is very much a systemic one. The issue is multifaceted and getting rid of bad tenured teachers doesn't even begin to fix the issue there. However, trying to remove tenure at the collegiate level is not doing anyone any favors.

@Corvus  Re "academics try to determine what is true", that seems (in my experience, anyway) to be mostly true in STEM fields, though even there you'll find the occasional academic who'll ignore facts in order to keep riding his/her particular hobbyhorse.  In the humanities & social sciences, the hobbyhorse riders seem to be the majority.

Conservative politicians would like to dismember higher education because an educated electorate is their biggest problem. Look at places like Pakistan and Afghanistan. Education? Not so much. And conservatives do really well there. Keep 'em stupid, feed 'em bullsh*t, and keep getting elected - a politicians paradise. :-)

@StrongBad Wow, really? O.o We have had lecture evaluations with open comment fields for decades now, and I don't recall reading something like that, ever.

@Raphael I think this interactive chart makes the point about sexism.

@StrongBad Interesting, thanks! (Given the low incidence of most words, the room for interpretation is probably limited, and I'd like to group by synonyms, but interesting in any case.) Nevertheless, this does not offset the fact that the official, standardized lecture evaluations at my (German, STEM-focused) university do not display this, at least not as openly as your first comment suggests. I'd be interested in word counts, though.

Welcome to the Hunger Games (the crowd roars)!

@Miguel: Funny you mention that! I found this on the facebook page of a friend (professor at Vancouver) who shared it with the same remark. :)

Proposals to "reform" or end tenure are not new—they have been going around for several decades at least (as I remember such stories when I was an undergraduate in the 1990's).
This is not yet enacted legislation—it is merely a proposal that, as far as I can tell, probably has not even had any hearings yet. As such, I would suspect that such a bill would be shot down in committee, as the proposed methods would probably violate at least some sort of labor laws, as the faculty would in effect be judged by students with whom they have never interacted. Such "popularity contests" would pretty much dry up any opportunities for faculty recruitment. (Who would want to work at such a school?)

The point that students would judge professors that didn't teach them is excellent; so at least in this form it seems unlikely to be constitutional. As someone -  other than you apparently :) -  who's never seen such idiotic attempts, I'm still worried that a somewhat mollified version could pass. I +1ed of course; just my 5 cents.

It seems overwhelmingly likely that this is just political grandstanding -- it's too absurd to be a serious proposal. But in any event, student evaluations are a terrible metric to use for this purpose because they closely reflect expected course grade -- and thus incentivize faculty not to make their classes demanding. If jobs depended on a metric like this, you could be sure that any remaining vestiges of actual content would evaporate and rampant grade inflation would follow.

The inanity is not limited to politicians. Several years ago, the Vice-President for Academic Affairs at my school proposed that all faculty scoring below average (whatever he meant by that) on course evaluations should be terminated. He became almost apoplectic when one of my math colleagues informed him that he was proposing to eliminate half the faculty. Much as we would like to believe otherwise, we are not living in a higher education version of Lake Woebegone.

@ChrisLeary in any individual round it would be possible for the number of terminated faculty to be much less than half (depending on the definition of average).  Assuming that the first round of cuts eliminated all the "bad" faculty and the university only hired "good" replacement faculty, subsequent rounds would necessarily eliminate "good" faculty - which probably does not bother some people too much.

@ChrisLeary I'm told that our administration once proposed something like this as a requirement for tenure. When the faculty senate and such pointed out that student evaluations correlate very poorly with learning outcomes, the administration engaged in classic bureacracythink: they suggested lowering the bar from top half of a meaningless metric to top 80% of a meaningless metric. At least the flip of a coin was being replaced by the roll of a die, I guess. Fortunately none of this was ever enacted.

