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What are the benefits for universities/professors to record online courses?
What are the benefits for the universities and particular professors  in recording online courses (MOOC)? Do they get paid by Coursera and similar sites? Do they pursue publicity?
I know that they are providing a useful service by spreading education to everybody in the world, but what do they get in exchange? Do they hope to get more students enrolled, or more public exposure for the university? Or do they do it out of the kindness of their hearts, or for some other reasons?

Why the "enormous fees"?  Running a university is very expensive, and the money has to come from somewhere.  Most universities operate on a non-profit basis, so the fees (along with other funding sources) go to cover their costs.

+1 for "enormous fees".
@NateEldredge in a non-profit organisation people are still getting paid.

May be I shouldn't have used word "enormous", but I was just contrasting the free-for-all lectures and high fees for in-class students.

I record my lectures (when possible) for the following reasons:

Easier access for students who can't attend class.  While I generally want students to come to class, there are valid reasons for being absent (e.g., I'm currently teaching classes to military members who often have duty that preempts class attendance).  I can also point students to a video to review if they ask me questions explicitly covered in class (and also for general review).
Open access.  I think it's pretty cool to live in a world where it is possible to get free access to videos that enhance knowledge.  I feel like I'm playing my little part by putting my lectures online.
Introspective review.  It can be extremely beneficial to review your own teaching methods, although I don't have time to do this for all of my classes.  I have gone back to particular sections to review, and I almost always find something I could improve upon.
(minor) The America's Funniest Videos factor.  I've had clips that have been unintentionally hilarious, either because of something I've said, or because of something students have said. :)

Universities have their own reasons for putting classes online, and you've already listed a number of them.  I'd like to believe that most of the reasons are altruistic, with sites such as MIT's OpenCourseWare and Stanford's Online Courses providing no-strings-attached courses for free.  I would also hope that someone is doing research on these types of course offerings, to see if they are really having benefits to the people that watch them.  I don't believe the bottom line at extremely selective schools will ever be hurt by offering free course material, but if they do start feeling the pinch I imagine they will change their models.
Sites like Courseara are for profit and starting to make money by offering to verify certificates of completion for a cost.

Why, then, some [Universities] charge enormous fees for attending courses?

The question of college expense is a can of worms that has as many differing answers as there are people asking about it.  Selective colleges charge what they do because (1) it is expensive to run a brick-and-mortar college, and (2) the applications keep rising and kids can still get loans, grants, and other aid.  Obviously it is much more subtle than that, and it would take more than a few free economics courses to get to the bottom of it.

@DamienIgoe True, though there is something particularly romantic about the School of the Air!

Thanks for your reply, @ChrisGregg! Your personal reasons are very laudable, and I understand and support them.
But from the point of view of university: it spends additional money on professors to record videos/prepare material for online course (not necessary directly, but it still pays for professor's time), and then puts it online for free, it is a loss of money which is not offset by the students paying fees - unless you increase them. But in this case I guess students will start to think twice before paying fees, considering the option that they can watch the lectures online for free.

I don't believe the bottom line at extremely selective schools will ever be hurt.

Yes, I tend to agree, but then it can lead to situation that only "elite" places remain. Why would you go to a smaller school if you can watch videos from top institutions for free?

@Max -- I think most of the online courses from places like MIT are simply taped lectures from already scheduled classes. Some do incur other costs (and of course there are hosting and equipment costs), and some courses are explicitly produced to be online. There is also something to be said for being a ground-breaker in the arena.  See, for example, Stanford's Class2Go initiative, which garnered a good bit of media attention when it was launched.

Why would you go to a smaller school if you can watch videos from top institutions for free? —  Because nobody goes to college for the lectures.

@JeffE I guess I was nobody as an undergraduate.

In addition to the good non-financial reasons mentioned, there is also a more financial reason - promoting your own book. I am sure this is not the main reason to give online courses, and having the book is not an explicit requirement, but it does provide a way to benefit financially.
For example, Prof. Daphne Koller from Stanford and Prof. Yaser Abu Mostafa from CalTech both offer free online Machine Learning courses, and both have relatively recent books that are top best-sellers on Amazon.

I believe that the university and professor are promoted by showing their work, people can watch their courses and see how good they are, and spread the word, this will increase the prestige of the university. Another thought is that this shows the university cares about the lessons and gets into this trouble, thus the faculty seem more invovled. A more benevolent thought is that it might help students from other universities.  I, personally, have gained a better opinion about MIT for example, or a different one anyway, having used it's online courses repeatedly to cover the gaps left by my professors.

I was under the impression that part of the reason courses are currently offered free is to gather data about how people use the material/how they study etc, and that's (partly) why they tend to have questionnaires about you at the start.
There's also a more cynical way of looking at it. Shortly after I first finished a course, I got an email saying lots of people had been asking about a course on a particular topic; there wasn't a free course available, but there was one you could do for $400.


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Licence that converts to GPL after publication but is copyrighted prior to publication
I would like to post an repository on github that includes data and analysis code in R. The analysis and data forms part of a journal article submission. I'm happy for people to view the code and data prior to publication (in particular, it might be an easy way for reviewers to examine the code). However, I do not want anyone publishing  analyses of the data prior to acceptance and publication of the journal article. After publication, I want to encourage people to re-analyse, re-use, re-publish (e.g., with a GPL licence with an encouragement to attribute).
Obviously, I could just keep the data and analysis code a secret until after publication, but I thought an appropriately worded licence might be more appropriate. I thought about just writing in plain English that the work is copyrighted at this time, and will be converted to GPL at a later date following publication.

Is there a standard way of licensing data and code so that people cannot republish the data and code until the corresponding publication has been published?
Or is it better just to keep the data and code secret until after publication?

UPDATE: I suppose there is a legal perspective to this, but I know that academia has its own norms and conventions regarding attribution and respecting the wishes of authors. So I'd be particularly interested in answers framed in that context. I.e., My broader aim is to be the first to publish my own research, generally get attribution, but also allow others to build on that work. So I'd be interested also in what is considered good practice when you are in the situation of wanting to share data and code while an article is being peer reviewed, but not wanting to lose your right of first publication.

This doesn't directly answer the question, but one possible workaround (depending on your perspective) would be to publish a preprint when you release the code, thus establishing your priority and giving people something to cite if they use your code.

Also, it's not totally clear to me that the legal system is the best way to deal with the issues you bring up.  Asking people not to scoop you might be just as effective as legal threats.  Especially since it's unlikely you'd ever actually sue anyone for infringement.  That said, I think it's an interesting question, so (+1)

Honestly, I doubt that copyright protection is of any use. The copyright on the code itself does not* extend to data produced using the code. Similarly, the copyright you would hold on the paper submission covers* that particular presentation of the data, but not the data itself. So as long as someone is physically able to view your data, I believe there is no legal avenue to prohibit them from doing their own analysis on their data.
However, for another researcher to take the output of your code and perform their own analysis in an attempt to scoop you, when they know you have your own paper doing the same analysis pending, is ethically very questionable. If it came to light that something like this happened, I think the academic community would strongly frown on it. That's a very strong incentive for any other researcher not to do this, and so I personally wouldn't worry about it.
Besides, if it does happen, the other researcher will have to cite your code anyway so you still get credit. This can actually be a good thing. I would recommend including in your code a notice of the form

Please cite the following reference if you use the results of this code in a publication:
[reference to paper or code]

(see this example from my own publication history) If you're worried about someone else abandoning all pretense of ethics and just using your results without citing them, rest assured that it is very difficult to pull that off, and it constitutes academic fraud, which is a career-ender if it's discovered.
And finally, as a practical matter, you have a very large head start on anyone else who might want to publish an analysis of the outcome of your code. Don't underestimate the time and effort it takes for someone else to go through your code in enough detail to learn what it does and figure out how to use it enough to generate original results, and then to write and submit a paper and have it reviewed, typeset, and published.
One more point worth mentioning:

So I'd be interested also in what is considered good practice when you are in the situation of wanting to share data and code while an article is being peer reviewed, but not wanting to lose your right of first publication.

You don't have a right of first publication. Not legally, anyway. If you want to ensure that you are the first one to have an opportunity to publish a paper based on some result, the standard practice is to keep the result private until you are close to publishing the paper yourself. But keep in mind that "publishing" in this context doesn't have to be peer reviewed. For instance, in physics it's very common to put a paper on arXiv before submitting it to a journal. That establishes the authors' claim to the result before it enters the peer review process.
*informed layperson speculation; see a lawyer for a definitive statement

The GPL FAQ item "Is there some way that I can GPL the output people get from use of my program?" agrees that license restrictions on a program cannot impact data produced by that program. (For what it's worth, that FAQ probably was drafted with the oversight of a lawyer.)

You write that you

do not want anyone publishing analyses of the data prior to acceptance and publication of the journal article.

