Dealing with dismissive reviews as an editor I am an editor of an academic journal. If I receive a review that makes valid points but is written in a very dismissive tone, what should I do?

I believe that you could: a) Explain to the reviewer that you find his or points valid but would like him or her to rewrite the review so that it is more constructive for the authors and therefore more likely to turn into meaningful edits, or b) find a new reviewer. Either way, I would discourage using this reviewer again, because authors find dismissive reviews discouraging and would especially discourage junior scholars who may have very significant research, but new to writing.


What does undergraduate tuition fund, and how does this differ between public universities and private universities in the U.S.? Does undergraduate tuition help fund professor salaries? Does it help fund graduate student salaries, especially if the grad students are TAs? What about lab facilities?

(This is very much a US centric answer; other countries structure their university systems differently.)

This is a difficult question to answer because money is fungible, so in some sense it doesn't matter what the nominal answer is---if the money isn't going to fund those things, it's filling in other expenses so that other sources of revenue pay for those things.  But in practice, most universities put undergraduate tuition directly in their "General Fund"---a big pot of money, which is then divvied up to support the general operation of the university, which includes all the things you mention.  (Note that many sources of funding for the university are dedicated for particular things, and don't go into the General Fund, but undergraduate tuition usually isn't one of them.)

The University of Michigan has a nice online presentation about this, and as far as I know, that's typical: undergraduate tuition pays into the general fund, which pays for most of the university's core activities.


My Supervisors are not helping in writing recommendations letters Maybe they are helping and I am the one who does not know how things really work and that's why I am seeking help here.

I am about to finish my Master in Computer science (waiting for the oral exam). And this is the time to apply for as many as possible PhD programs. The problem is that many of PhD programs ask for at least two recommendation letters (sometimes three) and they do not accept general recommendation letter. Rather, they send to the referee's email and ask him/her to write. Therefore, for each of them my referees should write a separate evaluation. So far I got them to write for three applications (two got rejected already). However, I feel I am still at the beginning and there are so many programs I need to try. I am totally aware of the program suitability and I should not apply for a program that I'm not 100% sure I have good chance.

Now the problem is that I chase my referees to write one letter and sometimes I miss deadlines because they are busy or not responding.  I found only this question is very useful here but the issue is I follow all steps there to help them to write my recommendation letters, but they mostly do not. I am one of top 5% students of theirs and I published three papers with them.

I feel like I am stuck between the hammer and the rock here. My question is what is the best tactic I can follow at this stage? Cut down the number of programs I apply for? Or talk to the supervisor about the issue. What advice do you have for me? I really appreciate your advice.

I don't know how many letters you're asking people to write for you. However, when there is a separate form that needs to be filled out for each letter, that is asking for a considerable expenditure of time for your advisors. You need to be aware of this, and plan accordingly. You can't ask people to fill out fifty forms for you at once, and then complain when they can't get it done!

So it's not really about applying to "as many PhD programs as possible." Your advisors should be working with you to select the schools and programs you are going to apply to, and you should be working with them to ensure that you are not placing too large a burden on them. This includes giving them a list that clearly states all the schools and programs to which you are applying, as well as the deadlines, as early as possible, so that they have time to plan accordingly. Then, if there's no response a few days beforehand, you need to send a polite email.

But to keep sending out request after request for more letters in a season is a good way to annoy your letter writers. Organize and plan in advance.


Sending official transcript with mistakes I have been admitted to a Ph.D. program in the US recently. I have to send my official academic transcript. The university issued me a transcript that has a number of courses with no grades written next to them. These were added by mistake. They were not included in the unofficial scanned copy that I used in my graduate application. Would it harm my application if I sent this transcript?

Also, I have received a transcript from my university (signed and sealed envelope) in February. Can I send it as an official transcript if I have it since February? My school does not have a mechanism in place for sending transcripts directly.

Would it harm my application if I sent this transcript?

Not if done correctly. This is one of those "special circumstances" where there is likely no established rule; you just have to contact a human and explain the situation. What you can do is:

Send the transcript with the errors
Reach out to the person in charge of admissions (either the professor and/or an administrator) at the University and explain that there is an error on the transcript.
Reach out to someone at your own University to see if they can send some kind of official notice to verify that there is an error.

Once everyone is aware of the problem, it should not be an issue. They can verify with your university that the transcript is indeed an error.

Of course, the best solution would be to contact your university to see if they can remove the errors and correct the transcript. But if this is impossible, then the above should be good enough.


Transitioning from languages to neuroscience/cognitive science for PhD, how to increase chances of success? I have background in languages (BA in English Literature and Teaching in China, MA Conference Interpreting in Manchester, UK) and I am eager to do a PhD in cognitive science in the UK.

During my MA studies, we were studying fundamentals of psychology and cognitive sciences related to translating/interpreting. During the course of this study, some modern research techniques such as FMRI, EEG were touched upon but the course was not very comprehensive, as the focus of the field was never really on how the interpreters’ brain works during simultaneous interpreting or other language activities.

I found languages and cognitive sciences closely related, because it is very natural to bring up questions in one area while discussing the other. It’s close to instinct that an interest in one can seep into another, at least that was the case for me.

I am really keen to further my education in the area of Cognitive Sciences, and it's been the case for the last couple of years. But it’s a bit saddening to see that the minimum entry for these programs usually require a science degree in relevant fields, for example, CS, EE, Psychology, Neuroscience, etc. And at the moment (I'm 26), I can't really do one more undergraduate degree.

However, I understand that there are gaps to fill for a person to change their area of study. Usually in the UK, PhD programs would encourage the students to do the 1+3 program, where first years have the opportunity to fill this gap. But I fell that even for these 1+3 programs, students who have a liberal arts degree are still discouraged from applying because these PhD programs specifically require students to have background in relevant science fields.

So what should I do to be more qualified and have a better chance to be accepted as a PhD student?

My plan is to learn some fundamentals by finishing online courses in the following areas: Math (e.g. Calculus, Linear Algebra, Probability, to be more comfortable with fundamentals), Computer Science (such as basics of algorithms and Python to be able to perform some scientific computing), and Neuroscience (as it is fundamental to Cognitive Sciences). What about MOOC courses, more specifically, how are they viewed in the academia in the context of someone who is using them to fill in the gaps when changing fields?

I would like to know whether or not I have underestimated the difficulty and hard work required to put myself on this track.

I studied at Edinburgh with a few friends who had come for the arts world into CogSci and CS Masters courses, they shared many lectures with us (Bio-Informatics).    I would suggest either doing a Masters in a related field, before jumping into the PhD.

I took some CogSci and Neuroinformatics modules for my MSc and I struggled not coming from that background, if I were doing it again and wanted to prepare I would look to the online courses. Many of them are excellent.

MIT have an Opencourseware section on CogSci: http://ocw.mit.edu/courses/brain-and-cognitive-sciences/
No one will look down on you for saying you have worked through an MIT course. They also have extensive CompSci resources. Coursera also has many excellent course, that will help fill in gaps in you education.

I don't think you will find many people in academia who will look badly on people using any resources they can find to expand their knowledge and understanding of a given field.


Is it plagiarism to reuse your own full-text material from a previous conference in a new conference? I am a reviewer at a conference. An author submitted a paper, and I searched the   author's previous papers. I found they have one paper with a very similar title accepted  to a conference in 2012. I downloaded the paper, and about 1.5 pages of the 6 page document is exactly the same as the 2012 paper (all words and everything else.) So is that plagiarism?

There is no reference to their own 2012 work. Without paying attention to the rest of paper? Should I drop that or not?

Update:
Yes the paper was accepted and indexed on IEEE web site. and I download the paper from IEEE web site.

Yeah, copying 25% of a prior paper without attribution is definitely self-plagiarism.  Report it to the program chairs of the conference, and let them sort out how to manage the problem from there.

Additional information, for any coming from different publication cultures: electrical engineering / computer science conferences are serious publications that take originality very seriously, and IEEE policy on the matter is quite explicit.


What is the difference between Project's background and Project Significance? I need to write my project's significance.
I googled to find examples on project's significance, but I found article referring to project's background and significance as the same thing.
https://orsp.umich.edu/research-proposals-background-or-significance
Do I need to write a background about my project in the when asked to provide project's significance?

Background: what (general) information should the panel know to properly judge the project. For example: What has been done before? How does your project relate to this previous work? If your project is about disease X, what is this disease exactly?

Significance is another word for "importance" or "impact". Why is the project important, for example: How many people are affected by disease X, and what do you expect to achieve when the project is completed. Better knowledge about the disease mechanism? A cure? A better detection mechanism? The structure of a protein involved in the disease (how does it help if we know the structure)? What they want to know is: How important is your project and how does it help to make the world better?

There is indeed some overlap between the two, but the requirement to write a section about the significance indicates that they want it to be separated from the background, without overlap.


How do I reassure my students that my grading really will be “strict but fair” when the university has an “official” grading policy? One of the biggest challenges I face year after year in teaching—and one that seems to affect my teaching evaluations—is that students are convinced that they are doing poorly in my course, no matter how much I reassure them that this isn’t the case.

