text:
Is it advisable to drop out of a PhD and look for a new one?
I am someone with an undergraduate degree in physics and am currently a over a year into a PhD in maths. However I am not feeling happy for several reasons:

I told my supervisor right from the beginning that my interests were
in physics (and very specific areas of physics), yet I have spent a
year without doing any physics.
I have been studying a problem that     on the one hand seems
extremely difficult and on the other contains     no physics and
doesn't interest me, though I'm worried about souring our relationship if I tell him to his face that it doesn't interest me.
Part of what makes the problem so       difficult is that    my supervisor has
no clue how to solve the problem    and suggestions    he gives are
never useful. In my meetings my       supervisors often    says
things that are wrong and (combined with the lack of ideas on his end) it has somewhat       shaken my faith    in
him. On one occasion he got angry when I disagreed with him on something, even though I was right. I get a slight sense he resents me for this. Instead of being supervised by someone who seems knowledgeable I feel I am for all intents and purposes working on my own.
I am concerned that I have picked an area       that doesn't      interest me as much as I thought it did.

All of these things make me feel depressed and make me want to drop out and start again somewhere else, somewhere I can do research that interests me. I don't want to waste 4 years of my life simply out of a desire to "see it through." If I drop out and apply to another PhD program is the fact that you've already dropped out once damning?

Why did you accept a maths PhD - just because it was there? You need to evaluate yourself and what you want to do - we cannot guess for you.

Is it possible for you to switch within the same university? That may be easier.

Move to physics Ph.D.

Well the PhD is in mathematical physics, and project title was very physics-y and in line with my interests. But the research I've been doing bears no relation to the title and when I ask him about it, he acts like he never had a concrete research idea.

[I] am currently a over a year into a PhD in maths. However...I told my supervisor right from the beginning that my interests were in physics (and very specific areas of physics), yet I have spent a year without doing any physics.

Seems like a rather obvious mismatch! Why are you in math if you want to do physics?

My supervisor has no clue how to solve the problem and suggestions he gives are never useful.

Another bad sign. Sometimes it's worth accepting a less-interesting area in exchange for an awesome advisor. But you don't seem to like your advisor either.

All of these things make me...want to drop out and start again somewhere else...I don't want to waste 4 years of my life simply out of a desire to "see it through."

Makes perfect sense. Also consider the quality of your work...once you have a PhD, people will care about your publications and letters -- slogging through a PhD you don't like is unlikely to produce nice publications or letters of recommendation.

If I drop out and apply to another PhD program is the fact that you've already dropped out once damning?

Nope, changing departments is a reasonable reason to drop out. But, it would be nice if you could declare victory -- "I was a brilliant math student who got awesome grades and interesting results, but I realized I like physics better" sounds better than "I got my a** kicked at math and physics sounds easier." Consider what you can do over the next few months to salvage your year (publishing, securing letters of recommendation, getting good grades, etc.)

+1, esp. for "if you could declare victory" - nice one!

I would add that the PhD sets up the research direction for postdoc at least initially; having a Maths PhD and wanting to go do Physics for postdoc would be much harder than doing so with a Physics PhD in the area you want to research.

Just start afresh if you think you want to.There is no use in doing something you never want to. When you look back in the future, you will always have the regret that you didn't do something you should have done. Secondly, if you think that your supervisor is incapable of his post, then just find a new one for your new Phd and warn any of your known ones to not take him as their supervisor.

Depending on your particular situation it might indeed be preferable to start a fresh PhD in physics.
However, let me also mention that some universities have interdisciplinary PhD programmes. (At my alma mater, the PhD regulations contained a special section on the particulars of such an interdisciplinary PhD — you need two supervisors from two different faculties, the examining committee should have two faculty members from each faculty, etc.)
Rather than quitting your maths PhD, it might also make sense to work with a co-supervisor from the physics department, working on a topic which is on the intersection of mathematics and physics (such as mathematical or theoretical physics).
I don't know if your current supervisor's research has any relationship to physics, but with all the ideas from physics floating around mathematics (from topology to differential geometry to number theory), chances are that a bridge can be built and this option seems worth considering, especially since in principle you seem to be interested in both mathematics and physics.
Whether it's something you would enjoy and feel you might do well in is something only you can answer. And whether your current supervisor would support such a move can only be discussed with them.

Thank you for your reply. Do you know if I were to switch to another department within the same university, would I have "lost" a year and a half or do I get to start again? (For context, I am in the UK and PhDs are supposed to last 3.5 years.)

If you want to start a new PhD in a different department, my guess would be that the default is you start like any other PhD student from zero. However, if you receive funding, it gets more complicated. If things are already not going too well, your supervisor will also have noticed it, so they might welcome you asking for honest advice. For your background research about switching programmes you should probably find and read the degree requirements/regulations first, but at some point you should also definitely get advice from a secretary (best after talking to your supervisor).

Part of the issue is that my supervisor does not think things are going badly. And research-wise maybe they aren't: I'm not against the idea of working on a hard problem for a year (and I have made progress). The issue really is that I don't find the problem interesting and I'm annoyed that my supervisor would allow me to work on something so obviously boring for so long.

Have you told them that from your perspective things are not going as well as you hoped (bad enough to consider quitting)? Not sure I can actually say much more without knowing the situation. Perhaps you could also talk to other students, professors, etc. to help you determine the best path.


text:
Mutual citations of two papers (in mathematics)
Given two research articles A, B, is it common for them to have mutual citations, in the sense A is cited in B and B is cited in A?
Does it not create (an initial) confusion on which work is done first?
As an example, you can take paper A to be https://sciencedirect.com/science/article/pii/S0001870813003022?via%3Dihub and paper B to be https://degruyter.com/document/doi/10.1515/CRELLE.2011.095/html
They have mutual citations. Both are written by same set of authors.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

sort: votes


text:
JabRef is renaming the citation keys
I am using JabRef in my Mac Big Sur OS.
If I import from MathSciNet, it is overwriting the citation key.
At some place it is suggested to do the following:

preferences -->  citation key generator --> uncheck overwrite existing keys
put default pattern as "[CITATIONKEY]"

I am attaching the screenshot of the window.

But, when I try to import from arxiv, the citation key is missing completely.
I am attaching screenshot of the same.

How do I fix this issue? Any help is appreciated.
Is there any other reference manager that has MathSciNet, arXiv, etc as extensions?

@Anyon arxiv entries already have keys. https://arxiv.org/abs/2012.08442 has citation key "biswas2021atiyah"

I see. I can reproduce that behavior now. Maybe it's worth trying one of the development builds. Seems like there's been some bug related to overwriting keys in v.5.3: https://github.com/JabRef/jabref/issues/7420

@Anyon I do not fully understand what do you mean by "trying one of the development builds".. Kindly explain.. I have already seen the link you mentioned and learnt about [CITATIONKEY] from the same link.. Do you suggest any other reference manager that you think is suitable for similar purpose?

Yep, that was a bug which is already fixed in the latest dev version. You can get it here https://builds.jabref.org/main/
Remember to make a backup of your library before trying out the new version. (JabRef maintainer here)

@ChristophS I think this should be made as an answer..

This is a bug in Version 5.3
Please try the latest development version
In Preferences -> Import : Uncheck "Generate a new key for imported entries"
Remember to make a backup of your library before trying out the new version.
Please note that there is also a JabRef support forum available here:
https://discourse.jabref.org/
(Disclaimer: JabRef maintainer here)

unfortunately, the bug is still there.. arxiv import is giving same error. It removed the citation key

can some one else please confirm if this new version is working for them? In the sense if it is not removing arxiv citation keys..

Generally: Preferences -> Import : Uncheck "Generate a  new key for imported entries".
If you use the web search panel: arXiv is a special case, JabRef query's the arXiv API which returns XML and parses that. That info does not contain a citationkey.

I am not sure if j understand this correctly.. Are you saying what ever jabref is doing it is not able to extract the citation key of arxiv.. If we ask jabref to not create new citation key, the arxiv thing remains empty..

@PraphullaKoushik Yes. you understood this correctly. No data from arxiv for this. (For reference: https://arxiv.org/help/api/user-manual#detailed_examples)

Ok. I am happy that I am not doing anything wrong. It just doesn't not happen in the way I want.. :D if [citationkey] is already fixing the problem of mathscinet renaming, what is the bug that is fixed in new version?

I forgot to say yesterday. Thank you so much for maintaining JabRef. :) :)

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
What are the most important factors to consider when deciding the time to teach a course?
I'm starting as an Assistant Professor at an R1 university, and will be teaching my first undergraduate course (~2.5h/week) in the Spring of 2021. I've been asked if I have a preferred teaching time. What are some factors to consider when deciding the class time? Is there a specific time that should be avoided at all costs?

If there are other courses that many of your students will want to take (or even be required to take), then of course make sure your class time doesn't conflict with those other courses.

Avoid Monday mornings and Friday afternoons. Many people, including me, like to extend their weekends as far as possible.

Some students don't like to get up early in the morning, so attendance can suffer then.
Just after lunch (or supper) can be hard as people can get drowsy.
None of that is necessarily a problem if the course is interesting and you have a way to keep them active.

