Why was I offered an associate professorship after applying for an assistant professorship position? How will this be perceived? I have applied for an assistant professorship at a top-tier Chinese university. After interviewing with them, they are now offering me a position: an associate professorship!
I find this very surprising. It’s not that I don’t think I deserve it: I have been a postdoc for seven years, and my publication record is significantly better than that of the average Chinese associate professor in my field. But I have never heard of anyone completely skipping the assistant professor level.
I have two questions:
(1) What do you make of this?
(2) How will this unusual feature of my future CV be perceived by universities in the west, if I later try to get back?

UK perspective

(1) What do you make of this?

They think you are good enough to be recruited directly to the higher-ranking grade. It sounds reasonable in light of your seven years' postdoc experience plus having publications commensurate with the grade. They obviously think you are an outstanding candidate, and may be offering you the higher-ranking grade to make the prospect of international relocation as enticing as possible. Congratulations!

(2) How will this unusual feature of my future CV be perceived by universities in the west, if I later try to get back?

To be honest, I can never remember the difference between "associate professor" and "assistant professor" -- most UK universities do not use these terms and the whole concept of "tenure track" does not really exist in the UK (although some UK universities have very long probation periods for more junior staff dressed up as fancy schemes -- here is an example that involves up to 8 years' probation). A UK academic reading your CV would, once he/she has familiarised itself with the relative seniority of the grades, be impressed that you skipped straight to the more senior grade. In the UK, an academic who reaches the equivalent of "associate professor" level (probably "senior lecturer") within seven years of getting a PhD will have done very well, but it is not extraordinarily unusual. Definitely, it would work to your advantage.

Since other users have already answered on the basis that this offer is made in good faith, I'll address the elephant in the room. This is China, they have a history of intellectual property theft, buttering up to univeristy professors and other academics to gain access to their work or simply a foot hold in academic institutions.
There is a real possibility, however small, that this promotion is simply a way of increasing their soft power.


When and why did journal article titles become descriptive, rather than creatively allusive? In 1926, the article titled “On a certain minimal problem” was published. Nobody could guess what it was about, from the title alone.

Nowadays, one may expect something more descriptive, such as "Workspace Augmentation of Photon Impingement Through Impurities Removal".

I'd be interested when and why did the titles change, from the allusive style of the early 20th century, to the descriptive titles of today.

Was it a gradual change? Was it prompted by some notable event or influence? Was there a period when journal articles (or "letters" as it was then) did not have titles?

There's an interesting discussion of this in the introduction to Titles are "serious stuff": a historical study of academic titles by Salager-Meyer and Alcaraz Ariza (link). One point they argue is that titles (as well as abstracts) increasingly need to be more informative given the growing production of papers, in order for readers to make quick decisions on whether to read them or not. If this is the main factor, the information content would be expected to increase similarly to the size of the relevant academic community.
However, there's something I find much more interesting hidden in the introduction:

Other scholars have stressed that titles should be as informative as possible in order to facilitate the process of storing, searching and retrieving the information (Black 1962; Mitchell 1968; Tocatlian 1970; Feinberg 1973; Manten and Greenhalgh
1977; Hodges 1983; Diodato and Pearson 1985).

The paper by J. D. Black (IBM British Laboratories) is titled The Keyword: Its Use in Abstracting, Indexing and Retrieving Information and discusses how

Librarians have been accustomed to using systems, schedules, thesauri, lists of headings, etc., to define and classify the literature which comes into their keeping. They use these same methods to retrieve and disseminate this literature. However, within recent years these methods have begun to show signs of strain, and in some cases breakdown, due to the tremendous increase in the volume and complexity of technical literature.

Specifically, Black showed that a 1960s era (punch card) computer can be used to extract keywords from a title to achieve a similar efficiency as manual classification, but for significantly cheaper cost, and allowing better scalability. Black also writes

While the index may be practical and usable, we still do not know precisely how efficient it is. In its present form, the efficiency is dependent on the author's choice of title. <...> before long the engineer, scientist, or mathematician will realize that if his title is not descriptive enough his paper will not be used as much as it might be.

Of course, if this automation of title processing is the main factor, one would expect to see a significant increase in the information content of titles starting some point in the late 50s, or early 60s. A 1970 paper by Jacques J. Tocatlian called Are titles for chemical papers becoming more informative? looked at precisely this, by comparing measures of information content between papers published in 1948, 1958, and 1968. (1958 being the year the KWIC index, or Key Word in Context, was introduced.) As Fig. 1 below shows, they found no significant difference between 1948 and 1958, but very different results for 1968. Here the measure A, for example, is defined as the total number of substantive or informative words. On the other hand, Fig. 2 shows that titles with few substantive words might have started being eliminated before the introduction of the KWIC index.

I don't know if there is similar evidence from other fields that the introduction of automated indexing was an important development, but it strikes me as likely that the same mechanisms would apply elsewhere too. So, long story short, a growing number of publications and the introduction of computers may have driven a large part of the push towards more descriptive and informative titles.

I see this as the result of online presence of people as we are more dependent on internet for any prior peice of informtion. So people search for results and google work starts here google bots pick most relevant and trusted content and produce as result for the users. Here comes bunch or results now users pick the most descriptive easy and picky titled post.
So there is a hunch in market to get more and more traffic resulting more descriptive or say over optimised titles


Uncommon order of authors names? In my field (theoretic CS) it is very common to list the authors names alphabetically on papers.

I have been working on a paper for quite a long time with three other researchers, which is almost complete, and in the last week or so we consulted another researcher who made a non-negligible contribution to the paper by pointing out (with a proof he thought of after considering the problem with us for a couple of days) some direction we were working on shouldn't work and suggesting considering a different direction - the final version of the paper will not include his ideas but we probably wouldn't finish it on time without realizing we are following a dead-end.

So, he deserves being listed as an author if he wishes, but the problem is that if we list the names alphabetically his name will be first - is it acceptable to put our three names (alphabetically ordered) before his, breaking the common alphabetical order? If not, what is the usual practice in such cases?

Thanks.

In fields (like pure math and TCS) in which the convention is to list authors in alphabetical order, it makes a very jarring, striking statement to put authors non-alphabetically.  The most common instance of this in my experience is when one author is very senior, enough to perform a power play on their very junior coauthor.  Unless the reasons for the non-alphabetical order are carefully explained and seem logical to the readers, this could make a widely negative impression.

Non-alphabetical ordering is almost never used in pure math and TCS to signal importance of contribution: the convention, for better and for worse, is that the authorial contributions are not disclosed to the reader.  As a result of this, unlike many other academic fields in which being a fifth author may be understood to mean very little contribution, in pure math and TCS there is a cutoff phenomenon: you have to decide what level of contribution merits coauthorship, and there will certainly be many cases in which a positive contribution does not result in an authorship.  People who are not coauthors but made intellectual contributions to the work should be acknowledged for this.  If you read acknowledgments on papers in this area, you will find that people are sometimes acknowledged for things that are clearly significant contributions: e.g. for providing the key idea of the project, or for providing correct proofs of key technical results needed by the authors.

The general conventions are to be generous and modest.  Namely, the coauthors should err on the side of generously offering coauthorship to those whose contributions were positive, even if they were lesser in magnitude than the other coauthors.  On the other hand, one should be modest in responding to coauthorship requests: if what you did feels like helping out a colleague rather than doing substantial, original work, then probably you do not want to be listed as a coauthor.

Of course in practice there is a lot of subjectivity here.  In the case at hand, another answerer says that because your colleague's contributions "did not actually make it into your paper", then they are not sufficient for coauthorship.  I don't completely agree.  Telling people what not to do and setting them back on the right track can be an invaluable contribution.

Recently a junior colleague found a key mistake in a draft of a work of mine in which she was not an author.  The coauthor and I withdrew the paper immediately and were able to fairly quickly recover the main result of the paper by arguing in a different way.  The paper was then accepted.  I think it is quite likely that if not for my colleague's contribution, the original, erroneous version of the paper would have been published.  In principle we would have fixed it eventually, but in practice: yikes -- she deflected a bullet.  I offered my colleague coauthorship...and she declined.  In this case the offer was essentially mandatory, whereas both accepting and declining it seem reasonable.

If the OP feels that the contribution to the work was sufficient to make it plausible for the contributor to be listed as an author, I would recommend that the coauthorship offer be extended.  If you know your colleague pretty well, I might follow the offer with an offer to discuss the situation: that's a good way
to make sure that you reach an outcome which you are both comfortable with.  I don't think your colleague's last name has any role to play in this discussion.

