text:
Can the process of review be so fast?
I submitted a paper in a springer journal. After just two days of submission status was under review. After another two days status changed to required reviews completed and your days have passed status is still required reviews completed. Why the process is so quick? How can the reviews be completed in just two days? What would happen next?

In the old pre-email days, when papers were submitted by postal mail, I once got a letter saying my paper was accepted just a few days after I submitted it. My best guess is that the editor, who I'm told was a speed-reader, had simply read the paper himself and accepted it on his own.  I wouldn't be surprised if something like that happened to your paper.

Was this a first submission or a resubmission?

I had a reviewer submit her review exactly two hours after I invited her to be a referee.

It might be indication that the referees are very close to the approach you have adopted in the paper and have understood it right away.

"What happens next" is obvious: the editor will inform you whether the paper is accepted.  Or, more rarely, the editor will decide that the reviews are not enough, and look for more reviewers.

@JoelReyesNoche Was that two-hour review favorable? I can easily imagine producing a report in two hours (or less) if I look at the paper and see that it's junk, or if I see that the main result is something that's already known. But it would take a lot longer to review a good paper.

@AndreasBlass, the review was not favorable.

With a ton of context I'd be guessing; without any it's worse than that. Some subjects are no doubt much easier to set up reviews for. Some are much less competitive, needn't have the anonymity as protected, aren't technical. In many subjects your contribution to the field can be quite meaningful without necessarily being disprovable--so the burden on the peer reviewers is more like that on any critic, and less like that of a judge.
When I worked as an editor at a journal considered prestigious in American Studies and Western American Culture/history/writing and that sort of thing--before it went under the next year--my handling-time on unsolicited submissions fell along a bimodal distribution. I was as likely to hammer it out and handle it in the hour as I was to file it away for ... next ... lifetime? Least likely was that I'd get it done in some reasonable amount of time, like two weeks.
All in all I'd guess your piece was "easy" for them. That means one thing or the opposite. To put it kindly (and probably true): not a fit for that journal. OR, definitely a fit, and easy to find reviewers for because of that.

It definitely can. I doubt it takes more than a day for most people to actually do a review. What takes much longer is for people to set aside the time to do the review. After all, it's not like you have several hours of free time every day.
So yes: it's possible to receive a review within a couple of days of submission. If a single review received is sufficient to update the status to "required reviews completed", then it's possible you will see that status within a couple of days as well.
As for what would happen next: nothing special happens. If there are other reviewers, the editor is likely to wait for them. If there are no other reviewers, you can look forward to a decision soon. (Notably however you can't predict if the decision will be positive or negative.)

Hmmm, I'll forgive you ;-) since math isn't your field, but a significant math paper isn't going to be properly evaluated in a day. This is highly field dependent. Of course, crankery might be detected in a day.


text:
How do I reply to a potential postdoc supervisor who has no funds at this time for me?
I am in the process of contacting potential supervisors for a postdoc position, and I need a bit of advice on how to reply to one of them. I have a PhD in urban planning, and I am applying to some American Universities for a postdoctoral position.
After contacting a supervisor, I got a positive reply, however he wrote to me: "You have impressive credentials, and I'm sure you could contribute  to our group. However, I have no additional funds at this point to support a postdoctoral position. I would be happy to talk if you have funding from another source. But at this point, my funding has been allocated to ongoing students. I am sorry that I do not have better news."
What and how should I reply? On one hand having some financial support is quite vital to me, but on the other hand I don't want to lose this opportunity. I would like to show how much enthusiasm I have to work in his group. I would like to suggest to write a proposal in order to give a grant, or asking him if he know somewhere I can find a financial scholarship. Or I ask him to let me know when he has a vacant position for me. I am unsure what to do!

Note that sometimes "I have no funding to support you" is used as a soft rejection reply.

Thank him.
If he had some ideas for funding he probably would have mentioned them.  That said, asking for some creative thought or asking to meet to have a creative session regarding funding ideas would not be improper and many opportunities start with conversations.
Certainly asking that you be kept in mind for if any funding or position arises is good.
Best of luck.

I am unsure how Post-doc positions are usually designed where you live. Was this an unsolicited request for a post-doc? Post-doc positions in the U.S. are often advertised along with regular faculty announcements. They typically have funding dedicated to them at the time of the announcement. I am not sure if you would be able to find a scholarship for a post-doc position very easily as well.
You could offer to co-author a grant together that might support your position. However, when the potential supervisor indicated he would talk to you "if you have another funding sources," he might be referring to your current ability to fund your position and may not have an interest in co-authoring a new grant. Plus, while you write and wait for the grant announcement, you could have already secured another job in the U.S. at a different university.
While this particular research group/department is of great interest to you, I would suggest looking at job announcements for post-docs or faculty positions where you would not have to be concerned with securing your own funding at day one. Even if you went to another university, nothing would stop you from collaborating with this group (I collaborate with people from all over). Another suggestion would be to see if the university has a visiting scholars program. That might be another avenue, but still may experience funding as an issue.
Hope this helps! Good luck.

source: Stack Exchange

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

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


text:
Can a fellowship be stopped suddenly? If not, why do PhD courses charge a fee?
I've been considering a PhD, but the details of how it works confuses me. For example, this course charges 45K per semester as fees, but offers a monthly fellowship of 38.5K. Why do they even need to charge a fee then? Can't they just deduct it from the fellowship amount?
Also, if there's a fellowship, doesn't it mean that somebody is sponsoring the work? So if a full-time scholar is sacrificing a corporate job to solve a technical problem and comes up with a new discovery for someone, isn't this a service being provided? Why is the scholar being charged a fee then? It's like asking a mechanic to pay me when he discovers a solution to a problem with my car.
This institution seems to provide scholarships based on entrance exam scores. So as I understand it, unless a person has good scores, doing a PhD is a financial risk for approximately 5 to 7 years.
If a scholar starts a PhD with a promise that fellowship will be provided for 5 years, can the fellowship still be withdrawn before 5 years? Won't that put the scholar under financial duress? I'm asking these because before I choose to do a PhD somewhere, I need to know the financial risks.
I've seen this explanation, but the concepts are still unclear.

A PhD scholarship is likely to be full-funding that isn’t attached to    a specific project. Some scholarships are also more specific,
  perhaps    being limited to a payment for fees or living costs, but
  not both.
A PhD fee waiver removes the need for a student to pay for their    tuition, but doesn’t cover living costs. Essentially this is a way
  for universities to offer partial funding by not charging you to
  study your PhD with them.
A PhD stipend is a regular payment for living costs. It functions a    bit like an annual salary, but is usually paid tax-free. It’s rare
  for a separate funding package to be referred to in this way, but
  full scholarships and studentships include a stipend.
A PhD bursary is money paid to a student during a degree. If this is    paid for living costs as part of a full-funding package it may
  be    referred to as a PhD stipend (see above). Otherwise the term
  ‘bursary’ is used for more general funding.
A PhD grant is a specific payment, usually made on a one-off basis in    order to assist a student in carrying out research. It might be
  a    substantial amount intended to provide all (or almost all) of the
  funding you need; or it might be paid for a specific purpose, such as
  research travel or the purchase of equipment.

I didn't went through the question in detail. But normally a PhD should get is living from the grant.

@Morgan: I think it's only if a corporate entity funds the project that all costs may be covered. The representative of the institution didn't explain it clearly.

This is a complicated question which depends on the country, university, discipline, and in some cases individual agreements.

Why do they even need to charge a fee then?

Here's a common situation for sciences:

Universities get grant money to conduct research.  Often it comes from a government.  The money can only be used for research purposes.
Universities use the grant money to pay students' tuition when they conduct research.
Tuition money can be used by the university for any purpose.

Universities are incentivized to charge themselves as much as possible for tuition so that they can convert restricted grant funds to unrestricted funds.

Why is the scholar being charged a fee then?

They usually are not.  The funds are deducted from the research budget and not paid by the PhD student.

If a scholar starts a PhD with a promise that fellowship will be provided for 5 years, can the fellowship still be withdrawn before 5 years?

If you read the fine print of the contract/offer, it probably has a loophole which allows funding to be cut off.

Won't that put the scholar under financial duress? I'm asking these
  because before I choose to do a PhD somewhere, I need to know the
  financial risks.

Yes.  Universities want a way to get rid of bad PhD students.  Getting rid of bad PhD students hurts the university's reputation.  If you are not a bad PhD student, your funding will only be cut off if:

You are studying at a bad university or with a bad supervisor, in which case you should leave for somewhere better.
Some external disaster takes away funding.  This is a risk with any employer.  Example: https://en.wikipedia.org/wiki/Effect_of_Hurricane_Katrina_on_Tulane_University

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


text:
How to know if an open-source implementation used for research and extended by the researchers with new code, does not infringe a patent?
How to know (beforehand) if an open-source implementation/code in a public repository with the source code available to the public, which is used for research and extended by the researchers with new code, targeting a journal/paper with experiments, does not infringe a patent?