This depends on several factors:

What is your mental rhythm during the day?
What kind of teaching are you doing?
What do you want to achieve with your teaching?
How do you want to balance that objective against your research time?

What is your mental rhythm during the day?

Are you at your best in the morning, mid-day, or in the afternoon? In other words, when are you intellectually sharpest? That's your "A" time, for doing the most difficult tasks. When are you less capable, but still pretty good? That's your "B" time, for managing important but routine tasks. When are you physically present but mentally shut down? That's your "C" time, for doing rote, house-keeping tasks that require no thought but still have to be done. Managing your A, B, and C times during the day is how we survive in an R1.

What kind of teaching are you doing?

Are you classes going to be lecture format? Lecture/discussion format? Are there several hundred students? or 25? Think about whether you are primarily working from a script, or working with student questions and/or student engagement that demands your full attention.

What do you want to achieve with your teaching?

Teaching in your first year requires a great deal of preparation time and if student ratings of your teaching are a factor in tenure decisions (that is not always the case), you will want to demonstrate at some point in the first 2-3 years that you can stimulate excitement about your course materials in the students. That connection with the students matters more to some of us than others, so consider where you want to fall on the spectrum between being 'engaging' vs. 'adequate.' That will influence whether you teach during your A, B, or C time of the day.

How do you want to balance that objective against your research time?

The balance in an R1 is always between teaching and research demands. Some professors will save their A and B time for thinking through their research agenda; the downside is that you are in the classroom when you are not at your best and least able to respond intelligently to smart student questions. Others will find a way to alternate days during the week, so that on some days you teach at your best time and on others dig into your research.
You are the only one who can make this decision about your "preferred" teaching times. So it is wise of you to ask the question, as it involves decisions about who you are, what your objectives are, and how you are going to balance the different demands of teaching and research at an R1. Being in your first year may mean you answer this question differently than you would if your were more advanced. It's fine to be flexible--you won't always get your preferred time, anyway, in most departments. So sometimes the question is pointless, in a practical sense. But if it helps you to define yourself as an academic professional, it is a very worthwhile consideration.

Avoid first morning classes: students miss busses, get delayed etc.  The first class of the day is always the most disrupted.  Moreover, it is difficult for me as an instructor to “get in teaching mode” when class starts so soon after I arrive (lest you are comfy with really early arrivals),
Avoid classes at meal times: students have their mind (and their stomach) focused on something else than learning,
Although this may not apply now, avoid back-to-back classes so you can more easily mentally switch from one topic to the next.


text:
TT summer salary withheld despite prior commitment
I'm a tenure-track faculty at an R1 university with a standard 9-mo appointment. At the end of July, I have decided to move to another tenure-track position at another R1 university (for personal reasons). I immediately notified the chair of my department (by email), who was aware of my personal reasons and received the information amicably. The move will happen in one year. Perhaps importantly, I have not yet submitted a formal resignation notice/letter.
Before the summer term began (and before my giving notice), the staff in my department had asked about my expected work commitment for the summer, and where would my funding come from. I proposed to work at 100% effort and to pull my summer salary from my startup (which had been done in the past without any issues). Accordingly, my 1st month summer salary this year was paid as expected. However, my 2nd month summer salary was not paid, and I expect my 3rd month to not be paid either.
I've reached out to the HR person and the department Chair. The Chair said that I can no longer use my startup funds to pay summer salary, since I'll be leaving the University within one year. While I understand their approach, nobody had informed me of this rule. My contract states that I have discretion on how to use my startup -- including using it for summer salary -- but that its use requires approval. Keep in mind that my summer salary had been approved when I first requested it.
So far, I have been working during the summer as previously agreed with the department. Accordingly, I don't think it's fair to have my summer salary withheld after having running my lab at 100% effort. Am I wrong to expect my summer payment as previously agreed upon?

Presumably when you started your position, you signed some sort of contract and this likely mentioned startup funds and any limits on those funds. Possibly you will find this policy there.

You need to work this out locally, perhaps with the help of legal counsel. Opinions here won't change anything.

It's quite common to have a clause in a contract or faculty handbook that requires faculty to repay sabbatical leave salary if the faculty member leaves shortly after the sabbatical (or never returns.)  It wouldn't be surprising if a similar clause applied to your startup funds.   Beyond that, it's no surprise that your funds were frozen once you announced your intention to leave the university.  Don't be surprised if you're prevented from using the funds to support students or buy equipment.


text:
What would be a more academically acceptable name for a cluster of four courses?
In higher education, we know what is a major or a minor.  What do we call it when there are only a cluster of courses, say 9-12 credit hours in the same discipline that is not part of a major like concentration or emphasis?  The intent is to make them available to non-majors to broaden their credentials. In some professional disciplines like education or social work, the name 'endorsement' may make sense.  In other areas, is there a name that is both intuitive and academically sound?

This isn't going to be a stand-alone program but rather something that student do within a regular degree program, right?  In that case, even at 9-12 credit hours, "minor" or "concentration" might be used.  I've also seen "specialization in"  used.

Thank you for the insight here.  We require 18 hours for a minor whereas concentration is reserved for students within the major.  You are right about the part that it is for students pursuing a regular degree program.  Appreciate taking time to share.

Such mini-programs are sometimes called certificates.
Certificate programs are sometimes meant to be completed stand-alone, often by students who are not enrolled in a degree program but are looking for continuing education in a particular area, e.g. to help with their career.  However, they can also be taken on top of a bachelor's or graduate degree. They often consist of just a few courses.
As an example, you can read about my own institution's Certificate in Music Technology, which consists of 12 credit hours.

Like certificates... Some institutions do tailor specific courses for industry partners and there is a very strong link between Uni and Industry - many final year projects are Industry based - to the benefit of both sides...

A certificate program normally ends with the student receiving a diploma like award that is recorded on academic transcripts and reported to potential employers.  It's different from a minor or concentration which are parts of regular degree programs.

Thank you for the insights here everyone. We have often been told that certificates require demonstration/proof of "gainful employment." Is this not true (applicable) then when students are degree seekers and the certificates are just part of their bachelors degrees, rather than on top of them? I believe it also has to do with whether the students are getting financial aid when pursuing the certificates. Thanks again for shedding light here on this topic.

@CalebChan: That would be up to the rules of your institution, or possibly your accrediting or regulatory body.  I'm pretty sure my institution has no such requirement.  As far as I know, we'll happily award that certificate to anybody who completes its requirements.  Financial aid is a whole other question - it's quite possible that students in degree programs are eligible for more sources of aid.

@NateEldredge: Thanks for the further clarification which is very helpful.  Will definitely look into that more to see if there is any reason why we can't call them certificates.

As has been noted, if there is a certificate afterward, or some sort of formal recognition, "Certificate" is a common one.
"Concentration" is another one I've encountered being used, when it's not a standalone thing, but more of a group of classes that one could arrive at via a number of different paths. For example, we have a group of classes open to a number of different majors that adds a particular flavor to them, without actually changing the major itself, that gives them all a concentration in X topic.

Thanks for your answer here.  We have been using concentration for a group of courses within a major. In other words, students are already in the major.  They just choose different concentrations such as marketing or management in a business administration major.  Thanks again.  May go back and look at certificates.

The following assumes the US. If these courses aren't meant as a package, then they might be collected under a heading like "course offerings for non-majors". If they are meant as a package, and there's a natural order to them (e.g. biology I, biology II), it's often called a sequence for non-majors. I'm not aware of a word for an unordered group of courses meant as a package.

Thanks for your comment here.  After seeing some of the other comments, certificate seems promising if we can overcome the question on demonstration/proofing "gainful employment."


text:
What will happen to Academia in the future when it takes too long to become an Academic?
Currently, here's how Academia works:

Study for many, many years, so that you have the necessary background knowledge to embark on your own research. You can still do a bit of research on the side, but mostly you are a student learning the ropes. You are (usually) not paid during this step. Even if you are, it won't be much.
Do research. You can (and probably must) still do a bit of study on the side, but mostly you are a researcher contributing to new knowledge in your field. You are paid during this step.

This path is only tenable if the first step, the unpaid one, is relatively short, otherwise it becomes economically unfeasible to become an Academic.
But in Academia, we build upon past knowledge. Hence, it stands to reason that as time progresses, the time and effort needed to complete step 1 and acquire all the necessary background knowledge also increases.
It increases sloooowly, but it does increase. So my question is, what happens when the time needed to complete step 1 has increased by so much that it simply isn't feasible anymore to become an Academic? Hell, what happens when the time needed to complete step 1 increases beyond the life expectancy of humans?
Again, this happens extremely slowly, but it does happen. So does this mean that in a few hundred years, Academia will be a dying field, since nobody simply has time to learn all the background knowledge?

We'll be too busy fighting off the Xenos.

Welcome to AC.SE. Please take a look at our [help]. While an interesting thought experiment, as it stands now, this question is about a hypothetical situation for which no one can know the answer. That means it probably is not a good fit for our community.

Well, if that does happen, than being an academic will be the pursuit of the rich. But - it kind of already is, in the sense that a person from a poor household without a supportive environment is much less likely to complete the first phase. Remove scholarships and it's even worse.

