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The problem of incompetent peer-review
In which fraction of the recent papers is significant incompetence of review(s) observed in natural sciences? In my searching, I've only come across one example of such a review... is anyone familiar with any others?

While I'm not a highly published researcher, it seems to me that if a reviewer is that far off the mark with his/her/zirs/their comments, the paper may potentially need to be re-written to be clearer in the misunderstood sections.

This is currently a polling question, and needs to be revised to be a solicitation for answers rather than a poll.

I have edited your question to attempt to change it from a poll question to a question aimed at definitive answers.  Please feel free to adjust if you find that my edits have problematically changed your intent.

@tonysdg: It is all very nice what you write, but I have clearly stated what we call an incompetent review and what we discuss. :-)

@phys_chem_prof we're not here for discussion. We're here for Q&A. If your motivation is "I would like to have a discussion about ..." or "I would like to rant about ...", or "I would like people's opinions about ..." or "I'd like to take a survey about ..." then this really isn't the place for that at all.

I think @tonysdg is on the right path. I never got a rejection for a paper. But, my coauthors and I made sure that they were clearly written to take the reader through the experiment, results, and discussion in such a way that there would be no unanswered questions. While it is easy to call the reviewers incompetent, and good writing is really hard (OK, really really really hard), perhaps you should look inward at least a bit. My take away from the listed comments that you objected to is that your paper was not clear enough, and that led the reviewer to go off the rails.

Despite @Jakebeal’s edit, I still think that this question can only attract answers treating it as the poll it was originally intended to be. The only way out would be asking for a study covering these aspects (e.g., “Are there any studies on the satisfaction of researchers with peer-reviews?”). Even if such a study exists (which I doubt), it will almost certainly not comply with the explicit criteria in this question.

@Wrzlprmft: The publishers make such studies by sending satisfaction questionaires to the authors of the accepted papers, but the results are kept for their internal use. The question is indeed about percentages rather than about the topic starter is a good writer or a bad writer. I agree that the question is a bit of a poll, but most questions on the website can qualify for a poll since an univocal answer does not exist to most of them.

@phys_chem_prof: but most questions on the website can qualify for a poll since an univocal answer does not exist to most of them – There is a huge difference between a (good subjective) question lacking a definite answer and a poll. In a poll I cannot agree or disagree with an answer (I cannot say whether the answerer gave an accurate account of their experience) – I can only post my own experience as an answer (thus we get tons of answers). In a good subjective question, I can agree with existing answers by upvoting.

@phys_chem_prof: I support reopening this question because it is a request for data, not a rehash of the "how to handle" question. However, I should also mention to anecdotal evidence is probably not your best route here—SE sites are not designed for guesswork and speculation.

@aeismail: As noted above, I agree that a question requesting data on this would be a good fit for this site, but this question would need heavy editing to be good, more precisely, all the restrictions would need to be removed (because there is almost certainly no study/data that exactly investigates the OP’s criteria). Due to this and the existing answers and downvotes, I strongly opt to have a fresh question on this.

I've reopened this question, but I'm not sure this should be re-opened, given that (1) the question is now completely different from what it was, and (2) the answers below don't really relate to the new question. I'm open to discussing on [meta] if anyone would like to.

It's difficult to provide any sort of general assessment across all fields.  My experience in peer-reviewed publication, however, has led me to conclude that truly incompetent peer reviewers are much rarer than it often "feels" to authors.
It's always fun and cathartic to slag on Reviewer #3, but I disagree with your assessment of what makes an incompetent review.
Scientific communication is not a one-way street, although people often approach it in this manner.  When you are writing an article, it needs to be well-matched in presentation to its audience.  Comments of the form that you discuss typically reflect a disconnect between author and audience, resulting from one of two failure modes in the paper:

The material may not be presented as well as the author thinks.  We get very familiar with our own work, and often start losing track of all of the assumptions and delicate connections between different aspects of the work.  It's hard to linearize the complex tangle of relationships in most work into an accessible form.
The presentation may be good, but poorly matched to the audience.  Different communities have different things they are looking for in papers and different contexts against which a manuscript will be judged.  Often a paper that will be lauded by one community will be hated by another because the paper isn't appropriately presented for that community.  This doesn't mean anything is wrong with the community, but rather with the authors' understanding of that community.  For example, different aspects of some interdisciplinary work of mine have been published in both the programming languages and synthetic biology, and the two papers are utterly foreign to one another even though they are about essentially the same work with the same piece of software.

A truly incompetent review, on the other hand, is one that doesn't bother to particularly discuss the paper at all.  For example, as a program chair a couple of years ago, I received the following review for one of the conference papers, as presented here in its entirety:

Nice work.

The reviewer was clearly happy with the paper, but this review gave essentially no meaningful input to the decision process.
So, after all of that preamble, let me return to the quantitative aspects of your questions:

My observation has been that the number of truly incompetent reviews is vanishingly small.  Editors and conference chairs generally deal swiftly with reviewers who fail to live up to minimal standards.
Reviews showing a frustrating disconnect between reviewer and authors, like you present in your question, have been steadily decreasing over time as my skill as an author increases.
I spend very little of my time appealing or writing rebuttals---probably less than an hour per paper, on average.  I spend much more time than that revising in response to reviewer comments, however, and my papers are generally much better for the work.

@phys_chem_prof I had a lot of experiences like you did as a graduate student.  Nowadays, I still get them (less often, because I'm a better writer), but more importantly I now understand that a comment such as: "This phenomenon was already studied by $authorX" actually means "It is easy for researchers not familiar with your work to confuse it with the work by $authorX.  You need to provide clearer explanation and evidence that differentiates it from that work."

@phys_chem_prof Please re-read my answer more carefully, as well as the one linked in "How to React to Incorrect Claims by Reviewers?" and you will find that my actual position is quite different than the caricature of it that you have presented.

Let's break the possibilities in two, shall we?

The reviewers are indeed incompetent. If it is a journal, answer the remarks. If it is a conference, submit somewhere else. It happens. However, this possibility is rather unlikely and will add nothing to you as a researcher, so..

Your paper is 'bad'. Don't be angry, but from your question, it seems like you failed to previously address the remarks. Most of the really good papers I've reviewed answered my potential remarks in the paper itself. For instance, they said that ""The applied method is wrong"", therefore, it would be good for you, and your paper, to have a paragraph somewhere saying "While it may appear that the method is wrong, we prove that it is indeed right because....". That way, not only you already cleared any ambiguities, you demonstrate that you reflected on the contents and possible ramifications of your work and that is important.
You might have made some wrong assumptions about your audience, for instance, assuming that they will have a higher level than the reviewers actually have. This is a bad assumption, in general, because it is pretty rare to get reviewers/audience with a proper level. You really have to "take you audience by the hand" and guide them through the work, making the minimum amount of assumptions possible (leeway here if you don't have enough room).

Long story short, your paper let the reviewers misunderstand the contents, and that's bad.

Keep in mind that the writing itself is more important than the contents.... yes, I know, but it is true. It's easier to get accepted when you submit a very well written paper, on some not-that-good ideas, than a revolutionary idea, poorly written. Indeed, if the idea is that different (which is very good), the writing part has to be even better, to surpass the bias people have against new stuff and make them understand. (we usually try to understand stuff based on what we know, and new concepts that contradict it are harder to accept).
Of course, without properly reading the paper, this is mostly guesswork, but I've seen it enough to guess with some certainty. Nevertheless, if you paper is good, it will get better by doing this stuff, so no harm done.

That said, I'm not sure if I have n publications in the last y years and I don't care to count (my name is there, my scholar exists, have fun). Sorry, but you don't get to rant and pick who answers it, that's not how the world works.
I know you are probably fuming right now, because none of what I said is what you wanted to hear. Please, before you answer, calm down. I've been there, done that, it wasn't good for anyone. I'm on your side here, otherwise I could've just downvoted the question, which would be justified, from your tone alone and moved on. This is not the place for those angry rants.

You put this much better (and more nicely) than I did in my comment above.  Perfect!

After the edits and comments removal, my answer doesn't make much sense...


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Does submitting a paper in Latex format enhance the chances of acceptance?
If there is an option to submit your paper in either Latex or Word, which format should be given preference? Does it affect the chances of acceptance? My paper relates to computer science & engineering, with a few mathematical formula, diagrams, and tables.

This is very field-dependent. Many non-STEM publishers don't even accept LaTeX manuscripts (unfortunately).

This question just makes me think of this.

If both are allowed then both will be fine. I would choose the one I am most comfortable with. Using a program you are less familiar with increases the chance of making a silly error. Such errors are much more likely to work against you than the choice between Word or LaTeX.

If both are allowed then both will be fine. I disagree. It is also allowed to submit a poorly written or poorly formatted paper, but that does not mean that all papers have equal chances of being accepted regardless of how they look. Considering that LaTeX and Word produce very different looking documents, saying "both will be fine" does not sound like very helpful advice.

@DanRomik In my field (sociology) papers are primarily judged on their content rather than their looks. Not because sociologist are superior human beings, but because most journals put quite some requirements on the submitted paper (double spaced, graphs and tables placed at the end of the document), which makes all papers look pretty ugly, regardless of what program was used to create it. You can still make errors, as you mentioned, and that will work against you, but the best way to prevent errors (in the short term) is to use the program you are most comfortable with.

