Should I retract an article published in a disreputable journal? I was published by the IJARCS in 2011 (International Journal of Advanced Research in Computer Science) and was wondering if I should retract my article due to the journal being disreputable.

I am under the impression this journal is hurting my CV more than helping it, but to have it removed I need to show that it has a serious flaw in the research.  The article can be found here:

http://www.slideshare.net/IanMalloy/l-2213-321470

Should I list the publication in my CV or not and if it comes up, it comes up?

I don't know of any journal that one could expect to accept "I don't like your journal any more" as a legitimate reason for retraction: a good journal would probably just scoff at you, while a crappy or predatory journal is unlikely to meaningfully respond to any request for retraction, no matter how legitimate.
Therefore, I don't think you should try to retract it, but simply to drown out your early mistakes over time with subsequent good work.

As for whether to leave it on your CV:

If you have reason to believe that this journal is a sham that does not actually peer review, then I think that @NateEldredge is right: you can leave it off of your CV entirely or (better), move it to a section on published non-peer-reviewed work, much as you would list an arXiv publication.
If the journal is simply crappy, however, I think you're stuck with it.  You really did publish there, and no matter how crappy, it's still an archived journal publication.


Combine multiple major fellowships? I have received both the NSF and another major fellowship (non-federal). Both stipends cover more than my departmental funding; do I get the sum of the stipends?

First of all - congratulations!

To answer the question, the NSF provides specific advice on this question:

  May I accept or be paid from a private Foundation Fellowship?

  Supplementation to a Fellowship while on Tenure is at the discretion
  of the GRFP Institution. Fellows should check with their COs.

In practice, I've found that you can at times get funding to combine with the NSF, but it is often intentionally limited by your local institution/department. For instance sometimes you can get summer funding or a 0.25 FTE assignment even while receiving the NSF, but you may get administrative pushback, and they are loath (or simply will not) allow more than that.

You will generally have a higher likelihood of getting them to agree if you can take the funding at different times. The NSF GRFP for instance is for 5 years, but only 3 years includes funding. If you have a fellowship that provides 1-2 years of funding, you can take that first and then stay "on reserve" with the NSF - and most institutions will be somewhat unlikely to object to that. One institution I talked to offered a 1 year fellowship, and on asking them they replied that I could take the 1 year and then take the NSF funding in other years, but that I would not be permitted to take them both in the first year.

But ultimately, the NSF says that is up to your local institution, so you'll have to check with your department to see what they say.

For completeness, note that the NSF explicitly cannot be combined with other fellowships provided by the US government (they mention "DOE, EPA, NIH, NOAA, USDA, DHS, DOT, NASA, etc."), but as the OP mentioned non-Federal this should not apply to them.


Cleaning up/Uniformize bibliography for long document I was wondering whether existed some software that would take as input a text file bibliography (for instance a bib file if you use bibtex), and that run it through google scholar (or any other database), so that it can return a uniformized bibliography.

As an example, suppose you have two items from the same conference

@inproceedings{mpi,
   author       = {Surname1 Name1 and Surname2 Name2},
   title        = {Some nice work},
   booktitle    = {Editor of the Name of Conference},
   year         = {2004},
 }

and

@inproceedings{RRnrj,
  author        = {Name3 S. and Name4 S.},
  title         = {Some nice work},
  booktitle     = {Name of Conference (Acronym)},
  year          = {2020},
  publisher     = {Editor},
}

and you would want it to return:

@inproceedings{mpi,
   author       = {Surname1 Name1 and Surname2 Name2},
   title        = {Some nice work},
   booktitle    = {Name of Conference (Acronym)},
   year         = {2004},
   publisher    = {Editor},
 }

and

@inproceedings{RRnrj,
  author        = {Surname3 Name3 and Surname4 Name4},
  title         = {Some nice work},
  booktitle     = {Name of Conference (Acronym)},
  year          = {2020},
  publisher     = {Editor},
}

(or whatever is the norm on the database).

If you have the DOI codes, the best thing is to use the API and get the references yourself:

curl -LH "Accept: text/bibliography; style=bibtex" http://dx.doi.org/[DOI code]

If you have them (and you should, for any modern article), parsing the bib to get them and getting the data can be done in a very simple script.


Journal standards vs. personal standards I am currently reviewing an applied math paper that I don't think is great; indeed, I am hesitant to accept it even with major revisions.  The language is poor, I'm not convinced by the arguments, and the numerical results are difficult to interpret based on how they are presented.  However, based on other work this journal has published (in particular, other papers by the same authors), I think the quality of the journal I'm reviewing for is a bit lower than my personal standards.

Should I based my final recommendation on my own standards, or the journal's?

There are many different notions of quality of a paper:

accessibility of the presentation,
soundness of the arguments and conclusions,
relevance of the research.

Ideally, the level of journals only differs in Point 3. Realistically, there are some differences in Point 1 as well (ironically, I find that middle-level journal score best here, but that’s a different story). However, even mega journals aspire Point 2 – and outrage ensues if they clearly fail.

I would therefore not let the level of the journal influence assessment of deficiencies with respect to soundness, i.e., if I consider a paper unsound, I recommend to reject it, no matter the level of the journal.
Also, think for a second what would happen if all reviewers would recommend to accept all papers that are better than the worst paper in the journal in question:
Due to the variability and laziness of reviewers (and the abundance of bad papers), the threshold would decrease perpetually.
Nobody wants this.

Also, irrespective of the journal’s level, I note everything I see wrong with a paper, and let the editor decide whether this is a sufficient reason for rejection. As language problems (and some other presentation issues) can be fixed by a copy editor or similar, I would not even let them influence my main recommendation, but just recommend heavy copy-editing or similar to the editor.


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.


Are there any studies on how lecturer review sites such as Rate Your Lecturer affect student choices? A version of the lecturer review website Rate Your Lecturer recently became active in the UK.

Do you know of any studies which consider to what extent students use this or any other review websites to guide their choice of university?

This is necessarily incomplete, but I do recall a few studies on the correlation between ratemyprofessor.com rankings and student evaluations. Two such studies are:

Hotness and Quality
Student evaluations and RMP

These are disappointingly old though (2006/2007)

There's a more recent study from 2011:

Researchers and RMP

As for other studies, your google is as good as mine :)


Is it possible to work full time and complete a PhD? Is it achievable to perform a doctorate while working in a private company (not in college) full time (8 hours per day, 5 days per week)? Or is it too much work or stress?

I am doing that right now.  I have a full time job and am working on a PhD in Computer Science.  It is definitely possible, but has been the hardest experience of my life.  I am past the hardest part and am wrapping up my first publication.  I've also been at it for 3 years (already had my masters degree), so it's taken me much longer to get to this point than it would be for a full time student.

It has been extremely stressful and you can kiss your life outside of work+school goodbye.  You will also need to be very good with time management and be aware that over the course of several years, there will be life events that pull you away from school.

When I was deciding whether or not to do it, I vastly underestimated the amount of time and energy required.  I'm very glad I stuck with it so far, but I have to say, if I had an accurate picture of the workload I probably would have opted against it.

You need a huge amount of dedication to the goal in order to pull this off.  If you have only a casual interest in the degree, then you will probably fail.  I think I remember somewhere that the graduation rate for PhD's is around 50/50.  Add a full time job on that and the odds are against you.  But it is absolutely possible to overcome that with enough effort.


Can a poster and publication have the same title? Can a poster and its related publication have the same title or do they have to be different?

Obviously you should check for yourself with whoever you attempt to publish the manuscript with, but I've never seen a journal state that the title of a publication must be unique, and I have publications which have appeared in some form as posters with the same title.

It actually makes some sense to keep the titles the same. Any buzz that you might have generated with the poster may increase readership of the article. If you have separate titles then potential readers wouldn't have the association.


An invitation to join the editorial board of a newly launched journal I am in the first months of my postdoctoral research, where I work in a highly reputed laboratory.

Recently, I got an invitation to join the editorial board of a newly engaged journal. They invited me because of one paper I published during my PhD, which perfectly fits within the scope of the journal. Now, I am wondering whether I should accept or not. I do not know the criteria, based on which I should take my decision. Any suggestion!

There are two types of "new" journals:

A genuinely new journal
A predatory/semi-predatory spam journal

Deciding whether to join an editorial board is largely about trying to figure out which category your invitation falls into. The first step is the email itself - is it written in clear, professional language that suggests actual editors? Stop by the journal/publisher's website - does it look legitimate? Check into the publisher's other journals if they have them - do they look like actual journals, or junk journals?

The next step is looking at the existing editorial board/editors-in-chief. Are these people you recognize in your field, and would make sense as the people to be on board? Are many of the "big names" in your field conspicuously missing?

