text:
Should one (if possible) report Professors for plagiarism
It has come to my attention, that some of the professors I studied with as an undergraduate, plagiarized their lectures.
In some cases, it was word for word. In fact, they did not even explain it any better or add anything, merely translating or in some cases just copying the original text.
The books in question were not cited as a source for the lecture, rather as a suggestion of additional "literature" for the lecture, most of the time, among many other suggestions, and not on top of the list.
I reside in Germany.

Short answer: no unless the instructor claimed the material as their own “creation”.  In fact in some situations sticking to one or few textbooks - which presumably have been proof-read and edited by professionals - is an entirely acceptable option.

It is not clear whether the professor has used lecture notes to produce some "publication" or whether the lecture follows something published. Either way, I do not see any issue!

There is no expectation that lectures consist only of original work. (Otherwise, most of us lecturing would be doing a very poor job). Embedding others' works and good examples is just part and parcel of creating good lectures. If I prepare lectures, I often read many books and some journal articles. When it comes to writing the slides, I would have difficulties finding the correct attributions. After years of teaching the material, the provenance of the material taught can become difficult to reconstruct.


text:
Research approach for PhD thesis in Taoism: top down vs. bottom up
Originally I conceived of posting a "Roadmap for researching x" but I assume that would be too localized for this site.
Background: After much dilly-dallying, I have finally zoned in to pursue lifetime in Taoist research. I have studied mathematical philosophy, cultural anthropology, symbolic logic and enrolled in Eastern studies class for next semester. I understand the professor for latter class would be an excellent source of reference but currently semester is closed.
Problems facing: As I learned in English class it is important to take copious notes during research even if it means 24 hours so I am currently photographing everything that pertains to Taoism. But due to the complex nature of the subject itself and the concept of wu-wei, action in non-action, I am unsure as to how to approach research. I understand if I pursue degree in this field I should familiarize myself with the language and journals and pretty much everything that is related to it. This brings me to my original point:
Question: What would be a good strategy to do research on Taoism? Do I conceive of a thesis and work downwards from it? Or do I start from the scratch - so to speak- and bootstrap my way to a knowledge base. Problem with latter and given the complex nature is if I start with no thesis, then it would be an aimless wandering. But- then again, isn't that what Taoism is all about?
EDIT: In lieu of JeffE's comment below I am rephrasing the original question:

During a research, is it a good idea to start with a working thesis as early as possible?

You're presenting a false dichotomy.  One does not work only bottom-up, nor does one work only top-down.  Rather, one balances between the two approaches, first pursuing one and then the other, as the sun pursues the moon.  The Tao moves in endless cycles.

You are quite right. I wanted to also add: "or both". I am editing the question in light of the comment.

In general, I agree with JeffE. Both top down and bottom up.
In the case of Taoism, there is more - how proficient is your Chinese?
You said pursue lifetime in Taoist research. I am not sure you can do that without knowledge in Chinese language equivalent to at least masters degree in Chinese.
Taoism is rooted from Laozi's original text Daodejing. Reference Taoism. Most native Chinese speakers do not understand that text. If you want to conduct life time research in Taoism, that book is a must read and must understand. Without fully understanding that text, you are at best a second class researcher in Taoism.
I am a native Chinese speaker. How much do I understand the text? Less than 5%. If I spend 20 years or more on it, I might be able to understand 80% of it. Actually, I am bluffing. Some people contribute his whole life in it and then claimed that he only understood less than half.

Somebody pointed to me after reading my answer that I should have used "proficient" instead of "fluent". I am not sure. Would anyone provide opinion?

Fluent is normally used for conversation (as it 'flows') proficient would be more appropriate in your context. That said, your point is an excellent one. Understanding the subtleties of a key work takes amazing language skills and the effort for that should not be under-estimated.

I can't help at all specifically on the Taoism part, but as an answer to your final question:

During a research, is it a good idea to start with a working thesis as early as possible?

You are talking about a thesis, and posting here, so I presume you want to do research in academical environment.
In my experience, you have Bachelor and Master years for establishing a broad knowledge base and identifying your interests.
Once you start as a PhD student, you get a research topic, but since it is research, it is subject to changes. The topic was defined before you actually immersed in the subject, so while you are working towards that goal while pursuing your thesis, the goal can change as you learn new things.
Oh, and you really don't need to familiarize yourself "with the language and journals and pretty much everything that is related to it" before pursuing a degree.
Note: The precise names of stages and the line between broad and focused research might be different elsewhere, but I think both phases should exist. In case you're aiming to start directly at a "focused research" phase, my (subjective) advice would be to take some time before to do some broad research on your own.

source: Stack Exchange

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

sort: votes


text:
will a lab feel deterred from hiring me if my undergrad thesis is in a different subfield?
i've interned at the same lab for two summers, and they highly encouraged me to apply for a research assistant position in the spring. however, i am concerned that they will not hire me based on my undergrad thesis topic.
the lab focuses on developmental neuroscience. i conducted research in the neuroanatomical etiology of autism spectrum disorder in children during the school year. but, my senior neuroscience honors thesis is on neuropolitics, technology, and radicalization. i love developmental neuro, but i'm fascinated by neuropolitics as well, and i was wondering if these dual interests are a deterrent at this point in my career.
any feedback is welcome and of help.

Since you have some history there, it seems very unlikely that such a thing would be a detriment. In fact, it might be viewed as positive that you aren't "too narrow" in your education and outlook.
But, it is up to them and you only learn by applying.
And picking a topic for such a narrow reason as obtaining a short term internship would be, I think, a mistake.

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


text:
Presenting skills in a presentation for a PhD position
I've got invited to a PhD interview in the field of computational physics. In the invitation mail I was told, among other things, that I should present my skills for about 5min. It is my first interview and I'm quite unsure how I design this part of the presentation. I thought about presenting the main skills for the position, where I learned them and where I could use them so far. But I don't know how to design the slides for this part. I would assume that it is pretty boring to simply listing them or shouldn't I do any slide at all for this part?
Thank you for any help and suggestions in advance!

If in doubt about such things it's always okay (and in fact strongly advisable) to ask the place that invited you!

Perhaps you should organize it around things you have done and then mention the skills it took to accomplish that. Projects undertaken, research done, ...
Some things are more nebulous. Do you read a lot in the field, and take (and organize) notes, for example. What have you written? What sorts of organizational skills were required for that?

Organize like crazy, five minutes will fly by. You want to leave your audience with a sense of your style and maybe an interesting nugget.

You should have a slide or a few slides and you should not be worried about a list being boring. They specifically asked for this list! What they want to know is whether you know enough to hit the ground running and complete a project. The content is what matters and will be interesting to the audience.
There are ways you can make a "list" slide more visually interesting, if you want to do this. For example, you can have each new bullet appear as a pop up as you advance the slides. A slightly more advanced version is to "blow up" the new bullets so they are larger or "zoomed in", but keep the old bullets on the same slide in a smaller font.
Anyway 5 minutes is a lot less time than you think. I would not focus on "where you got the skills" -- that will take time from describing your skills. But, you should try to be as specific as possible about what your level of experience is. Reread the ad for the position and play up any experience you have that is related to the description (use the same words if you can).
Since it is a computational physics position, here's an example of the bullets I might make for a slide (I am completely making up at the kind of experience you might have)

Research / problem solving experience

Completed project P and produced result R
Skilled at debugging and testing my code
Independent problem solver and worker [I would include this and the previous bullet in some form, and you do want to give an example for both]

Computing experience

Proficient in X, Y, Z languages
Used A, B, C software packages in projects
Limited experience with version control
Run several jobs on a cluster for a research project

Relevant courses

Computational physics
Python programming

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


text:
Salary determinants for faculty at public schools in the US
A follow-up question to this as I feel it is very broad. For example, consider this link displaying the salaries at a particular department in a public school in US.
I see very wide variations within assistant professors. Some assoc. profs earn lesser than asst. profs; people of the same age earn differently and so on. So, my question is, which of the following factors influence salaries at public schools and how?

Age
Experience as a faculty member
PhD at a top school
Number of years after undergrad/PhD
Experience at another school (Does a Stanford faculty with 5 years exp. moving to a public school earn more than a faculty member at the same school for 5 years?)
Number/Impact of publications
Any other factor

Given all data is in public, I assume there can be no pay negotiations, so is it possible to determine one's salary in advance before the interview process itself?

Which factors influence salary ? All of them.

There are indeed negotiations, despite the fact that the data is public.  It's impossible to determine one's salary in advance.  Some public universities have fixed salary scales, which sound like they should determine the salary, but they don't.  (There's always some flexibility about which step on the scale one should be hired at, and there are usually further adjustments that are possible.  This is by design, since nobody believes a fully deterministic system could work well.)