I very much agree that the answer will depend strongly on the field (which is why I asked OP to specify the field, and refrained from writing an answer myself since OP has so far not provided that information). My experience is that there are even fields where many people are so used to Word documents that (to my amazement) they consider them superior to LaTeX-prepared documents.

But you cannot deny LaTeX looks way better tha Word.

@ShaunHan I do deny that. see my comment  above: most journals I submit to have so many requirements that even latex documents look exceptionally ugly.

This is coming from a more engineering, physics and mathematics point of view. In many sub-area of these fields, LaTeX papers have a more distinct professional feel. This is mostly related to the formatting of the equations and the symbols. Furthermore, numerous authors in mathematics are openly LaTeX advocate. As such, I believe (but this is no hard fact) that you might get a slightly more positive bias using LaTeX than Word. Keep in mind that the most important part is to submit a clear well-written document and that the format is second to this former fact.

you might get a slightly more positive bias using LaTeX than Word If it's true, don't you think that's an issue?

I do not believe this is an issue. Allow me to explain. I believe LaTeX produces a much better typesetting and formatting of equations than Word. It makes the equation much more readable, better formatted, more structured. For the same reason you could prefer a paper to another because the figures were presented in a much better fashion, I believe you can be slightly biased toward a paper due to its good use of LaTeX formatting. When I see a poorly made Excel graph in a paper compared to a perfect matplotlib graph, I get a negative bias for the excel paper. Same for LaTeX and Word...

Do you find it equally unproblematic that I view LaTeX formatted papers in my field as likely coming from the Math/Physics/CS world whose decided to apply their field's tools to my field's problems - usually with an incomplete understanding of the state of the field, the context of the problem, and most of the complexities involved? Or does this clearly apply to the "prettiness" of a well-laid-out LaTeX document?

To me it is only a matter of equations and symbols being better formatted. I would not feel the difference between a well written word paper using MathType for instance and the same paper written using LaTeX.

Let's start by acknowledging that there is a very good reason why LaTeX is the standard system for writing papers across all of math and large parts of computer science, physics, statistics, and other technical areas. No one has yet come up with a system that produces better-looking, more esthetically pleasing, well formatted documents that do as effective a job of communicating complex technical ideas, especially those involving lots of mathematical symbols and formulas. By contrast, documents generated by Microsoft Word are generally... meh (and if they contain math formulas... double meh).
With that said, I believe that the answer to your question is: yes, LaTeX papers and Word papers are far from equivalent in terms of their chances to be accepted to a computer science journal. I see several issues here, some direct and some indirect:

One effect is that, as I was opining above, a properly written LaTeX paper will simply do a better job of communicating the content of your ideas to the reader than the same paper written in Word. Thus, the cognitive load on the journal editor and referees that stands between them and understanding what you are trying to say and what the contribution of your paper is will be higher with a Word paper. This will translate to a difference in the chances of acceptance (better chances for the LaTeX version).
Another effect involves the fact that if you are writing a technical computer science paper in Word then it is extremely likely that you are a very inexperienced researcher, possibly from outside of academia. That by itself makes it a lot less likely that your paper is well-written (aside from which software it is written in) and that the ideas in the paper are good enough to make it worthy of accepting. And the editor and referees know that, and are likely to take the paper less seriously as a result (this is the bias alluded to in other answers, and lamented by some), subconsciously and/or consciously, even if you are in fact an experienced researcher. This would again translate to a reduced chance of acceptance for a Word paper. Perhaps this bias is unfair, but there it is.
Even without the bias I mentioned above, for the reason explained in item 2 above I still predict a clear statistical correlation between the Word/LaTeX typesetting information and the quality of the paper (and therefore the chances of acceptance). This correlation of course does not imply causation; without the bias, it would not be the typesetting system that was used that caused the paper to be rejected, but the overall low quality of the paper. Nonetheless, the fact remains that by writing your paper in Word, you would be choosing to join a group of authors whose papers have a statistically lower rate of acceptance, even if your situation is somehow different than most of them.

As a final caveat, if your area of computer science has papers with very few mathematical formulas, then what I wrote above is probably still correct, but to a lesser extent, i.e., the chances of acceptance would be closer to equal, but I still predict a small advantage for LaTeX.
See here (including many relevant thoughts in the comments section) and here for related discussions.

Counter-example: In some aspects of what I do, "Author did some clever math but utterly misses the practical applications and scientific relevance of their question" is highly correlated with a LaTeX formatted paper. If I get a LaTeX formatted paper from an author I don't recognize, my first (and admittedly biased) feeling is "Ugh..."

@Fomite: LOL. Reading your "ugh" comment I feel like I'm staring into a looking glass world, but at the same time your description of how pure math people think is right on the money - hilarious!

I always love talking to computational/mathematical colleagues. It is a little bit like staring into a mirror universe.

"Another effect involves the fact that if you are writing a technical computer science paper in Word then it is extremely likely that you are a very inexperienced researcher, possibly from outside of academia" - care to substantiate this?

@jpou the first link at the bottom of my answer provides a good bit of evidence, at least for theoretical computer science. I am reasonably confident the claim is true for most if not all other areas of CS, but not sure how to substantiate that.

@DanRomik have you considered the fact that by using proper template, your article will look exactly the same, regardless if it was prepared in LaTeX or Word? All IEEE publications have uniform styling and look the same regardless if they were typeset using Word or LaTeX.

@jpou No I haven't considered it because it's not true. You can achieve similarity in superficial things like choice of font, but Word and LaTeX (more precisely, TeX) use completely different algorithms for line breaking, word spacing, line spacing, page breaking and more. TeX's algorithms are described in detail in Knuth's The TeXbook (a masterpiece of ultra-geeky writing btw). If you read it you would start to understand more in depth why TeX achieves such great results. Word simply cannot (or rather, does not attempt to) replicate this type of careful optimization in document preparation.

As for IEEE publications, I will hazard a guess that the uniform look is because they are all typeset in LaTeX, including the few occasional papers that are submitted in Word but converted to LaTeX prior to publication. But that's just a guess, and I'm open to seeing it challenged by anyone who's more knowledgeable about such things.

@DSVA For biomedical journals as well. There's nothing quite as effective as reading a raft of LaTeX formatted papers to make me happy to return to the warm embrace of professional typesetters and layout artists.

The final look and feel of your paper must look like it belongs in that journal, regardless of which software you use to produce it.  I will, as a reviewer, subconsciously bias towards a reject if I find that the paper looks amateurish. This means it is an uphill climb to change my recommendation to an accept.

I think this is probably accurate in many fields (although I really wish it wasn't).

OP is talking about the version submitted for review, how is the look relevant? The journal will edit the typesetting before publication anyway.

@Cape Code most papers in my area are submitted in the format of the final version.  Personally, I hate papers that look like an undergraduate report.  So 'look and feel' can be interpreted as a paper written by a professional either using MS Word or LaTeX.

@Prof.SantaClaus what other things completely unrelated to the content do you hate in papers you review?

I agree that having a professional look and feel consistent with journal and discipline expectations is important. I just note that in other fields (e.g., psychology and APA style). This look and feel is more about conformity to a style manual (e.g., double spacing, consistent paragraph formatting, headings consistent with styles, etc.). Word processors can sometimes make it easier to conform to these idiosyncratic requirements.

No.  Following submission instructions found in "Instructions to Authors", whatever they may say, will pretty much insure that your paper gets reviewed, and not whatever the digital equivalent of "returned unread" is, but reviewers generally see a pdf, and couldn't care less how you wrote the paper.  They will care if you gave the manuscript the attention it merits, regardless of the tools you use to prepare it.
As an aside, when you choose to work in Latex, you need to think about how that interacts with any collaborators who will need to edit and mark up your documents.    It's certainly not undoable to work with Latex nonusers, but it does require thought and planning.

If you are comfortable using Latex (i.e. it won't slow you down to use it), and it is well-supported by the journal (i.e. they provide a style file), I would recommend it, as it produces a paper that is much easier for the referees to understand. Reducing any barrier to referee understanding is great!
But just because a journal accepts both Latex and Word, doesn't mean there isn't an internal preference. Sometimes you have to dig a little bit to find this. Look at the publishing details: some journals will waive part of the publication fees if you give them a Latex file; others state they will take longer to move from acceptance to publishing with Latex than Word.
Personally, I think that the advantages of Latex in terms of appearance and bibliography-handling are large enough that I put up with its other annoyances, and use it whenever possible.

I think "it produces a paper that is much easier for the referees to understand" is something of an unsubstantiated claim. I've received well-formated, clear manuscripts in either format, and unintelligible garbage in both formats.

Fair point, but does not match my experience. This is probably half selection bias, but I have never seen a truly hideously formatted LaTeX submission in my field (where there are standard templates for many journals, which everyone uses). Meanwhile, even very respected groups have sent me Word-prepared docs that are just awful (figures in random locations, separated from captions, etc.)

Note: this answer comes from someone who does not review computer science articles. There seem to be a strong belief in your field that using LaTeX is The Way to go. I would suggest to comply for your career's sake. My answer still applies to other fields.

