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The full understanding of my bachelor's thesis requires the reader to watch a movie, how do I deal with that?
I'm currently putting the finishing touches on my bachelor's thesis. One part of that thesis is an analysis of a movie. I have written a short synopsis of the movie to go with it, however that is probably not enough for a complete understanding of the points I make in my analysis. I can't make the summary substantially longer as I have already reached the upper character limited set by my university for the bachelor's thesis. But I also believe that a written summary, however detailed, can not replace having watched the movie, as I'm talking about fine detail of the graphic style and aesthetics which can't be fully described using text only. In my analysis, I also reference other movies of the same director and explain how some topics and metaphors are used in those as well as in the movie I'm analyzing.
I am not sure how to deal with this. I can't just ask my professor to watch several movies in order to understand my analysis. But I also don't want to be graded badly because my analysis requires the reader to have watched the film (I believe that this is true of any detailed analysis of any work, so it's not just a flaw in my thesis that I should correct).
Here's what I have done so far:

I've included screenshots of the Blu-Ray release of the movie to illustrate some of my points.
There's a footnote at the end of my summary of the film that explains that this summary doesn't replace watching the actual movie and having not watched it might hinder the comprehension of the following analysis.
At the first mention of another movie, there's another footnote that contains a link to the official website of the director, which has detailed synopses of the mentioned movies. However, those can't replace the actual movies either.

I have thought about including a digital version of the movie when I turn in the thesis, but I don't think it's a good idea. I don't know if the assay office would even accept it, and even though I own the DVD-version of the movie, it would probably not be legal to give out copies. Also this wouldn't solve the problem when I put the thesis up on my website.
So how do I deal with this? Do I just ignore it as there is no better solution? Or is there a standard way of mentioning prerequisites for the understanding of a thesis?
I understand that I can include the movies in the list of references or just make it a separate list. However, the books that I reference in my thesis are not required to understand the points I make, as book references usually include the relevant quotes or repeat the points made by the authors. So I am not sure if this is sufficient.

I don't think I see a problem here.
If you were writing a literary analysis of Jane Eyre, you wouldn't include the full text of the novel in your paper, and it'd be entirely reasonable to expect the reader to read the novel in order to understand your paper.  I don't see why a film should be any different.
Your professor can, and should, watch the film, and any others they find necessary in order to make sense of your analysis.  That's not an unreasonable thing to expect, it's just part of their job, like any other background reading they might need to do.  If you can lend them your DVD, or tell them how to otherwise get it, that would be a nice courtesy.
Other readers will have to make out as best they can.  It might be nice to list on your website some ways they could acquire the film (Amazon link, Netflix availability, etc) but again this is more a courtesy than an academic requirement.
But to really cut the knot: Just ask your professor. They are in the best position to advise you, both on the academic standards of your field as to the content of the thesis, and as to what resources would be helpful to them personally in evaluating it.

Thank you! I'm always a bit wary of asking my professors how they would like it, as I believe the 'correct' way of dealing with such issues should not be based on personal preferences of respective professor but rather on general principles of academic writing. Of course that position puts me and my grade at risk, but I'm willing to take that stance and potentially accept that as a consequence

I think you're taking this far too seriously.  Obviously you should follow general principles of academic writing, and your professor is an excellent person to help you learn what those principles are, so you can certainly ask them about that aspect.  On the other hand, questions like "should I give them a copy of the DVD" are not about the content of your thesis, they're just about making it more convenient for your professor to evaluate it.  And only they can really answer what is most convenient for them.

In other words, your professors are entirely capable of distinguishing between what is abstractly desirable in the thesis and what is personally helpful to them, and can advise you on those two points separately: trust them to do it.  If you are unclear as to which is which, you can always ask for clarification.  It is foolish to pass up this obvious source of help; having access to it is the whole point of attending a university.  There should be no question of "putting your grade at risk".

@MoritzLost - "I believe the 'correct' way of dealing with such issues should not be based on personal preferences of respective professor but rather on general principles of academic writing. Of course that position puts me and my grade at risk, but I'm willing to take that stance and potentially accept that as a consequence" -- very weird comment.  Makes me wonder if there's more to this than meets the eye, e.g. is there some simmering tension under the surface?

@aparente001 while this may be the case, it is all too often that students overthink to extreme lengths the most trivial things, and act as if professors were members of some alien race that we have barely started to comprehend.


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Prior thesis examiners as potential future journal article referees?
I'm in the process of preparing a manuscript submission for consideration with a particular journal.
The article is an adaption of a portion of one of my thesis chapters. My thesis has not been formerly published in any manner in accordance with my country's copyright/publication practices with doctoral theses. While I've rewritten the majority of this article to fit the theme of the journal and become 'self-contained,' the hard data and some of the analysis is the same.
For this particular article and journal, a former thesis examiner of mine would be an ideal reviewer to list on the cover letter as having specialised expertise in the topic area. It is quite a 'niched' but also interdisciplinary topic which makes it difficult to locate potential reviewers, and this particular reviewer covers all of the interdisciplinary topics with their expertise. They have also written previous articles on this topic for this same journal, and I do draw on their work heavily throughout, so an editor might think to send this out to them regardless of whether I put their name down, or might think I don't know who the experts are in the field if I don't put their name down and this could hinder my chances.
My question(s) (knowing that editors don't always go with recommended reviewers):
1. Can I/Should I still list this person as a potential reviewer even though they have previously examined something very similar in my thesis? They will undoubtedly know that it is my work they are reviewing which means it will not be a blind review.
2. Should I list them as not reviewing my work, not because they are not capable, but because they examined something similar in my thesis and it will therefore not be a blind review?
3. Should I not list them and hope for the best?
4. If 2 is preferable, what would be the appropriate way to state this? Would something like the below be appropriate:

Blockquote *I acknowledge that ________would be an ideal reviewer, having an expertise in the intersectionality and main focus of this piece. However,________was one of my doctoral thesis examiners (of which this piece is adapted from) and would recognise the data and some of the analysis as being my work.

Any help or input would be appreciated!

So this is a double-blind journal? What are the rules with respect to that?

@SashoNikolov yes a double-blind journal. It doesn't list any rules regarding listing referees.

I would just shoot an email to the area editor to ask what to do.

Is seems to me that what you are caught on is one of the key tensions in reviewing:

The more knowledgeable the reviewer, the more likely they are to have some sort of conflict of interest regarding a manuscript.
The more independent a reviewer, the less qualified they are likely to be for a deep review of a manuscript.

Different journals and different editors have different places where they draw the line on the range of acceptable tradeoffs between knowledge and conflict of interest.
As such, I would recommend simply providing the information to the editor in your list of recommended referees, along the lines of what you have suggested but with less assumptions regarding the appropriate course of action:

X would be a good reviewer, but was one of the reviewers of my thesis.

The editor will then be able to make the call as best they judge (which they will do in any case), and will not be likely to feel that you are pushing them to either use or not use the person as a reviewer.

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How to notify Elsevier or Clarivate when then they are indexing predatory or very low quality journals?
What is the best way to alert Elsevier or Clarivate Analytics -- for instance, if I see a potentially predatory (or just really low quality) journal indexed in Scopus or WoS or if I see recent changes that possibly indicate a lowering of standards by the journal (such as a dramatic increase in the number of articles published)?

@Roland Many of these indexes form the basis of university rankings (I.e., how many articles is the university getting in listed journals) which influences university prestige, which in turn influences academic incentives, promotions, and rewards. So even if you object to such a system, surely it is better for such indexes to reflect valid journals.

First, Elsevier or Clarivate Analytics already monitor things like dramatic increases in the number of articles published. It's why excessive self-citation can and has lead to journals getting delisted.
However you can still write to them to highlight potential problems. If you want to do this, the best way is to use their "contact us" forms on their website. Here's Scopus's page on it, and here's Web of Science's. Be prepared for the exchange to go like any other investigation - you may be asked to provide proof.

You should not rely on indices and metrics to judge the quality of a journal.  Rely on the journal content and on colleagues who have experience with the journal's review practices.  There is no reason to alert any index.
If your library is paying for the publication, you might suggest the librarian bring it up with the publisher's sales staff.

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Does failing the qualifying exam leave a record?
For a PhD student, is it common that failing a qualified exam and thus leaving the PhD program results in a termination record, which any future academic program (the student will apply to) will be interested in accessing after getting the student's permission?
For example, some can leave their PhD program with a clean record, according to this blog:

The graduate committee chair who gave me the news reminded me that I could still apply to other programs and that it wouldn’t go on my record or anything so it will just look like I just left with my MS degree. If I ever want to, I can return to grad school in the future, and I will be better able to choose a department that fits me.

But if the student has received his masters way before his qualify exam, is there other way to write the record that looks better?

But if the student has received his master way before his qualifying exam, is there other way to write the record that looks better?