There is one thing that you are leaving out and it is critical to understand it. Researchers work at the frontier of knowledge, the frontier is vast and growing, but an individual only works (concentrates) on a very small part of it. Getting to the "research edge" has always been hard, but no one knows everything within the known bubble of a field if the field is at all advanced.
For example, it is no longer possible for any individual to know all of mathematics. The last time it was possible was early in the 20th century. Henri Poincaré may have been the last. There is too much there. But no mathematician worries about that. You can know a bit about a lot of things, but to work in mathematics you need to know a lot about a few things. So we specialize.
It is also the fact that the path taken by a researcher to reach the edge (say, in mathematics) isn't the same path that was taken 50 years ago, since much of what has been learned in the past hundred years has been abstracted into the courses that fresh students take. That compression wasn't available in the past when a sub-field was fresh.
What you describe as the necessary path isn't wrong, but you don't need to learn everything that it is possible to know in order to be effective in extending the frontier of knowledge. A researcher's path is narrow and deep. You focused on the deep, but it is the narrow that makes it feasible.
For completeness, however, I'll also note that there are parts of academia that value the broad as much as the deep. There is room for the people who know a lot (broad) and can synthesize it for students and for the creation of the learning materials that students use to guide their own path. Such people may not be state-of-the-art researchers, but they understand the edge of the known universe well enough to describe it properly.

Even Poincare surely did not know "all of mathematics."  (That said, yes, I completely agree about specialization.)

@Kimball, it is possible that he did. Pretty amazing mind. But very unlikely anyone later. The field exploded in the 20th century.

Even though the body of mankind's knowledge is ever-increasing, the relevant knowledge for pushing a field forward is not increasing at the same rate. In the very early days of electronic calculation, you'd need to understand Maxwell's equations to get a circuit to do what you want. Once that was developed a bit, you could learn to write assembly code, and get a computer to run instructions without having intimate knowledge of electric fields. After awhile, we developed compilers that abstract high-level instructions into something interpretable by the computer, so we don't need to know everything about bit registers to have a functional program. Nowadays, there's lots of freely available open source software, so we can apply sophisticated software to interesting research problems without having the knowledge to write the algorithm ourselves, or how a computer even works.
My point is, while understanding the fundamentals upon which a scientific field is built is important, it's not critical to have a deep of understanding of every single step along the way. Scientists need only to understand the present state of their science in great detail,  so long as there's a general understanding of how we got to where we are. Interesting stuff happens at the frontiers of science, which is where scientists rightly focus their attention and energy.

At least for me, the relevant knowledge is also increasing faster than I can keep up with it.  However, the minimum nececessary knowledge is perhaps not.

It's already a problem.  But problems can be opportunities as well.  Perhaps you can think of ways to more efficiently (this is key, key, key...too many academics ignore constraints) convey classical results in your field.  I routinely read classic papers or discussions (e.g. book reviews, committee reports) from the 50s (e.g. post Manhatten Project material science) and think...man, those guys were badasses!  Oh...and clear writers too.
Figure out how to make the knowledge transfer faster.  For example write a programmed instruction textbook in a graduate topic.  Things are so, SOOOO inefficient now.  Yeah, maybe in 300 years even with optimized teaching, things will be too hard.  But right now, I just see huge places where people spin their wheels and/or don't even know what they don't know.  For one thing "pedagogy" is severely lacking for graduate students (their time is treated as free).


text:
Can an independent institution run experiments without IRB approval?
Lets say a rich person has the funds to create a US-based research institution that does not receive any form of public or private funding with the exception of said persons bank account. Will this institution be able to run experiments on human subjects without IRB approval? Nothing extreme like giving people new medicine or trying out novel surgery techniques but rather something mundane like collecting surveys or conducting psychology experiments.
At which point does it become illegal to run an experiment with no oversight within US jurisdiction?

Collecting private information, data, even surveys are generally governed by law (that applies to all). I am not familiar with US legal system, but in other countries, it is common that you suppose to obey different regulation about how to collect data, how to handle personal data, etc independently from your status.

"Psychology experiments" are not necessarily mundane, and certainly not all are more mundane than all medical or surgical interventions - in fact, many of these are quite mundane.

It really depends on exactly what you are doing: "surveys" and "psychological experiments" are not the same. The regulations providing for IRBs in the United States are governed by the Common Rule, a policy of the Department of Health and Human Services.
The first paragraph:

§46.101 To what does this policy apply?
(a) Except as detailed in §46.104, this policy applies to all research involving human subjects conducted, supported, or otherwise subject to regulation by any Federal department or agency that takes appropriate administrative action to make the policy applicable to such research. ... Institutions that are engaged in research described in this paragraph and institutional review boards (IRBs) reviewing research that is subject to this policy must comply with this policy.

The definition of "institution" is broad:

(f) Institution means any public or private entity, or department or agency (including federal, state, and other agencies).

The short answer is these rules exist to protect regular people, so there is a broad authority to regulate research, it is not tied to federal funding. Private IRBs exist to do exactly what you are asking about. It becomes illegal when you start doing research that isn't part of the exemptions, although I would strongly recommend engaging an expert to make determinations for you.

First of all, failure to comply with an administrative rule is not "illegal"; something is "illegal" only if it is prohibited by statute.  And regardless of the the policy says, there is no legal basis in the United States of America for sanctioning anyone who is not in business with the government for performing non-invasive psychological research without going through an IRB process.

@Buzz I look forward to your answer, then.

In the US, government agencies are frequently authorized by statute to make legally binding regulations. These are compiled in the Code of Federal Regulations which has sections regarding FDA requirements for approving both drugs and devices for sale and standards of ethical review for research supported by the Federal government. Failure to comply carries legal penalties that can be severe.

I'll address the academic, rather than legal aspects of the question.  All legitimate scientific journals require ethics review for published human subjects research.  Any human subjects research which is has not passed ethics review must not be published.  In my opinion, any such research is not part of main-stream science.  So the answer is no.
It is generally accepted that these are not research, and therefore not human subjects research:

Testing a commercial product to see if customers like it.
Experiments whose results will be kept secret.

However, all activities need to be ethical, even if they are not subject to IRB requirements.

What if you publish a paper on a preprint server without ever submitting it to a journal?

Then it falls outside academia, so outside the realm of this site. It in essence becomes a legal question.

@JonathanReez Biorxiv will delete it.  https://www.biorxiv.org/submit-a-manuscript

+1. If you do otherwise-legit academic research without an IRB, but then can't publish it, is it really academic research? For all practical purposes, not really. Probably one reason why Google and Facebook prolifically contribute to the AI literature but not the psychology literature.

Interesting assertion that if it ain't published research it ain't research. Says much.

@Aruralreader Indeed, for all the hate that the publishing industry gets, publication itself is central to the "quality control" process for scientific research, and the distinctions between the academic publishing process versus the publishing process for everything else ("It's on my blog!") can't be swept away.

@BryanKrause Still plenty of room to criticize the publishing industry.  Example:  A very well known publisher that sent me a human subjects research paper to peer review that was missing its ethics review.

I speak, with trepidation, because of my former membership in three IRBs. I became a member in two cases because I got in trouble myself. When I was a member I pressed for scrupulous adherence to the law and institutional policy. IRB members and staff are frequently fuzzy on both. As a member I needed to have a copy of the law, the regulations, and institutional policy close at hand.
Your question requires arcane knowledge both of Federal law and of other practices. What you ask might be legally possible but might be foolish. The role of IRBs tends to be expansive. Most institutions require that all research be reviewed according to Federal standards because it makes their job easier. They also usually require that a determination that research need not be reviewed by made at least by the staff of an IRB. Many journals, by no means all, require that research be reviewed appropriately.
There are also state laws that apply. One of the more obscure ones I learned was that our state emancipated all underage women who had a baby for all legal purposes except for the ability to give consent for medical research. Go figure.
In short, your life will be easier if your institution has an IRB and has an agreement with a Federal agency to conduct its own reviews. It will also be made easier if the staff of the IRB understand the actual law, the accreditation standards for IRBs (yes, even those exist), the definition of "generalizable knowledge" (a total mystery), and shows some common sense about what is risky or not, and who is a patient or not.
So while what you ask might be legally possible under some, or even many, circumstances, if you want to participate in modern research with humans or even with animals and then publish that research in credible journals, you need the technical staff that usually support an IRB or an animal research committee.


text:
Why is it still considered acceptable to publish papers without also sharing the original data and code?
Given the "replication crisis" and numerous examples of outright fraud in academia in the past decades, why do reputable journals still accept papers where the authors don't share 100% of their data and code along with the paper? This would make replication attempts a lot easier and somewhat deter fraudulent researchers.
Also see: Are there any proposals to make sharing code and data with publications a requirement?

Related / possible duplicate: Why are papers without code but with results accepted? (also this one)

@cag51 it's been a decade since, I think we need a fresh question

@JonathanReez Looking it over, the reasons haven't changed, so why do we need a fresh question?

If you are doing research on people, there are competing interests with replicability and privacy of the respondents. So there are legitimate cases where the data cannot be made public. The data can still be made available to people wanting to replicate it, but depending on how sensitive the data is that access could be more or less convenient.