Part of the problem is that the university provides a standard grading scale, and many of the instructors in my department strictly implement, a grading scale where you need to earn 90% of the available points for an A, 80% for a B, and so on. A fixed, unalterable predetermined scale irks me significantly for a number of reasons:

Chasing after an arbitrary goal is a bad way to actually learn material. I’d rather students worry about being able to apply what I teach them later than the grade they’re going to get.
Difficulty must be pre-judged, and gauged accurately, to ensure a fair grade distribution. This means if I screw up the difficulty of a question, I end up “hosing” my students.
There is little opportunity to recover from one or two mistakes on an exam during the semester, particularly if they are worth a large portion of the grade each. I don’t think one bad day should screw things up for my students.
I could impose an alternate scale but then I’d be committed to that—same basic result just different checkpoints.
Because of the nature of the class, it’s easy to make a mistake early on in a problem that means you can’t solve the rest of the problem, and the result must unfortunately be a low score (a student might make an error early and can only get 5 out of 20 points, but a mistake later on might result in a grade of 18 out of 20).

So I use the basic scale, but adjust it in the students’ favor at the end of the semester to adjust for what I think makes a fair and equitable grading distribution, and most students do reasonably well, because that’s an accurate reflection of their performance overall. But no matter how much I tell the students in the class that this will take place, no one really seems to believe it. (A typical distribution will typically be 20% A’s, with most of the rest B’s and C’s.)

Is there a way I can convince my students that even though my grading is strict but fair, even when students don’t get very good scores on individual graded exercises?

There has been some issue about the amount of adjustment going on, so I should probably clarify. Typically, the curve amounts to about two-thirds to a full letter grade: so the borderline for an A would be in the low 80's rather than 90. This curving amount leads to a distribution that is about 20% to 30% of the students receive an A, with about two-thirds B's and C's, and a smattering of D's and F's.

There was also the issue of how much grading is done, and it caused some confusion because I worked in two different positions where the grading is completely different. For the course I'm describing in this question, the students receive grades on every homework assignment, take a series of eight quizzes, and have a project in addition to a final. So students know what the "worst-case scenario" will be if there is no rescaling, so there is plenty of opportunity for feedback and course correction. My issue is absolutely not with grading—it's with grading on a predetermined scale.

Dealing with the university "standard" is much easier than it seems, since they don't (can't) determine what a "point" is. So 90% of the available points is meaningless.
There is a form of grading called "cumulative grading" (maybe some other terms apply). Decide that the course as a whole is "worth" 1000 points. Create student exercises/exams/whatever that total to 1000. For example, Project A is "worth" 300 points toward the goal. When a student does an exercise they get a certain number of points up to 300. (See below for refinements.) Every piece of graded work has a value, possibly all different, and they add up to your total.
The list of tasks and their individual point "values" are listed in the syllabus. Students get to see the big picture, up front.
You can penalize for late work as you like.
The students always know exactly where they are. When they earn 700 points they know that they have a C or better - guaranteed. The University is satisfied and the student knows absolutely.
An additional element/benefit of this is that some students have many things to do and my class may not be the most important thing. They might be satisfied with a B if it gave them time to work on other, higher priority, things and they could do so without risk.
Important Refinements.
I always let students repeat/refine their work for regrading. They couldn't earn full points on regrading, but, say, up to 90% of the points lost at first grading could be returned to them if they improved the work sufficiently. This means, essentially, that if they got 270 points on that project, missing out on 30, that they could earn back 27 points leaving them only 3 points short of full marks.
Re-grading gave two advantages. One is that I never got whiny complaints about points. Second, when I thought a student (or team) really needed to revisit their work, I could give a relatively low score on the initial submission. They thus had more incentive to improve it.
You may not want to do the following, depending on your load and your students, but I didn't limit the number of times a student could re-do a piece of work. I made exceptions only if it got excessive as the down side, for a few students, is that they obsess over some early work, falling behind on the new. So it takes balance.
In computing summary grades, no student ever misses a mark by an insignificant amount. If someone is ten points out of a thousand short at the end of the term their grade is "rounded" up. This is perfectly justifiable as there is likely some (hopefully small) subjective element to any grading of projects and the like. I gave up on "objective" exams a long time ago, since they measure only poorly and can be greatly affected by other things such as student stress, etc.
Finally, at the end of the course, I looked at the grades overall according to the above measures. I asked myself whether this seemed to be a fair measure of what the group as a whole learned. Usually it was fine, but once in a while it turned out that the grading itself was somehow off, and the students were better than the curve suggested. I'd make an adjustment. No one ever questioned this, nor would they have any reason to. Tenure is a great thing, however, when you want/need to do something that the University frowns upon. At the end of the day (term) you need to be reasonable.
Note also that I had a reputation around the University of being very hard/strict/demanding. But the students always had a reason to feel good about themselves and how they did. This is, in some ways, nearly as important at the technical (Computer Science) things I taught them. Actually being more gentle than your reputation is a plus.
Also, note that the philosophy behind this whole scheme is "You aren't here to prove to me that you don't need to be here."


Traveling before graduate school I want to take a gap year and travel after getting my undergraduate degree in Physics. Is it possible to apply for a research grant that would cover my expenses that year? Can someone travel a lot as long as they meet the expectations of a research grant?

What you are describing is possible, however unlikely.

To receive grant funding, you need to work (otherwise youd be stealing). The vast majority of grant funds are tethered to a location and 24/7 remote work is not a reasonable request. This difficulty is compounded by the narrow time window that im perceiving in your question, finding that appointment is a challenge.

The more likely solution here is to make the travel part of your graduate program itself. Apply to a program 'locally', and target a different laboratory of your choice. Then, fully disclose your plans to graduate at the local program, and collaborate with the distant lab. Collaboration could be in the form of materials/facilities usage, etc. For example, summering at a lab for whatever reason. You could even make the case to your new primary adviser that you simply want to learn spanish during your career because it will make you a better scientist (thats a big sell).

This will be a little tricky and will definitely require far more investigating than just applying to a graduate program. But, tethering to the 'primary' graduate program is both possible and productive. this approach relies less on luck.

You cant get around the fact you have to work AND also find that work.

Alternatively, there are plenty of opportunities to pursue research appointments at far off, beautiful destinations (e.g. http://www.bios.edu/#!/who-we-are). These are typically farther down the research spectrum, and will contribute to your research career in a different (i.e. less) fashion. I myself held several appointments previous to grad school, and they were the best experiences of my life. the appointments are much easier to come by. however, i do not consider all of them to be part of my "science career".


How do I tell thesis advisor I want to withdraw from research? (mental health) Context: Back in May I had asked a prominent professor whom I really admire for research opportunity. He gave me some study material to do over the summer and said he'd decide in the Fall. So in August, he "accepts me", but he also decided to let me work together with another undergraduate (who asked in August) on this project. This was two weeks ago. Today the other undergrad and I met with the Professor to discuss things. Working in a "group" basically ruined it for me. It's childish of me I know.

For these two weeks, I've been an absolute wreck. I've been so stressed about working with this other student. I've met with her, talked with her, and it is certainly possible for us to get along but I am just so so stressed and anxious. I feel competition exists now and it's simply a lot of pressure. I "dealt" with depression, (social) anxiety, self harm, and an eating disorder for 7-8 years now, and these past two weeks my eating disorder has gone completely out of control, since I use it for coping, I'm sleeping 5 hours max and I feel like I'm going out of my mind.

I've decided I really can't stay like this and want to withdraw from doing research with this Professor. I considered asking for an independent undergraduate level project but he did say he does not usually take undergraduate students and since beggars can't be choosers, I'm really afraid to ask. I have another professor in mind I can ask for research for my thesis (whom I'm more familiar with).

Sorry, I don't have anyone in real life I can talk to about this so I'm writing a lot on here. My point is, how can I tell this Professor I want to withdraw because of this social-anxiety-induced stress that I cannot handle? I don't want him to think I'm slacking/lazy/not interested because I am but I can't stay here (but maybe I shouldn't care about this). Is it "proper"/ok to give him the true reasons (group work) (better worded of course)? I dislike lying.

Thanks

First, I hope you are working with a mental health expert; I always hate to see people lose good opportunities due to issues like this. As Buffy says, you should definitely see if there is anyway you can make this work (though, a clean break is better than performing so poorly he has to fire you. A mental health expert can help you weigh these decisions).
At any rate, to your actual question:

how can I tell this Professor I want to withdraw?

Clearly and concisely. In person if possible, but if you cannot face that, an e-mail will do the trick:

Dear Professor,
Unfortunately, I am going to have to withdraw from research. I really enjoy working with you, the research has been very interesting, but due to some mental health issues, working in a group is not really feasible for me. It's nothing against [the other student], and I understand that research is often done in groups, but I'm not currently at a place where I can support group work. I am sorry to have to withdraw; thank you again for your efforts.
Name


Is it appropriate to request that the department hire a female faculty member? Our department is currently hiring a new faculty member. At the moment, the faculty gender ratio in our department is very skewed, even for our field. I believe that this has a negative impact on the department environment.