The final step, if it passes these checks, is to actually email the editor-in-chief to talk about the journal. This serves two purposes:

It's possible for a scam journal to list someone as an editor without them knowing - contacting them directly should confirm they are indeed the editor.
It lets you talk about the journal's goals, the expected workload, etc. to make an informed choice about whether or not you have time.


Review or research paper for junior undergraduate students I am a junior (year-1) UG student, I have noticed that there are 2 different types of papers / publications, research and review papers. I would like to ask as a total beginner in reading papers, if I am interested in a particular topic (for me it is organic chemistry, biochemistry and cell biology), which type of papers is better, as to understand deeper into the topic and the general paragraph structure and uses of words in a formal paper?
Thanks.

Research papers by their very nature need to often focus on a very, very small and specialized topic. This means that it is hard to get an overview of the field by just reading research papers. Reviews are generally better at that. However, those reviews often still depend on the reader being familiar with what was previously done in that field. So beginning students often still struggle with these papers. Of particular use to students and researchers entering a new field are reviews aimed at a more general audience. For example, in economics there is an entire journal aimed at this type of review: the Journal of Economic Perspectives. Once you have an overview of the field, you can decide what kind of sub-topic interests you and find a research article. You can use those articles to refine your knowledge, and learn about the typical structure of a reseach article.


Why are most people so intellectually uncurious I'm not sure this is the right place to ask this question.

I've noticed that almost everyone I have met is intellectually uncurious. In a world where our daily lives depend on technology that would have been called magic a century ago (cell phones, computers, etc...), it's hard for me to understand why people aren't even interested in how it all works. Perhaps they've hust gotten used to it - I once I asked a friend if he knew how his computer worked, and his reponse was no, and I don't care I just use it".

This lack of intellectual curiosity sadly permeates into academic settings, in my experience. Even my peers who study mathematics and engineering  don't understand my fascination at lightning storms, or an airplane passing overhead,etc. The physics students seem to be pretty curious in general, but I don't understand. My engineering friends always tell me the same thing "we don't need to understand it at a deep level in order to build new things with it".

I thought kids were naturally curious creatures? I would guess it's a result of bad schooling, but i've never heard of teachers actively discouring asking good questions.

So what's going on here? What factors contribute to the apparent lack of intellectual curiosity amongst the general public, but more importantly amongst STEM students.

The OP seems to imply that it is a kind of moral failing to not be curious about everything. Plokavian's answer is good for covering why many people simply do not have the time to be curious, but I think that their answer fails to cover two points: 1) people in academia who are, to a certain extent, paid to be curious; and 2) why should everyone need to be scientifically curious?

People in Academia

What do you think drives people to pursue graduate studies in the first place? There are many factors, but in my experience curiosity is one of the top factors.

In applied science I have met researchers who study the patterns that water drops form when they land on a surface. They openly admitted that they have no idea what application it could be used for, but they thought it was interesting so they spent some time investigating it. In other words: purely out of curiosity. Even in areas of research where the application is clear, a lot of research seems to start with the question "I wonder what would happen if...?". That is, curiosity. Why would they care how a computer works? They have other things that they find more interesting that they would rather spend their time on.

Why do people need to be scientifically curious?

The OP seems to define curiosity as a desire to understand how things work, such as technology or physical phenomena and seems to conflate curiosity with intellectual stimulation. But there are many ways to be intellectually stimulated without being curious about how everything works from a scientific perspective.

Consider engineering (my field). I know many students who left their undergrad to work in industry. Of course some of them only pursued the degree for a good stable job (nothing wrong with that!) but many others derived great satisfaction (dare I say, intellectual stimulation) from solving problems. To them, a computer is not necessarily something that needs to be understood down to its finest workings. Instead, a computer might be a tool in a big project that is working towards solving a problem for a client. It is the pursuit of the solution that drives them, not a need to understand how all of their tools work.

Consider a doctor trying to decide on the best treatment for a patient (often many patients). It is a complex problem that requires a significant amount of intellect. The doctor draws satisfaction from solving the problem and restoring health to their patients.

Consider an artist (not necessarily my forte!). They may want to explore new ways of expressing ideas or emotions. Exploration of any kind is fundamentally an act of curiosity. They may be curious about how people react to a piece of performance art. They may be trying to solve a problem of how to abstract concepts or objects to their simplest forms (see abstract art).

Finally, some people simply have other priorities in life. It is not a moral failing on their part! We need scientists and engineers and mathematicians and doctors and artists and many others who push forwards in their fields in the name of intellectual stimulation. But there is much more to society than that!


Is hastily writing down the professor's lecture a good way of learning? I am writing this from the perspective of a mathematician. I am wondering whether there is any research on the standard mode of instruction.
Mathematics lectures, at least in my home country, typically work as follows: the prof starts writing on the blackboard (or whiteboard) while telling about the notes, and students copy down the notes from the board.
90% of the lecturer's speech is reading out the notes aloud while facing the blackboard. Depending on the level interaction, there may of course be questions to the audience, but mainly it is reading out the lecture notes.
Most students aren't really listening because they are busy copying down the notes from the board. You typically see them turning their back and forth between the board and their own notes. Students may find themselves in "unintelligent copy" mode, just copying symbols from the blackboard without any comprehension of meaning.
Irrespective of your style of instruction, I think this is a terribly ineffective concept of teaching right from the start. Individuals have told me that they believe in some sort of "subconscious diffusion" of the lecture material into their students' minds, even if their students are just in "unintelligent copy" mode. I don't believe in this and find this rather counter-intuitive.
All in all, much of the typical way of lecturing looks like a giant waste of time to me. I can only imagine that the most gifted students may benefit from this, and perhaps that is the reason such a mode of instruction is pursued.
Has there been any research on this mode of instruction and its educational benefits? Has there been any research on that "diffusion" hypothesis?

Prior to electronic media generally and after the start of mass, rather than individual instruction, this was the primary way of teaching a lot of things. It can be a good start to learning, actually. However, it isn't enough, and never was. Learning is an active sport, not a spectator sport.
We learn by actively engaging the brain. Copying down notes is somewhat active. Certainly more active than taking a phone picture of the board once it is full, or downloading a lecture. It is even more engaging than (just) reading a lecture.
However, if you really want to learn, or teach someone how to learn, I suggest a few additional steps.
One is to review the notes after a day or so.
A more extreme version is to take the notes by hand (pencil and paper) and then transcribe them and add annotations that are needed, perhaps preparing questions for the instructor or yourself to answer.
One is to extract and write down the most important message in a lecture. Or maybe a couple of them. This can be done at the immediate end of the lecture.
One is to ask questions during the lecture if a step in a proof isn't clear to you. (Yes, instructors make mistakes).
One is to review the most important points of the previous lecture just before the next one.
But the most important aspect is to do some kind of exercises based on the lecture. Perhaps these will be assigned. Perhaps they are available in a text book. Try to get some sort of feedback on your solutions.
Another is to start a discussion group with a few students to review the lecture material and update the notes.
But the real key to this is that you learn by actually rewiring the synapses in your brain and that takes repetition and reinforcement. To assure that you are reinforcing the correct ideas, you need feedback.
Note that watching lectures (say on the internet) without active participation is almost completely ineffective for most people. Especially for long term retention and the ability to put the knowledge to use.

For some of the biology behind learning that suggests reinforcement and feedback see: The Art of Changing the Brain by James E Zull

Note also that, as a professor, I've had to explicitly teach this to students and force some of the activities. For those that learn easily they may not seem to be needed, but eventually things will get hard and having good practice can save you.
For example, I'd end a lecture a couple of minutes early and ask for "the most important lesson of the day", expecting that the students would have note cards with a few ideas.


My paper was presented as part of a Keynote speech written by my advisor. What do I mention in my CV? I have written a paper jointly with my supervisor. He will be presenting our research as a part of a keynote lecture on an international conference. The lecture is in his name, but a part of that lecture has to do with my research. In fact, he will mention my name on one of the slide as an acknowledgement of my contribution. I am in need of items on my CV for upcoming funding applications and I am wondering if I should include this lecture on my CV? If yes, how can I list this item on my CV?

No, you shouldn't list it on your CV -- it's not your talk. Presumably, this work has or will be published, with you as an author. That, of course, should be on your CV.


Untrue negative comments on RateMyProfessor website I pay close attention to how my rating scores/comments are like on the RateMyProfessor website. Very rarely I reported inappropriate comments (which violated site guidelines) for removals, and the average score has been decent (4.8).