By "the researchers", do you mean yourselves or someone else?

Hire a parent lawyer to do a search for you. Be prepared to pay $$$.

IANAL, but "open source" and "patented" are inconsistent. They are at the opposite ends of the rules about intellectual property, though trade secrets might figure on that scale as well.
If it is specifically (and validly) open source, presumably with a permissive license, then you can use it within limits of that license. If it is patented then, for the terms of the patent, you may not without specific permission of the patent holder.
Software bound by patent should be tagged as such by the patent holder, just as open source software normally has a specific license (unless it is public domain with no claimed copyright). But the notice of a patent might not be within the source of the software itself (yes, strange), but listed elsewhere by the company.
Patent holders are permitted to give licenses on their "devices" to groups or individuals, either for free or with a cost, but they still aren't "open source".
However, an "extension" done by others than yourselves may have a separate license, or even be itself patented, but it would only be the extension to which such a restriction would apply and any restriction would need to be consistent with the original license.
NOTE: Patent law applied to software especially varies and IIRC is in a state of flux. "Devices" are patentable, and not all software meets the criteria of a "device". A web search will tell you more. See Wikipedia for example.
NOTE also, that a given piece of software might be open source in one jurisdiction and patented in another. My guess is that this is disappearing and is an historical artifact. Some early software patents have or will soon expire.

Open source and patented are not nessicarly opposed. Many open source licenses do not include patent grants, and the variations between jurisdictions and the fact independent origination does not protect against patents means there is a nontrivail amount of opensource software out there restrictions by patents.

Libmpeg2 is a classic example. It's open source (gpl) however the mpeg licensing authority (who have no relation to the lib authors) went after multiple company's who used it in there products for violating the mpeg patents.

@user1937198, that seems to confuse 'open source' with 'unwarranted claims of open source'. Either the patent or the license is invalid.

It's a three party situation.  Party one develops the code and offers it with no restrictions incompatable with open source. Party two receives it and uses it. Party three sues two for infringing their patent. Did Party one not open source it?

@user1937198, unlike copyright, which is automatic (most places), patents need to be applied for and granted by government bodies. You seem to be confusing patent with copyright.

I am not. Software patents need to be applied for and granted. And which point they apply to any use of any software that performs the process of that patent, regardless of if anyone involved in that software has any awareness, knowledge or understanding of the patent. As such, there a numerous cases of well intended open source developers building software to open source goals, that fit into patents already granted that they were not able to research or understand.

@user1937198, one can't claim that a patented item is open source and make it so. If you hold title to a yacht, I can't claim that it is mine (or free for anyone to use).

It comes down to what one means by 'owning' the software. At least conventionally, having a patent doesn't imply that you 'own' the software, that is usually only used to mean copyright rights, due to the issue of a patent holder a) getting patent rights over anything anyone else writes that fulfills the same spec. They own the algorithm, not the software implementation. And b) those rights being on a very different timescale and jurisdictional scope to copyright rights. So I don't think it's clear to make analogy to a yacht due to the different nature's of the rights.

Let us continue this discussion in chat.

@Buffy For the Libmpeg2 example, I could have gone and purchased the necessary patent licenses, then I can incorporate the open source library in my software. Open source licenses can have nothing to say about patent rights, e.g. the BSD license.

The two statuses 'open/closed source' and 'patented/unpatented' have fundamentally nothing to do with each other, other than that they are (in different ways) factors that can have a bearing on questions of freedom to use some particular subject-matter. (With all due respect to @Buffy here.)
As has already been indicated, patenting is a highly formalized and institutionalized process with a specific legal regime. It involves making an application to one or more patent granting authorities, which can lead (usually after much effort) to grants of patent rights limited by subject-matter, geographical area and term.  In principle that is independent of the existence (or not) of any other kinds of rights.
By contrast, there does not need to be anything formalized about open- or closed-source materials (often software codes, of course). If the originator/owner makes or allows some content to become publicly known, then to that extent it might be called open or open-source. But publishing something does not in itself entail giving up existing patent rights or copyrights (for example). [One must of course beware, before making public releases, of any risks of giving up eligibility for rights not yet applied for.]  There is nothing at all contradictory about having something publicly known, and it being the subject of patent rights or copyrights -- among other kinds of rights.
@Dan Romik's comment is fair enough and appropriate, it's often thought wise to check the existence or non-existence of patent rights by going through a patent lawyer, which can indeed be expensive. One might choose in the first place a patent information specialist, for a preliminary winnowing to see if there is any possibility of a legal issue to take to a lawyer, or any obvious way to limit or circumscribe such issues.
I'd also suggest (on the basis of professional experience, but also  making clear that I'm nobody's lawyer!) that in practice, the participants in a piece of research that has created something useful are often in the best position to know the literature, or get to know it if they haven't yet done that. They, perhaps more than anyone else, often know how and where to sniff out any possibly competing or interfering subject matter.  And nowadays it's not that difficult to extend literature-searches into patent searches, using such tools as those at the US patent & trademark office (https://www.uspto.gov/patents/search) and the European patent office tools at (https://worldwide.espacenet.com/). But it does take some effort, and the people concerned sometimes need persuasion to see that the effort is something necessary, and actually expend some of their energies on it.  Then the results may usually give a well-informed idea of whether there is any possible legal issue on which consultation is needed. At the very least, a well-conducted search can raise the effectiveness and reduce the costs of any later legal consultations found to be necessary.

Conventionally, open-source, implies a copyleft or permissive with redistribution copyright license. Open-source has become a term of art in the industry with respect to copyright licensing. Simply publishing the source without granting redistribution and modification rights is more typically known as source-available and would be controversial to advertise as open source.

https://opensource.org/osd spells out the usual requirements to be considered open source and not just source available.

@user1937198 -- But the documents you cite are guidelines, not laws. They don't address the point that fundamentally the legal regime of patents and the (non-binding) conventions of open source make for two statuses that have nothing to do with each other.

They describe the conventional meaning of the words. Just making something publicly available is not open sourcing it. Open sourcing it implies an intent by the author to allow free redistribution and modification. Classic examples of software that had publicly avaliable source but where not open source include the IBM BIOS. Which is different from what you said. And for patents this implies that ideally anyone who contributed also licenses their own patents that are relevant.


text:
I feel bad about rejecting a paper during review
I'm must declare at the very beginning that I'm a PhD student that suffers from major impostor syndrome, and very much feel very unconfident about myself or my abilities.
That being said, I recently received a paper to review for a conference, and when I read the paper I felt it wasn't well-motivated, and the introduction was shaped badly. Even though I felt that the rest of the paper was okay, it was generally hard to follow for me. I'm someone with related experience in the field of the paper, I understood much of the paper after a thorough look, and evaluated based on my opinions. After a deep battle with myself, I decided to 'weak reject' the paper and sent in my reasons to do so.
However, the other submitted reviews were quite positive, and now I feel like maybe I didn't do justice to the authors' work by rejecting it. As I looked further into the draft, I saw some basic things that I didn't consider before. So maybe I didn't understand it well enough because I'm just stupid, and not because the work was actually bad. Now I feel extremely guilty and feel like I'm not capable of sending confident reviews anymore.
Perhaps this is a question for my therapist rather than you all, but being experienced in academia, I want to know if these feelings are normal, how to cope with them, and is it okay to reject a paper the way I did?

Comments are not for extended discussion; this conversation has been moved to chat.

I decided to 'weak reject' the paper

No you didn't. It is the editor that rejects the paper, or not. You merely provided input based on your technical expertise, which it sounds like you did in good faith and with considerable care.

and sent in my reasons to do so.

This is the key point. Editors do not make decisions simply by tallying the votes; rather, they will consider the technical points you raised, and those of the other reviewers.

I want to know if these feelings are normal, how to cope with them, and is it okay to reject a paper the way I did?

As you move up in your career, you will find yourself doing this more and more. Eventually, you will be regularly giving students bad grades, rejecting candidates for jobs, and reporting students for misconduct (or making similarly difficult decisions outside of the university). The feeling of second-guessing your decisions never really goes away, but at some point, you get used to it.
I find it helpful to trust that it's pretty rare to be the single point of failure in someone's life. For example, even if you were the sole decider for this paper, the authors would just submit somewhere else; it's not like you torpedoed the paper forever. Similarly, if you fire someone, there is normally a long series of events (validated by other decision makers) before it reaches the point where you have to make the final decision. And it's also helpful once you have more experience on the other side of bad decision making -- for example, if you accept a bad paper and it ends up being publicly criticized or retracted, then you'll feel less bad the next time you recommend rejection.