@ChrisLeary - apparently the qualifications for being promoted into an academic vice-presidency do not require mastery of basic statistics. :-)

This bill won't be passed this session at least. The Iowa state legislature has a cut-off date that prevents bills from being considered if they haven't passed a committee by then. I think we're past it, if I'm reading this right

Who would want to work at such a school?  Maybe someone who's actually good at relating to students and getting along with them.  You don't even know how many teachers I had, both in public school and then later at college, who failed badly at this most fundamental of all qualifications!

The follow-up post to the aforelinked post mentioned above answers most of your questions. Specifically:

The bill is not a joke, it was actually submitted as proposed legislation.
The proposed bill, like many before it, is a very clearly a Bad Idea™. To quote from the blog:

The absolute nuttiness of the bill is the best defense against its ever becoming law. Iowa, though, has other protections. Katherine Tachau, President of the University of Iowa AAUP chapter, informs me that this dead-on-arrival bill was intercepted by the Iowa Senate Education Committee chair, a professor at Iowa State, who sent it to a subcommittee chaired by another ally of education. Tachau writes, “I’m inclined to think that this bill belongs to the large category of ill-informed bills on any number of subjects with no chance of passage with which the records of all legislatures are replete.” I agree.

It does not appear that this bill has any chance whatsoever of actually becoming legislation.
Unfortunately, this bill is not alone; there are other examples of the teaching professions being attached through legislation.

Thanks for pointing the follow-up blog post out, and I hope that author is right in his opinion of it having no chance of passage (the opinion supported by relevant people involved in legislating in Iowa). I agree that one must be vigilant though. Crazy bills have managed to pass, and it only takes one precedent for the case law machine to go into overdrive.

So if it doesn't die quickly, academics need to shout, hard.  Not only in Iowa, but across the USA and internationally.

As I understand the workings of Iowa's legislature (poorly), it is passed all deadlines for this year. Rather than shouting, we should oppose rationally.

Then there was this bill that should make Pi 3.2 by law... but that was in Michigan, I think!?

Neither life, liberty, nor property are safe while the legislature is in session... Just sayin'...

@Alexander - I believe you're thinking of the Indiana Pi bill, an early testament to the brilliance and fortitude of the legislature of the Hoosier State (whose recent actions have been so much in the news of late). Sadly the legislators of 1897 were not made of stern enough stuff and it was never enacted into law, and thus even to this day students at such great seats of learning such as Purdue and Notre Dame must still labor to memorize long lists of the digits of pi rather than the much simpler value of 3.2. What a shame, what a waste... :-)

authors: Bob Jarvis - Слава Україні


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Is there something special about "City Universities" and do the municipalities somehow govern them?
There are several universities with the title "City University". Is there something special about them, is it some kind of special model of founding, governing and developing the university by the local municipality/city/greater-city?
I am participating in the political party/movement and I see the need for some kind of focused higher education institution in our city for some demographics that is neglected by the central government and so - I have feeling that we can propose to establish our own city university to boost education in this special demographics. But are there "role models" for universities that are founded by the cities in the recent half-century?

Can you say what country? Both the US and UK have city universities and their models are very different.

In general, such schools don't necessarily have that close connection to the city government. The obvious example would be City University of New York. In that case, it was founded by the state government. Seven of the trustees are appointed by the governor of the state of New York , and five by the mayor of New York City. But all of those are with approval of the senate, which is a state level office. See https://en.wikipedia.org/wiki/City_University_of_New_York#Management_structure .
On the other hand, the equivalent in London has a closer connection to the City of London (which itself is a complicated entity). https://en.wikipedia.org/wiki/City,_University_of_London
I'm not aware of a specific city-centric model of the sort you want, and a lot of these seem to be developed on a case-by-case basis. Your best bet may be simply looking through a lot of these and seeing how they handle governance and other related issues and looking for what best meets your needs.

