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How to respond to "When are you graduating" when I'm behind
I'm a 5th year Ph.D. student. I've worked on several different projects in the last couple years, some of them not related to my dissertation topic, so I don't yet have enough results to say for sure when I will defend. I'm working solely on my dissertation project now, and I'm working as quickly as I can.
We have group meetings once in a while. Another faculty member and his student also attends because they collaborate with my advisor. In the past several meetings, my advisor has been too busy to attend, and the other researcher, who is not too familiar with my research activities, has been asking me things like:
Are you writing any papers?
Have you formed your committee?
How many years have you been here again?
When are you going to graduate?
When I say "no" "I don't know" etc., he has an expression of concern (or maybe pity). I am really annoyed by this. It's like someone keeps on asking me about my fish when it died recently. I'm already under enough stress trying to do research. The last thing I need is someone reminding me I'm behind schedule - it's demotivating. Not to mention this makes me look bad in front of my group mates.
What should I do? Tell him bluntly "it's none of his business"? Stop attending group meetings?
While it's unfortunate that my graduation is delayed, taking into account my own abilities and changes in research topics, I'm happy about where I am, working on something I'm interested in. I would much rather do some meaningful and quality work than slap together something half-baked for my dissertation. (Of course, I know I could be making more money by getting a real job sooner, but these are the best years of my life and I would rather spend it doing something I love.)

What should I do? — You should stop worrying what other people think and finish your thesis.

Send them there.

It is well known that "When are you graduating?" or even "How is your research going?" can be touchy questions among graduate students.  But this is well known in part because they get asked these questions constantly, including by each other.  And even if they can be unpleasant to answer, they are still fair questions.  I'm not sure that the problem lies where you think it does.

I'm working solely on my dissertation project now, and I'm working as quickly as I can.

That's a pretty defensive thing to say straight out of the gate.  Basically you sound like you want to ward off in advance any thought of optimizing or improving your path to the PhD.  An academic who sees no room for improvement is setting the bar pretty low.  I am a tenured faculty member, and if you came to me saying, "I think you could work faster / more efficiently / with greater output if..." then believe me, you would have my attention.

We have group meetings once in a while. Another faculty member and his student also attends because they collaborate with my advisor. In the past several meetings, my advisor has been too busy to attend.

Forgive my prying, but I have already seen something that to me looks more serious than some other faculty member asking you some questions you don't like.  Your advisor is too busy to attend your group meetings?  You know, I think you might work more quickly if....

When I say "no" "I don't know" etc., he has an expression of concern (or maybe pity).

Both concern and pity are positive emotions.  This guy sounds like he is -- you got it -- concerned about you.  The fact that he is showing up at several consecutive meetings while your advisor is not makes me think that he is indicating a desire to help you out.

I am really annoyed by this. It's like someone keeps on asking me about my fish when it died recently.

I find your simile to be pretty strange, but I'll try to play along: isn't it like he's asking about your living fish who has looked a bit less than healthy recently?  Maybe I'm not getting the picture: who or what has died in your recent life, metaphorically speaking?

I'm already under enough stress trying to do research.

Yes, you sound like you are very stressed out.  People who are too stressed out are not doing things in the best possible way, or even in a healthy way.  Most commonly there is some kind of disconnect between their future hopes and their present actions.  Talking through that kind of dissonance, and adjusting either or both, could be very helpful.

The last thing I need is someone reminding me I'm behind schedule - it's demotivating.

If being reminded that you're behind schedule is demotivating, then something seems off-kilter.  Being reminded that you're behind schedule should be motivating, unless the schedule is not reasonable, in which case that should be directly addressed with your advisor.  If it has been, then the problem seems to be that you haven't been honest enough about your situation.  If he expects you to graduate next semester because you're an Nth year student, and you and your advisor have decided that you're not going to graduate until the following semester, just say so.

Not to mention this makes me look bad in front of my group mates.

Your group mates should know your situation better than someone who has been sitting in for a few weeks, so I don't really understand why this makes you look bad.  Unless they don't understand your situation and these questions are revealing it....which is not the visiting professor's fault.

What should I do? Tell him bluntly "it's none of his business"? Stop attending group meetings?

Stop attending group meetings?!?  Presumably the group meetings are an important part of your own research and progress [although with your advisor absent, I have to wonder...], in which case not going would be a terrible overreaction.  (If they are really not valuable, then okay, don't go.  You'll work more quickly without having that waste of time.  But tell your advisor about it: why is he having you go to meetings that are a waste of your time?)
I think the bottom line is that this faculty member is trying to be helpful, but if you have fallen into an interaction with him that from your perspective is only getting you down, then you should talk to him directly about that.  I would suggest making an appointment with him privately and at that appointment have the conversation that he wants to have all at once.  Tell him about your situation.  You can tell him that you think he might be concerned about you but that now that he knows Extra Information X, you hope that he can see that you are now firmly on track.  If he disagrees, then he can share his opinion with you privately and perhaps even give you some actual help.  At any rate, one can only ask questions like "Have you formed your committee yet?" "How many years have you been here?" so many times.  If you give him the chance to spend as much time as he wants asking those questions, then with any luck he won't ask them again at your group meetings, and if he does you can say, justly, "We discussed this thoroughly last week, so I don't want to take up everyone else's time revisiting it now.  We can talk later if you like."
Anyway, please don't dismiss the idea that this faculty member could help you out.  Good luck.

Consider an analogy: Say your mother-in-law has started pestering, "So when are you guys going to have a baby?"  You are undergoing a fertility treatment, and have, together with your spouse, decided not to disseminate this information.  Now the MIL, who has expressed little interest over the years in getting to know you as an individual ("the other researcher, who is not too familiar with my research activities..."), notices some crud on your stove and some mold in your bathroom, and starts speculating on poor housekeeping leading to "problems in the bedroom", resulting in ...

... lack of conception.  ---  So here's my question for you: do you think your answer will result in the OP feeling less defensive and less sensitive to the collaborating professor's intrusive questioning?  Is the questioning only occurring when the advisor is out of the room -- and if so, let's ask ourselves why?  There is a balance of power between professors and grad students that your answer does not seem sensitive to.  ---  I remember my department chair pushing me to change my thesis topic from what my advisor and I had chosen together, to a humdinger of a problem he had in mind, ...

... which was not remotely related to my own research interests.  When I brought the story to my advisor, we decided together that I would go off the department grant that funded RAs, and switch to TA funding instead.  Once I did that, the meddling stopped!  ---  Your assumption that the advisor is shirking his duties is one of the ones I find most unfair in your post -- totally unsupported by the OP.  For all we know, the advisor was on a two-week paternity leave on the birth of his second baby.  Or moving his recently widowed mother into a nursing home.  ---  Your intentions and well ...

... wishes for the OP are clearly nothing but good.  But I've noticed that it is sometimes difficult for an established professor (not just you!) to step inside the skin of someone who is highly sensitive.  Sure, the OP would benefit from having a thicker skin -- but your post does not strike me as having a high likelihood of furthering that goal.

Please don't take it personally.  That your advice is motivated by a sincere concern and desire to help is also clear to me, even though I've never met you!  By the way, when I said "balance of power," I meant imbalance, of course.  Anyway, my 12 yo son with Tourette Syndrome and OCD finds it difficult or impossible to assert himself with teachers at school, when he feels that they have overstepped bounds, such as confronting him about one of his phobias, and asking him to explain it to them (which is excruciatingly painful for him -- but then standing up to them doesn't feel possible ...

... to him yet). They mean well but are oblivious to his experience of these things.... I think that learning about how my son experiences the world, and advocating for him, have given me a special view of that imbalance of power between teacher and student, and how tremendously subjective people's perceptions of exactly the same thing can be. What I picked up on in the OP was how intrusive the prof's public questioning felt to the student, and how powerless s/he felt.

One doesn't have to have a diagnosis to be hypersensitive, or to be an adult to have difficulties asserting oneself. If an OP gets tied up in knots feeling that someone is putting him on the spot, in a public way, that is his reality (I'm already under enough stress...The last thing I need is...it's demotivating... makes me look bad in front of my group mates). If an OP feels stuck between a rock and a hard place (be blunt or stop attending?), that is also part of his reality. We need to recognize when an OP is hurting, and not make it worse. Like the Hippocratic Oath -- "first, do no harm."

@aparente001: My answer most certainly addresses that the OP feels under pressure and stressed out.  Your suggestion that there is something in my answer that will harm the OP is a conversation-stopper.  Best of luck to you and your son.

I sincerely mean no offense to you.  Much of your answer and comments is constructive.

I think this is a great answer. OP is not a 12-year-old who cannot be expected to confront their teachers; they are approaching the end of their PhD and are essentially a researcher in their own right. Moreover, it is not clear from the question that the other professor is a bully that needs to be put in his place; he may indeed be concerned or trying to help or just (appropriately) curious about the position.

Since you probably don't want to confront him in front of others, I see two options:

Let your advisor know what's going on and let him or her deal with
the problem; or
Assert yourself directly with the collaborating faculty member outside the meeting.  You can say, for example (calm tone throughout -- that's important), "I appreciate the concern for my progress that you've expressed in recent group meetings, but I can assure you that I'm in good hands with Prof. So-and-So.  You don't need to worry."  If he doesn't get the hint, and starts in on you again during this conversation, then you can step it up a notch: "I mean this with no lack of respect, Prof. So-and-So: I am already being well advised."  Stop there, and look him squarely in the eye for a moment (just long enough for him to hear the unstated Butt out), and then calmly leave, thanking him for his time.  If after that he still says things that make you uncomfortable in the group meeting, the next step up is to stand up to him in front of the others: "I don't think it's appropriate for you to ask me these questions.  As I already told you, Prof. So-and-So is my advisor, and I have full confidence in his/her guidance of my studies."

