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Significance of American Mathematical Monthly Problems in Math Grad School Admissions
I have started solving problems from the American Mathematical Monthly. While I will definitely continue this, I am not sure how much this will help for math graduate school admissions (assuming I submit my solutions and they are recognized by the Monthly). How significant would multiple solutions to Monthly problems be in admissions? What about having the published solution to a problem? One issue is that I don't know how difficult the problems are presumed to be: all I know is that I personally have solved at least one of them!

I'm relieved to see that this question is not, in fact, about what to do if your grad school admissions interview and your period coincide.

@Ana Unless this started discussion of modular arithmetic in the interview, I do not see how that would be math specific.

@Ana I couldn't bear it :) - I changed the title.

It probably depends on the committee members, but I wouldn't expect it to help much.
If you get a really clever solution published, or they publish a problem you submit, that could make a difference.  It certainly wouldn't mean as much as a research paper, but it could be viewed as the same sort of thing on a smaller scale.
Otherwise, the potential impact is not large.  Solving Monthly problems would be viewed favorably, as evidence of talent and effort, but it's not likely to mean the difference between admission and rejection.  (Still, it's worth listing on your CV.)

Yes, list on your CV.  Probably it will make no difference, probably it will have no negative impact, and (some small chance) it will have a positive effect.

I agree with the other answer, but just to add another data point:
You might as well list it on your CV, but you shouldn't expect it to help very much.
I did (along with a few others) graduate admissions for the math department at UGA for four years -- and in fact am about to get involved in it again later this week, despite not being on the committee anymore -- and I remember exactly one student who listed it on his CV.  It was sort of interesting but not particularly impressive, and if I remember it right we did not admit him in the end.  He had a rather distinctive name and, while flipping rapidly through the Monthly problems in the months and years since then, I've noticed that he has submitted several more problems as well.  I am starting to wonder what happened to this student...but I wouldn't go so far as to say that I regret the decision we made.
In general I have to say -- and this is a very personal opinion, not a professional one -- that it seems to me that "problems" sections in journals like this are a bit old-fashioned.  They do not seem to play a nontrivial role in contemporary mathematical life.  I remember having exactly two conversations about Monthly problems:
1) As a first-year graduate student, I did solve a Monthly problem.  (This was the one and only Monthly problem that I can remember having thought about for more than five minutes, and I think it is telling that, while I usually have quite a good memory for mathematical minutiae, I remember precisely nothing about the problem.)  Rather I remember standing in a mezzanine outside of the mathematics department and telling a fellow student that I had solved a Monthly problem.  She politely congratulated me.  I asked her whether I should actually submit the solution.  She said that she couldn't  see why not.  I ended up not submitting the solution (thus I can't be completely sure that I correctly solved the problem...and it is telling that I don't care very much!).  Okay, that was not my most riveting anecdote.
2) This is slightly more amusing.  As a postdoc I remember having lunch with one of my close friends.  He told me that he was flipping through the problem section of the Monthly and his eye was caught on a problem that had been proposed...by him.  He racked his brains about this and did not succeed in recalling anything about the problem or his submitting it.  He did have a friend who was involved with editing the problems section at the time, so he guessed that must have had something to do with it (his friend was very conscientious; it is not plausible that he would have done it as a joke or prank).
I'm not saying that most Monthly problems are easy: on the contrary, I am a relatively experienced, relatively successful research mathematician, and I still sometimes at least pass my eyes over these problems while flipping towards the reviews, and I rarely if ever see one that I think "Oh, surely I could solve that very easily."  I'm just not really sure what the point of solving them is: I have plenty of other math problems that I'm trying to solve!  It's a little like math contests, only adults can participate too.
To be honest, I think that MathOverflow has significantly overtaken solving Monthly problems as being a minor way for young people to show their talent.  There are a small number of undergraduates that I would admit in a heartbeat because I have come to see their brilliance on MO (and to a lesser but still probably sufficient extent, on math.SE).  Most of these students are so brilliant that they do not condescend to apply to my graduate program, and I assume that if they did the rest of their application would be so superior that I would not have to spend much time explaining to my colleagues doing the admissions why their performance on math Q&A websites makes me confident that they will be excellent graduate students...but still.
I also think that participation on MO and math.SE is really better than solving problems or doing well in math contests...not better in an absolute sense, but closer to what mathematicians actually do and thus more indicative of academic mathematical career potential (as opposed to raw talent; certain kinds of raw mathematical talent are less useful to a career mathematician than one might think!).  Still not that close, of course: the fact that I have a higher reputation on MO than any of several Fields Medalists and other true luminaries that regularly contribute there is ample evidence of that.

For me, more than showing mathematical talent, it would show an extracurricular interest in math, beyond your course work.  Of course, things like participation on MO or MSE would also do this.  That said, I don't remember ever seeing this on grad school applications in the few times I've been on that committee.


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Origin of the thesis-degree procedure
It just came to my mind, currently if one wants to obtain an
academic degree one must to do a thesis. This is a widely accepted
method to prove the knowledge of certain academic level, sort to say.
But my questions are, where this method was originated? Which historical
or social circumstances originated it? Is there any philosophical background?

This might also be of interest in HSM.

(note: I have no references for the below, nor am I qualified in the topic)
First of all, the premise of your question isn't quite accurate: certainly in the UK it's very common for undergraduate degrees to have no thesis requirement. But putting that aside:
I think there are parallels with other mediaeval professions, which required proof of skill in order to become a member of a guild (the professional organisation). To be a 'master' of the guild one had to produce a 'masterpiece' (the origin of that word); this has obvious parallels with the idea of a thesis proving that an individual should be admitted to a degree (remember that historically a degree is more like a rank than an award, honour or qualification).
The MA at Oxford and Cambridge is still awarded automatically to those with a BA seven years after the start of the degree, which I believe matches the time someone in a professional guild would take to become a master.
Note also that the modern doctorate is a much more recent invention than the MA.

You're right, question was not bounded correctly. In Mexico there's algo degrees without thesis requirement, but at least to obtain a PhD in sciences I think it's a must (I guess this applies also to other branches of knowledge).

Hey, I just got my Oxbridge MA, I worked very hard for it!! :-)

A bit if history. The history of thesis is intertwined with the history of universities in the 12th and 13th century.. The early history of universities is not clear but with time systems develop on how information/knowledge is taught and discussed. The end (so far) result is what we have today. The written thesis is based on the fact that ideas need to be made more permanent than oral traditions. the advent of printing made wider distribution of copies possible. The first degrees were the baccaulerate and magister artium which corresponded to doctor in certain disciplines.
The thesis was originally what the word describes a thought or thinking that needed defending, which goes backs to Aristotle and Plato. As soon as writing was possible, the idea was to put the ideas down in writing and hence a written thesis was born. One has to remember that teaching early on did not necessarily occur as lectures, it could be mentioning and learned discussions. At the same time knowledge was not as structured and defined as now.
early on the teacher actually wrote the thesis and t was the students job to defend it. So the focus was less on developing knowledge but to defend a thesis with arguments and logic. During the renaissance the thesis in a form we can recognise was developed. These texts were called dissertatio (lat. development, presentation) where as the defence was named disputatio (lat. c. learned argument). From these relatively common beginnings different "cultures" developed which now are reflected in differences between countries in how a thesis is defined and defended.
Much more details can probably be added to this but the core is covered. There is no necessary connection between a degree and a thesis. Certainly not at a bachelor's leverl and it is also possible at a master's level. Differences also exist between disciplines.

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In a faculty job search, when and how should I reveal my preferences?
I am currently interviewing for tenure-track faculty positions at a number of top departments in my field.  Despite getting some very positive feedback about my interviews, I have not yet received any offers.  So far I have tried to avoid any "game playing," being very explicit with each department about where and when I am interviewing.  Likewise, in follow-up discussions with hosts, I have been careful not to state any strong preferences for one school or another, mentioning that I still have additional places to visit (seems only fair!).  I am starting to wonder, however, whether this approach was a mistake, especially given that others in my field are already receiving offers.
The question is, how should I proceed from here?  Part of the issue is that I do not fully understand how and when offers are made, which leads to several questions:
Question 1: How often are offers made before the end of the interview period (i.e., before all candidates have been interviewed)?
I know it happens, of course, but how frequently?  (E.g., as a percentage of all offers made by the department over a 10-year period.)  A related question is
Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?
In fact, can expressing this kind of preference actually hurt a candidate's chances?  E.g., perhaps it makes this candidate look like a "sure thing," which frees the department to first make an offer to another, "higher-risk" candidate.  In general, when is a good time to express such a preference?  Finally,
Question 3: To what extent do different departments talk to each-other?
For instance, is there any mechanism in place to prevent candidates from "falling through the cracks?"  E.g., one can easily imagine a situation in which lower-ranked schools don't make a candidate an offer because they expect she will get an offer from a higher-ranked school; subsequently, the higher-ranked schools make her no offer and she is left without a job.  Likewise, if I express a preference for school X before visiting school Y, do I risk pissing off my hosts at Y?
Question 4: Do I just need to relax?
I am almost tempted to write an email CC'ing all the department chairs, providing a complete ordering of my preferences... they can duke it out from there.  (Or simply tell me that none of them want to hire me!)  In general, the whole game-theoretic aspect of this thing makes me a bit queasy.  Wish some brilliant economist would design a mechanism that is fair for both departments and candidates alike.  Right now, it definitely feels like a buyer's market.