There is general consensus among the grad students on which candidate we support. This candidate is highly qualified in terms of her research and teaching. Moreover, among all the candidates who have visited, she is the only one who has any experience with diversity initiatives and getting underrepresented groups into STEM. This is very important to many of us, especially since the department is planning to add an undergraduate program in the near future.

We are planning to write an open letter to the department in support of this candidate, citing her qualifications as someone who has worked to make science a more inclusive place for women and other underrepresented minorities.

My main question is is whether it is appropriate for us to additionally express our desire for a woman faculty member.

EDIT: Thank you for all of the answers, it certainly gives us a lot to think about. I would like to follow up on a couple things.

When I say something like "we think the department should hire a woman", I don't strictly mean that the next faculty should be a woman regardless of any other factors. Rather, I mean that the department should hire someone who will be able to relate to the issues women face in academia and STEM, and help champion female students in our department. The average woman will be in a better place to do this than the average man, so perhaps I should have been a bit more precise about what I meant in the original post.
While "diversity programs" designed to get underrepresented minorities into stem are discriminatory in the strictest sense of the word, they are in place to address systemic injustices which have existed for a very long time. The hypothetical examples of discriminating against men and women don't account for the fact that many gender/race imbalances in academia exist because of previous institutional discrimination.

the new faculty should be female in order to help address the wildly disproportionate gender ratio in our current faculty.

This is not a good reason. Gender imbalance is fought by educating everybody (males, females and any possible group) equally and hiring the best people, regardless of their gender, not choosing people by gender; that's sexism.

  The candidate that we support is highly qualified in terms of research and teaching. Moreover, among all the candidates who have visited, they are the only one who have any experience with diversity initiatives and getting underrepresented groups into stem. This is very important to many of us, especially since the department is planning to add an undergraduate program in the near future.

These are very good reasons to hire someone, and reasons to be proud being hired for. If I were her, I'd find disrespectful being hired first because I'm a woman and second because of these good reasons.

  We are planning to write an open letter to the department in support of this candidate, citing her qualifications as someone who has worked to make science a more inclusive place for women and other underrepresented minorities.

Again, these may be good points to write in the open letter, but the fact that she's a woman shouldn't matter. She's a great candidate no matter what her gender is.

I find this logic of hiring women because they are women very sexist, towards both men and women. Towards men because they are at a disadvantage, towards women because you're treating them like kids, giving them a preferential route they don't need. Women can clearly be good enough to be hired just for their skills and not for their gender.

Fight for her to be hired if you think she's the best choice. Write the letter and explain why she's the best choice, that she's better than the other candidates because she is better, not because she's a lady.


Waiting time/silence after a postdoc interview I had an informal interview for a postdoc position that was followed by a formal one. Both went really well (at least in my opinion) and the formal interview exceeded its specified time because of the interest they showed in the work I presented. Upon asking, I was told that the process may take up to 2-3 weeks, speaking of which, there is no official/unofficial word about the outcome of the interview and more than two weeks have already passed. Should I wait a bit longer so that I don't come across as too desperate?

I think this might depend on whether you have other options that you need to pursue soon, or just want to quiet your fears. In the first case, you should probably ask so that your options become clearer. But in the second, I'd wait, perhaps even after the 3 week window ends.

I think that if things were bad you'd hear sooner, so it seems that you are still in contention, but there is no way to judge your relative position among finalists.

I would recommend, at the moment, that you wait, but don't neglect other options. But the only information I have is what you wrote. You may have more.

Not to mess with your mind, but it is possible that they have made an offer to another person and are waiting for acceptance/rejection before contacting you again. That would push the time frame out a bit. If that is the case then you aren't going to get much useful feedback from an inquiry now.


Referencing assignments from past students When working on an assignment (e.g. essay, report), is it allowable or ethical to reference (as in both "read" and "cite") previous students' submissions for that assignment? For example, the student may have a friend or relative that sat the subject previously and is happy to share their assignments.

From my understanding, unless the teaching institution has an explicit policy, this should be allowable assuming the referencing is done correctly. So saying, it may not be the best educational experience, as the student may not undertake the critical thinking and research the assignment expects.

To be clear, I am not talking about referencing assignments of students currently studying that subject. That is clearly collusion.

I also assume the student attained previous submissions with consent from all the authors. However, I do not assume that all students currently working on the assignment have access to all past submissions.

I think it is both ethical and within the rules (or at least it is within the rules at my university) as long as the reference is clearly cited.

Furthermore, it should also be fine with current students as long as the work is cited too.

For example for undergraduate experimental lab course I took during my 3rd year, I worked on an experiment with 2 other students working on the same experiment independently. We each had to write a project report on the results we obtained during the experiment.

Only one of us managed to get a particular dataset for a part of the experiment that was sensitive to conditions and difficult to get results on. In that situation we were able to used that student's data so we could discuss their result in our report (as long as we cited the person who actually obtained the dataset, of course).

In a seperate experiment I let someone use a java code I wrote for the analysis. This was also fine, because the person cited me when they used my code in their report.

I think if the handin were supposed to be completely independently written (e.g. a math problem sheet) it would be collusion to reference older (or current) work but that is generally acceptable to cite anything (past student work or otherwise) in work which you would normally expect to see citation (e.g. essay or report).

If you have assessment regulations, there is probably a clear indication of what your university expect in there. That would not be able to tell you the answer to ethics part of this question but otherwise might be able to tell you the rule at your College or University.


Pre-print service like arXiv but with private option, so I can correct my mistakes without publicly advertising my mistakes? As a student, I make mistakes all the time, and stealing my idea will not face heavy retaliation. I don't mind if someone comes up with concurrent works, but I do mind if my key idea is leaked. Many graduate students in my field therefore only use pre-print services if their papers are either publicly presented or conditionally accepted.
I am looking for a website that can do most of what ArXiv does, with an additional private option or limited visibility, for example an option to make the paper unindexed by search engines. This way, my paper cannot be seen for at least a few months. By doing so, I can at least claim that I am one of the first few researchers who got the idea right. And most importantly, I can privately correct my mistakes, if any. Publishing mistakes is embarrassing and sometimes harms one's career. Many mistakes will be revealed during the peer-review processes and I have a chance to correct them before publicizing.
Please kindly think twice before giving ethically and "politically correct" comments like no one will scoop me, everyone will cite me, and the scoopers will be punished. At least in my field, scooping and idea-stealing is commonly observable, and big-names don't care about publicizing pre-prints because they have resources to punish the scoopers. I do understand that keeping my work private might harm the community as the information becomes less transparent. However, it could also be possible that my un-reviewed flawed works misguide the community, and a paper reviewed will benefit the society more.
I personally wasted six months because of someone else's mistake in a published work.

I heard that in molecular biology there is a widely-used service to upload your research data, like protein structure and sequencing, to get a timestamp. The uploaded materials can be set to be private for a period, and fully disclosed later. A lot of people do use this function. This is not exactly what I am looking for but shares some similar ideas.
If I remember correctly, there is an interesting paper studying the scooping patterns with the aid of this database.

Solutions found! Zenodo and some other university-run pre-print services do have an embargo function.
Moreover, SSRN is a widely used repository, that, unlike arxiv, only displays the newest version to the general public, although still keeps a tag on the first submitted date!

Basically, if I understand you correctly, you want proof of priority without publishing.
Well, this problem is well known from middle-ages and renaissance where people wanted to be able to prove they have the earliest solution without revealing what it is (so that if someone finds it, they can prove they were there first).
They often used anagrams, today you probably would use some private/public key combination for this (I am not a crypto expert, you would have to read up on this).
However, to be honest, this will look weird. The current position in science is: if you have done it, publish it and expose it to criticism, and you may gain priority. If you wish to monetize it, you can create a patent that is public, but protects your rights (in theory), or keep it a trade secret and make money out of it.
As for a website that supports timestamps for unrevealed papers, I am not aware of any, but of course if there were, you need to make sure you trust the maintainers. Furthermore, if you had one and if somebody publishes a completed paper somewhere else before your paper goes live, this will not help you. The fact that you had worked provably, say, for multiple years on the topic will at best prevent plagiarism charges when you end up publishing. But this, if it occurs, could be proven otherwise, e.g. lab diary, emails, etc. It will not make you the "first to publish". Don't forget, there are quite a few cases where people who had publications were superseded by later, but more visible publications. So, even open publications may be vulnerable to "post-scooping".
So, your question needs to be what one would need such a service for? I therefore doubt that people would set up such a system with obviously limited utility. Of course, this is not a statement that there isn't.
I understand that this does not precisely answer your question, but I hope I was able to put things in context and why your question may not have a satisfactory answer.


Why/how APA was chosen as a standard for many fields? My background is in mathematics where we write papers to the style guide of the particular journal, often similar to that of the largest organizations like the AMS or the MAA.  I was a little surprised to learn that (at least in the United States – I immigrated here for university and now work here) apparently many fields use the style of the APA, even if they have nothing to do with psychology.  I was told by a colleague that they even have to follow the changes to that style, even though no one in their department actually belongs to the APA.