I would go for option 1 if possible.

I don't think it's appropriate for you to ask me these questions. — Downvoted for this suggestion.  The questions that OP describes are completely appropriate.  The visiting professor is there in a professional capacity and is asking professional questions about the members of the research group he is visiting.  If "So, how's your work going?" so threatening that you feel the need for this level of confrontation, something has gone very badly wrong.  Get help, either from your advisor, from the visiting prof, from another faculty mentor, or from a mental health professional.


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How to finish my PhD dissertation before funding runs out?
I am in the 4th year of my PhD and still has no paper published. I am working on my first ... but it has taken a long time because I had not been very satisfied with that piece of work and had been making modifications here and there. I have a second piece of work expecting to be published, but that one needs considerable improvement, too. My advisor is very grumpy about this, and he is now anxious to get me enough publications to send me off. Things are a tangled mess and I have no idea how to get out of this.
One, during the past three years, I had been working on something totally different from the main interest of my advisor. He is now sending me bits of pieces to work on in his main field. But I have little background knowledge, while still having to spend time writing that poor old paper and RA-ing on another project that supplies funding. I would never graduate in time were I to work on the new topic. I have not even identified a reasonable topic yet! On the other hand, if I were to incorporate some of the previous work into my dissertation work, it is different from my advisor's interest, and I fear another two unproductive years.
A second difficulty adding to the first one is, I find myself unable to discuss work with my advisor. The meetings are just like: I told him what I had, he made some comments, and then told me what to do next. Things never lasted more than 20 minutes. I feel lacking the big picture or a research objective. Sometimes I wish he could help me look at this piece of source code or that, but then in the meeting just failed to show it. Also, I am not a methodical or precise thinker, but my advisor is and he is very quick and sharp. I can make things clear on paper, but am terrible at taking facts from memory. This probably does not help him form any good impression. He also keeps mentioning I need more publications which are terrible blows to my psychology.
Finally, I have to graduate in two years, because funding is definitely running out by that time. In fact he is not even paying me at this time.
Seriously I want to quit, except to quit almost means the end of academic career. If I do not quit, what can I do to remedy the situation?

write an agenda/checklist of topics for each meeting, 2. have your advisor or someone else review the 1st paper, make any changes and submit it!

Thanks. 1. I wrote a checklist before meeting, but still failed to mention things. 2. Yes,I really should.

Try printing two copies of your checklist, and hand one to your advisor at the start of the meeting.

Advisors tend to be busy people. Try to find others (in the group, other students) to discuss details with. Send out your papers as they are, seek feedback that way. "Perfect" papers will never be done.

@vonbrand Thanks. Now that I think, one reason I cannot bring my papers to an end is that I found others have found out the same thing during the past couple years. So I really feel the paper is not of value. In fact one of the papers was heavily criticized because their results was old. I had not been good at extracting information from papers until the beginning of this year ... and missed a lot of information.

Here are a few ideas, hoping to help you get unstuck.

My spouse had a big-name, brilliant advisor who was impatient and rarely had time to meet with his students.  Fortunately my spouse found a person in the department who was able to be the mentor on the ground, the person to go to when a question came up.  He had a positive, supportive attitude, and was very knowledgeable, but was not able to be the advisor of record because he didn't have the right sort of title.  Perhaps you could find someone like this?  It might even be an advanced grad student or a postdoc.
Suppose your advisor is out of town for a month, but you and he still want to have some collaboration.  A good way of doing that is by writing a weekly email to your advisor, where you make an itemized list of what you've been working on and what questions you have.  I would suggest that you try writing this type of memo even when he is not out of town, and sending it to him the day before your meeting.  That can provide a helpful structure for your in-person meetings.
It sounds like you would benefit from having a study buddy.  This is someone who will listen to your troubles supportively from time to time, and help you stay on track with your goals.  It doesn't need to be someone you enjoy going to see a movie with -- this is similar to a study partner for a particular class, that you compare homework answers with.  Ideally this would be a mutually supportive relationship.

I would also suggest that you bite the bullet and resolve to spend some time learning the background material necessary for a productive collaboration with your advisor.  You don't have to continue working in that particular area your entire life -- you just need to get this PhD done, and it sounds like that's going to be the easiest way to do it.
Reassurance: it will probably not take as long as you fear it will to learn that background stuff.  Although you might not realize it, you are a more efficient learner now than you were a few years ago.  Also, I think you are motivated now to figure out how to do things methodically.
I can see that both you and your advisor have had your frustrations with each other.  I predict that as he sees you taking steps to meet him halfway, you will start to see more patience and a more positive, supportive attitude from him.

Thank you for all suggestions. I am not sure about the feasibility of point 1 ... there is no advanced grad student or postdoc in our group because my advisor is new. For point 3, I have not experienced that kind of study buddy...how could one just to find someone?

Once you know you are looking for a study buddy, you'll look at people a bit differently (in seminars and classes).  Be a good listener, show authentic interest in the other person.  Invite a likely candidate to have lunch or coffee with you.  It doesn't need to be someone in your exact field.

@eddieisnutty - It doesn't have to be someone in your immediate group.

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Describing Middle School in european grant application
I completed my PhD in the US, and I am currently writing a grant application for a EU grant.  While I was a graduate student, I worked on a grant that had me in a middle school classroom (8th grade, so 12-13 year old students).
What is the best, short way to describe this in my grant proposal? I don't want to waste a lot of space describing the specific age range of the students, if it can be avoided.  At the same time, I don't know if it will be clear what I mean if I write "8th grade classroom" or "middle school classroom".  Any ideas?

"I worked on a grant that had me in a middle school classroom" - if I interpret this the same way you mean it, the research/work you did based on the grant had to be partially or completely conducted in a classroom, while working with the 8th graders? In any case, while it is not unambiguous, either, I would strongly prefer "8th grade" over "middle school", given that the concept of "middle school" can be defined arbitrarily depending on the country (and also, doesn't even exist in some places).

Describe it like you did here: 8th grade, and then in parenthesis put (ages 12-13) to remove any ambiguity. That will only cost you a couple of words, and no one can misunderstand.
To expand on @ORMapper commented, in Sweden middle school would be "mellanstadiet" which is grades 3-5, and the students are aged 9-11. So specify both what the gade was "called" and the age, and avoid descritors like "middle school"that can vary a lot by country.

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Differing perceptions of men's and woman's evaluations of their own work
I wonder about studies of bias in academia, specifically about studies of how people respond to men's versus women's own appraisals of their own work.
Many studies have argued that people at large are more critical of women's claims in academia (or in business, but that is not my concern now) than of men's. I am looking for studies specifically on responses to self-evaluations.

This is a site on general issues in academia. What you look for is expertise in a specific field, in your case gender studies. The only direction you can expect here is : visit your library.

I'm not sure I understand what you're saying about Noether.  That people thought she was simultaneously extremely modest and an annoying braggart?  Meaning she suffers from Schroedinger's personality?

From what I know of Noether, she didn't publicly say much about her own work, possibly due to the fact that for a large part of her career she wasn't even allowed to lecture under her own name.

Noether is probably not a good case to study this question. First, her most important contribution is probably the modern foundation of algebraic gemoetry, and at the time of her death many mathematicians would have seen this as too abstract to be useful. Second she was jewish, which changed the way many people reacted to her well before 1933. So you would have to separate antisemitism, failed understanding of her importance, and sexism, which appears pretty difficult.

@zibadawatimmy I was saying that people have contradictory ideas about her.  This happens often, that people have contradictory ideas.  But I was not asking anything about her -- I was asking about studies of bias in academia (which I, personally will use in my work on Noether).  Mentioning her confused a lot of people so I took that out.

@MaartenBuis Are you saying that the gender tag here is off-topic?

Sometimes I think that we close all the interesting questions on this site.  I have voted to reopen.

@Jan-ChristophSchlage-Puchta yes, separating those is difficult. That is why I only ask about one of them here, and I do not ask specifically about Noether.   I am asking about one  kind of sexism.

@PeteLClark yes it is an interesting topic, but just asking for literature on an interesting topic is still off topic.

@Maarten Buis: I see your point, but I do not think it to be too compelling. The question is not just about literature in gender studies, but about literature in gender studies dealing with academia. The question touches the problems of imposter syndrome and ethics in hiring and publication, which are definitely on-topic for this site, so I would judge it as a borderline case.

@NatalieHogg I have published several articles discussing what Noether said about her own work.  If you write to me I can send you copies.


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Is there a standard English translation of ausserordentlicher Professor?
Of course the exact status of the title has changed in different places and times.
I mean it most specifically in the sense of Emmy Noether's title at Georg-August-Universität Göttingen in 1923: nicht beamteter Außerordentlicher Professor.  But I doubt there is a standard translation for that specific situation.
My question is, as in the title, is there a current, standard English translation of the basic phrase Außerordentlicher Professor?
By a standard translation I mean one that is currently in widespread use, in contrast to one that I or another person thinks should be an accurate way to describe the position.
However, a look at the confusion of the English language Wikipedia Ranks in Germany convinces me there is none so I was in process of deleting this question when an answer appeared.  Now I will wait and see what happens,

Can you either 1) elaborate what that title meant and entailed or 2) what you would consider as “standard”?