Added: Here is the American Mathematical Society's 2004 "culture statement" on coauthorship.  It says that more than 75% of coauthored math papers with at least one American author use alphabetical order, and that this percentage is over 90% in pure mathematics.  I think that for publications in more mainstream and prestigious journals, the percentage is even higher.  For instance, I checked the last 100 multiply authored papers in the Journal of the American Mathematical Society and found that alphabetical order was preserved 99 out of 100 times.

The cultural statement also says: "Joint work in mathematics almost always involves a small number of researchers contributing equally to a research project." Unfortunately I do not completely agree with this statement.  For one thing, the number of coauthors on papers has been rising so sharply that even a statement from 2004 seems a little out of date: I remember that 10 years ago, seeing a math paper with more than three or four authors was worth a raised eyebrow.  That is really not true anymore: a substantial minority of papers has a long enough list of authors -- with such widely varying expertise -- that it is not plausible that all are contributing equally.  Moreover, unlike alphabetical order, I don't know how one can gather statistics about whether authors contribute equally.  To me this statement reads like an aspiration rather than a description of reality.  In my experience, there is a cultural push for authors to contribute equally, but there are other cultural pushes as well.  Listing authors alphabetically essentially always in confluence with the reality that sometimes the contributions are not equal seems to me to an underacknowledged problem of our profession.

Some disciplines usually use alphabetical order, but this is by no means mandatory. In fact, I would say that one of the rules of writing papers with others is that you should have a conversation between all co-authors to discuss precisely this point: who should be a author, why, and in which order. In some disciplines, such as pure math, this most often leads to alphabetical order, which is used to indicate that everyone contributed to the same degree (or, at least, nobody feels strongly enough to push for having their name listed first). But other disciplines do it differently, including for example applied mathematics where many papers are written to indicate one of two things:

The first author really did more work than the others.
The first author is junior and needs a first-author paper more than others. (For example, almost all of my more recent papers have my students and/or postdocs listed before me -- because I have tenure and don't need these papers more than I do -- even though oftentimes I would have a fairly good argument for being the first author, having done a very substantial amount of work.)

So, in your case, I would suggest talking this trough with your co-authors: who did how much, who are the possible authors, what order should they be listed in, and then come to a joint conclusion that does everyone justice. I certainly don't see a stigma in figuring this out, rather than just going with the default alphabetical order.


Are good writers are good theoreticans? I am Ph.D student works in theoretical computer science (algebra). I will be graduating next year. I have been able to publish 2 paper currently writing a paper. Idea's are comming into my mind these days, and also I start writing as soon as possible. I try to write the things as early as possible. The problem from which I am suffering most is "writing skill", as the feedback I have from my collegue I have good idea's but writing is not that much good even after two months of writing ( I have written many drafts). Note that in those two months in which I were writing the draft of the paper, I was also working on some other problems.

I know that my writing is not great, but I have heard that good writers are good theoreticians. I may have very good idea but I may not be that much good writer and due to this thing I may not be much successful, Please help

Question : Are good writers are good theoreticians?

Since you started studying computer science, has anyone spent significant time teaching you how to write? Of your whole time learning, what proportion was spent learning computer science, and what proportion spent learning writing skills?

If your answers to these questions are what I expect them to be, then you need to put time into learning to write. It is a skill, not a gift. It can be taught, and it can be learnt. (I should know. I spent five years studying pure mathematics at undergraduate and postgraduate level without ever writing more than about three consecutive words. When I first attempted to enter my chosen profession, which required a written examination, I failed.) I subsequently put a lot of effort into learning how to write. People in my profession, which is very much based on use of words, tell me that my writing is very good.

For me, the career enhancing book was Barbara Minto's "The Pyramid Principle" that makes the case that clarity of thought leads to clarity of thinking. The logical approach she takes appealed to me as a mathematician, and maybe that might appeal to you as a computer scientist. But there are lots of books.

I suggest it is not helpful to comfort yourself with such thoughts as 'good theoreticians are never good writers, and vice versa'. If you are bright enough to be good at computer science then you are bright enough to learn how to be a competent writer.

Not necessarily.

Case in point: JK Rowling is a world-renowned writer, but I don't know anyone who has called her a good theoretician.


Convention regarding inclusion of both an abstract and introduction in a mathematical paper Good afternoon,

I am a high school junior in the process of preparing a real analysis paper for submission to a mathematics journal. I have written my proof and conducted an exhaustive literature review and now I would like to take the next step towards finishing my paper but I am unclear as to the convention with regards to including in my paper both an abstract and introduction or just an introduction.

I have read published papers such as this one by Erdos which include both an abstract and introduction but I have read many others such as this short proof of the prime number theorem which includes just an introduction. Then there are some like this one that have what appears to be an abstract without an explicit heading.

I have also read guides regarding how to write mathematical papers. There is this one which includes an introduction but no abstract. Then there are other guides like this one which make mention of both an abstract and an introduction.

My question is, is there a convention regarding the inclusion of an abstract in a math paper? If so, what is it? I understand that scientific papers traditionally employ both but I do not see a trend when it comes to math papers.

Thank you in advance.

The purpose of an abstract and an introduction are very different, so it may be useful to include either or both. An abstract is a summary of the whole paper, focusing on the main result. It might exist separately from the paper itself as, say, an online "teaser" to get people to read the paper. But an introduction is intended to give background on the problem to be addressed in the paper and to situate it within the literature. You would almost always include an introduction. You might also write the abstract, but not actually include it within the paper itself.

The purpose of an abstract is to summarize the entire paper.  It should have all the major findings, actual numbers (if applicable), etc.  An introduction gives the history of the problem, including earlier attempts or related problems as well as the motivation for the research.  They are different animals.

Perhaps you are confused because introductory paragraphs on high school essays often have an outline summary of what the essay will be.  But that's really not the main objective of a journal article introduction section.  (It could have that sort of outline explanation but probably more commonly doesn't.)

Also, you should just look at what journal you want to go to (pick something decent but not too high ranking).  Then just ape their format.

All that said, I am skeptical of a high school junior contributing an analysis paper.  Anything is possible of course.  But I suspect you don't know what you don't know about the topic, previous literature, etc.  For one thing, your question here shows some naivete about the structure of journal articles, so perhaps you haven't done a good lit search in your area.  But...don't let me hold you back.  Nothing like learning by experience (as I told my friend before he opened a restaurant),


Is it normal/ethical for student grades to be assigned according to quotas? In my undergraduate Physics courses, I have heard from my Professor last semester that he got in trouble from the physics department for passing too many students.

This semester, the TA in the lab portion of my class (who grades our lab reports) came flapping around a memo he got, also from the Physics department, stating that the average grade needed to be 75% and he will now be grading accordingly, after a few weeks of normal grading.

I typically spend up to 4-5 hours on these reports, typing up formulas and doing analysis, calculations, etc. I have gotten a 100 on every lab report in my first semester and up to that point in the second. Now, after the ultimatum, I'm losing points for things I didn't before, and being asked for additional analysis that has never been required. I already spend as much time as I can, and this harsh grading feels out of nowhere and undeserved.

Questions:

Is this normal that teachers have quotas?
Should it affect students who actually put in the work?
Does this seem like an ethical issue of arbitrary grading that I should bring up to the department or my professor?

Unfortunately, the universities and colleges are run by managers and not only by academics. In ideal world, all students' work should be marked according to its merit; for example, if all mathematical problems are solved correctly, then the paper deserves 100%. Academics usually understand and share this view (apart of a few strongly believing that "no work ever deserves 100%").

Unfortunately, people who manage universities, are not always guided by common sense or mathematical reasoning. They seem to invent some obscure metrics and force them on the rest of academic staff. Academics do not think it is correct, but they have to play by the rules which are set by non-academics.

Unfortunately, students become a collateral damage in a clash of two cultures: academic and management. If you want to query this, best ask not your professor, but a Dean (anonymously or as a part of larger group). The misguided policies arrive from the very top; your professor has not much power against it.

Let me take the possible situation you're in to an extreme. Imagine your TA had a marking rubric that consisted of "5 marks out of 10 for putting your name and assignment number on page 1, and 1 mark for each page submitted." 5 pages, good format: 10/10. Not only would you get 100% on every lab, so would the rest of the class, except for a few who only submitted 4 page reports. The department would not feel that your TA and prof were doing a good job preparing you for future courses or for work, or evaluating your competence, if that was the actual marking rubric. Furthermore, it's pretty easy to argue that this imaginary rubric is unethical.