I am not a lawyer, but I don't think there's any license to enforce that. Once you publish data, other people are free to work with that data, and publish their analyses (although they might not be able to republish the original data, at least not in the same format as you did). As Wikipedia writes, copyright does not cover information itself, it just protects the way that it is presented, or the verbatim description. If you want to prevent others from publishing analyses of your data, I think the safest way is to keep the data confidential until you publish your paper.
On the other hand, if you don't put a license on the data, you have whatever copyright protects there, so others will not be allowed to re-publish the data in the same format. Therefore, I think the risk that others publish an ernest journal based on your data is not that high, unless it's really spectacular data.
The code is a different issue of course. You hold copyright on that, and if you don't put a license on it, others won't be allowed to republish it.

A1 :  The legal department at your university or company should be able to help you out with this type of request.
A2 : This depends on the journal to which you are submitting.  Read their rules on copyright of submitted software and publication beforehand.
Other comments / ideas :
I have software freely available that I have submitted to a journal before publication (although, this may not have been the best idea) and software that is also ready and that I use that I could make freely available, but have not as of yet.
An alternative would be to say that interested parties may email you for access to the code before publication happens.
You could always publish the data (or paper explaining the data) on a pre-print server so that you cannot be scooped and then also publish the corresponding code.  This will outline clear dates as to who published the research first.

I'd like to point out that some universities might not have a legal department (or might not care about these matters if they do).

@Trylks -- Very true!  This is completely dependent on your institution.

To address your revised question:

My broader aim is to be the first to publish my own research, generally get attribution, but also allow others to build on that work. So I'd be interested also in what is considered good practice when you are in the situation of wanting to share data and code while an article is being peer reviewed, but not wanting to lose your right of first publication.

The usual practice in my field (mathematics) is that when the project is finished, you submit it to a journal, and simultaneously post it to arXiv, a public preprint server.  This establishes your priority in two ways, and lets people start building on it immediately.

Who prevents you from releasing the code under GPL only after the article has been accepted for publication?
In such case, probably you cannot add GPL header to the files in advance but unless it is very large project, this should not be a really big problem (you may write some script to add headers if it is really a lot of files).
If you setup a public repository on GitHub, by doing so you allow to view and fork it. If this seems not acceptable for you, publish on the university server instead and only publish to GitHub when you open source it. You can add any restrictions you want as long as it is your fully owned code. Just I am not sure if it will be easy to enforce these restrictions if somebody does violate.

Your right as a owner of intellectual property, allows you to release and allow reuse of that "property" in any way you feel correct.
The use by a third party of your "property" is not allowed unless the party has a way to demostrate that you have somehow allowed it.
The way you allow it is up to you.
Obviously that creates an enormous exercise for the judge, that could be called to decide on the fact. Essentially there is a big legal hole, because I could decide for example to sell a book and to allow the purchaser to read it ONLY ON NIGHT from 8pm to 11:59pm.
That means that if you use the book in other times you are penaly responsible.
So that is the reason that the legislator should take some decisions because if not a lot of problems may arise.
The limitions that the author may impose, may be illegal etc.
Most important is that fact that licenses may be so long and articulated that no normal person may be able to understand them and so that person shouldn't be liable for the infringement of them.
Any way my opinion is that you may impose any rule you may like. That is a one paty action and the other party should demonstrate that she is legaly using your work.

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How to estimate standard error of journal impact factor based on impact factor and number of citable papers?
The impact factor (and other indicators of citations per document per year) is often used (controversially) to evaluate the research impact of a journal.
Critics of the impact factor often point out that it  based on a skewed distribution with outliers. For example, many papers may have zero citations, another set may have a small number of citations, and finally a small set of papers may have a large number of citations (e.g., 50 or 100, etc.).
In general, I've read that this profile is typical of many mid-tier journals.
Thus, this is used to suggest that the impact factor may be influenced by outliers.
I agree that this distribution of citations does highlight that the impact factor overestimates the median citations per paper (as is the case with any positively skewed count distribution).
But another critique is that the impact factor is unreliable because of this distribution.
Thus, my question is:
What formula can be used to calculate standard error of the impact factor for a journal?
Presumably, this would help both critics and advocates of the impact factor to be able to quantify the uncertainty in estimating the impact factor. It would also assist in assessing whether it is appropriate to say that the differences in impact factor over time or between journals are a reliable difference.
Initial thoughts:

The standard error of the mean is commonly estimated as: s / sqrt(n), where s is the standard deviation of citations per article, and n is the number of citable articles. So presumably, the main factor that would reduce the standard error would be the number of citable articles published in the journal over the period. But unless we have the raw data, we wont have the standard deviation and the skewed distribution might lead this formula to underestimate the standard error.
Use existing literature to determine the distribution of citations over articles. Hopefully, its a distribution that can be approximate by knowing only the mean, or where the mean provides a good estimate of the standard deviation
Then apply a formula to get the standard error of the impact factor.

Why the down vote? Honestly, curious. Impact factors are relevant to academics. Presumably, being able to quantify the standard error of measurement would be beneficial both for people who like them and those that do not. For example, for those who are critical of impact factors, they could  say "look, the difference between 1.7 and 2.2 is not reliable"; but that requires them to have some estimate of the standard error. Such information would presumably be useful in promotion, grant, and other contexts, where you are making an argument about research impact.

I wonder if journals provide their own raw data that will have a huge impact on their publicity policies.

@Mithun you could probably get raw data from scopus or web of science fairly easily for one journal. You'd just need to work out how to do the correct dates for publication and citation windows.

Oh, I forgot. Another issue will arise as: when we try to obtain the citation count for an individual article within a time frame, how the citations outside this time will reflect the std? I know there is overall citations count and last five years citations count.

Standard error is really only meaningful for normally distributed statistics.  I doubt citation counts are normally distributed or even close.

@AlexanderWoo that is not true. Easiest counter example: the sampling distribution of regression coefficients in a linear regression model follows a t-distribution if the null hypothesis is true. More generally, the standard error is used to characterize the spread of the sampling distribution. You can use that for any sampling distribution. If you want to derive more from that (e.g. confidence intervals) you need to be careful to correctly apply the appropriate formula, but it is always good advise to be careful and do things correctly...

I think the standard error (of the mean, commonly estimated as s/sqrt(n) as stated in the OP) is a robust and good estimate for the uncertainty of the impact factor. It would certainly be interesting to know this together with the impact factors. Unfortunately, the standard error cannot be computed merely from the impact factor and the number of citable papers.
Note that the impact factor, being the average citation count, follows a normal distribution, even if the citation counts themselves don't (according to the central limit theorem).
A completely different question is whether, in view of skewed distributions of citation counts, the traditional impact factor (=average citation count) is a good measure for journal impact.

So I guess that just leaves the question of whether the standard deviation can be estimated from the mean (i.e., the impact factor). My guess is that  a reasonable approximation would be possible, especially if someone did some research. For example, my rough guess would be that the SD might  be around 1 to 2 times the mean (but that the ratio probably gets smaller as the impact factor increases); but I'd need to see more data to know exactly how it works.

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Is a PhD the highest degree?
I am curious to know whether PhD is the highest degree one can earn? Is there any other degree beyond that, if so what is it and what are the universities offering the same?

The degree you're looking for (at least in the sciences) is called "Doctor of Science" and you can read all about it on Wikipedia:
Doctor of Science
Edit: As aeismail noted: Sometimes this degree is considered equivalent to a PhD and sometimes it's considered beyond a PhD.  This distinction typically varies by country (all this is listed on the Wikipedia page).

Be careful—a doctor of science is sometimes the equivalent of a PhD. In Germany, there is a special term given to this, known as a "Habilitation," when it's beyond the first doctorate. Perhaps the better term is "higher doctorate" or "second doctorate."

It depends highly on your university and national system. The Doctor of Science title has already been cited by Dan C, and several European countries have a higher diploma called habilitation.

@CharlesMorisset it's definitely not a diploma, but I think it qualifies as a degree (“an academic rank conferred by a college or university after examination or after completion of a course of study, or conferred as an honor on a distinguished person”)

It's not a degree, it's a hiring process. You usually go through the agrégation to become a teacher, and the state guarantees that you obtain the position if you obtain the agrégation.

@SylvainPeyronnet That's not true for "Habilitation" in Germany. It is threatened to die out; it used to be a necessary but not sufficient requirement for attaining a professor position.

@Raphael the answer has been edited, my comment is about the agrégation, not the habilitation.

Address and abbreviations depend on country. In Germany, you become a “Dr. habil.”. In France, it is abbreviated HDR (Habilitation à Diriger les Recherches), but it does not change the form of address.

At the risk of answering a question that the OP may not actually be asking....
One of the biggest myths to deprogram grad students of is the idea that the Ph.D is "the highest degree" or is in fact in a well-defined ordering relationship with other degrees. It is true that a Ph.D will typically require other degrees as a prerequisite, and it is also true that (as far as I know) no degree program requires a Ph.D for admission. However, there's no useful sense in which the Ph.D is "highest" in anything. It is a certification that you can do research, and is almost always a mandatory step before getting a research position in academia.
But by that logic, an MBA, a J.D or an MD are also "highest" degrees.

And this is why many statistics in the US do not count faculty with Ph.D.s but rather "faculty with terminal degrees for the field." I do carefully say many rather than most.

And then you get the MD/PhDs (or the JD/MD/PhD I once met...) and it all goes pear-shaped.