I truly hope it doesn't. It would be extremely unprofessional for reviewers and editors to favor their pet typesetting tool when assessing the content of a paper. Especially knowing that in many cases, the paper will be re-written from scratch by the typesetter and thus it becomes irrelevant.
But possibly, writing papers with LaTeX might reduce your research output, and thus the quality or number of the papers you submit since it's been observed* that using LaTeX is less efficient than MS Word to write academic papers (with the exception of a small subset of fields).
So, unless your document is made mostly of equations, data suggests you will make fewer errors and spend less time writing your paper using MS Word than LaTeX.
*See: Markus Knauff, Jelica Nejasmic (2014) An Efficiency Comparison of Document Preparation Systems Used in Academic Research and Development PLOSONE

If only people would stop uncritically linking to that paper. Their conclusion is in no way supported by their study (unless you are in a field where you do a lot of retyping text written by others).

@TobiasKildetoft The retyping is to be able to standardize the task. I find it to be an appropriate proxy for writing, in absence of something better. I will amend my answer if new experimental data weakens their conclusions.

How is something being hard to test properly an argument for drawing conclusions based on something only vaguely related? The only conclusion one can draw from that study is that we still have no idea if LaTeX is worth it for people outside a few fields, not that it is not worth it (I mean, the study even barely disguised its accusations that everyone who uses LaTeX is irrational).

@TobiasKildetoft I think we have a pretty clear idea that using LaTeX for documents with mostly text is a big waste of time. Especially since in many fields, the typesetting is redone by the journal anyway.

I am not sure who "we" are (I certainly have no idea), and I also don't know how "we" have this idea.

The area is computer science & engineering with few mathematical formula, diagrams, and tables

You need to use Latex. Full stop.
Even when you don't know Latex, you are supposed to learn basic math formula, figures, tables in less than a day. (Tables are pieces of cake with this online tool http://www.tablesgenerator.com/)
I never heard of anybody in Computer Science that does not know Latex. Call me a jerk and down vote if you like, but such a person will become a topic of a joke.
If one can't prepare a document in Latex, how can (s)he do any programming? And if they can't do programming, I can't take their Computer Science research very serious.

UPDATE:
Everybody is talking about how Latex produces beautiful math equations etc, and forget how it is efficient even on basic tasks. I was once a Word user. In fact, I wrote my undergraduate thesis using Word 2003, and it was a painful experience, even though I didn't have any math equation in my thesis.

Creating a Reference section, and citing a paper in Word is painful, and time consuming.
Changing reference format from John Smith to J. SMITH (ACM style) is also painful, and it can take you days. Changing the citation from (Smith 2003) to [1] is also painful.
Referring to a figure is also painful.
Formatting (pseud-do) code is also painful.
Keeping the format Heading1, Heading2 etc is really painful.

The list does not end here. All of these are pieces of cakes in Latex, and the most important thing is it gives you the feeling of total control of your text.

But possibly, writing papers with LaTeX might reduce your research output, and thus the quality or number of the papers you submit since it's been observed* that using LaTeX is less efficient than MS Word to write academic papers (with the exception of a small subset of fields)

I don't care if anybody/paper says preparing documents in Word is more efficient. It's like saying typing with two fingers are faster than typing with 10 fingers. It is true for some people, but it will become a joke for many people.

Why would you assume people who don't use LaTeX are those who "don't know LaTeX" or "can't prepare a document in LaTeX"?

@CapeCode I am agree with you. If a computer scientist does not use LaTeX, it doesn't mean that (s)he can't learn it.

And if they can't do programming, I can't take their Computer Science research very serious. WHAT??????

Scott Aaronson, in his blog at http://www.scottaaronson.com/blog/?p=304, agrees with your general advice to use TeX; he lists non-use of TeX as the first in his list of "Ten signs a claimed mathematical breakthrough is wrong".  But in that context he also mentions two respected computer scientists who don't (or didn't at that time) use TeX: David Deutsch and Lov Grover

@AndreasBlass note that I linked to that same page (and another slightly relevant one) at the bottom of my answer.

@AndreasBlass Deutsch is a physicist though, not a computer scientist. He has forayed (a little) into CS but I very much doubt he’d describe himself as a computer scientist.

@qsp Endnote and other reference managers make managing references and moving between reference formats trivial. Word has styles which are trivial to use. You just need to learn to use them, which many users do not. I'm not saying LaTeX does not have benefits. But if you're able to learn LaTeX, then it would be trivial to learn how to use Word more effectively.

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CS PhD application with low GPA but extensive research experience
I have recently graduated from a non EEA university—though arguably one of the better/best schools in its field in my country—with a CGPA of 2.90, majoring in Computer science. I used to study Bioengineering/Bioinformatics—from which I hold a publication—before switching to CS. I suffered from an extensive period of burnout and some personal problems starting my second year in college—after getting a 3.30 in my freshman year, not exactly an upward trend in my grades in following years either—resulting in my current CGPA. I did a summer research at my school after my 2nd year which resulted with that conference publication I mentioned above, did two internships of Computer science (first one at a company, second one at one of the top 3 CS universities in the USA), I have two posters from my graduation project (one presented at an international conference the other one not-so international), and an upcoming journal or conference paper depending on deadline circumstances.
So, my cliche question is: should I take my chances with good/top Computer science master's programs throughout Europe (e.g., TU Eindhoven, EPFL, RWTH Aachen or TU Munchen) before applying for a PhD, or should I stay at my school for my MSc and then apply for the PhD? I'm not even hoping for a scholarship at this point, just an acceptance. I haven't taken the TOEFL and the GRE yet since now I'm in my gap year, I will be taking them soon in order to start my application procedure.

Apply for everything you are interested in. The publications and research experience will certainly help. If you don't get into a PhD, doing a MSc and doing it well (perhaps with another publication) will be the way to get a into a good PhD program.

Do you have financial issues? Can you afford to pay the application fees?

@scaaahu Thankfully no issues, I really don't mind if I don't get a scholarship -tuition waiver etc- either. My only concern is to get into one of those programs I mentioned above.

@CharlesMorisset Well, that went better than expected. I just wanted to know if applying was worth it. Will take my chances, thanks for your answer.

In the Netherlands the range of grades that is given is smaller than the existing range. Or rather, it's near impossible to get a top grade (a 10), and very difficult to get a 9, even though the passing grades go from 6 to 10. My experience is that the Dutch, even though they know about other grading systems, tend to have a bias for interpreting GPAs in their own system. In other words, your GPA might not hurt you as much as you think in Eindhoven.

You need to check the requirements of the individual schools to see if a transfer is even possible. For the German schools, at the very least, the computer science degree is often subject to "continuity" requirements, which make it very difficult to enroll in a master's program unless you already have the bachelor's in the same subject from a German university (or can demonstrate "equivalence" of your degree if it's coming from abroad).
In addition, admission often depends fairly strictly on GPA, at least at the master's level. Recommendations hardly matter, if they even count at all. At the PhD level, the process changes, and becomes more like getting hired for a job. So it may be better to wait until you're applying for PhD positions.

I will keep that in mind, thank you for your answer.

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Certificate in data mining
I am interested about getting a certificate in data mining. I found three so far, and these are the following:

MIT - Data and Models in Engineering, Science, and Business
Stanford - Data Mining and Applications Graduate Certificate
UCSD - Data Mining Certificate

Has anyone taken any of these courses, and are they worth it? Would I benefit in terms of career opportunities with one of such certificates?  I already have a background in data mining, however nothing is on paper, so I thought it might be good idea to get a certificate.

As with any certificate course, it really depends on what you intend on getting out of the program. All of those are well-respected universities, and the coursework will almost certainly be extremely informative. In that regard, you'll learn a lot. On the other hand, there exists a frankly ridiculous amount of high-quality, freely available information online related to data mining from many universities, including some of those you listed above, so you can definitely learn all that without paying a not-insignificant sum for the experience.
Regarding job prospects, it really depends on where you're looking to be hired. This answer from Workplace.SE is an excellent overview of how useful a certificate can be in helping you get hired, and this question from Programmers.SE has many useful answers discussing how certificates like the ones you mention are viewed in industry. Long story short, they're usually not that useful for jobs unless they're industry standards, which the ones you list are not.

+1 for links to other SE questions. And, somehow, cannot get "The main purpose of certifications is to make money for the certifying body." out of my mind (especially related to current raise in prices of higher education).


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Distributing published papers if I am the first author
In some interviews for industry positions, I have been asked about my prior (applied math) research experience and to go into detail about the models I have constructed. After I gave him a high-level overview, the interviewer asked that I send him the paper so he can see some minute details. The paper is published in a Springer journal and costs 39.95 to see without journal subscription. My questions are

As the first author of the paper, am I legally allowed I send him a downloaded version of the paper over email?
If not, am I legally allowed to send my personal copy of the manuscript (i.e. the version I submitted to Springer)?

N.B. the paper is not on the arXiv.

You've read the copyright agreement you signed when the paper was accepted, right?  What does it say about this?  That's the authoritative source; other answers will just be guesses.

Regardless of the specific language of the copyright agreement, just give them a copy of the paper.  Sharing copies of one's own papers has been standard academic practice forever.