"No you didn't. It is the editor that rejects the paper, or not. " --- There was no editor in play here. It's a conference hence the PC has seen the OP's review and based on it and other considerations decided to reject. But it's reasonable to assume that the OP's review definitely played a big role here.

Yes, I'm using "editor" here loosely to refer to whoever the primary decision maker is

This is good advice. Relax.

@Dilworth I'm not sure how you get from "it's a conference" to "there was no editor". Putting aside the bigger point that there will be someone collating reviews and making decisions, in many conferences that person (or the stack of people involved) will have "editor" in the title.

I find your formulation of Eventually, you will be regularly giving students bad grades, rejecting candidates for jobs, and reporting students for misconduct (or analogous functions in non-university jobs) slightly problematic.  Maybe the OP will never reach a position where they do so, and that's OK.  I would suggest replacing "will" by "may" to avoid the impression that not reaching such a position would be somehow a failure.

@RLH, in many (most?) conferences the ones deciding on acceptance are called PC members. Never "editors". And they decide this quickly based on sub reviewers' scores.

@Dilworth Every IEEE conference I'm involved with uses "editor" in these roles. https://academia.meta.stackexchange.com/questions/4471/academia-varies-more-than-you-think-it-does-the-movie

@gerrit - thanks for your comment, you raise an interesting point that I have been carefully considering over the past few hours. I opted to change "analogous functions" to "similarly difficult decisions" -- I think most career paths involve making "difficult decisions" at one point or another, especially as you gain seniority, but the examples I listed are rather interpersonal (e.g., hiring and firing individuals), and it's true that not all career paths involve these specific types of difficult decisions.

@RLH, Thanks for the input. Until your comment, I have yet to see any conference that uses "editors" instead of "PC".

Though I do not disagree with the thrust of this answer, "Editors do not make decisions simply by tallying the votes; rather, they will consider the technical points you raised, and those of the other reviewers" is a rather idealistic take. In practice, editors are often overburdened with reviews and have far more submissions than they can fit into print, and even a single vote for rejection can be hard for a middling paper to overcome. I'm not sure that denying this reality will do much to help OP with their impostor syndrome in the long run.

First and foremost, you don't make the final determination, and thus have a somewhat limited responsibility.  For a conference, some section chair or committee makes the final determination.  It is their job to read all the reviews, and make a determination as to suitability for a conference.  They had other reviews, and could certainly have looked at them and accepted the work.
In my field, my experience is that conference standards are lower than those of a good journal by design -- the research is a bit more cutting edge and raw.  Referees may or may not know the standards, and again, it is the responsibility of the section chair to make the determination.  The best you can do is be specific about the problems you see, so the responsible party has the tools they need to make the right determination.
Whether you're too tough or not, that's a different story.  We all get our experience some way, and reviews for conferences are a great place to start.
My personal policy for reviews of anything short of a grant is that I have no reason to write down anything that I would hesitate saying to the author's face (whether the review is blind, double blind, or signed).  Whether this is the right policy for you, that's a personal choice.  It's different for reviewing grants, where a single review can have a profound effect on a career.

This is also good advice. We tend to question lots of the decisions we make if they seem important to us. All you can do is your best.

Could you clarify what you mean with your distinction between grant reviews and other types of review? What kind of criticism are you thinking of, that you wouldn't write in a review of a paper, or say to someone's face, but would write in a grant review? Or do you just mean that you apply higher standards when reviewing grants?

@twesley The level of importance and impact, where you know that there is a real chance that a grant can have such a profound impact on a career, dictates a slightly different code of conduct for me.  Oddly, in most processes, it's fairly likely that the applicant can figure out who reviewed their grant, as they know the ID of everyone on the study section -- but I don't think worrying about how an applicant will feel when you tell them what they need to hear should be a high priority.

Also, you can get real nitpicky when reviewing a paper, but getting nitpicky on a grant can really keep good research from getting funded.  Grant reviewers need to learn to keep their mouths shut unless something is truly important.

As a counterpoint to the world-view expressed in other answers: I've never understood claims that grad students or recent PhDs could be good referees for serious papers. The lack of experience, if nothing else, diminishes perspective...
In particular, if/when a novice doesn't understand something in a paper, especially larger issues, it's not surprising. Yes, we might imagine a standard for writing which makes things intelligible to people not-quite expert... but that is (in math) not the standard for writing. Intelligibility to experts (plus meeting certain implicit stylistic expectations) is the goal.
In mathematics, anyway, it is not so easy for even very talented beginners to be able to appreciate/appraise serious papers. Despite some mythologies, getting a PhD doesn't really make anyone an expert in anything. It's a beginning. People equally capable and with decades' head start on a beginner operate in a much different context. No moral virtue there, but definitely scientific/intellectual virtue.
But, in your particular case, you did the best you could. Good to learn something about your own limitations, such as they may be. Don't worry, except to try to be a better scholar for future episodes.

Presumably, the decision makers know who the reviewers are, so they can appropriately weight the reviews

When I was mentored, my boss kept an eye out for reviews up my alley to cross his desk.  I think this is part of a mentor's responsibility.

@ScottSeidman, true, in a structure where higher-ups receive review requests and (are expected to) delegate them to juniors, things could be more sensible. If only ... :)

Don't feel bad and don't assume you are less qualified than other, more senior reviewers. Often, reviewers at the beginning of their "reviewer careers" are much more thorough in their work.
My first review was what I percieved to be a very bad paper with many errors and shortcomings. It was within my specific area of expertise, though, and I was very much able to judge the correctness of what they were writing. I wrote a very detailed review and voted to "decline". A few months later, I got the paper to review for a second time (the editor had decided for "major revision"), along with the comments of my fellow reviewers: most of the points that I raised had not been mentioned or noticed by the other reviewers.
Because of my comments, the authors revised several sections of the paper, redid some experiments and corrected wrong references. Whithout me bringing up all these points and my harsh judgement, the paper might have sailed through with only minor revisions and a bad paper would have been published. Because I was harsh, a better paper was published.
I also initially felt bad after I handed in my first review, and even wrote a private letter to the editor, explaining that I am not 100% sure about my judgement because this was my first ever review. But afterwards, it felt right and I have learned to trust my judgement.
Being able to honestly judge the work of other people (including saying it is bad when it really is bad) is an important skill in academia, but it takes time to acquire. Keep up the good work.

As others have said, you did your best as a reviewer, given your level of expertise and perspective on the field.
Other responses also point out that graduate students may not be the best to review research papers due to lack of experience. But, I don't fully agree.
Due to this impostor syndrome, I've declined to review many papers, though I am sure I would have done better, as a student, than 30% of the reviewers that reviewed my papers.
In your case, I would suggest to keep reviewing papers and getting better, even if it is at the expense of a few authors who see delays in their paper publication dates due to you.
There are plenty benefits to it. First, you learn to read papers better, frame them better in the big picture of the field. Second, you learn to write your own papers better. Third, if you are a consistently honest reviewer, you will start adding much more value to the field than you subtracted when you were just learning to review papers. Fourth, and most important, it helps you become a better scientist, by teaching you what is important and what is less important in your field and who the strong players are. All these will help you in your future career, even on the short term. For example, it's one thing to give an interview talk stating what you did and how, and one other thing to be able to tell exactly how your work is advancing the science and what it is built upon and what can be built upon it.
Related to the impostor syndrome, I don't think it's a psychological problem that should require years of therapy. When you do serious research, you are constantly humbled by your apparent powerlessness in the face of the infinite unknown. Whatever knowledge you may have, there is always need for more, and whatever skills you may have, they are rarely sharp enough. Faced with this constant humiliation, you are bound to experience the delusion that you're not worthy of being called a scientist.
But, so are the others that do science, regardless of their status in the scientific community. So, the only way to cure this ailment is to look at what your peers are doing. You'll probably notice that you are not worse than most, even at reviewing papers. There are outliers, some people that are exceedingly good, and, at the same time come from very strong places, but, even those people suffer or suffered from this disease.
In short, stop worrying and keep doing your best, and improve your work with every iteration.

At least, in my field, when an editor gives a paper to a Ph.D. student for review, they have probably already decided that they are going to reject it. Your job is to find reasons to reject it, and to give the authors helpful feedback. As a Ph.D. student, you should probably only recommend publication of papers that are unexpectedly good. You should feel uncomfortable letting it through, not rejecting it.
Give the authors useful feedback, positive and negative, and then feel very comfortable rejecting it as that was probably what the editor wants/expects you to do. You are just doing your job.
Talk with someone senior in your field or maybe at the journal to make sure as some practices do vary by discipline. I think you will find that this is the case.

Heh. I just left a comment about this above. I was told when I was in grad school that journal editors sometimes intentionally send papers they know are bad to PhD students to see if they will reject them. This answer sounds like it corroborates that (at least in some field).