These are good questions, but you might get better answers if you post them separately.

To follow up on what Mangara has written: asking just one question at once is how this site works. What if one person writes a great answer to questions 1-2, and terrible answers to 3-4: how should people vote - up or down? Should you accept, or not? What if question 2 is objectively answerable, but question 3 doesn't have a single right answer - should this question be answered, or closed & deleted? As it stands, this 4-question question is too broad.

I think that in this case, the 4 questions are part of a coherent theme, and are fine as a single unit.

You have good answers to most of your questions, however I have one more thing to add: I am almost tempted to write an email CC'ing all the department chairs, providing a complete ordering of my preferences... they can duke it out from there.  Sweet jeebus, don't do this!  Don't even joke about doing this! You'll look like a lunatic.

I've served several years on the faculty recruiting committee for my (US, top 10) computer science department, including three years as the chair.  Protocols vary significantly between different departments, different searches, and especially different fields, so take my experience as a sample, not as a definitive answer.
Faculty hiring is best thought of as a complex multi-player game of three-dimensional chess, using invisible pieces that occasionally explode, where nobody knows who the other players are or what rules they play by, and nobody wants to reveal too much information.

Question 1: How often are offers made before the end of the interview period (i.e., before all candidates have been interviewed)?

It happens, but normally only when one of the early candidates emerges as an overwhelming favorite, and that candidate has another offer with an inflexible (or already extended) deadline.  But nobody wants to be forced into this situation.  It's really bad form to interview someone for a position that doesn't exist.
Some universities allow limited gambling with slots.  A department might offer a position to candidate A, and then later make a second offer to candidate B for the same slot, under the assumption that at least one of them is likely to say no.  If A and B both say yes, then both A and B get jobs.  (I've seen this strategy go very "badly", with four low-probability offers made on the same slot, all of which were accepted.  Gambling was outlawed for the next n years.)

Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?

Especially at universities that (a) forbid gambling and (b) do not let departments roll unused slots from one year to the next, departments do balance the desirability of various candidates against the estimated probability that they will accept an offer, to minimize the risk of not hiring anyone at all.  (This scenario also tends to generate offers with very short and inflexible fuses, sometimes while interviews are still ongoing.)
But just telling us that we are your first choice probably won't help much.  We want to believe you, and we appreciate your effort in making that overture, but we don't really believe you, because lots of candidates have said that and then left us at the altar.  And even if it's true, you really don't want the rumor that that you prefer us to reach someone else.  Best to keep mum until you have actual offers.
On the other hand, evidence that we are your first choice is taken very seriously.   For example, if you receive an offer from somewhere else, especially from another top department, telling us in time to make a good-faith counter-offer is certainly better than not telling us until it's too late.

In fact, can expressing this kind of preference actually hurt a candidate's chances?

No.

Question 3: To what extent do different departments talk to each-other?

Not at all.  Different departments are competitors; sharing information is counterproductive.
We do, however, gather as much back-channel information as we can, for example by scouring our competitors' web pages to see who they are interviewing and when.   Sometimes I do hear rumors of the form "So-and-so is about to get an offer from X", but those rumors almost always trace back to the candidates themselves.

one can easily imagine a situation in which lower-ranked schools don't make a candidate an offer because they expect she will get an offer from a higher-ranked school

Unfortunately, yes, this does happen, although I suspect more often at the interview stage than the offer stage.  See "minimize the risk of not hiring anyone at all".  Nothing you can do about it.  Let it go.

Question 4: Do I just need to relax?

Yes, always.  I recommend building up an immunity to iocaine powder.

Interviewing for a position that doesn't exist (warning: humour).

Question 1: How often are offers made before the end of the interview period (i.e., before all candidates have been interviewed)?

I would say "early offers" only occur in exceptional circumstances. Universities have hiring policies and those policies require dotting i's and crossing t's -- paperwork and process -- particularly for tenured or tenure-track positions.

Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?

Let me put it this way: you do not want to express that the school is not your top choice. The hiring committee are looking for a monogamous relationship. Talking about all the other schools you're going on first dates with isn't a great idea.

In fact, can expressing this kind of preference actually hurt a candidate's chances? E.g., perhaps it makes this candidate look like a "sure thing," which frees the department to first make an offer to another, "higher-risk" candidate. In general, when is a good time to express such a preference?

This makes absolutely no sense.

Question 3: To what extent do different departments talk to each-other?

I guess you refer to the US? If so, I don't know but I would imagine there's very little communication on an inter-department level (though people in different departments may informally communicate).

For instance, is there any mechanism in place to prevent candidates from "falling through the cracks?" E.g., one can easily imagine a situation in which lower-ranked schools don't make a candidate an offer because they expect she will get an offer from a higher-ranked school; subsequently, the higher-ranked schools make her no offer and she is left without a job. Likewise, if I express a preference for school X before visiting school Y, do I risk pissing off my hosts at Y?

This again makes no sense. A university is unlikely to avoid offering you a position because you might be "too good for them" or that you might get other offers (in the worst case, it only costs a university a couple of weeks to make an offer for a position that will last many years).
A university may avoid offering you a position if you seem disinterested or if it seemed likely that you were using this position as a short-term stepping-stone to elsewhere.
Different departments are not going to compare notes. They are competing with each other.

Question 4: Do I just need to relax?

Yep. Maybe ease up on the coffee and take up croquet or smoking or something else instead.

Not sure why there's a downvote. Seems like a reasonable set of answers.

@Suresh: It seems reasonable to me, too.  But I have two guesses why someone may have downvoted: 1) 'A university is unlikely to avoid offering you a position because you might be "too good for them" or that you might get other offers.'  This has come up before, and there apparently are cases where it happens (though I agree with badroit's use of "unlikely" here).  2) The joke about smoking.

@badroit while you are right that there's little formal communication between departments, the informal communications are quite useful and are often used to "glean intent". I will also regularly spy on other departments' colloquium pages to make guesses about who they're interviewing :)

@Suresh "I will also regularly spy on other departments' colloquium" Not only faculty does that - candidates also regularly do that to figure out their competition :)

@Suresh, I'm guessing the downvote refers to advocating smoking. :)

Departments will not pursue a candidate because they think believe the candidate will not accept and I do not think, as @MarkMeckes suggests, that this is unlikely. That said, this question is about the offer going out to candidates who have already interviewed and the "too good" filter is usually applied much earlier. Once a department has a flown a candidate out, they will almost always give their favorite candidate the offer -- even if they think they are less likely to get a yes back.

@BenjaminMakoHill: It appears to me that we agree.  badroit and I only suggested that it is unlikely that a department will decide after an interview that a candidate is "too good for them" and therefore not pursue them.

Congratulations for getting as far as you have!
I think badroit's answer is very reasonable. I had two follow ups and elaborations.

Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?

It seems inappropriate, and slightly weird, to tell any school you are interviewing with where in your ranked list of preferences they currently fall. That's true for your top choice, your final backup, and everybody in between. Even if you are sure of your ranking, your preferences might change as you learn more about the programs and the particular offers.
That said, if you are legitimately excited about the possibility of joining a school's faculty, you should express that interest. If you feel like the faculty at the department would be great potential colleagues, say it! If you think they have great resources, say it! If you love the graduate students or the city, say it!
The comparison to dating with the goal of a monogamous relationship is a good one. Cultivating an air of disinterest seems unlikely to help and it's possible to show legitimate interest without being dishonest or leading people on. Everybody understands that you can be excited about one potential match, also excited about other potential matches, and that eventually you will have to make a decision.

Question 4: Do I just need to relax?

Sounds like it. It also sounds like at this point, you've done most of what you can and the next steps are basically out of your control.