So in a department where someone is doing that, it's not unethical to tell them "you have enough students in your class that your distributions should match such-and-such a pattern, and your average should be X." While it's possible that much higher or lower averages in a class are caused by happening to get a much smarter class, or the prof being an amazing instructor, it's far more likely to be caused by easy marking. Easy marking feels fun while it's happening. Everyone likes getting 100%. Even when you make mistakes (leave things out or do things wrong, you're not clear) you like getting 100% anyway. Where it's not so much fun is next year, when you get a hard marker. Or when you realize you don't actually know how to do certain things that everyone assumes you learned how to do in this course.

Having quotas is a way that departments try to rein in both easy markers (who you like, but are actually treating you unethically because they are not teaching you everything you need to learn) and hard markers (who crush your spirit with their nitpicking and unfair expectation.) It is not normal for everyone who "puts in the work" to get 100% on everything. And marks are not assigned as a way to be fair and recognize the time you put in.


How to proceed when the baseline (state-of-the-art) published results claim much better performance than I can reproduce? I am graduate student, to finish my degree I need to build methods outperform what is already there. An issue that I came across with, is that two papers reported way (I mean more than 20%) more than what resulted from my reimplementation. This could be due to two reasons:

I missed something during the implementation. Which is what I have been telling myself. For months, I tried all possible combinations and possible paths. One of the methods is straightforward. Still, I could not reach their claimed performance.

I contacted the corresponding authors, and no one replied. So I tried to contact the other authors.

The first paper, the author replied and sent me the code. He/she told me to keep all details ”confidential”. Well, it turns out they they are not using the data they claim in their the paper, of course their results are different than my reimplementation. And my implementation was correct.

The second paper author also replied and they didn’t send me the code because they say it is easy to implement, but confirmed that what I did is correct still I couldn’t understand why such difference.

Both papers are published in <2 impact factor journals. Their web servers are not working.
They are not honest.

Now I am stuck, my method does outperform my reimplementation of their methods but not what they claim. The first paper I can’t say anything because “it is confidential” the second paper I can only confirm that I correctly implemented their method for the most part  (based on my chat with the authors)

I know that I probably could not publish on this part of my work, because who is going to believe a young scientist who just started her way?
 But not sure how the committee are going to believe me. What can I say or do? Please help me

There is absolutely no reason that you can't publish a paper that says "We compared our method to methods X and Y. Since code the original code was not available for X and Y, we reimplemented the methods to the best of our ability. The code for these reimplementations is available in supplementary files A and B. Our new method out performed the reimplementations of X and Y by z%. However, it should be noted that it was not possible to reproduce the reported results for X and Y. "

People who want to know will have to look at your re-implementations and decide themselves if they think you have correctly re-implemented.

Seniority has nothing to do with it - be transparent, and the world will judge if they believe you or the people that won't release their code.

In addition to the other answers, you should consider publishing your re-implementation. Then any reviewers can check if they think your results are plausible or if they spot a flaw in your re-implementation.

In the first case, it is right to say "We implemented paper X, but could not reproduce the claimed efficiency" and in the second case the flaw found by the reviewer may help you to improve your re-implementation, so you achieve a similar result.

Most reviewers will not debug your code, but you did your best efford to allow anyone to verify your claims of less efficiency and at least your paper is as honest as possible.

If the algorithm is interesting, publishing an open source version may get some users, that point out issues with your code (or contribute improvements) as well. But make sure not to be too close to the confidential code, as the original authors may claim copyright infringement.

You may use clean room reverse engineering with another person or at least do it yourself by just using the given code to write down the parts missing in the paper and then reimplement it from the documentation and not from the code.


Splitting a relatively long paper into two shorter papers I have recently submitted a 40 pages paper to a journal, say (A). After about 6 months, the editor let me know that several reviewers have declined to review my paper, and so he decided to reject the paper. He suggested that I submit my paper to a more specialized journal. Journal (A) is already a specialized journal and I only know 1 journal more specialized than (A), let's call it journal (B). So, one of my options is to submit my paper to journal (B) and accept the risk of a similar feedback from the editors of journal (B), of course after several months.

In the mean while, I think the main reason several reviewers declined to review my paper is that (1) my paper is relatively long, (2) My paper consists of two parts and each part addresses a different subject. Therefore, the set of reviewers who have expertise in both subjects and are willing to read and review my paper is very small. Due to these facts, it is very likely the editors of journal (B) face the same problem. So, as the second option, I am thinking of splitting my paper into two shorter papers each consisting only one subject of my original paper. Regarding this option, I can think of the following pros and cons:

Pros:

(i) There are a good number of experts in each subject and it is fairly easy to find a reviewer for each one of my shorter papers.

(ii) This facilitates the referee process of each paper and hopefully reduces its time period .

(iii) Two papers (each approximately 20 pages) look better than one paper (approximately 40 pages) in my CV.

Cons:

(a) The second part of my paper depends on the notations and results of the first part. So the reviewer of the second part may prefer to read and review the whole paper at once, or even worse he/she may call the paper containing the second part incomplete.

(b) Part of the motivation of the developments in the first part of my paper comes from my work in the second part. By separating these two parts, the reviewer of the first part can complain about the lack of enough motivations and justifications for my results. In my opinion, it is not a serious problem because I will explain the application of my works which is going to appear in the second paper. But I am not the person who makes the final decision and the reviewer may blame this and reject the paper.

(c) I can imagine that it would be a difficult path to follow the referee processes of two related papers simultaneously, because of the following reasons: It is possible that the opinions of reviewers of the shorter papers differ significantly. Or it is possible that these papers get refereed in two very different time periods. It is also possible that one of the papers gets accepted and the other one doesn't, which is a pretty ugly situation.

Unfortunately, I have faced each of the above difficulties ((a), (b) and (c)) in my previous submissions and I know how they can ruin my papers. In fact, the main reason that I organized my results collectively in one paper was to avoid the above issues. But now that my paper has been rejected without any peer review, I am considering the option of splitting my results into two papers. So, I have the following questions to ask from people who have more experience and have been involved with similar situations (for instance as an editor or a referee):

(1) What do you think about the above pros and cons? Do you know any other pros and/or cons? And, is it a good idea to split my paper into two shorter papers?

(2) If it is advisable to split my paper into two papers, should I submit them to the same journal, (maybe same editor), or should I submit them to different journals according to the best editors who can handle my papers?

Well, in my opinion, the following fragment of your question outweighs everything else:

  (2) My paper consists of two parts and each part addresses a different subject. Therefore, the set of reviewers who have expertise in both subjects and are willing to read and review my paper is very small.

I appreciate that you are able to imagine the problem that will be faced by the journal editors. So, splitting into two is certainly not a bad idea in this case.

I can mention some instances where this has been done in the past. In each of these cases, the problem wasn't as acute as yours (i.e. both could actually be reviewed by the same expert), but perhaps the authors chose to do this because of length considerations (or some other reason that I can't imagine). Also, in these cases, it wasn't a case of two different journals A and B - it was two sequential papers in the same journal. So, that creates an additional option for you, if you find it appropriate. (The context here is Physics, but I'm sure this can be generalized to Maths, if I'm right!)

Example 1: R. P. Feynman was a charismatic Nobel Laureate (Nobel, 1965), as you probably know. Here are his two significant contributions to QED, appearing back to back in Physical Review:

Paper1, Paper2 (both are free pdfs officially, given their landmark status.)

In particular, he began Paper 1 by writing:

  This is the first of a set of papers dealing with the solution of problems in quantum electrodynamics.

and started Paper 2 with the sentence:

  This paper should be considered as a direct continuation of the preceding one ...

He had developed the formalism in the former and applied it to the problem in the latter. That makes a candidate for splitting into two.

Example 2 Here are two papers by Sidney Coleman which form the backbone of phenomenological effective Lagrangian method in low-energy Nuclear Physics. (These aren't free and I'm not sure you will be able to get past the paywall here!)

Paper 1, paper 2.

Notice again, that they are consecutive papers in the same journal. The second paper also has an extra author, and that could be one reason for splitting into two. But once again, from the point of view of content, the general method was devised in paper 1 and applied to some context in paper 2. But here, the authors spent a section of paper 2 in explaining what they developed in Paper 1.

Thus, long story cut short - it should be possible to go ahead and split into two parts. If they are consecutive, you can carry over everything directly, if not, spend a few sentences explaining your notation etc.

PS - Congratulations for doing this sort of work which could put the editors into this type of a fix. That smells like a significant contribution to Maths, having applications elsewhere (other branches?), which is probably why you insist that it would be rare to find a referee who can ably judge both!