In addition to @eykanal's list, there are several factors that can lead to salary variance even within a single department:

Negotiating ability — Some profs are simply better at negotiating for better salaries than others, even with comparable publications, funding, students, teaching evaluations, etc.  Conversely, some people have lower salaries simply because they don't realize they can ask for more.
Time in the department/time since PhD — All else being equal, the longer you've been here, the higher your salary.  But as usual, all else is never equal.  In particular, faculty hired with more post-PhD experience are generally paid more.
Performance — In most departments, faculty are reviewed annually, if only very lightly, to make sure we're doing our jobs.  Salary is one of the few levers that department chairs have to reward faculty who are doing exceptionally well, or motivating faculty (especially with tenure) who aren't (seen to be) pulling their weight.
Offers from other institutions — This is one of the biggest sources of salary jumps.  If a valuable prof in your department starts getting offers from other places, you department is very likely to raise their salary to keep them.
Administrative bonuses — Faculty who hold significant administrative positions (like associate head, or chair of the undergraduate program) often get a salary boost.
Variance in the job market — New assistant profs are generally hired at the prevailing salary rate for new assistant profs.  Departments do not collaborate explicitly, but information does flow through applicants who get multiple offers.  For example, about 10 years ago, a top-rated US CS department (not mine) decided to significantly increase its salary offers to new profs, to gain a strategic advantage over other departments.  It didn't work; other departments (including mine) just raised their offers to compensate.  It took several years to correct the resulting salary inversions.
Variance in university budgets — When times are good, faculty get raises.  When times are not so good, faculty don't get raises.  These times do not necessarily align with fluctuations in market rates.
Intramural politics — Academics are human, and subject to human failings.  Everyone who reaches a position of power arrives with their own agenda; sometimes that agenda favors certain people or groups over others, for reasons that are more personal than objectively fair.  In some departments, fights over limited resources can be ugly and brutal ("because the stakes are so low"); sometimes that ugliness is reflected in salary differences.

Do you have thoughts on how to negotiate well, particularly within academia?  It's easy to find articles on the web about "how to negotiate", but are there specific wrinkles for academics that these articles often miss?

Also: Other people in the department. For example, some departments may be mindful of what their female vs. male faculty are paid, etc.

In the US, everything you list above—and more—can affect salary. (Do note that, in the US, age discrimination is illegal. Not that it doesn't take place anyway...) The only thing I'm not sure of is "number of years as a PhD", that's more of a proxy for "work done during PhD tenure", which is included in the impact factor.
A few factors I thought of, not likely exhaustive:

Masters/PhD/postdoc alma mater
Masters/PhD/postdoc advisor
Number and quality of publications
Grant history
Existing grants
Collaboration history
Teaching experience
Field of research (psych vs history vs engineering vs etc)
Type of institution (public/private)

Economic environment (budget cuts in state funding, etc)

Teaching load
Location (Dallas, TX vs Palo Alto, CA vs etc)
...?

Note location may not be your location. For example, professors at WSU (WA, USA) enjoy relatively high salaries because professors at UW need higher salaries to afford Seattle.

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


text:
Is "working from home" a bad thing in academia?
Is it a bad thing in academia if a student works from home? Missing department talks and seminars is obviously bad, but in case a student is pursuing a problem alone and he feels comfortable researching at home, is it viewed negatively? At times the time spent on travel and a crowded lab may disrupt one's flow of thoughts, so in those cases home provides an edge.
Is physical attendance deemed important by the department as long as they are kept in the loop regarding your progress?

Most likely, there is now difference between academia and jobs like programming, graphical design, editorial work, etc. So general advices + http://productivity.stackexchange.com/ should apply. What does make the question academia-specific?

@PiotrMigdal Because it is. One of the hallmarks of academia is occasional flexibility, and there is a world of difference between academia and freelancing/contract work ala editorial work or graphic design.

@EpiGrad For 'normal jobs' there is whole spectrum from 'you have to work a home' to 'you have to do all work-related things in the office'. Without a further specification, the answer will not differ much for one for a specific non-academic job.

@PiotrMigdal True, but first it's not just a productivity question, but a cultural one, and second, academic work is just different at times. I've worked as both a freelance creative professional and a grad student - the problems and choices are different, even if the desk layout ends up the same.

@EpiGrad Now I see it, thx.

See also: http://academia.stackexchange.com/q/7698/1033

The answer is it depends - both on the student and the culture of the department.
There are of course some situations where working from home is impossible - graduate programs that are heavily lab based come to mind. Below is a summarization of my thoughts from a more data analysis driven field, having done both.
Positives

Lots of departments these days don't have lots of graduate student space. While some labs might have dedicated bench space, and there may be an RA/TA office or two, there's not "a place" where students can work anyway, which makes "is it bad to work from home" something of a moot point.
Working from home benefits certain work styles. If you're the kind of person who prefers to work in a spread out, sprawling fashion, with multiple monitors, tons of stacks of paper, and a whiteboard or two, that's just not feasible in most grad student offices, even when they do exist. And when the only spaces that exist are transient ones, like shared desks or cubicles, library study areas etc. you also can't customize your work space at all - and expensive textbooks and laptops are theft bait.
It facilitates more flexible schedules. Universities tend to be closed at 3:00 AM. I tend to do my best work at around that time. This seems to be relatively common in academia, and as academia seems to promote an "always working" lifestyle, having a single centralized space you have access to 24 hours a day is nice.

Negatives

You do lose out on departmental interactions somewhat. The concern about missing seminars is I think a bit of a non-issue. Those are easy to miss when you're working on site, and can be attended with just a little bit of diligence on the part of someone working from home. What I've found missing more is the transient, passing in the hallways interactions. I realized, for example, one day that I had gone several weeks without talking to anyone about  my field. That's not good. It also does some harm to cross-polination and ideas from unexpected places.
It can get lonely. Seriously, this seems to be a major challenge. It's possible, and the workload sometimes promotes, just disappearing into a cave.
It's possible to get distracted, as it always is working from home. "Real life" has infinitely many things to take care of, and its much easier to defend "work time" if you're at an office. But then unless you have an office its easy to get distracted in a department where your friends and colleagues are around.

Overall, I wouldn't say its bad. I know successful academics who work almost entirely in their office, and who work almost entirely from home. I'd say the best way to promote on-site work, if a university is trying to accomplish that, is not to focus on the bad parts of working from home, but on addressing what makes it appealing. I finally moved entirely to a working from home setup because I got tired of "work" involving camping out in cramped spaces, without the materials I needed, fighting for power outlets.
As for whether or not your physical presence is important to the department - it depends on the department. I've known some who don't care as long as you show up to what you need to, and others that absolutely want you there, and subtly penalize those who aren't around.

As this relates to students, I feel it is extremely bad to work from home regularly. Being a grad student is not about being efficient, or even learning to be efficient. It is about learning your subject area and making contacts. Working from home means you miss interactions with your colleagues. You will be judged by your senior collegauges both in terms of your productivity and percieved work ethic. No department sets out to hire people who they know will predominately work from home.

Not necessarily. With the way that some departments are rapidly running out of physical real estate, they may even appreciate students who chose to work in their dormitories, homes, or libraries. (Of course, there is a barrier where one's work needs to be able to be performed at those locales, which of course rules out lab-based works in the experimental sciences.)
When I was a graduate student the department actually sent out an e-mail to all students asking students who intend to work mainly from somewhere apart from the department building to declare their intention so that they can more efficiently assign (the very limited) office spaces. But this was in a math department and eccentricity seems to be more tolerated there.


text:
What should I do if I have found a major error after a year of postdoc work?
After my PhD, I continued with a postdoc in my PhD lab. The topic and the numerical method was quite different than my PhD and I had to read up quite a bit of literature to start the new work. However, as I was also involved in other projects as well, I took around nine months to complete the work. While writing the paper, I have discovered that I have done a major mistake in my simulation parameters and model. The work cannot be published unless I correct the mistakes and run the simulations again which would take at least a month more.
I was asked to submit the manuscript for review by the advisor and other collaborators by next week. However, now I can't write the paper with the errors. And I have to rerun the entire work again.
What do I do now? I am almost a year into my postdoc, and I shouldn't have made such errors. How do I approach this and what do I tell my advisor and collaborators?

The situation obviously isn't ideal, but there doesn't seem to be much we can help with. There aren't many ways to say "I found a mistake and I need more time to redo some of the work", and it seems like you already know you need to let the other people know and fix the mistake. Based on your title, I assumed the error you found invalidated the entire year of work (or your PhD). Simply having to take a bit longer doesn't seem like a huge deal (unless you'd miss a once-a-year deadline or something, but you still wouldn't really have options). Also note: your advisor is there to advise you.

Bad news doesn't get better with age, so don't delay in letting people know what's going on. But, speaking from experience, this kind of news is not as bad as you think (you found the error even before your collaborators even saw the paper!). In a few months, people will not remember this.

If the mistake you found was a natural mistake, and the finding of the mistake reflects deeper knowledge gained over the course of the year, perhaps that part of the research could be salvaged. Good papers have been written dissecting bad models.

If you find a mistake now, that's a lot better than finding it later after everything has been published, as then you would have to go through some rigmarole of withdrawing the article and so on.

could you throw more computing power at running your simulations? Might not be cheap but this is an ideal use case for cloud computing (assuming your simulations are parallelisable).