Something you should learn during your doctoral studies is to have confidence in your own judgement. This comes with time, but you can speed up the process by remembering that it is YOUR opinion and nobody else's. As long as you can justify it with facts, quotes etcetera, it is not a personal attack on the author[s] of the manuscript that you are reviewing.
Practise being more confident !

As it’s currently written, your answer is unclear. Please [edit] to add additional details that will help others understand how this addresses the question asked. You can find more information on how to write good answers in the help center.

It is true that the editor makes the final decision, but this decision is highly based/relied on the reviewer's comments. I know a Ph.D. student who couldn't sleep well for a few days because the paper that took months of research got rejected. In a case like this, you can always adjust your decision when you think it is the right thing to do.

Back in the days my paper were rejected, too. I invested months, but I learned from the reviews. You cannot pass everybody, just because they worked hard. You have to keep the quality of conference contributions about some threshold.

We are talking about a paper rejected due to some misunderstanding by a reviewer. The point that I am trying to make here is that if you (as a reviewer) found that all the other reviewers have provided positive feedbacks and you found that the paper deserves a second thought then why not just adjust your decision accordingly.

"you can always adjust your decision when you think it is the right thing to do." Can you? This seems very unusual to me in a peer review process. Have you ever done that?

@Snijderfrey At least at easychair, reviewers can edit the scores and add more clarifications if they want to, and of course they can always send a message to PC.

"I know a Ph.D. student who couldn't sleep well for a few days because the paper that took months of research got rejected." Failure and how to cope with failure is an important lesson to learn. Plus, the paper was rejected, most likely with some explanations, so the PhD had to put some more work in it, with some guidance. Maybe the issue for that PhD was "PhD student will miss their defense, loose their job and their visa and will be deported to Alabamistan because of that rejection" ... the issue then is not the rejection, but the non-sensical PhD-contracts/expectations/etcetc ...

If this worries you, there's a fortunately easy solution: never recommend rejection at the first review; always recommend revision. The line between revision and rejection is a fuzzy one, and no one will blame you if you recommend revision for a paper which you have serious doubts about. If, when you get the paper back after revision, you think the authors have not made a real effort to address your remarks, then you can still recommend rejection.
Based on your description I would also guess that the paper was sent for revisions and you're now looking at the revision. You can still recommend acceptance. It's not common for a reviewer to flip from recommending "reject" to recommending "accept", but it's not rare either. Of course, only do so if you think all concerns have been addressed.

Having a major revision first and then a rejection is a bad move. You make false hopes and waste the time of the authors. If it does not suite the journal / conference, give the authors early indication. Then they can withdraw and apply to a better place for publication.

Often enough, papers never come back for a second round of reviews. I think following this advice would lead to papers published without reviewers actually agreeing.

@usr1234567 the OP makes it clear though that this was not a "your paper is not suited to our conference" kind of reject.

@Snijderfrey you really think it's often that papers never go for a second round of review? In my experience most papers go for a second round of review, because even papers that are eventually accepted go through a 'revise' decision.

I don't have data to do statistics on this, it is just my experience. There are quite a few published papers that I reviewed where I recommended crucial revisions, that were however not taken seriously by the authors, and the editor decided that that was enough. That's fine with me because I value other peoples' judegement, I just would be careful to expect that you get back the manuscript for a second round, even if you recommended major revisions. Therefore, if you really think a paper should be rejected, I think it makes sense to recommend this in the first round.

This answer would deserve a - 2 button :)

@Snijderfrey upvoted. But even to papers rejected without referee even wanting.


text:
How do you measure success to remain motivated in academia?
I am currently pursuing a physics major in college. My question mostly applies to those working in STEM, but I am definitely open to hearing answers from others.
Right now, in college, most of the work I am doing involves solving math/physics problems. I have an easy way of measuring my success on this work: if I get the "right"/"correct" answers (or at least one that agrees with my professor's answer), I can say that I am doing "well".
This ability to measure success keeps me motivated. I was wondering what the analog to this in the real world is? When working in academia and pursuing unsolved problems, how do you measure your success to remain motivated? There is no answer key for you to check at the end of the day, so how do you know if you are "right" or "doing well"?

There is an answer key - the real world.

On the flip side: https://academia.stackexchange.com/q/108543/49043. But anyway, without exams there are still metrics like salary, promotion, publications, grants, supervising students to completion etc

Eventually you (hopefully) learn to check your own work.

This question is probably too broad and too subjective for SE.  That said, I measure my success by 1. The success of my students; and 2.  Perception of the value of my research, in my own eyes and the eyes of trusted mentors.

I think the answer by @astronat is about as suitable as you're going to get until you're older and "real world" becomes a bit narrower for you. That said, it seems to me that another measure of "doing well" is how much effort was needed to obtain the "right answer". The person who got the right answer in 30 minutes at his/her dorm room desk and whose write-up is a model of clarity was doing much better than the person who got the right answer after 4 hours that included asking several classmates for help and conducting some "library research" and whose write-up was hard to follow.

Isn't "success" most accurately measured by how pleasantly you are able to spend your days? Granting that, surely anyone would find powerful motivation. :)

@paul garrett: More precisely, the "daily value of pleasantness" is applied in combination with "future value" expectations of pleasantness in order to maximize some sort of linear (or non-linear?) combination of the present day pleasantness and the anticipated future days pleasantness (use smaller positive coefficients for days further in the future). This reminds me of the kind of word-play that seemed to take place whenever I wrote papers for philosophy classes, in this case, when writing about utilitarianism.

Unfortunately, and as it happens for most jobs, there is no such a thing, or at least, not as immediate and clear as a grade of an exam.
While one can argue that the number of publications, and the quality of the journals\conferences you publish at, can be good ways to measure your worth, this can often be biased by many factors.

If you do not work completely alone, publications are often the result of team work. There are cases where it is hard to see who worked the most, or who gave the key contribution that made the paper be accepted. I have seen people with many published articles move to another group and loose productivity all together. This probably because the previous group supported the PhD way too much and they did not learn from their colleagues. I have also seen the opposite.
Despite everything, publishing papers to journals or conferences (even the best ones) can really feel like a lottery. Usually, when you study a lot for an exam, you are almost certain that you will get a good mark, this is not true for publications on any level. A paper can be hardly rejected by conference A and, instead, accepted by conference B. This can be because of many factors. Maybe conference A was not the suited one, or reviewers just did not like the paper despite its contributions, in any case, as you can see you cannot really value your work on this type of outcome. You can, for sure, improve from reviews, but I would never use it as a way to evaluate yourself.
Depending on the specific topic of your PhD, there are different standards expected regarding the number of publications you should have. Maybe, you just need a couple and, in that case, it is pretty hard to motivate yourself for years with just two inputs (two accepted papers). Moreover, even the best PhD students have to deal with rejected articles, sometimes, even more than they have to deal with accepted ones.

I would also like to add that PhD students are pretty prone to mental illness such as depression, anxiety disorders and so on [1]. In my modest opinion (as an academic), these problems are also caused by the fact that many doctorate students evaluate their worth depending on this hard numbers (number of publications, number of paper not accepted).
Overall, I think that self motivation is a very personal thing. It is up to you to decide what motivates you and what makes you worth.
[1] http://www.sciencemag.org/careers/2018/03/graduate-students-need-more-mental-health-support-new-study-highlights (one of the many)

Unfortunately in academia there is really no objective way of measuring your success to keep you “motivated”.
Many factors that most people would think as indicators of success such as; grades in graduate school, number of publications, praise from advisor, praise from colleagues, number of grants obtained etc, although shows maybe you are on the right track, does not necessarily indicate eventual success. The main reason for this is that not all research activities or papers may be recognized immediately. They may be overlooked for many years before their worth is truly appreciated. In that case, a person measuring their success by acceptance of their work in academia or number of publications might draw the wrong conclusions.
Also work that has been praised for long years may turn out to be incorrect or incomplete eventually. In that case the apparent success of the author/group may be diminished.
So as you see, one sort of accepts the fact that there may not be measurable success when going into academia or carrying out academic activities (research, writing papers etc). As a result, the motivation does not come from success. The motivation comes from within the person (it sounds cheesy, I am cringing while writing it, but it is truly the reality of academia). If the motivation for understanding the world around you or contributing to the science is not within you, it is possible to become demotivated and leave academia (which occurs more often than not).

I second this point: "...comes from within the person...'.  Indeed, many famous scientists say that they are driven by their innate intense curiosity to find things out for themselves.  It's never about prizes.