First, the student doesn't get to write the record. The university writes the milestones that the student passes, specifically, which classes they took and with what grades, and which degrees they earned. (In some countries, the thesis itself also receives a grade, like a class.)  At least in the US, intermediate milestones like finding an advisor, passing or failing quals, proposing or failing to propose a thesis, probation, suspension, termination, and even academic integrity violations are rarely recorded on university transcripts.
So, for example, if a student were asked to leave a PhD program after 2.5 years, for whatever reason, the transcript would show five semesters worth of classes, ending without the student earning a degree, because they didn't.
Many PhD students in this situation opt to switch to an MS degree program in their final semester, so that they can plausibly claim that they were just a masters student.  (After all, in their last semester, they were just a masters student.) They don't have to explain why they left without a degree.
If the student already has a MS in their home department, earning a second MS in the same field is usually impossible.  But another option is to switch to an MS program in a nearby field, for example, applied math or computer engineering or operations research instead of computer science.  At least at my university, switching from a PhD program in department X to an MS program in nearby department Y is usually fairly painless, especially if you have a supportive advisor in department Y.
If even that is not an option, I'm afraid there's little one can do.  Your transcript will end without a degree, and most people reading it will assume that (or at least wonder if) you left because you were forced out.

At my US university, passing the qualifying exam is recorded on transcript. I don't know if failing is, though.

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What are some ways to increase grading speed?
I sometimes spend too much time on grading students' homework in the class I am a TA for. I am asking if there are some ways to improve grading speed? I hope that I can learn some useful tips from experienced people here.
For example, which one do you think will be faster, grading student by student, or problem by problem?

I always grade problem by problem, but mainly for consistency, not speed.

Like JeffE, I usually grade problem by problem.  I think it helps with both consistency and speed.

I find it very helpful to write a grading rubric.  It includes how many points I give for each part of each problem.  I also include how many points of partial credit I give for various common errors.  Typically, my key consists of a worked copy of the exam, and I make notes about each question on the actual exam.  Generally, my rubric gets more detailed as I grade, since it's only then that I learn what are the common mistakes.
If I feel that I'm taking too long grading, I'll often start timing myself.  Maybe I get at most 30 second per question (often less).  This isn't a hard rule, but it helps me know what to aim for.  (Recently I just graded a calculus exam, so most of the problems were pretty quick to grade.)  Your mileage will vary from one subject to another.

I have experience in grading math Olympiad papers; one principle we adopted there is to always grade in pairs, with one pair grading a single problem, or more pairs sharing a long or tricky exercise. I recommend this strategy especially for grading more important papers such as final exams, where good accuracy is important.
It may seem that this is a waste of resources; however there are several benefits:

Accuracy increases much. A subtle error has to slip through two people instead of one.
You do not waste so much time as it seems at first sight. Grading often follows an 80-20 law: 80% of the papers takes you 20% of the time, while grading the remaining 20% consumes the remaining 80% of it. This may be due to particularly non-standard solutions, bad handwriting, or edge cases that evade your marking scheme (as suggested by Dan C, always have a marking scheme, especially if there are multiple pairs on the same problem, and discuss together the more complicated cases). So, while you waste some time by having two sets of eyeballs looking at the easier papers, it is often invaluable to have a ready help in the more complicated cases. Your colleague may be faster than you in spotting a definition that you missed, a hidden line of reasoning, or deciphering a strangely-looking hieroglyph. This saves a lot of time on the  more complicated cases.
You will feel a lot less tired and find that you can go on with a steady rhythm for hours. You can chat together every now and then, share comments on good solutions, or make fun of particularly bad ones; this helps relieving tiredness.

Often we see one person trying to explain the solution to the other, or the pair spontaneously evolving a good cop-bad cop behaviour (one looks for weak points in the solution, the other defends the student). This method also doubles as training for beginner graders, that can learn from working with a more experienced partner.


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

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

It wasn't the first time I heard such a complain, as simplifying existing solutions is arguably a contribution, yet sometime despised.
Is there any research/study/survey that looked at the impact of the complexity of the method(s) proposed in a submitted paper on its acceptance rate?
I am mostly interested in the field of computer science > machine learning / NLP / data mining, and English-speaking venues.

I certainly agree that it would be interesting to read about such research.  Working as I do in a field like mathematics, I always wonder how researchers negotiate issues of imprecise definitions.  In this case it seems to me that the "complexity" of a paper is very subjective.  Or is the idea to see how perceived complexity correlates with perceived value?

I can imagine this will depend on the field of research; in my field at least (marketing) I haven't seen any study like this. Yet, if there were one, which journal would publish it? You would end up saying basically "this journal doesn't accept qualitative paper". Because the debate is really this one in marketing: qualitative vs. quantitative.
For quantitative studies you'll always find a journal. Depending on the complexity of the method the ranking of the journal will vary. Good quality papers will always find a journal interested in it. For qualitative papers the story is different.

This is highly field specific. For instance, the use of complex statistical methods in health sciences or psychology will dramatically reduce the acceptance rate.

I haven't seen any research on the correlation between the complexity of the methods and the acceptance odds of a work and I think it is relatively hard to do a study on this. First because being simple or complex is completely subjective and domain dependent and hard to quantify. One can not generalize a pattern that is seen in a particular scientific community to others. Moreover, the information about rejection of papers is not publicly or easily accessible making the hypothesis hard to investigate.
That being said, in computer science machine learning community, I have seen that people are pushing towards critiquing the unnecessary complexity of the suggested methods and putting more emphasis on the actual results rather than the simplicity or complexity of the methods. There are many simple methods that are being published because they actually work well. I personally don't think that simple ideas which show good results are necessarily prone to rejection, but the opposite argument (complicated methods having higher chance of acceptance) is sometimes true.
On a related note, explanation of the ideas and presenting a work in the most simple way for people to understand, is being emphasized more and more. One reason of people trying to complicate things is that they think the less it is easy for reviewers to understand their work, the higher their chance of acceptance. I personally think that ideas in the papers should be explained simply and clearly because if it can’t be explained simply, probably it can be done better. And reviewers should not praise the work they don't understand, because it is the duty of the writer to explain everything simply enough so that the corresponding community understands it well.

This is relevant to the Kuhn - Popper debate about the way science works, and there is a considerable literature here... I don't know about statistics, but I do know this is extremely common! A new simpler approach will usually be dismissed out of hand with scant regard by the powers that be with their strong ties to the traditional model.
Kuhn notes that researchers get locked into Paradigms.  Those in positions of power (referees and editors, professors and deans) prefer papers that continue their work, use the tools they invented or are familiar with, cite their journals or journals indexed by their favourite citation company. There is also a factor of workload in relation to interest: They skim things quickly and pay particular attention to headings, tables, figures, equations and references - looking for things that connect to them/their interests/their journal. Some reviewers show no evidence of having actually read the paper, particularly for so-called 'top journals'. If they are not interested, or they have decided it a 'poor approach' a priori, then it doesn't matter how good the approach is or the results are, and you will be flipped off with comments about the style, format, equations or references (e.g. a complaint of lack of references to X or insufficient or unnumbered equations, or lack of road map glue telling them there is are Introduction, Methods, Results and Conclusion sections). That is there are not only paradigms within fields, in relation to how you tackle a problem, or the theoretical framework or model you work in, there are paradigms in relation to modes of presentation.
Popper on the other hand espouses Parsimony and Refutation. The simpler theory or model is better, other things being equal.  A poor theory grows more complex as it keeps being adjusted or extended to deal with new cases that cause it difficulties.  Usually the poor theories and models don't die off until their proponents and perpetrators do, until they get so complex as to be completely unmanageable and they eventually topple over and fall into oblivion. Conversely, a simple model will be ignored until it is demonstrated that it handles everything that the older theories tried to do, and makes new advances and predictions that are borne out. Popper's ideal researcher is totally different from Kuhn's dogmatic paradigmatic researcher. A good researcher is making predictions into the unknown where the different theories predict different outcomes.  A good researcher is not trying to bolster their models, but rather to refute them - find the holes rather than plug the holes.
So how do you deal with this? A very good question - glad you asked...
You have to face it head on. Choose publication venues that are high quality but have the kind of format and expectations that allow you to present your new simpler ideas and models, even though it may not be fully worked out and compared against all your thousands of competitors and their thousands of datasets or examples. Get feedback, and find who is sympathetic, where they publish/review/edit etc. Eventually, you need to target the archival traditional journals, the bastion of the current paradigm, and fit things into their mould, follow their rules, explain the equations/models you are competing against in detail, especially those that are pushed by the journal and its editors/authors (at least they get a citation). Clearly point out the advantages...

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

While this is interesting, I don't see how it answers the question, which is explicitly asking for a reference with data...

But does it also back up or quantify these factors with research and where are you referencing it?