Sometimes when coding software, I would later discover that my discovery of an error was itself an error. So first I would say be sure you indeed have an error.

It's always best to find errors as early as possible. You've found this one before rather than after publication, so that's a big win. There's nothing magical about any step in one's academic career that makes them immune to making errors: everyone makes mistakes, no matter how many degrees they have or years of experience or papers they've published. It's a fair bet that the most senior researchers have made the most errors, simply by having had more time to accrue them.
Let your advisor and collaborators know what happened, and start running the corrected simulations as soon as possible. If you can update them with a timeline of when it would be feasible to submit the new results, then do so.
They may be disappointed by the delay, but they'll prefer this rather than having their names on a paper with a fundamental flaw.

I think this is the best advice you will get. You have to "fess up" and do it over. Science is hard and not all tries lead to success. If it were easy, then no one would want to pay us so handsomely to do it. Research is fundamentally looking into the unknown.

"So that's a big win" - excellently put. The error didn't make it into publication. Note that Michael Atiyah, one of the mathematics greats of our time offered a flawed proof of Riemann. It happens to the best of us. If you can fix it by just one month more work, that's another win, not every error can be fixed that way.

@Captain: Let me (in part because of my deep esteem for Atiyah) suggest a more purely inspirational story: Andrew Wiles first announced a proof of Fermat's Last Theorem in 1993.  This proof was (valuable but) wrong.  In 1994 he fixed it.  Thus one of the most lauded mathematical achievements of our lifetime was done wrong before it was done right.

@PeteL.Clark Indeed, good example. It was not at all out of disrespect to Atiyah, but to demonstrate to OP that errors are possible and part of the endeavour. Einstein had several wrong versions of general relativity before he got it right. We do not know of what category OP's errors were, but integrity, honesty and trustworthiness is the highest capital of a scientist, and fixing a recognized error is part of that.

Sadly I've met many researchers of the mind that it's better to find the error after publication. This way they get to publish two papers instead of one: one paper with the error, and one paper to fix it.

@Stef do these types not think it looks bad in the long run? If someone looks up such a professor, wouldn't they notice that quite often they're publishing fixes to papers they rushed? And not truly publishing new papers each time?

I fortunately can not claim to know any such researchers as @Stef describes. If I did, I would also have lost respect for them a long time ago, and so would likely everyone around me.

@Stef In math, accumulating a reputation for rushed results will become a major problem for the particular scientist. In other topics, not so much. Nonetheless, it's in the end about r/K selection. Each scientist needs to ask which one do they want to be?

@BruceWayne I guess? I don't know. I assume that depends on the domain, and the kind of error, and the frequency at which this happens. I would guess it's also different between journal papers, with a rolling submission process, and conference papers, with a deadline.

@CaptainEmacs The example of Wiles is in a very, very different ballpark from the example of Atiyah (who also claimed short "proofs" of Feit-Thompson, complex structures on $S^6$, etc.).

@Carl-FredrikNybergBrodda Indeed, it was Pete who mentioned Wiles, I originally didn't, because a reasoning close to yours, but forgot about that when I agreed with Pete.

@CaptainEmacs I think you misunderstand me. I don't think that the Atiyah example is a good example for illustrating mathematicians being incorrect and offering flawed proofs as part of their working lives.

@Carl-FredrikNybergBrodda Ok, I didn't get that. I think it is an example where probably overconfidence played too strong a role, but I still think it is relevant to OP.

This happens, and you just have to deal with it. A year and a half ago, I discovered a mistake I had made only after spending approximately 15 CPU years on computations. It led to a delay of about 6 months in the paper, during which every core of my collection of computers was busy recomputing the statistics I needed -- but at least I had confidence in the correctness of the submitted material.
In practice, the delay is often not terrible because only the computer is working on re-doing all of the calculations. While it's doing that, you can focus on the next research project, and once you have the new numbers, whatever little work is necessary to adjust the tables and graphs in the paper. In other words, little work is wasted, just time.

I have made plenty of mistakes in my career. Some real doozies. And I have been witness to many mistakes made by colleagues. I have found that confessing to the mistake and accepting blame and responsibility turns out the best. Even in cases where blame could be shared if you accept blame, apologize, and be honest it works out better. People will tend to attack someone who is defensive and tries to blame others. That's when they really pile on. Sure they will be frustrated and disappointed. But if they see that you feel bad and are working to fix it, they will have more sympathy and be more on your side.

There are already several good answers to the broader question, I just wanted to focus on the run-time aspect:

The work cannot be published unless I correct the mistakes and run the simulations again which would take at least a month more.
I was asked submit the manuscript for review by the advisor and other collaborators by next week. However, now I can't write the paper with the errors. And I have to rerun the entire work again.

Not knowing the nature of your work, I have no way of knowing whether this is an impractical suggestion, but - is it possible to reduce the rerun time by parallelising your workflow? For instance, by asking your colleagues to run some of the simulations on their own computers, or renting some cloud computing time?

@carterjack, the community at stackoverflow would be eager to help optimize and speedup your processing.  In addition to GeoffreyBrent's suggestions, a few broad ideas for your consideration are profiling your code execution, reducing memory overhead, optimizing loops and functions, and minimizing disk reads/writes.

There's a silver lining to your dark cloud, but only if you 'fess up: by admitting your mistake you are announcing to the world that you can be trusted and are a person of integrity, even under potentially embarrasing conditions.


text:
How can I tell if I'm making enough progress when working remotely?
I am starting a PhD abroad, but due to the COVID-19 pandemic I cannot leave my country at the moment. My advisor has agreed that I can work remotely (starting later is not an option). While we can Skype and most of my work can be done online, I am concerned that having no access to the department, not being able to attend seminars/workshops, and not being able to meet/talk to other students in person will put me at a big disadvantage.
I am keen not to spend these initial few months slacking off and want to catch any problems before it is too late. However, I have always found it difficult to judge my own progress when studying alone, and with a PhD it seems that it will be especially hard as I need to learn a lot of skills in a new area. Also, because my advisor seems like a very 'nice' person who does not demand that his students work very hard, I am concerned that he will not tell me if I am underperforming.
Would it be appropriate to raise this with my advisor, asking him to tell me if I am not doing as well as his students usually do? Or are there any strategies for people working from home to judge if they are doing enough?

I am also a PhD student working at home for two weeks now, as everyone else too. Your situation seems to be more special as you never really arrived and you seem to be quite far apart. But I can somehow relate, the research conversation, the talks/seminars, none of them anymore. But (what essentially I am doing now), take a few questions related to your research and write it down, in paper style. When you think you have finished something to a certain degree send it to your advisor. Discuss it, in skype, or by email. Keep things going! Keep your mind busy!

I work in theoretical stuff, so paper+pencil is all I need (+literature access). Might be harder when you have lab work to do. But maybe then focus on that what you can do at home/the more theoretical stuff.

Asking your advisor how you can improve and to help you find alternatives to whatever you're unable to access (the in-person contact, in this case) is usually better than asking how well you're doing. Never ask if you're not doing well (that's needlessly negative), and try to avoid asking how you compare against others. Your goal should only be to do as well as you can.

Yes, you should raise this issue, both with the advisor and with the university administration. Students need some feedback on their work and it is the university's responsibility to provide a way for that to happen. They need to provide the channels and you need to find a way to use them.
But things are in a bit of chaos now, of course, and effective response can be slow to occur.
Virtual seminars are possible using simple or sophisticated software. Perhaps you can set up (or the university can) a group of students and a professor or two willing to have an online session regularly. It isn't the same as face to face, but it can keep you engaged.
But at a minimum, write a lot and note where you have problems. Ask a lot of questions, but make sure they are pretty focused. Share what you write with your advisor, by email or by posting it somewhere.
Ask your advisor directly how you are doing and ask explicitly for next steps. You will most likely get suggestions about reading. Take a lot of notes on the readings and note things that puzzle you. Ask about them.
If you are starting the research phase of the degree it is normally a fairly solitary effort in any case, but the advisor should be willing to review and respond to your efforts and your questions.

Under the circumstances, I would not worry about whether you are working "enough".
Indeed, under these circumstances, many universities (in the US, anyway) are presuming that many students and faculty are unable to work effectively. For example, many universities have either changed all grades to pass/fail for the term (see here), or else are allowing students to switch to pass/fail grading until the end of the term. For faculty, many are delaying tenure clocks by a year (see, e.g. here).
If your advisor is usually reluctant to make demands, or tell people that they're underperforming, then he will be even more reluctant now. I don't think you can realistically have this conversation now -- it's up to you to set your own standards and work towards them as best you can.
But I would certainly recommend being in communication with your advisor: ask his advice; ask questions about whatever you're studying; discuss ideas for research projects; and the like.
One thing you might do is ask to have a regular weekly Skype meeting, where you talk about what you've been reading recently. This might help to keep you on task.
Best wishes!


text:
How should I tell a professor the answer to something he doesn't know?
Last year, I asked my physics professor a question that he did not know the answer to. This year, while doing a research paper, I also figured out the answer to the question I asked him. I want to send an email to my professor explaining the answer I found simply because he's a curious guy.
Typically, if I asked something that the professor didn't know, I'd email them a few days later saying:

Hi Dr. Professor, after some reading, I figured out the answer to why so-and-so happens. Here's what I learned.