^ medical data being one example

@MaartenBuis maybe you shouldn't be allowed to publish papers if you're not allowed to share the dataset used for the analysis? Or at least such papers should receive intense scrutiny and be presumed fraudulent by default.

As JackRed mentioned, this is an important issue in medical research. I hope you are not suggesting that we stop doing medical research... The main point is that there is no one solution that works in all situations.

@MaartenBuis I highly doubt there's a dataset that you couldn't just publish after removing personal info like exact names and birthdates

@JonathanReez You are free to doubt, but it would be even better if you did your research. An easy, and possibly pleasant, way to do that is to just invite a member of the IRB in your institution to a coffee and discuss that with her/him/them.


text:
Did any universities publish an official analysis on how successful remote learning has been during the pandemic?
Most universities around the world have now completed at least a year in remote-first mode due to the COVID pandemic. Some countries have been lucky enough to avoid/supress a major explosion of cases (China, New Zealand, Australia) but European and North American institutions have definitely been severely restricted in how much they could do in-person.
Did any universities publish an overview of how successful remote learning has been, according to whatever metrics they find important? I.e. graduation rates, median test scores, number of research grants approved, etc.

I'm not sure what metrics would make a good comparison. Grants approved will remain stable, because granting agencies have the same fixed pot of money to distribute. Most test scores are normalized in some way, whether via official grading on the curve or via more subjective subconscious marker adjustments. I guess a change in graduation rates might tell you something, but I've not heard of them really changing anywhere.

This will be an interesting study.  However, at least at my university and many in Australia, people are in survival mode; too busy fighting for their job, and making the transition to an online setting, which is made even more challenging if you are not too good with computers.  Also, given the huge job cuts, many of us have double or triple the usual load.

An interesting question, indeed, but I suspect many of the people who have the information (with whatever metrics) have incentives to not be forthright...

I expect it to take a couple of years, at least, before any studies get published.

Student course evaluation scores are a likely metric.

Also remote assessment means utterly rampant cheating, so you can’t corollate scores on assessment to any meaningful learning.

@Buffy I know an academic at my university who's looking for a PhD student to study this exact topic.

‘Also, given the huge job cuts, many of us have double or triple the usual load.’ @Prof.SantaClaus, I hope the years since that pandemic have improved for you.

What does remote learning have to do with number of grants approved?

@AzorAhai-him- professors not dealing with in person students might end up having more time to apply for grants. So instead of commuting to college to stand in front of a bunch of undergrads they’ve spent their time perfecting their grant applications.

What? Were you in academia during the pandemic? Time constraints did not go down at all with a shift to remote learning.

@AzorAhai-him- thousands of institutions went remote. Maybe they didn't at some (including yours), maybe they did at others. ~50 countries have ~respectable universities, each country has its own quirks, its own pandemic policies, its own professor workloads, etc, etc, etc.

I don't vouch for the content in each of these links, but this may go some way towards your question:

Review of Stanford’s ‘emergency remote teaching’ and learning
explores lessons learned from the pandemic

Student satisfaction and academic efficacy during online learning
with the mediating effect of student engagement: A multi-country
study

Negative Impacts From the Shift to Online Learning During the COVID-19 Crisis: Evidence From a Statewide Community College System

In terms of grants, I review this data all the time for my school [engineering school at an R1 in the US].  I can tell you that we had more submissions during the initial first year of COVID because labs were shut down [theory and computer science folks were less affected], which led to some projects stalling--especially ones with large in person education programs. So because of this we have had people with lower rates of submissions in the last two years while they were finishing projects that were extended.  Some people ended up with funding cliffs (all projects ending at the same time).  However, if you look in aggregate, our summary statistics are not easy to identify as a "COVID year" they are largely the same as 2014, 2016, 2018, etc.  Expenses is a different matter--those dropped precipitously in 2020.
What has changed with proposals is that sponsors like NSF and NIH are awarding differently.  The average number of years for a grant has gone down to about 3 years instead of the previous 4.  That means more churn for proposals, which is a lot more work in the end. Awards are also more likely to be interdisciplinary, have collaborators.  We now get huge awards with more than 50% sent to other institutions via subs.  This was rare 15 years ago.  It's getting closer and closer to the norm for senior faculty.  NSF publishes their data at "NSF by the Numbers".  My data would suggest that the reason there are fewer proposals to NSF from 2013 to 2023 is that my PIs are moving to DOD and other sponsors (the new agency, ARPA-H) that will give more money.  NSF CAREER awards are roughly the same amount of money as they were in 2010 -- it's untenable.  The number of PIs we have that are NSF-only is down considerably--mostly theory people only at this point.  15 years ago, you could get a single-PI R01 from NIH--no longer.  This need for constant collaboration is all more expensive and time-consuming to do now, but this is what is driving the changes, not COVID.
In sum, the changes to funding that I have observed from US federal sponsors are all unrelated to COVID and are about the overall funding environment that you can follow with Washington politics.
If you want statistics for a university across time, you can look up their annual reports and create your own dataset.  Here's an example of Princeton's page for their reports.  Not every university will give you the same metrics, but they do look at their peers when publishing these things; there will be some alignment.


text:
Why does something being an "experiment" automatically trigger the need for an IRB?
As an example, imagine you're running the faculty of computer science and decide which books to use for the next semester.

You pick book A for all students -> no IRB review needed
You pick book B for all students -> no IRB needed
You pick book A for half the classes and book B for the other half (due to professor preference, for example) -> no IRB needed
You decide to run an experiment where you want to see whether book A works better than book B -> IRB needed
You retroactively decide to analyze whether book A was better than book B -> simplified version of IRB is needed for retrospective data analysis

What is so special about something being an experiment?

I believe your prem8se is wrong, at least in the US.  It's not research unless you plan to disseminate the results.

Non-experiment research is also regulated. "Experiment" is not the relevant feature, research is

@DanielHatton sure but scenario 3 and scenario 4 involve the exact same set of actions. The only difference is whether or not you label the actions as an "experiment".

@DanielHatton you might have 4 different profs teaching undergrad Algebra, 2 profs prefer Book A, 2 profs prefer book B, so you split the student groups into two.

@JonathanReez - and now you have a useless "experiment" since you can't separate out the profs from the books.

Existing methods exist for Textbook evaluation. Doing legwork and a quick search to help inform this question would help to improve the question. For example, I discovered http://www.project2061.org/publications/textbook/articles/approach.htm for the US that covers the example in the question: How to evaluate textbooks. Also, many papers exist on using teaching evaluations for research. Lastly, the OP could improve their post by citing sources for their definitions or "research" and "experiment"

Research creates a conflict of interest between the researcher and the research subjects: researchers benefit personally in their profession for performing and disseminating research. Research protections exist because people abused their research subjects for these personal gains (money, fame, etc), they weren't invented to create paperwork.
Seemingly innocuous research is still regulated or at least subject to institutional review because it's not sensible to have the researchers who benefit from their research make their own decisions about what they think the risks are or what paperwork they want to do.
Many things are regulated in one context but not another; research is not particularly special in that sense (for example: if friends come to your house, you can make them dinner and serve them beer without any sort of permit; if you want to collect money for making dinner and serving beer you typically need a permit for each and are subject to many additional regulations). For this to work, it's necessary to define what is and isn't regulated somehow. The standard I'm most familiar with is that research is intended to contribute to generalizable knowledge. It would not be practical or reasonable to regulate an instructor's ordinary choice of textbook as if it's research any more than an ordinary medical procedure.

+1 but note that this also applies to medical procedures all the time. Hospital A decides to use procedure KB-1 for treating condition XYZ. Hospital B decides to use KB-2. If there's no "research", no one bats an eye assuming KB-1 and KB-2 are seen as equal options in the medical community. But as soon as you start doing "research", you get a ton of extra work on top.

@JonathanReez Yes that's exactly what I'm saying. We don't regulate all decisions as research, we regulate research.

@JonathanReez We don't merely “assume” KB-1 and KB-2 are equivalent. Patients expect and physicians have a duty not to carelessly chose a treatment that's inferior in every way. If the physician choses a treatment for any other reason, this expectation breaks down. In fact, as an experimenter, it's very tempting to chose treatments that you expect to be different to maximise statistical power and make it easier to publish. That's one reason why intent matters (and disingenuously omitting to “label” it as an experiment – as you put it in your question – doesn't really change anything).

@Relaxed right but my question is why "intent" is supposed to matter. Either KB-1 and KB-2 are safe and accepted within the medical community or they're not. Why you do KB-1 vs KB-2 shouldn't matter, assuming all else is equal.

@JonathanReez But not all else is equal, which I discuss in this answer.

@JonathanReez How could intent not matter? The intent of the physician is precisely what the expectation I was referring to is about. Either you chose KB-1 because you believe it's the absolute best option and you're not even considering any other factor or you chose it because you're looking for an interesting condition in an experimental design. It cannot be both.