Since you brought up the dating comparison, maybe you should had taken it one step further... Telling the school where they rank is like telling a potential date something along the lines "I will go out with you, but only if four other girls refuse me first"....

@NickS the question was about whether the OP should tell the top choice her/his favorite. Although I mentioned it, I should hope its common sense that one would not tell the later choices about where they sit in the ranking.

Yes, but later in the post he also mentions: "I am almost tempted to write an email CC'ing all the department chairs, providing a complete ordering of my preferences..."

@NickS You're right. I hope that was an exaggeration!

There's a saying in writing: "show, don't tell."  I think it's a bad idea to make any comparative statements between schools (exception: if you have an offer from one school, immediately contact the others to withdraw your application or say you would prefer an offer from them).  It's much better to show how excited you are about a school, by praising them and showing them in the interview that you've done your research.
If the interview's over, then I think it's good to say generic things in your communications with search committees and chairs, like "I'm really excited about the possibility of joining your department," but I wouldn't get more specific than that.  Always be honest, but often it's better to not say too much until things work themselves out.
Incidentally, some brilliant mathematicians (with follow-up by economists) did design such a mechanism that is fair for both departments and candidates alike, and won a Nobel Prize for it (or at least the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, whose status as a true Nobel is somewhat debatable).  If you would like to know why it will never be implemented in this context, read this comment thread.

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Why are reports written in the third person passive?
Generally it is considered to be "good practice" to write reports in the third person passive voice for a wide array of academic writing. It is even a requirement of publication in several journals.
However, I have been unable to find any sort of information for "why" this is the way it is. I can't find any studies on the effect of reports written in the passive vs active tenses nor the effect of 3rd vs 1st person.
Could anyone shed any light on why this is the way it is?

First and second person by definition are individuals 'involved' in the activity whereas the third person is someone who is merely an observer of the said activity.
Since reports are always expected to be objective (impersonal) third person passive tense is the most appropriate.

This doesn't really answer my question I'm afraid. It just leads to the reframed question of "Why are reports expected to be written impersonably?".

@JamesHughes What kind of answer do you expect? Of course, you can always go further down the rabbit hole.

Do you have any citations or references for your answer? Right now, your "answer" dominated by your own opinion.

My “opinion” is formed on the basis of inputs from academics I am working with. There may  study so to speak of effects as stated in question. But then again, this is something widely agreed upon in the academia. I don’t understand what else is required in the answer.

this is something widely agreed upon in the academia — Not in my field it isn't.  Academia varies more than you think it does.


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Research in "Research Engineering"
from Wikipedia:

Software engineering (SE) is the application of a systematic, disciplined,
  quantifiable approach to the development, operation, and maintenance
  of software, and the study of these approaches.

I was wondering if there is something similar for research, something that we could call Research engineering. I imagine it to be a research field on its own, with students "researching on how to do research". I believe software development has benefited a lot from research in SE. Maybe research could also benefit from Research engineering.
The questions are:

is there some institute or some university department in the world where they work on Research Engineering?
in which faculty you would position such department/institute?

Edited: After getting a couple of good answers, I am still not completely satisfied, so I would like to clarify my question. What I am really interested in is indeed a "software engineering" approach. I am not interested in philosophical or sociological research. In fact, the question I had originally in mind was whether it's possible or not to apply actual software development methodologies to research. In more concrete terms, I am wondering  whether anyone has studied the application in research of models similar to the waterfall, or the spiral model, or things like extreme programming, Scrum, etc... (Note: these are just examples, please don't comment to each of them one by one).

Interesting question, and interesting concept.

The name "Research Engineering" biases things a little bit by suggesting an engineering approach.  A more neutral name might be "Research Research", i.e., research about research.  Your question would itself fall under Research Research Research.  Research Research sounds like the academic equivalent of management consulting: outsiders come in with less domain knowledge, but they are supposedly smarter and with broader perspective, so they can offer valuable advice.  I'm skeptical that it would be useful, and I don't know of anyone making progress on this, but I can't rule it out in theory.

@AnonymousMathematician: I was indeed suggesting an engineering approach. "Research Research" sounds too meta. And so does "Research Research Research" :P

Perhaps we need a Department of Departmental Name Engineering.  On a more serious note, see http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2539276/ and http://www.theatlantic.com/magazine/archive/2010/11/lies-damned-lies-and-medical-science/8269/.  They are specific to medical research, but they amount to studying how and why research does or doesn't work.

@AlessandroCosentino An interesting question, but as AM has pointed out, the name (and starting post from describing another discipline) sounds misleading. Could you reformulate it as sth more neutral, e.g. "Research about doing research" + start post with the idea and only then relate it to other field?

Yo dawg I herd you like research...

@PiotrMigdal: I don't want to change the name, because I did mean research Engineering. I guess I should just edit the question and explain better what I mean.

@AlessandroCosentino OK, no I see. You are interested in the micro scale. Some Scientometrics research (eg. Critical mass and the dependency of research quality on group size) are implicitly related, saying that you need a critical number of researchers to make it working smoothly. Other things may be harder to find, as in science it work a lot in apprentice-master mode, with approaches differing from a group to a group.

@PiotrMigdal: I am glad that is clearer now. You can edit this comment to your answer and if nobody else answers, I will accept yours.

@AlessandroCosentino Expanded my answer. Is it the thing you are looking for?

@AlessandroCosentino Just found your question after asking this https://academia.stackexchange.com/questions/191638/equivalent-to-agile-software-development-but-for-research  I'm interested in the same, but more specifically equivalent to agile software engineering/development.  Have you found any interesting resources?

There is plenty of "research on research" (or "science of science").
There are dividid into different fields, e.g.:

Scientometrics - measuring citations, networks of collaborators, relations between topics and other quantities characterizing the scientific output.
Sociology of science - treating science as a activity of groups of people, with its history etc.
For example there is a great book Ludwik Fleck, Genesis and Development of a Scientific Fact.
Research on collective intelligence, innovation (when, where and how does it happen), etc.
General fields related to education, didactics, teamwork and management.

As you asking about engineering (i.e. how things work in practice), I don't even mention things like philosophy of science. Also, as you see, the answer depends on scale - from an individual, through a group or an institution to a country, the world nowadays or our civilization.
Typically it is done under umbrella of complex systems, complexity, network science, econophysics or data-mining and modeling in sociology. There are institutes doing it, see e.g. the front page of the Santa Fe Institute. Also, there are some projects on it, e.g. QLectives.
ADDED:
As you are interested in the optimization (not only the observation) and on the micro scale: some findings may implicitly give hints, e.g.:

R. Kenna, B. Berche, Critical mass and the dependency of research quality on group size (2010) says that you need a critical number of researchers to make it working smoothly,
B. Jamtveita, E. Jettestuena, J. Mathiesena, Scaling properties of European research units (2009) says that the larger an institute, the higher percentage of administrative workers it has.

Other things may be harder to find, as in science it works a lot in apprentice-master mode, with approaches differing from a group to a group. So it may be not as easy to be serialized (as in different fields, countries, etc. one may need to have different approach); and when you don't a large enough sample, you cannot use quantitive methods in a meaningful way.
Moreover, now we are in the phase preceding formalized studies, as only recently people started to share with the world their soft and subjective findings on that matter, e.g.:

Materials for Nurturing Scientists (a collection) on Uri Alon Lab website (BTW: he is the right person to talk about it, as he promotes such exchange of information on research)
G. Whitesides, Whitesides' Group: Writing a Paper (2004)
J. Gallian, Advice on giving a good powerpoint presentation (2006)

and on things like academia.SE, for a bit of self-reference.

Great answer.  In the comments above, I was thinking about research aimed just at improving how research is done, but as you point out, it can be much broader than that.

hi Piotr, thanks for the answer. Interesting, but not quite what I mean. I guess it's my fault, I should have been more detailed in explaining the question. I'll edit it soon.

@AlessandroCosentino Before editing (it is good to clarify a question, but not to change it), what exactly do you have in your mind? If I change 'software' to research in you question, then the answer is on it.

What about research on research on research?

I've never heard of a field dedicated to the study of research methods. There are journals dedicated to advances in methodology (e.g., [1], [2]), but the closest concept I've encountered to a field dedicated to researching research is Thomas Kuhn's classic work The Structure of Scientific Revolutions and other similar philosophical works, which discuss how science, as a field, progresses and evolves.
I would guess that the reason for the lack of such a field is such research is part and parcel of the actual work done in the field. In order to study biochemistry, one must understand how to study biochemistry; in order to study mathematics, one must know the types of questions and the methods used to find answers in mathematics. Each field is unique, and each field will find specific methods that will optimally serve the needs of that specific field. While there may be broadly-applicable research techniques, each field will solve the problem of "how to do research" differently, in the way that best suits that field.