In order to remain motivated in academia, it is important to keep the goal of becoming a renowned professor and maintain an inner belief that this goal can be accomplished. This motivation should be one's ultimate aim – not fame or fortune per se but recognition for making contributions to our understanding of how the world works, which will help shape the future. In short, you need a sufficient amount of passion for your field.
It is also important to develop a strong work ethic. You should learn from your teachers and experience what it means to be an active researcher in academia, developing strategies for doing research and cultivating the skills required for success. For this reason, you should not spend too much time on social media or idle chit-chat with friends but try to focus on research as much as possible.
There are three keys to success in academia: hard work, passion and diligence. You must work as hard as you can every single day, never giving up or running away from the challenges that life throws at you. This will help develop your character and allow you to rise above mediocrity.
It is important to stay focused on your goal, which means not wasting time on distractions such as television, video games or social media. These things are fun and can be entertaining but they will take away from the amount of time you have available for doing research.
It is important to develop a strong passion for your field of study. So what if you aren't the best in the world, as long as you love it, right? I am talking about true passion – an unquenchable desire to learn more and do better.
I am not going to say that you should never be afraid of failure. However, there are two things to remember: First, if you have failed a few times and given up on your goal, then it's time to take a break and reflect on whether or not this is really what you want.

My answer is focused on research in the context of UK universities although it may hold more generally.
I sometimes find it useful to consider an employers view point for successful academic staff members. Usually this comes down to how much money you bring into the department you are working in. (In the UK) this comes from three main sources:

In many countries there are mechanisms for giving funding to universities based on how many good publications are written by their staff. In the UK this is called Research excellence framework. So writing good papers means more funding for the department.
Most research requires some external funding, either for extra researchers, specialist equipment or travel and collaboration. This can come from many different sources. Built into most grants is some extra funding which is paid directly to the department for admistration/overheads (in theory things like heating, electrics, library access, ...). In more applied fields this can be done after the research has been performed with patents and spin off companies too. So getting people to fund your research means more money for the department.
The biggest contributor to (UK) finances is student fees. If you do some teaching your are doing your bit for the department to justify these fees. If you are a good teacher (making sure the students are happy and well educated) this leads to good feedback scores which potential new students will see and judge a course/department/university on. So doing good teaching means more students and more money for the department.

There are other income streams by doing things such as outreach activities, knowledge exchange or generating impact of your research. These all count to generate more money for your department.
In summary, you are a successful researcher (academic) if you write good papers, bring in grant money and do good teaching. Of course these are quite broadly defined criteria (how do you define a good paper? how much is enough grant money? what is good teaching?) but should give an idea of some metrics which you can use to judge yourself. In fact, these are often the criteria which job applicants and promotion panels will consider so these really are the way the employers think about defining a good researcher.


text:
Can a professor teach mathematics and computer science?
I assume this is nearly impossible in a university with separate math and computer-science departments, due to the way funding works (correct me if I'm wrong). However, I've heard that some small universities have joint mathematics and computer-science departments. In such a case, is it possible to get a professorship with the opportunity to teach both? Would I need degrees in both to qualify for such a position?

Strongly country (or even institution) dependant. In Spain, yes, there are Universities where Calculus is assigned to the Computer Science department (knowledge area is the legal term). And no, technically you do not require a specific degree to teach whatever.

Also I wonder if you mean if a professor can or may teach... The question suggests the latter, while the title mentions the former.

It's interesting that someone'd be interested in multiple teaching duties; I'd often felt that teaching duties were sort of a chore, while academics are more likely to be interested in research.  I mean there's no technical barrier; even half the undergrads in STEM fields could teach Calculus I without breaking a sweat.

@Nat IMHO real geniuses do not look down on teaching. Any undergrad can teach but when you read or listen to an oustanding researcher it makes a difference.

I’m a computational topologist. Which one do I teach?

Don't mathematics departments also offer "programming for mathematicians" courses and the like? And inversely, CS departments offer math courses. I definitely remember my undergraduate math for CS and my graduate convex optimization classes being taught by CS profs.

Computational physicists probably have it even worse.

Answer: Yes, that's what I've been doing for thirty-odd years.

I do this at a fairly large community college in NYC.

@Miguel What about this is country dependent?  Are there any countries where you wouldn't be allowed to teach a course in your department because of what your degree says?

It is even university dependend, I would say. In my current university, computer science professors do teach the math courses for computer science students, because they are separate from those for math students, or physics or... There are even courses (not sure if math's related though) which are taught together by professors from different departments.

I don't know how common this is now, but about 15 years ago I was a visiting assistant professor in mathematics at a small liberal arts college in the U.S., a position that became available because, in trying to fill a tenure-track computer science position, no suitable candidates were found by late March or early April, and so the search was ended and a new search was started for a visiting math position, with one of the math faculty members helping out by teaching a couple of beginning computer science courses and one or two of the computer science professors teaching an extra class. In fact, I had consecutive visiting positions at TWO different colleges/universities back then for this same reason (no suitable computer science candidates were found for a tenure track position), and in each case the reason the visiting position was for math and not for computer science was due to the overwhelming greater number of experienced (in teaching) candidates that a math search would generate this late in the hiring season.
The same department tried again the next year, with the same result (I believe the other place I had a visiting position at was successful the second time), and the same math faculty member pitched in again, this time I believe teaching only computer science. Over a period of several years this faculty member transitioned to computer science, and has since written two textbooks in computer science. For what it's worth, I do not think this faculty member originally had much of a background in computer science (maybe a couple of courses as an undergraduate), but I believe this person had started being interested in computer science at least a couple of years before I was there.

I'm hesitant to give specifics in my answer, since there they would be google'able and I haven't contacted any of those involved about my mentioning these things, but if anyone is really interested, this is the person in question and this is the "other place".

(I’m including this note mainly for my own possible later reference, as I recently came across a March 1998 Usenet post related to what follows.) From roughly Dec. 1997 to May 1998, I was involved in a search for a computer science teacher for this school (academically, in the top dozen or so public high schools in the U.S.), and by late February 1998 no one remotely qualified had applied (mainly due to lack of evidence of superior teaching experience and excellence). (continued)

Because of the job conditions then (very bad in math, very good in computer science), I suggested that we might have better luck if we removed the computer science degree requirement and also advertise where graduate math students looked for jobs, but still stress that the position was primarily to teach computer science. And, in fact, the person we hired (who is still there, in Fall 2020) was just such a person – someone finishing up a Masters in math who had an excellent teaching record and sufficient computer science background (had taught some CS courses at a community college, I believe).

In my first comment, the link for "this is the person" is no longer valid. However, it is available at this internet archive web page.

In my university, math and computer science are not only separate departments, they're in different colleges. (Math is in the College of Literature, Science, and the Arts; computer science is in the College of Engineering.) Nevertheless, it is possible for a faculty member to have a joint appointment and teach classes in both departments.

Yes, my university has a joint department of "Mathematics and Computer Science". Freshman year, my Computer Programming II professor taught a Discrete Math course because another professor in the department was on sabbatical.
So, yes, in my experience, it is possible for a professor to teach both Math and Computer Science. Note that my university's Math and Computer Science department is very small (4 prof, 1 adjunct).
Here's a link to the university's site (some of the information might be a little outdated, but here's an idea of this university's department).

Would you mind including a link to this department?  This can help people to see what kind of departments do this (i.e., where in the world, what kind / size of institution, and so forth).

I don't want to bump this old question but I want to record that my position, at another liberal arts college in Ohio (Denison University) was half teaching math and half teaching CS. Eventually, the "Department of Math and CS" split, and I could choose to either go full time math, or full time CS, or continue with my split. I chose the first option. Plenty of good small liberal arts colleges have a combined department of math and CS. Even if they are separate departments, sometimes people can teach in both.

You asked if this is possible. Absolutely! As evidence, I will point to my own department - a combined department of mathematics and computer science in a mid-sized private university in the US.
As a very specific exemplar, I'll point to my colleague Dr. Mike Slattery who teaches both programming languages as well as algebra. His research lies in the relatively rare of field of computational algebra.
In fact, our department encourages cross-over teaching and no, you do not need a degree in both mathematics and computer science.