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How many online courses have been removed due to accessibility laws?
Is there any research/study/survey/database that tried to quantify how many online courses/videos/audio lectures/other educational materials have been removed due to accessibility laws such as the Americans With Disabilities Act of 1990 (mirror)?

Truly interactive online courses are so much newer than the ADA that I doubt many have been removed.  What's at risk is material developed for other purposes that could be made freely available for non-credit study, but that can't be made available "because ADA."  Example: I record my lectures and make "narrated slides" available to my students.  I can do that provided I have no hearing-impaired students in the class.  What I cannot do is put my courses on the public web for anyone to use.

@BobBrown, I don't understand why you cannot put your courses on the public web for anyone to use (supposing for the moment that you have no students in your course needing accommodation...), especially if the material has no larger official status.

@paulgarrett  Every slide has the school logo.  Removing the logos and regenerating the video file is less work than captioning, but still more work than I am willing to do.


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Where are predatory publishers based?
Is there any research/study/survey that looked at the location of predatory publishers? (e.g., x% are based in country A, y% are based in country B, etc.)
I am mostly interested in English-speaking venues and the field of computer science. Trends over time are welcome as well.

(+1) for the question, as Beale's list is not there now. Sad! If you remove the constraint "English-speaking venues", then it would be India? However, Indian do use English as primary language now-a-days.

Given that many predatory publishers apparently consist of one person and some cloud-hosted websites, how would you define where they are "based"?  The country where the person lives?  The country where their bank account is set up?  The country where the web server is located?

@NateEldredge The study should indeed ideally clarify its definition of "based".

And how do you count? Some will be publishing 100s of 'international journals', will you only count them once? Or by spam email volume?

@coder there are archived versions.

What about those that use a front in say India or China, but the money actually flows to the U.S.?

There is a study by Shen and Björk (2015) which includes a figure (Fig. 6) showing

the distribution of the publishers across geographic regions. The distribution is highly skewed, with 27 % publishing in India.

Figure 6:

(the figure's license: Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made)


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Best search bibliographic database
I was evaluating Jabref and found it has a bibliography web search tool.
You can choose among:
ACM Portal
Arxiv
Crossref
DBLP
DOAJ
GVK
Google Scholar
IEEEXplore
Inspire
MathSciNet
Springer

Which one offers more or better results when looking for a given scientific or technologic article?

"Which one offers more or better results when looking for a given scientific or technologic article?" Surely this depends on the article. For example, if I were looking for an article that happens to involve Stone-Čech compactifications, I would not expect to find anything useful from IEEEXplore, and I would probably start with MathSciNet.


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Poor academic performance - should/can I apply to a PhD program?
I was always a distracted kid growing up. I found it difficult to pay attention to anything for more than fifteen minutes. Growing up in Asia, teachers at the school and college levels always put it down to me being a “bad student” and made sure I knew that I would never amount to much.
After moving to the US for my master’s degree in computer science over ten years ago, my distractions and poor academic performance started haunting me again. I was put on academic probation and faced expulsion if I did not bring my GPA up (from 2.5x to 3+). During one of my lectures, the professor noticed my fidgeting and asked me to meet her after class. She told me I exhibited the classic symptoms of ADHD (which I had never heard of before) and asked me to meet the university counselor. The counselor confirmed the diagnosis and referred me to a psychiatrist for medication.
This was probably the biggest turning point in my life as it was only then that I realized that there was something that caused me to behave the way I did. Knowing and understanding what the cause of my distractions made me able to address it and focus my energy and concentration properly. I transferred to a different university (lesser ranked than the first one, but well known for its notoriously rigorous curriculum) and was able to maintain a 3.5+ GPA throughout, in addition to being invited to PhD level research groups and being admitted to highly selective research internships in Europe. I enrolled in classes that were restricted to PhD students after I petitioned the school dean, and ended up topping 2 out of the 3 courses.
In my mid-30’s now, I currently work as a scientist in a reputed firm. I’ve been granted a patent in machine learning and one of my papers has been shortlisted for publication in a top tier conference (I won’t know for sure till next month). I came across a PhD program that pretty much aligns perfectly with my grad school research and social cause and I’m extremely interested in applying for it. The application process involves the regular requirements of GRE/recommendations/statements of purpose and transcripts from ALL universities attended.
My grad advisors and I have maintained good relationships over the years and they have encouraged me on several occasions to apply to a PhD program. However, I’m worried that my academic performance at the first university I attended for my master’s will come back to bite me. While I can just apply and hope for the best, I don’t want to have to ask my professors to invest the time and effort to write recommendation letters for me, only for my application to be thrown into the trash.
On a scale of 1 to 3 stars, (3 requiring the most effort), here are the requirements for the application:

Personal Statement (**)
Transcripts from all institutions attended (*** - insanely difficult and time consuming to get bachelor degree transcripts from university)
3 letters of recommendation (** - easy enough, but I feel bad about getting my professors to do this for me if there’s no change of getting it)
GRE (**)

The PhD program is in a field I'm very passionate about and has world class researchers on the faculty. At a recent graduate open house, I met the director of the program who said they had an 11 percent admit rate over te past few years.
All this said, would it make sense to apply to the program anyway or will the fact that I was nearly expelled due to my academic performance make the risk not worth the effort?
EDIT: I wanted to thank everyone for their thoughtful and supportive responses. I've decided to apply for the PhD but for next year's intake. As an update, the paper that was shortlisted to the conference I mentioned ended up being accepted, so that's sure to build up my profile a little more.

If you don't try, you'll never know.

Regarding the transcripts issue, do you have any unofficial transcripts? If so, you might want to try just including a photocopy of those and explaining the problem with getting official transcripts. Even if you don't have an unofficial transcript, if you have grade reports for the classes you've taken, maybe you can make copies of your class grade reports, staple them together, and send that in, again with an explanation of the difficulty in getting a transcript.

You might consider explaining how your ADHD diagnosis turned your academic life around somewhere (personal statement maybe? a cover letter? I'm not sure what US application materials look like exactly) if you want to explain those early grades. But as Dan Romik said, your more recent achievements will count for much more, especially as they are more directly relevant to a PhD than coursework, which is not a good predictor for research ability at all. So you don't need to worry that much about them in the first place.

You are now in your mid-thirties. You don't give a precise timeline, but based on your description I'll assume that the poor performance from the first university you attended for your master's happened about 10 years ago. In the meantime, you completed a degree elsewhere with much more distinction, and developed a career and a track record of successful achievements.
The logical conclusion is that any sensible admissions committee will look to your recent record as a much better indicator of your potential to succeed in the graduate program than your more ancient school history. The grades from your old school will very likely be seen as largely irrelevant. So, in my opinion this should not be a major concern.
And as @astronat said in a comment, you'll never know what would happen if you don't try. Good luck!

There is a rule I have for these things: "If you don't apply, the answer is automatically 'No'"
To address some of your concerns:

Transcripts from all institutions attended (*** - insanely difficult
  and time consuming to get bachelor degree transcripts from university)

Talk to the programs about this requirement - often admissions are written assuming a candidate with a "standard" path through academia, but are more flexible in practice. For example, we recently did some things to help a student coming back after a long period of time because, like in your case, it would be very hard to dig that deep into history.

3 letters of recommendation (** - easy enough, but I feel bad about
  getting my professors to do this for me if there’s no change of
  getting it)

There's a chance.
That seems to actually be the core of your question - is there a chance. And I'm going to say the answer to that is yes, despite your difficulties. Now clearly, I can't speak for any particular department's program, but some thoughts:

Time has passed, you seem to have built a successful and relevant career, and are doing good work. That counts for quite a bit.
You have a reason. Having undiagnosed ADHD is a perfectly credible explanation for having struggled early in your career, and you have actually demonstrated that this was a turning point. Admissions committees understand that people are human beings.

Some people are good at passing exams but bad at research and scholarship. Some are bad 'in school' but turn out to be great scholars and scientists. But for most people, academic performance correlates pretty well with research performance. So... the odds are stacked against you, somewhat.
However.
You are probably not the statistical average (few people are, in fact). So you have to honestly evaluate how you might stand out. Do you really really want the PhD? Are you capable of sticking with it, dealing with setbacks and unpleasant feedback? Are you creative, inventive, yet intellectually disciplined and rigorous? Are you good at dealing effectively with delicate situations? Are you a negotiator?
You probably get the general gist of these questions. And remember, life really is nothing like a Hollywood montage.

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text:
Can you submit to journals after presenting cases as eposter in conferences?
I had a few medical cases that I presented in conferences as an eposter, I sumbitted the case as eposter, It was presented as a slideshow in big screens in the conference
My understanding is that eposters are not considered publications; so can I submit these cases to journals?
Some journals specify as a requirement that the case submitted should not be published before on other journals or electronically. Where do cases presented as eposter stand on this?