Allow me to quote from the code of practice of a journal in my field, which (IMO) should apply everywhere:

  Fragmentation of research papers should be avoided. Authors who fragment their work into a series of papers must be able to justify doing so on the grounds that it enhances scientific communication.

The practice of splitting papers up into "publons" (or minimum publishable unit) is a scourge. Get rid of the "two papers looks better than one" adage in your mind. It's not necessarily true, and can be detrimental to the science.

As it stands, you present no valid reason as to why splitting the papers up will improve how your work is communicated. Therefore, you shouldn't do so.


Undergraduate Publishing Options I am an undergraduate student currently working in a co-op position at a company in my field. I was lucky enough to have the opportunity to be the lead author on a paper based on the research I performed here, and I have a couple of questions regarding what I can do with this information.

I would like to publish it while also making it as visible as possible (partly because I consider myself a proponent of open sharing of information, but also because I'd like to refer future potential employers to it and it would be easier if it were not behind a paywall). I understand that some journals have open access options, but these tend to be quite expensive. What options do I have for publishing in an open way without expensive costs (ideally no cost, since my company has made it clear that they will not financially support publication)?

I understand that one solution to this could be putting it on ArXiv. However, since ArXiv is not a journal, would it be considered incorrect or misleading to call my paper a publication if I were to post it there?

My last question is with regards to contact information in papers. Since I will be leaving the company in a few months, I would like to be able to put an email address in the contact information for the paper that will still be active for a long time. Is it frowned upon or does it look bad if I use my personal Gmail account for contact information?

Thank you for all your help!

What options do I have for publishing in an open way without expensive costs?

This is highly field-dependent, but there may possibly exist journals out there which will publish open-access for free. In my field it's common for papers to be embargoed for 6 months or a year, and then made open access, but again this varies from journal to journal and from field to field.

  However, since ArXiv is not a journal, would it be considered incorrect or misleading to call my paper a publication if I were to post it there?

Yes. The correct term for a paper that has been posted on the arXiv is "pre-print". This is not the same thing as a publication. To call your paper a publication it needs to have been published in a (reputable) journal i.e. to have gone through the peer review process.

  Is it frowned upon or does it look bad if I use my personal Gmail account for contact information?

This would be pretty unusual, and as a reader I would think twice about the legitimacy of the work if a personal email address was attached-- in fact (I may be wrong on this) but I believe you need an academic email address e.g. name@place.edu or name@place.ac.uk to submit to arXiv in the first place.

My advice: talk to your line manager at the company and make a case for publishing the work. It seems strange to me that they have had you write this paper but won't support publishing it.

I think it's also a good idea to talk to a member of academic staff in your university department if you can-- all the better if their area of expertise is related to your paper. Ask their advice about publication in your field. It may even be worth asking if they have time to read over the manuscript draft and provide some feedback.

In many cases when you publish a paper in a journal, you may still freely use and publish your preprinted version of the paper under some conditions. You should read this.

You should also know that arXiv is not your only option. You can also use ResearchGate which is very popular nowadays.


Is there research on the extent to which complexity of the proposed method(s) impacts the acceptance rate? I heard this speaker at IJCAI complained that his paper got rejected because the methods he used were too simple despite the results being highly competitive (twice the state of the art, at least according to one metric). The complain can be listened in this video at 29'30''. Excerpt:

  (Addressed to reviewers) Accept simple papers if they demonstrated what they were trying to
  show.

It wasn't the first time I heard such a complain, as simplifying existing solutions is arguably a contribution, yet sometime despised.

Is there any research/study/survey that looked at the impact of the complexity of the method(s) proposed in a submitted paper on its acceptance rate?

I am mostly interested in the field of computer science > machine learning / NLP / data mining, and English-speaking venues.

I haven't seen any research on the correlation between the complexity of the methods and the acceptance odds of a work and I think it is relatively hard to do a study on this. First because being simple or complex is completely subjective and domain dependent and hard to quantify. One can not generalize a pattern that is seen in a particular scientific community to others. Moreover, the information about rejection of papers is not publicly or easily accessible making the hypothesis hard to investigate.

That being said, in computer science machine learning community, I have seen that people are pushing towards critiquing the unnecessary complexity of the suggested methods and putting more emphasis on the actual results rather than the simplicity or complexity of the methods. There are many simple methods that are being published because they actually work well. I personally don't think that simple ideas which show good results are necessarily prone to rejection, but the opposite argument (complicated methods having higher chance of acceptance) is sometimes true.

On a related note, explanation of the ideas and presenting a work in the most simple way for people to understand, is being emphasized more and more. One reason of people trying to complicate things is that they think the less it is easy for reviewers to understand their work, the higher their chance of acceptance. I personally think that ideas in the papers should be explained simply and clearly because if it can’t be explained simply, probably it can be done better. And reviewers should not praise the work they don't understand, because it is the duty of the writer to explain everything simply enough so that the corresponding community understands it well.

This is relevant to the Kuhn - Popper debate about the way science works, and there is a considerable literature here... I don't know about statistics, but I do know this is extremely common! A new simpler approach will usually be dismissed out of hand with scant regard by the powers that be with their strong ties to the traditional model.

Kuhn notes that researchers get locked into Paradigms.  Those in positions of power (referees and editors, professors and deans) prefer papers that continue their work, use the tools they invented or are familiar with, cite their journals or journals indexed by their favourite citation company. There is also a factor of workload in relation to interest: They skim things quickly and pay particular attention to headings, tables, figures, equations and references - looking for things that connect to them/their interests/their journal. Some reviewers show no evidence of having actually read the paper, particularly for so-called 'top journals'. If they are not interested, or they have decided it a 'poor approach' a priori, then it doesn't matter how good the approach is or the results are, and you will be flipped off with comments about the style, format, equations or references (e.g. a complaint of lack of references to X or insufficient or unnumbered equations, or lack of road map glue telling them there is are Introduction, Methods, Results and Conclusion sections). That is there are not only paradigms within fields, in relation to how you tackle a problem, or the theoretical framework or model you work in, there are paradigms in relation to modes of presentation.

Popper on the other hand espouses Parsimony and Refutation. The simpler theory or model is better, other things being equal.  A poor theory grows more complex as it keeps being adjusted or extended to deal with new cases that cause it difficulties.  Usually the poor theories and models don't die off until their proponents and perpetrators do, until they get so complex as to be completely unmanageable and they eventually topple over and fall into oblivion. Conversely, a simple model will be ignored until it is demonstrated that it handles everything that the older theories tried to do, and makes new advances and predictions that are borne out. Popper's ideal researcher is totally different from Kuhn's dogmatic paradigmatic researcher. A good researcher is making predictions into the unknown where the different theories predict different outcomes.  A good researcher is not trying to bolster their models, but rather to refute them - find the holes rather than plug the holes.

So how do you deal with this? A very good question - glad you asked...

You have to face it head on. Choose publication venues that are high quality but have the kind of format and expectations that allow you to present your new simpler ideas and models, even though it may not be fully worked out and compared against all your thousands of competitors and their thousands of datasets or examples. Get feedback, and find who is sympathetic, where they publish/review/edit etc. Eventually, you need to target the archival traditional journals, the bastion of the current paradigm, and fit things into their mould, follow their rules, explain the equations/models you are competing against in detail, especially those that are pushed by the journal and its editors/authors (at least they get a citation). Clearly point out the advantages...

The theory explains more with less (effectiveness/parsimony)
The model/algorithm is shorter and/or runs faster (efficiency)
The results are more accurate and/or have lower variance (efficacy)


Is it plagiarism (or bad practice) to cite reviews instead of source material directly? My first source of information when preparing a manuscript are reviews. If up-to-date and comprehensive, I feel I can create most of my introduction by rephrasing and citing them. Nevertheless, reviews are based on citing other papers and, with the deluge of literature published these days, finding the source material for a single claim sometimes becomes a never-ending and time consuming play with a Matryoshka doll.

For example, in this review by Misteli (2007), the following claim is made and supported citing three papers.

  The recent development of methods to probe the physical association of
  genome regions in a unbiased and genome-wide scale should lead to
  rapid progress in our still-rudimentary understanding of the
  functional significance of chromatin loops (Simonis et al., 2006;
  Wurtele and Chartrand, 2006;Zhao et al., 2006).

I consider relevant to a point in my article that there are new roads being opened to study “the functional significance of chromatin loops”, To do so, I have three options:

Rephrase the sentence and cite Misteli, 2007, acknowledging that I extracted the citation from the review and depriving the authors of the source material of a citation;
Rephrase the sentence and cite Simonis et al., 2006; Wurtele and Chartrand, 2006;Zhao et al., 2006  without reading the three source papers, which is kind of deceiving but at least acknowledges the authors of the research and not the author of the review; or
Read the original articles, rephrase and cite Simonis et al., 2006; Wurtele and Chartrand, 2006;Zhao et al., 2006, which is the most “honest” option but incredibly time consuming.