An M.Eng. is also one of the ``highest degrees'' one can attain. Perhaps the OP means to refer to terminal degrees?

This is true in my country (Vietnam). For most people, especially who aren't academian, a degree after a PhD is... professor :D

Many countries have higher degrees than the PhD.
In the UK, there's

Litt.D Doctor of Letters / Literature
DSc Doctor of Science
LL.d Doctor of Laws
D.D. Doctor of Divinity (the highest)

Each of these typically requires the submission of a body of work - a research portfolio - together with a critique of the work. Or they may be awarded as honorary degrees; see the links above for the requirements for the degrees from the University of East Anglia (Litt.D, DSc, LL.d), and the University of Oxford (D.D.), accordingly.

I thought the DD was more of an honourary degree - I don't know anyone personally that would consider it higher than the other degrees you mention?

Another concept of "next step after PhD", at least in some countries, is the notion of an 'academic', i.e., a member of the relevant national Academy of Sciences.
That membership is in essence an awarded/elected degree for continued contributions to science and demonstrated expertise.

I heard that in Russia they have an equivalent to the standard Ph.D and a sort of "second Ph.D" after that, that is way harder to get than the first. One of my Russian friends argued that it is harder and rarer than the European "habilitation", but I guess it is open to debate to see whether it is just a matter of opinion.
Here is the corresponding article in Wikipedia:
http://en.wikipedia.org/wiki/Doktor_nauk
(On an unrelated topic, I think the name is quite cool.)

Yes, the classic USSR higher education process has a 'candidate of sciences' that is considered somewhat equivalent to PhD; and you'd get a full 'doctor of sciences' degree after multiple years of post-doc research&teaching.  It might be considered somewhat analogous (but also different) to USA concept of tenure track.

Actually this system was used in the whole Eastern European block, but disappeared as most of those ex-communist countries joined the EU and coordinated their degree systems to the regular Western one.

And further after that one can become a correspondent member of the Russian Academy of Sciences, then a full member. There's (rough figures) simultaneously only 1500 correspondent and 700 full members at any given time.

In Finland, someone with a doctor's degree and additional body of scientific work equivalent to another thesis can apply for the title of docent (dosentti). The title gives the right to mentor PhD students. Docenture is a degree in the sense that it does not imply employment at the university which bestows the title.
At least some professors consider it kind of a vestige and it might be phased out at some point.


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What words to describe "revisions" and "resubmission" to distinguish revise and resubmit versus submission to new journal following rejection?
This question was motivated by a desire to have a clean set of terms to describe the life cycle of a manuscript from draft to publication from the perspective of the author.
I could say:

I am "revising" my paper and "resubmitting" it.

Obviously, this could apply to (a) the situation where you have submitted a paper and been given the option to submit an updated manuscript (i.e., a revise and resubmit); or (b) you received a rejection letter and you are improving the manuscript with the intention of resubmitting the manuscript to a new journal.
I was wondering what concise language can be used to distinguish these two types of revising and resubmitting?

One should note that "revise and resubmit" is essentially a shenanigan invented by journals to make it look like their article processing time is lower than the real one. The proper name would be "major revisions recommended".

@Federico From my experiences I have found reviewer requests for revisions to be an excellent way of improving a manuscript before publication. So I don't quite get your point. Perhaps also I haven't clearly articulated my motivation for this question. I like to conceptualise where each of my manuscripts is in the publication pipeline. And when I describe each stage of that pipeline, I like to have a simple one or perhaps two word phrase that captures the stage.

Some journals use the term "major revisions requested/recommended" to indicate essentially the same concept as "revise and resubmit". Essentially, this means that there are several nontrivial points to address and parts to improve, but you should submit an updated version of your manuscript (and it's likely to be accepted, since it will be probably handled by the same reviewers). So, why do some journals insist on calling this updated version a new submission? My understanding is that the only reason to do it is so that their statistic "time between submission and acceptance" looks better.

Links supporting this view: http://academia.stackexchange.com/a/40906/958 https://dynamicecology.wordpress.com/2014/03/12/tell-me-again-what-major-revisions-are/.

@FedericoPoloni I see the point you are making. I'm seeing the problem more from the perspective of conceptualising the publication workflow. From this perspective "minor revisions", "major revisions", and "allowed to make new submission" are all conceptualised as the same step in the publication process (i.e., "revisions"). They just reflect a distinction in the amount of work to be done, the probability of ultimate acceptance, and perhaps whether new reviewers will be assigned. But in terms of conceptualising the process, they all mean "the publication is with me and I need to make changes".

My concept of a lifecyle. I've used a diagram to disambiguate the terms rather than using sentences.

Thanks (+1). I just had a few questions about this workflow: (a) Where is publication acceptance in this process? (b) does "resubmit" mean submit to a new journal or just submitting to the journal following a request for revisions? (c) does this workflow imply a distinction between "revise and submit" (i.e., following rejection) and "revise and resubmit" (i.e., following revisions)?

@Jeromy Anglim - I meant "submit" is always the first submission of a text to each journal. "resubmit" is sending it back to that same journal. You can revise and submit elsewhere as an alternative.

I personally tend to distinguish these words as follows:

"Revise" and "Resubmit" are reserved exclusively for updating a manuscript with the same journal.
Shifting to another journal is "Editing" and "Submitting again"

A submission to a new journal is considered a fresh start. So in that case, you would speak of 'a submission', regardless whether an earlier version of the manuscript was rejected at another journal.
A revision (of a manuscript) always refers to an earlier version, and is to be used exclusively in a context where the earlier version is known. So you can discuss a revision with your co-authors (even when that was submitted to a different venue), but towards a new journal you would not do that for an unpublished work, since they are unaware (and typically also not interested) that it might have been rejected elsewhere.
In case that you hand in a extended version of a conference article, then you might speak of a revision (but it would be better to just call it an 'extended version'), since the earlier version is publicly available.
Only when submitting a reworked version to the same journal, you would speak of a 'resubmission'.

Just to clarify, I understand your point that when corresponding with an editor you would not draw attention to the fact that the manuscript has been revised following a rejection from a different journal. However, I'm more interested in how researchers conceptualise the publication workflow. I.e., you have a bunch of papers that you are working on, and you want to say quickly what is the status of each paper.

I certainly think differently about the following three types of papers: (a) a paper that is in draft form but has never been submitted to any journal; (b) a paper that has been rejected and needs to be submitted elsewhere generally following some revisions; and (c) a paper that has received a request for revisions by a journal. I wonder how what you say above relates to that perspective.


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How to keep track of deliverables for supervised students when you supervise many students?
Background: In my area, academics often supervise a large number of students (e.g., 10, 15, 20 students). Many of these students are doing a small thesis as part of either their fourth year or coursework masters.
I am able to keep all these projects in my head, I do have documentation around each project, and I generally have a good understanding of what needs to be done next on each project. I can also see that one of the skills that a student learns whilst doing a thesis is project management and self-control.
However, I feel like I could develop a better system for recording and managing deadlines and deliverables on student projects. Such deliverables include concrete assessments (e.g., assessed literature reviews; the thesis; project proposals) and informal but required steps (e.g., finalising study materials; ethics applications; literature reviews; preliminary training; etc.). Such a system could let me know when a student has not provided an agreed deliverable by a given date. It would probably also have to accommodate some of the more fluid activities that unfold over time (e.g. data collection; data analysis; write-up; etc.).
A few features that would be good:

It shouldn't be too onerous too maintain
It should notify when deadlines are not met
It should highlight current tasks
It should integrate into the supervision process and make it easy to share deadlines with students
It should accommodate different kinds of deliverables (process; outcomes)

Question
What is a good system for helping a supervisor oversee deliverables and deadlines for a large number of research students?

Not sure if recommending software is what you are looking for, but as others have suggested as well, there is Jira, Trello, and (what our team uses) Microsoft Teams (for Teams you create a Planner). Using Teams was a major improvement for us.

You could probably get away with having a template in Google Sheets for students to fill out that could be uploaded to a central database, and then if you have an assistant, get the assistant to compile the notes in a tidy fashion.

When teaching undergraduates, before my retirement, I tracked/supervised student research/capstone projects with two methods.
1) I required the student to prepare an Excel document with their timeline for completion and the milestone dates.  After a joint review (and revision(s)), I then had the document which I kept in a binder (later on a shared server) which I could track completions and keeping of suspense dates.
2) The other method which I usually used for team projects was a written ONE-PAGE weekly activity report.  (And even up to 1 year ago, they were to be submitted in hard copy.)  The report included a summary of work done in the last 7 days, what is planned for the next 7 days, what were the next 2 milestones and their due dates.
Additionally, some of my colleagues were in the last few years using a shared Google gdrive folder for a shared calender for each student and project.  I did not do this because I actually wanted a record of how milestones were revised as the project processed.  (Part of good research is being willing to revise the plan in an appropriate manner, keeping all parties informed, and accomplishing the task at hand in the time required)

As an aside - It might be helpful to know that Google docs has a 'history', so you can go back in time and view the documents at a previous time. I'm not sure about the calendar though.