Is the eposter available online?

yea the eposter is available online in the website of the conference in the eposter section.
@Wrzlprmft I sumbitted the case as eposter, It was presented as slideshow in big screens in the conference, thats it. not published on journals online or paper.

Very few medical journals consider a poster presentation a publication. So vanishingly few that I have never encountered one in my career. Indeed, the primary expectation of the posters I've encountered is "This'll someday be a paper, but these are the preliminary results."
As long as it hasn't been worked into a full paper as part of the conference, there's no reason to worry.
If you're concerned about it, you can include a sentence in your cover letter to the journal something like the following:
"This manuscript is not under consideration at any other journal, however the preliminary results have been presented as an ePoster at the Conference of Big Deal Science."

You should check the specific journal's rules about this.
I have worked on the editorial side of a number of journals, and have been happy to accept full research papers based on work presented at conferences. This is assuming that the submitted paper has been "worked up" to full paper length and detail (the results presented at conferences are not typically comprehensive), and that there is not excessive overlap (a conference proceedings publisher may well hold the relevant copyright).
I write this with the caveat that I have experience in physics and related publishing but not in medical publishing. In any case, I imagine that there's enough variation in practice between different journals within your field to make enquiring with the editors a necessary precaution. Good luck!


text:
Are author names typically visible to reviewers for paper award decisions?
I wonder whether author names are typically visible to reviewers when they decide paper award recipients. (i.e. non-anonymous process)
I am mostly interested in the field of computer science (especially machine learning and natural language processing), and English-speaking venues.
Ideally, I would like to have a list of awards labeled with anonymous / non-anonymous.

I'm going to ignore the "reference-request" tag and answer from experience.  Please either explain why you need a reference (and I'll delete my answer) or else remove the "reference-request" tag.

@jakebeal I had added the "reference-request" tag as ideally, I would like to have a list of awards labeled with anonymous / non-anonymous. Shall I create the separate question focusing on the reference request? (thanks for your answer to this question)

I don't believe that your "big list" question is meaningfully answerable: nobody is systematically tracking conference awards.

@jakebeal it's unfortunately unlikely, but I guess it doesn't hurt to ask it, in case. Shall I create the separate question focusing on the reference request?

I think this question will suffice: if anyone is capable of answering, you can accept them and bump it to the top

@jakebeal Sounds good

In my experience with computer science conferences, I have encountered two general classes of award processes:

Reviewers nominate for an award, and then the organizers consider and choose between the nominees.
After reviews have been submitted, the organizers consider the top N papers by rating and choose between them.

Sometimes the decision is made entirely from the paper and reviews, while in other cases presentation at the conference is taken into account as well.  In all of these cases, however, notice that it is the organizers and not the reviewers who actually decide the award, and the authors are generally not blinded to the organizers.  If the first procedure is followed and the conference happens to be double-blind, then nominations will be made blind, but the decision is still typically made with knowledge of the authors.


text:
Sharing data (not a data set) with a research paper
How to share data accompanying a research paper? I know there exist some places to share datasets, but sometimes I would like to share data that are not data set (e.g. experiment parameters, results, etc.), and add a pointer in the research paper to the online location of the data. The data size typically range from a few KB to a few MB, and the license is not an issue.

For those interested in the question on sharing data that is a data set, here is the link.

e.g. experiment parameters, results, etc.

In the past, I have shared this kind of data from a conference paper in any of a few ways:

Create an extended tech report version of the conference paper, that includes all that data in appendices. Refer to the tech report in the conference paper.
Put the data on a lab wiki, and include a link in the conference paper.
Put the data in a Github repository, and include a link in the conference paper.

I choose between those based on the nature of the data, i.e. which format seems most natural for it.
I've never used Figshare for this, but that would be another idea, (if you wanted a DOI for it, for example.) You can put any kind of "research output" there.

The typical way to share a moderate-sized set of data accompanying a research paper is to attach it to a journal article as supplementary information.
For conference papers, however, there is often no option for adding supplementary information.  My recommendation for this case is to simply wait and attach to the extended version that is ultimately published as as the final archival form in a journal.

Thanks. In my field (natural language processing), conference papers are typically end products: they are rarely transformed into journal papers.


text:
Why don't publication venues systematically make the LaTeX source of papers available?
I wonder why most publication venues don't systematically make the LaTeX source for published papers available? (which implies systematically asking authors for the LaTex source)
LaTex source are more machine readable than PDFs, and make it easier for humans to reuse part of it (e.g. math equation or figures), amongst other advantages. I fail to see any downside.
(I am aware that some authors write their publications using other tools such as Microsoft Word: let's ignore it.)

I've worked with people who sent me LaTeX code for drafts that did not even properly compile, although the pdf looked ok… BibTeX files were sometimes even worse…

Commercial publishers such as Elsevier and Springer are not part of academia, and they don't share their culture of openness. Very far from it. They consider the final TeX code and their mix of classes and packages as a trade secret.

Many figures are submitted as separate files and access to the LaTeX won't help at all since that only contains a link.

Reclarifying old question: Why would LaTeX being more machine readable than a PDF be an advantage? (Other than being able to extract equations from it, which I expect is also possible with PDF).

What matters is the content of a paper. So the pdf is kind of the black box that hides what lead to the binary decision of pixel or no pixel. Some people use code that should better be hidden in a closet than made publicly available, just as @Dirk mentioned. Also, the big publishers use LaTeX in a way you are not expecting it.

@FedericoPoloni it's not a "trade secret", if anything they legally own the text and figures. Besides, professional publishers typically use commercial software for typesetting, and often re-type articles entirely. There is no Latex source to share. It's much more efficient than dealing with everyone's pet Latex package mix.

@Pharap E.g. extracting information from a table is typically much easier when the table is in LaTeX than when it is in PDF. Also, my experience with PDF->LaTeX conversion for equations is not so good, and it's one more tool to use..

Searching text is not easier with LaTex or such. Even in StackExchange formulas are discouraged in titles as they confuse the search engine.

@Greg machine readability != searchability.

pdf is a binary format. This is like asking for a tool that gives the code base of Microsoft word. Once you cooked up the stew, it is extremely difficult to know all the detailed ingridients.

God bless whoever opens my LaTeX file... I just patch things here and there to achieve a certain effect and it's like a space shuttle launching platform supported by recycled cardboard, duct tapes, and popsicle sticks.

@Penguin_Knight You seem to be the rigt person to drop in the TeX.SX chat once in a while :-)

@Penguin_Knight: I just joined this community in order to +1 your comment. :)

@Johannes: do not tell there are ducks around academia too. :)

If I was asked to provide the LaTeX file, I would be very concerned with cleaning up the code and removing all the commented text that was either rewritten or just notes to myself. I am happy the venues I submit to don't ask for it.. Maybe the organizers think the same?

@MohamedKhamis You can easily remove all comments with a script (the publication venues could take care of it).

I suspect that this is a solution in search of a problem. Most likely journals aren't making LaTeX versions of papers available because they don't see a demand for such a service from the side of the readers; this would take effort to implement and maintain; and some authors would object to the idea of making it easier for others to reuse (read: plagiarize) their papers. In other words, publishers simply have (or at least think they have) better things to do with their time and money.
It should be noted that arXiv does make LaTeX source code available, and in fact will only accept submissions in the original source code rather than as PDFs (for papers that were written in LaTeX), so in those areas of math and physics where uploading preprint versions of one's paper to arXiv is the norm, this "problem" (such that it is) is already solved.

+1 I think this is the major point.  PDFs are quite sufficiently machine-readable for purposes of search engines, and unless people are clamoring for LaTeX source, they'll focus their resources on the things that people are clamoring for, like better per-paper metrics.

I guess it's a bit like binaries and source code: binaries are enough for most situations, but if one day one needs the source code while only binaries are available, problems arise (-> PDFBox).

I think your question is actually about why publishers don't make the LaTeX source of papers available to readers rather than why publishers don't accept submissions in LaTeX form.  You might want to clarify your question.
Some publishers prefer to accept PDF versions of paper for review, but then ask for LaTeX source code after the paper has been accepted.  Doing the peer review process with a PDF version of the paper saves the publisher the trouble of running the paper through LaTeX and fixing any problems that the authors might inadvertently have introduced into the manuscript (such as using non-standard packages of macros.)
At the final publication stage, authors typically submit LaTeX source to journals.  The journal then applies its own style to the paper, adds copyright notices and page numbers, and produces a final version of the paper using LaTeX.  However, journals typically only publish PDF versions of the papers rather than the LaTeX source.
Many journals make their style files available to authors and ask them to prepare the manuscript using the journal's style.  This helps to avoid problems when the final version of the paper is prepared by the publisher.
Having the LaTeX source of a paper makes it slightly easier for plagiarists to cut and paste mathematical formulas and text from the paper or to maliciously produce alternate versions of the paper. Commercial publishers are also generally opposed to any use of a paper that goes beyond simply reading the paper- making LaTeX source available tends to make such reuse easier.