Incidentally, that's a very contrived example, it makes no sense to run an experiment if you already know KB-1 and KB-2 to be perfectly equivalent. That would be unethical, if only because it's wasting resources. Which brings us back to the point I was alluding to earlier: If your intent is to research something, your mindset is completely different, you have a very strong incentive to include at least one treatment you believe to be inferior in some way and you have a conflict of interest when deciding whether both are safe and accepted.

@Relaxed often times KB-1 and KB-2 efficacy rates have large error bars, especially once you try to understand how they work for a particular subset of patients. I.e. for ADHD one might use Ritalin, Adderall, Dexedrine, Evekeo, Desoxyn, Vyvanse, and a few other more exotic treatments. There's no consensus on which option is the "best" so different psychiatrists will use different options in a different order, even if you only look at the best ones from top schools. Lots of medical conditions are in the same boat.

@JonathanReez You're describing things for an IRB to consider when evaluating a research proposal. Having researchers decide their own work is low risk would be like having the police investigate themselves for possible wrongdoing in policing.

@JonathanReez You're the one who contrived an example with two equivalent treatments but ultimately that's completely irrelevant, the point was about how you approach the treatment decision for an individual patient, whether you are only trying to do what's best for them in their specific situation or if other considerations figure in your choice.

You wrote “either KB-1 and KB-2 are safe and accepted within the medical community or they're not“ but as you just pointed out, it's usually not that easy, especially for any treatment you would care to research so starting from this assumption isn't very useful.

To be specific to your scenarios:
In the US, the controlling department is Health and Human Services, and their requirements are easily found at HHS.gov. From "§46.104 Exempt research." subpart (d) we find

(d) Except as described in paragraph (a) of this section, the following categories of human subjects research are exempt from this policy:

(1) Research, conducted in established or commonly accepted educational settings, that specifically involves normal educational practices that are not likely to adversely impact students’ opportunity to learn required educational content or the assessment of educators who provide instruction. This includes most research on regular and special education instructional strategies, and research on the effectiveness of or the comparison among instructional techniques, curricula, or classroom management methods.

So, in the US at least, no IRB review is required in any of your scenarios above.

Good answer. As an aside, I've worked with academics who wanted to use course evaluations for research and their specific universities still required IRB approval. Likely specific universities erring on the side of being risk adverse given your references.

@RichardErickson - that is a grey area, because you are now (potentially) collecting information from individuals ("interaction" or "intervention" in the definitions section). I would bet the IRB would go very smoothly, particularly if the course evaluation questions were the standard set used by the institution already. Asking specific, course-related questions could be seen as different.

The professor I worked with wanted to evaluate her teaching methods using research and you're correct. She got IRB approval prior to teaching and had no problems. Sometime real life human interactions go smoother than hypothetical internet questions :)

While I don't believe you posit research here, research subject are protected, often with IRB review being a part of that process, because horrible injustices have been done to subjects in the guise of research.
When dealing with students, in particular, some of the main risks have to do with coercion and voluntariness.  Also, in the US, subjects have a right to NOT PARTICIPATE in research, and the IRB would look to make sure you have a fair path around the research for student who opt not to participate.
Also, students who are research subjects also need to have their privacy protected, and they need to be protected from social wrongs.
But again, I disagree that the activity in your description, in and of itself, constitutes research under US PHS definitions.

If I publish a paper comparing student performance with Book A vs performance with Book B, can I do so without IRB approval?

@JonathanReez No, you cannot -- but it's the publishing (or plan to publish, anyway) that makes the difference, not the assessing textbook efficacy for your own teaching purposes.

If you are conducting/disseminating research related to human subjects, you will need IRB approval. This is a safe-guard. Just switching books and keeping note internally is part of departmental pedagogy and something those students signed up for, being the subject of research is not (unless you allowed them to sign a disclaimer, which itself would require IRB approval).
It's not the experiment that's the trigger, it's the human subjects.
In a case like this your IRB approval will just sail through. Someone looking at efficacy of pedagogical material is not high on the list of the type of ethical violations universities/agencies are trying to curtail.
EDIT: I see from your other comments that you are looking at the requirement for IRB approval as meaning that the work or topic is not acceptable. It is perfectly acceptable. It just requires one layer of overview/review to ensure compliance. That's all.
Not the best analogy, but on the fly I see it somewhat similar to when you order something from a foreign vendor, your credit card may need an authentication code to make sure there's no fraud. It doesn't mean you can't buy it, just one layer of protection for everyone involved.

I disagree with your characterization, at least in the US.  It's not just the Human Subjects, it's the subjects and the RESEARCH, and research is "a systematic investigation designed to develop or contribute to generalizable knowledge relating broadly to public health, including behavioral and social-sciences research." (from https://www.ncbi.nlm.nih.gov/books/NBK22941/)  -- no desire to contribute to the generalizable knowledge (i.e., no publication, or plan to do so) == not research.

@ScottSeidman my response was implicit that it was research related to Human Subjects which triggers an institutional review. That seemed to be the crux of the question from the OP, ie what is triggering IRB, not necessarily all of the nuances of IRBs. Perhaps I misunderstood.

@DanielHatton  I suppose different IRBs can be more stringent, but the definition comes right from the Code for Federal Regulations.  I can tell you that I've gone to my IRB about 20 times with questions like this, and every time, the question I get back is "do you intend to publish?", and if the answer is "no" their response is "you don't need IRB approval because it's not research".

I don't think this study would necessarily "sail through" an IRB.  There is no described way for a student to opt out of the study.  There are classes of studies that don't require this, but in this case, there is conceivable harm to subjects (e.g., if students with textbook A do great in the course, but students with textbook B all fail, then the latter group has been harmed).

@ScottSeidman yep, IMO the answers so far downplay the experiment / research aspect. If Book B sucks but there's no experiment, the students will just be told "its a you problem" if they complain. But if Book B sucks and its an experiment, then all of a sudden it becomes a problem.

@JonathanReez  -- no, they're not necessarily told it's a "you problem" if book B sucks.    It doesn't always reach a level of law.  Sometimes it does. If different classes of students are being given different educational  materials, it may be a Title 9 or some other discrimination issue.  If privacy in education is compromised, it may be a FERPA issue.  If it's a research thing, then it may be an IRB issue.

@ScottSeidman in my college the leadership would just shrug and say that Book A (along with any other book on the planet) was widely accessible to everyone on the course and that would be the end of it.

What is so special about something being an experiment?
The answer is location specific for exact policy, but largely depends upon what you want to do with the results. For example, Loyola notes

Do student course evaluations of faculty need to be reviewed by the IRB?
Student course evaluations of faculty do not need to be reviewed by the IRB,
unless the evaluation results will be used for research purposes or will be published or disseminated.

Basically, if you want to do (including the important step of publishing) research, you need IRB approval.
This example would directly apply to your example as well.

But how could something be perfectly acceptable if done on its own but then not acceptable without IRB if tagged as "research"?

What makes you think it's not acceptable. It is perfectly acceptable, it just undergoes one layer of review to certify it is compliant.

@JonathanReez -- This is because the IRB exists -- in the US, by Federal Mandate -- to review the treatment of human subjects research, not teaching.  Students, just by being students and participating in coursework, are not "research subjects".  There are certainly ways to abuse your students while teaching, but they are beyond the purview if the IRB (though many of them are covered by different laws, federal or otherwise)

A necessary element of research is 'generalizable knowledge.' If your purpose is to develop a conclusion that can be widely generalized to the pedagogic process then you are seeking generalizable knowledge and you must have IRB review. If you just want to choose a better book for yourself, you don't.

Anecdotally, some psychologist at my school was doing a study surrounding course evaluations, and a different evaluation was used for a subset of courses.  The questions weren't shown to faculty.  Some of the students were not comfortable with the questions.  Students and faculty in the involved courses got an apology from the Dean and Provost, stating that the IRB had retroactively determined that IRB review was required to roll this out (I can't remember if they also said informed consent was required). I know this, as I was teaching one of the courses involved, and got the apology letter.

@ScottSeidman yep - but if the same questions were shown without the intent of doing "research", its likely that no one would take the complaints seriously or apologize for anything.


text:
What recourse do I have if an author refuses to share data despite their data availability statement?
According to a recent paper:

Of 3556 analyzed articles, 3416 contained DAS. The most frequent DAS category (42%) indicated that the datasets are available on reasonable request. Among 1792 manuscripts in which DAS indicated that authors are willing to share their data, 1670 (93%) authors either did not respond or declined to share their data with us. Among 254 (14%) of 1792 authors who responded to our query for data sharing, only 122 (6.8%) provided the requested data.

Assuming I encounter such a paper where the author refuses to share their data despite claiming otherwise when publishing, what recourse do I have? Should I contact their institution? Or perhaps I should contact the journal? Or are data sharing statements non-binding and there's nothing I can do to force the paper author to comply with their original promise?

I assume it is a hypothetical question, but could you still specify the assumed reactions from the author(s) on the request? No response will be different from a blatant "Actually we don't want to share it" answer and again different from a "Sorry we've lost the data" answer.

@silvado the paper says that 86% didn’t respond at all and out of those who responded half outright refused to share the data. I’m interested in both scenarios.

I am not sure I would share a large data set with researchers who were not going to use it for beyond checking a box.  That is, the study authors were not making a reasonable request. These numbers seem skewed.  The hypothetical question is still a good one.