Thanks for the answer! Maybe "relatively rare," but sounds awesome to me.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
Research plan for a first-time faculty application
I'm in my 3rd year of postdocs and started to apply for Lecturer positions in Computer Science the UK (the entry level permanent faculty positions). As part of my interview process, I am required to give a 15 minute presentation about my current research and my three year research plan, and am looking for some advice on how to do the latter. The focus of the research plan presentation is not only on the ideas you propose, but in major part about how you plan to obtain funding for it and how many research staff you can bring in from that funding to support your research.
I've looked through some other questions regarding UK faculty applications, research plan writing and content, which offer some good advice. However, I am looking for advice specifically targeting early-career researchers applying for their first faculty position.
The two specific aspects I am concerned about is the transition from postdoctoral positions where shorter-term career plans are the norm, as well as my relative inexperience with grant writing (I've recently been included in the late stages of grant writing by my advisor, but that's it).
Of course I am not planning to take the answers I get here my only source of information; I have an advisor happy to discuss this with me and give me specific tips, and have been looking up information about funding for new faculty members online as well as through chatting with fresh hires in my department (with some hinting they rely on the informal support and sharing of more junior research staff from within their team while applying for initial external funding).
So, considering that I've never held a faculty position, have limited experience with grant applications (but an understanding that it is an acquired skill as well as very competitive and thus uncertain), never independently proposed a research project (tho I am always active in proposing and typically independent in choosing which approaches I want to apply to problems), and never formally worked with a PhD or a postdoctoral researcher for full the duration of a project, the questions I have are:

How "confidently" am I supposed to write the research plan? Should I write it assuming I will have a student / research postdoc available to work with, or should I also present a plan for the situation where I do not have "my own staff" for a while?
One major consideration is that UK faculty typically has about 40% of their time dedicated to research (rest is teaching and admin), as opposed to research staff (PhD students and postdocs) with 90+% of their time dedicated to research. Therefore the amount of research that one realistically can conduct would depend substantially on how much funding one manages to secure.

How many backup grant options do I need to include? I understand there is some grant options specifically targeting fresh faculty in the UK, so should I demonstrate that I plan to ask the appropriate parties for funding, or also try to cover the case of no applications being successful?

To summarize: I am concerned and would like advice about the level of confidence in the tone of a 3-year research plan for a fresh faculty member.
I worry that, on the one hand, including many backup options could be seen as "setting myself up to fail", while, on the other hand, too confident a tone would make me come across as somebody not understanding the competitiveness and difficulties in obtaining funding due to my lack of experience.

The level of detail is clear from the format: it's a 15 minute presentation with some time for questions, so I won't have time to talk in much detail, but I might be asked to elaborate on any aspect of it. All in all, I am a fair deal nervous, and I'm not even sure I'm asking the right questions here; any advice from the perspective of applying for a first-time faculty position would be great.

I see from comments that the interview is past, but here's still some thoughts on this that might be useful for someone else.
I would say that your results at a 3-years horizon don't depend that much on funding prospects, mainly because you're not starting with those funds from day 1, and as a new lecturer you're certainly not expected to have an army of postdocs working for you in the first couple of years.
You might spend a few months writing the grant proposal, then the process will take some more months, and then from decision to start date there's more time... so assuming success you might be able to hire someone to start in a year at best, more realistically two. Then would you start immediately with postdocs? Unless you're one of several investigators in a larger project, that doesn't sound realistic. Rather you'll probably be supervising MSc projects, and you might hope for one or two PhD students to start within those three years, and with any luck get their first paper or two. I think what you need to pitch is a set of ideas that could form a grant proposal and some realistic-sounding MSc and PhD topics.
The bottom line is that you're being asked for a 3-year plan to see whether you can actually prepare a plan that involves medium- to long-term goals, rather than just think of the next development of what you're doing at the moment.

My situation was a bit different as I went directly from my mathematics PhD to a faculty position (in the US). But when I finished the doctorate I had a file drawer full of speculative ideas and ideas left unexplored from the work on the dissertation. If you have such a thing, or could create it, you should 'mine' it for ideas that are yet to be explored. These should be easy for you to discuss since you already touched on them in your past, though if you haven't already recorded them you have some work to do. For such work you can probably speak with confidence.
Fifteen minutes isn't very long, so you don't need a lot of material. But you might think about the fact that since you will also be teaching, research that students could potentially participate in could be especially valued. Also, you have likely gained insight into a wide range of ideas that are at least peripherally related to your current research. That wide range opens doors to a moderately broad "area" of research that increases your likelihood of success in exploring at least some of the ideas. While research is necessarily narrow for a given idea, there are related areas, most likely, that increase your range and hence your desirability as a colleague.

Sorry that I can't speak much about UK funding, but in general, "interesting" ideas are also interesting to funders. Likewise, appearing to a funder as someone with a lot of ideas (and therefore potential) is also an advantage.

Thank you for your answer. My interview was a week ago at this point, so waiting for the response atm. The "idea drawer" sounds very interesting, and something I will try to implement from now on. However, the focus of the (research) presentation in the UK is in a big part on obtaining funding so your answer covers just half of my question. I was more interested in how to go about presenting the uncertainty with funding applications - about half of what I said regarding each research proposal was about the idea itself, the rest was about getting it funded and making (industrial, social) impact

Also, just for extra context, while the main part of the interview follows and is with the same panel as the presentation of the research plan, there is in fact a separate teaching presentation before of a different panel. Since the bulk of the interview follows the research plan presentation, they were also asking some questions about teaching, but that aspect is mostly covered in front of a different panel.

I think, when I wrote the question, I was interested mostly in how funded I should assume I will be during the time I am presenting the research plan for. You only get about 40% of your time allocated to research as faculty in the UK. So, the actual goal of the presentation was to say stuff like: "for research idea A, I will aim to fund it from the agency B, which will allow me to hire a postdoctoral researcher for X years to work on A". Consequently, the research plan takes a much different shape depending on how much funding you (assume) you are going to obtain.

Also, I might be wrong on this, but the only way to appear to a funder as "prolific" is by your past profile in the terms of what you published, and which projects you got funded. Since PI grants are usually given for a specific project with concrete goals, I was advised that including too many ideas in your research proposal for a grant application will make your application weaker, as it appears you have no clear idea of what to do and and/or have not clearly defined your project goals.


text:
White paper justifying the publication of a survey paper
We are currently trying to submit a comprehensive survey article I have been working on for a while as a journal paper. Some of the journals we're considering (I'm in Computer Science) require, for survey articles, submitting a 2-5 page white paper to the Editor-in-Chief, in order to evaluate the relevance of the proposed survey (upon which the EiC would either discourage or encourage the submission of a full survey):

Authors interested in submitting overview articles are required to consult first with the Editor-in-Chief (EiC) of their Transactions of choice before submitting a white paper proposal. White papers are limited to 2-pages and should motivate the topic, justify the proposal, and include a list of relevant bibliography including any available tutorial or overview articles related to the subject matter. (...) The EiC solicits input from the Editorial Board on whether to encourage submission of a full paper.
(specific requirements example taken from: http://www.signalprocessingsociety.org/publications/overview-articles/)

I have found some questions on the topic if white papers, but it looks to me like all of those are either concerning short standalone papers, or white papers for grants, which differs a bit from my situation.
Just to summarize, this white paper (2-5 pages, depending on the journal) is not ment to ever be published, but rather to help the Editor-in-Chief and the Editorial Board in deciding on the relevance of the proposed survey. So, for me as the author, the goal of this white paper is to motivate the EiC to invite me to submit the full survey manuscript.
So, my question is how to structure and what information to include in a white paper, meant as a proposal for publishing a longer survey paper. Some specific questions I'm thinking about:

Should I divide it into sections, similar to a regular (short) paper (introduction, discussion, etc.) or should it have some different, (specific or not) structure?
The reqirements mention including a "list of relevant bibliography": as this is meant to be for an survey article, my complete list of bibliography is much larger that 2 pages. Do I just mention "related work" and omit the references used as sources for the survey from this white paper, or something similar to that?
Should I repeat some parts of the survey, or just include the motivation and explanation of the survey topic in this white paper?

If I understand your question correctly, the longer survey paper is mostly or entirely written already, right?
The purpose of a presubmission like this is generally to help the editor decide if the topic is broad enough and well enough aligned to be of interest to a large fraction of the journal's audience.
As such, the introductory material that you've written for your survey paper should be just what is needed: it should already give the scope of the survey, the motivation for it, and an outline of how the rest of the survey is structured.
I would recommend clipping out your abstract and introduction, keeping its references, maybe adding a few other key references if your introduction was reference light, and sending that in.
Finally, in your cover letter, you should say that this is exactly what you are doing.  That will also let the editor know that this isn't a submission in advance of having written the manuscript, but an inquiry of whether to proceed with a fairly mature manuscript.  Speaking as a sometime editor myself, that's very useful information.

White papers are a great way to get noticed. Many universities also offer them as resources for current students as a way to gain insight to popular concerns within the area of expertise.
Just look at:  http://www.kenan-flagler.unc.edu/news/publications/white-papers
You want to make sure that the white paper gives insight or focus to the main thoughts of your subject, and that proper credits are given to any of the relevant discussion within your paper.  If you do decide to include the focus on your survey, that would be ok. However, discussion on what the highlights are and not giving the survey the main focus, may lead to offers to have the survey published or have you give more in depth discussion of your findings. Hope this helps.