Sometimes, if I decide to do 3, I may find myself spending a lot of time reading, only to write something that was already said in the review.

Which option you would abide for? Am I somehow plagiarising the reviewers or primary authors if using any of my strategies? In terms of ethics and good scientific conduct, which is the best option? How deep and when should I look for source material?

I am not asking about which version of an article to cite, like here. I assume that versions cited in reviews are the most up to date. I am asking when it is correct to cite the review or the primary source found in such review.

Note: My strategy up to this days is a mix of 1 and 3: search and cite the source material only if the paper is relevant for the core of my article and cite the review when filling the generals.

Yes and No.

A review is not (or at least should not be) just a list of papers in the field, it is a research paper in its own right. A review should provide some form of new structure or idea that come from reviewing the scientific output the field in question. Thus a review can be useful when either pointing at the results emerging from the review or when you wish to provide an example of where a throrough description of a field is provided. So citing a review should primaruily be for general purposes.

If you need to cite a specific detail provided by one or several references in the review you should turn to the cited articles and check them. There is, first of all, no guarantee that the citations are correct and citing something that is not correct propagates errors in publications. In addition, the cited work may not be all the relevant work supporting a point from your perspective so your sources may become biased. After all your point for writing is most likely not the same as for the one writing the review.

A review therefore has a function on its own for providing overview and synthesis which can be cited but if you need to cite details you must go to the original work and also not limit yourself to the reference list of the review.

EDIT: Just to answer the question in full: plagiarism is only if you copy the text with out quotes. If you copy the references you are not necessarily plagiarizing but you will then give the false impression that you have actually read, in part of fully, the articles concerned and that is in the realm of unethical behaviour. In the best case, it is unwise for the resons given above.

For my perspective as a computer science researcher.

You mention 3 cases in your question:

you can depend on the review and follow the author's opinion. In this case, you will not get the whole picture.
That is plagiarism.
You can check the 3 source abstract and read the relative papers to your study then rephrase based on your opinion.


What are the consequences of refusing to grant honorary authorship to a superior? Recently, I learned about honorary authorships in papers and publications - e.g. the head of an institute or person who secured the financial grants.

If you are in an inferior position, like a PhD student or not being the head of an institute, and you do not believe in giving credit via authorship to anyone who was not significantly involved in the studies directly; (by the way, according to some scientific boards, not even securing grants or offering the lab counts as such), can you successfully deny adding an honorary authorship for your supervisor or other superior without having to bear negative consequences for your work and later supervision?

After all, honorary authorship has a bad influence on life balance of scientists if seen on a large scale.

I'm surprised this is still an issue - though I guess not as surprised as I'd hoped to be. It's rather sad that there are still people out there who demand to be credited for work they haven't done.

Some journals have clear guidance for what merits authorship. For example, pretty much all medical journals sign up to guidance from the International Committee of Medical Journal Editors (http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html#two) which requires

Substantial contributions to the conception or design of the work; or
the acquisition, analysis, or interpretation of data for the work AND

Drafting the work or revising it critically for important
intellectual content AND
Final approval of the version to be
published AND
Agreement to be accountable for all aspects of the
work in ensuring that questions related to the accuracy or integrity
of any part of the work are appropriately investigated and resolved.

(So in the example above, getting the grant money would probably count as contributions to conception or design, so warrant authorship as long as the putative author then didn't abandon the project but could meet the other three criteria; but providing space for the work e.g. in a lab or recruiting participants, on it's own wouldn't be enough)

Most journals then require a statement of what the authors did to meet these requirements which is published with the article - so in order for someone who doesn't warrant authorship to claim it they, and their 'co-authors' have to lie in print.

So in the unlikely event my head of department, or anyone else, insisted on being added as an author when I thought they didn't warrant it, I'd ask them to justify the request using the ICMJE criteria.

Of course - thats the easy bit.

If you're working in an area which doesn't work like this, you have to think about keeping on board with the community. If someone senior really thinks they deserve authorship on your paper, and you don't, you have to decide whether you're going to keep them happy.

I'd suggest you may need to find someone else to persuade them they should't be named. That may be someone superior to them in your institution, or you may need to discuss with the editor of the journal you're submitting to - who can then ask for justification of contributions should they see fit.

Fundamentally though it seems that attitudes like this may suggest something rotten in the culture of either a department, or possibly a discipline. And culture change like this will take years.

To specifically address the "honorary authorship for your supervisor" part of the question:

If your supervisor was not helpful in guiding you toward developing your publications, I believe you have a much bigger problem than your author list.


In academic papers, is it really a bad thing to not report the relatively not good results? I am going to submit a computer science paper to a conference. So the thing is fairly simple. On some datasets with 1:1 ratio, our model achieves really good performance. On datasets with 1:5 or 1:10 ratio, our models only reaches mediocre results.
I just want to report the results of datasets with 1:1 ratio in this case since they are pretty good. Putting a mediocre result (on the 1:5 or 1:10 ratio datasets) may extremely lead to a whole paper getting rejected. However, my PhD advisor told me that we have to put the mediocre result as well.
Meanwhile, the PhD advisor seems really angry about this behavior and disappointed about me, and I feel really sad because I didn't cheat, and I just not want to include the relatively mediocre results in my paper.
I think many other computer science papers do something like that, not reporting their results on some datasets if the result is bad, and reporting their results on some datasets if their result is good.
I don't get why my PhD advisor is so angry about that. Could someone tell me? I am really appreciated it.
Currently, I feel wrongly judged by my PhD advisor and afraid of the whole paper getting rejected because of this since we are going to submit to a top-tier conference.

Research is a search for truth, not for happy talk. If you have evidence of some behavior then you should be honest and report it just as it is. Don't try to dress it up.
Giving only the "best" results will sometimes mislead people and will cause them, perhaps, to waste time and effort.
You are currently the best source to give an honest and complete review of the meaning of your results. I strongly suggest you do that. At some level, not doing that is malfeasance.
I suggest that the reviewers themselves probably think like I do and won't reject a paper that is honest and complete, other things being equal. They aren't looking for happy talk either.
But you may also have an opportunity to investigate why you get different outcomes. Is it something about your model, or something special about the data? Inquiring minds want to know.

Your question is mostly on why your supervisor is angry with you.
You acknowledge that you only wanted to include the results when operating on datasets where the model handled them well as you perceive such results as carrying more cachet with conference editors. Your post suggests that you see little wrong with doing this.
Your supervisor impressed on you the scientist's obligation to report all work done, the bad as well as the good. He "seems really angry about this behavior and disappointed".
I think that I know why.
In every working relationship there is a basic trust demanded. Clearly with your supervisor, he trusted you to appreciate the need to report the full facts as they occurred - not as you or he may have liked them to have occurred. Somehow when he took you on as a PhD student, he thought he could rely on you having that much integrity. How or why he thought he could rely on you, we don't absolutely know. But we can hazard a guess that other things you did - and perhaps to a greater extent how you did them - assured him that you would be sound on data reporting integrity.
I'll be fully honest about what I think here. I believe that you have been playing your supervisor rather than having honest exchanges of view with him. From the outset, I believe that you adopted a nice smooth manner with him and deftly ignored any likely areas of conflict. You picked up from your undergraduate days how academics tend to assume that people with agreeable manner would share their views and standards. In reality, life isn't so simple. Many people with forthright - even tactless - manners can often have very high standards and many with great social finesse show little scruple when their own immediate desires are involved.
Now that you have shown your true ethical colors, the professor realizes he has not been vigilant on the professional character of his student. He must be very angry and disappointed with himself for being weak and falling for your pretences. On top of this his own reputation in the eyes of peers would be stained by association with someone withholding relevant facts in a conference paper.
You may not realize it but your career in research could be nearly over. A single nuance in how a supervisor's reference is phrased could eliminate you from any serious scientific position after your PhD. You have to accept that, notwithstanding the growth  of the "executive academic" in the last 30 years, research is still largely a humdrum occupation demanding more of our endurance than of our creativity. If color, glamor, travel to exotic convention capitals is what you seek you need to move into marketing. I know a few PhDs from my own era who did that and are now multi-millionaires. But if - after a period of contemplation - you decide you want to stay in research then you have to learn to take the bad with the good as far as presenting results are concerned.
Lately I had an idea related to a field that has 60 years of global research activity. It was counterintuitive and yet still hard to believe that so many others could have missed it. After a literature check to see if anyone had reported anomalous results, I found a few who had done the very experiments that would bear out what my idea predicted. It would have been easier for these researchers to just not mention these experiments and focus on the more agreeable data from other experiments. (In fact very difficult in the case of one of them, a PhD student who had to present plausible reasons for his observations to some external examiner.) Yet they did not and I appreciate their honesty and integrity.
EDIT
I also note from here that this supervisor took over your programme after 1 year. You should appreciate the fact that someone was prepared to "stand" for you when you changed supervisor. You therefore owe him some consideration even if you see nothing wrong with your own intention.