One thing of note - on the one hand you mention  Emmy Noether in the year 1923 and on the other you want a current translation. Which is it? Are you interested in what Emmy's position was, or what today the position of an "Außerordentlicher Professor" would be? Also, are you specifically looking for Germany, or also for other countries with that title, such as Austria?

@xLeitix It is as I said in the question, I am asking for a current standard translation.  I seriously doubt that there is one such for Germany and another such for Austria.  Indeed I now doubt there is one for either country.  I know very well what Emmy's position was, i am interested in how best to describe it concisely in a book chapter.

First, the expression "außerordentlicher Professor" is no longer in current widespread use in Germany (although still understood; the exception is, as so often, Bavaria); a non-ordinary professor position is now usually referred to as "W2" (after the pay scale) or, in some states, "W3 ohne Leitungsfunktion". Most people who now hold such a position would translate it as "associate professor", although there are a number of significant differences between the positions that make this translation misleading in some regards.
It is also a very different position from the one Emmy Noether held (which was unpaid, for a start). In fact, Emmy Noether's position was actually that of an "außerplanmäßiger Professor", a title given to tenured university assistants after their habilitation, which entails most of the academic, but very few of the administrative, rights of a university professor. (The "nicht beamtet" previously disambiguated the two positions; the title was renamed during the Nazi regime.) This position -- which no longer exists in the German system, and, confusingly, was called "außerordentlicher Professor" (and now "assoziierter Professor") in the Austrian system -- has no analogue outside the very hierarchical traditional German system. Hence there is no canonical translation; if pushed, I would translate it either as "tenured research assistant" or "lecturer" (if there is no danger of confusion with the UK title, which would give the wrong idea), both capturing (different) aspects of the position.
Especially in a historical work, I would therefore do exactly what the English wikipedia article on Emmy Noether does -- use the original German title and give a parenthetical explanation:

the title of nicht beamteter ausserordentlicher Professor (an untenured professor
  with limited internal administrative rights and functions)

I think one can not get more accurate than this on this complicated issue. +1

The concept of Ordinariat (a Latin word used in the German-speaking academic circles) is similar to the English chair. A non-ordinary professor is a professor who does not have the responsibility of a chair.
So that would translate often to "associate professor" depending on the individual situation and local practice.
Keep in mind that since academic hierarchy varies a lot between countries and that it is not always possible to translate positions, and that is not a question of language. In doubt the safest thing would be to use the original title.

Thanks.  The variation between your first and second answers exactly matches the ambiguities of the English Wikipedia article which had me on the verge of deleting the question.

Pet peeve (+1 for not making that mistake): While "Ordinarius" indeed corresponds to "ordinary" in English (as a noun), this is not cognate with "standard, usual" but has a more direct common root with "ordained" -- an ordinary is someone who has ordinary power (as in civic authority in a church order), and hence a "Professor extraordinarius" ("außerordentlicher Professor") would be someone outside the ranks with ordinary power. Hence, a "non-ordinary" but not "extraordinary professor" (which would translate as "außergewöhnlicher Professor").

As a side note, the translation of "außerordentlicher Professor" on the web page of the university in question also goes with "associate professor": https://www.uni-goettingen.de/en/74993.html (compare german/english versions)

@ColinMcLarty I edited mostly to remove ambiguity. Ordinary professors "have tenure" in the Anglo-Saxon sense but most non-ordinary profs. also do. So the chair thing is really what's making the difference.

@ChristianClason I though a non-ordinary professor would be a "Unordentlicher Professor"… But we better keep quiet before this thread get mirgrated to http://german.stackexchange.com/

@Dirk I've known examples of both :)

However, in the US an Associate professor is a member of the faculty and votes in the faculty Senate.  I believe that in the Weimar Republic an außerordentlicher did not vote in the Senate.

@ChristianClason as another side note, in French it's not uncommon to see professeur extraordinaire which indicates that the distinction was lost in translation at some point.

As a counterpoint to Cape Code's answer, in Austria an Außerordentlicher Professor generally has tenure, at least in the sense that her or is position is not time-bound. The main difference here is that a "full" professor holds a chair ("Lehrstuhl") and has been appointed through a (nowadays international) faculty search with all its formal procedure. An Außerordentlicher Professor has often held a long-term postdoc in the same university when (s)he applied and received "Habilitation", and has been made Außerordentlicher Professor and received tenure as part of standard habilitation practices.
An Außerordentlicher Professor formally holds no chair and is instead associated to a specific chair in the university hierarchy, although what this means in practice varies widely given that an Außerordentlicher Professor is still a professor with all the guaranteed independence of teaching and research. The widely accepted English translation is "Associate Professor", although this transports the (wrong) message that Außerordentlicher Professor is an intermediary career step from which there is a clear progression to a chaired professorship. Instead, many (or in some institutions, most) researchers who become Außerordentlicher Professor remain in this position for life.
In Austria, this position is now widely considered a legacy of former times. Automatic promotion to tenured Außerordentlicher Professor when successfully defending a habilitation is as a practice discontinued in most departments, and there is no formal way to become Außerordentlicher Professor in the traditional sense otherwise. Many departments nowadays use this title much more in line with the US meaning. That is, younger new hires sometimes are hired on the rank Außerordentlicher Professor, with a an agreed-up promotion to regular professor after an evaluation phase (e.g., 5 years).

That is actually not (always) true -- speaking from experience, an "ao.Prof." (and more recently, "Assoz.-Prof." -- some universities have reinstated that system under a new name) is part of the "Mittelbau", not the professorial curia; they are the highest rank of tenured assistants. So while from the point of independence of teaching and research they are indeed equal to a full (chaired or non-chaired) professor, they are treated differently by the administration (no possibilities for negotiations, for example). How much difference this makes in practice depends on the individual department.

Which doesn't actually contradict most of your answer... (Although I'm very surprised to read the last paragraph, which is in direct contradiction to everything I know about the Austrian system (as opposed to the Swiss system, where this is indeed common practice, at least at the ETHs). But, academia varies, so...)

Here's the key point: An Austrian "außerordentlicher Professor" ("ao.Prof.") is not an Extraordinarius (which is just "Univ.-Prof.", in contrast to an ordinary professor's "o.Univ.-Prof."), but corresponds to an "außerplanmäßiger Professor" ("apl.-Prof.", a title granted to tenured assistants with habilitation) in the German system.


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Why is explainability not one of the criteria for publication?
A paper is eligible for publishing in reputable journals in general if it satisfies the criteria objectivity, reproducibility and (optionally) novelty.
But why are they not considering Explainability as a criterion? Although the model proposed in the paper satisfies the above mentioned three metrics but not explainability, then how can it be considered as a contribution to field?
PS: Low "explainability" means proving something works without explaining how it works. See also "Interpretability"

If it didn't satisfy explanability, how did it get accepted by peer reviewers?

Some subfields of computer science has wide acceptance without explainability.

@hanugm I think that you mean a different kind of explainability. A paper containing a bunch of complicated equations without explanations will certainly be rejected by every reputable journal. The type of explainability that you talk about appears to be "using these insights from the problem domain, we found that this new approach works", with an in-depth explanation of the approach, but without a (possibly statistical) analysis on why exactly it works. Is it so?

@DCTLib  Yeah, I am talking about the second part of explainability you mentioned. Say neural networks....

What's explainability? Do you mean accessibility?

@user2768 I mean proving something works without explaining how it works.

@Anyon True, since the both terms are used interchangeably, I used explainability.

So experimental results should not be published until they are well understood?

i edited your Q to add soft definitions and link to explainability/interpretability explanation.

There are huge realms of knowledge where we know what happens, but not why it happens... are you proposing that that should not be publishable?

You specifically mentioned neural networks - is this what the core of the question is aiming at? If so, I agree that we have a severe problem in computer sciences with people publishing thousands of black boxes in different sizes and shapes, and nobody dares to even try and understand what they are doing. Well, at least https://de.wikipedia.org/wiki/Explainable_Artificial_Intelligence has gained some attention recently. People are probably noticing by now that all this grew out of hand...

@fqq Then why restriction on objectivity if some subjective results (from experiments) are reproducible?

@Flyto With similar argument we can't rule out objectivity as a criteria?

Academia is broken anyway, so...

From the comments and answers, it seems to be clear that a proper answer highly depends on the field that you are referring to. It may not be a bit too late to narrow down the question in this regard. But (at some risk of creating a "duplicate"), you might consider a question that is more specific to the field that you are interested in, maybe also elaborating what "explainability" means (or is supposed to mean) in this field.

Who are these monolithic "they" who rigidly adhere to 3 criteria? Your question seems like it is based on a caricature.

Coming especially from a biomedical sciences perspective,

I mean proving something works without explaining how it works.