But since it's been so long, he definitely doesn't remember what I asked him. So I'd like to remind him what my question was. However, writing:

"Hi Dr. Professor, last year I asked you a question that you did not know the answer to, and this year, I figured it out. Here's what the question was, and here's what I learned"

sounds a bit insulting to me, because I'm writing that he didn't know the answer. What is a good way to share an answer with a professor without being "insulting"? Am I just overthinking this?

Just a mini nitpick / quick heads up that "Hi Dr. Professor" would be a non-standard greeting. If in doubt, always stick to "Dear Professor X,". (Hello and hi usually work too but some professors would consider it too informal.)

@user2705196 in which country?

"Hi Dr. Professor" would definitely be unusual in North America. And most of Europe that I'm familiar with.

@user2705196 I think there's a chance that the OP was just using the word Professor as a placeholder for the person's surname.

Welcome to Academia.SE! You may want to check out these two Meta question and answers. (For context, meta.SE is where users can discuss the running of the stack overflow network. Discussion there often helps us moderators guide policy.)

Don't obsess over it. Just. Do. It.

Seeking, but not having an anwer to some things .... is that not a scientist's job?

Use "we". "We did not know the answer to."

@user2705196 I know this is a culture thing, but I can never understand how "Dear" is more formal than "Hello". It just feels too intimate to me, like I'm writing a love letter.

@Vaelus - Well, there's always "Esteemed."  (You should see how formal letter greetings look in German!  Priceless!)

@Buffy. Exactly. It looks like from many answers there that faculty staff are some kind of deities. The prof was interested, OP found the answer - a simple email is great.

I'm dumbfounded by these answers. Not one says to ASK HIM OR HER!  "Dear X, this is Y, do you recall we were discussing Z? Since that time I found an interesting solution, would you like me to forward it to you?"

I think there is an easy way to phrase this to make it tactful, after all professors are often curious about learning new things too!

"Hello Professor X,
  I hope you've been well! Last year I asked you a question and we couldn't figure it out at the time but I've since come across an interesting answer and just wanted to pass along the info just in case you're curious. We were discussing Y ... "

I would suggest to replace 'last year I asked a question' with 'last year we discussed a question/[or problem]..'

I would also open with a compliment. Something like "Dear Professor X, I really enjoyed your classes last year....", then go on to mention the question and answer. This will serve to positively frame your question.

Depending on the professor, you might also say something like "You've probably already found the answer, but I only just discovered  that explains it and wanted to share it with you just in case."

Depending on the field and on the person, even a basic compliment like "I enjoyed your classes" would be too much and considered a waste of time. And "you've probably already found the answer" could even sound rude to some (as if your question was supposed to be important). I especially look the maths/CS and physics way :)

If you're going to take 3 lines before getting to Y I hope you mention Y in the subject. Being nice is one thing but get to the point.

I agree with Greg. It's good to be polite, but not good to be self-disparaging. Treat your professor as an equal and they will respect you in return. The suggestion in this answer is good, but the comments are way overboard.

As an alternative to Juan's answer (roughly in the same spirit), I suggest that you can phrase the email regarding the issue itself--since presumably the professor would also be interested in knowing the answer to the problem. Something like the following should suffice.

Hi Professor XY, recently I learnt about [...], which seemed really interesting to me because [...]. If you recall, this is similar to what we discussed a while ago regarding ABC, which is what prompted me to look into this further. I thought I would send this to you in case you happened to be interested in it. Have a nice day!

The point is to focus on the part which the professor would also be curious about/interested in, and to not dwell on the fact that they weren't aware of the answer beforehand.

I find this answer more tactful than the chosen one.

@RuiFRibeiro While I agree, I think perhaps the professor would be more likely to dismiss this version because it starts with discussing the new information without indicating why this would be relevant to the professor, so it may only make sense if the information discussed is implicitly of interest to the professor.

The polite way to do this in academia is to pose it as a question.  This way, you show your humility.  You acknowledge that the solution or answer you found might be flawed or incomplete.  Also, you open yourself up to collaboration.

This is a great answer. I totally agree that it makes sense to phrase a solution as a question not just for politeness but for scientific reasons because there'll often be a discussion about whether the solution actually answers the question!

I think this is unnecessary. The OP is saying that much later he/she discovered an answer to a question that both admitted not knowing at the time. There is no reason for humility.  It would be different if the prof was put on the spot and the OP knew the answer.

@Cell - Humility is a habit.  The person I have dealt with who had the most humility was my advisor -- and one might have thought he had the least need for it.  But it was inherent to his character and his whole outlook on life.

I would say: pose it as a question if it is actually a question.  If the OP is sure they've found the answer, and they are just sharing it to potentially satisfy the professor's curiosity, there's no reason to frame it as a question.  Posing it as a question is the same as asking for a favor: to read through and verify the OP's solution.

"A few years (semesters?) ago we were discussing the issue of _____ and the specific problem that ______. I recently came across something that brought the topic back to me and discovered that ______. I wanted to share that with you and to see if you have heard of this as well."
This way you are making it something of mutual interest and still being respectful.

There are two risks here:

Sounding insulting (as you have noticed)
Being boring (by bringing up some trivial thing from a year ago)

You should avoid both, because there is nothing to gain from emphasizing them.

Dear [name], lately I've been working on my current [paper/research/assignment] and here's some updates on how that is going. We can talk in more detail in our next meeting.
Incidentally, I ended up learning [thing], which we had discussed in the past. It was interesting to find out that [implication].

I think this is a better answer than the accepted one because:

Doesn't remind the professor that he "didn't know" (if it's been a year since, you may even be remembering wrong and perhaps he did know)
Doesn't sound petty by referencing something from a year ago
Isn't wasting his time with some random thing that hasn't been relevant in a year
Sticks to relevant, pertinent things that matter to the work that's here and now, not ancient history

There is of course nothing wrong with discussing history. Sometimes there are unanswered questions that linger for decades or centuries before spurning great discoveries when their time comes. But a productive researcher should maintain focus on priorities. If this thing from a year ago was that important, a year ago wouldn't have been the last time you discussed it. So one has to wonder, if nobody's cared in a year, why should anyone start now? I think answering that question is the most constructive direction to go here.

I wrote the above assuming you have a relationship with the professor already. If you are talking about an undergraduate instructor, the same principles still hold, but a better example template could be:

I have decided to work on [problem], and I wanted to share my findings with you. I actually became interested in this problem due to a discussion we had during our [class]. I have found that [answer], which is [implications].

I would add a dimension:
The amount of time spending  on the problem:

Your professor probably thought a few seconds / minutes about it
You probably spend minutes / hours and from your text

This year, while doing a research paper, I also figured out the answer
  to the question I asked him.

it even sounds that it wasnt your main purpose to answer the question, but you found it while working on a research paper.
So you could include that in your text:

Last year we discussed an interesting question to which we didnt find the answer "ad hoc". I just wanted to inform you that i stumbled upon a clue towards the answer while working on a research paper. In case you are curious,....

I am XXX. Last year, we couldn't figure out(state the problem that the professor did not know the asnwer). While reading (State the source of your answer so he can refer to) this year, I realised(state what you found). I just thought it would be nice to share with you.
Kind Regards
XXX

Hi and welcome to Academia.SE! Could you please expand your answer to better explain your suggestion? As is, it may not meet the quality standards of the site.


text:
What should I do if a paper's theoretical justification isn't right, but the method based on that justification works?
This is a problem that comes up every now and then when I am asked to review a paper.
In my old field of research (robotics), papers straddled the line between creative problem solving and theoretically sound science. The general layout of all of the papers is to first provide a scientific reason that your method should work, and then present the method and any tweaks you had to make in order for the actual engineering problem to be solved.
Many times this led to a dubious scientific background and leaps of logic.
Here is an example: A paper might be about an algorithm to solve X problem. X is something that humans do naturally (for instance, grasping a delicate object without breaking it), so logically one would go to the scientific literature to find out how humans do it. The paper would then include a detailed and theoretically correct background section into the biology that governs human abilities. Then, the paper would include a big leap in logic that is not supported by the actual science, and that leap in logic would be used to justify their algorithm. Authors would state this leap as though it is an established scientific fact, when in fact the science is either unsettled or their conclusions are wrong about the biology.
The problem is that the algorithm does in fact work when tested on the engineering system (a robot, in our continuing example). It just doesn't actually have any significant resemblance to the biology that the authors claim it was based on. So really the issue isn't that the algorithm is a bad one or that the testing and data were fudged; it's that the justification of the design didn't follow from the evidence presented. If it weren't presented as though it was decided fact I wouldn't even think about it.
In addition, it is highly unlikely that, if I were to ask the authors to justify their results better, they would be able to do it—the science simply doesn't support it, but they tinkered with it enough that it works.
What would be an appropriate response here?