Someone referenced my work in a journal paper using my first name only, do I contact them or the journal it was published in? Someone referenced my work in a journal paper but they did not cite it the right way.

They only included my first name, my supervisor's first name, the name of the paper and the date.  They did not include our last names or the journal that the paper was published in.
Do I contact the authors or the journal to correct this? Or can it not be fixed?

Currently, the citation is not included in my Google Scholar page because they didn't write my last name nor my supervisor's last name.

I would recommend approaching this problem through the following layers of triage:

First, is it a serious journal, or a predatory trash publication?  If it's not a serious journal, just ignore it and move on. It won't really count as a citation anyway, and there's basically nothing you can do to get a meaningful response from the people running it.
Second, if it's a real journal, is it in the final form or a "just accepted" pre-print?  Some journals give early access to "just accepted" manuscripts before any copyediting occurs, typically with a big warning label saying "Not yet final, things may change."  If this is the case, then you may be able to count on the production staff catching the problem and getting it fixed before the final form; if you don't want to count on the error being caught, it is reasonable to (politely) contact the authors.
If neither of these is true, and the paper is in its final form in a real journal you can write to the editorial staff to request a correction.

I suggest,check for the format of the published Journal or other papers in that Journal. If format of the paper is as such only FIRST authors and no JOURNAL name, nothing much can be done.

Manually, you can add this paper to your GOOGLE SCHOLAR profile, under the PROFILE NAME click on "Add" button and "Add article manually" on left side. Hope, this helps you.


Missing final exam due to exhaustion? A student is asking for an alternative exam because he was "completely exhausted" due to overwork the last month or so of the semester, including the exam day.

He provided a doctor's notice validating the claim and explaining the physical symptoms. He also provided another notice proving he did actually took an excessive number of courses recently and did well.

Should I give him the opportunity to retake the exam?

You should do whatever you or your institution would ordinarily do for a student who brought a doctor's note after missing an exam. You are not the student's doctor and the cause of the student's illness is completely irrelevant.

I come from a background where it is totally acceptable and common to not attend the regular exam just because you want some extra time to study. Any students who missed the first exam or failed it are automatically registered for the make-up exam, no justification needed. So, leaving out the "moral indignation" aspect, unless you have strong practical reasons not to organize a make-up exam, let them take it.


How can I increase my chances of being accepted to a top 20 MS CS program? I just graduated from one of the older IITs (Indian Institute of Technology), majoring in EE and have a GPA of about 7.8 / 10. I want to pursue a masters degree in computer science from a top 20 university in the US. I have a paper published in an international conference on machine learning and have good test scores(GRE / TOEFL) but I'm worried that my grades could affect my chances. I have some experience in competitive programming, my team finished among the top 10 among 300+ teams in the ACM ICPC regionals and I have a decent Topcoder rating. Not sure if this matters though. I have also made contributions to open source projects and have open sourced some of my projects, some of which have been downloaded thousands of times.

I've seen people from  unknown colleges with higher GPAs getting in to places like Stanford, UIUC, Cornell, CMU etc. Realistically, do I have any chance of getting admitted in a top 10 or 20 program. If not, what can I do to improve my chances within a year?

UPDATE: Well, I guess grades do matter, I didn't get into any of the good schools I applied to. I'll have to give up my hopes of grad school now.

Realistically, do I have any chance of getting admitted in a top 10 or 20 program.

With a publication in an international conference?  Definitely!

Of course, I'm assuming that you mean a good publication in an internationally recognized conference (not just a conference with papers from more than one country), ideally indexed in DBLP and available over the web.  I'm also assuming that you will have strong recommendation letters describing your contributions to the paper, in specific, personal, and credible detail, as evidence of your research potential.  Ideally, your letters will make direct comparisons with other IIT graduates who have succeeded in strong graduate programs.

I'm also assuming that you have a compelling statement describing your research experience and interests, written in flawless English, and that those interests are a good fit for the faculty at your target departments.  Be sure to describe your ongoing open-source projects.  (The contest stuff?  Meh.)  As Daniel suggests, focus on the work you want to do, not the ranking of the department.

And of course, I do mean you have a chance, not that you have a sure thing.  Graduate admissions is a random process; you have some influence on the distribution, but someone else rolls the dice.  Machine learning is a particularly competitive area, so if you want to continue in that direction, you should apply broadly.  In particular, you should not limit yourself only to programs that appear at the top of some list in some stupid magazine.  Rather, aim yourself at departments whose faculty and students have similar research interests to your own.

(I regularly serve on the CS grad admissions committee at UIUC.)

You don't have a chance of getting into a top 20 university because you don't have enough GPA for that. Top 20 universities are for students getting  GPA of above 9.5. But in your case, excluding the GPA you have a great chance of being accepted to top 40 universities like University of Virginia but Cornell, Stanford and all ... You can't just dream of that. So please try for the university which you can afford mentally, academically and financialy.


Has anyone, based on great performance, ever been awarded a higher degree than the one they enrolled for? Out of curiosity, I was wondering if anyone, historically, has ever been awarded a degree that was a level higher than the one they were enrolled in and studying for, simply because their performance warranted a higher award? For example, somebody could have been awarded a MPhil instead of an MSc or a PhD instead of an MSc?

Although a bit old, there's the case of Luzin's Master's thesis: . . . he completed his thesis The integral and trigonometric series which he submitted in 1915. After his oral examination he was awarded a doctorate, despite having submitted his thesis for the Master's Degree. In fact, even for a Ph.D. thesis, Luzin's is one of the strongest ever written in mathematics --- in my opinion easily in the top 20 (and probably in the top 10) of all-time Ph.D. theses in mathematics for its influence on later developments.

This appears to be the published version of Luzin's thesis, which is 242 pages and in Russian, with the table of contents on pp. 241-242. For references to it, this search and this other search seem to work the best. I didn't get many hits for the title's French translation, by the way.

It depends on the academic regulations of the respective institutions.  I don't think this is generally possible these days.  However, if you check this academic CV, you'll notice a conspicuous absence of a diploma which I know (due to personal knowledge) to be no accident.  This was in Germany in 1962, considerably later than some other examples here.  I should be surprised if this was a singular (even though rare) occurence to happen at that time even though I don't know personally of other examples.


Publishing someone else's thesis work without their consent Finished my MRes recently. My supervisor has told me that their ex-PhD student (graduated a year and a half ago) had some results in their thesis that they hadn't published. He asked me to complete some additional lab work and tweak a draft paper the student had put together, then I could be looking at getting a lead author position.
It sounded great initially, but I was a bit curious about the situation with the old PhD student and asked one of the post-docs (who is connected to this work). They explained the ex-PhD student was working on the paper after they graduated, but after some personal situation (unsure what but sounded serious) they basically vanished and were uncontactable.
I was a bit uneasy about this. I asked my supervisor and whilst they said the PhD didn't confirm they were happy to have someone else write their paper they didn't respond to emails saying that the supervisor was planning this. So from my supervisor's perspective this is all above board.
For extra info I looked up the university's policy and it says that the copyright for the thesis, and all of the data described, is owned by the PhD student.
Could writing this paper potentially get me in major trouble? Wanting a career in research and a paper would be good but this feels like this could easily go bad given the universities position on IP ownership and it using the work carried out by the PhD student.

I think in this case, the easiest solution would be to publish your paper with a reference to that other student's thesis (or unpublished work).

Assuming that the original PhD student is kept as an author, and the paper states clearly who did what, I'd say you are in the clear.