I am curious if anyone knows how or why that is the case?  I imagine there is an interesting historical reason for this.

I am posting my reply as an "answer" because of its length and detail, but credit goes to Nate Eldredge and Andy Gillett (see below).
I agree with Nate Eldredge's comment (May 5 at 18:38):

I always assumed that APA saw the need for a standard style and
created one, and then other fields simply adopted APA's style because
it was good enough and less trouble than creating their own.

An English professor and professional writer (Andy Gillett) published a superb blog post in 2014 that provides the most thorough history of "APA Style" I've seen. The blog post is titled, "'The Harvard System' of referencing" (September 28, 2014).
Although the post's primary subject is the so-called "Harvard System", Gillett discusses APA Style at some length. For example:

The earliest version of the Publication Manual of
the American Psychological Association was a short, seven page guide
published in the Psychological Bulletin in 1929. This was followed by
a 32 page version by John E. Anderson and Willard L. Valentine in a
1944 issue of that journal. The first edition of the Publication
Manual appeared as a supplement to the Bulletin in 1952 and was 61
pages in length. It was revised twice prior to the publication of the
second edition (1974, with many reprintings).

Gillett also offers a nicely detailed list of the various iterations of APA Style. Here is the beginning of that list:

History of the APA Publication Manual

Instructions in regard to preparation of manuscript. (1929). Psychological Bulletin, 26, 57-63.

Anderson, J. E., & Valentine, W. L. (1944).The preparation of articles for publication in the journals of the American Psychological
Association. Psychological Bulletin, 41, 345-376.

American Psychological Association, Council of Editors. (1952). Publication manual of the American Psychological Association. > Psychological Bulletin, 49(Suppl., Pt. 2), 389-449.

Although Gillett's blog post doesn't necessarily provide a complete answer to question posed by TrivialCase, it provides more history, detailed information, and references than anything else I've been able to find.


How to check geographical variation/self citation in the citing articles on Google Scholar? In my department, I have been assigned to find geographical variation and self-citation in the citing articles of some research papers. On Google Scholar, manually it is very difficult to check citations for every research paper. For example, one of the research article has 650 citations, it would be a laborious task to check every citing article for geographical variation and self-citations.

Is there any tool which classifies citing articles based on their geographical variation and self-citations?

Many universities subscribe to Scopus. Scopus make it much easier to identify self-citations. It also makes it  easier to identify articles that belong to a given research and export citation of these articles for analysis.  So you might want to check that out.

I think scopus will identify how many citations to a given author are self-citations.

Identifying more complex features such as geographical patterns is likely to involve more work. It's unclear even what is meant by geographical pattern. I can imagine that each author could be assigned to a country based on their current institutional affiliation. And each paper could then be assigned to one or more geographical locations based on the affiliation of the authors of the paper.

However, this would probably involve a lot of manual work. Perhaps there are scripts that could automate this. Scopus does have the affiliation of many authors.


What is the downside of not pursuing postdoctoral fellowship position? Suppose after graduating from a PhD program, you don't do a post-doc. Are the chances of getting a tenure-track position severely reduced? Also is it possible to do a post-doc after a completion of a masters program (probably should be called a "post-masters")?

The purpose of a postdoctoral fellowship is simply to gain the skills detailed in this answer to a similar question, notably:

Get involved with obtaining funding
Build an international reputation
Start collaborating with external parties
Learn how to manage projects and a lab
Start to devise a strategic research plan
Improve your publication record

If you have all those things from your work as a graduate student, then you should have no problem finding employment and furthering your academic career immediately after you earn your PhD. Most students don't, which is why they try to find a postdoc position to help them  gain these skills before attempting to run their own lab.


How to assess an unknown journal's quality? [I apologize if it has been asked, I think it must have been but I couldn't find a similar question.]

I often receive invitations / calls for papers to write papers in journals. 95% of these cases are obvious spam publications, but in about 5% I see a letter that's not entirely generic, e.g. they mention my previous publications in the subject** and they write something that appears genuine about the publication. They also write the name of the editor in chief.

My question is how to assess this new journal's quality? I mean, nice journal pop up once in a while and just because it's a new journal, does not mean it's necessarily "fake news".

Here are a few points I thought about:

Wait a few months/years until I see reputable people publish in it, but then I will have missed my shot, possibly.
Inspect the editor's reputation. If she/he appears reputable (e.g. have published in journals I know to be good), then the journal is okay.
Inspect the publisher's "parents", for example if it's ACM, Springer, IEEE, etc., then maybe it's worthwhile (but then, I can't say definitively either way).

I would appreciate any points on the subject.

** yes, these messages can nevertheless be generated automatically.

When 95% is junk and the other 5% is sufficiently irrelevant that neither you or your supervisor and colleagues know about them, a safe and efficient strategy is to ignore all journals that actively request contributions.

I have also never heard of a legitimate journal using mass emailing to recrute editors (this is more a habit of author-pay open access journals that are looking to increase their market share).

Yes this strategy, if adopted broadly, would prevent some new journals from being known. The good news is: we already have way more journals than we could possibly wish for. It's good content and quality curation we're short of.


Balancing short-term academic position and pregnancy A close friend of mine was offered a three year postdoc position after she finished a previous 3 year postdoc fellowship. She is very excited about the new position but at the same time she is very worried since she and her partner are planning to have a first baby. She mentioned that she felt like she would be taking advantage of the professor who offered her a new position, if she would become pregnant soon and would be on maternity leave for several months, while she only just joined the new lab.

I didn't really know how to respond. Should this really be a concern for her? Or how to balance moving between (relatively) short-term positions and starting a family?

If I understood right, she is not pregnant at this time.

If the post-doc is a one-year appointment, I don't see a problem.  Pregnancies generally last approximately 9 months.  It often takes more than one cycle to conceive.  If she wanted to be sure the birth wouldn't interrupt a 12-month appointment, she and her partner could always wait a couple of cycles before starting.

She may start to want to have an afternoon nap at some point; she'll probably want to bring some extra snacks to work; she would be smart to plan in such a way that she doesn't have to spend a lot of time on her feet in the lab in the last trimester.  Some women find their concentration isn't completely what it was pre-pregnancy.  She might want to build some flexibility into her project(s) in case she finds her productivity is a bit less than what she's used to.

Other than that, the only limitation I can think of would be if she works in a field involving radiation.

If the post-doc is a two-year appointment, then she may want to plan her work flow to allow her to ease back into work part-time after the baby comes, while still making progress with her research.

(How to combine work with care of a young baby is whole topic of its own which I won't get into here.)

Note, my answer would be different if she were about to jump into a tenure-track position, with a solid teaching load and having to build a lab program from scratch.  But this position sounds nothing like that.

Whether or when to start a baby is a very personal decision.  I see nothing objective here to stand in her way if she and her partner want to do this now.

(Note that in the U.S., employment discrimination against pregnant women is strictly prohibited.  I can't imagine things would be substantially different in the UK.  If in doubt, however, http://law.stackexchange.com can help.)


Research in Progress papers What exactly is demanded in a Research-In-Progress (RIP) paper? Specifically, how do they differ from other types of paper submission? A sample call can be found here: http://www.ecis2016.eu/en/RESEARCH-IN-PROGRESS-PAPERS.html

Is it merely sufficient to clearly outline a research question, the background and proposed solution, without any substantive results? I am curious because many of these sort of calls have relatively long page counts (around 6, which seems fairly typical of a journal paper). Is the difference that a RIP paper may talk about the entire scope of one's research, while with many other types of submission it would be prudent to merely focus on a single aspect of one's research?

I would give a research-in-progress paper the same format as a typical research paper (using a typical format such as introduction-methods-results-conclusion).  However, the content of some of the sections would be different.  Using this format as an example:

Introduction This would probably be similar to the introduction on your final paper, but it should also give a bit of context on the progress of the project, so the reader knows how far along it is.
Methods Depending on the progress of the project, talk about what have already done, what you plan to do, and/or any decisions that still have to be made about what methods to use.
Results If you have preliminary results that you are comfortable sharing, definitely include them.  However, "results" can also be about progress so far on the project. e.g. "We have successfully completed three out of the seven ice cream launches", "We have recruited fewer accordian players than expected, but so far the drop out rate has been only 2.7%", and so on.
Conclusions You might reach tentative conclusions based on preliminary results.  But more likely the "conclusions" should be reflection on the overall progress of the work, as well as lessons learned so far.

For scope, use your judgment. As with any paper, the key is to make it tell a good, clear "story" that will be interesting to the audience.  Focusing on one aspect of the work, or giving a broad overview of the project, are both possible approaches.

Beyond this, refer to the call's specific guidelines.  The page or word limit is usually a good guideline to how much detail they are looking for.