Different publishers have different guidelines, but I think they all allow your first case. For example, Elsevier's author rights page states:

Authors transfer copyright to the publisher as part of a journal publishing agreement, but have the right to:

Share their article for Personal Use, Internal Institutional Use and Scholarly Sharing purposes, with a DOI link to the version of record on ScienceDirect (and with the Creative Commons CC-BY-NC- ND license for author manuscript versions)
...

If you're worried, I do recommend checking each publisher's page to verify your rights.


text:
Why reference articles from and/or submit articles to low impact factor journals?
I recently read this FAQ that explains a bit about impact factors. After reading, I was curious... what would be some reasons why researchers would use papers from a low-impact factor journal, say, a journal with IF = 1?
Wouldn't all researchers concentrate their efforts on starting their literature search from the highest impact factor journals, and then develop their new work on this basis?  That seems logical to me and also most beneficial to a researcher's career in academia.

"What would be some reasons why researchers would use papers from a low-impact factor journal, say, a journal with IF = 1?" - to ultimately increase the journal's impact factor to 2?

More seriously, please expand your question as it is currently not very clear. What do you mean by "use"? Build upon and cite? Read? Read first, before reading others? "and then develop their new work on this basis" - what makes you think the findings that the researcher wants to build upon have been published in a high-IF journal? What if a researcher works on a project X that relies on findings Y, and Y can only be found in a low-IF journal? "most beneficial to a researcher's career in academia" - why do you think that is?

Because there would be a whole heap of additional work (and brain power) included for sorting the search by impact factor. And then you might miss the best, the needle in your haystack. This is why people like to have search results ordered by relevance, which is a much more complex measure than impact factor, keywords, the number of citations and whatnot alone.

I think you have a very poor idea about how research ideally should work. It is not just ad hoc, random redressing and fiddling with the latest results published in Nature, but most researchers actually have an established (and preferably somewhat new) direction of research of their own.

@Greg, I would love if that were included as part of an answer.  It's just perfect.  :D

@Greg, your comment is presumptuous; nowhere in my question do I suggest that I, nor the researchers I work with, do not have established and new directions of research of our own.

Two reasons come to mind. A) They're good papers. B) They are relevant to his research. (?)

The question is flawed. IF is a journal-level metric, not an article-level metric. Even as a metric for journals, it has come under serious criticism, as a simple Google search will show. E.g.: http://www.editage.com/insights/why-you-should-not-use-the-journal-impact-factor-to-evaluate-research

When you're doing a literature search, do you even know what journals particular papers are published in, let alone the impact factor of the journals?  I find papers with online searches, skim them to see if they're relevant, and only when I decide to cite them do I look at the journal - and that only long enough to create a BibTex entry.  And often the entry will be provided, so I don't even look.

Just say no to impact factors: http://www.nature.com/news/beat-it-impact-factor-publishing-elite-turns-against-controversial-metric-1.20224.

Contrary to many of the above comments, I think this is an excellent question. The process used to select journals for publication is completely opaque when viewed from the outside. If someone thinks academic research is like the olympics, where all participants are competing for the gold medal (such as nobel prize or fields medal), this question makes perfect sense.

Also, i made a number of edits. OP, feel free to revert or fix if I changed too much.

@eykanal your irresponsible edit of the title changed the question substantially. Please revert.

@eykanal: "If someone thinks academic research is like the olympics (...) this question makes perfect sense." - if you start from an absurd enough premise, almost every question makes perfect sense. I do not think the question is absolutely terrible as a question, but I think the flaws in the premise (some of which I have pointed out in my early comment) are obvious enough that they would have deserved some consideration by the OP before the question becomes worth asking and answering on its own.

The question is unclear, but let me try to answer anyway.
You assume that for any given field of science, there exist journals with high impact factors. This ignores the specifics of individual fields. In very basic sciences, impact factors are usually high, because many researchers from other fields will use the findings in their own for. For example a researcher from the field of neurology will be cited from the people from neurology, psychology, psychiatric medicine, artificial intelligence, computer science.
On the other hand, more niche the field becomes, smaller is the pool of the scientists that could use the results. While a computer scientist may cite the paper from neurology to reference certain brain structure that inspired his algorithm or massive processing cluster architecture, there is basically no way that the neurology scientist would cite the aforementioned computer scientist.
That's why there are huge differences among fields regarding the impact factor of the top journals in the category.
Does this mean that the paper on some novel computing architecture is less valuable? Certainly not. While very few computer engineers working in R&D of new commercial computer systems will be interested in neurology, quite a few of them will read the paper on novel, more efficient architecture of massive computer clustering.
However, since they are end-users, their reads will not transform in citations, while significant proportion people that read advanced neurology paper will publish papers on their own and perhaps eventually cite it somewhere (because they are scientists, in that essence, not end users).

First thing I thought: IF1 isn't that bad! :)

Thanks @xmp125a.  I think your answer, as well as Walter's answer, address my misunderstanding the best and most concretely, despite there being other great and highly upvoted answers to my question.

"In very basic sciences, impact factors are usually high" - Well, I would guess pure mathematics is just as basic as a field can be, and math journals have low IF (1 is actually pretty high, none raising above 5 last time I checked). Maybe the point being that math result are not used by other fields in the two years after publication (but rather, in the next century or so).

@BenoîtKloeckner Depends on the definition of "basic".  In this case, I think it is meant to apply to those areas which tend to have significant, multi-faceted, and immediate applications in industry and commerce (and the military, probably). Mathematics is basic in the "fundamental framework that all science is executed within" sort of sense, but rarely sees immediate use. As you say, it usually takes more than two years to synthesize a mathematical result well enough produce publishable new results, and most results only lend to a small number of potential new research vectors at the time.

There are some major flaws in OP's other assumptions, but "You assume that for any given field of science, there exist journals with high impact factors" - that is actually a reasonable assumption, since some of the highest impact-factor journals (Science, Nature) accept papers from any branch of science. If we're talking about literature reviews though, you wouldn't normally start with those journals.

@arboviral: I do not think I have ever knowingly encountered a publication in Nature or Science that was in any way relevant for my area of applied CS. Some interdisciplinary niche projects aside, I'd claim that both Nature and Science are not a part of the reasonably eligible publication venues within my field.

@O.R.Mapper both Nature and Science accept sufficiently important findings from any area of science. "Science welcomes submissions from all fields of science and from any source" (http://www.sciencemag.org/about/mission-and-scope). I don't have any Science papers either, but that doesn't stop it being theoretically within-scope :)

@arboviral What O.R.Mapper said, but replace "applied CS" with "theoretical CS".

@BenoîtKloeckner Mathematics is pure {/warning:XKCD}, not basic. Probably the term basic was misused here. I can't correlate basic with neuroscience either.

@Mindwin I meant "Basic" as an opposite of applied. Perhaps there is a better word for this, don't know. As with mathematics, yes, the 2 year window basically precludes mathematics to benefit from applications of its results. Nevertheless, my point still stands: there are fields where readership immediately translates into citations, there are fields where it does not, and there are fields with very small population of consumers of any sort :)

@xmp125a "pure"

The "impact factor" of this answer is lower than a half of the highest one, yet it still be accepted by the OP.

@Mindwin Pure mathematics works for me, pure neurology not so much.

@O.R.Mapper in my broad area of CS I am aware of exactly 1 article (letter) published in nature, and 1 article published in science. And the citation counts on each of  those 2 articles are roughly as high as the next half dozen papers I've read combined. (Though citation counts follow a Zipf distribution so not surprising really)

What would be some reasons why researchers would use papers from a low-impact factor journal, say, a journal with IF = 1?

Researchers use papers that are relevant to their research, regardless of where they've been published. Being published in a less prestigious journal doesn't mean the result is less true - it usually means the paper is seen as less significant, usually because the authors/referees/editors think fewer people will be interested in the result.
But sometimes those people are wrong, and a paper is more significant than it appeared, and sometimes the paper may be obscure but it has exactly the thing you need for the work you're doing.
(Also, IF values vary dramatically by field.  The top journals in my subfield have impact factors between 0.6 and 0.7, so an impact factor of 1 doesn't sound low-impact to me at all.)

Wouldn't all researchers concentrate their efforts on starting their literature search from the highest impact factor journals, and then develop their new work on this basis? That seems logical to me and also most beneficial to a researcher's career in academia.

No, they wouldn't.  Indeed, if everyone else were doing that, a researcher could get a big advantage by being the only person mining paper published in low impact-factor journals for ideas that other people were overlooking.  In my experiences, researchers skim pretty broadly, looking for papers that might suggest new ideas or ways to advance their work, and I've never heard of anyone restricting their reading to the journals with higher impact factors.

+1 for "Indeed, if everyone else were doing that, a researcher could get a big advantage by being the only person mining paper published in low impact-factor journals for ideas that other people were overlooking." I was thinking along the same lines. Indeed, I sometimes wonder why there seems (in this group especially) so much emphasis on working on the hottest new fad, things that all the big-shots are working on. It seems to me that average ability researchers would have better success looking for small gems slightly away from where the giants of the field are strip-mining.

Relevant article: https://www.linkedin.com/pulse/easiest-most-effective-way-improve-return-investment-rd-kelvin-stott

I know of someone who built significant work using a result from the diploma thesis of someone who had not pursued an academic career. The thesis had to be obtained from the library of the university that had awarded the diploma degree.