+1 Excellent point about how providing "LaTeX source of a paper makes it slightly easier for plagiarists".

Actually, I'm not sure that journal publishers do "produce a final version of the paper using LaTeX." My understanding is that the large publishers use their own in-house systems for final publication and that, while LaTeX is clearly an input to that, the final work is not done using LaTeX but with some other proprietary software.

I can more or less confirm what @DavidRicherby said in at least one case: when submitting to the American Physical Society journals, I am told as part of the publication process that the submitted paper will be converted into their proprietary XML format.

Clearly, my answer is only applicable to those publishers who produce final versions of papers using LaTeX.  In my experience that includes Elsevier, SIAM, and INFORMS.  This is getting a bit beyond the original question though...

@DavidRicherby are you suggesting that there is proprietary software out there that duplicates the functionality of TeX and LaTeX without using the original TeX/LaTeX engines at some point during the compilation? If that's what you're saying, I'm willing to bet money that that's incorrect. (And if that's not what you're saying, then I'm not sure what you mean by "I'm not sure that journal publishers do 'produce a final version...using LaTeX'".)

@DanRomik As I said, "LaTeX is clearly an input". However, my understanding is that producing an issue of a journal or volume of conference proceedings does not necessarily involve producing a big .tex file, running pdflatex on it and sending the resulting .pdf file to the printing company. I don't know what other steps there are, whether they involve massaging the .tex, the .pdf or something else, but I'm pretty sure they exist (I'm pretty sure I remember reading author instructions that say that even using the supplied LaTeX style file only produces an approximation of the final output.

@DanRomik This post on TeX.se talks about software used by some typesetting companies, though some of the comments to the answer dispute its claims.

@DavidZ, American Institute of Physics similarly (in fact I think it's the same software)

@DavidRicherby LaTeX being an input does not say anything about whether the TeX/LaTeX engines are used. I claim that (in the context of academic publication of papers in CS/math/physics) all publishers will in fact use those engines (or possibly use PDF directly generated by the authors). They may have some complicated workflow involving layers of proprietary software, but at some point, code written by Knuth/Lamport/etc. will be run. So your statement "I'm not sure...using LaTeX" seems to me like it was phrased in a misleading way, given that apparently you meant something subtly different.

@DanRomik I'm sorry you felt I was being misleading but I think what I've written is an accurate summary of my admittedly vague beliefs on this subject. The relatively large number of upvotes my comment received and the confirmatory comments by Chris H suggest that other people believe that what I said is some kind of approximation to the truth.

@DavidRicherby okay, I'll bow to the wisdom of the crowd then and admit that I was being silly. It does happen from time to time.

@DanRomik The use of XML as an intermediate step by APS is very clearly documented; indeed, it's the very first line of the APS guide to REVTeX 4.1. Their system obviously uses some form of the (La)TeX stack at some point of the process (they explicitly ask for REVTeX source files), but a tex->xml->pdf workflow is nonstandard in terms of what an author might do. §II of the guide explicitly says that the REVTeX output is only an approximation to the final pdf produced via the XML, which also produces the HTML output.

@E.P. that's interesting. I understand and agree that there are some nonstandard LaTeX-based workflows around. However given the above discussion and the votes on Davis Richerby's comment it seems that your "obviously" may not be so obvious to everyone. Thanks for helping to clarify the situation.

I have been told by insiders at IEEE that they do not actually use LaTeX to typeset papers. Instead "some proprietary software" takes the LaTeX source as input, translates it to some intermediate XML format and produces the final output from that.
I guess the point about using or not using LaTeX to typeset LaTeX documents is that many publishers generally do not only use LaTeX to do it. Consequently, the final output may not be exactly reproducible by outsiders (such as the authors themselves) using only freely available software such as LaTeX.

Related question on TeX.SE, with another claim that APS journals use Advanced Print Publisher.

Those publication venues that have use for the code typically ask for it (e.g., EPTCS). But if a publication venue does not need the source, why should they ask for that?
While in principle, LaTeX source code may look more readable than PDFs, there are many limitations to LaTeX source code. Those who ever tried to use a LaTeX2HTML converter know what I mean. As an example, there are documents that will compile with XeLaTeX, but not with LuaLaTex ... and vice versa! Furthermore, there are documents that will only work with the latest TikZ version. Then, there are documents that do not compile anymore with modern LaTeX distributions. So reusing LaTeX code later may need manual work to make the code work with modern TeX distributions.
But also applications that make use of TeX code snippets are hard to do based on author-supplied TeX code. Copying a figure is difficult as the needed macros may be scattered through the complete document. Also, the figure code may depend on packages that can clash with other packages, which makes pasting them elsewhere difficult as well. Furthermore, searching in TeX code is difficult (which would be another application for which the source code could be used), as heavy use of macros may lead to the search term not being shown in the actual code. Both of these issues do not exist with the later PDF.

"If a publication venue does not need the source, why should they ask for that?" -> to allow machine readable access, and make it easier for humans to reuse part of articles (e.g. math equation or figures). In these two use cases, most of the time there is no need to compile the LaTeX document.

@FranckDernoncourt I added a paragraph discussing that.

A substantial number of all-OA publishers do offer machine-readable versions of papers - they just do so as XML rather than as LaTeX. See, for example, the XML links on these papers in various journals:

Cryosphere (EGU)
PLOS One (PLOS)
Journal of Economic Structures (SpringerOpen)
Remote Sensing (MDPI)

As the XML is probably more machine-readable than the LaTeX source, why go to the extra effort of providing an intermediate format - especially one with all the reuse/interpretation problems that DCT & others refer to?

Many journals convert LaTeX to XML, thus the XML is the intermediate format.

@ChrisH surely the XML is (one of two) final formats, rather than an intermediate one, in these cases?

LaTeX files are less searchable than PDF and are almost always useless on their own.
Next to the packages problem already mentioned here LaTeX files often use a lot of other files as input, which makes redistribution a hassle. This also makes the file less machine readable. A search engine such as Google will not understand where a given image, or other other input file will appear in the text and thus will not link the two, hurting the context and search results the file is placed in. This is not the case with PDF files where everything is grouped together (or at least understood where it should be placed, see the HTML view Google makes of PDF files).
Now one could argue that you should publish all files required to build the LaTeX file. But even in my extremely limited academic experience I have found cases where this is impossible. Some tables in my thesis were generated by LaTeX using 500MB of raw data. It would be crazy to have to distribute these (or for a machine to need to parse these).

You get into open-data question rather quickly if the LaTeX is interpreting your files to build the tables (though that is probably rather rare in papers if they're compiled at the journal).

The opposite case is argued quite eloquently in arXiv's Why Submit the TeX/LaTeX Source? piece.

@E.P. that piece does not address any of the context issues with linked content I speak of or any issues with large input files :).


text:
How often can the reviewers correctly guess the identity of the authors when the review is double-blind?
Is there any research/study/survey/dataset that looked at how often the reviewers correctly guess the identity of the authors when the review is double-blind?
I am aware that the answer is likely field-dependent, or even publication venue dependent. I am mostly interested in computer science, machine learning and natural language processing, but curious about other fields as well.

I would guess in pretty much all the cases where it isn't the first publication by the authors within the subject area.

Are you interested in if they blatantly disregard the blinding process and actively search for the author's identity or simply be asked to "guess" the identity after completely an rule following review.

@StrongBad both

If the research area is niche, the odds are pretty high!

Conferences in programming languages are moving toward double-blind reviewing, and since the idea is debated, people are collecting some evidence, including actual peer-reviewed papers.
In particular, even when reviewers believe they guessed the authors, it turns out they are sometimes/often incorrect, as profmartinez’s answer suggests. In the citations you’ll find actual numbers; I won’t attempt a literature review myself.
Links

A short FAQ
This points to this literature review (done as an editorial in SIGMOD, a database venue):
This in turn cites Fisher et al. (1994), published in the Journal of the American Medical Association — hence, a peer-reviewed publication where reviewers understand statistics well:
There are also reports from program chairs evaluating statistically double-blind reviewing, by (for instance) surveying PC members for correctness of their guesses.

+1 for answering a reference-request question with references. Great answer.

After many program committees, I've come to the conclusion that we grossly overestimate our ability to guess authors based on the content of a double-blind submission.

I agree with this. One journal I review for "unblinds" on acceptance - on one where I was near certain, I was wrong, and I missed the work of someone I know personally.

I consider it my duty as a reviewer not to get distracted by irrelevant data like authors, so I just check the paper as is. I'm sure that with a bit of guess work (and a fast search or two) I'd be able to identify most of the authors, I deliberately try no to do so.
Most areas are really closely knit, you'd be able to identify a colleague by manierisms in writing, approach elected, results used (and papers cited). And give a good shot at identifying students of colleagues, at least up to advisor.