@TerryLoring Seems like a slippery slope excuse to never sharing your data at all.

@JonathanReez Highly disagree there is a slippery slope here, there's a pretty clear distinction between someone asking for your data to use it, and asking for your data to not use it.

I actually encountered this two times. It would be interesting to know the options I have.

First, you should ask them again, but nicely. Often, the papers / projects are "administered" by Ph.D. students, who after graduation loose access to the machines on which the data might be. They might also no longer have an institutional email and their supervisor might have difficulties getting to them. Thus, getting the data to you might not be quite trivial and involve some work. An explanation why you want the data is therefore more than appropriate.
You might seek someone out that is more senior and commands more respect to intervene for you.
If you really want their data and they do not oblige you:
In academia, you can contact their department and school. In industry, you can contact their PR people and their supervisors. Promising data and not giving them is somewhat close to plagiarism. If the threat of a committee will not work, it will take a long time in academia for a committee to report their findings and even longer for any reaction.
You can also check whether any one of the authors is a member of a professional society that has an ethics statement. Not keeping promises could lead to sanctions.
Many funding agencies (e.g. NSF) will have a data availability policy for funded research. They will not be glad to hear that one of their fundees is taking data availability statements too lightly. Losing access to funding is a very serious threat.
You can also write to the editor of the journal. They have more standing in the field. If the editor of a journal that publishes them is angry, any author will reconsider.
You might also have legal recourse. After all, the data availability statement is a type of public promise that can be enforceable. Starting a lawsuit will get the attention of the legal team of the hosting institution.
Finally, administering data is not simple, especially when there is churn among the administrators (e.g. graduate students) and things get forgotten or lost. In this case, there is not much recourse. You might get an admonition and shaming of the leader of the group, but not the data.

Can you clarify your basis for suggesting some of these courses of action? In particular, your statements about plagiarism and your suggestion to start a lawsuit seem very questionable; stating your experience with these courses of action might help mitigate these doubts.

If an academic is credibly accused of plagiarism, either they themselves or their department or their institution will start an investigation of faculty misconduct. The same should happen if public promises are broken. Saying that data is available when it is not is not proper conduct for faculty.

The thread of a lawsuit can be very powerful. If you are harmed by authors not keeping their promise, you can have legal recourse. It should of course be your last option.

Also, keep in mind that these data availability statements are relatively new and there is no system yet in place.


text:
Can editors affect the odds of a paper being accepted into their journal?
Assuming one submits a paper to an academic journal where the editor is positively or negatively biased towards you, what can they do to affect the odds of the paper getting accepted? An ideal answer would include links to academic research attempting to quantify the prevalence/effect of such bias.

Do you mean besides making a desk reject?

@AzorAhai-him- yes, besides that. I'm assuming they could manipulate acceptance rates in other ways as well, if they want.

Given the same set of referee reports, an editor could decide one is an accept, or a minor revision, or a major revision. The referee recommends, the editor decides. No idea whether journals have audits or whatnot...

Have you put some own effort into finding the "academic research" you are looking for?

@Snijderfrey yes and I will post my own answer later

Any editor worth their salt will know which reviewers are more likely to like a paper and which are less likely to like it.  How else would they interpret reports?  If they wanted to, they could pretty much rig whether they will get a recommendation for acceptance or a recommendation for rejection simply by choosing whom to send it to.

Did one of your papers get rejected recently? You seem to have a theme here haha

Editors don't "affect the odds", they literally decide it. If they want to stop a publication, they can even if all the reviewers say "accept". Similarly, if they want to publish something, they can even if all the reviewers say "reject".
So if the editor is biased against you, best you can do is ask them to recuse and let another editor handle the paper. If that's not possible, you are screwed.

This answer gets most of it right but leaves out an important bit. Some journals, e.g., those published by the American Physical Society, will allow you to appeal an editorial decision. In that case you may be granted additional reviews, assigned a new editor, or both, depending on the nature of the appeal. Your appeal may also be rejected, but I think the key point is that it would be a different editor deciding on that (e.g., the editor in chief).

I would guess that an editor with a vendetta against an individual or group could be successful in the short term but would probably cease to be an editor if they generate frequent complaints that are well founded.
However, an editor has a lot of influence over what gets published as they (possibly as part of a group) are the decision makers, not the reviewers. An evil editor could probably cook up rational sounding stuff to "justify" a rejection and it might work a few times. Unlike reviewers, editors are known to authors.
Even uniformly positive referee reports aren't a guarantee of getting published, but if their recommendations are ignored referees will want to know why.
As to "acceptance rates", it is much more unlikely since that assumes long term fairly frequent intervention. Most authors don't publish enough in a single journal to have this come in to play.
But, if you think something is fishy complain about it. Go above the editor if needed. But have some evidence of bias. Bias is bad for scholarship and bad for journals publishing it.
There is also the following effect. If an editor rejects a good paper or accepts junk it will be noticed by the community and the journal administration. In the former case because that good paper probably gets published elsewhere boosting the reputation of that other journal. Again, if it happens rarely (as it does) no one notices, but frequent occurrences will get noticed.


text:
How to cite something when you cannot remember where you've read it?
Let's say you're writing a paper about a novel problem in Mathematics. While writing the paper you remember an interesting result concerning a different related problem. You can derive that result from memory, but you cannot remember where exactly you've read it - it could've been a paper, a pre-print on Arxiv.org, a post on Math.SE, a book from the library, a lecture that you've attended, etc. No matter how hard you try you cannot find the exact source.
What is one supposed to do in this situation?

Step 1: search harder. Step 2: ask colleagues. Step 3: claim as a folklore result.

"it can be shown that...". And don't claim it among your contributions.

Since you're already here, an obvious step would be to post a question on a relevant Stack Exchange site. (Other websites are available.) Such questions are routinely asked and answered on MathOverflow, for example.
Similarly, asking colleagues can also work. They don't necessarily need to be people you know personally either. There's often someone in a field with a reputation for a "near-encyclopedic knowledge of the literature" you could send an email to.
However, if nothing works, honesty is the best approach. Just present it as a known result of unknown origin, or something to that effect. Here's an example where that kind of formulation is used for a problem, not a result, but the same idea applies.

That's a good way of searching for a reference. But what if nothing helps and you just don't can't find it?

There's also often someone who seems to know everyone in the field and what they're working on, so that when you ask that person a question, you'll get the response of "I don't know, but try asking X."  If X doesn't know either, he or she might refer you to someone else, and, several e-mails later, you can get an answer.

@AlexanderWoo Yes, tenacity is certainly required sometimes.


text:
Why is it acceptable to cite unpublished works?
If an article, theorem, etc. is unpublished, presumably the work is only available to people who track down the author and get a draft copy. Today we have arXiv and can find many preprints on the Internet, but people have been citing unpublished works longer than arXiv has been around. It seems like an unscrupulous author could claim anything he wants, cite an unpublished work that doesn't support his claim (or even one that doesn't exist), and get away with it unless the bad claim is caught in the review process.
I suppose the reviewers could ask for a copy of the cited work, but I recently saw a citation that was just "private communication 1981" for a paper published in 1985, and that could easily have been a phone call where no record could be provided to a reviewer.
I've never published anything myself, so maybe I'm unaware of a part of the review process that is meant to catch this, but what prevents authors from making bad citations of unpublished works?

How is this different from citing an obscure book? Just because the content isn't easily available, doesn't mean it can't be cited.

@Mast What do you mean by an "obscure book"? I assume that your obscure book went through a refereeing process and so it is, most obviously, completely different from an obscure phone call and in fact from any phone call. It is crucial not to write nonsense such as "private communication 1981" in the references (in other places it is basically acceptable, we can live with that).

@JohnB why do you assume that "book went through a refereeing process"?

@DanM. Why do you assume that you can call it a book otherwise?

@JohnB There's nothing inherent with books that implies it should be refereed. Of course, books published by a reputable publisher should undergo copyediting process, but that's not peer review. Though obscure books published by a proper publisher in most countries should at least have a legal deposit available; so not completely unobtainable from a third party, compared to unpublished private communications etc..

There are three things to consider here: often the publishing process takes long in mathematics, I had at least couple papers for which the review took 1+ year and then it took over two years since they were accepted till they appeared. Once a paper is accepted, there is almost no difference between it and a published one, even if it is still "unpublish". (2) Very often, people find about new results at conferences, and very often, if the speaker is good and gives enough details, I can get a good understanding of the proof from the talk. (3) This is not always possible, but often I try

@JohnB I don't think that matters. If you disagree, just make your point and explain where I was wrong isntead of asking personal questions. Any qualified librarian at your institution or public library will tell you about what kind of books qualify for reliable sources in academia, e.g. http://ncu.libanswers.com/faq/168497

.... to understand the results I am using, no matter if it is published or just a pre-print. Sometimes I find mistakes (even in published works); and often I can see if the proof is correct or not, sometimes I even learn new tools or ideas. If I do check the proof carefully, I trust myself more than an unknown reviewer, and then the publishing status of teh paper is irrelevant.