Hey! Thank you for your answer, but I think the explanation you offered more describes general white paper (see the links in my question, e.g. this question), something meant for publishing. This white paper is not intended to be published (it is limited to 2 pages) -- the only motivation for it is to persuade the Editor in Chief to ask for the submission of the full manuscript of the proposed survey. Hence the quote and the link I added to my question.


text:
How should I cite a tool or a library in my article?
When using an online library, tool, framework or something similar, what is the proper way to reference it in an article?
(I work in Computer Science). For example, I want to say that many popular implementations of the method presented in [article reference] use a slightly modified version of the main formula. I mention some examples for the implementation (e.g. OpenCV, VLFeat).
When thinking of a way to reference this, I have several dilemmas:

I could put a small explanation in a footnote or add it to the list of references
I could use the link to the main webpage or to an online manual
do I reference it at all?

This question about how to reference Python is somewhat similar. The difference is that the tools I want to reference are fairly well known in my community (unlike Python for biologists).
In short, I am looking for a good way to acknowledge tools, frameworks or libraries not associated to any article in my writing.

Possible duplicate: http://academia.stackexchange.com/questions/15374/should-i-cite-conference-papers-to-acknowledge-usage-of-tools (although the question goes into a slightly different direction, the answers there should answer this as well)

@xLeitix I didn't see that one, but now that I have, the tools in question specify a way to cite them: one is even associated to an article. But, what if there is no publication associated to the tool? I actually found the citation specifics for the two tools I asked about (not publications, btw), but does every tool specify how to cite it? If not, the question might still be relevant and more general than the one  you linked.

Duplicates? http://academia.stackexchange.com/questions/8948/how-to-cite-a-product/8955#8955  Not as related but relevant: http://academia.stackexchange.com/questions/8098/how-to-cite-a-website-url http://academia.stackexchange.com/questions/9617/how-to-cite-software-documentation/9618#9618

To be honest, I don't see the difference from the question you refer to: How do I reference the Python programming language in a thesis or a paper?. The way how you cite it should not depend on their popularity (unless something is so well-known that you abstain from citing it). One addition is that if you want to be more specific (e.g. implementation of X in framework Y, you can treat X like a chapter (and point to a specific file/class/function)).

A good citation has the following properties:

Gives credit where it is due for an (idea, tool, dataset, etc.) that is not your own.
Directs the reader of your paper where to look, if he/she wants to verify that your claims about the (idea, tool, dataset, etc.) are correct.

Any of the following can be used to cite a tool, as long as the above properties are satisfied:

If the authors of a tool explain how they would like it to be cited, follow those recommendations.
If there is a paper or tech report about the tool, cite that, because that is what the authors would probably want (if they didn't specify).
If there is no paper or TR, cite the website of the tool.

Of course, in most cases, you're not the first person to cite the tool - go search Google Scholar for the name of the tool, and find out how others cited it.

I'd put emphasis on the literature review section of your article and/or thesis. From this perspective, there are two possible citation styles. First, instead of referencing a programming language, reference the concept that you are writing about. For instance, instead of saying
C++ (Stroustrup, 1986) is a programming language.

say
Stroustrup (1986) extends C to develop object-oriented programming by doing so and so.

In this way, you enrich your literature review and not simply accumulate references.
On the other hand, if the tool is quite novel and not used anywhere in literature yet, then cite who and where it was developed. For instance, SuperComp has developed SuperLang that you want to cite. It could look like this:
SuperComps (2014) develops Superlang for this and that so on and so forth.

The reference for it could be an online resource, book, manual, etc and will simply follow your referencing style e.g., APA, Harvard, etc.
So, you can simply cite OpenCV, VLFeat as either website, online resource, related paper, or patenting or licensing author(s).

If there where an article related to the presentation of the tool, framework or library then a proper citation should be used.
If you are looking for a good way to acknowledge tools, frameworks or libraries not associated to any article, (such as the case of Python) then you can do this in a footnote.

If I'm using a tool "generically" and want to point the reader to where they can find the code, I'd prefer a link to the code, not to an article describing it.


text:
How can I document depression for later reference in grad school applications?
I am currently a third year undergraduate at a good university studying computer science. I am planning to apply to top graduate schools when I finish my undergrad and I need a bit of advice.
In the first two and half (5 semesters) of my studies, I took the most challenging CS/Math courses in my university and did very well in them (GPA 4.11/4.30). I also joined two research groups and have 2 publications where I am the first author, published in reputable journals. I also have a very good relationship with my 2 research advisors.
Now in my sixth semester, I decided to go on an exchange semester and things just started crumbling. First of all, I couldn't integrate well in the culture and I was left very lonely with no new friends in the area. My Girlfriend of 5 years broke up with me, my mother got into a car accident which affected her health, and I started taking depression medication due to that. I also gained a lot of weight which lead to some health problems. Needless to say, this term is coming to an end and I can't wait to leave this place. I am going to probably fail 2/4 courses, and in the remaining ones, I will barely pass. I am expecting a 2.0 GPA at best.
Now I know this won't go unnoticed by graduate school admissions. I am just wondering what steps can I take as of now to document all of this so that I can justify the poor performance in the exchange semester during my graduate application?

I can't imagine anyone would ask you for proof that your girlfriend broke up with you... these things are usually just believed (unless someone has a concrete reason to think you are lying about them).

I have a friend that had similar problems when in Erasmus in Germany. He never disclosed his problems abroad and got admitted in one of the most competitive PhD program in our country. Today he is almost finishing his PhD with several papers published in high IF journals. Hang in there, things will get better for you. The experience you are having is important and is not quantified by a GPA, try to hold the best of this. Good luck!

Your transcript should be all you need. Presumably, your transcript shows that you studied at a foreign university, and that things did not go well. If you are back to 100% next semester, it will be pretty obvious that the problems were related to studying abroad. You may then want to write something in your statement of purpose when you apply to assure them that attending grad school won't cause problems similar to what happened when you were studying abroad. This should be an easy sell, especially if the exchange program was in a very far away country and the grad program is in your home country/region.
At any rate, graduate school admissions people certainly do not want to see documentation about your health or personal relationships. They just need a believable reason for why that one semester doesn't indicate you are unfit for grad school, and the transcript showing you studied abroad far away and had some problems should address that. The only place you may run into problems is if your application is automatically filtered out before it reaches the committee -- but no way to avoid that.
The question posed in the title is a bit more challenging. You are able to attribute your difficulties to having studied abroad. For students who suffer mental health challenges at their home universities, graduate school admission is more challenging. Even in this case, however, I do not think they are interested in seeing medical or other documentation.

I'm sorry to hear about the difficulties you experienced while you studied abroad. You're right- grad programs will notice this, so I think it's important to acknowledge it, but find a way to put a positive spin on it/use it as a way to showcase your other strengths as an applicant. I don't think providing documentation of any sort will come into play though.
Assuming you have personal statements to submit, I would find a relevant way to include that you studied abroad because (insert a good reason here), but that you struggled during your time there for a number of reasons, including not integrating well with the culture. Then, turn it into a positive by saying what you took from the experience (maybe that you just discovered something new about yourself, you learned a new language, interesting coursework, etc), and talk about how you've bounced back (you're doing your best to improve your final grades, you now have a much clearer idea of what you want/need from an academic program, what you need to do excel, etc...)
The trick (and difficult part) is to do this in just a few sentences, and then quickly move on so it's not the focus of your personal statement.
Ultimately, I think the message you need to get across to them is "I know I took a stumble, but look how I came out much stronger and better prepared for your graduate program!"
One last thing I'd add: if any of your references writing your recommendation letters are privy to what you've gone through, you could always discuss your concerns with them. Now, you can't specify to them what to write in their letters since they're confidential, but in sharing your concerns with maybe just one of them, they might take it upon themselves to corroborate what you say in your personal statement by commenting on how you're an excellent student who - yes, took a stumble - but is still a great investment because of (insert strengths here). Of course, I would only discuss your concerns with your professor if he/she is someone you trust/are comfortable with.

Having experienced health/family/personal problems of any kind doesn't give one a magical get-out-of-jail-free card when it comes to grad school applications, so in this sense, documentation is irrelevant.
The area where documentation can be helpful is when one is trying to get reasonable accommodations due to a health condition that affects one's studies (in the UK I think the term is reasonable adjustments).  If you are about to leave your current geographical area, and you have consulted a medical or mental health professional where you are now, you might want to sign a release so that those recent records can be transferred to your primary provider, who would be the ideal person to hold a repository of all your records.
(Side note, some SSRIs have less side-effect weight gain than others, so you might want to talk with your doctor about possibly switching your SSRI to one with a lower side-effect profile.)

I agree with your answer--including the wisdom about transferring health records--but your first sentence comes off as a bit harsh.

@aparente001 I am not looking for a "get-out-of-jail-free card". I just think that I had circumstances which affected my true performance throughout the semester and that my performance in this semester doesn't reflect my true performance. I just don't want them to get an idea of "He went on exchange, neglected all his studies, had parties, and then failed" image, which is what most exchange students did in my school.