Since last week, after I reported a comment (with improper language which violates the site guidelines), very suspiciously the same student (who is angry about their bad grade) has been trying to (even until now) leave 10+ intentionally untrue, deceiving comments with low scores.

My average has now been brought down to below 4.0. I've been frustrated because this severely compromised all true comments left by previous students. I reported this to the site and am still waiting for a response. Any suggestions?

As the comments suggest, just ignore it. You will always have disgruntled students even if you do a great job. Some will blame you for their own shortcomings.

But the best "defense" against such negative comments is the positive comments from those who think you served them well. If those appear also, then a reader can easily judge it for what it is.

If you want to "sabotage" such things, just point other students to the site, without comment. You don't need to "defend" yourself when your other students naturally do so themselves.


What is the difference between a concentration and a track within the major? We want to improve our undergraduate curriculum in my department by offering new concentration. Looking at many different programs in the US, the following questions came to mind:

If there is a difference between a concentration and a track within a certain major (I am talking about science major such as major in physics or maths or chemistry or computer science)? Or is there no difference?
If there is a difference between the word track and concentration, then is it possible to have both track and concentration offered within a certain major or it is uncommon?
If a department offers tracks/and or concentrations, is it possible for a student to graduate just with the major without any tracks or concentration?

'When I use a word,' Humpty Dumpty said, in rather a scornful tone,
  'it means just what I choose it to mean — neither more nor less.'

  'The question is,' said Alice, 'whether you can make words mean so
  many different things.'

  'The question is,' said Humpty Dumpty, 'which is to be master — that's
  all.'

  -Through the Looking Glass

"We don't have majors, you see..."

First, some institutions don't have "majors", they have "concentrations". This doesn't seem to be what you are interested in specifically, but I include it to avoid confusion. And it's also a good example of just how much definitions of these terms can vary between places.

Track

A "track" usually means there are two (or more) relatively independent paths of study within a single program (major), especially when the goal is to be ready for a certain end-goal (such as for a certain profession or field of research). These usually have suggested courses to take in a certain order, and while they may have a common core at the beginning, by later years people on different tracks will likely have completely different courses to satisfy their graduation requirements.

A very common use of track is to cater to those who are planning to go on to graduate school vs those who want to go directly into industry, or even to cater to different professional requirements. This is perhaps heavily influenced by many high schools in the US having "college track" and "job track" offerings/programs.

Focus

Similar to a track but with less differentiation between tracks, many institutions will offer a "focus". This usually means that all focus areas have most of the same basic courses and electives, but that just a few select higher-level courses and electives are in a certain direction and have maybe additional lower-level requirements. A Computer Information Systems program might offer a focus for software development vs networking/infrastructure, for instance. Focus options might only differ by 3-4 classes, and often have all other classes in common.

Concentration

A concentration (when it isn't a synonym for a major) is often just a more extensive and directed version of a focus. A concentration at an undergraduate level will usually have 4+ courses to satisfy a specific concentration, and often have additional special requirements. A psychology program might offer a general psychology major and a human services concentration for those who have a particular interest in being a clinician, for instance. Using my example programs, a concentration might have preset options for core classes (a choice to take a class in personality vs abnormal psychology is made for you if you want to concentrate in human services), electives are replaced with required classes or must be chosen from a restricted list, and some have special requirements for a final course or internship/residence experience.

So just at my one present institution the words concentration, track, and focus are all used and they all mean different (yet relatively consistent) things. Other colleges in the US often use similar definitions, but the range on this is pretty wide; as I pointed out above, some colleges use completely different meanings for these terms.

Minor Details

I've heard some programs even replace the idea of a "focus" or "concentration" with having a minor program to be chosen, for instance. As a small taste of diversity even within a mid-size institution, over in our History department they offer a minor in Peace Studies, yet its requirements are not very different than a "concentration" offered in our Psychology department.

Typical Physicists

This is to say nothing of our Physics department, which offers no less than five versions of a bachelor's degree - plus a pre-engineering two-year option and a tight relationship to Astronomy - and they don't call them a track, concentration, focus, or minor: it's an "emphasis"!

YMMV

My list here highlights meanings and differences within just a single mid-sized institution, and I've pointed out at least one place where the words mean something completely different, and shown a small taste of variation between programs.

For any specific case of actually deciding what your department would offer, I'd suggest looking up a few hand-fulls of 'competing' departments from a variety of US institutions and comparing how they handle the officially listed tracks and meanings - I suspect they will be all over the place, but I think this general idea will be a common theme. It might also be wise to compare your department to others within your specific institution, under the assumption that there will be more interaction within campus than between far-flung US campuses (though your recruitment/admissions office might not agree with that).

If nothing else it will 'feel' more scientific and professional than handing out darts at a faculty meeting (and perhaps less dangerous).


Submitting a paper to a new journal with responses for the rejection to the first journal I submitted my paper in IEEE Transcations of XXX and got a rejection. But the comments were really helpful and has helped me a lot in improving the paper. But, unfortunately, I cannot resubmit that paper to this same journal again and now I am looking for another journal.

I am writing a proper response again every comment and thinking to submit the response letter as part of the submission to the new journal. The basic idea is to let the reviewers know that this paper has been reviewed (by reviewers of another journal) and improvements has been made. Will it somehow improve the chances of acceptance. (as I am in the final stages of my PhD now)

What does the community say?

I wouldn't do that, actually. Use the comments of the reviewers of the first journal to improve the paper as usual. Simply submit the revised paper to the other journal.

It is actually better that they look at it with a fresh viewpoint, rather than having their view possibly clouded by the opinions of others. Let your paper stand on its own.

You will get additional comments, of course. Hopefully they will also help you improve it further.


Acknowledging a single funding source: do I say "partially supported"? I wrote my first academic paper recently (it is in math). I need to put a footnote crediting the NSF for funding. I have noticed that papers almost always say "Partially supported by [grant]". I got all of my funding from one grant. Should I still say partially supported? If so, what is the reason for this?

The NSF requires the following text (or its equivalent) in publications from work funded by their grants:

  "This material is based upon work supported by the National Science Foundation under Grant No. (grantee must enter NSF grant number)."

No need to quantify the level of support.


Are there any measures to ensure "academic honesty"? I have been reading some reflections on research and academia lately, and it has gotten me to think more critically towards what we do, and what the life we are pursuing has in store for us.

Some of you might remember another recent question of mine, where I was inquiring about the right way to set up projects based on an open-letter I read  about how academia is not what it claims to be. Now I have stumbled upon this blog entry which focuses on the shortcomings of the single-blind peer review process overwhelmingly used in biomedical research publication.

Now it all brings me back to a disturbing idea that I had some time ago; that the quality of the research and the truth to all we do is essentially hanging on a rather fragile virtue, what one could call "academic honesty". We count on the reviewers and editors objectivity, we count on publishers and researchers naive and good intentions with their work, we count on people not putting their personal benefits before that of the society.

As anyone out on the streets will tell you, we do not live in an ideal world and [call me a pessimist if you will] thus I don't believe in the inherent good of the people (at least I do not rely or count on it). I don't see how academics should be exempt from a degeneration in the society that affects everyone else.

That brings me to my question; what measures exist to ensure this "academic honesty" we seem to rely so heavily on? How do we know/ensure:

that the reviewers do not lose their objectivity, for instance when looking at a manuscript of a competitor
that there's no collusion between high-profile PIs and editors of "high-impact" journals?
that academics (at varying stages of their career) do not consider/prioritize "pushing up" the numbers (e.g. "h-index" or "impact factor" etc) when they set out with their research projects?
that grants/prizes/titles are actually given to the better projects/people from the perspective of the greater good, and not based on how well-connected the applicants are? (after all such committees need to have or be composed of other researchers, who else is going to be able to judge the impact and importance of cutting edge research than other researchers?)

I realize that it's a broad question, but I have tried to give a thorough background story to give you an idea about how I got to this idea. Likewise I tried to narrow my concern to one over-arching question (rather than to seek discussion), with a couple of example follow-up questions to make my point clear. I can ask them separately if-need-be, but I think they sit better together, as is.

Let me throw in a few points in addition to @Peter Janssons great answer:

There are "tools" that help with some of your concerns

  that the reviewers do not lose their objectivity, for instance when looking at a manuscript of a competitor

For one thing, most journals I know not only ask for suggested reviewers, but you can also ask that particular persons are not asked to review your paper.
The journals I know have at least 2, usually 3 reviews. So a firm "reject" means that several reviewers did agree that the paper is bad. While one may have a biased opinion, with 3 rejects it is maybe time to stop and think whether the paper really is good or not.
Bias in peer-review is one thing, but variance is another. And, from my experience, variance is high. IIRC there are studies about marks on texts by different school teachers which were found to vary between good and barely passed for one and the same text. My guess is that peer review is similar.
Personally, I'd prefer if peer-reviews were done openly (both sides named, some journals do, though none in my field) as opposed to one side more-or-less blind.

  that grants/prizes/titles are actually given to the better projects/people from the perspective of the greater good, and not based on how well-connected the applicants are? (after all such committees need to have or be composed of other researchers, who else is going to be able to judge the impact and importance of cutting edge research than other researchers?)