Coming in to Mechatronics (Engineering) I can tell you that there are orders of magnitude more examples of this to be found in design 'justification' in Architecture programs...

It's appropriate to respond just as you have here: criticize the unfounded motivation and ask that the authors present their paper without it. For example:

the authors suggest that humans and other great apes navigate diverse terrain using wheels, however the authors do not support this assertion with appropriate citations to the literature on human physiology, and it seems to conflict with evidence that apes in fact use legs. Therefore, while their horse-drawn wheeled cart does seem like a promising logistical solution, I recommend that they remove any suggestion that this solution is biologically motivated unless the authors can provide sufficient references for their assertions.

As a neuroscientist I must say I very much sympathize with this problem, and occur it regularly on other Stack Exchange sites as people confuse what is known and useful within artificial neural networks with what is known about biological brains and neural circuits. However, while it's understandable to encounter these issues among learners in a field, it's not something that should ever make it into published papers.

I've never personally encountered something like this (and it's pretty unlikely in my area), but I think it might make sense if the authors say that whatever algorithm they have is inspired by some biological phenomenon, even if there is no rigorous way to derive one from the other. This is of course very different from what OP seems to describe, which looks to me like bad, misleading science.

I want to point out that it's not just misleading science, but it has effects outside of academia as well, as someone can then go point to this robotics paper and claim chimps are doing wheelies in the jungle, and they would have gained some ethos doing so.   The fact they would have a paper, that may even have a bunch of people citing it makes it hard for the people on the ground to argue against things that are not just speculative, but flat out wrong.   We see this all the time with climate change.

For example, oten when we see this in climate change, since there's so many different disciplines working in the field, what actually happens is someone, working on something that will help reduce energy usage, or use clean energy, will say something about a prediction that was never said by an actual climate scientist or paper, and then climate change denialists will then go use that paper as a source for saying "See, obviously the world hasn't melted by 2020, so clearly all of this is bunk!"

I remember reviewing a paper about a database model for doing search and query on music. The problem was that the musicology was completely flawed, in fact it was essentially dreamt up in the researcher's head. But I was relying on my own extremely limited knowledge to recognise that. So the only thing I could really do was to tell the editors that the paper needed some expert musicological input.

I would just ask the authors to rewrite that part to ensure the science is correct, and state the algorithm is inspired by the biological aspects of human abilities.
This is how researchers in the bio-inspired (nature inspired) meta-heuristics research areas approach the problem; FYI, these researchers design algorithms that mimic biological processes.

See also: Genetic Algorithm - "a metaheuristic inspired by the process of natural selection"


text:
Should authors omit statements / citations of well known results in response to referee requests?
I am asking this question to get further perspective on an issue that has come up with a student (undergraduate, mathematics) I am mentoring.  At last summer's REU he wrote (in particular!) a solo paper.  I was not directly involved with the research, but I gave him some feedback on the writing before he submitted it for publication a few months ago.  He has now received a referee report, which is very positive and is of the sort that I would recognize as being 99% likely to lead to acceptance.  The referee requests revisions, many of which I agree with.
However, one of the referee's suggestions is for the student to not explicitly state two well-known theorems that he is making use of.  (In case it helps to know, these are Dirichlet's Theorem on primes in arithmetic progressions and Minkowski's Convex Body Theorem.)  The referee follows up by saying that even if he does want to state them, he should not give citations to them, since they are so well known and google searches easily turn up references.
My questions:
(1) How would you respond to this referee request if you were the author?
(2) How would you advise a young student to respond to this request?

I have added a link to clarify the meaning of the REU acronym, which may be unfamiliar to readers. If I did not pick the intended meaning, feel free to revert the edit, but please insert a link to the intended explanation.

If it were my paper, I'd leave the citations in the paper, explaining to the editor the reasons for doing so, but adding that, if (s)he really insists on deleting them, then I'm willing to comply.  That should remove the danger of getting the paper rejected over this minor issue.  (The relevant insistence would be the editor's, not just the referee's.)

Are the citations to the originals or to textbooks?

@Noah: The citations are to number theory textbooks.

Three brief comments: 1) The fact that I know (roughly) what both those theorems say probably means that the intended readers of the paper really don't need their statements. 2) I find the referee's suggestion of giving an explicit statement without reference bizarre.  More typical practice would be the opposite, in my experience.  3) I would advise the student to follow the referee's suggestion to leave out explicit statements (assuming my comment #1 is correct).  It's just not important enough an issue to make a big deal out of.

One thing to keep in mind (although it need not apply here) is that it's sometimes necessary (and often helpful) to know the precise formulation of a well-known theorem that is used -- there can be subtle differences in assumptions and conclusions that would trip up a reader looking at the wrong formulation. For this reason, I tend to give references wherever I can, although I would only include the full statement (with citation!) if I a) expected that most readers would have to (or want to) look it up and b) wasn't already pushing the page limit...

I would recommend approaching a referees recommendation to drop a citation in the following manner:

First, consider carefully whether there is good reason to keep a citation in the paper at all.  The key factors to consider are reading audience and the customs of others in the field.  For example, in cross-disciplinary work I have often cited extremely basic material because core dogma known by every undergraduate in one field are sometimes viewed as nearly unbelievable statements in another field.  On the other hand, students in particular are sometimes prone to over-citation because they have been well-trained in citation and decide to err on the side of caution.
If a citation is warranted, consider whether to use the primary source or a textbook source.  Notation and interpretation change over the years, and for purposes of elucidating a well-known result, a readily accessible modern text is often a much better citation for the reader than a difficult to find or understand original.  In certain cases, however, returning to the original is important: for example, the standard interpretation of the Turing test is different than what Turing originally proposed.
Whether the decision is to keep the same citation, change the citation, or drop it all-together, in responding to the referee one should explain carefully why one made that decision.  I would be startled if a paper could be imperiled by deciding to keep a citation when a referee recommended dropping it---it's just such a minor issue, all things considered.  With a careful explanation of how the choice has been reconsidered and the final decision, most referees are likely to be sufficiently satisfied, even if they might have chosen differently.

Bottom line: no paper is going to be put in peril by a few extra citations as long as the author is reasonable in explaining their decisions.  The citations might ultimately get dropped or not, but in every case we are talking about "minor revisions" territory and not the boundary between "major revision" and "reject."

Here are my answers:
(1) Erring on the side of being slightly more careful / explicit / wordy has never hurt anyone.  I agree that a large majority of the readers of this article will know the theorems of Dirichlet and Minkowski, but if some do not then omitting the statements signals that the paper is not for them whereas including them makes it much easier for them to continue reading.  (Of course I agree that anyone can google and find the statements of these theorems and it is easy to do so...but it is even easier to put the paper down and go on to something else if your interest was borderline.)  On the other hand, a reader who knows these statements well can just skip them: no problem.  So provided that as an author I had made the expository choice to include these theorem statements, I would not be easily talked out of it by a reviewer.  As to whether I would actually have done this: I have a paper where I state MCBT. I often say "by Dirichlet's Theorem" (more often: "by Cebotarev density"!) and assume readers know what I mean.
In terms of citation: I don't like the idea of a referee talking an author being talked out of citing work that they use in the paper.  It feels like getting pushed in the wrong direction.  I have to admit though that I would not myself cite either of these results, and I do have some sense that if you cite things which are too basic then people start to wonder about your background.  ("No one cites Einstein..."  And Einstein came after Minkowski and way after Dirichlet.)
(2) Not lightly do I advise anyone to do anything which could result in their paper not being accepted.  But in this case I am tempted to advise the student to leave in the statements.  He should respond to the referee: for instance if his response includes other papers published in the last decade by the same journal which include statements of one or both of these results, his case looks strong.  That one should not rewrite papers so as to make them harder to read seems like an important lesson.
I am tempted to tell the student that I would not include these citations and the referee is really correct that they are not needed.  If he does want to leave them in, then maybe he should go "whole hog" and include primary source material.  I haven't seen many contemporary math papers with works by Dirichlet and Minkowski in their bibliographies...but I wouldn't mind at all if I did see them.

I've known a few mathematicians that, when they opt to cite something, insist on citing the oldest, most primary source material they can find.  Even when more modern and accessible versions exists.  I recently cited a result of Remak (early 1900's) in a (joint) paper.  While the result is almost certainly either very well known to group theorists, or considered easy to prove on first sight, no modern reference for the result could be found.  And the intended audience was more algebraists than group theorists.  Thankfully the paper was actually freely available online.

I cited Archimedes once, but it was out of playfulness --- I could not resist! I would advise making habit out of it though :-)

I do have some sense that if you cite things which are too basic then people start to wonder about your background.  There's definitely a potential issue there.  I've seen a paper, written by a student, which stated the Cauchy-Schwarz inequality as a lemma, which struck me as ridiculous.  But it's not obvious to me whether Dirichlet and Minkowski are on the same side of the line as C-S (and, of course, where the line is depends on the paper's audience).