(from a comment describing what is meant by 'explainability')
this would be an absolute disaster for science. Many results are not explainable according to that criteria; many treatments are known to be successful without being explained (some examples: anesthesia, paracetamol, anti-depressants). If we waited until findings were understood before publishing, science would move a lot more slowly.
If you had a black-box image processing algorithm that, for example, beat the state of the art in tumor detection in processing MRI images, that result would be very interesting and publishable without being able to explain the black-box. In fact, it would likely be unethical to not publish such a finding.
However, that also doesn't mean that everything that is published is "true" and definitive: further confirmation by repeated studies, applying a consistent algorithm to new/independent data sources, etc is necessary to build consensus. Those aspects need not present a barrier to initial publication, however. To the contrary, it's important to publish even negative results to facilitate future meta analyses.
Certainly, a paper which can explain some phenomenon has a lot of merit and value, and is better than work that cannot provide such an explanation, it's just that "explainability" cannot be a required criterion.

For the field of medical science your statement may be true, but that particular example from your last paragraph strikes a chord for me. Currently, we're seeing a flood of papers in computer science that apply "deep learning"/"neural networks" to a variety of highly specific problems, and do not say more than "It works (but we don't know why)". Many people are publishing like mad and literally do not have the slightest idea of what they are doing - even though that may seem hard to believe for other fields. Really, cf. https://xkcd.com/1838/ : If it looks right, it will be published.

@Marco13 Indeed, though of course people still need to be cautious of https://xkcd.com/882/ - that shouldn't be a barrier to publishing, though, it should be a barrier to how studies are interpreted and how results are validated on independent data. I should make clear that I have in mind things like paracetamol which are in wide use, definitely effective, and yet...still oddly not well understood.

Superconductivity would be another example.  New superconductors may require hundreds of papers before they are explained.

@Marco13 It's a horrible problem really.  How can we know that the neural networks actually work if we don't know how they work?  I know they had an AI that could check chest X-rays for tuberculosis, and while they did better than human x-ray technicians, many of the false positives it found were correctly assessed as negative by humans. The issue was the AI knew the xrays were coming from a hospital, it had learned this meant he or she was sicker, and this biased the test to think it was more likely tuberculosis.  If you can't explain what patterns it's finding, how do you know they are real?

@BryanKrause The comment indicates that the barrier for something that can be published at all seems to be much higher in the field that you are referring to - specifically when you talk about "validation" and "independent data". In some branches of computer science, people are really throwing any data into any neural network and produce any result, and then use 4 pages to argue that it "looks right". It is like sampling the parameter space of neural networks, where each sample point is a paper. That's a waste of time, really.

@AnonymousPhysicist Hundreds? I think there's been over 100,000 papers on high-T_c superconductivity already...

@Marco13 I mean subsequent papers. Not in the same original paper.

I agree with most of this answer, but explainability being a criterion does not mean that non-explainable results should be excluded. It just means that explainable results should be given extra-merit

@David Agreed, and edited to make clear.

@Ryan_L If an algorithm repeatedly and reliably works in a real-world setting, that's sufficient information to say it works. False positives are part of the assessment of an algorithm. Understanding how an algorithm works can be very useful in improving it, but is not necessary to evaluate how well it works.

I fully agree. But I'm also with @Marco13 in that validation in many (including biomedical) studies isn't as rigorous as the claims would demand.

@cbeleites I agree that validation is often not as rigorous as it should be, but I think a lot of times that's more an issue with interpretation, not the results themselves. I think (hope) most scientists understand that a single publication is not proof and that proof really doesn't exist in science, only accumulation of evidence to the point that it becomes progressively less likely that future work will upend the status quo.

This answer and its reasoning is the reason we have less than 30% reproducibility rate in biomedical sciencs (machine learning likely similar), where researchers can often neither explain exactly how they produced the results nor why. This is the current desaster. As mostly CS guys are frequenting this site it shows how flawed the methodolgy/rigor/explainability is in statistical sciences and peer review as expressed in comments above. The upvoters (large majority) think really this way, this is shocking to me, not the answer so much, which had to posted by someone.

@sera What would you do about paracetamol? Anesthetics? Anti-depressants? (we don't know how any of those work) I maybe shouldn't have included the ML example but did because I thought it would be more relevant to OP's interests, but I wrote the answer with medical science in mind, going back long before ML. (and maybe read the second-to-last paragraph, too)

@BryanKrause I really think biomed cannot be the standard here with so low reproducibility and Bayer, BASF researched this fact in several meta studies. The interesting question to me is if in Anesthetics etc. science is really based on pure random trial and error and if you can then still call it science, do peer review of papers and funding proposals and spend billions every year on unreproducible research. This is sure not the case in hard sciences like physics that there is nearly zero explainability how and why dinstinct results are produced. Maybe I post such a question when I have time

how common pure random trial and error research and publications really are. Maybe I'm strongly anaware of it in biomed as a physicist. But reproducibility is the most important criterion if you want to call it science, otherwise the voters don't understand and would also argue for homeopathy instead of Anti-depressants? :-)

@sera My point is that we know anesthetics work, going back to the use of ether in the 1800s. Give someone an anesthetic in the proper dose, and they are unconscious, unresponsive, and have no memory of a surgical procedure (yet wake up after). No idea how it works. Now we know some of the molecular targets; still don't know why it works. We know anti-depressants work (and homeopathy doesn't). We even know some of their molecular targets, but we don't know which ones are important for the effect. Explanation isn't necessary to be useful.

@BryanKrause sure, but this justs shifts the problem slightly. Usefulness cannot be the goal of epistemological research, a PhD thesis or a bigger fundamental research project. Also vodoo medicine by aborigines in the forests is working somehow better than homeopathy, but can/would you call this science? You know it works over molecules, in machine learning they often have no clue what the nonlinear complex neural network does at all...

Papers are evaluated on a variety of criteria, including accessibility and the contribution to the field of research.
Now papers that not only report findings, but analyze findings and provide root causes for effects observed in the paper are obviously more valuable and are more likely to be accepted.
But from a scientific point of view, requiring that papers have this property would not be a good idea. Quite often, the root cause of an observed phenomenon is not known. Not being able to publish papers without finding the root cause would mean that information stays "unknown" until the person making a discovery also finds out the reason for an observed phenomenon, which could mean that it is never found out. For instance, if Mendel with his discovery that traits are inherited until the DNA was found,
 that would have been quite a loss.
In computer science, you need to distinguish between pure theoretical computer and the rest. While in the former, the proofs provide all the reason you need, in the applied fields, at least part of the argument is some utility of the finding. There are many subfields in which algorithms are published that work well in practice despite not giving theoretical guarantees that they always work. Finding out why certain algorithms work well in practice would require to define exactly what "practice" means, which changes over time. Machine learning is a good example: we know that many machine learning algorithms can get stuck in local optima, and we have some ideas on how to prevent that (in many interesting cases). And then there is some theory that tries to capture this. But ultimately, the reason for why many of the approaches work are that the models to be learned are easy enough and the algorithm is good enough, which is very difficult to  impossible to formalize to a level that it would be acceptable in a scientific paper. And then requiring an in-depth explanation of why a new approach works would essentially mean that there will be almost no publications of practical relevance.

I'm not sure what you mean exactly by explainability and it cannot be a scientific metric if it doesn't exist in a dictionary.
So I conclude what you are thinking about is that the content of an article has to explain something: an not well understood process, a new method, a new theory.
Different fields have different standards and metrics. I'm sure there are different for publishing a new physical theory vs. an optimization of a machine learning algorithm for image recognition. But this is normally covered by the novelty and significance metric by a journal.
From a philosophy of science point of view you also should see or inspect what the modus operandi of researchers in your field is. For example, in particle physics or cosmology researchers try to falsify the scientific paradigm/theory, especially if there are too many flaws in a currently used theory. I know some of the basics of machine learning theory and that many of it is based on mathematical methods developed in quantum physics. This is a bullet-proof theory pretty much, no one has falsified it until this day and physicists still try. But in engineering and even in applied physics depending on the topic/resarch question rather a positivistic modus operandi is used by researchers, e.g. optimizing/enhancing/backing up a machine learning algorithm without substantial questioning or falsification underlying theories. And for minor incremental improvements an explanation in the sense of why rather then how may be not necessary in your field and therefore no general metric if the underlying theories are not really touched. As soon as you question a theory or common measurement process, at least in physics, you need to input a good explanation in your article, why and how you do this. What is the motivation, why it is more accurate to describe something.
When you say in the comment "proving something works without how it works", I think this is what sometimes in industrial machine learning happens, input - black box - output. But if you can neither explain how or why your algorithm works (better), in the best case you can call it smart engineering but not science that can/should be published ;-)

"My black-box model predicted this transaction is fraudulent" is an unexpalinable result. "My model predicted this transaction is fraudulent because there were 100 similar transactions in the last few minutes which also came from town X, most of them being for an amount in the [Y,Z] range and being cancelled seconds before...." is an explainable (and explaind) result

Explanations are maybe not always as useful as you are probably thinking.
On the one hand, say, a mathematical proof why this machine learning approach behaves the way it does is fine. As long as the proof is correct, this type of explanation will never become wrong (only maybe outdated).
On the other hand, consider complex systems as you encounter them in the life sciences. An explanation in a paper would often really not be at the level of a mathematical proof (that level of certainty is impossible to obtain in the natural sciences), it would be a plausible hypothesis in line with the experimental findings.
 The catch is: had the experimental findings been different, very often (sufficiently complex system) plausible "explanations" could be formulated which would be contradictory to the plausible explanation formulated for the findings actually at hand.
In that sense, explanations (hypotheses fitted retrospectively) are a dime a dozen.
Personally, I think it more important to limit the claims to what the data in the paper can actually support. Iff you bring good data that shows your model successfully deals with the situation at hand, that's fine. And coming from an experimental field, I'd still ask for a proper and honest experimental support (which is more than a quick verification with a few not-so-independent cases*) alongside any explanation.
And: Just as validation may be wrong in that a major influencing factor was overlooked/unknown at the time of the study, wrong/mistaken explanations have been known as well.
All that being said, this may be too much for a single paper - so IMHO it's fine to publish "advances in theory" and "experimental findings for this application" papers (as long as each of the papers has sufficient substance on its own).