I think this is fundamentally impossible, because that would imply that it is possible to know which project will be a good project beforehand*. This may be possible for very applied projects, but those would typically be industry projects, not basic research.
The "interesting" projects always imply a risk that the thing doesn't work out, no solution is found. Otherwise no research would be needed on the topic.

Sometimes, the huge importance of projects is clear only years (or even decades) after they are finished.

* On the other hand, I think it is possible to find out in advance that a project is poorly designed, so it should not be funded.

  that there's no collusion between high-profile PIs and editors of "high-impact" journals?

Of course that can happen. Corruption exists, and I don't think science is fundamentally different from other fields of human professions.
(see below for my thoughts on how to deal with that)

  that academics (at varying stages of their career) do not consider/prioritize "pushing up" the numbers (e.g. "h-index" or "impact factor" etc) when they set out with their research projects?

In a way we cannot, and IMHO it has to be expected that scientists are intellectually quite able to understand how to optimize a given measure. Thus, the assumption that e.g. bibliometric measures do not influence the measured system will not hold.
Whether they actually do it, is another question.
There is one very important point: the papers are not kept secretly, you can read them. As a scientist, you can, should and do judge the quality of the papers. IMHO peer review does not allow you to switch off your brain when reading paper - I think peer review is meant to be a sieve that gets the "failed" papers out of the system - while what I want to read are not "barely passed" but "excellent" papers. However, there is a tradeoff, and if you push up the rigour of peer review you'll inevitably throw out also good papers, or papers whose importance will become apparent only later on. That is, too strict peer-review may pose a restriction on the publishing system that disfavors really new ideas, and allows to pass only predictable results.
However, you won't be able to help realizing who publishes by salami-slicing and who publishes lots of studies with e.g. very low numbers of patients, poorly designed experiments, and OTOH, which groups take the effort to get meaningful numbers of patients, publish on relevant controls, do their homework validating their findings and so on.
Also the authors are of a paper are named clearly. And taking together your judgemen of the quality of papers and maybe some citation network tool, you can get an idea  who optimizes e.g. citations.
Attending conferences and workshops and talking to people you'll get to know people personally so you can judge their character. In addition, you'll hear a fair amount not only of "rumours" and "stories" which also tell about people.

All in all, I think this works as "real life" does: how do you know a company is honest you consider dealing with? You put some advance trust in them, and you use your judgment, including what you hear by your peers about them: e.g. were they recommended by someone you consider reliable.


Found error in published article where to submit a correspondence? I have found an error in a published article. The error lies within the method section.

I would like then to write a correspondence to let people know about this issue and to explain what could have been done correctly.

I tried to look into the journal webpage but it seems they do not publish correspondences. Where can I then submit my ‘correction’?

My field is applied physical science.

Thanks

If the error is simply a typo, or two, or a wrong sub-result which does not fully invalidate the findings, don't bother: the chances of publishing are almost zero. (E.g., in mathematics, around 80% of results are expected to be wrong in the strict sense of the word, e.g., not checking whether your claim "for all n≥0 ..." really includes the case n=0. I don't know about the applied physics, though.)

Thus, let's now assume you have found a serious error. A typical procedure is submitting a corrigendum. Corrigenda get seldom published, though. Read the submission guidelines of the journal in question, and, if it doesn't help, ask the editor.

Usually, the chances of getting such a corrigendum published oneself are slim  unless one collaborates with the original authors ‒ otherwise, they would be asked to evaluate the corrigendum.

An aside: If methods mean methodology (rather than, say, algorithms), my personal approach to refereeing the paper would be checking whether the new authors

justify why the published part is wrong as it is,
improve the wrong part,
and re-do it completely, i.e., improve the methodology and apply it.


Stating a post doc research fellowship that I declined on my CV due to personal reasons? So, I have recently finished my PhD in one of the "pure" sciences, in the UK. I have applied and been successful in obtaining a prestigious and rather lucrative research fellowship for a post doc position at a university in a country abroad (different to UK).

However, I have declined this award due to personal reasons, as I decided that a short-term post doc abroad without further career certainly is not something I want, due to my financial and family situation. Instead, I decided to either :

a) apply for a permanent position in the industry

b) apply for permanent teaching / lectureship positions in my current county of residence at "low" ranking universities / or so-called community colleges that emphasise teaching over research. (This is because I have virtually no chance of getting a permanent position without doing a post doc at a high quality research-orientated department.)

c) Apply only for post docs at "good" departments but only in the location I live now (since this way I will be able to save most of my salary, since I live at home with my parents), and transition to industry at a later date.

In either case, is it a good idea to state the fellowship that I have won, but declined, on either my CV and/or cover letter?

I don't think there is a clear answer to this that would apply in all situations. There are both positive and negative aspects to it. Yes, you were awarded a nice position. Yes, you backed out. For some situations one or the other of these might be more important.

I'd suggest that for purposes of applying to a position you evaluate the situation and send a CV tailored to their needs. It may, in general, be safer to omit it if you think it might raise any questions. You can always bring it up in an interview later if you think it might be worth it.

But most employers will want some assurance that backing out isn't a habit. So, for a general CV visible to the masses, maybe a bit better to omit it.


How far can research deviate from the original research proposal? During the course of a research project, one may have new, more promising, ideas that were not foreseen and thus not covered in the original research proposal. What should one do in this case? Is it all right to work on the new idea under the original proposal? Or should one stick to the lines suggested in the original proposal and perhaps submit another proposal for the new idea although this means that one has to wait before he can work on the new idea?

There's two opposing forces here:

You're probably not doing research if you can say exactly what you are going to do beforehand in the research proposal. At the heart of research is exploration. Hence it is expected that you demonstrate some agency and adapt the research as you explore the topic more.
On the other hand, the people who fund you are funding you to work in the area of the proposal. Switching to a completely disconnected topic on a whim is (generally) not an option.

  How far can research deviate from the original research proposal?

This is difficult to give a concrete answer to and it will differ from fund to fund. Most generally, if you can show the funding body a path from what you proposed to what you ended up doing (i.e., you can show that your intent was to follow the proposal, but you discovered new evidence that a better alternative was possible and you followed that alternative instead), then I think you're on safe ground.

In other cases, it will depend entirely on what your funding body is looking for and how they justify their funds to their bosses. You will have to try understand what the objectives of the funders are: is it publications, creation of a product, teaching and dissemination, contributing towards some high-level national/EU directive, etc.? Will your new direction likewise satisfy those objectives under what was originally agreed in the proposal? These are important questions. (Even if you stuck steadfastly to the topic proposed, groking the motives of your funders and what they will look for during reviews is vital for success. If you understand these motives well enough, then as a side result, you'll have the answer as to how much deviation is acceptable or even desirable.)


How can a distance education student get a copy of the lecture notes? I am a distance education student at a Parisian university, and I am currently preparing for the exam in a research-level mathematics course.

While on-campus students have attended the lectures and presentations of sample problem solutions, distance education students only get incomplete lecture notes in pdf format, sample problems without solutions, and a list of recommended textbooks.

I think I was quite successful studying about 85% of the course this way, but the last one or two lectures and sample problem solutions cover some very advanced material, which is not adequately addressed by the recommended textbooks. I also could not find this material is a sufficiently concentrated form in research articles, and I estimate that it may take thorough reading and understanding of no less than 50 articles and maybe 3 months to properly figure this out by myself.

One of the professors recommended to me that I get a copy of the lecture notes and sample problem solutions from a student that attended the course in person, but when I requested a few email addresses from the secretary, she said she is not authorized to divulge that information. I asked the other professor of this course, but got no reply.
I can't go to a course lecture to locate such students, because the last lecture was some time ago.

I would like some advice on what else to try to obtain the lecture notes.

Some comments and the already given answer give advices that can be counter-productive in France. You mention that this is about a research level course so I understand that this is a "Master 2 recherche" course.

It is unlikely, for privacy reasons, that someone will give you email addresses of other students. My advice is to ask the professor to forward to a few targeted students your request.

Going to the department chair/dean will probably be useless. If you really want to go up the ladder, ask to the person in charge of the master 2. But it will probably be useless too since in the French system professors are free to do as they want for their lectures. For those surprised by that last sentence, keep in mind that having lecture notes in pdf and a list of recommended textbooks is something that you don't have in all lectures in France.