Citations serve two purposes:

Acknowledging the original source of ideas
Giving readers easy access to a source to read more about a result that they may not understand.

In the case of standard theorems that are named after their discoverers and which are sufficiently famous to be in Wikipedia, I don't think citing a textbook accomplishes either of these goals.  It's much faster and easier to google the theorem than to find the particular text mentioned.
I don't think there's any harm in this kind of citation, so I don't know why the referee cares.  But I also don't see a good reason to include them.
If anything, I would cite Wikipedia with a hyperlink.  That at least saves your reader some time.

... and some referees will revolt at the notion that Wiki is a legitimate source for anything at all... (which I think is foolish, but nevermind).

Well I'm sure you've already made your advice by now, but for future reference, here is my perspective.
First, my general philosophy is that one should try to make papers reasonably accessible to young people who have not spent months or years working on this specific problem.  I generally feel that most math papers should do a better job of providing references than they do.
(1) I would hear the referee's suggestions and with those in mind, I would rethink about whether it is worthwhile to include references, taking into account both how well known those specific results are and the target audience (whether I would specifically refer to those theorems of Dirichlet and Minkowski depends on who I am writing to--for a "regular" research paper, I would probably do the same as you).  As a somewhat experienced mathematician, I think I have a reasonable idea of what is worthwhile to provide a reference for and that I can make suitable decisions on my own.  However, referee reports constantly remind me that things I think are obvious or well-known are not obvious or well-known to a lot of people.  Consequently, what one thinks should be included as a reference varies a lot from person to person.
(2) When I was a student, I viewed comments like this from referees and my advisor as learning experiences about what to include and not to include.  I would first of all tell the student (i) you don't have to make all changes the referee suggests but (ii) you should consider them seriously.  However, as people may have different perspectives, and the student has limited experience, it would probably be useful for the student to hear other perspectives (e.g., yours and possibly another colleague's).  After giving your advice/suggestions, let the student decide what exactly to do (as I'm sure you would).


text:
What is a good checklist for last minute changes before submitting a PhD thesis?
I have finished my thesis, it's been proofread by my advisor and myself, yet I have 24 hours to make last-minute changes to it. What should I be looking for? I will not make any substantial changes to the content, but what about the form? For such limited amount of time, where should I focus my effort? Or, said another way: what’s in your last-day check list for a thesis?
Major modifications to the original question. Thanks to F'x for the advice.

First, if you've already proofread it recently, a second try will most likely not help. You won't see the typos and weird sentences anyway :)  I'll advise to focus on specific short parts that can make a difference in the reading. It's also the right time to get someöne else on board to give these specific items a second look (with fresh eyes).
Without further ado, I suggest you limit yourself to checking the following items:
Text
The main check here is not really for typos (although be sure to fix those you will see), but rather for clarity.

General introduction, general conclusion
Introduction and conclusion of each chapter
Summary/abstract, if one is included (sometimes it's written in 10 minutes in a haze, in which case it's worth extra checking in the end)
Acknowledgments, if it's already present (some people only include it after the defense is over). Make sure you're not forgetting someöne important, like your wife or your bonsai.

Figures and figure captions

Quality of the graphics
Do color and symbols mentionned in the caption match the figure?
If you intend to have black and white figures in print, are the figures understandable in black and white? Do the captions make sense for both version (color and B&W)?

Equations
Check your equations. Again. Typos there are typically hard to find.
Numbers & tables
All tables, all inline numbers: make sure they include units, make sure the number of significant digits displayed is reasonable and consistent.
Bibliography
Do not care to much about the formatting: if most of it is okay, noöne will really complain about one or two missing page numbers or lack of italics in one title. However:

If references are hyperlinked (using DOI number), click on each to check that they match the right online paper
If a paper is “in press” or “accepted for publication” or something else, check if it has been published since and update its status

(The starting point for this was my answer to “Examining paper proofs”, but it is now significantly different)

I found the checklist for captions and units in the tables to already be very useful!

+1 for paying special attention to the figures and figure captions. Incorrect captions are easy to miss and one of the more common mistakes, especially if you've been reordering your figures.

Make sure bibliography entries are sound and complete.

Your goal is to present a viable thesis to your examiners so perhaps there is a need to change your thinking about not making "substantial changes". I know this is a difficult call at this late stage but if you discover a gap in your thesis, it is better to address it before submitting it to your examiners, rather than getting the examiners to point it out to you. If the latter happens, you will have to substantially revise your thesis and this will tax you emotionally to say the least.
As for the checklist, I have the following suggestions:

Check that you have really built up your case for the research. Your examiners will not be convinced if you present a flimsy case. Ensure there is a strong reason why you conducted the research (i.e. define the gap in knowledge that you are addressing).
Check that you have actually answered your research questions. I am unsure in which field you are situated but in sociology the answer is often not that clearcut. However, you can still make a strong case for or against your research proposition.
If you have done statistical analysis, make sure you demonstrate that you have a good understanding of what you did (i.e. you understand the assumptions that underpin the technique, for example Pearson's r is for linear relationships).
Check that you have a section (in the concluding chapter) that spells out in black and white what contribution your thesis is making in your field. Often we just assume that the examiners will understand the contribution. We know our research so well (after doing it for 3 or so years) that the contribution is apparent to us, but it is a different story for the examiners.
Demonstrate critical thinking with a blend of personality. This is a bit controversial but your thesis is a reflection of your interests and a little bit of personality in your thesis will not hurt (only a little bit, though as this is academic writing). In my case, I incorproated my experience as an immigrant to explain why I chose to study what I studied.

Remember, you will not get a poor result because of typos (though many typos will create a poor impression), so focus on the bigger issues if you can. All the best!

I like #4, and maybe #5, but I don't think #1-3 reasonably fit in the “last minute” or “last 24 hours” category… each substantial change made at the last minute carries a risk!

@F'x As I said, it is better to correct any shortcoming yourself, rather than let the examiner point it out and then you have to spend a semester or so addressing the examiner's concern. This is time well spent in the final 24 hours in my view!


text:
Is there anything to do while waiting for results of a thesis examination?
I handed in my PhD thesis for examination. From reading the examination instructions it appears that if I get my degree, it could be between 6 weeks to a year. It all depends upon the comments I get back from the examiners.
My plan during that time was continue work on my research, get more results and publish more papers. Also, help out other PhD students in their research.
Considering the time-frame is so variable, is there anything else I should be doing or planning? The only advice I was given, was don't take a holiday.
BTW: I am quietly confident that the examination results I will get back will be positive.

Do you have a job waiting for you when you graduate?

@Paul Availability is always a key issue when considering job candidates.

Why don't you write a PhD memoir? Only one person has done it so far.

What have other students at your university done in similar situations?

@Paul I don't plan on a job until I get my degree.

That is not a great idea, as getting a new position can take some time.

@PaulHiemstra Aren't employers hesitant to accept people when there is no date nor virtual 100% certainty?  Or perhaps they can't even start the bureaucracy before there is a PhD diploma?

I do not specifically mean actually getting a new job, but investing some time in scouting around for possible institutes to work, what are popular grant providers, spend time growing your network into the direction where you want to go. You could be lucky, and find an advertised job just after finishing your PhD, but it doesn't hurt to prepare.

Don't you have some sort of oral exam/defense/viva to prepare for?  Apart from that, I definitely recommend working on getting a job already.  I think it's perfectly normal to start applying already before completing your PhD.  I actually started my first job before I submitted, but most postdocs probably do require you to have the PhD already by the time you start.

What does your advisor suggest?

From reading the examination instructions it appears that if I get my degree, it could be between 6 weeks to a year.

Have you talked with your advisor about the time frame you should expect?  University policies often allow for a wide range of possible schedules, to account for differing circumstances.  The advisor generally has a clear idea of which part of the range a student is likely to end up in (although of course there are no guarantees).
When you reach the point of graduating, there should be little uncertainty left about the quality or value of your work, because your advisor should have been offering feedback and guidance along the way.  If your advisor is genuinely unable to predict whether it will be closer to 1.5 or 12 months more, then it is a worrisome sign (suggesting inexperience or negligence on the advisor's part, or that they suspect something may be wrong with your dissertation).

Considering the time-frame is so variable, is there anything else I should be doing or planning?

I agree with the comments above about job applications.  In the cases I am familiar with (mathematics in the U.S.), academic job applications are due around December, which is typically about six months before graduation occurs.  This includes both faculty and postdoc applications.  Practices may differ in other fields or countries, but it's almost always a good idea to begin looking substantially before you actually graduate.


text:
What licensing concerns are there for using content from Stack Exchange in an academic paper?
All content under Stack Exchange is licensed under a Creative Commons Attribution-ShareAlike license. Does this mean that any academic paper that uses content from Stack Exchange must also be licensed under said Creative Commons?
If not, what is the actual rule on this part?

Essentially the question can be rephrased as, "does using content from a Stack Exchange post make the work that uses it count as a derivative work?"