Simple: By citing someone you acknowledge their contribution. You acknowledge that their ideas/contributions were made and important to your work. It does not matter whether these ideas are formally published or just transmitted personally, e.g. in emails. And for lesser contributions there is always the acknowledgements section.

This is too basic for an answer, but it may be helpful to think about. Bad citation is lying. It is fundamentally no different to say "Professor Bob told me that the moon is cheese" than "I took lunar samples and my mouse confirmed they are cheddar." What stops lying? Honesty. Professionalism. Not wanting to say something stupid. Not wanting to be caught because it sounds stupid. Not wanting to be caught in reproduction attempts.

For the record, I have contacted someone who was listed in a "private communication" citation before and asked for an explanation of the cited content, and they were happy to oblige. While that's not always possible, its not as if that entire class of source material is definitively unobtainable. And as others have pointed out, if you got an idea from someone else, you have to credit them for it, even if it was private communication.

Whether it's under the purview of a reviewer or not, it is the prerogative of the end user to vet citations. What is unacceptable is ever taking anything at face valve. - If your cite is a phone call I'm going to call bs and move on.

You seem to be interpreting citations as a way of proving something by appeal to authority.  That is not what citations are.  A citation is a way of giving appropriate credit to the originator of an idea and pointing the reader to the explanation of that idea.  Not giving credit to the person who gave you an important original idea is unethical, whether that idea has been published or not.
Citing a "personal communication" related to a mathematical fact (for instance) does not eliminate the need to prove that fact.  Appropriate usage would be to write something like "the following was communicated to me by X. Y. [personal communication]", followed by (for instance) a theorem statement and its proof.
Note that if something is in a technical report or on arXiv, it is not unpublished.  People publish blog posts, novels, and Youtube videos.  Published and peer-reviewed are completely different things and it's wrong to conflate them.

I interpret citations in two ways: 1. to give credit to the originator of an idea, and 2. to provide further reading to the reader (e.g. for details not pertinent to the current paper, but which the reader might be interested in). Maybe the second point is me assuming too much, but it seems that every other form of citation satisfies both points.

Zaen is correct.  Please edit accordingly.  Citing a work which will be published in the future is a way of providing further information to the reader.  Private communications may be in that category.

Very good points; I have edited the answer to incorporate them.

Somewhere here on Academia I've read that YouTube videos are not appropriate source for citation, which kind of conflicts with your answer.

Whether something is an appropriate source of information and wheather you should cite it are two different things. The problem with citing YouTube videos is not that you shouldn't cite YouTube if you got something from there, but that you shouldn't be getting your information from YouTube.

A YouTube video surely beats "personal communication" as a source, and a YouTube video of an academic conference could be a decent source.

The bigger problem with citing YouTube videos is that they vanish too easily.

Also, a citation doesn't mean that you regard the cited work as the objective Truth. One might even cite results which have since been proven to be wrong, if you need them as an example, or you need to discuss the shortcomings of the methods they used and show how to improve them. Because even "wrong" results can be useful as building blocks to build something better (or to demonstrate the shortcomings of a method in favor of another), and if someone already did the groundwork, why not use it? Or of your work is about disproving an old theory, you have to cite the old theory you are refuting.

@IanSudbery Whether something on YouTube is useful or not is not a property of YouTube itself.

In addition to giving credit to the source of information, regardless of whether the source has been pubished or not; citing unpublished material or even personal communicaitons provides the reader with a clue where to search next. If an author uses method X for her work, and I am interested in this method, a citation to an unpublished source or personal communication provides me at least the name of the source. I can use this name to look for further material, or contact the source.

@user2357112supportsMonica the proper way would be to web.archive the video first and then cite that. Otherwise - I see no fundamental problem with that. There are papers citing 4chan, since some anon solved some decades old math problem.

All these things are super context dependent. But when people say that you shouldn't cite Youtube, its because they don't believe that its a suitable source of information, but because there is anything inherently wrong with citing youtube. We spend a lot of time telling our undergrads not to cite wikipedia, or youtube etc because we don't want them trusting these as sources when more authoritive sources for their needs are available. I'd probably still cite a conference talk without a published abstract as pers comms,  even if there were a youtube video.

YouTube is a publication platform. Like any other platform, the author of the work is more important than the platform. As an example, Lawrence Lessig is a recognized expert in copyright and he posts videos about copyright occasionally on YouTube. It seems perfectly appropriate to cite to one of his YouTube videos for a point on copyright, even if only to give him proper credit.

@vsz While law and social sciences are notably different from the hard sciences, I have frequently cited to prior work that I disagreed with to explain why I believed they were wrong or no longer relevant. Citing sources to attempt to refute them is absolutely commonplace in legal scholarship.

Doesn't this depend on the field? For example in law, a citation typically is an appeal to authority.

'You seem to be interpreting citations as a way of proving something by appeal to authority.' ...well actually they kind of are. This is why we cite peer-reviewed literature, they indicate a minimum level of scientific rigour and scientific method. Maybe different for non-science fields but anecdotal evidence is not really acceptable

What's the alternative? I can only see two:

Don't write the text. This would also mean you have something worth sharing, but are not sharing it. This goes against the purpose of publishing in the first place.
Write the text, but don't cite it. That's plagiarism.

Since the alternatives are undesirable, it's acceptable to cite unpublished works.

'Don't write the text. This would also mean you have something worth sharing, but are not sharing it. This goes against the purpose of publishing in the first place.' this seems like a logica non sequitur. It isn't ones to share (it is someone else's) and needs to go through peer review first.

An answer by David Ketcheson highlights the importance of giving credit for ideas as a reason for citing unpublished works.
Another reason for citing unpublished works can be grey literature. The linked Wikipedia article describes the history of grey literature coming out of World War II, when the Allies produced a large amount of nuclear research that was not formally published, but still scientific important.
In my personal experience in applied ecology, grey literature can be an important source for management decisions and data. For example, a wildlife preserve manager might do controlled burns every 5 years based upon their wildlife preserve's local monitoring program. But, they would not formally publish their work as an article. Instead, they might summarize their work as part of a report that lacks peer review. However, a researcher studying fire ecology might describe the wildlife preserve's management as part of a peer review article or describe trends at the preserve.
More broadly, nuance is key to understanding what is acceptable to cite. First, different academic fields have different general expectations for how to cite non-peer reviewed science and journals usually have a distinct citation style (e.g., inline vs reference section). Second, a nuanced view is important for what is being cited. Citing facts, observations, and applied choices differ from citing conclusions.
Last, to answer your final question, what prevents authors from making bad citations of unpublished works? Nothing. But, a nuanced view of peer-reviewed articles helps here. Just because something is peer-reviewed, it is not infallible. Additionally, I've had authors make bad citations of my published works. I've joked I sometimes learn new things about my research by reading work that cites it.

A complement to the good answers already here:
Giving people credit for the ideas they bring to you, by whatever means available even if not ideal, signals to possible future collaborators that it's safe to bring other ideas to you. Safe in the sense that you're not just going to let people assume you're the source of the idea.
If widespread enough, the practice of citing by whatever means available signals that it's safe to bring ideas to the community without worrying about first getting proof that it's yours. That's established to some extent in the scientific community, and we all should contribute to keep it going.
There's a lot to be said about the advantages of exposing preliminary results, doubts, even half-formed ideas to colleagues, even those who are otherwise strangers. That's most of the point of conferences.

(To add to the already good answers. I'll assume math, since you mention "theorem" and "arxiv", but this probably applies way more in general)
What would "get away with it" mean here? Publishing is not a magical process that endows the published article with an indelible aura of perfection for the ages. Publishing is just the (usual, normal, common, accepted) way of disseminating one's research. If someone's research is wrong, this will be known rather sooner than later.
Papers are most often refereed by people who are experts in the topic, so getting away with claiming something outrageous from an obscure source will not get you very far. The more important the journal, the more true this is.
Also, research is not something that happens in a vacuum. There is a community. If you are doing something that is not related to anything anybody cares about, and you publish in bad journals, you can probably "get away" with almost anything. But a normal researcher cites people, talks at conferences and meets those people, themselves and their work become known. Those "mysterious preprints" form the past were available to anyone who asked (you would send a letter to the researcher and get a copy, that was standard back then). So, the people who cared about those preprints did have them.

What does harm research progress is quoting any literature without having read it or dropping citations for the bang of it. There, sloppiness or bad faith are disguised under the shine of a DOI or ISBN. Anything that is not peer-reviewed, and reported as such, will be looked at at face value and put in perspective: let writers write critically, let readers read critically.
As others point out very well down this post, the crux is doing justice to the others' work, conscientiousness and creativity, in accordance with their own job specifications.
Off-note. Once you mention you are new to publishing, among countless resources, you might find it interesting to read the science pages that the British newspaper The Guardian dedicates, with some regularity, to peer review and scientific publishing.
It is sometimes useful to have journalists looking at science.
These ones among and along others.

I think if a work is not unpublished, there is no such thing as "cite", it is merely mentioning. But I do think it is important to do so.
First, when you make a scientific argument in your work, you always need evidence and support. Mentioning unpublished work tells readers that what you are talking about is true, and they will keep it in mind and go to validate it when you actually publish it.
The second is that to show others you are the first one to make these discoveries, but you have not published it yet. This is important in academia as well.