* if you take the time a well designed validation study with, say, 3000 patients needs to work towards a deeper mathematical/theoretical understanding, you may get quite far in that respect as well...

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text:
Professor wants to change my thesis' interpretation in favor of his research. How to react?
I am about to finish my undergraduate thesis. The interpretation/conclusion i wrote is basically a statement which matches well with research of other groups and has a widely accepted scientific background.
After letting my supervisor (who has been mentoring me) and then my professor(who gave me the topic and is in charge of the decisions in the group) control my thesis, my professor wants me to edit my interpretation and write one which mainly goes along his research but is not widely accepted in science.
My supervisor said I should do what my professor asks me to.
Should I?
Edit: My professor asked me to change because I had no clear evidence for my assumptions. But I would not have any evidence for his suggestions neither.

Thanks for clarifying. Can you also [edit] to add what reason your professor gave when suggesting the change?

By supervisor I mean advisor, by professor the main person in charge. I edited the post.

It sounds like there may be potential arguments in favour of both interpretations. First pin down what they are - then you're in a better position to have a discussion with your professor. It may turn out that one of you is unambiguously right - and that's a good way of finding out. More likely, there are arguments for both interpretations, in which case you might be best off presenting both together with some critical analysis. TL/DR: Follow the evidence. Without providing any evidence, neither of you is demonstrably right.

@StuartGolodetz Sounds like an answe. Can you post it as one?

It sounds like there may be potential arguments in favour of both interpretations. First pin down what they are - then you're in a better position to have a discussion with your professor. It may turn out that one of you is unambiguously right - and that's a good way of finding out. More likely, there are arguments for both interpretations, in which case you might be best off presenting both together with some critical analysis.
TL/DR: Follow the evidence. Without providing any evidence, neither of you is demonstrably right.

If you have no clear evidence for interpretation/conclusion A (drafted already, by you) or for  interpretation/conclusion B (suggested by your professor), then it sounds like it's time to draft a new ending to your write-up.  How about the following:
Lay out A, with some supporting argumentation.
Lay out B, with some supporting argumentation.
Both would be worded as conjectures.
Then talk about what work would be needed to be able to support or rule out one or the other.
And then comes your Bibliography!
Since this is not a PhD thesis, you can sit on the fence.

Stick to the truth:

Write up the results that you obtained (which are the facts of various kinds).
Say that "I conjecture that [A is true]."
Say that "In a personal communication, [insert name here] suggested that [B is true]."

You should bear in mind who will be marking your thesis and later on writing letters of recommendation. If you want to stick in the same field for later study, people who hire you will almost ask either your supervisor or the professor in your group of their opinion of you. You should offer some concession to the professor. Maybe a good middle ground would be to evaluate both viewpoints, and lay out the whole field as aparente001 suggests. If you really think your interpretation is right, maybe you should talk to the professor about it, and see if (s)he can persuade you or vice-versa. Note that if you are going to dispute this with the professor you really need to be understand the debate, with well thought out reasoning (not just "big wig professor" says so).
At the same time, intellectual dishonesty on your part helps nobody - don't write a conclusion you can't stand behind and defend.


text:
Why is it inappropriate to compare computer languages with natural languages in a Bachelor thesis about an assembler and emulator?
In a manuscript of my Bachelor thesis (about a PicoBlaze assembler and emulator), I made a few statements I was forced (by my mentor) to delete. These include:

I was explaining what the parser (a part of an assembler or a compiler) does using the following sentence from Caesar's De Bello Gallico: "Ea, quae fertilissima totius Germaniae sunt, loca aliquibus Graecis nota fama esse loquuntur.". Which word is the word "nota" (known) syntactically connected to? If you know only a little bit of Latin, you will probably assume it is connected with "fama" (fame, rumour), that it is a pleonasm and that the word "nota" should be ignored. However, that's incorrect. The word "nota" is connected to "loca" (places). Parser, I explained, is there to resolve such situations when they occur in a program code. In an abstract syntax tree produced by the parser, "nota" and "loca" would be children of the same tree node.
I compared the assembly language to the Piraha language because both of them lack linguistic recursion.
I said that programming languages mostly use a mechanism to divide words (tokens) that somewhat resembles the one used in the Japanese writing system.

However, I was forced to delete those things because they were supposedly inappropriate. Why exactly are they inappropriate?

If you were writing a paper meant for a computer science audience, why would it be helpful to make analogies to natural languages which the readers aren't assumed to have any familiarity with? All three of these explanations could be written in a way which gets the point across better for the intended audience. So (2) and (3) are more like irrelevant side-notes than explanations, and (1) works as an explanation but would work a lot better if you chose a domain which the reader already has knowledge of instead of relying on them following your explanation of Latin grammar.

Also it would help to clarify, by "forced to delete" do you mean that your mentor is also an author of this thesis, or do you mean that they strongly advised you to do this out of concern for how your thesis would be marked?

It seems moving that explanation to the appendix would let you treat it as an interesting aside.

I must say, if well-researched, these would be interesting things for me as a supervisor. If they had come in isolation, I might have suggested for statements like this to be moved to the later, speculative parts of a discussion, but would still have found them interesting. If your supervisor doesn't, remove them from the bachelor's thesis which is essentially an examination document. There will be other opportunities to develop your style.

This is probably going to get closed, since none of us can know what your professor's objection is.  But as a computer scientist, I would raise an eyebrow because computer languages are designed mathematically to have certain properties relating to ease and speed of parsing (including ambiguities).  Human languages emphatically do not, and any analogy at the level of a bachelor's thesis is suspect right there.

Please take the "inappropriate" as "off-topic" or "distracting".

It is a convoluted expression, that aims at explaining something by showing how someone without knowledge of topic A would falsely interpret a sentence in language A: not very useful.
It is at best still debated (as you can read from the wikipedia page), at worse it seems something taken out from wikipedia just to fill some gaps (which I doubt, because the wikipedia page has many more insights in the topic, but that's the way it would look like ;) ).
Imprecise, even controverse (since many western languages divide the words in tokens, called syllabs, that somehow resembles the japanese language), if you were to be japanese mother-tongue or very fluent it may be helpful, otherwise it looks like (again) some random fact copied from wikipedia.

Do not overstress too much, it is a bachelor thesis, you want to have it remarkable and that strikes out and you want to show some independent thinking on the topic ... please remember that a boring bachelor thesis with no errors and concise to the point is already remarkable.

a boring bachelor thesis with no errors and concise to the point is already remarkable Which tells a lot about our lack of ability, or, rather, willingness, to maintain minimal standards in science and education. +1 otherwise :-)

@fedja Or, it tells us that a bachelor's degree is just the start of a specialised education, and we expect students to continue learning their field or craft as they go on to begin practicing it.

@kaya3 I would agree if it were just about "concise to the point", but I certainly draw a hard line at "no errors". :-)

@fedja A textbook with no errors is remarkable enough.

I will, once again, use the universal answer of this forum: "Ask your adviser". When you say "forced to delete", I suspect what you mean is that they read your thesis and suggested that you remove certain parts by striking them through. Why they suggested that is something only your adviser will be able to fully explain -- so go ask them! Everyone else here can only speculate.

Why is it inappropriate to compare computer languages with natural languages?

Personally, I don't think it is inappropriate, however, that may be the wrong question. The right question is, will these comparisons help your audience understand your work?
At least to me, they are not helpful, but they may come across as interesting side notes (or "easter eggs") which give some personality to your writing. They also indicate that you are a person who is interested in linguistics. So, while the remarks certainly could be fun/enjoyable (for some audiences), you should consider whether they could be off-putting for a reader in your field who is looking to understand your work.

However, I was forced to delete those things because they were supposedly inappropriate.

I understand your frustration! Pragmatically speaking, the big question here is, is your supervisor's name on your thesis?

If they are, then they do have some say over the contents, since it reflects on them as much as it reflects on you.
Once you graduate and go elsewhere, you can certainly write things without paying attention to what your supervisor thinks.

If not, then in my opinion you are free to deviate from your supervisor's advice. However, I would think twice before ignoring it entirely. It is likely that your supervisor has more experience in writing than you. It is possible that by following their suggestions, you might become a stronger writer, and more effective in your communication in general.

Either way, it may be helpful to take a step back -- this is a relatively minor dispute (over a few sentences), and you will likely have bigger differences to worry about as far as the content of the thesis, and much bigger things to worry about later on down the road. Don't let such a small issue take over all of your time and energy!

Parser, I explained, is there to resolve such situations when they occur in a program code. In an abstract syntax tree produced by the parser, "nota" and "loca" would be children of the same tree node.