I'm using google docs that each student creates and shares with me. I find that a very useful feature since I can review these documents whenever I want (and provide feedback in them, as appropriate). But it doesn't track deliverables.

In my department we use Trello and Kanban
We have two boards:

All Students board, their advisers and how far along they are in their thesis writing process. This is mainly used by the program director/dean.

Individual  student one Board that shows how they are doing in each part of their thesis.

It includes Articles Read, Summary of those articles, etc.
The different Label Colors represent different kind of activities: Reading, Executing, and Writting.
There is a review Column. When something arrives to that column I get notified and start reviewing that activity.

Finally with Burndown for Trello we control time and schedule, so that we know if they will finish on time.

In fig. 4 yellow lines represents ideally what the student should have left every week, blue line represents what was actually left ( you can obsevre he was a little behind schedule in the middle)
And red line shows the accumulated effort.

You might ask your university if they can hook you up with some project management software. They probably have licenses sitting around. In the past I've used JIRA with a SCRUM add-on to track things like this, but there's a learning curve and it might be overkill for you. (However, it is quite reasonably priced.) There are LOTS of project management suites out there, some free and some commercial.
Get something that can draw Gantt charts. They're perfect for tracking progress vs. milestones. That makes it easier to see what's going on at a glance.

I've started using OmniFocus task management software for the Mac. It is very useful for supervising research students. I imagine other flexible task management software could also do the job (see here for list of alternatives), but OmniFocus has a number of helpful features (see screenshot at bottom of post). The following describes the workflow.
Actions: Actions are the unit in the task manager. Actions can be given a context, due date, and details.
One context per student: I have contexts for different categories of supervision (i.e., masters, fourth year, PhD). And within these contexts, I have a context for each student. OmniFocus makes it very easy to add actions to a context (e.g., keyboard shortcuts, auto-completion, automatically assign context when you are viewing within a context) and view the actions assigned to a specific context.
Monitoring completion: The interface (see below)  has a colour coding system to easily flag actions that are approaching a due date (yellow) or are over due (red). There are numbers next to each context, so it is easy to see at a glance which students have an approaching or over due action.
Distinguish who needs to do action (student, supervisor, both): If I need to distinguish tasks based on whether it is something the student needs to do or whether it's something I need to do, I put the name in parentheses.
Typical actions that a student might need to do include sending me a draft of a literature review, thesis section, ethics application, confirmation document, presentation, experimental method protocol, funding application, etc. Such actions will include a mixture of interim tasks as well as submission dates for formal assessment. Typical actions that I might need to do include submitting paper work, reviewing drafts, submitting various forms (ethics, funding), finalising programming of tasks, etc.
Notes: I use action notes to record reasons why the action can not be completed. For example, we might be waiting on receiving a signature. It can also be used to store essential details, but mostly I avoid storing details about the task OmniFocus.
Setting deliverables with students: In supervision meetings, I record tangible due dates, and we agree on other deliverables with due dates. Thus, the student is clear on what needs to be done next and by when. In some cases, due dates need to be extended (especially more flexible due dates). Thus, this system encourages the setting of a new deadline rather than leaving things more open ended.
General discussion of benefits: There are several benefits of the above system

Adding actions is efficient
It is easy to see what tasks are due and when for a given student. This makes it easy to follow-up.
It also makes it clear what I need to do as a supervisor to ensure the project is not held up by my inaction.
It encourages the setting SMART goals for students (specific, measurable, assignable, realistic, time-related), which is particularly important for something as potentially flexible and open-ended as a student thesis.

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text:
arXiv is running out of IDs -- is their solution known?
I just noticed that arXiv.org is basically running out of monthly IDs, as can be seen in this graph (source [13-12-09]):

They have gone over 8000 monthly submissions 3 times in last 1.5 years. With the steady increase in the number of submissions, it can be expected that it gets over 10000 in cca 2 years. However, the current ID format is restricted to 4 digits, i.e., 10000 submissions.
I haven't found any information regarding this on the webpage. So: How will the submission IDs look like if they don't fit into the scheme? It interests me because in some helper applications, I tend to rely on the yyyy.xxxx format of the IDs.

Could please the two down-voters explain me what is wrong with the question? Thanks.

Interesting question. I see Prof. G around sometimes in the department. I will bring it up next time I have a chance to talk to him.

@tohecz the downvotes don't matter. You've got your answer. Voting is primarily to promote or demote a question on the board, not primarily to raise or lower your cred.

@JonathanLandrum I have 25k rep, so I know what voting is for. However, if someone downvotes a post, they should have a good reason for that. I just want to know that reason ;)

The format presumed in the question is incorrect. The format is YYMM.NNNN, rather than YYYY.NNNN. Shortening the year to YY and including the month as MM gives a factor of 12 increase in the number of available IDs. Version numbers are appended to the ID, as v1, v2, and so on. That said, it is still a problem, but arxiv have thought about it.

NNNN is a zero-padded sequence number starting at 0001 and permitting up to 9999 submissions per month. If current growth rates
  continue, we expect to change the sequence number to 5-digits NNNNN in
  10 to 15 years. We will do this in a uniform fashion so that, likely
  starting on some year boundary, all subsequent identifiers are
  zero-padded to 5-digits. We cannot currently anticipate extension
  beyond that although extension to 6-digits would be possible.

This was posted in 2007 so we are 6 or so years into their 10-15 year window. Submissions of multiple versions might grant some extra headroom, however it does appear that we could run into problems in about two years. It looks like they underestimated their growth a little bit!

Status change in 2015. arXiv.org switched to 5-digit IDs in January 2015. The format is now YYMM.NNNNN or YYMM.NNNNNvV.

Thanks. Two comments: (1) I'm aware of vV and yes, I wrote yyyy instead of yymm, my fault. (2) The numbers over 8k are new sumbissions: the largest numbers for the last 2 months are 1310.8658 and 1311.7692, so the original prediction of 10-to-15 years seems to be too long.

@tohecz I am a little surprised they didn't future proof it at the "beginning". It seems like they were being pessimistic about their potential success since it doesn't look like the growth rate has changed that much since 2007.

Well, I think they didn't expect people to use arXiv as a repository for every publication, not mentioning having solely-arXiv-based e-journals, and not mentioning people publishing very short notes on arXiv so that others can cite them. However, in all honesty, +(put a large number here) for the changing attitude towards open-access!

another comment: they could use hex numbers, it's pretty standard and 4 digits (64k) would be enough for a very long while...

they could use hex numbers — Oh god, please no.  ArXiv IDs are meant to be read by human beings.

@JeffE: But it's not clear to me that the numerical value of an arXiv ID is of any real significance to humans.  Is 1312.1976 really more meaningful to you than 1312.07b8?  Does the fact that the ID is 1976 and not, say, 1796, have any real significance?

Moreover, if your first NNNNN is a zero, you can delete the zero and the link works, per usual.


text:
Why would academics spend funds on an apparently unnecessary publishing fee?
I recently worked on a paper with some colleagues as second author, and suggested that we publish  in an open-access journal with a decent impact factor. Our university also has an agreement with this journal so we would have been able to publish there for free. However, I was turned down in favour of another journal that my colleague suggested, which had a similar impact factor but wasn't free. The reason given was that 'we have some funds left over, so we may as well use them'. As I'm still a student I didn't have much say in the matter, but it seemed quite wasteful to me.
What are the reasons for academics choosing to 'waste' grant money (if this is indeed wasteful)? Is it to save their own university money, or to artificially inflate their expenses so they can apply for more money the next time they apply for grants? Or something else?

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Apologies if this answer sounds trivial but it might be helpful for a student.
It often depends on the funding conditions.
In some of my grants, I allocate some money for publishing. This 'looks good' when the grant is evaluated by external reviewers because it suggests detailed planning ahead with the available funding.
Money that is allocated for publishing can't be used otherwise without a big hassle. (The funding agency can request a detailed report of the used funds which basically forces me to use it the right way.) I often don't mind paying the publishing fees with this dedicated money since I can't pay anything else with it.
Could this money be used in a better way? Yes, definitely.
Would I risk submitting a grant without dedicating money for publications? Probably not since reviewers might criticise missing publication funds as happened to me in the past.

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What happens to unused money, especially money designated for a specific purpose, depends a lot on the source of the grant, the country, the university, and even the department. Sometimes, researchers can use it for other things. Sometimes, the university gets to take it. Sometimes, it has to be returned. Sometimes, it's something else even more complicated. And, as indicated in a comment by MisterMiyagi, unspent funds can have other effects.
That said, it could just be a strategic decision. It's possible that the open-access journal rejects the paper. It may take a long time to get that result, and by then, perhaps access to the grant funds for publishing will have expired. So, in that sense, it could be safer to go for the paid journal first and leave the free one as a backup.
Another possibility is that the agreement with the open-access journal has limitations. Maybe there is a limit to the number of articles accepted from the university, or maybe there is a per-individual limit. In either case, going for the paid option now with the grant money may leave the free option for a future paper where that type of funding isn't available.