Should a PhD student be credited in supervisor’s article that is based on a book chapter by both? Jane is doing a PhD and is supervised by Professor Mary. Mary asked Jane to put together a review article for a book based on a draft chapter from Jane’s thesis with additional suggestions from Mary. The book article was submitted with the authors listed as Jane and Mary (corresponding author). I am unsure whether this has actually been published, though it was submitted well before the now-published review by Mary.

Sometime later, Mary submitted a broader review article online which used large chunks of text and figures from the book article which were directly written/generated by Jane. Whole paragraphs were copied verbatim from the first article to Mary’s article, and many more paragraphs were slightly rewritten but contained exactly the same references and phrases from the first article. Mary’s paper did not cite the book review. Mary was listed as the sole author. Jane was not informed this review was being written, and was not asked for permission to include her figures or content from the book article, which were originally written by her for her thesis.

Did Jane ‘hand over’ the rights to her written material to Mary by agreeing to submit the book article under both of their names?
Should Mary have credited Jane in the article as a second author because she used exact sentences from the book article which were written by Jane?
Will Jane still be able to use these (her) phrases and figures in her thesis despite not being credited on Mary’s online article?

Here are the relevant facts:

Copyright

The copyright of everything you create belongs to you by default (in any reasonable legislation).
In some legislations, your copyright or parts thereof may automatically be transferred to your employer upon creation.
Apart from that, any sort of copyright transfer can usually only happen due to a contract you signed, e.g., with your university, supervisor, or a publisher.
In the latter case, your co-authors (i.e., your supervisor) usually do not gain additional rights.
Publishing content to which you hold the copyright without your permission constitutes a copyright infringement.
The crucial question in case of a lawsuit will likely be what you can prove that you created.

Academic Ethics

If you creatively contributed to an article, which particularly includes conceptualising figures and writing paragraphs for a review articles, you have to be made a co-author according to academic authorship standards.
Even if Mary were the sole author of both articles involved, re-using material in the way you describe may constitute self-plagiarism.
This mostly depends on the publisher’s requirements regarding the absence of prior publication and the status of book articles in your field.
Submitting any content you created for publication without citation or similar considers a breach of academic ethics even if you are listed as an author or do not hold the copyright.

What you should do

Secure all evidence of which content you created.
Check your contracts and what has been published.
Talk to your supervisor.


Is grad school typically time-intensive? I would like to know what is graduate school supposed to be like? I started grad school for mathematics 2 months ago and I find myself studying all the time with no time for anything else (except activities of daily living). Is this typical?

Some notable advantages that I have:

I commute from school to home.
I am a U.S. citizen and obviously did not have to venture outside of home for any of my schooling.

Graduate school is an experience and like any other experience, it differs for different people.

You may or may not let your work overwhelm you. That is entirely your choice unless you have to catch up with your cohort. Time management is one of the most important skills to learn in graduate school and as I understand, it carries over to real life significantly later on.

Therefore, specifically in response to your question, your current experience is typical for certain graduate students but not all graduate students.


Should response to an email of accepted article with some comments I received an email from one journal telling me that my paper will be accepted if I consider all the comments from the reviewer. They did not ask me to write a response to the reviewer as the comments are very minor as they said.
Should I respond to them saying that I am working on the comments?
Kind regards,

It is probably worth doing that, unless your revised paper can be re-submitted very soon. Don't leave them in suspense. You might even want to give an approximate date by which you will have the revisions ready.


How to use competitions to encourage students to work harder and study more In order to encourage and motivate students to work harder and study more, it seems the teacher can use various competitions in class or after class. But on the other hand, competitions could cause jealousy and other destructive emotions among students and therefore affect the performance of some students adversely. Due to my doubts and my lack of experience, I haven't used competitions in my classes as a means of motivating students yet. But I would like to know if there is an experienced and useful method to do that. So my questions are:

Have you ever used competitions in your classes? What are the pros and cons of students compete in the class for higher grades? Which points should I consider before encouraging students to compete with each other?

I often have competitions in class. I try to use them primarily for motivation, not assessment.

Let me give an example: I was teaching an image processing class and we had some images of x-rays of "old master" canvas paintings. The goal was to create an algorithm that could count the density of the thread weave patterns. The quality of the answers could be assessed by comparing the algorithmic answers to manual counts, and I had about 200 locations where I knew the answer. I gave them 100 to train the algorithms. After about two weeks, there were 25 different algorithms submitted (most people worked in pairs) and then I ran the submitted codes on the 100 "unknown" locations.

I called it the "2010 Thread Counting Olympics" and made a big deal about giving out "medals". I created several different ways of measuring the quality of the algorithms: closest in least squares error, number of answers within +/-1 mm per thread, number within +/-2 mm per thread, closest in absolute value of error, closest on the canvases by Van Gogh and closest on the canvases by Vermeer. Then there were bronze, silver, gold, and titanium medals in each category. As I presented the results to the class, I described the various approaches and pitfalls of each of the algorithms, and often asked for clarifications and comments by the authors of the algorithms. By the end of the competition, well over half of the students had won "prizes"... plus they had the recognition of their peers.

The amount of effort that the students put into this project and into the class were amazing, and I think the "competition" aspect was a prime motivating factor.


When does "copying" a math diagram become plagiarism? If you copy paste a diagram from a paper/book onto your own work, without permission or attribution, that's plagiarism.
What happens if you see a beautiful diagram about what you want to explain and you replicate it identically without copy pasting?
What if you don't copy it identically but it's still similar (say the colors are different, and the vertices/edges/boxes) have slightly different shapes? For example the original used a 3D blob to explain what a local chart is, and your diagram uses an ellipsoid.
What if you transfer mediums? For example a chalkboard diagram turned into a metafont diagram?
Since there are only so many ways to convey certain mathematical ideas, such as what a bivector is, or how to compute a spline. When do you know where your source of inspiration is too close to your own work that you walked over into plagiarism?

Paraphrasing Simon Peyton Jones here, credit is like love. Giving it to more people does not diminish it or you.
Even if you recreated an image yourself, there’s literally no reason to not attribute your inspiration for it (apart from your own ego).
The threshold for plagiarism is vague at times, but if you saw someone’s work, liked it and built upon it, give them credit.


Are scientifically detached professors referred to as ‘clinical’? I have come across this term fairly often, where full/associate/assistant professors are referred to by the term ‘clinical’. Given that their departments had nothing to do with medicine, I thought the term referred to the second meaning of clinical:

  scientifically detached; strictly objective

Is this interpretation correct? If yes, isn’t such a branding offensive?

There can be clinical professors in fields other than medicine, though they may be labeled something else.  The definition of a "clinical professor" is not limited to medicine:

  "The prefix Clinical identifies appointments that primarily provide practical instruction and application of practical knowledge. On the Medical Campus, the title describes faculty whose primary activity is limited to clinical or public health practice and associated teaching. The duties, terms of appointment, and salaries (if any) of such persons are specified in the letter of appointment. In general, the applicable rank and any subsequent promotions should be determined by the relevant academic achievements, professional accomplishments, and demonstrated effectiveness of the appointee."  (Boston University faculty handbook)

So, though I don't know much about engineering, I imagine that a professional from an engineering firm that specializes in a particular process could be hired as a clinical professor.  S/he would teach about the particular niche they occupy in the industry.


Industrial Engineering is to be better with computer engineering and mathematics department or mechanical engineerring? Assume in a university for some organizational considerations, industrial engineering must be either in a department with computer engineering and mathematics groups or in another department with mechanical engineering.

My question is:

Which choice is better to have a more productive university in terms of research and teaching?

Caveat:IANAIE and this answer might ignore aspects of IE in Europe.

This is an interesting question, but industrial engineering gets bunched up with mechanical engineering more often than not, and IMO that is more appropriate.

The reasons are as follows:

(1) The one part of IE that seems like a better fit to Math is Operations Research / Optimization, but in reality that fit is not a very good one.
OR researchers mostly publish in applied math journals (SIAM ***) which is not (ok, this is controversial) what gets actual mathematicians excited.
I'd say it bears the same relation to mainstream math as statistics: Closely related but a discipline which, having been motivated by applications, has taken a very different path. Also, OR folk typically do not call themselves mathematicians.

(2) Ok, even if you somehow shoehorn the OR guys into Math or CS, the rest of IE just does not fit into CS or math or even any other science department.