The following paper presents findings from a recent investigation at three major Software Engineering and Programming Languages conferences (namely, ASE, OOPSLA and PLDI 2016).
Claire Le Goues, Yuriy Brun, Sven Apel, Emery Berger, Sarfraz Khurshid, Yannis Smaragdakis: Effectiveness of Anonymization in Double-Blind Review. CoRR abs/1709.01609 (2017)
During the review process, the reviewers were urged to provide a guess if they thought they knew an author of the given paper.
On the percentage of papers where a guess was made:

For the three conferences, 70%–86% of reviews were submitted
without guesses, suggesting that reviewers typically did not believe
they knew or were not concerned with who wrote most of the papers
they reviewed.

On the correctness of guesses:

When reviewers did guess, they were more likely to be correct
(ASE 72% of guesses were correct, OOPSLA 85%, and PLDI 74%).
However, 75% of ASE, 50% of OOPSLA, and 44% of PLDI papers
had no reviewers correctly guess even one author, and most reviews
contained no correct guess (ASE 90%, OOPSLA 74%, PLDI 81%).

On the effect of reviewer expertise on guessing:

We conclude that reviewers who considered themselves experts were more likely to
guess author identities, but were no more likely to guess correct.

On the effect of (correct and incorrect) guesses on paper acceptance:

We observed different behavior at the three conferences: ASE submissions were accepted at statistically the same rate regardless of reviewer guessing behavior. [...] OOPSLA and PLDI submissions with no guesses were less likely to be accepted (p <= 0.05)  than those with at least one correct guess. PLDI submissions with no guesses were also less likely to be accepted (p <= 0.05)   than submissions with all incorrect guesses.

Summary:

We find that 74%–90% of reviews contain no correct guess and that reviewers
who self-identify as experts on a paper’s topic are more likely to
attempt to guess, but no more likely to guess correctly.

Probably every time. Anyone that admitted to breaking the blinding though would probably face some serious negative repercussions, and so I wouldn't expect anyone to speak up or respond to a survey that would allow a good study to be done. I've never deliberately broken the blinding on a double-blind review, but I've certainly received papers that were improperly blinded where the true authors were obvious just from looking at the title page, so I had to send them back to the editor/program chair as unreviewable.
I know of no studies about this.

Thanks. "I wouldn't expect anyone to speak up or respond to a survey that would allow a good study to be done." -> sure the study could be retrospective, i.e. once the actual review process is over.

@FranckDernoncourt, even if promised anonymity, would you answer such a survey truthfully if you had managed or tried to break the blinding?

I agree there would be some bias. Many surveys encounter this kind of issue, e.g. https://www.amstat.org/Sections/Srms/Proceedings/papers/1996_162.pdf , I guess that's life :)

Guessing the authors' identity is so normal that a PC surveyed his reviewers to see if their guesses turned out to be correct.

@Blaisorblade, is that true? I never try to guess since I respect the ideal of double-blind review in attempting to reduce conscious and unconscious bias against underrepresented groups in paper review.

@BillBarth: "Trying to guess" is indeed discouraged, but that's different from "guess" (as in, reading the N-th paper on topic X associated with researcher Y, and automatically guessing this paper also comes from Y). I certainly meant the latter, which is hard to avoid. References in my answer; in particular, the PC survey is here: https://www.cs.umd.edu/~mwh/papers/popl12recap.pdf.
And this FAQ from our conferences distinguishes "guess" from "seeking out information on the authors' identity".


text:
How much time do professors have to do research on their own?
As part of their job, professors have to take care of getting funding, prepare classes, advise students, fulfill administrative tasks and attend to various meetings/conferences.
How much time do professors have to carry out research on their own (i.e. excluding the above-mentioned tasks)?
I am especially interested in the field of computer science > machine learning, in the US, in an averaged-size university.
I am mostly looking for studies that try to quantify how much time professors have to carry out research on their own.

Professors don't write papers, professors write grant proposals :P

It depends on the field. For pure mathematics and theoretical physics, professors suppose to have more time for their own research.

Not enough - that is to say, not as much as he or she would like.

I found this small-scale, not randomly-sampled survey from Boise State University:
Warning:

All charts below are from TAWKS Phase 1 Stats, initial survey of 30
  higher ed faculty from Boise State University. While findings are
  highly suggestive, they do not represent a random sample.

Answer to question:

Only 17 percent of the workweek was focused on research and 27 percent
  of weekend time.

Graphs:

I'm a little confused by the first graph. I wonder why professors spend a greater proportion of their time travelling at the weekends? Also, what is "Professi..." that only seems to take up time on Fridays? I so hope it's "Professing".

@DavidRicherby - they probably spend the same amount of time in transit, but their total hours are fewer on weekend, so it takes bigger percentage of graph when fewer hours are scaled to the same height. But that's just my guess, could be completely off the mark.

@DavidRicherby Just a guess, but I'm thinking "Professional Development"?

These charts seem to suggest that professors are a bunch of loners who read emails all day.

@DavidRicherby Nothing strange with that -- most conferences are Mon-Fri, so the travel often takes place during the weekend.

@FedericoPoloni Oh, because travelling to work (i.e., getting to the office each day) doesn't count as work time, but travelling for work (e.g., going to conferences or travelling to a different campus to give a class) does. And the very limited sample size means most of the people they talked to have conferences that run Mon-Fri, compared to most of the conferences in my field which are 3-4 days and only involve one day of weekend travelling.

The answer is going to vary greatly depending on whether the professor is in a tenure track, has already obtained tenure or is in a contingent/adjunct position.
Besides these issues of rank, it also matters a great deal what kind of university/college we are talking about. If you're a tenure-track professor in the so-called "R1" institution, you will surely be spending significantly more time doing research than a non-tenure, contingent adjunct at a community college.
The size of the university generally matters much less than individual and university rank.
On top of all that, it often comes down to the individual professors' interests and ways they conceive of their career.

To add to your answer, this is even greatly variable by sub fields within a general area of scholarship. i.e. ubiquitous computing research is quite different than critical design in the broader field of HCI.

I read your second paragraph as -    if institute A is a pure research institute (i.e. only PhD's and post-doc's - extreme example - IAS, Princeton, NJ) and institute B has {research + normal teaching activities (UG, PG) - example MIT or Harvard}, then people get more time for research in A than B. Valid observation, in general. +1 for this. However, productivity isn't that absolute. IAS is notorious as far as I know. Still +1.

The National Center for Education Statistics in the United States surveys faculty of post-secondary institutions (see the National Study of Postsecondary Faculty page for information on methodology). The most recently available data is from their 2004 survey, with 26,110 respondents across the United States.
The NCES allows you to create custom tables from this dataset using the PowerStats tool on their website. (You have to create an account to use the tool.) This is a valuable tool if you're interested in exploring these and other statistics.
As per user20959's answer, time spent on research varies quite a lot by academic rank:

and by institution type:


text:
Why do some Universities give honorary degrees?
Most of the question is the title: Why do some Universities give honorary degrees?
E.g. the President of Indonesia, Sukarno, got 26 honorary doctorates, and Zimbabwe’s president Robert Mugabe has been awarded around a dozen honorary degrees.
What is the benefit for the Universities? Donations? Political leverage? Genuine attempt to give to somebody the recognition he deserves? If last option, why calling it a degree instead of using a more general term like award/medal/etc, like some other Universities do?

Related: How does a university award honorary doctorate?

There is some history at http://en.wikipedia.org/wiki/Honoris_causa that may be illuminating.

Might be helpful to differentiate even between honorary degrees. E.g., are these degrees given to a dictator by a university within the country vs. by universities which are "independent" and widely acknowledged for their scientific work. BTW, I think Mugabe has lost a couple for human rights violations.

Benefits to the university include donations, drawing important people or celebrities to give commencement addresses, and publicity. I'm sure genuine attempts to give recognition are a factor at least some of the time :)
Here are some data points:

Higher ed writer Tim Johnson asked the University of Vermont for a list of honorary degree recipients from 2002-2012, and how much each of those people has contributed to the university over the last decade.
Of the 60 recipients, 35 were on the record as having made donations to the university, for a total of >$13.6 million for an average of $228,248. (Excluding one degree recipient with an outsized $9 million contribution, the average was $68,854).
According to the chair of the UVM honorary degree committee, it's not only a thank you for a donation:

Gary Derr, UVM’s VP of executive operations and chair of the university’s honorary degree committee, defends the practice, explaining it has to do with recognizing individuals for outstanding achievements or service to the university, state, nation or world. A degree is not, he insists, just a thank-you for writing a fat check.

From the New York Times:

"Sometimes they are used to reward donors who have given money; sometimes they are used to draw celebrities to make the graduation special," said Arthur E. Levine, president of Teachers College at Columbia University... "I've always viewed it as a last lesson a college can teach, by showing examples of people who most represent the values the institution stands for," Dr. Levine said.