Is including references of journals with low or no reputation considered bad practice? I am working towards my PhD in a quite specialized area of engineering, at the overlap of two technologies. Because of this, there are not as many publications available in my field compared to other topics. Furthermore, there is no journal specializing in my area of work, and articles are published in a wide range of journals, some of them not the most reputable ones, to put it gently.
I nevertheless have used such references from journals perceived by some as disreputable, just because there are not that many in total to choose from. But often also because the articles aren't of bad quality, in fact, some of the articles in "shady" journals can be of better quality (IMHO) than articles in more reputable publications.
On the other hand, a lot of academics seem to find the idea to publish in a "low quality" journal abhorrent and claim they would never do so, indicating that these journals represent second-class science.
So my question is: is it bad practice to reference journals of low or no reputation or is it OK to do so if

there is a limited overall number of references to chose from?
the quality of the article is high enough? (This would beg the question if I, a lowly PhD student would be able to determine quality in a publication...)
any other reason

I am curious what your opinion on this is.

If you use insights from a publication, you must cite that publication, no matter how low the regard in which you or others hold the venue.
If you're nervous that there's a high risk the insights will be wrong, there are things you can do to reduce that risk:

seek out an independent corroborating source for the same insight (and cite it in addition to the "low quality" source);
check the chain of logic from evidence to conclusions in the "low quality" source step-by-step for yourself (and still cite the source);
if it can be done ethically and affordably, repeat a few of the experiments (if any) reported in the "low quality" source to see if the results are reproducible (and still cite the source).

As a PhD student in engineering myself I personally got the feeling that not many scholars care about the journal reputation in our field of research.
I do not know how it is perceived in other areas, but, if the articles you cite are of quality although they are published in a „low reputation“ journal, you should absolutely cite them.

Edit: I expressed myself very poorly in my original answer (hence, I deleted the paragraph!). My original answer could be (and was) understood in such a way that I recommended you to not cite papers from predatory journals. What I originally wanted to imply was that you should proceed with caution when using results from such papers if they were published in predatory journals. However, if you use them, you definitely have to cite them, also!


Is open-plan office for academia at all? Where I did my PhD, typically two PhD students shared an office room. In constrast, where I am working as a postdoc now, about 50 PhDs and postdocs share an open-plan office.

I find it difficult to concentrate in the latter kind of arrangement because of the noise. Some people use head/earphones, but I guess not everyone likes to listen to music while working. I am wondering if this is a common arrangement in academia. My guess is that while it might work elsewhere, the nature of academic research precludes an open-plan type of office.

In any case, is it appropriate to ask my supervisor for a room or a smaller/quieter space to work in? I don't think I would ask, though, because everybody else seems to be fairly content, but I'm just wondering.

There is plenty of research showing that open-plan offices are a very bad idea, not just in academia but everywhere (see below for some examples).

Unfortunately, they are also much cheaper than proper offices (mainly because you can pack people much more densely).

Danielsson et al. (2014): "Office design's impact on sick leave rates", Ergonomics 57(2), doi:10.1080/00140139.2013.871064:

  The cumulative evidence thus indicates that traditional open-plan offices are less good for employee health.

Oommen et al. (2008): "Should Health Service Managers Embrace Open Plan Work Environments?: A Review" Asia Pacific Journal of Health Management 3(2), 37-43:

  Research evidence shows that employees face a multitude of problems such as the loss of privacy, loss of identity, low work productivity, various health issues, overstimulation and low job satisfaction when working in an open plan work environment.

As a Spatial Designer that designs university interiors in the UK, I will keep this brief: University's cannot afford singular offices. Researchers and academics need to realise this. The energy costs for the institutions are crippling, heating and lighting hundreds of small offices (which are often empty) is financially and environmentally unsustainable, never mind the maintenance. Meanwhile undergraduates: the paying customers, have to make do with poor quality learning environments and tired social spaces because all the money is being spent behind closed doors. What university academics often fail to realise is that there are many many people in the commercial world that do very high level research in contemporary and efficient open office environments - not hidden away behind a wall of yellowing books and completely unaccountable.


Is the curse of knowledge a real effect? This post is inspired by this question discussing what is known as the curse of knowledge - the ostensible effect where having knowledge about something makes it hard to put yourself in the mental shoes of someone who doesn’t have it, and the corollary effect (which is of clear relevance to the academia setting) that teachers tend to become less good at explaining a subject the more their expertise on the subject grows.
Question: is this effect real? Please cite actual research that supports your claims.

It is worth considering at the outset, that both the extent of knowledge possessed and the ability to teach are subjective and difficult to directly quantify. Therefore, when examining research on the subject, we shouldn't forget that quantification is usually based on indicators loosely correlated to these qualities.
For instance, gauging the extent of knowledge possessed would require some sort of a test (I doubt many academics would subject themselves to the indignity!). Luckily, subject matter knowledge has been tested amongst school teachers, so we have something to go by. Unfortunately, there appears to be a weakly positive correlation, or none at all, between knowledge and ability to teach [1]. Of course, ability to teach is measured by student outcomes, which is also indirect and subject to other factors. A bunch of other markers for knowledge have been  examined in the past, with most exhibiting weak correlations [2].
It is interesting that none of these convey the negative correlation that the 'curse of knowledge' suggests.
Conversely, more recent studies show stronger positive correlations between teaching experience and teacher effectiveness [3,4]. It would then be a fair assumption that the more knowledgeable academics would in general be more senior and therefore have more experience, and thereby be more effective teachers.
Certainly, many of us have personally encountered counter-examples. These encounters probably reinforce the idea of the supposed negative correlation, but are quite clearly a case of confirmation bias. Since the question is about actual research, I think we should just treat the 'curse' as a bit of amusing anectodal folklore.
[1] Byrne, C.J. (1983). Teacher knowledge and teacher effectiveness: A literature review, theoretical analysis and discussion of research strategy. Paper presented at the meeting of the Northwestern Educational Research Association, Ellenville, NY.
[2] Linda Darling-Hammond (2000). Teacher quality and student achievement:
a review of state policy evidence. Volume 8   Number 1, Education Policy Analysis Archives.
[3] https://learningpolicyinstitute.org/product/does-teaching-experience-increase-teacher-effectiveness-review-research
[4] https://www.edweek.org/leadership/new-studies-find-that-for-teachers-experience-really-does-matter/2015/03

If you take the meaning literally, then yes, it is real. The wikipedia article you point to itself has pointers to some of the research.
But it is a "cognitive bias" not an absolute block. In most situations people speaking to other people have a tendency to suppose that the other person shares their context. If we didn't, then we would find communication impossible, needing to give background and context for nearly everything. If the conversation is two-way, with someone from a similar background, then it is relatively easy to fill in the blanks in most cases. Generally it works. But Americans traveling around the world often make too many assumptions, leading to the Ugly American effect when the visitor doesn't understand and refuses to learn. Imagine being the first human on a newly discovered planet of intelligent beings and trying to communicate with no shared context at all. Everything we know is wrong.
But I don't extrapolate this bias to assume that teachers become "less good", unless they ignore pedagogy and make unwarranted assumptions about students. A few of us do that, of course, but many of us are conscious of the fact that our students are not like us unless they are in doctoral programs and share our context.
In fact, recognizing that the tendency exists can make you a better teacher if you try to remember what you were like when starting out. When I started teaching Tai Chi, as a non-science example, I was very careful to explicitly capture the learning difficulties and misconceptions that I started out with as a practitioner. It made me more sensitive to the issues students had and more patient when they repeated mistakes. That focus made me a better teacher.
I've also written here in a few places about teaching students in CS how to learn. How to take notes. How to summarize. How to make learning deep and real. But first I had to recognize (a) my students are beginners at this, (b) they are all different from one another, and (c) they aren't like me.
So, no research to share, but a lifetime of getting better as a teacher by recognizing a few things and especially, how to be patient while still being insistent with students. Well, that, and being less didactic, too.
And note that for a teacher of some complex subject (not just STEM), the instructor and the student don't share important context. Otherwise there is no point to teaching.


Shall I apply again after all my PhD applications are rejected? I am 29. I've had informative, goal-driven, well written SOP, I'm guessing good recommendations. I have a masters in the related field (Computer Vision) with tier 2 publications. I'm in a research engineer job which can not add publications to my profile. I have been rejected by 13 US universities (all not Stanford, Berkeley). I had contacted the professors. Many did not respond though.

How do I ask for recommendations again if I try next year?
What can I add to my profile in this scenario?
Are younger students preferred?
Will there be sufficient opportunity if I complete my PhD after 35?

Age is not a discrimination in your age range, there will be opportunities when you complete your PhD but you should ask yourself what kind of opportunities are you seeking by completing a PhD.

If you stay at the same job your LOR will likely be the same in one year, so you have to change something else. I would suggest you reach out to 1-2 professors whose work is closely related to your job and see if you can be involved in one of their projects, and see if this can also benefit your company. I am afraid if you don't build a more direct connection with academia/research your chances will stay low. Otherwise you have to aim lower, less prestigious schools, but then we go back at WHY you want to do a PhD.