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It's been mentioned in the comments, but not in an answer yet: impact factor is a terrible measure of both how good a journal is, and what it's reputation is. And also things like how fast the turn around is, how many editing services are supplied, what the space or figure limits are.
People in a field will have their own internal, subjective ranking of journals based on things like where the things they reading are published, the way people talk about a journal at conferences, the journals that they and their colleagues have table of contents alerts for etc. These rankings probably roughly correlate with impact factor,  but won't be exactly the same.

Here's one aspect that hasn't been mentioned yet if I'm not mistaken. My university has agreements with some publishers to cover Open Access fees, however these agreements have limits, and money regularly runs out before the end of the year. If there is grant money available for publishing elsewhere, this will indeed allow somebody else from the university to publish one more paper under the agreement. The university also says, for this reason, that if grant money for publication is available, use it!
Furthermore, the publishers with whom there are agreements are big players such as Springer, Elsevier, Wiley, all of whom can be criticised for making lots of money from researchers working for them for free, or even paying them for publishing the researchers' own work. A non-profit like PLoS is not covered, and some people may take the ethical stance that if possible it's better to pay PLoS (or similar) than the ones named previously.

To add a perspective I haven't yet seen in the other answers: I do intend this respectfully, but you say it yourself, "I am just a student." I have definitely provided simplified answers to students over questions that I didn't feel like they'd have the context (or need, at the time) to understand the full answer. Importantly, the rationale for this choice may have a lot of different interdependent reasons, like the professors' opinions of or experiences with the other journal, or maybe even some (light) internalized biases against OA (I wouldn't assume so, but it's possible). Familiarity matters. And of course, the myriad grant-related issues mentioned here already. I can relate to having a similar complicated opinion on some choice and opting for a simpler explanation when asked by a student.
I can't know your relationship with those involved, but I imagine if you asked at the right time, politely, for more information out of genuine interest (and definitely not in a confrontational manner), it's possible you might learn more. It is a good thing to learn.

although not a direct answer to the question, this answer holds valuable advice +1

As the other answers pointed out, funding for publishing is sometimes not an issue. Having the same impact factor, other aspects remain:

Where does the topic of the article fit better?
Is the journal read and cited in your community?
Do you know the editor?
Where is the expected acceptance for this paper higher?
How long will the review process take until the paper is finished?

As a student, you might not know these factors or have missed them in the discussion.

In a majority of cases such as this, I am willing to bet this is "use it or lose it" money that has to be spent by/before a specifically-set date. As an academic, I have seen - and experienced - this numerous occasions myself. There are often other bounds/terms that limit how the money must be spent as well (in addition to strict timelines). I am certain this is why they chose the route they did; how would you have known what other routes/options were available?

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text:
What is the "power" a PhD advisor has over their advisees?
I'm an undergraduate Physics and Mathematics student, who is planning to do a PhD. I have seen many PhD students on this website who are struggling to solve problems about their advisor in authorship, advising, relationship or in unethical manners, etc. and also many answers which are strongly suggesting that they shouldn't prolong the problem if it is possible and try to graduate once like they have the power to destroy the students all career, at least it was what I've perceived.
So, I am asking what is the power an advisor has legally or illegally over their own advisees?
Note: I couldn't find more appropriate word instead of power :).When I said power, I generally implied the rights the advisor have which can affect the student's PhD negatively.

I think those problems are relatively rare. There is a strong selection bias because a PhD student with a healthy relationship with their advisor and some other problem does not ask a question here - they discuss the problem with their advisor.

@Leth advisor basically has a huge impact. https://www.quora.com/What-happens-if-you-get-a-PhD-from-a-low-ranking-school/answer/Karl-Merkley?srid=3UuV&share=0797e36e     My former HOD used to tell this story. Regardless of the rank of the uni, supervisor does matter alot when it comes to defensing your PhD.

Most PhD advisors are really good caring teachers and mentors, who want their students to do well and prosper. I suspect that on this site you see a disproportionate number of postings about power problems. You probably don't have to worry. Do try to ask current and former students of prospective advisors where you are applying to graduate school.

Your advisor can totally destroy your career, and there's not much you can do about it. It's also essentially random, with a low but nonzero probability.

@PatriciaShanahan: There's an assumption in your statement that advisors are reasonable people and that discussing problems with solve them without restoring to this site. Some problems are advisors' faults, and some are unsolvable.

@anomaly I am just pointing out that the distribution of questions here is strongly biassed in the direction of problems in which the advisor is part of the problem, rather part of the solution.

@anomaly http://en.wikipedia.org/wiki/Selection_bias

@Kimball: Sure. My objection was to the idea that a healthy relationship with one's advisor would necessarily solve the problem, or at least obviate the need to post any problems here. One can have, for example, a perfectly healthy relationship with a useless advisor.

In many programs, the advisor signs off on the PhD student's thesis. If the advisor doesn't approve the thesis, it is difficult to impossible for the student to graduate and earn the PhD.
In many programs, the advisor is responsible for securing funding for their PhD students. If the advisor withdraws funding that the student was expecting, the student might not have another source of financial support.
Advisors are responsible for training and mentoring their PhD students, which is a major part of the PhD. If an advisor withholds that training, their PhD student might not become a successful researcher without it.
In general, advisors interact closely with their PhD students. If these interactions are unpleasant or abusive, the workplace becomes very, very uncomfortable.
Faculty tend to have a lot more influence in an academic department than their PhD students do. An advisor can potentially make things difficult for their PhD student with other faculty in the department.
In many cases, on applying for jobs after a PhD, a student is expected to have a recommendation from their PhD advisor. Without it, it can be much more difficult to find a job. Also see: How to handle not having my PhD advisor as a reference? and What to do when a thesis adviser refuses to recommend me?

While the first points probably have a general validity, the last one might be typical only for the US. Luckily I've never had to write a rec letter for my PhD students and, afaik, nor have had my friends around Europe.

@MassimoOrtolano That being said, times are (unfortunately) changing. For literally every entry-level faculty job I applied to in Europe in the last 2 years I was asked to provide references - and this is a problem, because as you say neither my advisor nor other senior faculty I am in good contact with are particularly aware of the intricacies of this process.

@MassimoOrtolano, that is not my experience in Europe. Formal letters of recommendation may not be required when making an application, but the names and contacts of 2/3 referees is commonly (dare I say always) requested. My PhD supervisor was contacted via phone a few times to provide feedback on me when I was applying for a Posdoc. And just to be clear, he has also written letter of recommendation for me (UK), and in both Germany and Portugal that is also common. Those are are also part of Fellowship applications (Life Sciences).

@xLeitix If I understand it correctly (correct me if I'm wrong), in the US letter of recommendations are expected also when applying for jobs outside academia. In my experience this is really uncommon in Europe.

@MassimoOrtolano Not sure, but I would guess what ff524 means are also jobs inside academia. In the US, "seeking jobs" for PhD students almost always seems to mean faculty or postdoc jobs :D

To expand on oint 5: if you have a great relationship with your supervisor but they've annoyed half the dpeartment, things will be harder for you.  This combination is rare though.

Point 7: Advisor can abuse any of the above points purely for their own benefit.

@MassimoOrtolano: In my experience in the U.S., letters of recommendation are actually very rare outside of academia.

So, I am asking what is the power an advisor has legally or illegally over their own advisees?

ff524's answer provides a lot of the positive impact an advisor has. I will elaborate a bit more on the... darker side of the advisor power relationship.
Because unfortunately, the most common situation for recognizing this imbalance is when a student has problems.
First, and most importantly, is the following: your advisor is your boss and ultimately who determines if you graduate (in concert with others, but normally your advisor has the significant impact). This is unique in the graduate world compared to normal jobs because oftentimes problems with your boss/advisor that in the working world would result in quitting and moving on cannot happen the same. A PhD student that is 2-3 years into their program is much prone to suffer through problems with an advisor than a person in a more normal workplace, because if they quit they generally will lose a fair bit of the last years. Whereas in the working world, if your boss is making life miserable it often is possible to go to a different company. You likely will even benefit career wise from this! But it's quite difficult to take 2-4 years worth of graduate work with 1 advisor and get another advisor to work with. This factor gets worse the further you are in your graduate study.
What this translates to is that as the PhD student gets further into their studies, the less they can "walk" and keep their academic efforts during their graduate work meaningful.
This doesn't generally cause problems because in theory, advisor and student work together well. But when it does, it makes PhD students feel completely powerless.
It really isn't that advisors have so much power, per se, but they effectively are a single-person gatekeeper to a person completing a multi-year project. Unfortunately, normally by the time you find out you have advisor problems you are often far enough along that you feel the need to finish anyways. And just slog through it.
Keep in mind your goals and your advisors goals may be different. For example, your goal of graduation may be counter your advisor's goal of finishing different research projects, publishing more papers, etc.
A few examples I know of firsthand from my graduate work and interactions with other graduate students:

Your advisor is unresponsive/slow to get back to you. Your timeline matters more to you than to your advisor, generally. In cases where you need timely responses from your advisor (whether for research guidance, paper review, dissertation approval, whatever) you may be delayed for weeks or even months.
Your advisor isn't engaged in your research. When you are first starting graduate work, having some direction and mentorship is fairly important. If you don't get this, you may flounder for months or years. When you recognize this, you likely are unable to get time with your advisor and be far enough in that you feel trapped.
Expectations to spend too much time doing non-graduation relevant work. The reality is most graduate students spend some time on non-graduation specific work - whether teaching, working on research for grants tangentially (or unrelated) related to dissertation work, etc. Good advisors help keep your time spent on things relevant to your graduation. But if you are in your 4th year and your advisor "needs" you to spend 40 hours a week teaching a class...
Unwilling to "approve" final defense without . Normally you need your advisor's buy-in or approval in order to make your final dissertation defense. An advisor expecting more work continually or otherwise not ever being satisfied can make this process hellish, particularly if it's combined with other factors here.