Hi eykanal, thanks for the answer and for the comment. Well, you could say the same in software engineering, you could say that methods applicable to, say, Web programming, are different from methods for desktop applications programming. Or that some patterns can only be used when programming in some languages, rather than others. I still believe that in research there are common patterns applicable among all the fields. If we don't know them yet, it might be just because no much research "on how to do research" has been done yet. What do you think?

@Alessandro - You're correct that there are some "universal truths" in research, so to speak. However, those are fairly well understood, without the need for further research. The details, as I described, are left to the individual research fields.

I would be happy to know those "universal truths" :), or even better, to see them somewhere written down. I must disagree with you, though, I think there is too much improvisation in the field and those few known methodology truths are revealed only at some introductory graduate skill seminars for first year grad students.

Check out virtually any course on this list. Many disciplines have their own "Research Methods" course, and that's where they share both research fundamentals and field-specific techniques.

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How to write abstract for conference when you have no results yet?
This situation is not uncommon; in my case, I have to submit abstract for conference in September by the end of January already. But the problem is I have no results yet. I'm pretty sure that in those 8 months I will get pretty interesting results. But..
How to write smooth abstract without reporting results?
I started something along these lines:

This and this is an important factor ...
However, few studies on this topic have been done ...
In our study, we compare this and this
??

Now the problem comes in point 4, where I should report some results.

How should I go around that?
What formulations should I use?
Shall I speak in present, future, or past tense? The studies are usualy written in past tense like "we analysed, we compared...", but in this case I would tend to present tense.

Thank you for your help. Examples are welcome!
P.S.: this is an interesting discussion however didn't give me actual guidelines of how to write it.

Don't do it. No results means no abstract.

No abstract means missed opportunity; I cannot afford that. I have to present results I'm sure I will have by the time of the conference.

My suggestion is, if you're sure you'll have interesting results, write the reasons why you're sure.

I should point out: if this situation is not uncommon, you should be thinking of January as the deadline and not September. this is very common in CS for example.

I find it fascinating that the "don't do it" and the "I can't afford not to" comments both have many upvotes. This definitely speaks to the pressure to publish at these venues. @DanielE.Shub

heh, I'm in a similar situation --- as a part of interview for a PhD position I am meant to give a talk on a group seminar on what I want to research. Obviously I have no results, only arguments.

@Suresh The situation in CS is different because, although submission deadlines are typically several months before the conference, you have to submit a paper describing your work so the work must be essentially completed at submission time. Here, the question is about merely submitting an abstract for a talk to be given several months in the future.

@Yrogirg No, that's a completely different situation. You're being asked to give a talk about research you plan to do in the future. Tomas is supposed to give a talk about research that he will have done by the time he gives the talk but he has to provide a summary of the talk now, when the work has barely started.

Don't write results you don't have. Neither in the present, past or future tense. Just don't do it. Yet, I agree with you that there are circumstances where you do need to write an abstract on on-going work. For example, many big conferences in my field now ask for abstracts to be submitted up to 10 months in advance of the conference itself! If you are a post-doc staying on a 12-month project, you want to present something but you might not yet know how things will turn out. So, two techniques I propose:

Just write about the methodology, and present your goals in a general way, without “predicting” particular results but insisting on the importance of the topic. That is, emphasize strongly your points #1 and #2, and then describe point #3 as you would your “results”. Things like:

In this particular study, we compare the efficiency of methods A and B on given subsets of a reference database. We use a large number of different criteria for measuring efficiency, including …, … and … We also discuss in detail the implementation of subprocess X in method B, because its has not been specifically optimized in the existing literature.

I know it sounds vague, but that's the best you can achieve honestly, without pretending to know what you expect to find.
Bait and switch: if you have existing results in a closely related study, you can incorporate them as part of your results. Mix this approach with above, so that you have at least a few specific results to list in your point #4. Then, when you will make your presentation, just present your new results alongside the old (some people would remove completely the old results, but that makes it too much of a “bait and switch” for my taste). It is, after all, quite common for people to include newer results in orals/posters that they obtained after the original submission. It is not frowned upon, as long as you keep a decent agreement between the original abstract and the final content.

Thank you. As for point 2. In the link I posted they justify bait-n-switch a lot, arguing that people won't remember. I wouldn't be afraid of that. The problem is that I have only small portion (like 1/8) of final results. I'm afraid that reporting this small subset of results would make it even more apparent that results are missing or cause people to think "..and that's all?"

people won't remember — Careful.  The internet remembers.

@JeffE, I agree with being careful, but the internet won't usually join the conference to see the poster or oral presentation.

@silvado nowadays if its a major conference you will be recorded and it will end up on the web. This has happened to me in the past 4 conferences I have presented at so internet is starting to join all conferences...

If you mean 'write abstract, don't write results', that should have been put that way I think.

Inre: Bait and switch. I've seen more than a few people simply get up and say "Things have moved on since I submitted the abstract for this talk, and what I'm really going to talk about is ". The audience understands the problem with abstract deadlines perfectly well.

This is the most useful answer. My final solution was exactly that: not writing about results, just talking about the hypotheses, why they are so much interesting and how this study helps to finally shed light on them! I registered it as a talk, not poster... let's see!

@Tomas: Did it work out as you said?

The challenge with ever-earlier deadlines for conferences (sometimes six months or more in advance of the actual date!) makes planning for a conference a very difficult prospect.
You're left with only a handful of options, none of them particularly appealing:

Submit an abstract on incomplete research, and hope that the work is completed in time for the conference. In this case, you say something like "we will present our work on X, Y, and Z." You make no claims about the findings related to your work in those areas, though. You also try to edit the abstract, as appropriate and if possible, to better reflect the subject material that you will actually present at the conference.
Submit an abstract on already completed work. The advantage is you know you will have the results and you can put together a good presentation. The downside of this is that it means you will be presenting last year's results at this year's conference. If you are in a "hot" field, this can mean ceding significant ground to your competitors if they get just a little bit luckier than you, and they have findings just before a deadline and you don't.

Ultimately, there's no right answer to which option to take. You have to decide this based on what is expected of you in your field, and what impact this will have on you and your career (if you can opt for the safer track, or if you have to go for the higher-risk option). The only thing that you should never do, as I said above, and as other posters have mentioned, is make claims that you have not obtained.

+1 for "no claims about the findings", assuming you mean those that are only wishful thinking at that point

Presumably if you competitors have run and analyzed the experiment at the submission deadline and you haven't haven't run the experiment yet, you have more to worry about than a missed deadline.

You cannot predict the future. You may obtain the results you hope for1. But things can also both go horribly wrong (your laboratory burns down, your samples mysteriously evaporate,...) or extremely interesting - you may happen to measure something beyond your dreams. Let your abstract only tell truths - what your (vague) setup is, what you want to measure and what you expect to happen. But don't pre-claim results when you cannot even foretell their existence for sure. Just be honest - say that you will present the results obtained by them, whatever they may be. I don't like cliffhangers, but they tend to work...

1 But make sure you don't "accidentally" measure only what you expect to be measured!

Short Answer:
Writing something you didn't do as the time of submission is a lie even if you are sure you will have it eventually (I believe uncertainty exists everywhere).
It's simply not your turn this year, target another one or wait for the next year.

Long Answer:
I would speak from Computer Science (CS) perspective.
Submitting an abstract in CS conferences is one of two:

Submitting to the abstracts (short papers) track of the conference.
Submitting an abstract (i.e. 250 words) first then submitting the full paper. For example, these days AI has the big guy  submission deadline.

I assume you mean the first case otherwise you will have no time for preparing your results.
Then the missing results is one of two:

Part of the contribution (method)
Evaluation (support) of the contribution (method)

In the first case, I really recommend not to submit at all unless your results are ready. You just do not have something new in this case.
The second case I will be more tolerated about it.  In CS, you can play around it by:

In case your missing results are the experiments of your method, you can do initial experiments and believe its the general case. Thus write your abstract based on it.
Illustrate with examples and/or real world scenarios.