"City University" seems to be a common name pattern when other universities are already established: https://en.wikipedia.org/wiki/City_University I am wondering whether people just liked the naming convention and used it for their cities


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How to efficiently progress on a complex problem in research?
I am writing my master thesis in game theory and realized one type of situation where I am often stuck for a long time and feel frustration creeping in. It is, to no surprise, when facing a complex situation: one with too many variables or different cases to look at.
Example setting: I build a model and look at some equilibrium points as results. The different equilibria are conditioned on many parameters such as the income of people, their social ties, their level of empathy etc. My task is to understand these conditions in order to be able to generalize some of the results.
Example being stuck: I a-priori think that the plan to crack this issue is to look at each equilibrium individually and understand the conditions for that case and then move on and in the end put everything together, I know it is going to be annoying but at some point it will just work. Unfortunately, I often fail to stick to the plan when the conditions for a certain equilibrium point are hard to understand, my mind starts to go back and forth, loosing focus and in the end failing to understand the situation at hand. I usually succeed by repeatedly going the same way again and again, but it is very costly.
I know this isn't something specific to me, this happens to many/most people when the problem contains too many cases, variables or causal links.
Do you have tips or resources on how to best handle problems like these?

Not really an answer, but there apparently is a saying: "How to eat an elephant?" – "Just like anything else, piece by piece."

One presumes you would also like effectiveness?

@OlegLobachev as I mentioned this was my way of looking at things but the point is that there's a lot of possibilities of how and which pieces to eat, and there lies the fun. Maybe even taking a few pieces at once and eating them simultaneously would work better.

@JonCuster exactly, I know that I can crack anything by just trying to go this direct path of piece by piece but at what costs, maybe even time that I don't have any more.

Write notes as you work. Brainstorm a list of questions, then try to write down answers to them as you investigate. Bonus points if some of them are questions that you would have asked before knowing the term game theory, or if some are ones a six-year-old would ask. It sounds like one of the questions on your list already is, "What conditions produce each equilibrium?"
You've already found the equilibria (do you know if you found all the equilibria?), but why is that interesting? How can you interpret that for someone? So what? (The questions that end up being most interesting or giving you the most to say should be your research questions, with their answers being your thesis statement(s).)

Below, I'm taking a lot of liberties guessing about what you're doing and what might be productive. Wherever I assume something wrong, try to use that as a jumping off point. ("That's completely silly! This wouldn't be a complex system because X!" or "Using an agent-based model wouldn't capture Y." or "Existing small world models don't account for Z.")
Depending on exactly what model you're using (e.g. an agent-based model for a repeated game) you may be creating and analyzing a complex system. There might be emergent properties you're trying to capture, and you may want to tune the model to better illustrates that emergence. If you just altered one variable at a time you might get a tipping point model ("Huh, turns out the dividing line for getting cooperative behavior is if everyone starts with an endowment of X.") but just cataloging those univariate effects doesn't necessarily capture emergent behaviors that involves interacting traits or evolving patterns of behavior. (E.g., an interesting emergent result might be: "Generally, increasing equality of endowments or increasing N leads to an equilibrium of cooperation. But when you have perfect equality of endowments and increase N, you paradoxically have higher rates of defection." Then you could illustrate how that typically plays out, turn by turn.)
Maybe mathematicians or others who work with complex systems could tell you about classes of functions or models that are thoroughly understood, and you could compare your system to that. My guess is that systematically recording the results of your playing around with the model (potentially trying to answer 6-year-old-style questions) will lead to better work.

I like the suggestion to write questions down, I think that is something I do a lot. Being systematic is also a goal, which I am doing my best for. How do you exactly mean it with "Wherever I assume something wrong, try to use that as a jumping off point"? Wrong as counter-intuitive? Or wrong as actually proven wrong?

@FrantišekKaláb - I meant "Wherever I assume..." as meta-commentary: below the horizontal line, I was making assumptions about the details of your Masters project content. So the most likely way I would be wrong is that what I'm saying doesn't match the reality of the problem you're solving. And in fact, I'm probably overstepping the Academia Stack Exchange boundaries by trying to make suggestions related to the specific content of your research rather than sticking to general approaches. ;)

Near the bottom of your thesis draft, add a section along the following lines.