Have you considered writing a blog post or similar, where you can put these remarks?
I think you have a nice way of thinking about it, in which you describe your view on some of the connections between your field and linguistics.
That could be a better venue for your ideas as it is more informal, and could reach a more general audience than a bachelor's thesis (which is generally a bit more formal and technical).
And, if we're being realistic here, the blog post will probably get more views than the thesis anyway :)

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text:
Can I add an inscription on a bachelor thesis that I have been working on for almost a year?
I have been working on my bachelors thesis for 10-11 months now and am about to hand it in. Without bragging, my topic was by far harder and more work than most bachelor theses.
Now I am wondering whether I should add an inscription to my parents in it. I really want to show that I am grateful for giving me the opportunity to study. Now I have read up on some advice on the internet saying that I probably shouldn't do it because bachelor theses are generally only meant for a small amount of people.
With my thesis this is different as I am planning on releasing at as a documentation of my work (my bachelor thesis was to write an improved version of an existing API).
What do you think?
EDIT:
I am talking about a short "To my parents." on a separate page in the beginning.
EDIT2:
Please remember, a Bachelor thesis is different to a dissertation.

Would you mind providing a link to said "advice on the internet saying that you probably shouldn't do it"?  It sounds like there's been some misunderstanding.  It sounds like very strange advice.

it is in german if that's okay to you i can try to find it again.

Yes, please, I can ask my German spouse for help if need be.

Now that I think about it, the links are from bad sources. Anyways, I guess it's probably best to hand in the version without the inscription and keep it for a released version.

I don't get it!  The inscription doesn't do any harm; you and your parents will all derive good feelings from it; no one will mind; and if you look at other theses, you'll see inscriptions that thank everyone from the kindergarten teacher to the lady at the laundromat around the corner.

I think that the rules for dissertations apply here: namely, unless it's expressly forbidden by your university's rules, it's fine to include dedication and acknowledgment pages.

If you want to dedicate your bachelor thesis to somebody, or acknowledge people: by all means, just do it!
It is your thesis, after all.

Our thesis format explicitly reserves space for dedication after the title page.

Can you please expand a bit to actually answer the question fully?

A title page dedication may come across as a little pretentious.
I would recommend an acknowledgements section at the back. This is a more traditional way of thanking anybody who helped out, and it's a perfectly normal thing to have in any kind of thesis. You can also use that to thank your supervisor, your friends who helped to proofread, and anybody else you like. This also allows you to state why you want to thank your parents, which may make it a bit more meaningful.

Could the downvoters please leave a comment?


text:
I want to opensource my code. Is it legal? Can I still publish?
I am a PhD (stipend) student at a Max Planck Institute (for a biological science) here in Germany. I came here to write software, but ended up spending practically all my time doing wet-lab work. As a consequence, the programming I wanted to do had to be done in the evenings outside of the institute (although what constitutes 'PhD time' and 'programming time' is a bit of a blur, since I use my programs to solve PhD problems...)
Coming to the end of the PhD, I am now finally ready to "publish" the first of the three programs I have written during my time here in Germany, but there are three stakeholders all with competing interests in my software which make it difficult for me to know how to proceed...
The Max Planck - they will want to claim ownership of the software, because I wrote it while doing a PhD with them. Over the course of the PhD, no one from the Max Plank or the University have had any input whatsoever on the software, however, certainly between 10-20% of the code was developed 'on PhD time'.
The Journals - publishing is not a requirement, but it would be nice. It forms a stamp of approval (in some people's minds) and acts as free advertising at the very least. But for this to happen, I suppose I cannot "publish" my code already, meaning open source it and share it so people can bug-check it before publication?
The Users - Arguably the most important stakeholder for me, because I wrote this software for them. I want to make the code's licence as permissive as legally possible, probably under Creative Commons Zero to aid with this, but I feel this will make publishing impossible, and it may not even be allowed if I am not the owner of the copyright in the first place.
How should I proceed?

Please can you remove all the distracting stuff from the question, and simply tell us what your contract with Max Planck says?

I cannot read German so I do not know - that why i specified Max Plank and Stipend so maybe someone else knows.

@user3329564: Are you serious about that? You have signed a contract without knowing what is stated in there?

You have obviously never done a PhD in Germany. I was given about 30 contracts to sign, no translation help, and to hire a translator cost €30 an hour. They wanted a week to translate it all, and the MPI gave me a weekend to return the forms else I couldnt be enrolled on the PhD. This is incredibly common in Germany. Probably everywhere else too..

In general your employer owns al the IP concerning the work you do while at work, or at home if working for them or with equipment provided by them, unless stated otherwise in your contract.

I suppose I cannot "publish" my code already, meaning open source it and share it so people can bug-check it before publication? Yes you can. In fact, you have to. Typically you need to show active user interest before you can publish your software formally (e.g. github stars, download, mentions on twitter, ...). See for instance JMLR MLOSS guidelines, which state "Evidence of an active user community should be demonstrated ...".

Speak to your advisor, or your local bioinformatics team. I'd guess rather than MPI trying to wrench your code + IP from you and commercialise it, they'll be pretty uninterested and let you publish under whatever license you want.

@MarcClaesen  - oh wow! That is totally new information to me - I would have thought having an active community around the software constituted 'prior publication in the public domain' and would have barred it from any journal. This essentially answers the 'heart' of one of the issues this question addresses - could you make it an answer? :)

@MarcClaesen This is totally not the case in life sciences, indeed may be very specific to your field. No comparable evidence is needed for PLOS comp. biol., Bioinformatics etc.

@blmoore - I highly doubt it too. But as we've seen from signing contracts I could not read, I dont want to end up in a difficult situation in the future because I was told "everything will probably be ok" in the past. The MPI has a track record of being ruthless with money, particularly when that money can be extracted from PhD students.

@user3329564 publications are not patents. Just because software is already available, doesn't mean you can't still publish a paper about it. Fortunately, it really doesn't work that way.

Note: Creative Commons recommends against using Creative Commons licenses for software.

Yeah, i was actually recommended elsewhere to go for the WTFPL (https://tldrlegal.com/licenses/tags/Public%20Domain) but the name is the only thing holding me back. How could I tell a visiting emeritus professor  'I released my code under WTFPL' without expecting them to take a big sigh and mumbling 'god damn millennials... '

@user3329564: It is extremely uncommon in Germany to sign a work contract without understanding it (and at least in a privately owned organisation, it is totally irresponsible because you will most probably be scammed in some way). Even as a native German speaker, my work contracts at German universities so far were always explained to me by the university's HR department step by step to make sure I really know and understand every single detail written in there.

"I was given about 30 contracts to sign, no translation help, and to hire a translator cost €30 an hour. They wanted a week to translate it all, and the MPI gave me a weekend to return the forms else I couldnt be enrolled on the PhD." This is incredibly irresponsible. You should discuss this with your PhDNet representative and make sure it doesn't happen to others.

I did and they were really supportive - they helped me understand the difference between an MPI stipend and a contract, got me a 10% bonus on my stipend, helped me get proper health insurance... I literally don't want to know what kind of state id be in if it wasn't for PhDNet. I never asked about IP because i didnt have anything back then, but now perhaps I should find out...

@user3329564 Only "they" (your Max Planck Institute) will be able to tell you in detail. Having said that, IF you were on a DFG grant or some EU grant, there may be a stipulation that the code has to be openly accessible - so you may want to research the conditions of your grant. (E.g. in the UK EPSRC requires that work is published in a way that makes it openly accessible.)
However your research institution may very well still have a claim on the copyright as well as have a say on the license under which the code is released and only they can help you with that.

Even if you didn't understand the contract at the time, I hope you kept your copy and can translate them now.

@JoErNanO "In general your employer ..." - I don't know how it works in Germany, but in the UK a PhD student is not an employee (except for possible part-time employment for supervisions etc).

I'm the main developer of several open-source libraries, one published and one under review, so I can give you a pretty up-to-date overview on open-source in the machine learning community. This may differ for your field, but probably not much.
Whether or not your university will allow you to open-source and/or publish depends entirely on them. Based on my experience, open-sourcing can be sensitive depending on how old-fashioned your university/lab is. However, if they are fine with open-sourcing, they will certainly be OK with publishing too (after all, it's a free paper!). Only way to know is to ask your advisor.
The only move you have here is to ask your advisor. To my knowledge, at least some MPIs are very much in favor of open-source (e.g. Bernhard Schölkopf, head of MPI intelligent systems, is a co-author of an important open-source mission statement within machine learning).
Releasing software before publication

I suppose I cannot "publish" my code already, meaning open source it and share it so people can bug-check it before publication?

Yes you can and in fact you should. Typically you need to show active user interest before you can publish your software formally (e.g. github stars, download, mentions on twitter, ...). See for instance JMLR MLOSS guidelines, which state "Evidence of an active user community should be demonstrated ...".
In any case, releasing software prior to submitting your paper is not a problem. Publications don't work like patents.
Publication venues
Lately, there is a lot of journal interest in software. To name a few:

JMLR MLOSS
Plos Computational Biology: Software
The R Journal
Journal of Statistical Software

A more complete list is available at http://www.software.ac.uk/resources/guides/which-journals-should-i-publish-my-software
Next to journals, you have a lot of conferences/workshops specifically about software. For many projects, you are actually better off publishing there with the added benefit of shorter review times and far less drama.
License

I want to make the code's licence as  permissive as legally possible, probably under Creative Commons Zero to aid  with this ...