+1 for "[it] is a lie even if you are sure", though I wouldn't say don't submit at all - I've heard enough talks at conferences which deviated more or less from the abstract, usually "excused" by e.g. "I'd like to focus more on some results obtained after the abstract's submission", which is fine as long as long as it obviously is an extension of what the abstract promised anyway. It may be annoying that the abstract (which may be published at the proceedings) will not reflect the entirety of the work, but a) there may be a paper submission after the conference and b) you'll publish anyway

I agree that you shouldn't report results you don't have, much of the advice on this thread is sound. I would say don't get too into the literature review either...this doesn't necessarily belong in the abstract. The methodology and reasons why are probably key here.
I too am in this boat (though I realize this is an old thread, I'm sure people like me will come here in the future, just as I did).
What some of the people here don't quite seem to understand are mandatory requirements. I don't have data for my thesis yet at all but I'm required by my program to submit an abstract in a few weeks, and I have to submit the abstract for a grade in my class right now. I have no way to get any results at the present time--it's not an option for all of us. Being in academia and research may require you to write an abstract without results. That's okay. Improvise--we're all here to learn, and you won't succeed without that skill.

Good luck with the abstract! You're right, programs have requirements and expectations that may mean submissions are more like research proposals than final results. Early in grad school I was confused when my advisor expected me to submit even though we didn't have any conclusive results--turns out in that context that just writing up the data and methods we'd used and what we were investigating was what the advisor had in mind. Depending on the field and conference (especially if there are no proceedings, and if there are large poster sessions), the submission may also be successful!

I commented on the original question

Don't do it. No results means no abstract.

While this received many upticks, I have also been told

That sounds incorrect. Any references or related experience?

and that statement also has some upticks. While this is not an answer to "how to write an abstract" it attempts to clarify my comment (but is too long to be another comment). Hopefully it is helpful.
I think there are so many things wrong with writing an abstract without results that it is difficult to explain my thinking. The apparent reason for wanting to write an abstract without any results is

No abstract means missed opportunity; I cannot afford that. I have to present results I'm sure I will have by the time of the conference.

Which has recieved essentially the same number of upticks as my comment not to do it. I disagree with "I cannot afford that". I have never seen or heard of someone being denied tenure or a job because they didn't present at a conference one year. Hiring decisions are never so close that a single conference presentation (no matter how prestigious) sways the decision. I would argue that there are very few upsides to submitting an abstract without results and potentially some downsides.
Submitting an abstract without any results will not get you a place at a highly prestigious conference or a keynote address. It will get you a place at a conference that essentially accepts all abstracts, but not much more than that. In fields that I am familiar with conferences happen at least every 6 months and more often every 3 months. This means that by not submitting now you are merely delaying your presentation by 3-6 months. Therefore the cost of not submitting is a 6 month delay and a slightly different conference that is potentially slightly more prestigious (e.g., with results you might be able to get a talk instead of a poster).
In slow moving fields 6 months is essentially meaningless. In fast moving fields, 6 months is a long time, but in the fast moving fields I am aware of you don't present results until they are about to be published. This means you don't want to submit an abstract of results you don't yet have. Therefore I see very little cost of waiting for the next conference.
So what are the benefits of waiting. Again they are not great. The abstract will actually represent what you are going to talk about. You will likely get put in the correct session. There is a higher chance of getting a talk. If everything goes tits up, you will not have to withdraw. While most people will not remember, some of your close colleagues will and this could hurt future references. Withdrawing also screws over the conference organizers and they will not forget.
There is also the issue of how long do you need to get results. If the abstract was due the day of the conference, presumably you would want to have results before submitting the abstract. What about a week? A month? 6 months? Where is the line?
Finally there is the issue of integrity. While one can write the abstract to make no promises and only state the current truth, this is in fact difficult. If you do this frequently enough you will likely eventually make a statement that is a lie.
In an attempt to answer the question, what about:

We don't have any results yet as it is still N months before the conference. By the time the conference rolls around we are sure we will have something interesting. If not, we will present some old data or just not show up.

The results for my project were not a pretty as expected, but I had months to optimize. Unfortunately the abstract had to be submitted asap. So I added great detail to background and methodology, some vague noises about the results, and ended with "preliminary results are discussed." It wasn't perfect, it sucked actually, but it did the job, and the results are now where they need to be for the conference in the summer.
I realize this feed was originally discussed in January, but figured anyone desperate on Google would see this and maybe see a glimmer of hope.

Here is an example of an abstract with no results that was accepted for a conference source:

Evaluation of genetic susceptibility for non-Hodgkin lymphoma in the InterLymph consortium
The incidence of non-Hodgkin lymphoma (NHL) has steadily increased worldwide for many years and is still present after taking into account changing diagnostic patterns and HIV infection rates. Although most other important risk factors have yet to be identified, there is substantial evidence suggesting a relationship with conditions that alter the immune system. A consortium that includes essentially all case-control studies currently being carried out in Europe, North America and Australia has recently been formed (InterLymph) to help stimulate and coordinate etiologic studies of lymphoma. Studies are using the new WHO classification of lymphoproliferative disorders and have comparable questionnaire data for most key lifestyle and environmental exposures. InterLymph will have substantial power to study the main effects of less common SNPs, gene-environment interactions and rare sub-entities. Most studies with complete enrollment plan to carry out genotyping of an initial group of SNPs in genes that play a role in regulating the immune system, including IL1A, IL1RN, IL1B, IL2, IL6, IL10, TNF, LTA, and NOD2. The SNP list will be expanded based on interest and resources over the coming years. A set of DNA samples from 102 ethnically diverse individuals that have been sequenced and analyzed on one or more platforms as part of the SNP500Cancer project (http://snp500cancer.nci.nih.gov) will serve as gold standards. Further, a round-robin of sample exchange will assure genotyping consistency across participating laboratories. Initial results from the analysis of SNPs in the above genes will be presented and analytic issues will be discussed, including an approach that will help evaluate the probability that statistically significant associations are false positive findings.

Just keep it vague and talk about the topic and that results will be presented.  Don't make any predictions or guesses.  Yes, this makes the abstract a bit more nebulous, but who cares, it is a conference abstract, not a journal abstract.  And it's better than lying or predicting.
This is no big deal.  Write up the abstract.  Go to the conference.  Have fun.


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Is it appropriate for reviewer to offer cooperation on a reviewed paper?
I am currently reviewing a paper for a journal (area of ecology, organism-environment interactions at various spatiotemporal scales, so including macroecology and evolutionary ecology). Now I am doing a second review of this paper (after resubmission). They submitted a valuable manuscript, but they ran into challenges which are quite difficult to solve. In particular, their statistical population models didn't converge properly; the models would need at least 10x, preferably 20x or 50x as much iterations to run, but they are very slow - taking 2 weeks to run already. I already investigated a bit and found an approach which would make the models run 1000x faster - this would solve the issue. I don't think this approach has been used yet (currently investigating this).
I am about to give them very detailed instructions on how to implement this approach in their models. I am not an experienced reviewer (this is my first paper to review), but (1) I think this is a bit beyond the usual work done by the reviewers? It is also possible that this work will be very challenging for them, since not every biologist is skilled with models and it's much easier for me since I am a specialist in development of new population models. So, (2) is it appropriate for me to offer them cooperation on their paper, with the possibility of becoming a co-author? (3) Should I ask for co-authorship for this? Or, is it better to just contribute and wait if they offer co-authorship to me? If this happens then the editor would probably need to find another reviewer instead of me for the next revision, because of conflicts of interest.
(The review is currently double blinded, so I don't know their names, but I signed the first review and offered my email already, so they know mine.)

"I am about to give them very detailed instructions on how to implement this approach in their models."
This imply that you are suggesting them to use an unpublished, untested method? It means then they are already using state-of-art techniques: they are doing nothing wrong, and a reviewer must find what's wrong. If you can, you can provide a reference and a quick walk-through. If you cannot ... you are adding the need of review for their paper: a review about the work done AND about the methodology

@EarlGrey unpublished yes but not untested; it's not difficult to test if the new method works, they can either compare the model results with the original slower model (on a smaller dataset), or compare the results on generated dataset. The wrong part is that their models have not achieved convergence and that is by my opinion not acceptable for publication.

Ok, much clearer now. Then you are on track: finding what is wrong, then suggesting a way to correct it. Do not write an extensive guide, see the good answer you have been given.
Regarding suggesting you being a co-author: you are doing it honestly, but it can be read as blackmailing. Double-blind reviews are done exactly to judge the work done only, without inferring who is doing what and who can influence it.

Complete agreement with nabla's answer. Personal story: still in postdoc my paper is rejected. The journal sends me a referee report that says "Your paper will be rejected, but I like it. Here are some suggestions for improvement." Follow 10 pages of a complete rewrite. Anonymous. Wow. I submit elsewhere. I receive an email by a famous professor: "I'm the guy who reviewed the paper the first time and I'm at it again. Small world. But this time it's good enough." Published. Later we co-wrote. But that prof was super generous and had nothing to lose. Don't give away too much for free. It's work.