@DaveLRenfro The most likely explanation for that is the most likely explanation for most things: money. Certain funding agencies want to fund "the next big thing" and to be part of getting big breakthroughs out into society. The average person likes to hear about medical breakthroughs that fix current problems, and not so much about how a treatment for something that's been "not a big deal" for a long time has been improved, for example. Who really cares about polio?  Fix zika!

Wouldn't all researchers concentrate their efforts on starting their literature search from the highest impact factor journals, and then develop their new work on this basis?

No.  My literature searches start at DuckDuckGo, Google, Google Scholar and maybe my institution's library search.  I don't even know the impact factors of the venues of the papers I end up reading.
If the papers (or books, or blog posts, or Stack Exchange Q&A) I find are relevant, I will read them, regardless of impact factor.

+1 Let me go a bit beyond "I don't even know the impact factors of the venues of the papers I end up reading." I don't know the impact factors of any journals, and I don't see any reason to learn any impact factors. I have a general idea of which journals are important in my field, and that idea might or might not agree with impact factors. I also have a general idea of which researchers are doing important work that I should read regardless of where (or even whether) it's published. Impact factors are simply irrelevant for me.

@AndreasBlass ... agreed.  I'm in math, I did not know anything about impact factors until I was on a college-wide promotion and tenure committee.  Then we in math had to somehow find the impact factors to add to the papers in the promotion dossiers, since the other departments thought they were relevant.

This question is very open and will probably generate a lot of answers. Here's two important reasons I see:

The impact factor of a journal does not indicate the quality of an individual article. I have seen awesome articles in poorly-known journals. As well as articles with serious flaws in high-impact journals.
Impact factors varies with field: some smaller fields have lower publication rates, thus lower impact factors when compared to other fields In ecology, for example, an impact factor of 2 is fine (at least from my experience). Above 3, you have a very good journal. I'm pretty sure this would be considered low for a medicine journal...

Impact factor being a dimensionless ratio, it is not at all evident that smaller fields should have lower IF journals. For a field that is not cited by other fields, average IF is equal to the average number of one-to-two-years-old cited papers in the field (otherwise it is above that). In small fields researchers might cite slightly less, but since there is only so much one can read and cite, this effect probably only influence very small, closed subfields. The habits of citations are certainly a much greater factor than field size to explain the variations in average IF.

@BenoîtKloeckner well I though this was well documented. But I do not have the time right now to find references for this... will do if I can later

Because if they didn't, nobody would've heard of the Krebs cycle yet, one of the most important discoveries in biochemistry. It was famously rejected from Nature, and instead published in an obscure little Dutch journal called Enzymologia. Luckily, the Nobel Prize committee didn't care about impact factor ;-)

You are kidding me?! +1

Nope: http://www.the-scientist.com/?articles.view/articleNo/28819/title/Nature-rejects-Krebs-s-paper--1937/

In addition to the excellent points made in the prior answers, consider the issue of originality as a requirement for article acceptance.
A professor who selects based on relevance etc. will know if a line of research has already been covered by articles in low impact journals, and avoid duplicating what has already been published. A professor who only reads articles in high impact journals could waste a lot of time duplicating prior research, and getting articles rejected for lack of originality.

I understand that you meant "Why would a researcher read papers from low-impact journals?"
In many research areas, articles are communicated (and read) well before they are published, for example by means of preprint servers such as arXiv. In this case, the reputation of the journal to which a certain article has been submitted/accepted can be used as some simple indicator for the quality of the research.
Since impact factor is essentially an attempt to measure journal reputation, this implies that articles submitted/accepted for low-impact-factor journals tend to be regarded less.
However, IMHO few researchers explicitly use impact factor to select their reading list, rather they judge from several factors, journal reputation being only one (others are the reputation of the authors, as well as the interest generated from reading the title and abstract).
Note also that, in particular for interdisciplinary journals such as Nature and Science, impact factor may not correlate with good quality articles. This is because these journals tend to select not on quality alone, but also on potential impact. Now, unfortunately, a wrong/marginal result can have a huge impact, since if it were true that would have dramatic consequences (IMHO, a substantial fraction of articles in aforementioned journals fall into this category).

What you are proposing here is a circular self-sustaining system where the impact factor of a journal could never increase because no one would cite it. This, coupled with the occasional digging for hidden and/or forgotten gems of research means that there is good reason to use those resources too.
And let us not forget: Impact factor says very little about both validity and value of the contained work. Not directly, anyway.


text:
How do I go about publishing a paper without a university affiliation?
I graduated with a B.S. degree and I have been working in industry for a few years as a software engineer. I am very interested in reinforcement learning, a sub-field of machine learning, and I am interested in performing research and publishing a paper on that topic.
The problem is, in my city there are no professors working in this field (or related fields) who could help me. I contacted other professors in different cities and they rejected my help request for a variety of reasons (such as I am not their student, they don't know me, they are busy, etc.).
Still, I want to perform research and publish a paper. I can't attend school as a full time student and my collaboration requests were not successful. Given all that, how can I publish by myself?

How to choose a research topic?
Should I read all the papers on this field?
How to decide which problem to work on or which is not obsolete? I don't want to work on something which no one is interested in.
Should I read and study all the prerequisite material, or fill in the gaps during research efforts?

I think the first question you'll have to answer is, why do you want to publish? What goal are you hoping to achieve? Once you answer that, we can probably give  you more directed advice.

possible duplicate of Does one need to be affiliated with a university to publish papers?

The title and the question are unrelated, and I think you confuse conducting research and publishing stuff.

Why are they unrelated ? I want to conduct research and publish my results if they are publishbale.

I don't want to achieve anything specific, I want to work on a problem and solve it. After that I want show my results to the world. I like working on a problem  finding interesting solutions. It is an obsession for me.

Perhaps Sylvain is alluding to the fact that not all research—not even all successful research—is publishable.

I think this question is sufficiently different from those cited as duplicate: he is asking about his options for research/collaborations or independent research, very much distinct from "can I publish a paper without affliation".

I agree with @Legendre; the linked questions address the question of "can it be done?", this question asks "how can it be done?".

@Legendre, you say that "this question is [...] very much distinct from "can I publish a paper without affiliation"."  If so, then why is its title "Is it possible to publish a paper without a Professor?"

@JoelReyesNoche : Similar to what eykanal said. This question asks how to go about conducting (potentially publishable) research without being supervised by a professor. While the other question asks whether publications without academic affiliation can be published. I suppose you're right in that the title needs to be (and has been) updated.

@teenageninjaturtle Since you have some responses below that seem to answer your question, please consider marking one of them as ‘Accepted’ by clicking on the tickmark below their vote count. This shows which answer helped you most, and it assigns reputation points to the author of the answer (and to you!).

Is it possible to publish a paper without a Professor?

Sure.  Nobody gives a rat's patootie about the academic ranks of paper authors (at least in my field).  I published sole-author papers as a graduate student.  I have colleagues who published as undergraduates, and others who published with no university (or research lab, or corporate) affiliation at all.

How to choose a research topic?

Choose something you're good at, that you're passionate about, and that other people will care about.  If you're not good at it, you'll never get anywhere.  If you're not passionate about it, you won't put in enough effort to succeed.  If nobody cares, then, well, nobody cares.

Should I read all the papers on this field?

No.  Reading all the papers in any field is simply not possible.  But you should read a lot.  A few hundred papers should get you started (ha ha only serious).

How to decide which problem to work on or which is not obsolete? I don't want to work on something which no one is interested in.

Read lots of papers; talk to lots of people; go to seminars/conferences and listen to talks.  Or decide that the topics that you care about are so fascinating and your results are so compelling that you'll make other people interested (but be prepared for disappointment).  Or—my personal favorite—just make up something cool out of thin air.

Should I read and study all the prerequisite material, or fill in the gaps during research efforts?

Yes.  Both.  (Except not all the prerequisite material; that's impossible.)

I have heard people say that for those remaining in academice after their PhD, professor-less publications are a good thing to have as they indicate you stepped out of your advisor's shadow.

I would like to comment that "ask > read". It's easy to miss an important paper (or idea) when just searching for papers plus it's hard to decide if a problem is of the interest of others (it might be technically correct and novel, but considered as unimporant).

This is very true. I know of an IBM employee who publishes about star formation in astronomy journals; he's not associated with a university.

@Geremia But he still has an affiliation. What about freelancers, or unemployed people?

I can't comment on the later issues—they are too general for the scope of a single question.
To address the first issue, yes, it is possible to publish without a professor. People at corporations and small companies publish all the time without academic collaborators (and without PhD level staffers). The challenge is having a topic that is worth publishing, and finding an appropriate venue to publish it in.

Is it possible to publish a paper without a Professor?

Yes, sure, why not? The point is whether the paper (your work) is worthy enough to be published or not. It's not the point if the paper has a professor or not; it's about being professional and not about a professor.

How to choose a research topic?

First, it depends on your interest. Then it depends on if it's useful, uses new method, new knowledge, etc.

Should I read all the papers on this field?

Not all but only related to your topics. Because you have to "re-search" if others have done it already. You need their results and methods to compare with your work for reference.

How to decide which problem to work on or which is not obsolete? I don't want to work on something which no one is interested in.