"if a work is not unpublished, there is no such thing as cite" <- I think you may have included more negatives than you intended to here.


text:
What are my chances of getting into an REU program?
I am currently trying to apply to 7 different environmental REU programs and was wondering what my chances of getting into one would be.
I am a current senior pursuing a B.S. in Environmental Science with minors in French and Environmental Toxicology and will be continuing my 5th year next year (I switched majors in Sophomore year). I go to North Carolina State University, a R1 university, my GPA is 3.92, and I am a female, Asian-American first-generation college student who comes from a low-income middle class family (close to my state's qualifications for the "poverty" line). I have experience as a research assistant who assisted with research on aquatic stressors on aquatic macroinvertebrates, and I won a research grant from my university to conduct environmental engineering research last year.
I am seeking to participate in an REU because I would like to pursue a PhD and would like to learn as much as I can through research experiences in preparation for grad school. Right now, I would like to experience research outside of my home institution since I would like to explore graduate school options and other kinds of environmental/aquatic research, and the living expenses being covered would be incredibly helpful for me since I nor my family would have no way of paying for my living expenses.
Unfortunately (or fortunately?), being at a R1 university and having had other previous research experiences, I am unsure as to how likely it would be for me to get accepted into an REU program. I understand that most of these programs seek underrepresented minorities from liberal arts or community colleges with little research experience, therefore I am seeking a realistic analysis on whether or not I can get accepted into an REU program. I was told by others that I should exclude the fact that I got a research grant, but I am unsure as to how to feel about fabricating the truth to make it seem as if I have had little research experience. I am at a loss for what to do, but I have to complete my personal statements by next Friday, and I am rather stressed about my odds of acceptance.
Any advice would be greatly greatly appreciated. Just as a heads up: there are unfortunately not many other REUs with research/themes specific to the field I am going into (Non-marine Aquatic chemistry/ecology), so that is why I am only applying to 7 programs. Most other environmental REU programs are focused on forestry, climate change, or marine & coastal sciences as far as I can tell.

You have to apply, we don't have their criteria that they will use to evaluate candidates.

I am unsure as to how to feel about fabricating the truth — Good! Do. Not. Lie.

"I am unsure as to how to feel about fabricating the truth to make it seem as if I have had little research experience."
Experience is good.  Just clearly explain how your work at the REU will be different from what you can do at your home institution.
Do include your demographic information.
Carefully check the rules to see if you are still eligible after four years of undergraduate study.  Carefully explain why you are doing a fifth year of undergraduate study.
It is normal to feel stressed, but there is no need to worry.  Not much is at stake, and you have a good chance of success.  Seven applications is plenty.


text:
Graduating Early and its effect on Graduate Admissions
At my current rate of taking classes I will be able to graduate from college with a B.S. in math from a top 50 US school in mathematics (according to U.S. news) in a total of 2 years with around 3.7-3.8 GPA. However, I am interested in pursuing a PhD within mathematics. If I do graduate within 2 years it will be somewhat of a "bare" degree, i.e. minimum requirements (3 quarters of Analysis, 1 quarter of Algebra, 1 quarters of Complex Analysis (at the time of application) and 2 more quarters of Algebra and 1 more quarter of Complex Analysis by the time I actually get my degree).
Reading this post it seems that the extra rigor is extremely valuable, and sticking around for another year or two would greatly help my application.
However, is applying still worth a shot? If I was to apply and get rejected would that negatively impact my application if I was to apply the next year or next two years? Would applying for a masters degree be worth it in this case, and then switching over to PhD later?
I do want to attend a top graduate program, and I will be talking with an adviser soon (I came here first to get an idea regarding this situation beforehand and not go in blind). So thank you for whatever feedback you give.

Do try to avoid graduating in December rather than May.  Most programs are set up to have incoming students start in September and don't like to have incoming students start in the middle of the year.

You linked to a previous post, for which mine was the accepted answer.  I stand by what I wrote there.  Just for the record though: what you describe as a "bare" degree is not bad, really: we have admitted people in my department with less coursework than this.

Having been on the graduate committee of the departments I am/was in for the past six years, and having looked at around 500 applications over that time, I've got something to say about this:

The time it took you to graduate doesn't matter. 2 years is fast, and if you've got good grades, then you're clearly quite good and that speaks to your case.
If you're only doing the bare minimum of classes, then that raises questions about your preparedness. That's no different than the many applications we see from small liberal arts colleges whose math departments are so small that they can't run anything other than the standard set of courses. The question then always is how such candidates will do in advanced classes, given that they don't have as much background in the different branches of mathematics as applicants from larger schools. There is also the question of the level of courses you've taken: Many applicants take graduate classes in their last year as undergraduates, and if they do well there, that is definitely a plus on their applications.
You can always apply. If you get rejected, that's ok, and it won't be a stain on your file if you come back better prepared next year. But you'll have to have an answer to the question of what happens if you get accepted into a program of lesser quality: Are you going to take it, or hold out for something better next year. Declining an offer definitely will look bad if you try again next year, but of course there is also no guarantee that you'll actually get accepted at a better program next time around. So there is a risk involved in all of this.

At the end of the day, your best approach is probably to consider what happens if you graduate now, get accepted into a good program, and then find that you're not adequately prepared. Grad school is fast-paced, and you're thrown into the same pot as all of the other students, many of whom will likely have taken more (and more difficult) classes than you had -- in many cases, first year graduate program classes. You'll struggle -- I'm pretty confident saying that because essentially every graduate student struggles, and the question is only to the degree with which they do.
You can get ahead this curve a bit by staying for another year at your current institution, taking advanced courses, maybe a graduate course or two, and doing well. Your file is going to look better for it, and you'll have better chances of getting into the good graduate programs. On the other hand, your file is not going to look noticeably worse just because it took you three instead of two years to graduate -- your competition will have taken four years. The only real downside I can think to staying for a third year is the money you will have to pay for tuition and cost of living.

I completely agree with this answer.  Just to underscore a key point that you make: the risk in applying now is not that the OP won't get in but rather that they will, in which case they will have to decide whether it is "good enough" and try to figure out the extent to which 1-2 extra years of schooling would get them into a better program.

Correct, that was the point I tried to make.

There is a good chance the admissions committee will not even see you've graduated in 2 years
There are a couple of questions here, let me address them.
1) It's likely worth staying the full four years and doing undergraduate research with a professor.  This will put you in a much better position when letters of recommendation need to be written
2) Generally applying and getting rejected won't affect subsequent applications.
In general, the only advantage to graduating early is you get to make money sooner.  If you're not careful, it can actually put you at a disadvantage as you'll likely have less work experience.  You've enrolled at a university to learn, not plow through it as quickly as you can.
Slow down, take fewer classes (and make all As in them).  Intern during the summers to both make extra money and gain experience.  Finally, college (at least in the U.S.) is also about growing as a person.  Take some time to get involved in extra-curricular and clubs.

My advice is go for 3, not 2 or 4.  Same applies if your Ph.D. is going fast.  People have a hard tme taking 2 years seriously.  But the 3 years shows credible acceleration.  Even if you could be done in 2, just enrich during 3.
I gave a more detailed post earlier with several ideas on what to do during year 3 undergrad for similar question, but can't find it now (was during a previous guest).


text:
Google Scholar referring to broken link with deleted ResearchGate article
Here is the timeline of events:

A recent paper of mine was posted on ResearchGate (RG).
The RG link was picked up by Google Scholar (GS).
The RG article was deleted (this was already 2 months ago now).
My article still appears in GS, but GS is still using the old, and now broken, link. When it tries to access this link it redirects to the RG home page.

I would like GS to correctly refer to the article, either using a new RG link or the link to the article via publisher.
Has anyone had a similar experience? Do you know how long generally the Google Scholar crawlers take to fix broken links (and if they ever do fix broken links)? Also, because it redirects to the RG home page maybe it's not even detected as a broken link?
After some digging, it looks like Google Scholar's help/support is non-existent. And it is not possible to restore a deleted ResearchGate article.
Here is the broken link, which automatically redirects to the ResearchGate homepage: https://www.researchgate.net/profile/Cara-Steger/publication/360977657_Integrating_Equity_Considerations_into_Agent-Based_Modeling_A_Conceptual_Framework_and_Practical_Guidance/links/6296589c55273755ebc63c52/Integrating-Equity-Considerations-into-Agent-Based-Modeling-A-Conceptual-Framework-and-Practical-Guidance.pdf
Here is the Google Scholar entry: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=t9WLfKQAAAAJ&citation_for_view=t9WLfKQAAAAJ:kNdYIx-mwKoC
And here is the article at the publisher: https://www.jasss.org/25/3/1.html

Sounds more like a ResearchGate issue - for all Google knows, RG messed up the link. Not quite sure how a web crawler can correlate an old RG link with some new article somewhere else. GS does the best it can with whatever info it can find crawling around, but it is not a replacement for something like Web of Science.

I don't know if it will work, but if possible in your situation you could try uploading the paper at another source, e.g. arXiv. This could result in the arXiv link appearing as the main link.