"The review is currently double blinded" - not anymore it's not!  Unless the editor (hopefully) removed your identifying information before forwarding the report.

Since this is your first review, you probably ought to keep the following in mind:
It is not the job of the referee to fix the paper, it is the job of the referee to provide grounds for the editor to decide whether to accept or reject it. Presumably you have research of your own, and while it is no doubt very kind of you to offer very detailed instructions for how to carry out a new analysis, this is ultimately not what you are tasked to do.
What you can do in your review (which is to be addressed to the editor), is to point out that their current analysis has a flaw, and whether or not you think the paper is publishable with this flaw. If not, then you can suggest that the authors (and not you!) revise the paper using a better method. Here you can give a comment stating your suggestion, and point them to a reference.
And to answer your question concretely: No, it is not appropriate. It would place you in a double role, where the authors might feel pressured into accepting you, to have their paper accepted. If you are very keen on publishing your method under your own name (provided that it is, in fact, novel), you have to wait until their paper is published, and then write a paper of your own. Note that you cannot use privileged information obtained as a referee.
Finally, don't sign your reviews. I would hope that the editor removed your signature. If you don't like giving blind reviews, you should abstain from accepting them, and provide reviews on open platforms which allows this. Like it or not, blind reviews is the name of the game.

Excellent advice. Take it.

They don't have a version of their paper on a preprint server somwhere? If so, you could use that as a starting point for your own work without needing to wait. You could have even contacted them based on that, but this is now spoiled as you signed your review.

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A major journal in my field is published by Elsevier. How can we move the field to a less objectionable, more open publisher?
Many people complain about Elsevier and over eight thousand are boycotting it, but actual solutions seem hard to find for certain fields- I'm thinking of research areas for which an Elsevier journal is very important and funds are not available to subsidize an open-access journal.
How can we move an Elsevier-dependent research community to a less objectionable, more open publisher?
I'll post a partial possible answer myself; I'm asking because I think we need more/better answers than mine.

Maybe a right answer to this question could be a community wiki with journals sorted by fields, where we first put the elsevier journal, and then people post equivalent alternatives?

You seem to be referring to a strategy of encouraging support of existing alternative journals. That'll be very good for certain situations, and so the list you imagine indeed should be started somewhere, but above I was thinking of Elsevier journals that are central to a particular research community, so that it's unlikely most researchers will leave it without a concerted effort and broad agreement by the community- hence the partial answer I give below. As for the community wiki idea, I don't know stackexchange well enough to have good judgment about that- maybe you're right.

A specific example in theoretical biology.

We've now started an information resource for journals thinking about making the jump to open access - psyOA.org

As a publisher who has launched an OA journal and seen what it takes to do so, I see the biggest problem for starting any journal being lack of an Impact Factor (IF). I've polled authors at ECVP and about 90% said IF is what determined where they submitted. Everyone knows why this is, so why don't academics turn inward and try to undermine this reliance on IFs? Doing so would insert true competition into the journals market. Maybe academics have tried to do this, though I've never read of any real substantial attempts. I could be wrong. The second problem after IF and before funding is loyalty. Ed board members are often tied to multiple journals and in those first few years you really need those big names on your board to commission for the journal. Big names often care more about another journal or just don't care.
You need a publisher, be it nonprofit or profit, that can put in the work to promote the journal and help commission. Financially, OA journals are very easy to start. Subscription journals require more financial backing, which perhaps could be gotten through grants if you don't want to be tied to a commercial publisher. The answer is long and requires lots of discussion and more important, commitment.

Thanks for this- I agree completely with the need to reduce the reliance on impact factor. Unfortunately, as long as IF is the only widely-recognized measure that is perceived to be correlated with journal quality, research administrators and bureaucrats and grant reviewers will continue to judge us by it. Some people are working to address this by developing alternative metrics.  Try #altmetrics on twitter, and total-impact.org for one example. Of course, the only real way to judge research is to read the paper, but no-one has time for that :)
Alex

First one must assess whether researchers in the area agree that the community should leave Elsevier. If there isn't strong support for leaving Elsevier, then any move is likely to fail, as it will probably involve a new venture (such as a new journal) requiring the support of many, many researchers in the area, perhaps as authors, editors, or readers pressuring their university to subscribe to the new journal. If the research community is not supportive, this may because they have very good reasons or it may be out of ignorance / lack of imagination of the alternatives.
Discussion of the possibilities in your researcher community serves to explore the options, educate, and potentially build support. You may be able to start a discussion of the issues on mailing lists, social media, or run a conference symposium/satellite related to this topic.
If there is community support, there are a few possibilities for actually making the move. In most (all?) cases, Elsevier owns the journal and its name, therefore one cannot simply switch publishers and keep the same journal name. As a work-around, moves have occurred when all or most of the members of editorial boards of Elsevier journals resigned and started a new journal, usually issuing an open letter explaining their action and encouraging the community to submit to and subscribe to the new journal.
A new journal can use the traditional subscription model or be open access.
With a subscription model, one can use a traditional publisher- a non-profit university press may be less objectionable than Elsevier or one of the other mega-profitable corporate publishers. I have started a list of possible publishers. To get started with a new publisher, one must convince them that they will make enough from subscriptions for the new journal to be worth their while. This may be difficult, as new journals are frequently risky. It takes a few years for a journal to receive an impact factor, and may also take years to be indexed by the major databases, and many authors will only submit to journals that have already achieved these things.
An open-access journal can use the author-pays model, in which case a large publisher can provide all the traditional services (manuscript submission software system and reviewing workflow management, layout, copyediting, production, webhosting, accounting, exporting to databases, DOI registration, proper metadata, etc.)  or it can be run on a shoestring, with academics handling everything perhaps with a few administrative staff. For research communities willing to submit all their manuscripts in LateX, this is quite feasible but for communities that demand layout (figures and text arranged to fit a standard page appearance and possibly typesetting) be done, this is more labor-intensive.
Several open-source software tools assist in publishing journals. Open Journal Systems is most like a traditional journal publishing platform but I hear it may be difficult for academics to use. Annotum is based on Wordpress and I believe it works by having authors write their manuscript directly in its software, so that it can guarantee that the paper will look exactly as you expect it (WYSIWYG). It is used by PLoS Currents and other journals. All of these tools could probably use more skilled programmmers contributing to the project.
I am only a researcher, not a publisher, so perhaps not everything I have written here is correct. I think we researchers are in particular need of estimates of the person-hours needed to publish and manage a journal by various methods, so that a research community considering a move can budget appropriately / be comfortable knowing what they're getting into.

"for communities that demand layout (figures and text arranged to fit a standard page appearance and possibly typesetting) be done, this is more labor-intensive" — Um.  LaTeX can do that.  That's what LaTeX is for.  It's not even that hard.

Unfortunately you won't be able to get most scientists, e.g. in biomedicine, to use LaTeX. It may be easy for you and for math/CS/physics types, but not for your average doctor/psychologist/biologist. Many have never used any scripting or markup, e.g. html, in their lives, and are not willing to try it.

"Doctor, doctor, it hurts when I do this."

Thanks for the Lyx tip- if it is very robust, then it should be suitable for some traditionally-not-LaTeX researcher communities! Although I'm sure there's some, probably including the author communities I'm involved in, that will say they absolutely positively need Word's Track Changes feature or something.

@user107 I assume you never really used Microsoft Word.

Open Journal Systems (OJS) is pretty straightforward to setup if you have an already-existing web server with PHP and database support; that's all it needs.

It occurs to me that in our field (vision science), Journal of Vision already is an open access alternative to Vision Research. I haven't noticed a big difference in quality or acceptance rates between the two journals, they publish at a similar rate (JoV=270, VR=252 articles in 2011) and their impact factors are within 0.5 of each other. Also, around a third of the VR editorial board are also on the JoV board, and Denis Levi is about to transition from VR editor in chief to JoV editor in chief. Given these similarities, I guess the fact that the whole field hasn't abandoned VR suggests that people still feel there is a place for it. Or, from the other perspective, the success of JoV shows that lots of people wanted an open access alternative, and it's great that they now have one. {reposted from Google+}

Journal of Vision is open access but charges a fee. Many of those who prefer it to the alternatives may nonetheless not submit to it due to lack of funding. Therefore it's hard to conclude anything from the continued success of other journals.  It is more valid to compare two subscription journals, e.g. VR and Perception, one of which is published by Elsevier and one not. Again however, there is a major confound- the VR impact factor is lower, and many authors feel they must publish in the higher-impact journal to win grants or a permanent job.