Manufacturing, for instance, is a heavily applied field and often considered an area of mechanical engineering. Many Mechanical Engineering departments have their own manufacturing groups. ME and IE are linked like conjoined twins, with people moving from one to the other at all stages (as faculty, as postdocs, as grad students). How would justify moving manufacturing to Math?

(3) Other areas of IE, like production engineering and human factors / ergonomics are even more distant from Math and CS, if that is possible.

(4) Moreover, you'll notice that students need a sound mechanical engineering background to succeed in most areas of IE: A pure math or CS background is not likely to be as helpful. (They're better off knowing machine design, solid mechanics and heat transfer than measure theory or complexity theory, at least in the beginning LOL).
In many IE programs, students are taught courses in Optimization Techniques, Linear and Dynamic Programming and so on. In grad school they might even prefer the more rigorous versions of these courses.

So in conclusion I'd say IE belongs in engineering, as a separate department if possible, but with Mechanical engineering if not.


reference letter from current line manager? I am currently a lecturer at a UK university, and I got an oral offer from another university. I was called by their HR today saying that their official is condition on satisfactory reference checking with my current line manager, who is the HoD of my current department. In my case I do not know my HoD is willing to provide a reference letter, as I am pretty sure that he will not be happy knowing I want to leave.

I am wondering if this (requiring reference from current line manager) is a common practices for UK universities? If there is any alternative solution to it? Thanks for your suggestions in advance.

It is common practice in UK universities. It would also be considered bad behaviour if your HoD was unwilling to provide a reference, or if he wrote a bad letter out of spite or revenge or similar. Of course, there are people who take it personally and are unpleasant when people leave so there's no guarantee he would be reasonable.

You should be prepared to have a discussion about why you want to change universities. Is it a promotion? Or is there a research group that is closer to your field? Presumably you applied for the job for some reason. You haven't said why you think he may not be happy. If you have been there only a short time, there might be some bad feeling. But people move all the time for all sorts of reasons.


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.


Are there any available studies on the effectiveness of "learning by teaching"? There is a study which claims that "learning by teaching" has a 90% retention rate. However, the study is no longer available and it is not clear what kind of research was actually done to support that claim. The legitimacy of that particular study is the subject of a related question on Skeptics.

Are there other studies that are available, proving or disproving that "learning by teaching" is more efficient than other learning methods?

According to one source, a man named Edgar Dale developed that retention rate pyramid.  Edgar Dale had been both a teacher, and a school Superintendent.

The wikipedia article makes an interesting statement regarding this:

  However, Dale included no numbers and did not base his cone on
  scientific research, and he also warned readers not to take the cone
  too seriously. The numbers may have originated as early as the 1940s,
  when a scholar at the University of Texas at Austin created visual
  aids for the military.

Wikipedia points to another article written by a Dr. Thalheimer, whose PhD was in Human Learning and Cognition, which is possibly a better resource.  He makes this statement in his introduction:

  People do NOT remember 10% of what they read, 20% of what they see,
  30% of what they hear, etc. That information, and similar
  pronouncements are fraudulent. Moreover, general statements on the
  effectiveness of learning methods are not credible---learning results
  depend on too many variables to enable such precision. Unfortunately,
  this bogus information has been floating around our field for decades,
  crafted by many different authors and presented in many different
  configurations, including bastardizations of Dale's Cone.

Dr. Thalheimer goes further:

  The bogus percentages were first published by an employee of Mobil Oil
  Company in 1967, writing in the magazine Film and Audio-Visual
  Communications. D. G. Treichler didn’t cite any research, but our
  field has unfortunately accepted his/her percentages ever since. NTL
  Institute still claims that they did the research that derived the
  numbers. See my response to NTL.

  Michael Molenda, a professor at Indiana University, is currently
  working to track down the origination of the bogus numbers. His
  efforts have uncovered some evidence that the numbers may have been
  developed as early as the 1940's by Paul John Phillips who worked at
  University of Texas at Austin and who developed training classes for
  the petroleum industry.

That's interesting... does marketing voodoo usually stick around in the public mind longer than original research?  Anyways, he re-emphasizes the importance of listing citations and the importance of understanding where research originally comes from, up to and including context.  There were two guilty parties, according Dr. Thalheimer; of course, the original people who generated the tables, but also the folks who disseminated the research without checking the citations.

Thalheimer goes on to suggest that the information floating around in his industry can not be trusted.

  It tells us that even our most reputable people and organizations may
  require the Wizard-of-Oz treatment---we may need to look behind the
  curtain to verify their claims.

So, how does one answer your question?  Well, the US News rankings show Stanford as being the top University for psychology, at the moment.  So, I'll take that at face value; because I don't have better information to go on, and assume that there are some decent researchers on cognition in Stanford.  Out of the researchers who study cognition, which one's seems like they might be doing research on human learning?  After I find one, I might be able to identify some of the journals in the field.  They might even be some of the "top" journals in the field.

Part of the reason why this trick works, is that professors and fledgling professors usually keep a curriculum vitae, or CV.  And often, listed on their CV is a set of references to papers that they have written in the past.  Some are even so kind as to showcase some of the papers that they believe to be part of their best work to date.  In some cases, this can act as a kind of roadmap to show you how to become a professor.

So this procedure pulls up a list of possible resources for journals that might have articles on that topic:

Cognition
Developmental Science
Developmental Psychology
Perspectives in Psychological Science

Here are two possible resources:

Frank, M. C., Tenenbaum, J. B., & Gibson, E. (2013). Learning and long-term retention of large-scale artificial languages. PLoS ONE, 8, e52500.
Shafto, P., Goodman, N., & Frank, M. C. (2012). Learning from others: The consequences of psychological reasoning for human learning. Perspectives in Psychological Science, 7, 341–351.

That might be enough of a seed to begin to answer your question.  Let's begin by trying to read Shafto et al's paper in the journal Perspectives in Psychological Science.  The official version is behind a paywall, but a version of the paper is freely available from Goodman's web page at Stanford.

In the abstract, Shafto et al says:

  From early childhood, human beings learn not only from collections of facts
  about the world, but also in social contexts: from observation of other people, from communication, and from explicit teaching.

Beyond the abstract, in the 'Learning from others: The consequences of psychological reasoning for human learning', Shafto et al states:

  Children are often compared to scientists, but even a perfect scientist,
  using experiments alone, would struggle to rediscover all of human knowledge in  the span of one lifetime. How then are children able to acquire a good fraction  of this knowledge in just a few years? The answer must be that children do not  rediscover everything—they use their ability to reason
  intuitively about other people to learn what others already know.

Below figure 1, Shafto et al make the statement:

  Research on human learning paints a very different picture of how datapoints are
  selected.  A wide variety of approaches have pointed to people and their intentions, as an important factor in learning, highlighting that data are
  chosen rather than random (Bruner, 1966; Vygotsky, 1978) and that observed data are
  often the consequence of goal-directed actions (Bandura, Ross, & Ross, 1961; Gergely & Csibra, 2003; Meltzoff & Moore, 1977) or intentional communication/teaching (Coady, 1992; Csibra & Gergely, 2009; Harris, 2002; Tomasello, 1999; Tomasello, Carpenter, Call, Behne, & Moll, 2005).

So what can we gather from this?  Within the field of psychology/cognition, there is discussion in the literature to support the possibility that people do, in fact, attempt to describe the process of learning by teaching.  But the focus of Shafto et al's paper is not on trying to find the learning retention rates for different types of learning.  In fact, nowhere in the paper does it even mention the term 'retention'.  The focus of their paper, as described in the abstract, is rather to develop a formal framework for how a learner might observe someone's actions and infer from those how much that person knows about the world.

The focus of this paper could potentially be useful in trying to develop a learning model for an artificial intelligence.

In the conclusion, the authors make an interesting statement:

  Our approach suggests that intuitive psychological reasoning potentially provides a very strong lever by which learners may capitalize on others’ knowledge to learn about the world (see also Coady, 1992; Csibra & Gergely, 2009; Harris, 2002; Tomasello et al., 2005). The key difference from previous formal approaches is how one views other people. If other people are viewed as random or even malicious in choosing their actions, then learning will likely be very
  difficult. However, if people are viewed as approximately rational,
  goal-directed agents, or as knowledgeable and helpful teachers, then the learning problem becomes much more tractable.

This statement appears to mean that the ability to learn by observing an observee's actions depends on the observer's assumed framework.  If the observer assumes that the person whom they are observing is acting randomly, or perhaps that they are malicious in their actions; then it's more difficult to create a model to represent who they are observing.  It is more difficult to learn.  I'm not convinced that my interpretation of this statement is correct, given the context.

This paper also makes some references to studies done in the past.  We could follow up by reading some of these as well.  You may find this necessary, as this paper doesn't address your question directly.