What's the equivalent of this degree in Europe and USA? I'm an undergraduate student in mathematics at the University of Buenos Aires. The name of the degree is "licenciatura en Matemática", which is a 5 year long degree. To graduate you must make a small work called "thesis".
Now while the degree is about mathematics, you can choose between two orientations, in the third year: pure and applied.

If you understand spanish: http://cms.dm.uba.ar/academico/carreras/licenciatura/

The University of Cambridge's International Qualifications page recognizes a "Licenciado with an overall grade of between 8 and 9 out of 10" as "At least a 2i honours degree from a UK university or an equivalent standard from an overseas university", but also says that it's equivalent to a Singaporean Master's degree. I'd guess that most universities would consider it definitely equivalent to a Bachelors and probably also a Masters degree.


Publishing datasets as a journal articles We have created an NLP dataset out of written texts of a certain group of people.
I thought perhaps we can publish the dataset as a journal paper (the data is an external appendix to the article and published somewhere on the internet).
Data in Brief and Nature Scientific Data publish such articles. However Data in Brief charges $600 and Nature has a very high quality expectancy.
Are there other journals where we can publish our NLP data sets?

If I search on Web of Science for TOPIC: (natural language processing) AND DOCUMENT TYPES: (Data Paper), then I find various results from Scientific Data (which you mentioned already), one from BMC Bioinformatics, one from Bioinformatics, and one from the International Journal of Robotics Research.

BMC Bioinformatics asks for APCs of $2490.00, but offers waivers on a case-by-case basis.

Bioinformatics: I did not find any information about APCs (though, according to their Instructions, they charge for OA licenses, for colour figures, and for excess pages).

International Journal of Robotics Research: I did not find any information about APCs - but to be sure, have a careful look at their submission guidelines.

By the way, Data in Brief also offers reduced APCs or even total waivers under special circumstances (see here).


Choosing which version of an article to cite I sometimes find an article published in several conferences.

  If similar material is published in different conference proceedings,
  how do I choose which one to cite?

It's a little unusual to have the same or even similar material published in different venues. First of all, you didn't say whether your area uses conferences as primary publication venues or not - I'm assuming it does, otherwise why even cite a conference publication.

In that case, what exactly are you citing in the article ? If it's a specific result (empirical, theoretical etc), then probably the oldest venue where it appears is the first occurrence of that result, and should be cited. If you're citing background material or motivation, then either the first paper that discusses the relevant motivation, or maybe a survey article ?

At any rate, the key is to understand exactly what you're citing the article for, and find the oldest occurrence of that concept.


For conferences with an abstract deadline shortly before full paper deadline, does the "no simultaneous submission" rule include abstract submission? It's generally forbidden to submit the same paper at two different venues at the same time. In addition, many computer science conferences have two different submission deadlines: a deadline for the submission of abstracts, followed by another deadline (1-2 weeks later) for the submission of full papers. A complete submission consists of an abstract and the accompanying paper.

Let's say we have a situation that involves two conferences, A and B:

Conference A had its abstract and paper submission deadlines some time in
October. A's website says that acceptance notifications will be sent
to the authors on December 7.
Conference B has its abstract submission deadline on
December 1 and its paper submission deadline on December 8.

Is it OK to submit a paper to A and an abstract to B simultaneously, cancelling the submission to B in case the paper is accepted at A?

(It surely seems advisable to ask the conference chair of B, but since I know the chair of B personally, I don't feel comfortable asking, since this might come off as a request for favouritism.)

To answer this question, let's recall why many journals and conferences do not allow multiple submissions. So,

  Is it OK to submit a paper to A and an abstract to B simultaneously, cancelling the submission to B in case the paper is accepted at A?

Multiple submissions are beneficial for authors, since they generally increase the chances for a paper/talk to be accepted and/or reduce the time until acceptance.
However, this strategy is not beneficial for journals/conferences, since each venue will spend time and resources on processing the submission (register and peer-review it), and only one journal/conference will eventually publish it. The efforts spent by reviewers of another journal/conference will be wasted.
This strategy is also damaging for the community of researchers. Firstly, peer-reviewers and editors are also academics, and they do not have much time to spare, so it is best not to waste it with pointless review process. Secondly, and more importantly, readers generally benefit from well-written and well-edited papers, and this relies on careful and time-demanding peer-review process. Faster acceptance may indicate better organised peer-review process, but it can also mean that the process is superficial (like it is in predator journals and such). By preferring a faster route, one can waste time of highly professional reviewers and also rob himself of a chance to get their valuable advice and improve their paper/talk accordingly.

So the answer is no - it is not OK.


Is it problematic to not include a reference letter from home institution? So I have done an one year exchange program in the US and one summer research project, which give me three letters (I have asked the professors before I leaved there). However, my friend warns me it is bad if none of the three letters is from my home institution. Will the admission committee regard this as something like a red flag?

By the way my home institution isn't that famous. In case it is useful, I want to apply for phd program in (pure) math.

Its better to have atleast one letter of recommendation from your home institution as you might have completed the course work from there. And therefore better to have someone who can tell about your performance during studies.


Citations when mixing of factual evidence and interpretation in one sentence I have a bit of a technical question about constructing narrative while writing as a historian (I guess it also applies to other humanities).

This never really occurred to me as an issue during undergrad and graduate school while writing my thesis, but I have noticed now as I revise my thesis that at times I write sentences that contain both the factual events contained in the primary source I cite in the footnote at the end of the sentence and my interpretation of the source I cite.

For example, if I describe the relation between Event A and Event B, I might first describe the general context. Then follows Sentence A that describes Event A and cites Source A describing Event A. Then follows Sentence B that says:

  In reaction (to Event A), Event B happened⁴.

Where Footnote 4 describes Event B.

My question about this example is about the two words “in reaction”. The source I cite at the end of Sentence B does only describe Event B. I derive the connection between the two events and that Event B is a reaction to Event A from the general context. Thus “in reaction” is my interpretation of the causality between the two events.

Now if one is really squeamish I guess one could say that by not separating “in reaction” from Sentence B I mix interpretation and factual evidence and some readers could be misled that the source I cite at the end of Sentence B also includes that Event B happened in reaction to Event A.

The same kind of situation seems to happen at times in my writing when I have a sentence that is built like this:

  [Interpretation], [relative clause with factual evidence] [Footnote with evidence for events/facts in relative clause].

My question is whether this style of writing is acceptable at all? It certainly does not occur often in my writing, but it does at times. No one who has read my writing really has ever said anything about this. Although it is hard to check the writing of other historians with regards to this question, as I do not have the sources to check in most cases, I have noticed that other historians do this kind of mixing at times as well (some even seem to simply cite sources at the end of paragraphs that clearly contain both factual statements and interpretation). I also wonder what having to interrupt sentences to clearly separate interpretation and facts all the time would do to the flow of the narrative.

Still this is a concern now, and I would like to know how to approach this dilemma. Is there a convention or best practice? Is mixing interpretation and evidence acceptable, is it sloppy writing or is it completely unacceptable?

Crosspost on Reddit

Footnotes should be placed in connection to the material that they describe. There is literally no reason other than a style sheet that they can only be at the end of a sentence. If it belongs halfway through the sentence, before you begin interpretation, then put it there, where it makes the most logical sense.

Remember, your writing is what is paramount. Use the tools you have to make your arguments and narrative work, rather than the other way around.


Pros and cons of (co-)authoring a reference book in early career? I am early in a tenure-track position. I undertook with a publisher to write a reference book a while back and with a light load to start with in my new position, I recently agreed to set a deadline of later this year.

I progressed quickly through some of the core chapters where I knew what I wanted to write.

Now I have a heavier teaching load, preparing course material from scratch week-to-week, and am struggling to cope with my work hours.

But spending all my few spare cycles in the book seems to be carrying a huge opportunity cost. Though my research profile is sufficiently strong for me not to have to worry about journal output for a while, and I'm currently in the "harvest cycle" of a couple of journal papers that are coming through from about a year ago, I feel I am missing opportunities to start collaborations with other faculty members. I want to start on some new directions and target new communities with the help of new colleagues.

Furthermore, I feel like I don't have the bandwidth to bring the quality of the book to the level I would like. Writing the book has thus become a disheartening chore, trying to balance progress and quality. Working odd hours here and there, I can't dedicate myself to it. There are more pressing things to think about while showering in the morning. Every time I go to work on it, it's a cold start.

In this rather excellent answer on an unrelated question, @Pete L. Clark mentioned the following:

  With regard to writing books: one of my most distinguished colleagues, Dino Lorenzini, wrote an excellent and rather successful book near the beginning of his career. He now tells anyone who will listen that junior faculty should not write books. Of course sometimes the heart wants what it wants, but from a strategic perspective I think this is eminently sound, and I say this as someone who may turn around and write some books now that I am solidly into my mid-career.

This prompts me to ask, is it generally the case that writing a book early in one's tenure-track career carries too much of an opportunity cost? My hope is that the book will stand in good stead for my tenure application, and may attract citations in the long term (I believe it is in a good niche), but would I be better off with two-to-three more good journal papers instead (what I estimate the opportunity cost to be)?