Another possibility is to segregate lengthy quotations in another file.  If you only need to quote small amounts, you can probably do that under fair use.  If you need lengthy quotations or other data sets, you could have an auxiliary file (with the CC BY-SA license) that presents the data you need, and then you could refer readers to that file in your paper.  This would give you a stable, archivable file that highlights what you need, without letting the license affect the rest of your paper.

Related but not quite a duplicate: http://academia.stackexchange.com/questions/10459/is-it-legal-ethical-to-use-data-grabbed-from-a-stack-exchange-site-in-a-paper

Making a reference to CC Attribution-ShareAlike content is always okay. In fact, referring to any work is okay, regardless of the copyright status. Only content is copyrighted, not bibliographic elements (including author names and title). For example, the U.S. Copyright Office says:

Copyright does not protect names, titles, slogans, or short phrases.

Quoting is a more complex matter. It depends on copyright laws, and thus your country. In most cases, if the material is quoted raw and the quote is kept short, most academic use should fall under the doctrine of fair use. By contrast, read also the article on derivative work to get an idea of these two extreme cases.
This is mostly a theoretical question, however: the scope of fair use is grey are in US Copyright Law, and provided you do it for academic purposes and in a good faith, you won't get into trouble.
Finally: if you really want to quote in a bulletproof way, either (a) consult with a lawyer or (b) ask the copyright holder for a waiver to relicense his content to you.

By "referencing" I meant using content that would merit a citation, not citing in a bibliography. Sorry for being unclear.

(That definition probably carried over from my work in art, where "referencing" somebody else's work means using it as a reference for doing your own thing.)

@Joe it's not really clear what you mean by referencing. But like F'x says, the key issue is whether you are quoting (i.e. copying) the content from the SE site or not.

For quotations that are covered by "fair use" of the copyrighted work, you don't need to get a license. Even if you already have a license to use the work (such as a CC license), you don't need to stick to the terms of the license for this type of usage.
So, even if your paper may be a derivative work, you don't have to apply the terms of the license, and you wouldn't have to put your work under a CC license. As soon as your quotations go beyond fair use, you would in fact have to put your work under the required license.


text:
Ethical nature of multiple post-doctoral applications
I am a student applying in different places for postdoctoral positions and asking various faculties for position. It happened that, due to limited resources, I am not getting much response. However more than one faculty (from different institutes all in Europe) gave positive responses. The caveat is, I have to jointly write a research proposal with them for grant application/some fellowships. Whatever be the outcome of the proposal(s), I am starting my collaboration with them soon.
My dilemma starts here. The fellowships each one suggested are very competitive. Those faculties themselves informed me that getting those fellowships became more difficult in the present financial situation. Now is it ethical to do apply for multiple funding agencies in this way? Fortunately, each of them suggested applying for different fellowships. I am slightly afraid of the morality of the whole issue (like: what if all of the projects get funding). Please help.

There is nothing wrong or strange to apply for several fellowships and funding as you describe. The opposite would mean you have to gamble on one and hope it comes through. What can be a bit problematic is perhaps if each proposal causes a lot of work for somebody in a department if you later is a no show despite funding. In such a case it would be good to let people know you are sending in other applications as well so they are not completely in the dark about your situation. I am sure everyone will be sympathetic. If they are not you may not want to go there anyway.
The risk of getting money from several of your applications seems like a luxury problem. Yes, you have to decide which one to go for but that should be a pleasant problem. I would tackle the problem IF it becomes reality and not worry about it at this stage. Your first step is to get applications in, not worry about what to do when and if any funding comes through.

Let your grant-collaborators know upfront seems like the core of it here.  Writing a proposal with Dr. X and then walking out on them without warning might indeed be unethical; but as long as you tell Dr. X upfront that you’re making other applications which you might take in preference to theirs, they can decide for themselves whether they’re happy to accept that (usually slight) risk, and in that case, you have no need to feel guilty if you end up doing what you told them you might.

Peter Jansson is right, don't worry about that perspective, it may not happen. If it will happen, you'll worry about it; but if it won't happen, you're now worrying in vain. “I have lived through some terrible things in my life, some of which actually happened.” (Mark Twain)

It depends a lot what kinds of grants or fellowships you are applying to. In any case, you have to check the guidelines of the fellowships very throughly. It is not uncommon that you have to indicate if you have submitted a similar proposal elsewhere (stating precisely where). It may even stated that "cross submission" is not allowed.

Who says the other proposals are similar?

Nobody. But it may well be that the proposals have some thematic overlap and often one has to indicate this too.

@gerrit That is a good point. Fortunately for me, that problem did not appear as of now.

You are applying for a job. A prestigious, noble and publicly-beneficial job, but that does not change its fundamental character. And as a post-doc you will do research work, and get a salary for it - just like a Professor, on one hand, and a security guard or cleaning crew member, on the other hand.
Do you think any of them should only apply for one position at a time?
Another aspect of this fact: Nobody will be doing you a favor. They make offers, and you can accept or reject them; just like they get applications and may accept or reject them. Your tone seems slightly self-deprecating - and there's no need for that. You're a (soon to be) recognized Doctor of Philosophy. Stand tall!

It is perfectly ethical and reasonable to write multiple applications because chances are low. In most of cases, you will get only one application accepted anyway and it will be no problems. In unlikely case when you get more than one positive response, it should make no problem to pick that suits for you best.
Of course, theoretically if you are good enough for a position A, you should also be good for the positions B, C and D, if the requirements are similar. However this also depends on many random factors. Maybe you know some method they plan to use in research but for some reason did not state clearly in the announcement. Maybe the professor has (grounded or not) personal opinion that your institution or journal where you have published is very bad or very good. People pre-screening the applications may apply different priorities. Depends a lot on who else has applied for the position. Many things can happen.
Waiting for the solution that often takes weeks at least and significantly reduces the number of applications that are possible to write, creating risks that you will never succeed with any.


text:
What is a "publishable" thesis?
What is a "publishable" thesis?
I have often heard this term thrown about in conferences and even as advice to new grad. students.
From what I know, it is indeed rare for a thesis to be published entirely as a book, though one can publish papers out of the thesis.

In some cases it might mean that the thesis could be published as a book. However, I'd generally interpret the phrase to mean that the thesis could readily be adapted and published as one or more journal articles.

and the conclusions don't make the sponsors of that journal angry... So much of science has become politicised to the point where studies that counter the agendas of major pressure groups may be impossible to publish because there's simply no publication that dares take them on for fear of losing lucrative business deals with other parties that have more money to spend than you.

I assume that, once again, this probably depends on your field and country.
In the Netherlands, apparently, it is required to leave a large quantity (>100) with your university. Also, an ISBN will be assigned, according to my contract. This should mean that anyone could quite easily order a copy. I don't want to know the costs of such an order though.
Sometimes you can also find them on Google Scholar. Although I'm not sure how i will have to proceed to have mine appear there (in years), I like to read them. They usually are well written and give a very good overview of the field in a concise manner. Reading papers to achieve that kind of overview usually takes a lot longer.
This would be my answer to the title question. A well written overview of the work, done during your PhD, in relation to what is known in the field.

In some places, all theses have unique ISBN. In some places, the university issues theses as a series with ISSN. In some places, the university do not care.


text:
Issues with publishing dissertation on an interest/advocacy group's website
I am wondering if it would hurt me (professional creditability etc.) if I publish my dissertation on an interest / advocacy group's website.
My dissertation is in one of the areas that this group has been advocating for a long time. Obviously, there are many other contrary views to the views of this interest group. The interest group is known nationally and, in essence, functions as a political lobby.
I am employed in the same industry, so chose to study in this area from a well respected university. It was easy to identify this gap in knowledge and to address it with robust research.
There has been no issues to date but now that the dissertation is approved, I am thinking of making it more widely available, hence the above option.

Note that if you publish papers in open-access journals that have Creative Commons-style copyright, there's nothing that can stop them from copying your paper. And even if you don't, they can still — either with papers or with journals — write articles naming you and linking your research. I've had a (journalistic style) photograph I've taken end up on a nationalist website, with the website crediting me (as they are obliged to); I'm not 100% happy with that...

I would be cautious. That said, I think there are easy alternatives that don't involve giving up exposure of your work through their advocacy.
If you value credibility as an independent researcher, you will be well served by not being perceived as shilling for any particular organization or political cause. I think the interests of the organization that is requesting permission to republish your dissertation is in line with this. If your research is findings that are politically expedient for them, they benefit from the enhanced credibility that you garner from perceived intellectual independence.
My advice would be something like this:

Publish your dissertation on your own website or in your institutional archive. (If you don't have a website, now would be a great time to set one up!) It should only take a day or so to get set up.
Once you've done that, suggest that the organization write a summary of your work on their website — clearly in their voice — and to link to or repost (if they feel that is absolutely necessary) your work.