Are tuition subsidies taxables for research staff? I have two Bachelor degrees and an MMath, not looking for any more degrees at this time, but I might be interested in taking some Japanese and Chinese language courses.

I'm working as a research programmer for a university in the US (IU), and they offer the option of

  a subsidy toward the tuition costs, under Section 117 of the Internal Revenue Code.

What does this mean for me?

Would such subsidy be included in my income, and would I have to cover for the taxes as if I have received all such subsidies as real money in income?
What happens to the in-state / out-of-state tuition differential?  I've moved from a different state for this job mid-summer, and might start taking courses right away in autumn.

I am not a Lawyer or Accountant, and if you really worry, you should ask one of those or at the very least talk to human resources at your university.

But, based on my reading of the relevant law, part (d) [usually referred to, I guess, as Section 117-4] specifically states that if you are an employee of a university, then tuition reduction for you to take classes at said university should not count toward your gross income when calculating taxes.

The US code does not distinguish between in-state / out-of-state tuition.

Caveat: your local state laws may have different interpretation of "gross income".


Why do Swedish postdoc ads typically have a requirement that PhD date must not be more than 5 years ago? Ads for postdocs in Sweden appear to always have a rule like PhD degree obtained preferable not longer than three-five years ago:

Example 1, 2.  I've seen it many times in the past but job opening links are particularly temporary.

Is this to protect people from becoming career postdocs?  Is it a requirement from a funding agency?  Or is it just a habit?

I don't know about Sweden, but in the US there seems to be increasing mood in Universities to end, or at least not contribute to, the "perpetual postdoc" cycle.  I don't know that there is real pressure from the funding sources, so much as a tough love from community leaders to stop taking advantage of a relatively cheap labor source by dangling prospects of academic success over them.

For example, our policy is to keep the total postdoc tenure to 5 years.  If you come in having done a 3-year postdoc, that leaves you with two more years here.  After this time limit is reached, the lab has to find means to fund you as an employee on the scientific staff if they want to keep you around.

Not all faculty love this, and some point out that by nature of some fields, postdocs tend to be longer.  For example, if you're recording from single neurons and need a large data set, this can take forever.  Despite such arguments, I haven't heard of any cases where the time limit has been waived.

The postdocs are not necessarily hung out to dry.  We have a number of programs designed to help them find satisfying employment.


Taking individual subjects not related to my career I would like to ask for advice in this particular situation of mine:
I am a Mexican medical doctor, and I am applying for a Master Degree in Biomedical Engineering at a german university. The program offers bridging subjects for students from non-engineering students in the first semester, however, when I e-mailed them about more in-depth information to prepare a more robust application, they told me that mathematics, physics and chemistry subjects are compulsory requisites for this program.

At medical school, I took chemistry and statistics, which may suffice the chemistry and maybe maths with a little bit of imagination, but the physics one eludes me. They specifically required for it to be taught at university so I am struggling a little bit.
As a solution I have tough I may ask for a physics course at my home institution and maybe they will allow me to take it and it may be shown in my transcript (even though I have already finished my career). I don't even know if it is possible to this yet.

I have studied maths and computer science on my own and I have held a chief developer position at a software company for two years now, however, no university is backing up my knowledge on math nor computer science. This at no point does anything for the physics requirement though.

Can anybody offer advice on how could I overcome this complication?

As a faculty member of a German university that also offers a Biomedical Engineering program I can confirm that the admission rules can be quite strict.
However, in almost every study regulation is a clause that the program's examination board (Prüfungsausschuss) can overrule any formal requirement.
The keyword here is "equivalence". E.g., being a software developer can compensate missing software classes, etc. Additional certificates from courses at your home university (as you suggest), even if you take them outside a regular program, can help as well.

So my advice is to bypass the administration and contact directly the head of the program's examination board, or (if such person exists at your target university) the head of the study program (Studiengangsverantwortlicher, sometimes, s/he is the same as the study dean of the program, but not always) and ask what would be needed to prove equivalence.


Should I list declined fellowships/grants on my CV? This question is similar to the following question:

Is it a good or bad idea to list declined fellowships (for a PhD program) on one's curriculum vitae?

Whereas that question focuses on fellowships for a grad program, I am asking about including other competitive fellowships and/or grants — those awarded after acceptance to a PhD program — in the CV.

Examples of these awards could include:

Travel grants
Research fellowships (e.g. NESSF, NSF, Early Career)
Research grants

Many will wonder why somebody might decline these awards after being nominated or applying for them. Possibilities could include schedule conflicts, conflicts of interest, and more. (This question is agnostic to the reasons for declining the award, though a follow-up question could be to ask when one should explain why the award was declined on one's CV....)

This depends largely on (like what Buffy commented) the circumstances and the grant. In my opinion, the circumstances may include where you are in your career. I see graduate students state declined fellowships on their CV relatively often, but I rarely see it on the CVs of professors who usually have enough (and usually more impressive) things on their CV.

But in terms of the grants, consider this example of the two of the most prestigious general graduate fellowships: the NSF GRP and the Ford Fellowship.
Both offer honorable mentions. It's pretty common to see graduate students state on their CVs that they got an honorable mention. However, suppose that a student received both the NSF GRP and Ford Fellowship in the same year. Because the Ford Fellowship prohibits one from having additional fellowships simultaneously, the student decides to decline the Ford Fellowship and accept the NSF GRP and reap the benefits of a much higher annual stipend as well. Should this student not state on their CV that they were accepted for the Ford Fellowship? What about a student who got the NSF GRP but only an honorable mention for the Ford Fellowship? Should this student be able to list both awards on their CV? It doesn't make sense (in my opinion) that the prior student should not be able to list the declined Ford Fellowship while the latter student should be able to list an honorable mention for the Ford Fellowship when an acceptance is clearly better than an honorable mention (discounting all the minority statuses that Ford takes into consideration).

However, that example was for two very prestigious fellowships. For minor grants/awards like travel grants, listing declined grants can be seen as 'padding the CV' since many travel grants/awards can be based on lottery rather than merit.

To sum it up, if the fellowship or grant is very prestigious, I see no reason as to why you shouldn't have a declined offer on your CV. However, if the fellowship or grant is minor or small, and your CV is already riddled with other awards or grants, then consider how it may be padding your CV with relatively trivial things that distract the reader from the more important fellowships/awards/grants. It's similar to why graduate students should consider deleting their undergraduate research symposium poster presentations from their CV as they progress in their academic career...


Tense for literature survey I am writing a literature survey for papers from 2000 to 2017.
Should I use a present tense or past tense when I am describing methods that were used in those papers?

Either past or present tense is reasonable for a literature survey. You could argue for the past tense since the work was already completed, or use the present tense because the papers currently exist and describe something that can be found now.

The main issue is to be consistent in your usage throughout the review.


Is a paper with no citations likely to contribute to citation metrics in a way which reduces my job prospects? Last year I did some work to help out my friend and his supervisor on a project that they were working on. I wasn't very involved with the project, but the work that I contributed was important for them to be able to find the main results that they were interested in. I asked at the time if they would they be happy to include me as an author on the paper based on this contribution, and they said they would be happy to do that.
I think it's quite likely that the paper might not get very many citations. The most closely related paper to the one they will publish soon was written by my friend's supervisor, and it has only one citation. It was published in 2015, and I think it's in an area that doesn't have so much research interest in general.
I've been wondering what different people think about whether being an author on this work would look better or worse for me, with respect to future positions in academia. I'm hoping to look for a postdoctoral position in the near future, in a different but related field.
I feel like it might look better: I would have more publications and it's showing more of my skills. I could put it on my CV.
Or it might look worse: I know there are different metrics which take into consideration how many citations papers have, and having a paper with no citations might reduce my score on them.
I'm currently at the end of my PhD and I have 6 publications, one has 4 citations and the rest have between 10 and 25. I think at this point it would be reasonable to ask them to include me only as an acknowledgement on the paper, if I decided that was the best option for me.
Any opinions/perspectives on this appreciated.
I appreciate that it's my choice whether I put the paper on my CV or not, if I choose to stay as an author.
Thanks

No, this is not a problem. Everyone has papers on their CV which have few citations, including older papers. If this were true for all your papers, in particular even all of those which are several years old, this could be an issue - but this does not seem to be a problem at all in your case.  (Note that the distribution of citations vs. papers is somewhat similar for everyone, reflected e.g. in the fact that there is a clear relation between the number of publications and the h-index.)
Moreover, if you really feel later on that a given paper does not represent you well, you can always omit it from your publication record - you are not obliged to list everything you ever published there, in particular if you feel it is not relevant.
So I would go with being a coauthor of the paper, if the others offer coauthorship to you, and you feel it is deserved.