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Getting a job in industrial math with only a Masters?
Is it possible to get a job in industrial mathematics with a Masters in math but no work experience and no PhD. Or would one be limited to only nonresearch industrial math jobs?
How about the type of jobs listed here: http://www.siam.org/careers/thinking/solve.php
?

Would you please explain what's on your mind about a "job in industrial mathematics" and "nonresearch industrial math jobs"?

I'm voting to close this question as off-topic because it’s about a non-academical career.

The link in your question lists many possible job opportunites of what applied mathematicians have. They all look exciting to me (and possibly you) and they are useful to human society.
However, you probably will have some difficulties when you apply for those jobs. There are two things you don't have yet: Math knowledge in depth (you don't have PhD in Math) and domain knowledge (you have no work experience).
For example, How might disease spread in populated areas in the event of a bioterrorism incident, and how would it be contained?. Do you have enough Virology background to devise algorithms to simulate this? Do you have enough Math knowledge to solve the math problems behind the algorithms?
Another example, How can you allocate an investment among various financial instruments to meet a risk/reward trade-off?. How much do you know about Finance? How much do you know about quantitive finance mathematics?
You need to have at least one of them, either math in depth or domain expertise. Without either one of them, the best you can do is a research assistant or simply a programmer (to implement the algorithms other scientists  and mathematicians devise).
My advice to you: either pursue a PhD in Applied Math or a masters degree in an area that suits your most interest.

Students with master's degrees an applied mathematics (and statistics, OR, actuarial science, mathematical finance, etc.) often find work in industry doing applied mathematics, but this work is not typically "research" of the sort that results in publications in research journals.   If you want to do publishable research, then complete a PhD.

PhDs are usually preferred for research jobs, since a PhD is literally 3-5 years of training how to do research. However, if you did research during your Masters, you might be considered.


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If I order GRE score reports before my Subject GRE score is available, will schools receive it?
I am planning to send both General and Subject GRE scores to some universities using the "order additional score reports" option. My subject GRE score is not available yet. It would take twenty more days. After selecting both of my GRE scores, it shows that one test score is being sent. I want to know if my subject GRE score will also be sent once it becomes available or do I have to spend $27 again just to send the subject GRE score to those universities?

Have you asked the GRE people?


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Which areas have the most competition for tenure-track positions?
Being a professor in a general interest department, students from diverse backgrounds and aspirations come to me for career advice. A good number of them aspire to professors but unless they're in my own discipline I'm very hesitant to say anything. But I think it would be good to have an approximation for various fields as an advisor. For example, I know that securing a tenure-track position in CS is not as competitive as a tenure-track position in math. I assume the competition is brutal for history/literature/philosophy etc. Is there an approximate rule of thumb that I could use to advise the students?

What on earth is a "general interest department"?

I do not know of any datasets that would empirically answer your entire question. However, several different datasources may provide insight into your question. First, the NSF has survey and reports that may help. These provide insight into overall employment:

The NSF Conducts a post-graduate survey for Science and Engineering. Data in here may be insightful to what happens to students post graduation.
The NSF includes funding rates in their annual report. Check out the appendices.

Also, this Inside Higher Ed has a table of job placements by broad fields.
I would add the following caveats to this data and other data you may use to answer your questions. In some fields most PhDs go the academy. But in others, most PhD holders go to industry or government jobs. Additionally, not all university jobs are the same (e.g., small school versus R1). I would highlight this difference to your students as well.
Finally, I would suggest checking out salaries for different departments. Many state schools make this public (or newspapers in their state though public data requests; e.g., the Texas Tribune's listing for the state of Texas). Presumably, departments that pay more have more trouble attracting and retaining faculty.
Edit to clarify the last sentence: Engineering and physics can be closely related disciplines. However, there is a much larger job market for engineers outside of universities. Therefore, one might expect universities to pay their faculty more to account for competition from the private sector. At the University of Texas, the median salary for the Department of Physics was $105,536. The median salary for the Department of Electrical Engineering was $118,143. Following the links, there are even better break downs of the data by position (e.g., professor vs postdoc). Comparatively, the Department of English had a median salary of $84,839.
Without speaking to the University Leadership, I can only speculate as to why some departments pay better. My guess would be the higher paying departments have more difficult recruiting and retaining because the private sector has more jobs, pays better, and often requires fewer hours.
I would also add a personal anecdote about competition for tenure track jobs. My own PhD is in Environmental Toxicology. Most of the people I knew in grad school (both at my school and others) went on to work for industry, consulting firms, or the government in roughly that order. Few went onto universities, but those that did only needed a short (1-2 year postdoc). Conversely, my friends who are ecologists often need 5-10 year postdocs to get university jobs. This is because the ecologists have much greater competition for their tenure track jobs.

Surely that last sentence needs fixing.

@DanielR.Collins : If the department has a problem, but needs staff, they may very well pay above the going rate to get the staff they need.

@DanielR.Collins No. I clarified my answer, but stand by it. Some departments pay better because they face more competition from industry and/or government. You're a mathematician. Do applied mathematicians or pure mathematician have more trouble finding work? My guess is that pure mathematicians have more trouble finding work.

I see. Perhaps the particular sentence could be clarified as "Departments that pay more due so as a result of competitive pressure" or somesuch.


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Citing sources of problems in assignments
This question was raised by Dave Clarke here.
When a textbook author approaches a topic in a novel way or presents a particularly interesting example, I believe that a teacher who creates lecture notes using this novel approach or interesting example would be doing the right thing to cite the originator of the approach or the example.  Similarly, whenever I copy a clever (and clearly unique) problem from a textbook and give it as a question in an exam or an assignment, I try my best to indicate (in the exam or assignment paper itself) the source of the original problem.
Does anyone know of any written document indicating whether or not it is considered unethical to copy a published problem and put it in an exam or an assignment without citing it?

I don't know about ethics, but what you try to do can be impractical if the original author includes solutions. I guess offering the credits after students have to hand in exercises would work, then.

Problems are much the same as jokes. And similarly, sometimes it's difficult to track the origin.

I'd like to thank all those who submitted answers.  I have found them useful and have upvoted them all.

I'm a textbook author. I agree that it's hard to formulate a cut-and-dried answer to your question. One criterion to consider: If a colleague would compliment you on a copied problem or question because it was particularly clever or insightful, you should probably consider a citation. Stated differently, if you're getting academic credit (even if informal) for the contribution, cite the source.

Too subjective, just cite source to all problems in your notes/book. Better safe than sorry.

I think it's considered more of a courtesy rather than a requirement to credit someone who has developed a problem, provided that there is no new technical content introduced in the problem. On the other hand, however, if one is to use a problem in a problem set or examination completely unchanged, then some citation of the original source is certainly recommendable, as otherwise one is guilty of a copyright violation.

I'd think the question of citation and copyright violation are somewhat orthogonal to each other. Unless dictated by licensing terms (e.g. Creative Commons), copyright violations are still copyright violations even if you cite your source.

I agree with the other comment, and would also point out that copyright often allows you to use small portions (e.g., one chapter, or a handful of exercises) for teaching purposes.

Does anyone know of any written document indicating whether or not it
  is considered unethical to copy a published problem and put it in an
  exam or an assignment without citing it?

I know of no document that addresses examinations and assignments directly but reusing someone else's words or ideas is plagiarism. It doesn't matter the source, purpose, or intent. For teaching materials I think there is a little leeway in that plagiarism may be unintentional. I am sure that some the examples I use in my teaching ,that I think are my ideas, are in fact someone else's.

I am trying to give a point of view different from what some of the answers.
Citation is generally associated with new, clever or original creations. But sometimes it is very hard to know the origin. What if the author him/herself does not cite some examples or questions taken from someone else. How do you know they had the original idea? Often questions are borrowed modified and then presented. Should we take the credit for them or not? We learn some techniques of setting good and relevant problems from someone else and then we create new ones. Should we cite them?
What I mean to say is that it may not be practical and possible and even clear if we need to cite and I agree this may not always be the case. I guess that is why none of us has come across any such documents and guidelines.