Future Work
This investigation suggests several interesting avenues of exploration for future research. In particular:

Does Theorem 3 still hold if the assumption of a perfectly spherical cow is relaxed to allow for ellipsoid cows?
Does the albedo of the cow affect the maximum time in orbit?

* Is anybody willing to hire me to research these questions, preferably for more money than I am currently earning as a Master's student?

Every time you have a new idea for something that should be investigated, ask yourself whether it really needs to be explored within your Master's thesis, or if you would do better to put it in the "Future Work" section. Think about how valuable it would be to your thesis and to the field vs. how much work it would require, and prioritise accordingly.
If you're doing interesting research, your work may well open as many new questions as it answers. You don't have to answer them all, or at least not yet! Just ensure that what you do cover is enough of a contribution for a solid Master's thesis, and de-scope the rest of it for now.
If your work has an applied focus, I would also advise asking yourself which of these questions really need to be answered in order to solve the problem at hand.
For example, my PhD project involved some issues of fluid dynamics. Modelling them in detail would have required a great deal of work to learn the fluid dynamics, and very significant computational difficulties (modelling a non-Newtonian fluid of poorly-known physical properties reacting to a poorly-characterised force, in a grid likely to require thousands of cells, using mid-90s technology.) I figured out that a static approximation would provide answers which were good enough for practical applications, so I was able to avoid a very long digression.
Above all, check in with your supervisor about how much they expect you to cover.

+1000 for "check in with your supervisor about how much they expect you to cover."


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Is Scimago or Scopus more reliable in terms of quartile classification?
I have seen that, for example, a journal X appears in the Q3 quartile according to Scimago, but when I do a search using the sources and quartile from Scopus, this situation changes; putting the same journal in Q2. I have read that the differences between quartiles could have a marked variation between both sources. For example, in this situation, for CV purposes, which one should I consider, Scopus quartile classification or Scimago? And for not opening another thread which calculation is more reliable in terms of the academic quality of a journal?

Reliable about what to whom? As for 'CV purposes', as somebody who hires PhDs, I read a lot of PhD CVs - I'm not going to be impressed if somebody tries to tell me how good the journals are based on either rating - I know already.

Thank you @JonCuster for your reply, but I was a little bit dubious why the quartiles measurement are so different if we consider Scimago or Scopus

One presume they look at different factors, rate them differently, and weight them differently. Why do two people buy different cars?

Your premise of one of these metrics being objectively better than the other is flawed: they are simply different. Counting citations is hard: should one also consider all the Facebook posts where the article was mentioned. If not, where to draw the line?
And the line they draw, by limiting citations to a subset of all sources, only considering the past five years or so - so while we are at that, why not add a few more bells and whistles?
Scopus' CiteScore is closer to the "naïve" impact factor calculations; Scimago's SJR is weighted by the "prestige" of the source the article was cited at. The comparison between different metrics could be found e.g. here.
Like Jon Custer stated in the comments, they are just different (and, I might add, rather arbitrary!) ways to compare journals. For CV, this is entirely irrelevant; funding agencies would it explicit which rating to refer to so you would not have to bother yourself with that.


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Which university ranking is more reliable in terms of academic reputation?
I have doubts about which of the university rankings is more reliable in terms of academic reputation, because there are notable differences in ranking for the same universities across different portals.
For example, if I consider a university X, I will find the following results:
a) QS World University Rankings (QS): no results
b) Academic Ranking of World Universities (ARWU), result: 601-700 Note: Here I am confused, its rank is 601 or 700?
c) Times Higher Education (THE Ranking), result: 801-1000; the same as before, its ranking is 801 or 1000?
d) Scimago Institutions Rankings (SIR), result: 669.
so which rank should I consider?
Thanks

I think the ranges mean that the ranking of university X is anywhere between 601 and 700 or 801 and 1000 respectively. They just don't state the exact rank.