You will benefit from the traffic to your website and they will benefit by having your work seem like the work of an independent researcher and not something done by someone inside. And indeed, it sounds like this is exactly the case!


text:
Co-authorship for not very involved supervisor
I have now completed my PhD by research.
I received support from my supervisor in the form of advice on my chapters (for which I am indebted to him; we have a very good working relationship).
The advice mostly related to clarity of arguments. My supervisor was not actively involved in my research and he did not amend or add to any chapters. He just provided broad advice on the contents of each chapter so that I can fulfil the requirements of my degree.
In this case, should I credit him as a joint author in any paper I may publish from my dissertation? I cannot see a case for joint copyright of my work!

What did you agree on before you started working together?  (You did discuss co-authorship standards before you started working together, didn't you?)

I guess it would depend on the field of study.  As I understand it, in engineering, the adviser of a dissertation is automatically included as the last author in papers involving the dissertation.

@JeffE This matter was never raised (I wasn't even aware of it until I completed my dissertation and got some free time to think about the next step from here.) We did not work together in the co-author sense; it was a student-supervisor relationship.

@JoelReyesNoche: ...except in (some parts of) computer science.

@JeffE Sounds quite unusual to me. Did you discuss authorship when you started your Phd?

@FedericoPoloni: Yes, absolutely!  (In theoretical computer science, mere advising or funding is not considered an intellectual contribution meriting co-authorship.  For example, I am not a coauthor on all my students' papers; if anything, I'm less likely to be a coauthor on papers involving their dissertations.  Also, "last author" only means "author whose name is last in alphabetical order".)

This question should be relevant: Supervisors and authorship if not a duplicate.

I'll assume that you have a good relationship to your PhD advisor and that you can have a reasonable discussion with him. If this is not the case, then ignore the following as you will potentially have much bigger things to worry about.
It sounds as if the papers have not been written yet, so I'd suggest you discuss this with him as soon as possible. Lay out to him which papers you want to write, what will be in them, and where you plan to submit them, and ask him if he would like to be a co-author on any of them.
Now, the important thing is that this co-authorship you're offering is not a free ride. I would assume that a good supervisor knows that this will imply a significant contribution to the preparation of the manuscript and/or any follow-up work that still needs to be done. If he is willing to actively contribute to the papers, then you have a bona fide co-author and nothing to worry about.
If your supervisor is not willing to contribute anything to your publications, then there is no reason to add him as a co-author.
In any case, you should be open and honest about your intentions. Your supervisor is a very important person in the critical post-PhD phase of your academic career, and even if you leave academia, he is your previous employer. In any case, he will be writing all your letters of recommendation, so don't do anything that may have a negative influence on your relationship.
In summary: Ask him first, and if necessary, remind him that co-authorship implies active collaboration. If he does actively collaborate, you have a good and valuable co-author, and if he does not, he will either not want co-authorship, or you will have a valid reason not to add him.

I strongly agree, with this answer. Just ask.

Yep. I've had supervisors kindly rejecting authorship in cases where they didn't see it appropriate.

I think this kinds of discussions boil down to if a person has had a significant impact on the paper. This can be in either of the following categories:

conception and design of the project
data collection
data analysis and conclusions
manuscript preparation

These are the categories in the quantitative uniform authorship declaration (QUAD) system (Verhagen JV, Wallace KJ, Collins SC, Scott TR (2003) QUAD system offers fair shares to all authors. Nature 426: 602., or this link for some information). THe QUAD system quantifies what each author has contributed to. Ofcourse, where you put the line when someone is a co-author or not is debatable.
If your supervisor does not tick a lot of boxes, you could put him in the acknowledgements of your papers. Alternatively, if you feel his contribution is significant in either of the above categories, or more than one, add him as an author.
In addition, co-authorships come reasonably cheap. You have collaborated on your project, and you make your supervisor happy with an additional publication. Also, your supervisor is probably more well known in your field of study. If he associates himself with this paper that might mean more attention for your paper, although how valid this point is depends on the reputation of your supervisor.
In regard to copyright, often you sign the copyright of your paper over to the publisher of the paper. Maybe you do not mean copyright, but attribution. You did the work, and adding him as a co-author makes it look like you did not do it alone. If you feel like this, it looks like you feel his contribution has not been significant enough to make him co-author.
A lot of things to consider.

+1 for pointing out that having your supervisor as co-author increases visibility of the result. Still, he shouldn't get it for free, that's certain, but it can influence your decision.

From your description it sounds like your supervisor was acting as a supervisor, not as a collaborator; however without knowing the exact details of his contributions, and what the etiquette/standards of your field are, it would be impossible for us to assess whether or not he should be a co-author. Why not just ask him?
Also, keep in mind that in certain fields it may look bad if your post-PhD publications are all joint with your supervisor - people sometimes assume that means the supervisor did all the work, or question your ability to perform independent research. For this reason, even if his contributions to your work were substantial, your supervisor may prefer to forgo being a co-authour to help your career. Best is to just ask.

+1 Or, if there are several papers, let the supervisor be co-author on some of them. Ideally, I think this co-author issue should be solved by looking at the contributions someone had. Although, both you and me showed some additional things that could be added to the mix of considerations

I know this is quite old, but I am providing an answer as I have experienced something similar recently. Given your description, it looks like you have done the majority (>90%) of the work and, as such, I see no reason why you should even bother with asking your supervisor if they like to be a co-author.
I strongly disagree with Pedro's suggestion, as if you do ask them, they're unlikely to say no (who DOESN'T want to be a co-author on a paper?). And if they say yes, then you have no guarantee that they will do the amount of work necessary for said authorship. In fact, and from my experience, listing someone as a co-author in the hope that they will, along the way, contribute in a way that makes them deserving of that authorship is counterproductive and poor project management. As you said, you've already done the majority of the work - what makes you think that someone who wasn't actively involved in the research will do a good job writing the paper?
PhD students vary. Some of us are self-motivated and know what we're doing and thus require next to no-input from supervisors. Others are not so fortunate and require significant input from supervisors. I see no reason why supervisors should be included as co-authors in the case of the former. Hope it's all sorted now.


text:
List of reputable open access journals
I found a list of "potential, possible, or probable predatory scholarly open-access publishers" here.
I am just wondering if there is a similar list of reputable open-access journals in the social sciences.

I would suggest going about this a slightly different way. The reputation of journals derives from views of scholars in a particular discipline. There are many closed access journals that are not very reputable and many open access journals that are reputable. You can figure out the ones that are reputable by looking at three things:

What journals are being cited in other journals of known reputation? Journals that get citations in other journals are likely to be publishing decent research. This is not a guarantee, of course.
Who is publishing in the journal? Reputable scholars tend to publish in reputable outlets. If a journal has prominent scholars publishing good work there, it's probably a decent journal. This is not a guarantee, of course.
Who sponsors and publishes the journal? Reputable journals (especially in the social sciences) tend to be published by or endorsed by scholarly associations. This is not a guarantee, of course.

Thus, rather than trying to find a list of reputable journals, think about how you would evaluate any particular journal. If you find correct answers to any of the above questions, there is a good sign it is a reputable journal since the idea of "reputation" is a social construction that reflect precisely the above criteria.

The Directory of Open Access Journals (DOAJ) is an attempt to create such a list for all fields, including the social sciences:

DOAJ is an online directory that indexes and provides access to quality open access, peer-reviewed journals.

They have a search function that lets you drill down to specific fields.

DOAJ is a useful reference, but it's worth noting that it's not 100% reliable: building a long list of good journals is much harder than building a list of bad journals.  For example, in mathematics DOAJ includes the "Research Journal of Pure Algebra" (http://doaj.org/toc/5423b3e616b74dac9205ff787f86d0aa).  I can't say for sure whether this is a reputable journal, since I can find almost no information about it on the web, but their entire web site seems to have died with a message of "This account has been suspended".  This is a bad sign, and all the published papers seem to be inaccessible.

OnlineSchools.org produces a list of various open access journals. While I can't say all are reputable, most look like they point to well established and credible organizations or educational institutions.

I am not aware of a list of "reputable" open access journals in the social sciences.  But, as a safe starting point, the most reputable open access journals in the social sciences have an ISI impact factor.

Do you mean reputable or infamous? The vast majority of Elsevier journals have ISI impact factors.

@StrongBad what's infamous about Elsevier journals?

@Jigg how about http://thecostofknowledge.com/

The real problem (and probably the reason for this predatory journal explosion) is that the classic journals have become abusive and predatory themselves. For example Springer/Nature journals will reject your paper without explanation and direct you to one of their fee-paying open access for guaranteed acceptance on resubmission.
Worse, the old classic journals do not do peer review often, make decisions based on profitability of your paper and sometimes take months or even over a year to respond. Some do not ever respond. This includes Springer/Nature which did not respond at all to a submission and did not respond to the inquiry about why they did not respond. So, may be these predatory journals are just as predatory as the old corrupted ones. We may have to switch to the new era.

Welcome to academia.SE. This is a question and answer site and answers are supposed to answer the question. Could you edit your answer to include a list of reputable open access journals, or instructions on how to identify such?