Don't do it. If 13 institutions have rejected you, there is likely a consensus that you are not suited/fit for getting a PhD. And even if you make it in, it may be difficult/impossible to finish the PhD. The GRE is an awkwardly good predictor of grad school success. If your GRE is bad, nothing else matters.

Can't speak for computer stuff, but my program has (previously) admitted people over 60. Different fields vary on ages, as they vary by both admissions age and time to completion. (Average for a history PhD is now 10 years...).


How can a young student get a mentor? I am a young student. However, I do have a lot of curiosity and am very hard-working and will try my best to work with others and try my best to learn new things.

I have been reading Security Papers on Arxiv a lot (I am also confident with my knowledge) and conducting my own tests on security systems. I have got far with it and feel I am able to understand most of the papers in a certain field in security programming very clearly. I have also tested my skills across the field by helping out in certain forums and I feel I am worthy enough to start learning research techniques from professors or even help out trivially in research.

I am very interested in the field. I would just LOVE to research in it.
How can I get a mentor?

Two ideas:

Ask around for a student assistant job that can yield a first glimpse inside the world of research.
Write your thesis about one of the topics that you alluded to in your question. This can be a first step towards a paper and it is an opportunity to discuss your topic with a professor.

This may depend on the institution where s/he studies, for example:

For schools, these young students can select a teacher who has a postgraduate degree in their subject of interest as their mentor, just as in colleges & universities, the person who supervises a young student during his/her thesis, which is generally written for a postgraduate degree, becomes his/her mentor.


How to handle a paper by a reviewer who wants to be paid? A reviewer declines to review a paper because he wants to be paid. Some time later, this reviewer submits a paper to the journal (or to another journal who's aware of what happened – very possible with today's editorial management systems). How should the journal handle this?

Possible options:

Pretend we didn't notice and review as normal.
Write him an email to tell him we're aware of it, but are reviewing the paper anyway because we're a magnanimous journal.
Charge him a submission fee which we then use to pay the reviewers for that paper only.
Charge him a submission fee which we then use to pay the reviewers for that paper only, plus some extras which we use to pay the editor.
Desk reject because "our reviewers are on strike because they're not paid so we can't find reviewers for your paper".

I'm concerned taking retributive action will come across as petty and / or lead to a lose–lose situation. However, not taking retributive action doesn't feel right either – if the reviewer is not willing to review unless paid, then it's hard to expect other people to review (or handle) his paper unless paid either.

If it matters, only the first part really happened: The reviewer used the "decline to review" button with a reason that went something like: “Sorry, I don't review unless I'm paid. Feel free to contact me again to discuss rates”. Still, this decline reason is logged in the EMS, so it can happen in the future.

First of all: Is there a rule that you need to be available as reviewer if you want to publish in that specific journal? People decline reviews for all sorts of reasons (often lack of time, which may or may not be the case), and I never heard that somebody got "punished" for that.

Your reviewer wanted to get paid. It is very unusual to pay reviewers, but on the other hand, it is not per se unreasonable or offensive to ask for compensation for work.

I would see it this way: Either you establish a general rule that authors must be available as reviewers or you accept that some people do not review papers (although they publish).

Why not

Reject his paper, informing him that your journal's QA process works by having its potential authors do unpaid peer reviews, and hence, willingness to do unpaid peer reviews is a condition for being an author.

Only do this if this is actually your policy, and you uphold it strictly.

Other than that, only your first option seems reasonable. Never make it personal.


How should a teaching assistant explain his absence to the course instructor? As an international TA getting accustomed to the landscape of my University, I managed to earn the ire of my instructor/professor for having not shown up during the discussion/office hours.

In a strongly worded mail, he has sought an explanation while reprimanding me saying that another instance of this would lead to serious consequences.

I am afraid that I may lose my assistantship as I curse my folly for being so careless. I have apologized to the Professor over mail but from the tone of his reply, he seems to have not considered it. Please suggest how I must handle this predicament.

The best way to handle this is to acknowledge that you've screwed up, and to explain how you're going to make sure that you won't miss any class meetings and other events in the future. If there's a justification for why you missed the event (for instance, if you had an examination for a class you were enrolled in overlapping with office hours), you can mention that.

For the time being, do whatever it takes in order that you do not get sacked. Technical advice for that has already been given.

If it is indeed true that the instructor already rejected a reasonable apology from you, then work on an exit strategy from the employment relationship with that instructor. I always demand reliability and meticulousness from those whom I work with. However, mistakes happen, and when they do, it is important to limit the damage and then move on quickly. There is no need to humiliate anyone for making a mistake, like demanding multiple apologies. (If mistakes by the same person accumulate, the situation changes. But this seems not to be the case here.)


How to find collaborators for just writing and formatting manuscripts In our research group we do many things, but have little time for writing papers. Sometimes things like formatting the manuscript for some specific journal or just writing the intro and methods sections can be very easy things if what you do is almost always the same, or you just need to rewrite some parts from one paper to other. This is always (from my opinion) straightforward but needs lots of time. Therefore I started to wonder how could I find people for just writing and formatting manuscript 100% of the time. How would you do this?

P.S. I remember some years ago there were some websites where programmers could interchange between them "services" for free, for instance one would write some C# code if the other one could do a website for the other. Do something like this exist for academics where the services are "writing papers", "formatting grants", "getting bibliography", etc.

Writing the manuscript is a significant scientific contribution. Is your research so trivial that anybody can interpret the data that you give them and write to a high scientific caliber on them, with no further inputs from you? Most likely, you'd need to also provide them with a rigorous analysis of that data, probably in writing form, since they might no share an office with you, and also for record keeping. That explanation becomes the crux of a paper that you could write yourself in the first place. The time spent explaining the data to someone not involved in an experiment will be greater than just writing the thing yourself. You'd be only saving time on tiny matters of sentence formulation, if you'd even save time at all.

Formatting a paper in my experience doesn't take that much time, so I'm not sure where you're coming from in on that point. Most journals provide you with a template that you can literally copy paste into. If something is straightforward as you say, it shouldn't take that much time at all. If by "getting bibliography", you mean compiling the bibliography, that will also be something that only you, being familiar with the experiment, can provide. A bibliography should be something that arises naturally from the need to reference previous methods/works for your analysis, not a chunk that you copy paste between papers without thoughts.

If you mean that they also do the data analysis, then they just become a regular scientific collaborator, with full authorship rights.

On the first look the problem of finding collaborators has to do with motivating people and to find people who are interested in a subject. For example, a group is formed around a robotics research project and now the question is why it is so hard to find somebody who likes to fix the typos in a manuscript or likes to write the introduction. But what exactly motivates people to contribute to a project? Is it only money or has it to do with the academic subject? The answer is a bit more complicated. It has to do why a certain project is done by a group of people.

A research project doesn't start by itself. In most cases, the environment of a research group assigns a question to a group. A typical example is, that a university likes to figure out how to program a computer vision system for a biped robot and assigns this task to a workgroup. The reason why the people in the group are motivated is not because they are interested in the task itself, but they would like to do the job for the university.

Answer the problem of how to find collaborators is possible by referencing to the external customer of a research project. A research group can announce, that they have the assignment of a concrete customer and then the question is which authors likes to do the job too. Individuals are not motivated by money or the subject, but they would like to contribute to a certain external customer.


PhD problem: a new student has the same idea as me I am in second year of my PhD. I have a plan for my second paper, I did a full scale literature review etc. But then I put it on hold to finish my first paper.

A new student started this term and is coincidentally pursuing the idea for my second paper!

I highly doubt we can both have the same paper.

I know that co-authoring is a possibility. But, is there grounds for me to argue that she should find a new topic, instead of me. As it will mean that I wasted a large chunk of my first year on this topic.

We plan to use data for the same country, which means that we will ultimately end up with the same statistical model, because the data available is not the best, so there is not much leeway on what model I use.

From what the student has told me, her statistical plan (is the same as mine), which is also the popular method in the literature field.

You should probably talk to your advisor and possibly arrange a meeting with the other student, her advisor, your advisor and yourself. You need to sit together and discuss how your work and her work are going to differ, because nobody has anything to gain from two competing PhD students undermining each other within the same research group. Once you have fixed boundaries, you will be free to go your own way and collaborate on the common parts, which will benefit both of you.

Your professor is your god on this one.

You come to him with wisdom and patience, and not with wrath.
You tell him:

this is the situation (describe).
you tell him/her that you will do whatever he/she tells you.
you ask him/her what to do.

You do exactly as your professor says. No more and no less.