An unusual benefit mentioned in the same article:

Chapman University in Orange, Calif., awarded an honorary degree to the author John Fowles after he agreed to let it create a writing center and literary festival in his name.

Similarly, former George Washington University President Stephen Joel Trachtenberg reports that "people have asked for an honorary degree in exchange for a donation" but adds

We also give honorary degrees to people who don’t give us a penny. It's just because their lives are exemplary.

Another potential benefit to universities is publicity. Reportedly, when Southampton College awarded an honorary doctorate to Kermit the Frog in 1996 (commencement address here),

31 newspapers picked up the story, a free marketing bonanza that raised the college's profile and drew hundreds of new admissions

Of note: honorary doctorates are an easy offering for diploma mills, since they don't have to pretend it's about anything but money. Here are some examples:

The University of Berkeley Online offers honorary doctorates for a minimum "support honorarium" of $2,000.
The Los Angeles Development Church & Institute awards honorary degrees for "a simple, one-time donation of $89." You can get the degree in a wide range of diverse fields, including Ufology.
The Abundant Life Bible College and Theological Seminary recently offered honorary degrees for a limited-time offer of $85, down from the usual $150.


text:
Is it allowed to ask for help in community for thesis?
I'm writing on my master's thesis. A specific part causes some troubles and I hadn't any progress here for several weeks.
I'm now considering to describe my problem, my ideas and my accomplished work so far in detail in a community and ask there for help.
Would that be plagiarism, if I got some help from the community? So I would be using someones idea.
The thing is, my problem is very domain-specific, so I can't really generalize it and ask at anonymously.
My adviser already tried to help me, but still I'm not really making progress.

I'm afraid that I'm having a hard time understanding what you are asking: is this a question about plagiarism, or a question about the Academia.SE policy (which should go on meta), or something else entirely?

@jakebeal: No, it's not about Academia.SE. It is a general academic question on how to deal with help from the community.

Being "stuck" for several weeks is typical. Read more, think more, and let things percolate in your head. MS theses and PhD theses are not like homework projects or even term-long projects. Indeed, part of the benefit is the encounter with a new (larger) scale of effort.

It is certainly fine to ask for pointers to a solution to your conundrum. If somebody does give a solution to your problem, you should ask them for complete contact details and cite it e.g. as the SE post and personal communication from the author.

Plagiarism is when you use other people's ideas and fail to give them credit.  So if you make it clear that an idea came from someone else, and credit them appropriately (with a formal acknowledgement or a citation), you will avoid plagiarism.
Of course, in order to be acceptable for a degree, your thesis will still have to contain a sufficient proportion of ideas that are your own.
Before discussing the details of your work with others online, you should ask your advisor whether it's a good idea to do so.  It's possible that your advisor specifically wants you to work out certain parts for yourself.  Another concern is that sharing your ideas increases the risk that someone else will carry out your research before you do - in most cases, this risk is outweighed by the benefits of sharing, but your advisor needs to agree.


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Motivating students when teaching a widely disliked course
There is a general tendency of students (master's or less) to rate highly those courses that create a value for them at the industry. For example, in CS, networking or OS courses are found to be attractive by many students simply because these are (almost) indispensable for most job interviews. It is difficult to find the same kind of enthusiasm for say, an optimisation course.
Another example from ECE will be courses pertaining to electromagnetism. Students generally love VLSI-based or telecommunication courses and ignore or dislike the ones on EM. Similarly there could be subfields in many areas where research has stagnated and relevant courses do not carry industrial value, but it is impossible to exclude them from the syllabus.
How does a professor teaching such a course sustain the interests of the students? How does he/she make the best out of a bad job?

The enthusiasm that students have for particular courses is heavily influenced by the instructors of those courses, and varies significantly among departments.  Networking and OS courses are not popular in every department.

I worked so hard trying to get out of taking OS when I was an undergrad.

I had a Electronic Devices and Integrated circuits course which was highly dependent on the Professor teaching it.

There are many ways to motivate students, including but not limited to

showing practical relevance of the course
explaining what makes the teacher passionate about the subject
linking the course topic to their own experience
actively engaging the students in discussions
giving the students adequate tasks and providing them with rapid and positive feedback (adequate = not too difficult and not too easy)

Some tips and tricks can be found on http://serc.carleton.edu/NAGTWorkshops/affective/motivation.html

+1 - for showing practical relevance of the course. If the student knows "Why" they need to learn something (other than in order to get a good grade) then that will motivate a lot more of them. IOW, make use of "I worked on a project at company X where we had this problem and we used this equation and give some details."

I hate to resort to youtube but:
http://youtu.be/WgWNQVdhE9A
Channing Robertson at Stanford teaches Intro to Chemical Engineering which is essentially a glorified way to say Mass Balance and Stoichiometry. It is literally a course on converting values from Metric units into English units. It is literally a course about realizing that what goes in a box must come out of the box. It is dry and boring material.
As described in Why do so few universities offer OpenCourseWare videos of their lessons?, not every class is worth making an OpenCourseWare video but they did for this one. He kills time with stories and lots of them. He goes into the history of chemical engineering. He teaches use the Socratic method. They do problem sets and then go on field trip to see what their problem set was about. It may be dry stuff but at least it would be entertaining.


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Is a co-advisor a good solution if my advisor is not very familiar with part of my research area?
I am currently a 4th year PhD student and have no publication so far. I switched project after 1.5 years after realizing I don't want to have a PhD in that topic.
The new project is really interesting for me. I feel much more motivated and believe I have the analytical skills to solve it. The project is composed of two parts: image analysis (A) and machine learning (B). Eventhough my advisor is very knowledgable about the first part, he is not familiar with the other part, which is actually the most important cue to solve the problem.
That results in lacking of general research guidance from him. He would points me to unfruitful direction, and when I present literature's approaches he is not interested in. A metaphor is that like doing programming big project without the knowledge of data structures. Would a co-advisor be the best solution?

It sounds like there are two related issues:

convincing your advisor about the directions you want to take
finding someone to talk to about your research directions.

For the first one, I'm not sure what you mean by "he's not interested". Does that mean that your advisor doesn't want you to pursue directions even though he's not familiar with them, or that he's not giving you rousing encouragement ? If you have a direction you think might bear fruit for your problem based on your literature scan, why not try it out and show him the results ? Since you imply that your advisor is an expert in the application domain (image analysis), you should be able to demonstrate the quality of the results even if he doesn't fully understand the methods being used. Or is it that he is requiring you to follow certain directions and does not want you to follow other directions ?
For the second, a co-advisor is one possible outcome, but even a colleague in the relevant area (another professor who could be on your committee, or even a fellow student you can brainstorm with) might suffice. You didn't indicate whether your advisor is aware of his shortcomings in the techniques area (ML): if he is, then he might even be able to introduce you to the right people, thus opening doors that might be difficult for you to open yourself.
as always, talking to the advisor would help. You can approach it as "I'm looking for some extra help in topic XYZ: do you know who I could talk with ?". Of course, how you approach this precisely depends hugely on the interactions you currently have with your advisor.

While our groups are really good at feature selection (image processing), we are not familiar with learning algorithms beside simple one such as kmeans, nearest neighbor. To be able solve the problems, we need to use more sophisticated algorithms such as graphical models, deep learning etc. And while I propose these directions, my professor usually steer me out of those directions. He has a tendency to use "intuition" to solve a problem and find really simple solutions, not mathematically rigorous approach.


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What to write in appeal for a rejected PhD application?
I have applied for PhD scholarship in Computer science at a European university. My master is from Malaysia. Unfortunately, my application has not been selected (only 9 has been chosen among 116 applicants).
The email I received informs me that I can file an appeal form attached against the decision made by the committee. Although having a form is supposed to be helpful, I have not written such an appeal before and am not sure what to write. The form is one page (A4) and five lines of it starts with

I expose

and I have to fill the five lines and other five lines start with

And therefore, Kindly ask you for.

The question is, what should I write here? I have no idea about appeals and their justifications and consequences. The only thing I can add since my original application is that another paper has been published. I really believe I am very strong candidate for the program as it conforms exactly to my research area (which I had published two conference paper in).
My question is therefore, what and how to write in the two sections of the form if I decide to write an appeal?

The reason everyone is focusing on whether you should write the appeal or not is because with the information  you have provided, there is really nothing that could go into the appeal. I get that rejection hurts, but you need more than "I got rejected" to appeal their decisions.

To be fair to the community, yes, you did say: "The question is, what should I write here?" But you also said: Any advice would be highly appreciated.

@J.R. and the first thing I mentioned in my update is Although all answers and efforts are highly appreciated .... I just need to understand what can be written after (I expose) and (therefore I kindly ask you for). I would say 80% of the answers have not touched this.