@Coconut - When you sit down to write your grad applications, you can write a short explanatory statement about the bad semester if you want to (this has already been covered on this site); however, students do not always choose to disclose a dx and the need for specific accommodations until after the admissions process is complete. At any rate, even if you do disclose in your application, at that stage documentation would be superfluous. Now, there is another possible way of dealing with the blip semester --

-- that is, through the letter of recommendation.  A recommender who knows you well could say, for example, "Candidate's poor grades during exchange semester [year] are not an accurate representation of her/his general performance" and just leave it at that; or (and this is something you get to decide, and indicate to your referrer) this person could add something like: "Candidate experienced family/personal/health problems during the semester [year] abroad." // You may find it helpful to read about 504 accommodations in higher education.

Just suck it up.  Talking about depression will make it worse...not only did you underperform, but you make excuses.
This is not a troll.  I have underperformed on all kinds of things in my life.  But once you are an adult nobody wants to hear about your excuses.  Get it done or don't get it done.  But just deal with it when you don't.  Life goes on and there are a million second chances.  But don't ask for special forgiveness.

Having a bad day?

I agree that people are quick to blame mental health or other outside factors rather than their own underperformance. That said, admission committees are interested in context. Certainly one can't explain away their entire undergraduate record with such claims, but in this case only a single semester is bad, and there was an obvious, temporary, and unlikely-to-recur cause for the problem, so I think it is altogether reasonable to provide such context for the committee in cases such as this.

This is not constructive advice, and speaking as an academic who is involved in monitoring the progress and well-being of graduate students in my department, I would hate to feel that any of them felt unable to disclose personal difficulty for fear of seeming to "make excuses"


text:
Are Prior Publications allowed in IEEE Transactions on Information Theory?
I have a paper written that is about 17 pages. I plan to submit a shortened version of it of only the main ideas to a conference with a 10 page limit next month, but I also want to submit the full manuscript for review to IEEE Transactions on Information Theory in parallel. I was reading their FAQ and I read the following paragraph which really confused me:

Policy on prior publication
Contributions should comprise novel and
  previously unpublished material; however, prior publication at (or
  parallel submission to) conferences does not preclude publication in
  this Transactions, provided this is properly referenced in the paper
  at the time of submission to the Transactions. Thereafter, submission
  to other journals is precluded, unless the paper is rejected by this
  Transactions, or is withdrawn. If all or part of the paper was
  previously presented at one or more conferences, a statement such as
  the following must be included in the authors' footnote on the first
  page of the paper at the time of submission: "This paper was presented
  [in part] at ... [and ...]."
If authors submit a paper that is a nearly verbatim copy of a prior
  conference publication, they have to indicate to the editors in a
  cover letter why they feel that republication is warranted. Editorial
  decisions will take into account any previous publication of submitted
  material.

Here is what's confusing me. At first, they say that its okay to have parallel submission as long as this is referenced in the paper. Then they say but we have to indicate this to the editors with a cover letter. I am confused, is what I am doing okay or not?

In the cover letter, simply indicate that the paper has been published by conference X (or in submission at X), and then list all the new items/parts in the journal submission that are not in the conference version.  The editor can then make up his/her mind whether the new parts are sufficiently different.   Usually parallel submissions are a waste of time because you would want to get some feedback first before going for a journal.  Also note that conferences usually do not allow parallel submissions.

There is no confusion, you can present the paper in the conference and submit it for publication.
But you have to tell the editors in a letter with the paper which conference it was presented at.
This is so that they know at the time and don’t find out “by accident” or, you never know, they could be at the conference...

Wouldn't this count as double publication with the conference proceedings?

"however, prior publication at (or parallel submission to) conferences does not preclude publication" taken from what you quoted.


text:
Can you publish a paper Simply Implementing another Paper's Algorithm?
There was a highly cited paper published earlier this year in my field which introduced a highly theoretical, non trivial, algorithm that relied on extremely heavy theory. The algorithm was exact (Gave the correct solution) but 3 papers were published later on criticizing that it was highly non practical (Its implementation was a nightmare) and proposed approximation algorithms that were simple to implement.
So over the past year, me and 2 of my friends have been trying to implement the exact algorithm and finally we were able to implement it. The algorithm spans 14 files and is implemented in Python. The running time is acceptable for the input size in my field (takes 3-4 minutes on a modern computer to terminate). We also verified its correctness on a data set and it really did predict the exact solution.
We would love to publish the code, but one of our advisors said that it is unlikely that Code only would be publishable in a reputable journal/conference. One option is that we can just put it on Github but that doesn't really count as a publication. Are there conferences/journals which would take a 1-2 page paper that just describes a hard implementation? The only novel thing we did was that we've had to make very minor changes to the algorithm to make it practical but proved that these minor changes don't change the correctness (just makes implementation a lot easier!).
Any ideas?

Does this algorithm have an advantage over others? Is there a problem you can apply your implementation to in order to show (with numbers and not just theory) that this algorithm performs better or faster than others?

@Steve That algorithm is exact, all other 3 algorithms are approximations. There are several data sets that the algorithm can calculate the exact answer for. Not sure if that's what you're asking.

In my limited experience: so far, reviewers nor editors ever commented/reacted on "open source" basis/aspect of my research. It could be for several reasons (like: core of the paper was so bad that they never reached paragraph where GitHub was cited) - but my impression is that journals with IF above 0 really don't value code/implementation/open source aspect, but the method, methodology and theoretical foundations. Also, I received only negative remarks on execution time / efficiency reporting in my papers -- algorithmic complexity is of significance, but timing is really useless for others

I believe you actually have two separate things here: your implementation, and your updated algorithm (plus the proof that the result is still accurate).  Even if the former isn't publishable, it seems like the latter should be.

Maybe you can provide deep insights from that algorithm in your paper? That's a good contribution.

It is hard to say without the details if it is useful for anyone to read such a paper but if the code itself can be beneficial to other researchers in the field, I would encourage you to send it to a proper journal.
Several open-source codes in my field have been published already. Assuming that the novelty of the code is sufficiently high, you can try to submit to journals at least partially specialized to code publishing such as Computer Physics Communications or SoftwareX. However, they have a relatively high reputation and prestige, so I would recommend them only if your work is interesting enough.

Well, there seems to be novelty: All experts in your field regarded the original algorithm as correct but unusable / inpractical. You demonstrated, that it can be used, and that approximative solutions are not needed.
You should elaborate on this and show, how the "small differences" improved the algorithm's run time.

This is a judgement call and will be for editors and reviewers. But the main question they will want answered is what is new/novel in your paper? If you can give them that, then they will be more likely to accept it.
The other question is, whether exactness is worth the effort. If the approximation methods give good enough answers then the expense of an exact solution may not be worth it in practice. Can you address that issue in your paper?
You don't describe anything here about scaling if that is an issue with the algorithm. A few minutes on a modern system may be good or bad, depending. If the algorithm needs to be executed once for each Google query, then it is pretty bad. If it has to be executed once per "noticed supernova" then probably fine.
There are a lot of questions your paper could address that might push the editor toward acceptance if you can handle them well.

An unprecedented implementation of an algorithm is trivially novel. This however doesn’t mean it’s publishable in a conservative journal.

Yes. However, rather than looking in a computer science journal, look for journals the users of your software read (unless, of course, your end users are computer scientists). For example, if astronomers would use your software, browse and search astronomy journals.
After browse the journals and finding example articles, write your software and manuscript so end users can easily use it. Your results will also need to be polished enough in order to be publishable as software. For example, many R packages get published in journals that either target statistical computing or domain specific journals. To build upon another answer that lists two journals, other ideas might include:

JSS if you're writing statistical software;
JOSS for general open source software;
EMS for environmental software;
PLOS Computational Biology for biology; and
SCFBM also for biology or medicine.

In fact, you should not underestimate your effort that you put to make a pure theoretical approach into some practical application. I may not be an export in your field of expertise, but I know sometimes implementation of an algorithm worth more than its theory behind it these days from computational science point of view. If you are working in a pure theoretical department that may be the cause of the underestimation of your adviser. But there are a lot of research paper out there, which are published in reputable journals/conferences just based on their remarkable implementation which made life easier for computational science research community.
I would recommend first of all find a good benchmark dataset, which could show both the correctness of your code and also the power of its accuracy in comparison to approximation approaches. If you choose a benchmark dataset, which has a practical value itself (e.g. a biological dataset to find a relation between some genes of bacteries which may be a hot topic in biology)  it could add quite a more value to the novelty of your work.
At the end, I believe it depends on you or your collaborator that how think about your research and how you could make good story out of it. Besides some few other example of journals that are addressed in other answers, you could consider this one: https://joss.theoj.org/, which their editorial board members are quite reputable.