Edit: To follow up on your updated title, a paper with a low number of citations will not have a negative effect on citation metrics: Typical metrics are either the total number of papers, the total number of citations, or (most importantly) the h-index, none of which gets worse if you add little-cited papers.  The only indicator which would be affected is the number of citations per paper, but this is rarely used - and even then, a single little-cited paper will not have a big effect.


Are PhDs from former Warsaw-pact countries recognized in North America? Is someone completes a Ph.D. from a former Warsaw-pact country, would her Ph.D. be recognized in North America as in the same status as a North Americal Ph.D. in case of academia related career?

Yes, of course. Go into any American mathematics department's webpage and odds are that you will find an academic with a PhD from the USSR.
Edit: with regards to "status", it really depends what do you mean by it. Do they have same legal status? Yes. Are they valued the same? Most likely not depending on who makes the evaluation. American public (and surprisingly good portion of academics) seem to value "university rankings" a lot more than other people do. Non-American schools seem to fair much worse on these metrics compared with the American schools. As an example, current times higher education world ranking ranks.

104th University of Arizona
105th University of Bonn
125th University of Göttingen
189th Lomonosov Moscow State University

Now, I have seen much stronger mathematicians with PhDs from the last three compared to the first. I personally would value higher either one of the last three than the first.
P.S: Indian IITs don't make it to first 300. However, they seem to have incredible students. Perhaps because they admit incredible ones. Even than why would, say Harvard, be any different.


What has the effect of publishing salaries been? In the US, many (most?) states have laws which require the publication of full salary details for all employees of state universities.  For example, California has a full online database of all state workers  it seems which includes UC Berkeley amongst others.  Salary details to varying levels of approximation are also available for public university employees in some countries outside the US.  In which countries are academic salaries published? has more details .

What effect on state (or public) universities has this publication of academic salaries had? Specifically,

Have they had to pay more on average in salaries because private sector competitors (including private universities) now know exactly how much to offer someone to entice them?
Have they found it more difficult to recruit people from the private sector (including private universities) who might not want their financial details to be public?
Have there been any other negative or positive side effects?

Have they had to pay more on average in salaries because private sector competitors (including private universities) now know exactly how much to offer someone to entice them?

I've occasionally heard of these lists being used to identify woefully underpaid faculty members who might therefore be disgruntled and easier to recruit.  However, I don't think this has had a substantial effect overall on salaries at public universities.  Most faculty members don't inspire bidding wars between universities, and recruitment is based on many other factors beyond just salary.

For context, note that average salaries vary substantially between universities, and these differences are sometimes pretty widely discussed in the community.  Even in the absence of data on individuals, that's potentially useful information for recruitment.  However, there seems to be no trend towards salaries evening out.  Instead, they tend to end up balanced with factors like desirability of location.

  Have they found it more difficult to recruit people from the private sector (including private universities) who might not want their financial details to be public?

Not to a noticeable extent, at least for ordinary faculty positions.  This could be more of a factor for mid-level administrators, whose salaries might come under greater scrutiny.  (By contrast, the salaries of top administrators are public information for every non-profit university in the U.S., public or private, because they must be reported on IRS Form 990.)

  Have there been any other negative or positive side effects?

Transparency about salaries has a weird mixture of effects.  On the one hand, it makes the overall patterns clearer, and anyone can judge for themselves whether the results are fair.  For example, it's easy to gather data on whether women are being paid less, whether there's salary compression or inversion, whether different people receive comparable salary increases upon achieving tenure, etc.  I don't know of any formal studies (which could be interesting), but there's at least a fairly widespread belief that this transparency helps cut down on abuses.

On the other hand, it can also increase disgruntlement.  The actual salaries are almost guaranteed not to align perfectly with what would seem just to any given person (because of course different people have different visions of what would be appropriate).  I've certainly looked on occasion at salary lists and wondered why on earth X was being paid 15% more than Y, and I once talked with a friend who had discovered that he was Y in such a case.


Is there a term to describe when students are in one classroom for most of the day? When I was in elementary school, I was in a single classroom the entire day. I would have different teachers come in and give classes, but we as students wouldn't change our classroom. When I was in high school, we were in two classrooms, first half and second half of the day.

There seems to be a term for every single possible classroom arrangement, but I haven't found one for this. I've seen it once called "Homeroom," but the Internet seems to disagree (https://en.wikipedia.org/wiki/Homeroom amongst other places). Any suggestions?

Additional context: The company I'm working for is building a school software so terminology is critical when initially setting up courses/classrooms etc. We've spent a ton of time researching terminology, but this one has us completely stuck.

Something close may be a “floating teacher model”.

A room is predominantly occupied by one instructor then another comes in during the primary instructor’s prep period to teach his or her lesson.  There’s no reason one room would be restricted to only two teachers in this practice. “Cart” teachers or “mobile” teachers are also commonly used terms for these roles. While there is research on this practice, I haven’t come across any where all teachers are subject to moving between rooms. That’s not to say a universal term for the structure does not exist.


Quitting a collaboration project without hurting collaborators I am a PhD student collaborating with another PhD student A, under supervision of Prof. B & Prof. C. I am student of Prof. B. Student A is co-advised by Prof. B and Prof. C.

Prof. B chairs the project. I was asked to join this side-project because of my certain experience.

Our work requires knowledge from both A and me. A is doing well in his part. However, the novelty in my part, is problematic (in my view) and hard to produce. To this, not everyone is convinced: Student A thinks I need more tunings; Prof. B is dubious yet believes the novelty; Prof. C agrees with me but with a little suspicion.

I have now enough lab evidence to support my claims (i.e. the failure novelty). And I believe I will convince others at next meeting.

I would like to quit this project, and do not want to waste more time. Student A can still publish his part, just not a "big" paper though. And I will not ask for any credits of course.

The question

How can I, with enough respects, yet properly quit the project without hurting feelings of other colleagues? Especially student A and Prof. B?

Just graciously explain yourself and be firm. They may not be happy but if you just won't go forward, they have to deal with it.

You can't always make everyone told happy.  Sometimes you just need to cut things off.

Don't belabor or debate.  Just be respectful, but firm.  And brief.

https://www.youtube.com/watch?v=ABXtWqmArUU


Bibliographic entry for a pseudymous work with known real author This question is the bibliographic pendant to this question.

Let us suppose I write an academic paper where I cite the well known paper English sentences without overt grammatical subject  (pdf), written by James d. McCawley under the pseudonym Quang Phúc Đông. What is the bes way to format the bibliography?

[1] Đông Q. P., “English sentences without overt grammatical subject”, doi: 10.1075/z.63.06don. Actually written by McCawlay, J.D. under pseudonym
[2] Đông Q. P. (alias McCawlay, J.D.), “English sentences without overt grammatical subject”, doi: 10.1075/z.63.06don.
[3] McCawlay, J.D. (as Đông Q. P.), “English sentences without overt grammatical subject”, doi: 10.1075/z.63.06don.
Something else ?

I want to make both the name and pseudonym appear in the bibliography.

Bonus question: Once the “academically correct” solution is known, how to implement it in a bibtex bibliography?

The "academically correct" solution is usually to format that bibliographical item as any other item, with the name which appears on the paper (this is also remarked in the answers to the linked question). Then, you can add a bibliographical note saying that the name is a pseudonym: in bibtex you can do this by means of the field note. However, about this, take into account the objections that have been pointed out in the answers and comments to the linked question.

The above solution would roughly correspond to your [1], with the exact details depending on the chosen style.

Of course, if you are writing a paper for a journal, the style guide might require a different formatting or might not accept notes.

Edit: I've checked The Chicago Manual of Style, 16th edition, and it suggest a slightly different style, more similar to your example [2]:

  14.81 Pseudonyms -- unknown authorship. If an author's real name is not known, pseud. (roman, in brackets) may follow the name. (In a
  text citation, pseud. is omitted.)

and

  14.82 Pseudonyms -- known authorship. A widely used pseudonym is generally treated as if it were the author's real name.

  [...]

  The real name, if of interest to readers, may follow the pseudonym in
  brackets.

According to the above, your example would become:

Đông, Q. P. [McCawlay, J.D.], “English sentences without overt grammatical subject”, doi: 10.1075/z.63.06don.

The New Oxford Style Manual suggests the same format.

For what concerns LaTeX, if you want to follow the above format, it appears that the biblatex-chicago supports it. However, it is probably not applicable to specific publications. For instance, the IEEE BibTeX style does not support explicitly pseudonyms, but it has a note field. The people at TeX.SE can probably give you better information on which is the best way to implement that specific format.