These are just a few potential problems that I have seen firsthand in different advisor/student relationships. I and others could list many more. Keep in mind that you are far more likely to hear of graduate school horror stories than "I had a totally normal PhD experience, my advisor was exactly what I needed, nothing more, nothing less" stories.
Notice that most of these are not really actionable short of working with your advisor, either. There is an entirely different set of issues that you can pursue more formal action against, but these are all "entirely permissible" problems that are nearly impossible to resolve should your advisor not desire that.
The non-actionableness makes it a double feeling of powerlessness. Not only can the student not really quit without sacrificing potentially years of work but there is nothing they can really do about it by staying, either. Combine this with entirely normal feelings of despair, meaninglessness, and futility that are present as part of graduate work?  (I'm kidding about that. But only sort of,)
The key is to understand all the issues through the advisor/advisee relationship. When you do this, it becomes easy to see how a PhD student (and masters students, though to a lesser degree) can feel completely powerless.

I am quite surprised how accurate the points made here are. I am in my last year in PhD. I am required to submit my dissertation the following month. I have finished writting in May (with almost no supervision by the way), still haven't got response for any of my chapters. It really feels like you are in the cockpit of a B-52 falling in flames. But I think I'll manage it.


text:
Suggestions on how to find a valid thesis topic
I am in my third year of PhD in Finance program, and I still haven't found a topic yet. I almost got burned out searching for topics. Stuff that I can think of are either trivial or have been done by the others before. Recently, I start feeling overwhelmed and self-doubting.
Coming from an eingeering background, I used to solve problems, but not really good at asking problems. I am in need of some plan to overcome this, or else I will probably quit the problem for good.

Did you talk to your advisor about it? If so, what did he/she suggest?

Vote to close as "unclear what you're asking" because I don't see a question here.

Coming up with a proper, well-formed, sane, attackable research problem is challenging and part of the job of a researcher. It isn't always easy.
Elements of a plan for you:
Talk to your advisor/supervisor
As others have mentioned as comments, you haven't indicated what your advisor has said to you or what guidance he or she has offered in finding a topic. What has he or she said/done/advised?
Talk to your final class teachers
Presumably over the previous three years you have been taking classes in your subject field. If this is true, and since your institution is a PhD-granting one, the teaching at this level should be research-informed. This means that the people teaching the subject material at graduate level should know what the limits of knowledge are in the field, and where there may be interesting questions to ask. Note --- they may not know what the questions are themselves (that's part of your job) but they should have some ideas where interesting work might be done.
Talk to your peer group
Who is in the same or similar field as you and doing research? Bounce ideas off them.
Get to a conference/workshop/summer school
If there's little to be gained in asking people around you (which is unlikely), see what summer schools are offered in your subject area and proceed as above: ask lecturers there what are the interesting areas in which to work. Ditto conferences --- whose work is interesting to you? Go talk to them. Find where your interests or skill sets overlap with what they consider areas of interesting opportunity.

Read more articles! You must gather a critical mass of information.
You select some relevant topic to your field, then collect and critically analyze related background information. In other words, read tons of articles. Don't force an idea, instead you will eventually reach a critical mass of information. Things will fit together and it will look shimmery in your mind's eye. All of a sudden the critical mass becomes your idea.
The beautiful thing about this approach is that depends on the work of those around us/in our field. As well it should! Speaking for myself, before I learned this technique, I was quite arrogant to think I could just come up with a brilliant and fresh idea on my own. We're in graduate programs for a reason!
You got this! Discovery is hard because what you're looking for doesn't exist yet, self doubt is the totally appropriate reaction to that. ... go read a bunch of papers and good luck!


text:
How to calculate Hm-Index?
Michael Schreiber proposed the Hm-Index.
It is related to the h-index but it adjusts for the number of authors on a paper.
So, for instance, if you had two people with a h-index of 10, but one had all sole-author papers and the other had multi-author papers, the one with the sole-author papers would have a higher hm-index.
However, I can't find a concise statement of the formula on the internet.
While a close reading of the paper provides the answer,  I think there should be a concise statement of the method quickly available on the interent.
Thus, how do you calculate the hm-index?
Schreiber, M. (2008). A modification of the h-index: The hm-index accounts for multi-authored manuscripts. Journal of Informetrics, 2(3), 211-216.

This appears to be the algorithm:

Order publications by decreasing number of citations
Assign a weight to each publication as the inverse of the number of authors (e.g., 1 author paper = 1; 2 author paper = 0.5; 3 author paper = 0.33, etc.)
Take the cumulative sum of weights while this cumulative sum remains less than or equal to the number of citations for a given paper. This is the hm-index.

So, in R code, it might look like this:
hmindex <- function(citations, authors) {
    dat <- data.frame(citations = citations, authors = authors)
    dat <- dat[order(dat$citations, decreasing = TRUE), ]
    dat$weights <- 1/dat$authors
    dat$cweights <- cumsum(dat$weights)
    list(
        citetab = dat,
        hmindex =  dat[sum(dat$cweights <= dat$citations), "cweights"])
}

And here's an example using the data from the paper of an academic with 8 papers each with a certain number of citations and a certain number of authors.
citetab <- data.frame(
    citations = c(16,15,14,12, 10, 3,3,2),
    authors = c(2,2,3,3,2,2,3,1))

hmindex(citetab$citations, citetab$authors)

It produces the following output:
> hmindex(citetab$citations, citetab$authors)
$citetab
  citations authors   weights cweights
1        16       2 0.5000000 0.500000
2        15       2 0.5000000 1.000000
3        14       3 0.3333333 1.333333
4        12       3 0.3333333 1.666667
5        10       2 0.5000000 2.166667
6         3       2 0.5000000 2.666667
7         3       3 0.3333333 3.000000
8         2       1 1.0000000 4.000000

$hmindex
[1] 3

I.e., the researcher's h-index is 5 (because they have 5 papers with at least 5 citations. But their hm-index is 3 (i.e., largest cumulative weight that is greater than or equal to paper citation count).
Some comments:

So it does not distinguish between different author positions (i.e., 1st or last author are weighted more in some metrics).
If a researcher only publishes sole author papers, h-index equals hm-index. In all other cases hm-index will be less than h-index.


text:
Funding of research by commercial companies, what is the sentiment in the USA?
I attended graduate school in Switzerland, where for engineering, it is not uncommon to have research projects that are funded, in part, by commercial companies. I'm not talking about consulting, but scientific research projects, more on the translational side, for which there is full academic freedom and that have scientific publications as primary output. I also received a conference travel grant from a company during my PhD (although my paper was critical of the performance of one of that company's products).
I am now a post-doc fellow in a reputable american* university and realized my mentioning of funding from companies stirs unease and awkwardness among my colleagues (I should mention that my field is somewhat related to medicine).
How would private funding look like on my CV when applying to an american academic position? Is it considered more prestigious to have received government/foundation funding? I'm looking for answers that are general or specific to health-related research.
*I use this term to describe the USA.

Speaking from epidemiology as a field, with some dabbling in clinical and translational research:
Commercially funded research should absolutely show up on your CV (it does on mine), and it probably won't hurt you, especially in the early stages of your career. There is however definitely more prestige behind having NIH/NSF etc. funding, or foundation funding - several departments I've talked to have all said they prefer to see that. NIH funding especially is something of the "brass ring". Commercial funding isn't bad per se, but a notably dependence on it might have people wondering what is it about your work that isn't passing muster in the traditionally peer-reviewed federal funding system.
There's also some uncomfortableness around conflict of interest - industry-funded science doesn't have the best track record in terms of creating unbiased medical research, but they're also the only people who fund some research, so it will depend very heavily on what specific area you're in. I've worked in some areas where it gives people an uncomfortableness, and in others where nearly everyone has industry funding of some sort.


text:
How should academics handle communication with the media?
I'm not famous enough of a scientist to be frequently solicited by the media* (plus my field has little political/social controversy around it), but I had a few encounters with local newspapers and one with a public national television. The results were not entirely bad, but the general sentiment given was significantly different than what I would have wanted it to be.
It seems like I'm not alone, I just got back from a conference in my field where more senior scientists discussed their relationship with the general media. It came out that more often than they would like, the relationship was bad.
Problems stated, among others†:

Misquotation, or words taken out of their context significantly changing their meaning (this is the most frequent).
A general difficulty for the media to understand, and convey, uncertainty ('we think, it might be so..' or 'we are rather confident that ...' becomes 'it is so')
Difficulty to apprehend results, applications, consequences that may or may not appear 10-20 years down the line.
Exaggeration of the conclusions

etc.
These are not without consequences, at the personal level, as it can give the impression that you don't know what you are talking about.
My first thought was to ignore the media attention and advocate that scientists should do the communication themselves to bypass the regular media (having a blog, entertaining a profile on social media, etc.), but it is extremely time consuming and would distract from the actual research work. I think there must be something to do, on our side, to help with that.
I understand that it is due to how media works, and I don't believe it will change by a lot. But the question is then: are there any strategies that would help reducing this effect, at least to protect oneself against the consequences?
*newspapers, television, magazines, etc. i.e. not scientific journals.
†anyone who has items to add to this list is welcome to do so.