I give up for this Q. Actually,it's not hard to answer but not easy too. Because there's no right or wrong answer, only depends on your like. People select scientific papers by their own standard and so do I. No one knows exactly which standard criteria should be decided, but at least you may know the trend of interests, so please "re-search"!

Should I read and study all the prerequisite material, or fill in the gaps during research efforts?

Oops! I have to do it a lot.
PS: This may not the most correct answer because I'm not a professor but at least I hope it helps.

Based on your comment above, that you "want to work on a problem and solve it", I strongly recommend that you change your goal from "publishing in a journal" to simply "solving a problem". By limiting yourself to research that would be publishable in a journal, you place yourself under the following very harsh constraints:

You must become familiar with the existing academic literature such that you can properly cite other academic sources when discussing prior findings.
If you don't take the journal route, you can become familiar with existing techniques through books, tutorials, wikipedia, and blog posts, and work from there.

When publishing to a journal, your work will have a higher likelihood of being published if it relates to the topic du jour. Certain concepts go in and out of style, and researching a less popular topic can have an impact on when you can publish. On a related note, there's a lot of time between submission and actual publication; a number of months to almost a year is common.
Alternatlive, if you go your own route, then you won't have that delay.

You must be willing to work in areas which are of interest to whatever journal in which you wish to publish. This requires knowledge of the different journals and what they typically publish, which may be difficult for you to find without academic contacts.
If you don't take the journal route, you can simply publish your findings in a blog post or other open setting (there may be places specifically intended for this sort of thing, I'm not sure).

You will have to pay non-trivial fees for publication.

I want my contributions to be notable. And the best way of this is publishing in journals or conferences. I don't see a way my work is recognized or respected via a blog post. At the end if I achieve something I want to get proper credit for it. My main target is conferences and their short paper sessions. Mainly I will target ICML and confs. one tier lower than that.

@teenageninjaturtle - Having a publication ≠ notability, or even recognition. The likelihood that your publication will make very little impact at all (along with the vast majority of publications these days) is quite high. I don't mean this personally, I fear this is just the reality.

Good point. One might want to start with posting stuff on arXiv (or a blog) and sending links to people in the field (important: be professional). The feedback (if any) can determine the next step. About (4): that's not generally true (although it unfortunately happens).


text:
How to get a university to make an admission decision more quickly
I received an admit from University A with an acceptance deadline of March 22nd. But my top choice is University B, which—according to their website—won't get back to me until the end of March. I definitely want to join B if possible, but the timing on A means I may not even have heard back from B before A's deadline passes. Is there anything I can do to speed up B's getting back to me?

Universities are aware of this problem. I suggest you either email or call the admissions office at both universities and tell them exactly what you said above, without naming the other university. For the first, ask for an extension for acceptance. For the second, ask whether they can inform you ahead of time about your application. They may or may not be sympathetic to your problem, but at least you'll have tried everything. Do note that if both universities simply say, "sorry to hear that, but we cannot do anything different," you will simply have to make a decision with limited information. Best of luck!


text:
Is it bad style if a section has exactly one subsection?
In a discussion on why subsubsections are evil, egreg comments:

If you have subsubsections, you must have at least two of them in a subsection; you must have at least two subsections and, of course, at least two sections. Draw the tree and you'll understand.

When I'm writing long texts, such as for my thesis, I might have sections that contain only one subsection.  For example:
5.3 Topic X

... bla intro bla ...

5.3.1 Special Case in Topic X

... bla detail bla ...

Is it considered bad style to have 5.3.1, but no 5.3.2?  Should I rather put the bla intro bla in a 5.3.1 Introduction and have the special case in 5.3.2?  What are the general approaches here, what is considered good or bad style, and why?

I think it is a matter of opinion, but my advisor would make me re-write all sections such as the one you mention so that there were more than one, or none. I suggest running it by your advisor or other committee members.

This is probably the wrong forum for this sort of discussion; I'd imagine you'd get more help on English.SE.

@eykanal I don't agree. This has nothing to do with a language. It is the same whether your works is in English or Klingonian. It has a lot to do with academic writing (which differs from other sorts of writings when you discuss the structure of the text)

While I most agree with you tohecz, this does have a lot to do with language. While there are international standards, each language has differenct expectations as to style and structure, hence why style guides are language specific. With that being said, since this is academic in nature I'm ok with it being here.

Academic writing is almost exclusively in English.

A lot of thesis formatting is handed down from a central person/office institutionally, frequently (but not always) associated with your library. This person/office is where your thesis goes after you defend and have your paper work signed and make all your corrections. Ask your adviser AND ask this person/office what is permitted.

@BenNorris The library at my university appears to have no rules except for the paper size and the dust cover.

Having a section with a single subsection is usually considered bad style: most style guides, academic or not, advise against it. In particular, the Chicago Manual of Style advises against it.
Regarding the reasons why this is considered bad practice, I'll quote Wikipedia:

Single Subsections
  Just as your English teacher told you, if section 2 has a subsection 2.1, there'd better be a section 2.2 as well. If you see a section with a single subsection, you have three choices:

If there's a lot of text in the section, followed by the subsection, you ought to be able to carve out a good subsection from the initial material, or even two, to create multiple subsections.
If most of the section's material is in the subsection, you may not need a subsection. Just combine the two.
If the content of at the top of the section is short and substantially different from what's in the subsection, you might be able to promote the subsection (for example, change the heading from level 3 to level 2). On other hand, if the subsection covers something relatively unimportant, then don't promote it to a level 2 (top-level) heading.

Other sources, both style guides and writing advice, say the same thing: 1, 2, …

I might be missing something, but I don't see where your quote answers the question why this is bad practice.

IMHO, it is a bad style in most contexts, and I will try to explain why, on your example:

5.3 Topic X
  blabla
5.3.1 Special Case in Topic X
  bleble

If you write a long work (like a thesis or a chapter of a book), you have to use sub-sectioning, still you should keep a good structure. In your case, I would use

5.3 Topic X
5.3.1 General Approach [or a similar title]
  blabla
5.3.2 Special Case [and not "Special Case in Topic X", that's redundant]
  bleble

One of the reasonable measures whether you have a good structure of your work is the Table of Contents. Just look at it: If it looks good and truly helps in using the text, then the structure is good.

If you write an article and this would likely be the only subsection in it, just make it a section:

5 Topic X
  blabla
6 Special Case in Topic X
  bleble

If it's too short to deserve a section, it's quite likely too short to deserve a subsection, in the case you don't use subsections to keep some general structure of the works.

(Needed to say, I speak as a mathematician and as a typesetter of a tech journal. I've seen solitaire subsections a lot. Unfortunately it is out of my privileges to remove these in the articles I typeset.)


text:
I am a PhD student seeking to collaborate with PhD student/professors from other department. How can I make this happen?
I am a PhD student seeking to collaborate with PhD students and/or professors from other departments, for the first time: I wonder how to start. In particular:

If I already have some specific research questions in mind (which I will use for my dissertation research), is it important to ensure that the research lab is a reasonable match to my specific research goals? For example, if my field is natural language processing and I am specifically interested in doing a research in Transformer language models, should I ensure that the potential research lab for collaboration is also heavily into Transformer research? or can I try contacting any natural language processing labs in general, even if the lab's subarea of research is not a great match to my research goals?

My main supervisor is open to the idea of collaboration. To make the collaboration happen, can I just contact the individual researcher/PhD student whom I am interested in working with? or should I first contact the professor who is leading the lab that the researcher/PhD student belongs to?

Should my main supervisor contact the research group on my behalf, instead of me approaching them?

If I collaborate with a research lab in different department, does this automatically mean that I will formally be a member of that research lab and have the professor who is leading the lab as my co-supervisor?

Is it okay for PhD students to collaborate with research labs from different university (assuming that my main supervisor is okay with this)?

Related: How should a PhD student approach a collaboration?

Don't ask us, ask your supervisor!!

Yes, go for it.  It sounds like a great idea.
Regarding your formal status with the other labs you collaborate with, as a grad student you could be considered more appropriately as an "intern" for them, which is not in the usual sense of the word, in terms of responsibilities, but I've seen the term used a lot in academia for researchers collaborating at other labs.

It sounds like you've already given quite some thought to what the content and direction of this collaboration would be. Good for you! But while I think it's good to have a plan in your head, you really don't need to have all of the specifics thought out entirely.
IMHO, establishing a professional research collaborations is a bit like professional dating. You need to test the waters, see what the other party is like, whether they are open to sharing, whether they have the same attitude towards research as you do, whether they really have the expertise you need, and, as in real life, whether there's that little piece of magic that ensures that you understand each other and like to collaborate with that other person. The last bit can make or break a collaboration.
As for first contact: Ask your supervisor how they prefer to go about it. And ask yourself what you prefer. Sometimes it helps if your PI sends out the first e-mail to the other student's PI. In either case it is super important to have both in the loop (at the start and keep updated throughout) because out of enthusiasm ideas and reagents and tools will be shared and maybe there are rules or regulations or MTAs in place that only the PIs know about.
As to how it develops and what the formal structures will be (co-authorships etc.) it's good to discuss that early on (though not necessarily in the first meeting) - although you cannot set these things in stone because things will change as a project progresses, but at least make sure expectations are clear on both ends.
But first: get talking, test the waters, don't force the other party to commit to something in the first meeting, give them time to think it through and do the same from your end (in your enthusiasm don't promise something you may later regret).
I think it is super important to be open and sharing in research, but it is still business...