Essentially I'm looking for anecdotes on how writing a book helped/hindered early-career (tenure-track) researchers.

I agree with the advice Peter Clark offers in the bit you've quoted. You're further along in your career than I am. (Defending in May). However, I've had many friends in your circumstances. Here are two things that I have gleaned from their experiences:

(1) A mediocre book has little impact on the field, just like a mediocre journal article does, except that the book has such a higher opportunity cost.

(2) A bad book can actually be a kiss of death. People might laugh off a bad article, but if you put out a bad book, you might actually harm the good reputation you've built with your other publications.

(3) To write a good book requires so much time, and such a high level of expertise, that it's usually not worth doing for a junior person.

My sense is that these three sentences might not hold in all fields universally. Some fields are book fields where you are expected to publish the dissertation as a book. In those fields, I'd assume there's more reasonable expectations about book length publications. But in primarily journal based fields, I suspect (1)-(3) are true.

Can you write the publisher and ask for a long extension so as to be able to keep a more reasonable research/writing schedule?


What is the difference between a Teaching Philosophy and a Teaching Statement? Context: I am a PhD student in mathematics currently applying for tenure-track positions at small colleges throughout the US.

In general, most openings I've seen are asking for what they've termed a "Teaching Statement," while the remainder ask for a "Teaching Philosophy."  Is there a difference between these two documents?  If so, what is it?

I've posed this question to a wide variety of people (colleagues, panels, etc.), and they can't seem to arrive at a consensus.  Some say that there is no difference whatsoever, whereas others say that a statement is supposed to be much more concrete and give more specifics than a philosophy.

I realize that this question was already addressed in some of the answers to this question, but I'd like to hear a little bit more detail, if possible.

One of the confusing aspects of the various fields of academics is that within one field there can be many terms that essentially mean the same thing. People may try to state that there is a difference but normally the differences are so minor that it is essentially hair-splitting.

The difference between a "teaching philosophy" and "teaching statement" is basically the second word used in both terms. If there is more difference then this it is so nuanced that the average person would fail to notice.


Is ethical to rewrite tutor work and submit it? I hired a tutor to help me with a programming task (he did the whole assignment for me) a few days ago, but instead of submitting his own work to my professor, I changed the code from him into mine (I rewrote the codes from him into something else, I modified functions, I changed the code structure, and I tried to make sure the similarity of his work and mine was nearly zero, and when I checked the similarity report the similarity was low about 10-15%)).
Is my action considered as cheating or academic dishonesty?

First: That you take into account a "similarity report" sounds worrying. Of course it is possible to commit plagiarism which a similarity report cannot detect (reformulation of ideas or translations, for example). You might want to read up or ask around what plagiarism is.
Next: What you did sounds very much like cheating (if the expectation was to do this task on your own): You got the idea from somewhere else and rewrote it. It seems to me that rewriting was not the idea of the task. "Rewriting" sounds to me like "changing variable names, restructuring, exchanging loops, some functions" but not like thinking again etc.
Finally: Whether this is considered cheating (and if the assignment was "important enough" to consider some action "cheating") is up.to the prof and your university. You might want to ask them. If you don't want to, this most likely either means your prof is unreasonable or you yourself consider your action to be wrong.


Are translators of mathematical texts into English in demand? Are translators of mathematical texts (books or articles or whatever) from a foreign language into English in demand today? Specifically, I'm interested in German and Russian. If they are, then what kind of organizations (or what specific organizations) are interested in such translators? Do people working for those organizations usually combine the translation job with a teaching and/or research job?

It is hard to tell if they are really in demand today. I have no statistics at hand but I guess that the demand is (slightly) declining since most books are written in English these days. But there are of course counterexamples to this statement. There has been a popular German book on functional analysis, being first released in 1985. In 2016 it has been translated into English, see below.  I studied at a German university and the recommended books in my undergraduates were mostly German books, only a few being translated into English. It is hard to tell whether it is worth it to translate them because there are already a bunch of English books on "basic" subjects.
What kind of organization is interested: Probably the authors are interested, but not for monetary reasons, but so that more researchers in the whole world can read their books. The publisher should also be interested, selling more copies. And of course the researchers. I'd wish there would be an English copy of "Quelques méthodes de résolution des problèmes aux limites non linéaires" by J.-L. Lions.
In general, the translators are not working directly for the publisher. They are active mathematicians in research and/or teaching at a university. Most of them are no regular translators (see my examples below), having translated only one book so far. But you can look up Richard A. Silverman, who translated a dozen Russian books for Dover.
From German into English:

-"Linear Functional Analysis" (2016) by H.W. Alt:
"The present book is the English translation of a previous German edition, also published by Springer Verlag. The translation was carried out by Robert Nürnberg, who also did a marvelous job at detecting errors and mistakes in the original version."
Robert Nürnberg is a mathematician at the Imperial College London.
-"Vector Analysis" (2001) by K. Jänich:
"Speaking of translation, I would like to acknowledge the excellent work of Leslie Kay in translating the German text into English. We have exchanged detailed e-mail messages throughout the translation process, discussing mathematics and subtleties of language."
Leslie Kay is a mathematician at Virginia Tech.

From Russian into English:

-"Lectures on Partial Differential Equations" by V.I. Arnold:
Translated by Roger Cooke, University of Vermont.
-"Mathematical Aspects of Classical and Celestial Mechanics" by V.I. Arnold et al.: Translated by A. Iacob, Brandeis University
-"Mathematical Methods of Classical Mechanics" by V.I. Arnold:
Translated by K. Vogtmann, Cornell University, and A. Weinstein, University of California at Berkeley


Paper with lots of Greek letters I developed a system, and wrote a paper about it.  It includes formulas and pseudo-code.  During the course of development I used Roman letters in the formulas.  I eventually ran out of meaningful letters (letters that I could associate to some extent with what they represented), and started using Greek letters.  The development went on until somehow I ended up having about 8 Greek letters and 2 Roman letters used in the final formulas and pseudo-code.

Now that the paper is written, I wonder if having all of these Greek letters is unusual.  Would it be better to replace them with Roman letters?  Would it be better to use Roman letters with subscripts, such as t for time, and t_scaled for scaled time, instead of using Greek letters for that?

EDIT: To clear things up a little, my general question is: is it preferable to use Roman letters or Greek letters in a technical (engineering) publication, and is it acceptable or even preferable to use letters with word subscripts instead of entirely new symbols to label related variables or constants?

This depends entirely on your field, and specifically, what the norm is in your field. In mathematical fields like statistics, economics, physics, and math itself, and to a slightly lesser extent in chemistry and computer science, using Greek letters as variables is exceedingly common - in fact, it's unusual to see a paper that doesn't use a few, and there are many quantities for which the well-established standard notation involves a Greek letter. In other fields, perhaps that's not the case.

If you're still not sure after examining the norms in your field, I'd just go ahead and do it. Given that mathematicians use Greek letters all the time, it stands to reason that when you are doing math in another field, you should be able to do so as well.

However, I would caution you about one thing: try to make your variable names descriptive. That is, it should be easy for the reader to make the association between the variable name and what it represents. So when there is a standard notation for some quantity, use that; when there isn't, subscripted symbols like "t_scaled" are one good way to do it. They do take up more space on the page, though, and can make formulas look unwieldy, so you have to strike a balance between aesthetics and clarity of meaning.


Should I include funny pictures in my slides? I am preparing slides for a short (10min) talk at the group meeting. The talk is about a fairly serious piece of (pure) mathematics, and it so happens that there is a very relevant one-panel webcomic. A thought appeared to me, and got some support from my fellow PhD students, that it would be cool to include this comic, perhaps at the final thank-you-for-your-attention slide.

I am probably not going to do it, so I'm asking mostly out of curiousity: Would this be a bad idea to go ahead and include a comic on the final slide?

Note: The comic is genuinely funny (based on a sample of 6 non-randomly selected students). It is not - as far as I can tell - offensive in any way. It could come across as somewhat silly.

Human cognition is a strange thing, and I won't pretend I know it well enough to give you a guide, but I will suggest that you simply consider your audience and how you want them to move through the information.

A dense, heavy talk with few breaks will tire most audiences.

A light talk that doesn't require much thought will result in many people letting their mind wander.

A talk which carefully weaves the "story" with a variety of dense to light moments, may actually improve retention.

Adding levity in the form of a joke or humor, if the joke is very relevant to the talk, can actually increase retention, as long as it isn't too much of a distraction.  Placing it appropriately is key, though, and I wouldn't do it at the end, because that's what people will remember.  The last few sentences should be a quick summary of the talk and should be memorable.

Placing it in the middle, during a transition - for instance between the problem statement and the methodology - could be good, and allow a release of tension if the problem statement was pretty densely packed.

Starting off with it, as an into to the topic and a method to get attention is also a pretty good choice.

In all things, though, consider your audience first.  What is the journey you are taking them on, and when would be an appropriate point for a rest break, a transition, a wake-up, etc.


How recent should the English language certificate be to apply for Master thesis? When applying for Master in an European country, English certificates such as CAE, CPE, TOEFL, IELTS are required. Is there a limit about the "age" of the certificate?