This is a thorny issue. It comes down to copyright and license, and, particularly, what is and isn't copyrightable. If the problem is not copyrightable, then you can do whatever you wish. If the problem is copyrightable, you should assume it is copyrighted,  which means you can't use it unless you have a licence to do so. The only way you are guarantee that you have a licence is to use that book in your course. If you require your students to purchase the book, then they are purchasing the license to use all of that content. You can then use the same content with them.  Even providing a reference is not good enough if the material is copyrighted, and you don't have the licence.
If the problem is fundamental or factual, then it's probably not copyrightable unless there is something peculiar about the wording. Thrse questions can be complex. For example, the following would not be copyrightable:
What is the derivative of x3 + 4x?
What is the major product of the reaction between calcium carbonate and sulfuric acid?
Write the time-independent wavefunction for the electron in a ground state hydrogen atom. Then, provide the eigenvalues for this wavefunction with the kinetic energy operator.
Draw a simple set of supply and demand curves for a generic free market for a manufactured product. Describe or draw the effects of each of the following changes on the market: 1) discovery of a cheaper method of production, 2) closing of a plant, 3) government enforcement of a maximum price.
I'm having trouble coming up with a question that is copyrightable. Feel free to add one to my answer.

A complex problem that involves an extended set-up would probably be copyrighted. On the other hand, the underlying idea is not copyrighted, and could be used without any concerns about violations. It's the specific expression that's copyrighted.


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How to list online publications (e.g. blog posting, etc.)?
I am updating my CV. As for my own publications, I have the usual sections:

Journal articles
Book chapters
Conference proceedings

I would also like to include the articles I have posted on different blogs.
The question is: which heading would you use for such electronic articles? They are not really conventional, peer-reviewed articles, so frankly I don't see fair to include them under the "Journal articles" section.
I saw some people use "Other publications", but I would like to be more specific.

See also: http://academia.stackexchange.com/questions/11195/can-something-published-on-arxiv-or-optimization-online-org-be-mentioned-in-my-c?newreg=a5f0ba18ae3d47e98cee73b0ac1f7ea9

Just keep it under a relevant label to make it sure that you don't pretend to have more peer-reviewed publications.
E.g. "Blog posts", or as I do: "Popular science and education-related articles (selected)".
If there are many, be sure to select only the most important/relevant ones.

I have a section called "Other public output". (And  my articles section is "Peer Reviewed Articles.")


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After a PhD in biotechnology/engineering - more opportunities in industry or a postdoc positions?
Currently, my fiancee are both currently pursuing our PhD's in bioengineering and materials science and engineering, respectively, at the same university. She wants to eventually have an industrial research position and I want to do a post-doc with the intention becoming a professor. We are ~3 years away from needing to have the serious version of this conversation, but which route of the two would be the bottleneck in our eventual decision? Are there more industrial jobs available than post-doc positions? Are there any other dual-academic-career couples out there with advice for us? I hope the content of this question is appropriate for this stackexchange. Thanks so much.

I am in a similar fix, would love to see some nice advice!! :):)

On the "positive" side, the world as we know it could not exist in 3 years. It's good to plan ahead and to have a strategy for life, if you keep in mind that in several years there are several things that can change: a) the wold, b) your mind, c) (very specially) the opportunities.

I just want to point out that the answer will vary depending on field. For instance in biology, there aren't many industry opportunities unless you want to leave biology totally. My impression is that things are very different for engineering (and even for non-biology sciences)

In some universities, if one member of a couple is given a position, the other will have better chances of getting a position, so the couples don't split. If there is collaboration between a company and a university, it could help.

I don't know much about bioengineering and materials sciences. In my area (CS) there are many more industrial positions available than academic positions.
However, industrial positions often tend be clustered in regions, and there might not be too many academic jobs in those regions (or they might be very highly competitive).
Sadly though, I suspect that basing your decisions on where you might do a postdoc is a problem, because a postdoc itself is a temporary position, and so you're really only deferring the real problem. One argument would be that if postdocs in your area take a while (say 3-4 years vs 1-2), then you might as well operate as if that were the permanent job, and then reevaluate after your time is done and you're on the academic job market.
Good luck: two-body problems are tricky, and when one partner is on the academic track it gets even trickier.

Ah, thanks for your insights. I was under the impression that usually post-docs are "usually" offered professor positions.

@tquarton Post-docs are considered more likely to be offered a given open, available position than other applicants - but in general most institutions are not hiring on the same timeline as your average length of postdoc. So if you have a postdoc of 1-4 years and your university only hires professors in that field every 5-20 years, you can see how this heightened opportunity to be chosen might be an utterly moot point.

I don't know about your area: as @BrianDHall says there's a huge imbalance between number of postdocs and number of faculty slots in that area. and even if there's a vacancy it's by no means a given (or even close to it) that the in-house candidate will be preferred.

First of all I would like to mention that I am a PhD student in a Bio-Engineering department and this answer contains information about the issue from that perspective.
When I have started to my PhD I was thinking of pursuing an academic career in my field and would like to conduct research on tissue engineering. Then I saw that there is no straight way to this career. The first thing that disappointed me was that the field that I would like to improve myself was a the field of expertise of anyone in my institution. Due to lack of experts on that field in the institution I couldn't study on that field. If you ask why I didn't try to find an another institution, I can only tell that there are not many institutions in the country that have that sub-field of Bio-Engineering. I then choose to studied a very different field than my original intent and now I am close to the graduation.
I am looking to industrial jobs and also to the post-doc positions and I can tell that there are more post-doc positions for our field than industrial jobs. The problem is that those post-doc positions almost always require publications in Nature, Science etc. so it is very competitive. I wish you and your fiancee could find the place that you can fit. Me and my fiancee are not successful at finding it yet, but I have not lost hope.

Thanks for sharing Umut, I wish you and your fiance the best as well.

I am in a similar situation @tquarton. I'm a BME phd and my fiancee is a medical student. 2 comments that i don't think have been made about the academic route.

I've been told, and seen a few times already, that post-docs in our field are actually less likely to make the jump to assistant professor at their current school. The reasoning I've heard is that your colleagues making the decisions are often unconvinced of how important your research is to the field since they cannot possibly stay up to date on your niche, so they expect that you should be able to find jobs at other universities to "prove it"... If you do get external position offers, I think you are more likely to bargain for a 'raise' at your current location. I say this because I am in a similar situation and I tell my fiancee that I expect my post-doc will not be my final landing spot, which is important for our future planning.
also, it is common, if one of you is especially talented or lucky for that matter, that universities will accept you as a couple. This is a nice situation when it happens, and I've seen it once at both locations i've been so far in my career.

I'm very interested in this question, and this is my perception so far (4th year phd). If one or both of you are willing to take an industrial job, this will certainly increase your chances. Good luck! :)

The main advice that I have on this topic is that it can be difficult to return to academia after a stint in commercial enterprise (i.e. "industry"). There are exceptions -- some people do publish from commercial positions, or otherwise develop some exceptional expertise that gives them opportunities as academic researchers. My impression is that returning to academia is easier for engineers than for basic science researchers (such as biologists, like myself).
The flip side is that if you want to go into industry, you might as well get started ASAP, unless you think your post-doc project will make you an attractive candidate for companies.
So at least for biology, my understanding is that if you shouldn't leave academia until you are sure that you want to. This is especially important for biologists, since there aren't very many "biology" jobs outside of academia, so leaving academia often means leaving biology.

I think you might have misunderstood the motivation for the question. She doesn't want to go PhD->Industry->Academia. The concern was geared towards which of our two distinct paths would be the limiting factor in eventually settling in the same place together. Thanks for your answer though!

I shouldn't answer prior to having coffee.

Haha, no problem.


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Should I put my not-yet-submitted work on my web page?
I am planning on submitting a paper to a journal.  Is it acceptable and advisable to upload it to my web page for public consumption, in the mean time?

Many of the questions and answers with the preprint tag are relevant here. Do these answer your question?

Depends on your field. In math and theoretical computer science, sure.  In chemistry, absolutely not.

@JeffE: What's so special about chemistry?

See http://academia.stackexchange.com/questions/10284/what-are-the-reasons-for-journals-to-reject-any-manuscript-that-has-already-been

I varies with fields and journals.
Some journals do allows posting preprints on one's webpage, or on a preprint server.
Some not, but they don't care. (And some academicians do put their papers on their websites, even if it is against rules.)
Some don't allow and do care, so putting the preprint on your webpage may disqualify you from publishing this work.
(If it fits your discipline, why not using http://arxiv.org/?)

I don't use arxiv.org because one has to be invited, and I am an independent researcher with no contacts aside from my old adviser.

@horsehair Try asking your advisor, or authors of papers you cite.

One does not have to be invited to ArXiv.  One has to be endorsed.  There's a difference, and the latter often means just convincing one person, not many.