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


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Is all research connected via citations?
When looking at the paper-is-cited-by-paper binary relation in an undirected manner: Is all research connected to each other or will there be many connected components?
In other words: Is there a way from a, say, computer science paper to a chemistry paper by walking along the citation graph?
Let's say we are only looking at publications in established, well-known conferences conferences/journals.

It's like playing the Wikipedia game. You go from one article to something really random just by clicking the in-text (anchor) links. If a paper has a citation to one paper that has a lot of citations and so on - by the rules of large numbers you will eventually get to something random.

It is unlikely that all reearch across all fields forms a single tree. All it takes is one paper which does not share the main tree to establish that and I'd be surprised if there wasn't one such. Then again: what practical difference does that make? What's the real problem you're trying to address?

It may not be appropriate to use the term "good" when defining conferences and journals in formal context.

@keshlam: Purely philosophical/interest ;-).

@ÉbeIsaac: That was done on purpose. I think each researcher knows the "good" (established, well-known conferences ) in her/his area. Let's say tier 1 journals/conferences.

The global graph of citations (directed acyclic graph) produced need not to be a connected graph. Although paths do exist from one discipline to another and by philosophy all matter in this world are connected, clusters do form on a general basis.

@keshlam It doesn't form any sort of tree or even forest. At the very least, it's a directed acyclic but I'm sure that, in fact, you'll find plenty of papers that cite each other, especially in the modern era of preprint servers.

There are many papers that cite each other, but that isn't what was asked. All it takes is one instance which does not point to the rest of the universe to answer the posed question, and the odds of that not existing are nil.

Pólya wrote a influential paper on combinatorics with applications to chemistry ("Kombinatorische Anzahlbestimmungen für Gruppen, Graphen und chemische Verbindungen", Acta Mathematica 68:1 (1937), pp 145-254), and that very same paper is routinely cited in works on computer science (combinatorics and analysis of algorithms, in particular, like Flajolet and Sedgewick's "Analytic Combinatorics", Cambridge University Press 2009). Not at all farfetched.

@DavidRicherby There's usually a few papers that annoyingly don't follow the partial ordering (ie. they cite papers in the future), so even directed acyclic isn't a safe bet.

@keshlam You seem to have missed the point I was making. You said, "It is unlikely that all research across all fields forms a single tree." That's not a matter of probability: it's a matter of clear fact because there is nothing even remotely tree-like about the citation graph. The situation where A cites B and C, and B and C both cite D is extremely common. That is not a tree.

@keshlam: The question explicitly says "undirected", which already implies no-one's looking for a tree. As such, all it takes is one instance which neither cites anything else, nor is cited by anything else. While this might exist, it might be difficult to identify it while still establishing it to belong to the considered class of documents in the first place.

Let's say we are only looking at publications in "good" conferences/journals — Oh, no, please, don't ruin a perfectly good question.

@JeffE: I changed the wording to "established, well-known". Do you think that is better? I think this is equally vague, isn't it?

Nope.  A citation, even from an arXiv preprint, an economics working paper, or an otherwise unpublished PhD thesis, is still a citation.

My next research project will be "six degrees of citation" I guess...

@NajibIdrissi: Unless we are not dealing with a tree to start with, but with a (non-tree-shaped) graph. Who said we are looking at a tree? Yet, "undirected tree" - just as well, then "one paper that doesn't share the main tree" can be reached as soon as the branches of its tree touch those of the main tree, as movement is not restricted to one direction.

@JeffE: I think your suggestion of adding anything up to a "unpublished PhD thesis" makes an already hard to answer question entirely unanswerable.? I still do not understand, why restricting the question to some document set "ruins" the question.

@knub Not answering for JeffE, but for me, because restricting certain things for, essentially, convenience, moves this from a question about how citations actually work to a musing on a particular and artificially restricted graph (this is also the root of my issue with your strict definition of clustering). I'd propose that "If I take a citation graph and alter it in some very fundamental ways, what does it look like?" is headed toward off-topic for a question about how Academia actually works.

@Fomite: If we allow everything, is that how "citations" actually work? My general issue with dropping a restriction to peer-reviewed papers or something similar is that the "natural limit" of citations is removed. Only so many papers get cited by other papers because there is a desire (if not a requirement) for brevity, and you have to pick what you cite by relevance. At the same time, the number of papers on a topic is restricted in the first place, as each paper needs to present a novelty. Lastly, the attention dedicated, and thus the number of papers written, is somewhat linked ...

... (maybe even roughly proportional sometimes?) to the degree of interest a research topic attracts. Superficially speaking, none of these restrictions are true for documents like Bachelor theses. There is often no page restriction, so everything that fits somehow can be cited. There is no requirement of containing new content or, especially, new insights. And the number of Bachelor theses is strongly dependent on whether a researcher knowledgeable on the respective topic happens to spend a lot of effort with offering/supervising Bachelor theses. Thus, the distortion might work the other way.

@O.R.Mapper I would assert that it is. I have cited arXiv pre-prints, white papers and unpublished dissertations over my career, where it was necessary to do so. And I think "they can cite a lot of things" is probably one of the weakest reasons to consider excluding grey literature.

@Fomite: In that case, is that really what we want to know? The question "Is all research connected via citations, if we count all mentions and references in any resources?" sounds rather uninteresting to me (we might choose to count Google Scholar, as well as the complete catalogues of all publishers as valid connecting resources, for instance) sounds rather uninteresting to me, compared to "Is all research connected via citations, if we only count a very specific set of citations?" Looking at the text above, the OP has alraeady answered which question they are asking.

@O.R.Mapper And I'd argue that "Is all research connected via citations, if we only count a very specific set of citations?" feels a lot like "I need a network, but I don't like the network I picked, so I'm going to change it until the problem is easier." Frankly, I think how grey literature cites and gets cited (which will vary wildly by field in some cases based on things like the acceptability of arXiv and the prevalence of sandwich theses vs. traditional theses) would be fascinating.

@O.R.Mapper Yes, that is how citations actually work, and moreover how they should work.  My journal papers include citations to arXiv preprints, unpublished technical reports, unpublished PhD theses, Usenet newsgroup posts, blog posts, and StackExchange answers, because those were the correct primary references.  Conversely, preprints,  technical reports, blog posts, and StackExchange posts that I have written have been cited in multiple journal articles because those were the correct primary references.

@JeffE: I think the issue here is that no-one has defined what is meant by "how citations work" in the context of this question. As was stated in another comment, if Stack Exchange posts are included, as soon as someone posts an answer with an example of two absolutely disconnected papers, they will not be disconnected any more by virtue of that very answer. This is certainly one interpretation of how citations work, but it is one by which the question at hand ...

... becomes, in my opinion, quite uninteresting. In my opinion, a much more interesting question is whether the set of papers is still connected if we restrict the considered citation links to a specific subset of all existing citations. And, based on the OP's statements, that seems to be the question the OP intended to ask here. I personally do not find the question of connectedness across any kind of citation very interesting, but others might - yet, it is a different question to this one, and as such, it might be worthwhile to actually ask it as a related, but separate Academia SE question.

When looking at the paper-is-cited-by-paper binary relation in an undirected manner: Is all research connected to each other or will there be clusters?

First, it's possible to have an unconnected paper. Unlikely, but possible, to write something that has no citations and is never cited. This is clearly an edge case, but you did say all.
Second, all research can connect, but there can still be clusters. The two are not mutually exclusive - fields will cluster, presumably, but there will then be some links between fields. My suspicion, from personal experience, is that these papers will be methodological in focus primarily.

In other words: Is there a way from a, say, computer science paper to a chemistry paper by walking along the citation graph?

Third, yes, you could get from a CS paper to a Chemistry paper. I know this because I can trace that tree in my own work, and the work my work cites. The path isn't even all that convoluted or exciting.

I understand cluster in the strict sense, i.e. a cluster consists of everything that is connected. In that case, the two are mutually exclusive.

@knub in the strict sense, that's a clique, not a cluster.

@OrangeDog What knub describes is a connected component. A clique would be a subset of papers that all cite each other directly, ie. one step.

A clique is fully connected. The term would be connected component, which I just edited in the question.

Doh. Well at least we all agree it's not a cluster.

@knub I'd suggest that a connected component is an overly strict definition for actually understanding citation graphs. Lets say there's a field that cites only itself, meeting your definition. Hundreds, nay thousands of papers, all as a connected component. As insular a field as you can get. Then one paper is cited in a literature review of another field as a brief aside. Is that really a meaningful change? For your definition, it is. I'd suggest viewing clustering in the "clustering coefficient" sense, which allows a little more nuance.

@Formite: I think it is okay, if only one paper connects two fields, that's the interesting ones. The "as a brief side" aspect is really hard to judge, compared to just looking at citations.
As the opinion so far is that there is no giant component, I think it is not necessary to increase the requirements now.

@knub, there probably is a giant component. As you can see in my answer, the proportion of disconnected papers is tiny. So the whole graph is not connected, but there is a giant component.

@Peter: Sorry, I was unclear again. I meant one component connecting everything and nothing else.