I got CPE 5 or 6 years ago. Is it acceptable or a more recent is needed? The programs which I have seen, do not clear that out.

Yes there is an expiration limit on these language tests.

I believe most tests are valid for 2 years. I know for instance that the TOEFL test has a 2 year expiration date. Unfortunately, I do not have any experience with the CPE test, but I have personally never heard of any standardized test being valid for more than 5 years.

I would suggest you retake the test. That being said, you should contact the program you are applying to directly to get the most information about what tests are/are not accepted and for how long they are valid after taking them.


Show accepted (but not published) paper to potential advisor It is time for me to apply for graduate studies.

I am wondering, if I have a paper accepted at a journal or conference, is it OK for me to show this accepted paper to others (such as potential advisor for my graduate study) even if the journal or conference has not yet formally published (or made public) this paper?

In general, I would think so, but I suppose this depends somewhat upon the culture of the field that you are in. To be on the safe side, simply check with your co-authors and get their permission beforehand.


Course development: can I pay someone to make slides for the course? I am asked to start from scratch and develop a new under-graduate course this fall. I still have about 2.5 months left but since there are tons of research commitments ahead, I am basically a bit unpositive on whether I can get all the course development task done before that.. The central hurdle is to make slides for about 12 weeks' teaching load.

I am writing to inquire some conventions on course development. In particular, can I pay someone to make slides in my situation? If so, then:

do I need to acknowledge certain authorship for such cases?
where should I find such services?

Theoretically you can, but practically I doubt you will find someone qualified who is willing to do it for a reasonable price. Designing a course is hard work and pretty individualized. Look at how many different ways there are to teach the same course. Everyone does it differently and I hate teaching to someone else's syllabus and cannot image using someone else's unaltered slides.

As for acknowledging the author, you probably need to let your department know that you have outsourced this aspect of your job. You will need to make sure that the material is appropriately licensed so that you and the department can use it as needed.

As for telling students, I believe there is a fair amount of leeway regarding the reuse of material. Specifically, for many courses, you are not presenting "original ideas" so it is not plagiarism in my opinion. That said, when possible, redirecting students to the original source can be helpful.


Will the research activity during my Master's program seriously impact my PhD or career path? I've posted a few questions here seeking advice on my life as a first-semester graduate student. I have a question that is somewhat related to those, and also related to this question (What happens if you don't enjoy your research partially through your degree?) but felt it was slightly different and wanted to ask my own.

TL;DR

The lab that I'm at now has recently been heavily focused on one specific field of research, and I'm also expected to conduct research activity in that field and squeeze in time to work on things that I personally want to pursue later as a more serious PhD student and possible career. Will my research being heavily focused in an irrelevant area impact my future prospects of applying to PhD programs?

Long version

I'm currently enrolled in a Master's/PhD integrated program at a Korean University. The lab that I'm at does AI/deep learning research. My personal interests lie in computational linguistics, and I made it clear to my advisor that it's what I want to pursue and I wanted to work with those in the field at his lab, which he was happy to hear. I also told him that I have plans to complete my Master's here and go for a PhD to the US. He recommended that I finish my PhD here and go for a postdoc abroad, but that he's also "more than happy to let me go if it's what you want."

Recently, he's really taken a "passion" into this thing called "AI-driven drug discovery," where you're basically using deep learning techniques to find which chemical compounds may potentially become new drug components. It's interesting and important for sure, but it's not really what I had in mind when I first came to the lab or what I imagined to be doing later in life.

The fact that 1) I'm fluent in English, and 2) I'm "technically enrolled in a PhD program" and so will be at the lab longer than regular Master's program students has caused my professor to take a liking to me and him and other senior lab mates have really urged me to at least take a look into the field of bioinformatics. I thought "what the hell, I'll give it a try and if it's not for me then I'll talk to my advisor and back out."
 It is a bit naive of me to think that backing out of  research I've been engaged in will be easy.

I've talked to other seniors at the lab about my concerns, and  they all understand where I'm coming from and advise me to "do the bare minimum to keep me out of trouble" while spending all my time and resources doing research in things I want to and prepare for applying to PhD programs abroad (publishing papers, attending seminars and conferences, etc.)

I'm still a bit concerned though, as bioinformatics is a little distant from computational linguistics. My undergraduate degree wasn't even from a STEM field or linguistics either (international relations major and computer science double major). Has anyone either been down this road, or seen anyone go down it? From a professor who's seeing my application as a potential PhD candidate, how would it look if much of my prior research is in bioinformatics when it says I want to do PhD-level research in computational linguistics?

Any tips or advice are greatly appreciated. Thanks.

The further you are in your studies, the more your track record will dictate where you go. But I think that you are not at a point that experience in a related field is going to harm you. And, if you do things cleverly, you can gain very relevant experience.

For instance, you can gain experience in a relevant programming language doing bioinformatics (which is basically open to any programming language), and this technical experience will be relevant to any computational work you do. This seems like a great opportunity to gain that experience while improving your academic track record. I believe that in both these fields a PI will be most interested in someone with technical knowledge (given that a PhD in applied CS is not a course in CS), and luckily for you, this knowledge is independent of whether you are studying genes or phonemes (sorry for that terrible pun).

It's really rare in academia to be able to do exactly what you want. You'll always be carrying out research under someone else's vision, and rather than trying to find the perfect position or such, you just need to find a way to shine in that project/position/etc. As I said above, I believe that the credit and technical experience you will gain in this current position will be relevant for computational linguistics also, especially given the stage you are at. If there is a time to diversify your abilities, earlier is better. At a later stage this will have different consequences.

So I think you should take the bull by the horns and learn as much as you can. I can't imagine someone turning you down from a PhD because of being involved in a computational project simply because it doesn't perfectly overlap their field. All these computational-related fields have a huge overlap nowadays, and computational linguistics is in itself an interdisciplinary field.


How to handle a common misconception when writing a Master's thesis? I'm writing my Master's thesis in a field where there exists a common misconception regarding the properties of a material, stemming from some papers published in the 80's and 90's and disproved in a more thorough study published in the 00's. While most of the serious publications in this field cite this newer paper, the misconception still thrives and is sometimes even used in the papers citing the article that disproved it. The properties of this material are of great importance for the field.

The only reasonable thing is of course to use the new data in my thesis, which I will do, but since the misconception is so common I wonder if I should mention it in the report.  I can think of three different ways to handle this:

Don't mention the misconception at all.
Mention it, but in a general way and not providing sources. For example "A common misconception is ... "
Mention it, and provide sources. "A common misconception, seen for example in [references]... "

Usually, it is a bad habit to make statements without backing them up with facts, which makes me doubt option 2. But on the other hand, option 3 seems a bit too aggressive.

(This is my first post on StackExchange, I hope I didn't mess things up to much.)

I agree that option 2. is not good. If you want to mention the misconception but avoid shaming anybody, you can write something like

  "While the belief in the 1980s and 1990 was … it was proven in […] that in fact…"

That way, no one is blamed. If, however, you feel that you need to explicitly mention that still some people follow the old belief, you should back this up by citations and I don't see a way around option 3.


Math Undergrad Wants to do Master's of Statistics BACKGROUND

I am a Canadian who is just finishing my undergraduate studies in mathematics. I enjoy mathematics, but I have recently realized that I would rather study statistics in graduate school, and I am excited by the idea of working as a professional statistician. I really did not take very much related to statistics in my undergrad (intro to probability, intro to statistics, intro to stochastic processes, advanced probability). I did however do very well in my undergraduate math, so I have solid grounding in analysis, and other kinds of math used in statistics. I also have some research experience through an NSERC USRA (canadian undergrad research award).

Those in charge of the stats masters programs at my school said that we could make it work, and encouraged me to apply (and essentially told me I would be admitted). However, while my school is solid comprehensive research university, I do not think that its stats department is all that amazing. But, seeing as I would be a little behind, it is sort of a positive for me that the program is not super-elite. It is late for my to apply elsewhere for stats this year.

GOAL

My short term goal is to have a good experience as a master's student in statistics - I want to be exposed to both theoretic and applied stats and probability. My longer term goal is to work as a professional statistician. However I do not want to rule out research.

OPTIONS

Current School offers an 8-month coursework-only Master's, including decent financial support though a TA-ship. I like this because it is short, and what I am looking for in the short term: learning statistics. While I expressed some doubt about the stats department, I have no doubts that the courses will be of high quality.
Current School offers a 16-month Master's with Thesis, with good funding. This seems better and more comprehensive, however that is an extra 8 months during which I could be gaining work experience. Also, because I do not think my current school's statistics department is so great, I am less inclined to commit to research here.
Take some time, take some extra undergrad courses in stats, apply next year to a wider range of stats schools. I am not a huge fan of this option, as I have grown a little tired of being an undergrad and would like to gain some other sort of experience. It is also makes more financial sense here to study as a graduate student.
See below:

QUESTIONS

Is it possible/advisable to use the coursework [masters] at the current school as a way to learn statistics, and possibly pursue graduate studies elsewhere, perhaps after a period of working? Is a non-research masters an asset at all from the point of view of admissions to other graduate programs?
Because (1) seems convoluted, what are further pros/cons of the above three options that I may not see?