In order to answer this question without being self-referential one first needs a definition of reputation and a way to measure it that do not directly rely on one of those rankings. What definition and what method of measurement do you have in mind?

To rephrase @JochenGlueck: what exactly is your goal, what do you want to do with this?

In view of the comment to my answer: are you asking which ranking is most highly regarded, or which ranking best reflects a university's academic reputation?

Do you really need to choose?  Why would you not consider ALL the data you can get (rankings and otherwise)  when making a decision?

thank you @JochenGlueck I was thinking about academic production like quantity of papers published over the year, academic  production per researcher and impact of their publications

In short: none.
In long: really none of them. Academic reputation is known to the practitioner of a specific field, it is very qualitative and there are no metrics, because it is limited to three categories:

departments in the top 20 universities;
good departments in some other universities;
unknown departments in unknown universities

and you will get it by simply looking at which affiliation had the people who got prizes from conferences and international research associations in the last 5 years.
If you come from an unknown department of an unknown university, it does not matter if the ranking of the university is 50,500,5000, it will be simply unknown.

I'm downvoting because this answer is provably incorrect. Academic reputation is known to the practitioner of a specific field, it is very qualitative and there are no metrics is exactly how the THE reputation rankings are compiled.

I disagree that there is no difference between 50 and 5000.  If people think that University X is the 50th best in the world, a lot of people will apply there and they will get better students.  Also top 100 universities in most rankings are usually well-known, respected universities.  That said, I agree that there is not much difference between 600 and 1000 as in the OP's case.

@Kimball Let's say you are coming from the Physics department from a very well known Business School: you will find someone giving credit to your work (mostly people not knowing anything about physics, but people having influence/money/power and any combination of the three), whatever you do, because you are a physicist from well-known university.
On the other hand, if you are coming from the unknown department of Electronic engineer of the Hanoi University, it is most likely that only other engineers capable of judging your work will give you time/interest.

@Allure if you ask all the people in the world "what is your preferred color" and then do a ranking out of their answers, you may think about calculating a huge array of statistical values on them, but it is still a qualitative statistic.

If you are looking specifically at academic reputation then the best ranking is the THE World Reputation Rankings, which is based solely on reputation. The next-best ranking is the QS ranking, because it gives a 40% weighting to "academic peer review" (see the methodology).

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Could a journal publish the articles presented in a conference?
In the case that one academic institution publishes a journal but also they organize a conference each year in the same area. Would it be possible to publish the articles accepted at that conference in a special edition of this journal; instead of having separate conference proceedings? This journal is published quarterly. Is there any problem doing that or is somewhat atypical?

This set-up is quite common in Computer Science. The Association for Computing Machinery (one of the two dominant scholarly associations, the other one being IEEE) publishes a number of Reviews. The conference proceedings of a few stellar conferences are published as special editions of this otherwise "lightly reviewed" publication.
Second, many conferences make a deal with a journal for a special edition. The authors of the best papers at the conference are invited to submit an extended version of their paper to this special edition. An extended version is very briefly defined as having 30% additional material. A conference will often advertise this because it allows authors to claim a second publication in a more permanent form, important e.g. because some combined EE / CS departments insists that only journal articles count fully for promotion. The 30% rule also helps with the publisher of the conference proceedings who in general apply rights to the articles published. If your institute usually publishes the conference proceedings themselves (as opposed to e.g. IEEE Digital Library), there are no problems, provided the authors know about it beforehand.
As Buffy pointed out, you need to make sure that authors at submission know about your plans. In short, at least in my field, a special edition of a journal is reasonably common.

You need permission of all authors. You need permission of any copyright holders.
Usually it is the conference that arranges such things in advance and the conference submitters are fully aware of what will happen with their work. Doing it after the fact is much more problematic in terms of getting all necessary permissions.
If the authors have retained copyright then it is a logistical problem.