I'm not savvy enough to give a full answer, but the advice I've heard most often is to prepare your own sound bites (i.e., minimal media-style statements), and be rigorous in only authorizing their use if they are not changed (and demand the last word!) If you don't boil it down, they will, and they are certain to get it wrong. For appearance on radio or television, rehearse (a lot), and if it happens often enough, get professional coaching (universities usually offer such things, since it's in their interest that you look good).

One important point to keep in mind is that the reporter talking to you likely knows nothing about your field. You need to explain it like they're five.

@Nit well, sometimes the issue seems to be that they know just enough to be annoying, and sometimes harmful.

Some universities offer training and advice to staff who might need to talk to the media.

Have the guys from phdcomics.com illustrate your 2min description and give that to the media.

@Raphael I'd put my money on the xkcd fellow.

@rubenvb With the small difference that phdcomics.com actually had that offer. They illustrated several 2min versions of theses.

@Raphael oh cool, didn't know about those. I'm sure Mr. Munroe could be coaxed to do something similar (albeit not a video).

I've had one paper I wrote garner significant media attention, so while I'm not a practiced hand at it, some things I learned along the way:

Be able to convey the idea behind your paper simply. A brief, non-technically "What happened", and why this matters. Don't oversell, but if you provide good information, you have some more control over how it gets conveyed, instead of forcing a non-expert journalist to translate your work into words.
Keep it short. It's harder to misquote or provide out-of-context soundbites if you keep things short and to the point. Don't pontificate.
Make the caveats of your work clear, but don't over-hedge.
If it's clear they're trying to get you to say something in particular, decide if you're okay with saying it. If you are, just do it. If you aren't don't go anywhere near it. Don't dance around, or try to add qualifiers - just don't approach.
Be prepared for rage-inducing discussion of your work online after it hits the air. Learn to have a thick skin, or purposefully ignore it.
Remember that, in the grand scheme of things, even a fair amount of media attention is a flash in the pan, and the odd story that makes you wince is just that - a single story.

While I think you can help mitigate some of the problems around media coverage of your work with an active social media presence and a blog, it's only by engaging the audience. It's not going to let you "stand aside" from the media - no website or news paper is going to go "Oh, Dr. X has a blog. On second thought, lets not bother with the story..." If anything, an active social media presence will probably raise your profile among science communication types, and increase the odds of getting a bit of media attention.

I'm more concerned about a hiring committee member saying "Dr. X, wait isn't it the one who said pigeons will cure cancer on the evening news? Do we really want our institution being associated with that?'

@Jigg See the 1st, 2nd and 4th points.

I should have mentioned that I found your answer helpful and up-voted it already. My comment was only about the blog part, I was thinking of it as a bypass to reach the public directly, than a way to fend off questions altogether.

Hiring committees are smarter than that.  (Or if they're not, you don't want to be part of that department.)

@JeffE Hiring comities are human beings, and if they got a wrong impression, they will be affected by it, regardless of how smart they might be.

(At the request of the OP, I'm expanding my brief comment into an answer.)
The advice I've heard most often is

Prepare your own sound bites (i.e., minimal media-style statements). If you don't boil it down, they will, and they are certain to get it wrong. If they already made cuts you don't agree with, don't hesitate to send them a counter-proposal: something similarly short but more correct. (Reputable journalists usually are more concerned with meeting word-count restrictions than with increasing sensationalism.)
Be rigorous in demanding the last word on any change and in exercising that right. If they don't grant you that, do not agree to speak to them (it's a sign they are not up to professional standards). This especially applies to the uncertainties or caveats you mention; make it clear that they get either a quote with qualifications or no quote at all. Getting wrong exposure is worse than getting no exposure.
Repeating Fomite's excellent point: If you are worried they will distort something, do not mention it at all -- especially if they seem to insist on it.
For appearance on radio or television, rehearse (a lot). (Even for interviews in connection with a written piece, it pays off to spend some time beforehand to formulate and polish the key statements you want to make.)
If live appearances happen often enough, get professional coaching (universities usually offer such things, since it's in their own interest that you look good). They are probably also happy to look at any written communication you want to send to the media and to point out possible pitfalls or help boiling it down to make it media-ready.

Excellent, I think it's useful to document these tips for the community. It should be added that sometimes reporter grants you the 'last word' right although they don't have the authority to give it to you, the article gets edited further down the line and there's nothing you can do about it, so watch out!

Number 2 is not realistic at all. With something like 60 minutes, BBC Horizons, or whatever, you will have zero say over final cut. So I recommend you do not follow number 2 slavishly. It is not how things work with large professional media outlets. You will come off as an amateur.


text:
A comprehensive question about personal statement
I have some questions regarding my personal statement for graduate school (US/Canadian universities) in math. My question(s) are comprehensive and long, as the title suggests, thus I have numbered and sub-numbered the questions.
Note that these questions are targeted at schools that do not allow me to upload a CV otherwise I think half of these questions would go away.

Courses

1a) Is it silly or a waste of space to talk about your math background? Or should I assume the graduate committee already has this?

1b) Some schools I have checked out actually asked me to list out all my junior/senior courses along with their books, I guess for those schools I don’t need to? What about those who do not?

1c) Should I write or mention courses I have self-studied? Or is this completely irrelevant to them?

1d) Should I also bother explaining one W and one ‘bad’ mark that happened in the summer?

1e) Should I mention my math department is understaffed and I tried to take as many “hard” classes as possible? How understaffed? We have only at most four math classes at the senior level every year. We are so small that most junior/senior classes stop only at the introductory level.
For example, we only have: introductory PDE, introductory Number Theory, introductory Algebra, and Topology does not even exist at my university.
Very rarely do we get continuations to those courses. In comparison with all the other areas, we have quite a lot of Analysis courses, but all of them are focused in Optimization (excluding Real Analysis, we usually have one to two Analysis classes).
We have no Calculus of Variation, no Measure Theory, almost nothing.
I had to go out my way to bug a professor to request an extra Analysis course this year to the unit head and even then I am short on Math classes next year.

TA experience

2a) Should I talk about this? How will they even verify me? Because I have done some things that most TA don’t do at my university – writing exam solutions. The prof I TA’d for left everything for me to do, except the teaching and actually writing the midterms/finals. I never had a class with him, so I am not so sure about asking him to write a letter for me.

2b) I also TA’d for another prof at another campus during one summer term (same university, but different Math department), should I mention this?
I can provide a link of my exam solutions through the prof's site. I think he will give me permission, should I include this?

Research Experience
I have very very little experience, so much that I could probably only write one or two short sentences about it. I also have no publication, but I think the prof I worked for can
confirm that I did do research under him.
By the way, the “research experience” I had was a problem the prof had written by hand on a math paper and he asked me to answer the question he posed. It was not an analytic problem, it was coding, graphing, and writing a report.

Area of Interest.

4a) I already know my area of interest, I am wondering if it is a good idea to write why I got interested in the first place or is this completely irrelevant to the graduate committee?
My reasons are rather absurd, I am going into my desired area because of a textbook writer and the textbook I read by him isn’t even the area I was interested in, although the writer did write a book in the subject and I was simply in love with his style of writing.
I later found out the writer’s background and plus some neat stuff I read on the Internet sealed the deal for me. If people think this reason isn’t silly or “cliché” (e.g. “I liked puzzles when I was young”), then please tell me.

4b) Also one major problem is that I can’t talk too deeply about my area of interest. I can mention specific subfields, but that's about it. For instance, if I liked Number Theory, I could mention "Analytic Number Theory" and the "Riemann Zeta" or if I liked Differential Geometry/PDE, I could mention "Geometric Analysis".
So would it be better to omit the details if I can't comment too much on the details of the subject and simply write "Number Theory"?

Thesis Advisor
I can find people and mention their names easily on my personal statement. I am just curious if I should narrow it down to only ONE person? Does it look bad that I am just listing out the people whom I want to work with instead of writing down just one name?

Scholarships/Award
I have never liked the word 'Award', so I am going to use 'Scholarship'. Do I need to mention about a scholarship I got from a professor? Again, how can I be verified for this? I think I could ask the prof who gave it to me (whom I did research for) to mention/confirm this?

Skills
How much will it add to my application if I tell them I can use LaTeX (honor's thesis not required for honors degree at my university. I asked one of my profs why and even he doesn't know.), high proficiency with Mathematica, Maple, MATLAB, etc...? I was going to add Photoshop, but then I realize how pointless and irrelevant that is. I can also use Python, but since I am postponed my 1st year computer science requirements till my last year I do not think they will buy this. Also my school teaches Java.