(On a meta note: I think in many ways this question could be applied to any field, I am not asking a whole lot about Stats specifically. So I hope it is considered appropriate, I am not so familiar with SE Academia.)

The good news is that it almost doesn't matter which path you take; you've got sufficient drive and determination, and from your observations about yourself, skill.

You're clearly interested in getting out there and working, which is great. Just remember that the work will always be there (for decades and decades to come), and that your time at school will be finite; try to enjoy it. :)

To that end, I believe Option 2 is a really good option for you, and is the least risky option. TA-ships are fantastic, and if you can score one while being in school, it really helps cut down on financial pressure. Additionally, you're giving yourself time to really develop your own stats knowledge which will help you in either corporate or research environments. Even if your stats department isn't that great, your research is what you make of it; plenty of awesome people have graduated from non-elite universities and have since done amazing things, and it's not unusual to seek a little guidance or insight from people outside your department. Besides, if you're as talented as you sound, being a shining star in a department has its advantages. ;)

Getting to your Question 1, if you finish your Bachelor's while taking extra stats coursework, and then enter the workforce, that's fine, but it then becomes harder to reenter grad school due to various other real-life factors such as having to fully support yourself, possibly getting married (and/or having a kid) which may bind you to some location, and so forth.

Also, maybe your prospective job after Bachelor's will pay for your education, but going to school under those circumstances takes a bit longer, and it also means the school will have to be close to your job (unless it's an online program or whatever). It's just too easy for complications to creep in once you step foot out of school.


Copyright for creating a video that is a chapter-by-chapter Analysis of a Technical Book? There is a technical book that I like a lot and is widely respected in my field.  It has about 80 "rules" in it with example code.

I would like to create a series of videos to further explain and review each of the "rules".  I will narrate the video in my own words.  My goal is for the video series to be like a tutor that is walking the viewer through the book.  I plan to fully credit the author and cite his work.  Some questions:

Can I use code samples from the book if I give proper citation (title, author, page #)?
Is creating a chapter-by-chapter review of a book and putting it on YouTube considered an ethical gray area?  To repeat: every video will fully credit the author of the book and it will be obvious that I am explaining ideas in my own words.

I am asking this question here because of all the stackexchange sites, people here seem to be the most well versed in copyright and fair use.

Thanks.

Disclaimer 1: I am not a lawyer, I know sh*t about law, it is not a legal advice and you should consult with a professional.

Disclaimer 2: ethics and law are two different question, this answer tries to give ideas about the law part (and you should not fully rely on it, as stated in D1)

If you using substantial amount of the book (its code, its ideas), especially blatantly copy its structure making it obvious what you copied, then you are way beyond fair use and you are in a gray or even red copyright area. Depending on publishers they generally put some short examples in their copyright session what constitute fair use, you can check those. What you describe here goes far beyond this. Also the whole purpose is to spread it to wide audience on youtube, so publisher can claim that they suffer significant loss of revenue, because the whole thing with all the details and secret sauce is on YouTube.

What you can do about it?
You can try to get a permission from the publisher (most probably the author himself cannot give this). It may help if you have a reasonable discussion with the author / publisher about your idea and tune down the "I will discuss every little details of your book and copy out all the codes" part. For example it helps if you have your own intellectual effort in this whole stuff, e.g. analysing problems not presented in the book and show how the books method can be used, and not just reading/summarizing the book on video.


Unsatisfactory Instructor Evaluations: balancing of expectations of engineering students I teach undergraduate and graduate level courses in mechanical engineering at a research oriented university in the United States.  I am a teaching track professor and my sole responsibility, on which I am judged for pay raises or promotions, is teaching efficacy.

The courses I teach have a strong mathematical component to them.  Some notable examples would be: computational fluid dynamics or finite element methods.  For those here familiar with these courses, you would know that calculus background is necessary to understand the nuances.

However, I find that the students I teach this to (mostly 4th year undergraduate students) balk at the prospect of doing some analytical "pen-on-paper" work and would like only to know how to use relevant software skills for these, with no mathematical background.

This leads me to receiving unsatisfactory end of semester evaluations (3.90/5.00) from students with a lot of them complaining that "the course is too math-y"(verbatim).  The department requires teaching professors to consistently receive a 4+/5.00 for courses they teach and base promotions, continuing contracts and raises on this.

Unfortunately, I refuse to pander and just teach students "software-button-clicking" alone. Software skills can be learnt from Youtube and they don't really need me to teach them that.  I continuously tell them that mathematical/fundamental analytical skills are far more important because the software landscape is quite fickle and ever-changing based on industry whims and fancies.  However, fundamental mathematical skills are resolute and robust and may be applied to most engineering problems.

Has this been encountered by other folks on this SE and is there some effective method you have devised to counter this? My university is significantly "engine research" driven and students end up getting jobs at the "big 4" automotive companies.  Perhaps I need to ply my trade at a different department like "applied mathematics"?

On my part, I juxtapose software results with analytical results continuously to explain how analytical results are necessary for validating software results.  However, students are under the impression that the "software is always right" irrespective of whether or not their problem set-up and boundary conditions are correct or not.

The professor that taught me statistics dealt with this basic problem, which is that students would come into the course thinking it was like any other "narrative" style of course (like a history class), but the truth is it was a math class that was not listed as MATH 3XX.

Part of the job of a student is to pick courses, ordering them and balancing them into a semester that allows them to handle all of their classes. If they do not have the information they need to balance their schedule (as some classes are naturally heavy loads and others are light), they cannot do their job. So here's how I learned to help them do their job so that they would feel that you were doing your job.

Reset Student Expectations

On week 1 or 2, assign a special test. Include absolutely the most challenging math you expect them to do for the entire semester (not hard for the sake of being hard). Make it  absolutely clear that this course does in fact require previous knowledge and ability, and that this test is designed to do just that - test their readiness for this class. You can make it an in-lab assignment and just give credit for doing it - you can give them the answer key and let them grade themselves.

Clearly explain to students that if they cannot complete this test satisfactorily, that is information for them to decide if they are ready for this class. When I ran this lab session I personally explained to students that if they weren't willing to spend at least X hours per assignment per week, they would be unlikely to do well and should reconsider their plans now while they can still re-arrange their schedule. I had a few students drop by the next week, but then everyone who stayed stuck with it all semester.

Don't Make Students Feel Dumb

One of the great dangers of being an expert and a teacher is that you become very distant from that point in time when the material was truly difficult for you, and you lose some of your understanding of what it was like to not know. You are also likely to have an IQ far beyond the average, as well, so you might not ever have experienced this material as difficult - which makes it even harder to avoid this mistake.

I personally remind myself of the time where I had scrawled out about 8 pages of hand-written calculations and equations to solve a factorial analysis of variance by hand, because my professor said it was important. If someone at that moment had looked at what I was doing and even vaguely implied "oh, that's mostly just basic algebra, that's not so hard" I would have stabbed them in the neck with my pencil right then and there. (The pencil was dull and my wrist was tired, so they would have probably escaped serious injury. But still!) Maybe it wouldn't have been hard for them, but it was a challenge to me.

With your advanced understanding of mathematics, you might unintentionally be sending your students a message along the lines of, "oh, this math is pretty basic first year stuff, you shouldn't have any trouble with it". Math is often hard and time consuming and mind-bending and forgotten quickly, even if it is important, and to imply otherwise is insult your students intelligence and character. This will likely result in them not liking you, and worse - they may not learn as much from you as they could have.

Be honest, but take care to honor their struggle with fundamentally non-trivial material. Students appreciate "I know this may seem hard, but you can work through it" more than "this is easy, work harder".

...and make sure the material Is Really Relevant

Yes, math is important and sometimes being able to do it by hand is even important. But I've had teachers include complex material based on the idea that it would be on X industry test that was 3+ years away and that I would not ever be taking, and could otherwise be looked up in < 10 seconds if I really needed it. Sure, now if I get stranded on a desert island I'll be able to calculate proper binary subnet masks so I can build a complex routed network for all my coconuts, but otherwise I'm still a little annoyed I spent hours on that mess when I could have spent it on my research projects.

Motivating the material with a calculation the computer can't solve but they can do it by hand, if such an example exists, can help. It may also be helpful to really drive home the point that if you don't understand the underlying math you'll click stuff that is laughable and makes no damn sense, but the software didn't know any better so it did what you asked anyway.

Still, make sure you really aren't including tough material (according to the students) just because you really think its cool and is technically somehow applicable, but not really necessary or very valuable to the student. Those topics might be a perfect fit in another course - just not this one.

I think you'll find that if students are made to understand what will be expected and necessary upfront, you empathize and honor the challenges your students deal with, and you pair down the material to what truly best serves students, you'll find that not only will students like you more and rate you more highly - but they'll also learn more and the class will be more fun to teach, too.