@hawk - I noticed that. Nonetheless, the words Although..., I am afraid that... don't come across as sincerely appreciative.

user45756 is correct: there is nothing here to inform us why your decision should be appealed. That's why nobody can really give you useful advice here. You need a convincing reason why the admissions committee's decisions should be reviewed. Simply saying "I'm a strong candidate" is not enough; there needs to be a procedural reason that motivates it.

RE: update 2, it looks like you have answered your own question. Don't send the appeal form, but just send a short and polite email asking them to provide feedback on your application, so that your application can be improved in the future. It comes off as much less aggressive, and your reputation will not be damaged.

I edited out the "updates" in this post because they were more (no longer ongoing) discussion than clarifications of the question; for future readers, discussion-y updates distract from the actual question.

You don't say why you are appealing the decision.  If only 9 out of 116 applicants got a scholarship, then it is overwhelmingly likely that they turned down many strong applicants.  Do you have a good reason to believe that your application is stronger than the 9 who received the scholarship?
I hope you're not under the impression that simply not having received an award is grounds for appealing the decision.  What if all 107 unsuccessful applicants appealed the decision?  The program would surely have to reconsider having an appeals process or perhaps even giving out the scholarships at all.

My reasons I have exposed in my statement. It is impossible to compare my application to others as I know nothing about others applicantions

"It is impossible to compare my application to others as I know nothing about others applications."  Right -- so that means that you do not have any reason to think that the scholarship decisions were made improperly.  If your question is "Why are they telling me that I can appeal the decision?", it depends on the university and probably even the country, but it seems to me the most likely answer is simply that that university/nation has, or feels it has, a legal obligation to tell all applicants that they can appeal any scholarship decision.

In other words, the people who actually made the decision are likely to be different from the people who insisted that the legalese about the appeal go in all the rejection letters.  Please think about how much trouble you would be making for people who read the applications if you file an appeal without yourself thinking that you've been wronged in some specific way.  Note also that such an action is not necessarily without consequence: in many academic fields the "community" is small and you could get a reputation for being "difficult" by doing something like this.

With all due respect, it is allowed to me to appeal, and I think they also will consider the trouble I went through sending my certified paper documents. My question is about what to write about, not if I have right to write or not

@hawk It is your right, but it is not necessarily wise or effective.  I would think situations where an appeal would help are very rare indeed.  I've been assisting some time during my PhD handling e-mails from scholarship candidates for a Master programme, and I can say that in the days/weeks following the decision, we received A LOT of e-mails from candidates 16-150 (assuming 15 scholarships awarded to 150 eligible applicants... hmm, perhaps that's why they needed minion help ;).  I couldn't tell anyone anything they didn't already know (except perhaps #16, if one of the top-15 dropped out).

I think it is legitimate to at least kindly ask to see the accepted students' applications. As the OP states, you can't know if they have selected worse candidates than you, because the whole selection process is not transparent enough. I wouldn't fill in an appeal form for this request, though. A kind, motivated inquiry via email will do a much better job.

@FedericoPoloni Really? I think that it is wildly inappropriate to ask to see the accepted students' applications, or even request their names (unless someone tells you personally). The most I would do is to email them and ask why I was rejected, but I would hesitate to do even that.

@FedericoPoloni I strongly believe that would be very far from legitimate...

@FedericoPoloni: In most European countries it is illegal in most cases for admissions committees to provide such information.

Asking to see other applications would be asking for a privacy violation. However, I think one could ask the question in a more generic sense. The committe might be able to reveal something like, "An accepted candidate typically has a 3.85 GPA, graduated in the top 5%, and has published at least three papers," or something along those lines.

The appeal form is likely for situations when you feel that your application had strongly misrepresented your abilities. For example, you had some examinations recently re-graded and your grades were notably increased. Or you had previously been accused of academic dishonesty but have been cleared of blame.
You cannot expect the admissions committee to thoughtfully reconsider all the other 106 unsuccessful candidates as well, as I'm willing to bet most of them feel rather hard done by as well.

Exactly, I was half way through typing something very similar.

How about I have some conference paper has been published recently? (I mentioned it was presented in my application but not published yet)

@hawk Unlikely. Publishing a presented paper is simply a "continuation" of your career, so to speak, not a misrepresentation. Your current research being very similar to the program you want to get into may not be the huge boon you think it is, either. Research groups usually like to bring in people with a good diversity of skills. I don't mean to dishearten you, but the Dunning-Kruger effect is always something to keep in mind as well.

I am a little confused as to what circumstances you're suggesting that being cleared of academic dishonesty would be grounds for an appeal.  Isn't the OP applying to a program in a different country?  If s/he turns in an application to another country's PhD program, that application says s/he is under investigation for academic honesty, s/he does not get scholarship consideration specifically because of this, and s/he is then cleared of blame then...s/he gets to appeal the scholarship decision?!?  That doesn't make much sense to me.  Rather s/he should feel free to apply again later on, no?

To be honest, I am having trouble of thinking of any plausible situation in which an external scholarship candidate could know that an appeal would be reasonable.  Maybe for a program which has a documented history of gender/ethnic bias?  Are there (m)any such programs nowadays?

@PeteL.Clark As you might be able to tell, so am I ;). I just wrote down the only two things I could think of that could really be cause for an appeal. Discrimination might be a valid reason, but there are two problems still: (a) how can you prove gender discrimination on a case-by-case basis (historical statistics could tell a different story), and (b) appealing to the same committee who discriminated against you might not get you very far!

I don't understand.
Are you certain that you would have been better than at least 107 other applicants? Are you able to demonstrate it? Or do you have strong evidence that somehow your application was discriminated against/overlooked? (Information of this kind is what should be in an appeal form)
I also don't understand the format of your appeal form. The appeal form already have the words "I expose"? If you are writing it, it sounds very accusatory, and it probably won't win any extra points for you.
Having two conference papers is pretty good, but I don't think that it is exceptional in computer science. Which conferences were they published in?

The committee knows that I have no clue about the other applicants. What is the point of offering writing an appeal. My conference papers one published in IOP journal and one IEEE. Any these words (I expose ... etc) are part from the appeal form they provide. They are not written by me

Well, here is a scenario in which you could file an appeal form. Your classmate A gets the scholarship, despite the fact that you have more papers, and your referees and A's referees tell you that you are much better and that you should have won the scholarship instead of A (and they are willing to vouch for you). Judging by the information that you have provided, you don't have any valid grounds on which to build your case.

@user45756 I doubt that scenario would be grounds for an appeal. If all of those facts were represented in each applicant's respective application, the decision would likely have been made on other grounds (such as personality, interview performance, or a desire to bring greater diversity into the research group).

@Moriarty OP didn't mention anything about interviews. Personally, if senior academics told me that I should have won the scholarship instead of A, I would go through the trouble of an appeal, just in case. But I wouldn't expect to reverse their decision.

@user45756 There was no interview, just online application and then certified paper documents sent

Here's what I would ask: is there anything you could include in the appeal that you didn't already include in your application?
You mentioned that you have published two papers. Did you mention that in your application? If so, that you don't really have any new information to give them – that is, you have nothing to "expose."
However, if that information was not included in the application for some reason (perhaps because you applied before the papers got accepted, or because there was no place on the application form to mention such accomplishments), then I would advise you to go ahead and file an appeal. Mind you, I'm not saying that your chances of success would be very high, but this might be one of those situations where you wouldn't have much to lose.
If you decide to appeal, I would recommend keeping the appeal short and too the point. Too much rambling might come across as quibbling, and probably not help your case. Simply mention that you have something new to mention, and that you would appreciate it if they would kindly reconsider. Don't say, "I think I'm a strong candidate;" let your academic record speak for itself. And only inclide information that was not part of your original application; otherwise, you risk irking the committee. (I can imagine three folks in a room, looking at your paperwork with ire and disbelief, saying to each other, "There's nothing new here – why is he wasting our time?", or, "Which part of ‘No’ does this fellow not understand?")

They might also be thinking — If only we could award some more scholarships, it's a shame we have to turn down a strong candidate because other candidates are even stronger.

It is also OP's fault if he did not mention the published papers in his application; papers are an important part of the application, and he should have realized this much, much earlier! I doubt that papers getting accepted after the application deadline is grounds for appeal either. He should have been more on top of things, and make sure to submit to conferences where the papers could have been accepted by the deadline.

@gerrit - Not outside the realm of possibility at all; hence, the last sentence of my third paragraph. I think we agree: this seems like a serious long shot.

The most likely scenario would be if there was some sort of conflict of interest on the admissions panel. But that would just lead to reconsideration. It would be very unlikely to actually lead to overturning the decision.

I would say, do not waste time on the appeal. There is no shame to loose the competition when only 9 from 116 applications are selected.
Learn that you can from this rejection (maybe some feedback have been provided) and write the next application. And one more later.