Creative Commons licenses aren't really suitable for software. Be aware that choosing an open-source license isn't entirely trivial, that is open-source licenses don't necessarily allow users to do whatever they want. Most commonly used permissive licenses include BSD, MIT, Apache and WTF licenses as opposed to the GPL. I do recommend informing yourself about the main differences of highly permissive licenses vis-a-vis GPL-style licenses. Some questions you should ask yourself include

Do you want your license to permit commercial use within closed-source projects for free? If not, slap a GPL on it and (optionally) dual license your software.
Do you want to permit non-GPL open-source software to build upon your work? If so, then make sure your license isn't GPL (this is because of the copyleft nature of the GPL).

In my opinion, the best license types for relatively small (but useful) research software projects are usually highly permissive (BSD, Apache, ...). Your university's technology transfer office may disagree, if you even have to go through them (if MPI claims IP ownership of the software you developed you have to pass through the TTO).

The link to software publishing journals is great!

*Sigh* Once again, with feeling: GPL does not stop anyone from using your software commercially. It doesn't even stop anyone from modifying copies of your software as long as if they publish it in any form they also publish the source code.

"MPI is generally in favor of open-source": there are many MPIs, and they are more-or-less independent. A statement from the MPG (Max Planck Society) would be relevant, but the opinion of an individual research at a different MPI is not really indicative of the whole situation.

@l0b0 while I agree that my blanket statement should be modified (which I will do later), it must be noted that in many cases the GPL effectively prevents incorporation of a given module in larger commercial projects. Software that is sold in its own right is typically closed-source. Point remains that GPL significantly restricts use cases, and was originally aimed at preventing inclusion in any closed-source system (which was the key characteristic of commercial software at the time of origin of the GPL).

@Max thanks for the info, I didn't know about that!

@l0b0 "You must license the entire work, as a whole, under this License to anyone who comes into possession of a copy. This License will therefore apply, along with any applicable section 7 additional terms, to the whole of the work, and all its parts, regardless of how they are packaged. This License gives no permission to license the work in any other way, but it does not invalidate such permission if you have separately received it." - This seems to contradict your claim regarding publication.

Cc0 is absolutely acceptable for software.  There are other cc licenses that are not, but cc0 is similar to unlicense, wtfpl, bsd 0-clause or public domain dedication

CC0 can be problematic for software, as for that matter can Unlicence and PD dedication, due to the vagaries of public domain law by jurisdiction. BSD is typically safer, for software that will be used worldwide.

@Taemyr Yes, by "publish the source code" I meant implicitly "under the GPL". Sorry, legalese is not my forte :)

The Journals: Generally, open sourcing a code should not be an obstacle for publication. To the contrary: there is a movement to make as much academic code as possible open - see for example GitXiv. The only problem I see is that open sourcing the code prior to publication may impact the anonymity of blind review. I have however read and authored multiple CS papers where the code was open before publication and nobody complained. Sometimes it was kind of ridiculous - we wrote a paper reporting on an already released new version of a relatively known tool that our group develops for almost ten years, but with anonymized authors :-)
You may want to ask editorial board of the journal on their policy on open code and possible delay opening the code past publication.
Max Planck: Have you asked the institute on their opinion? Or is there a precedent where they refused to open source a code they developed? In my field, having other groups use your software is a bonus and thus the university supports open sourcing code.
EDIT: If the institute opposes open sourcing the code, you may still argue that the code is not owned by them. It depends whether you worked for them (had an employment contract) or if it was "school work". If you had an employment contract, open sourcing would probably be on the darker side of gray area, as at least part of the software was developed "on the clock".

I was recently interested in this issue as well. Although I'm not a lawyer, there are 2 interesting paragraphs in the German law which are relevant.
Copyright law 69b (http://www.gesetze-im-internet.de/urhg/BJNR012730965.html)
§ 69b Urheber in Arbeits- und Dienstverhältnissen
(1) Wird ein Computerprogramm von einem Arbeitnehmer in Wahrnehmung seiner Aufgaben oder nach den Anweisungen seines Arbeitgebers geschaffen, so ist ausschließlich der Arbeitgeber zur Ausübung aller vermögensrechtlichen Befugnisse an dem Computerprogramm berechtigt, sofern nichts anderes vereinbart ist.
(2) Absatz 1 ist auf Dienstverhältnisse entsprechend anzuwenden.
In my interpretation this essentially boils done to, although you retain the copyright, your employer has the exclusive right to do everything with the software you wrote (including prohibiting it from open source distribution), unless the employer explicitly refrains from this right.
That being said, there is another paragraph in the German constitution which is possibly in conflict:
German constitution Paragraph 5 (http://www.gesetze-im-internet.de/gg/BJNR000010949.html)
(1) Jeder hat das Recht, seine Meinung in Wort, Schrift und Bild frei zu äußern und zu verbreiten und sich aus allgemein zugänglichen Quellen ungehindert zu unterrichten. Die Pressefreiheit und die Freiheit der Berichterstattung durch Rundfunk und Film werden gewährleistet. Eine Zensur findet nicht statt.
(2) Diese Rechte finden ihre Schranken in den Vorschriften der allgemeinen Gesetze, den gesetzlichen Bestimmungen zum Schutze der Jugend und in dem Recht der persönlichen Ehre.
(3) Kunst und Wissenschaft, Forschung und Lehre sind frei. Die Freiheit der Lehre entbindet nicht von der Treue zur Verfassung.
Part (3) garantees that work produced in science (of course this includes the software written in the framework of a phd thesis) may be distributed freely and may not be censored.
In a nutshell, the law seems not to be entirely clear on this (although I guess that the constitution takes precedence), and your best bet is to discuss the possibility of opensourcing you software with your employer.

I don't know about Germany, but in the UK a PhD student is not an employee, so there is no employer to have exclusive rights.

Whatever the legal situation, you must talk to your advisor and the people at MPI about what you want to do. If nothing else, just out of common courtesy. Getting into some squabble or even legal trouble with them is definiteley not in your best interest.


text:
Repeatedly citing same item of personal communication
The APA style indicates that personal communication should be cited in the format "J. Doe (personal communication, M dd, yyyy)" in-text, without a bibliographic entry. I was wondering what the best solution to citing such an item repeatedly is?
Example:

J. Doe (personal communication, August 21, 2017) proposes that concept
  X is inherently meaningless without mechanism Y.
[...]
Doe (2012, 2015, 2016) presents mechanism Y in terms a, b, c. We could therefore
  assume that this predicts concept X to exist independently of Y,
  nothwithstanding J. Doe's (personal communication, August 21, 2017)
  objection that doing so would lead to undesired behaviour Z---it is
  what strictly follows from the system proposed in Doe (2012, 2015,
  2016).

Is there a better way to refer to the same personal communication the second time? Options like J. Doe (op. cit.), J. Doe (ibid.) etc. seem to not really work semantically (given what kind of object op. cit. and ibid. refer to) and be potentially ambiguous with Doe (2012, 2015, 2016), although I suppose the initial of the first name here may disambiguate.
Are there any established ways of dealing with this elegantly?
[Edit:] I should add that I have to refer to a different instance of personal communication with Doe elsewhere, so simply citing "Doe (p.c.)" later on would be potentially ambiguous, unless it somehow only referred to the most recently cited instance of personal communication.
[Edit 2:] To provide some context, we're talking here about a situation where the papers by Doe (2012, 2015, 2016) outline a particular theory but leave some aspect of it poorly defined or ambiguous. The private communication entails asking Doe for clarification as to how he intended that ambiguous aspect of the theory to be understood/implemented. So this is not really about relying on data or sources that are unavailable, it is about giving fair shrift to Doe's theory, and making clear as a starting point both for my own work and others how the original point was intended. If this is not taken into account there's a real danger of just attacking a self-made straw man here, and neither Doe nor I nor others in the field would probably be happy with that. It seems inevitable to me that full disclosure here entails citing the personal communication on more than one occasion, namely whenever Doe's disambiguating communication comes into play.

Without knowing the context, what you are trying to do seems poor practice to me. "This is important because person X said so in private" is impossible for peer reviewers to verify, and hence not authorative when written in a paper.

Personal communication in my experience rarely entails some claim that something is significant because person X claims it. These things are usually about giving additional information on something already published that isn't necessarily publicly available, perhaps because at the time the author didn't think it would be relevant, there were space constraints, etc. I don't think my example indicates a situation that is any different.

If you are essentially just mentioning privately stated opinions, then don't. Constantly citing the private opinions of others is bad form and constitutes you ducking the proper work of performing a literature review to establish the importance and shortcomings of your work in a proper, verifiable, and objective fashion. You are tacitly telling the reader "I don't really know what I'm doing but I think this guy does."  Avoid this. Your paper is your work, your voice, your opinions. Do the literature review and make your own case about your own work.
If this private communication is significant to your work in a substantive way (proofs of theoretical results, experimental data, etc.), your options include:

Ask them to be a coauthor if their work is essential to a significant fraction of the work.
Ask them to write an appendix to attach to your work that contains the relevant material.
Ask them if these are things that exist in a preprint, article under review, or in fact published article. If the material is reasonably accessible to the public, then a reviewer will be able to check it and verify that it provides what you claim, and if it is trustworthy enough to stand on its own.  If it is not, you should ask if they would approve of you providing a (confidential) copy to the reviewers of your own work.
Include the result, with full details of the proof, in your own work, saying something like "The proof of the following was kindly provided to us by X in a private communication."  It is not uncommon for an author to include such a line, or any variation thereof, such as "The author thanks X for their helpful discussions", which is a polite recognition that they were important to the development of your work (and possibly why you even started it), but not to such an extent as to warrant coauthorship.  Most researchers don't come up with things in a vaccuum, and are guided towards problems by their conversations with others—that's part of why we talk to each other about our research topics, even the incomplete ones. And sometimes we need one important lemma to get anywhere, and someone else we talk to figures out a proof but doesn't otherwise contribute to the work. I've also seen things like "We learned several of these results from X, but since they do not seem to appear in the literature we state and prove them in full." This sort of statement can be very common for "folklore" results: things the biggest experts all seem to hold as common knowledge, but yet no one has ever actually published.
Failing all of those, you're in a bad position.  It's very undesirable for you to make claims that are impossible to verify, and going ahead and reproducing things this other person has done when they didn't want you to, while not necessarily "wrong", may strain your professional relationship with that person. I would expect this scenario to be very unlikely, but there's always tales of that one intransigent curmudgeon...  While "private communications", especially in the pre-internet age, are hardly a new phenomenon, generally these communications have been provided to reviewers whenever they contain material that needs verification (a proof of something, in particular), and as such this is typically seen as a natural and non-threatening matter.