@knub I think given the consensus is that there is a single connected component, asking about clusters within that component remains far more interesting than just "Giant component: Yes/No". But this is headed toward something that should probably go in chat.

Most likely not (but almost). Apart from the specific papers without references that people have already mentioned, we can look at crawls of large collections of papers. Take, for example, this dataset of all papers in the theoretical high-energy physics section of ArXiv:

Nodes     27770
  Nodes in largest WCC  27400 (0.987)

The largest weakly connected component (WCC) is what you're after: the largest subset of papers that are connected to each other by a path of citations (ignoring direction). While the largest WCC is almost as big as the entire graph, there are papers outside it. Usually, with graph like this, these form little clusters of their own.
For a more cross-domain dataset, consider the citeseer graph, again a small proportion of papers, outside the largest WCC.
Now, of course, these datasets don't contain all of academia, and adding more papers would mean connecting some islands to the WCC, but I'd say adding more papers also adds new little islands. No matter what rule you use to decide which papers count and which don't, I think you always end up with disconnected islands.
Of course, if your question is whether any randomly chosen paper in domain A is likely to be connected with a random paper in domain B, the answer is yes. There will be a large WCC encompassing all domains, and a few tiny islands. I've seen visualizations to this effect, but unfortunately I can't find them at the moment.

Interestingly (by the citeseer stats), for any two papers that are both in the WCC, you have an expected shortest path of 6.35 citations. So while there may be disconnected papers, most of academia is pretty well connected.

Just as a comment, for me the best network graph visualization of the arxiv database is this: http://paperscape.org/. You can clearly see clusters and clusters close to each other resemble very well the connection between research fields. If you look for famous big physicists you will find them connected everywhere.

@Santi The best network graph visualization of the physics subset of the arxiv database, please.

@JeffE it is actually the whole arxiv, which includes also quantitative finance, quantitative biology, math and computer science. Of course, as you can see, they are just very faint clusters in the lower left corner, because physics dominates the landscape.

In short, no. For starters, and perhaps surprisingly to many folks, a large number of papers in the scholarly literature have neither incoming nor outgoing citations. These obviously won't be connected to anything else. Let's throw these out and look only that set of papers that do cite journal articles or do receive citations from journal articles. Even then, not all articles are connection by citation relationships.
Depending on which data set one uses, the fraction of papers in the giant component of a citation graph will vary, but in my experience typically 90-95% of papers will be in this giant component and the rest will be singletons or members of small connected components.

Note that the OP explicitly asks for undirected paths. So even if one paper has no citations at all, it will still be connected to the larger academic world if it is itself cited.

I should have been clearer in my answer. I propose throwing out all articles with no outgoing citations and no incoming citations, and then looking to see if the remainder are all members of single connected component. One will inevitably find that they are not.

@Corvus Can you give an example of a paper that is in not in the giant component and a paper that is in the giant component?

@JiK  hey, that is a trap! As soon as he does it, we have both articles connected here in this page and then both going to the giant component.

What you say makes sense and is what I would expect but it seems to be purely based on conjecture. I would expect no path from a paper on the dietary habits of 13th century farmers to one on Newman modularity but that doesn't mean there won't be one. I don't see how this can be answered without actually building the graph and checking.

@arivero: Indeed - this highlights how it makes little sense to examine this question without establishing what set of documents is considered (e.g. only peer-reviewed publications). Otherwise, we could, for instance, argue that a large number of otherwise disconnected papers are indeed connected ... via appearing in the Google Scholar database, which forms one huge document full of outgoing citations.

@O.R.Mapper: I did establish a set of documents, right? I said papers published to conferences/journal, which inherently includes peer reviews.
I further constrained to "good", established conferences/journals to rule out bogus, very low-quality conferences/journals.

@knub: Maybe you did, but I was responding to a comment that implied counting something like Stack Exchange postings as well.

I don't see how this can be answered short of actually generating the relevant graph and analyzing it. All answers here are simply conjecture. Very reasonable conjecture, based on valid assumptions and reaching conclusions that I find very plausible, but conjecture nonetheless.
I would expect most papers to be connected by a (sometimes very long) path, but not all. However, there is no way of demonstrating this unless we have the graph. I'd be interested to check this, by the way. If anyone has an idea of how to get the relevant nodes and edges, I'd be happy to give it a go.
Until then, I'm afraid this question has to remain unanswered.

I'm sure, each paper is connected to all others. The question is, how long is this citation way from one paper to the other. This is the sort of the 5 handshakes rule thing.
I bet, one can even prove that all academic texts are interconnected through the works of, for example, Sigmund Freud.

This is a bet I would be very happy to take! It would not take long to provide a counter example given any particular bibliometric dataset, given that you can find the connected components of a graph in linear time (Hopcroft, J.; Tarjan, R. (1973). "Algorithm 447: efficient algorithms for graph manipulation". Communications of the ACM 16 (6): 372–378.) and that you will never find everything contained in a single giant component.

@Corvus, then, take it. A cool reference does not mean you are automatically right

You could in principle publish a completely spurious paper that cites one paper in the giant component plus everything you want to pull into it. Therefore any example Corvus gives is liable to be nobbled by someone who wants it to be wrong, and it is impossible to publish a paper that actually cites an example of each kind of paper ;-)

@stevejessop "A reductionist approach to unifying the citation graph", J. Bibliometrics (2017). I can see it now...

@SteveJessop: I hope my question is not that important, that someone tries to publish such a bogus paper to an established conference, and it gets accepted.


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Grants.gov v NIH ASSIST for grant submission
I am writing a training grant--what is the difference between Grants.gov and NIH ASSIST for submission? Is one preferable to another?

There are similar issues with submitting NSF grants through grants.gov rather than NSF's Fastlane system.

Functionally, you can use whichever system you prefer; there is no inherent advantage in submitting via either system, since both are approved methods for submitting proposals.
The decision on which system to use basically boils down to which system you feel is easier, and which one your university's grants and contracts administrators are more comfortable using. (The easier it is for them to use the system, the easier it will be for you to submit your proposals according to the rules and deadlines!)

One practical issue with using grants.gov is that will do its computerized checking of the proposal before sending it on to NIH and then NIH will do a second round of checking.  If NIH finds something wrong with the application, then you'll have to update on grants.gov and resubmit.  This can be slow down the process of submitting your proposal and might cause a huge problem if you miss the deadline.


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How do admissions committees handle a missing “extra” letter of recommendation?
If a student has sent 4 letters, one more than required, and the 4th letter is missing, what will happen?
Will the committee contact the applicant if his application is strong enough?
Will they ignore the letter and decide based on the other 3? Will they delay the review till they have the 4th letter?
I know this varies between schools but how it's usually handled?

If the required number of letters have been received, then most likely the candidate’s application will be reviewed normally, with no penalty attached for not having the fourth letter. If a required letter was missing, then things get a little dicier, depending on whether there are too many applications and if it’s a rolling or fixed admissions cycle.

Will reviewers know one is missing?

If the application lists who's been asked for reviews, then yes.

Well, duh. Is that common?

Most of the applications I've seen are either PDFs or straight "dumps" of what's been entered in an online application, so yes.

If 4 were sent and that is one more than required then the 3 necessary are there.
If 4 are required and only 3 sent then it may not be accepted.


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Conditional Offer?
In US graduate programs, what kind of conditions, usually, universities set, if they accept a student who has yet to finish his degree?
The obvious one is to finish before fall, but aside from this, how common is for them to set minimum GPA requirements?
For example, if a student has 3.6 GPA and is admitted, what kind of GPA should he maintain? Will a 3.55 be OK? How common is for programs to withdraw their offer on GPA basis?
I understand that this varies a lot, but please give me an idea of how it works in competitive programs.

I’ve never seen specific grade or GPA targets mentioned as conditions for admission after acceptance.
I believe that the usual (informal) requirement is that your performance remain consistent with your previous performance. If your grade point average changes a little, no one is going to complain. However, if you contract a severe case of senioritis and barely pass your final-semester classes, that will definitely raise some alarms, regardless of how hig( your GPA was beforehand.


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How should I cite a specific section of the LabVIEW online documentation?
How can I cite a specific page of the LabVIEW online documentation?
I need to cite these two pages: from the tutorial and types of graphs and charts.
Would I be better off citing the online help documentation?

Not an answer, but I would suggest that there's nothing on those two pages that really warrants citation unless you're doing something that is really novel and unusual for your field. Most fields of engineering and science can safely assume that National Instruments plotting and computing software is a standard software package (like MATLAB or Mathematica) that might deserve mention but not citation.

Also consider that there are dozens and dozens of softwares that allow you to do plotting and that allow you to build and run state machines, so if this work is really so novel in your field that you feel like citation is deserved then you might want to spend a day looking up the different tools you might mention as well.

You can cite them as a webpage. This answer gives some info on that for a specific citation style: https://academia.stackexchange.com/questions/67209/acs-style-image-citation/104049#104049

It's generally best to provide the location of the cited material in such a way that, should a reader need to find it, they can do so without searching extensively. The pages you are citing are in two different locations (the first is a tutorial on the site and the second is essentially a section from the 2012 version of a manual) on the LabVIEW site so it likely makes the most sense to cite them separately from each other. There's always the potential issue of resources changing location and links breaking, so include other identifying details where possible, like page names and edition dates.