Thank you very much for reading and taking this time to read this ridiculously long question(s)

I would hesitate to use the word "anti-social" for such behavior. Its quite common for many academics, especially the older generation to not have personal websites or even have too many interaction hours. I bet he will meet you if you ask him to. :)

Some ideas on your statements/questions:
(1a)-(1b)-(1c): It seems to be your undergraduate university is not a very well known one and/or even not considered strong in mathematics. Graduate schools may be wanting to be sure you covered what they consider necessary as undergraduate mathematics. Upon being asked I'd consider sending along a short syllabus of the courses you took. I'm almost sure your university must have these things.
(1d)-(1e) Don't even mess with this unless specifically asked, which I think it's unlikely to happen.
The lack of any topology/measure theory (and perhaps more) courses in your university (or college...?) is a rather serious one, imo, and it may point, again, at some lack of elementary basis most mathematics depts. are supposed to have.
in fact, I think it is likely some universities could require from you to complete several courses before they considere you as an actual candidate for graduate school in mathematics...are you sure that what you studied in that school of yours was "mathematics"? Perhaps it was something like "applied mathematics"?
I don't think serious graduate schools require TA from undergraduates. In fact, mentioning you TA'd some course before being a graduate could be considered as (another) sign of a low mathematics level in your school.
To require research? From an undergraduate? I don't think there's such a university. What could be required, imo, is good skills to "hunt" for books, papers, etc. in a mathematics library and, in our days, perhaps also in the web.
No need to dwell a lot with your area of interest. Perhaps mentioning some of the wide areas (analysis, topology, algebra) could be enough, though imo most decent graduate schools require from graduate students to take two or more rather hefty, year-long course in some of these areas, and only later you begin to drift towards your love...
The same applies, imo, for thesis advisor.
Please do mention any scholarship-award you got that's connected to your studies. This may be rather important.
About skills: I don't think anybody will really care about it. Most probably schools will be more interested in finding out about your seriousness, love for the subject, responsibility, etc.
Good luck!

My math department is renowned for the analysis group, but most of them are busy teaching general requirement classes like calculus/linear algebra. 2. So I shouldn't talk about TA? What about the one I did at another campus? It is bigger and more renowned.

I thought it usually score a lot of points mentioning the people you want to work with.

@sidht, perhaps it does though it could be so after the first year or second one, when you already studied some more advanced material. Anyway, that's how it was in my school.

@DonAntonio, I am having trouble understanding why you think it may be bad to mention about the TA thing

@sidht, because it could be seen as if university uses undergraduate students to do jobs that in other universities only do graduate and even postgraduate students. For example, in my university when you are graduate student you can not be a TA, but rather some that helps with grading exercises, exams and substitutes instructors and, very rarely, lecturers when needed. Only when one is a master student (PhD candidate) one can then be a TA and freely substitute lecturers and, even sometimes, be a lecturer. All this with scholarships, grants and stuff. This is why.

Isn't it also because the university wants to spend less money and thus use undergrad to do their work?

Also, you say mentioning "skills" aren't necessary. Does it 'add' anything to my statement if I do? because I am finding my personal statement somewhat short - only 253 words.

Also do you recommend me to talk about my math background? Or should I hide that until asked? Again, do I assume they know my background?

Well, your mathematical background certainly is relevant for you getting accepted in graduate school: they must know it, either from interviews with you, from your academic record, etc. I can't be completely sure about TA, but it might be something you feel during an interview: if you think it may help then mention it, otherwise don't. I think it's important to realize that graduate students are considered in many universities as worth investing in them for the future. OTOH, there are so few of them in general that, at least in my univ., we were the only ones getting automatic scholarship

About skills: anything related to studying mathematics is worth mentioning, imo.

They do interviews?

I suppose some may, I can't tell for sure.

I haven't come across any grad school would want an interview, maybe in undergrad.

Well, then perhaps easier: they shall base their assesment according to you undergraduate school, your grades, perhaps recommendation letter from professors there, from the Mathematics Dept. Head, etc.

As a general rule, math PhD programs in the US do not interview applicants.

@JeffE, that's what I thought and maybe I didn't make it clear (I will do it now), but I am applying to US/Canada

Responding to questions approximately in order:
It is not a waste of space to talk about your mathematics background. Mere course titles tell almost nothing, so it's good to explain more. Telling the authors of the texts used explain a lot to experienced mathematicians.
Especially if your school has a relatively weak program, and even if not, telling what self-study you've done is very important. It is all the more important as an indicator that you take initiative, are driven by curiosity about mathematics, independent of grades and structured programs.
Explaining briefly that you've had TA experience is a small plus, because almost all grad students in math are supported by TA work, so knowing in advance that you can communicate will ease the minds of admissions committee members.
Despite the contemporary pretense that undergrads "do research" between their junior and senior years, it is very rare that any sort of genuine research occurs. Sometimes, but rarely. After all, if research only takes 8-10 weeks in the summer, with almost no prior background, why does a PhD takes years? :)  (There is a good purpose served by the summer programs, though, of giving undergrads the idea that mathematics is not confined to a classroom and textbooks, as well as creating social connections with other undergrads seriously interested in math. But these situations don't really produce cutting-edge research.)
About "specific interests": of course it is vastly better to have tentative, ill-formed, and inevitably ill-informed, "interests", rather than not. :)  I'd encourage you to tell how these interests arose, giving the admissions committee some insight into your approach to mathematics.
It's good to mention scholarships. People will not be so skeptical that you need to document it.
Computing skills are a positive, and deserve a brief mention. Again, there is little need to offer "proof".
In summary, it is a mistake to think that one's transcript explains what the admissions committee wants to hear or needs to know to make a reasonable decision. An informative personal statement makes a huge difference, especially in communicating your motivations and learning outside classrooms. Also, letters of recommendation from mathematicians well-acquainted with you, from contexts of relatively advanced mathematics (rather than elementary) are very important to give an idea of how well you'd fare with more advanced/sophisticated work. (After all, many people do well-enough in undergrad material, but find that graduate-level mathematics has a slightly different nature... of less interest...)

+1 In addition summer research can be seen not as producing a novel independent result, but as a hands-on training for reading/searching the scientific literature and for an experience writing things up. Those are skills that will be useful for graduate school.

Just to get more opinion, do you find my reasons stated in the question cliche or even ridiculous?

@sidht, these questions are completely reasonable. I have heard them many times, yes, but how could anyone who hasn't been through the system guess how it works? It is hard to guess the working of a machine one has never seen, etc.

@paulgarrett, I just asked to get opinions from possibly former grad committees.


text:
PhD Student reapplying to other PhD program, what to indicate in CV?
My advisor decided to move to Industry and it is likely that he might not come back. I do not have an option of continuing with my current PhD program or finding a co-supervisor as suggested. I am in my second year at the moment, and I think it is best to reapply to other PhD programs.
I was enrolled as a full time PhD student and our department does not offer a Masters+PhD program, so officially I was enrolled just as a 'PhD student' and not as a 'MS/PhD Student'. I might likely be given a Masters, give that I have completed the course requirements.
However, for writing Statements of Purpose and CV for my applications, I am stuck with the following:

How should I describe my 'education' section? I did have a PhD topic assigned with a pending publication on the same. Should my current status be of a 'Masters' or a 'PhD' student?
Does it make sense to explain my situation in my CV or Statement of Purpose to describe what exactly made me reapply to PhD programs?
My advisor is less responsive these days and I am unsure if it is a good idea to give his name as my potential recommender. A fallback option is to ask my course instructors at Graduate school which would probably not guarantee a strong recommendation as compared to recommendations from people I have actually worked with during my undergraduate. If I do not have any recommenders from my current program, will that go against me?

Since every country/state/university has its own regulations on Ph.D. programs, my answer might carry little value to your concrete situation.
I dropped my first Ph.D. program last year due to some financial difficulties. It was the 4th year of my Ph.D. life. I am currently enrolled into another PhD program after a prolonged period of struggling. I think I can totally understand your situation.

Put your current PhD program into your CV, mark yourself as "Ph.D. student" because you are. And this actually helps since you already know (more or less) how academia works and how to proceed with your research. You are not a Masters student, don't put "Master" there.
Like in any CV or application letter, honesty is always appreciated. Explaining your situation would help them to understand you and your goal (which I assume is to continue with your research).
It's really subjective. Recommendation letters don't matter THAT much for Ph.D. students compared to Master or Bachelor students. What you really need is a quality list of publications and/or projects in which you have participated.

I agree with #1 and #2, but think that recommendation letters do matter.

Agreed with @jakebeal. I even think that not only do you need ideally strong letters documenting that you did well in your current program, but that a letter by your current adviser should be your goal. It depends on culture and their personality, but in the countries I studied and lived, almost every adviser would be appreciative of your difficult situation, and help you as their former charge. So be friendly, but insistent.

They do matter, I agree. What I mean in my reply is that the recommendation letters have relatively less value comparing to publications or awards.

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