These seem like reasonable ideas as a general guide. However I think they are all not really feasible/applicable in the present situation, I've added some additional context to the original post to clarify the context. (The appendix thing might be applicable and sounds intriguing, but Doe is highly unlikely to do that).


text:
Mathematics or software engineering?
I am currently in a dilemma and could not decide where I am going in the future.
My undergraduate and master degree is in software engineering and I am currently doing a computer science PhD. I did well and I had participated in more than 5 projects with more than 100,000 lines of programming experience. About 5 years ago I started to grow interest in mathematics although I never had chance to spare much time to learn it.
Now my wife has got an offer in math PhD. In the summer I finally dedicate 3 months to learn graduate level mathematics. When I say "dedicated", I wrote a study note on Real Analysis with about 50,000 words in three months! I type in every word I learned from the textbook, made illustrations using Mathematica and wrote my understanding whenever it is possible.
Then I grew an idea to transfer to mathematics PhD. To achieve this goal I even participated in my wife's classes and did homework in order to get recommendation letters. I was planning to study probability, statistics and numerics that are more near to computer science if I got admitted.
However, this plan is strongly vetoed by my family members and my PhD adviser. None of them agree, including my wife. The main reason is that our universities are not top ones (the math dept. of my wife's math department is ranked about 80+ by Us News and 2nd tier by AMS) and we examined recent graduated PhD's jobs and got pretty shocked -- almost none of them get tenure, and most of them did 6 or 7 years in math but their current jobs get paid 30%~40% below software engineers (accroding to glassdoor) even considering tax and life cost differences.
There was only one exception who did another PhD in statistics in Wharton School of Business for additional 5 years and tenured at a top-10 statistics department. He did 10 years in PhD in total. This is also a possible path for us but it took a really long time and the future is of uncertainty.
I am currently 2nd year in CS. My current adviser told me in 3 years I am guaranteed to get a high pay in software companies. And under his sway even my wife told me she wants to enter software industry. My adviser's words to my wife is "you have learned advanced math pretty well and that proves you are smart. If in addition you learn computer things and then your will one of the best. ".
Yes most of these companies value more about programming and algorithm skills than your mathematics. Those mathematical stuff in CS like "machine learning", "pattern recognition" are not of daily use in software if you don't get a research position.
I am really in a confusion right now I need to decide and focus. Otherwise I would not be able to excel in either direction. So I post here hoping that someone can give some opinion. Thank you!

Hi, and welcome to Academia.SE!  Unfortunately, strangers on the internet are not in a good position to judge which of two reasonable paths is the one that best fits your personal circumstances, goals, and desires.  Is there some aspect of the situation that you would find useful to get more objective information about?

Have you actually published anything? You only talk about programming experience, number of words but none of this is research.

I understand your confusion to opt an interest or to go with skills which will yield you a corporate job. I had been in the same pass; I thought to leave my PhD in Electronics Engineering and join PhD programme in Biophotonics. I got full tuition waiver with a handsome scholarship from a top UK university but I considered the following points to reach a conclusion.
Firstly, there are many more industry jobs for electronics people when compared to a Biophotonics PhD. Secondly, I can always try for teaching positions with a PhD in electronics engineering i.e. I have two career paths to choose from. However, if I talk about Biophotonics PhD, chances to find a job in industry would be pretty less (given my undergrads in electronics engineering). Ultimately, I'll be forced to find a birth place in some university or college. Salaries in universities/college when compared to corporate world needs no introduction.
I would suggest you to carry on your PhD in Software Engineering and you can always work on Mathematics after your PhD (obviously not in the form of a PhD). Mathematical research doesn't needs lab as such so you can carry on your research after your office hours and do publish them.
Another important point, you will spend ages to gain a ninja level of mathematics knowledge which is essential to finish your PhD in Mathematics (if you enroll). That being said, where is the progression in the life? Personally, I am a strong follower of "Money is the ultimate motivation" and don't overlook your family anytime while taking a decision. (I continued my PhD in electronics engineering and after graduating I have a nicely paying job in industry.)

Thank you so much for spending time clarifying this for me. I have made a decision to stay in the industry. Sometimes a kind and generous reply affects another person for life. Thank you!

@RalphB. I am glad to hear that. Thank you! Wish you a great career ahead!


text:
Creating a virtual institute
I have been toying with the idea of becoming an independent researcher, raising money by working very long/hard hours for a year, then taking a year off for solely for research. This would be partially for financial reasons (Post-Doc salaries are really awful), but also because I think my research would benefit if I could pour my undivided attention into algorithm design for a year.
The biggest problem with this plan however is that in order to publish my research after a year or so of intensive work, I would need to be affiliated with an institute - even journals like arXiv require this.
This got me thinking - what actually is an institute? From the little bit of research into it I have done, it seems to be no different to a standard company, although most have charitable status and are tax-exempt or non-profit.
If other people would also like to work for-profit for a year, then for-research for a year (or at some other frequency), then a virtual institute to publish under would be quite a useful thing. In fact I'm surprised such institutes don't already exist: we have scam journals and scam conferences - why no scam institutes?
Of course if I did set up an institute to publish under it wouldn't be a scam, (there are numerous benefits I can see a virtual institute providing for members), but the idea of a on-paper-only institute is applicable to both.

Your question is based on a false premise.  You don't have to be affiliated with an institute in order to publish - no reputable journal requires this.  See http://academia.stackexchange.com/questions/3010/does-one-need-to-be-affiliated-with-a-university-to-publish-papers.  And arXiv (which is not a journal) doesn't require affiliation either; you just may have to be endorsed.  So this is why there are no scam institutes: there's no need.

http://ronininstitute.org/

Thank you both! Nate, you're right, one only needs to be endorsed - but reading that post and others on SE, that seems to be fraught with difficulties. Having said that, most of the people looking for endorsement have little or no formal academic training, which is a separate issue and may make endorsement look harder than it really would be for a young PhD student who simply doesn't want to play the tenure game. Stephan, the Ronin institute actually appeals to me a lot! Thank you! I will look more into what they offer in terms of support, but I see a conference budget mentioned so looks good!

Right.  Frankly, for most people who complain about having difficulty getting endorsed, the problem isn't really "I don't know anyone and the community is so elitist", it's "My work is junk and really doesn't belong on arXiv but I won't listen to anyone who tells me so".  For a young PhD student, getting endorsed should be as simple as writing a two-line email to your PhD advisor, or anyone else in the field you know: "I'm trying to upload to arXiv but since I am no longer at the institute I need an endorsement.  Could you please endorse me? Thanks."

For that matter, most PhD students in an arXiv-able field will already have posted preprints during their studies, and thus can post for the rest of their lives without further hassle.  If your studies are over but you still have access to your institutional email address, that may also entitle you to automatic endorsement.

my research would benefit if I could pour my undivided attention into [it] then don't waste a minute creating an institute.

Example.

I know a number of independent or semi-independent researchers who have set up a small company for themselves to affiliate with (e.g., the whimsically named Turing Ate My Hamster, Ltd.), for various different reasons.
This is pretty easy to do and, I believe, achieves everything that you are looking for from a virtual institute.  It also has the advantage of not being fake in any way---just very small.

If your research is valuable then you should be able to find an institute to affiliate with. If there is a lack of interest in for temporary or part time affiliations in your field (that would work with your research needs) then perhaps there is a demand for institutes more welcoming to non traditional relationships.
There is no reason why such an institute would need to be a scam as you refer to it. Find others in your situation and form an institute together. Depending on the research you are able to produce, perhaps you can attract funding at some point.

Sorry the scam paragraph is probably a bit misleading. What I was trying to say was if anyone could set up their own institute, i'm sure I would have seen a scammer try it by now. If one did actually set up the institutional equivalent of arXiv for example, then it would not be a scam at all.
I love the idea of finding other like-minded researchers in my field to come together and setup an institute. There are tech companies with similar origin stories. I will have to think more about how one could do this...

"If your research is valuable then you should be able to find an institute to affiliate with." Why? It might very happen that his research is valuable but there are too few positions in his field, or there are even more valuable research areas, etc. Obviously I would say this is the most common situation.

@Dilworth I meant valuable in comparison to other research happening in the field. I agree that some fields have so much high quality research already happening it is hard to fund every new idea that shows merit.

You might want to correct your phrasing then.