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What to remember when supervising female PhD students?
I have been supervising a female PhD student for a couple of months. She is the first female PhD student I am supervising and got the position on merit.
My view is that her gender does not/should not change anything in how I supervise her or what I expect from her, the rationale being that doing so might ultimately hurt her in her post-PhD career. For this reason, I have not brought up her gender in any of our discussions. I briefly contemplated telling her that I will treat her the same way as her male peers, but did not do so because it seemed wrong (as in "of course, why is he telling me this?").
Lately I have been wondering, however, whether there are things I should do that I might not even be thinking of. Perhaps my own experience and the male-dominated environment blind me so that I do not perceive my own sexist/reverse-sexist attitudes and ultimately do not do things that I should be doing (and vice versa)? So I am interested in reading advice/views on supervising female PhD students (in male-dominated academic environments).
A few notes to address anticipated follow-up questions: Yes, I am male. I did not specify where my institution is located because I am interested in a range of opinions/comments. The agency that finances her project offers a special stipend to attend workshops/meetings for female students; I have encouraged her to attend.

"a special stipend to attend workshops/meetings for female students" - maybe rather than that (see ff524's comments), you may want to look out for research funding exclusively available to women. This kind of funding particularly appears in areas that are very male-dominated. I have seen cases where institutes that were short on money could finance some additional conference trips by tapping funding sources that are reserved to female researchers.

"The agency [...] offers a special stipend to attend workshops/meetings for female students" Do you mean a stipend for female students to attend workshops, or a stipend for attending female-only workshops? I can imagine these two situations could lead to different advice.

@David Richerby: This is of course an important distinction. I don't remember the details and don't have the documents in front of me. As far as I recall, the primary goal of the stipend is for her to attend workshops/meetings for female students but ultimately she is free to decide which workshops/meetings she attends.

Why should it matter unless she's planning a maternity leave?

"...and got the position on merit" - Would you feel it necessary to clarify that a male student got in on merit?

I'm don't think this is worth an answer, but by the time I got to grad school I was both keenly aware of being a minority and used to it -- chances are she is too. I only wanted to be treated as a student, not as some special "female student".

@whrrgarbl: I'm glad you bring this up. The only reason I mentioned it is that I wanted to make clear that (a) she is a capable student and (b) was not hired as part of any kind of affirmative action drive. I've witnessed cases in the past where female students were accepted as graduate students although more qualified male candidates were available. That's not the case here.

@novina: It should not matter and does not matter in my opinion. I thought this was clear from what I wrote. But because I'm faced with this situation for the first time, I want to make sure any potential blind spots of mine are not holding me back from doing what is right and/or needed.

I think this is a lovely and considerate question. The fact that you are already reflecting over your treatment of the girl and the current environment, says a lot already, not everyone would do this. I think you probably have nothing to worry about, and she is lucky to have you as a supervisor.

"Lately I have been wondering, however, whether there are things I should do that I might not even be thinking of." I'd recommend you take an implicit association test. There are decent ones at Harvard's Project Implicit. This can help you know about your implicit biases.

The one thing I can think to add is to be prepared so slap down less open/thoughtful folks. There may be a few very specific concerns -- different vulnerability to chemical hazards and -- as IBM found out somewhat embarassingly -- a slight difference in skin pH -- but the answer is generally that, shockingly, women are people and -- especially in a situation with possible power dynamic -- should be treated exactly as such.

In addition to the suggestions here, beware.  Be very ware.  Some students (though certainly not all or even remotely close to most; and regardless of gender) take significant umbrage at even the slightest perception of sexism.

My only advice: Always leave the door open.

My view is that her gender does not/should not change anything in how I supervise her or what I expect from her, the rationale being that doing so might ultimately hurt her in her post-PhD career. For this reason, I have not brought up her gender in any of our discussions. I briefly contemplated telling her that I will treat her the same way as her male peers, but did not do so because it seemed wrong (as in "of course, why is he telling me this?").

That is exactly the advice I would give in this situation, so congrats, you've already figured it out.

The agency that finances her project offers a special stipend to attend workshops/meetings for female students; I have encouraged her to attend.

Try not to overdo the encouragement. I get so much spam inviting me to assorted "women in engineering" events.
On a related note, you might want to watch out for the possibility that you (or your department) might have a tendency to overuse the students who are "visible" minorities (race, gender) in publicity materials and outreach events.  Some people don't mind (some even appreciate this), but some dislike being used as "poster children" to show how diverse the department is. (There's a joke in this TV episode, where the African-American doctor calls out his college for overusing him in their brochure by photoshopping him into the same picture twice.)
I'm sure people must have published studies about how female PhD students are statistically more likely to have families and be concerned about work-life balance issues, and how you have to be more supportive, etc.  But all that really just comes down to being communicative and supportive of your students, whatever their individual needs might be. For large numbers I'm sure there's a gender dimension there, but at the individual level it's just about being a good supervisor to an individual student.

@march There is plenty of committees also for male staff to serve in. Do you believe that women get diversity-related committees in addition to, or instead of other committees that a man in the same position would get?

@FedericoPoloni Based on my experience it's almost certainly in addition.

I would also add that having a poster child mentality can also grow a large amount of resentment in your other grad students as they find themselves not sent anywhere while one colleague because of their race/sex/etc goes to everything. This hampers their own professional development, which you have agreed to oversee as advisor, and so it does everybody involved a disservice. Resentment like that can grow and cause those students to some day dismiss the poster child character for only getting what she got through favoritism rather than merit, which is a stigma which never washes off.

@SimonW - too low. +10000 for last sentence!

@FedericoPoloni I suspect you're thinking about "diversity-related" too narrowly.  One of the biggest administrative burdens in a department is hiring/admissions, and what could be more diversity related? It's now often required that every such committee has a female member.   This rule exists for a reason, but it can get to be quite a burden when you have 3 hiring committees (permanent, postdoc, and graduate), and only 1 or 2 female faculty members (as many smaller math departments do).

@FedericoPoloni I recently came across some data on that. See the third figure in this article

@ff524 Thanks! Great find, these data answer my question in the most compelling way.

Although the question has arisen with increasing frequency "how do I handle said female in x (male dominated) environment?", your approach to it is not common - and it fills me with hope for the future to read how you've handled it. You're doing what so few can figure out how to do - you're not treating her differently. You're holding your concerns about what that may or may not mean at bay.
Most people do one of two things: over or under compensate, and it's my experience that in this time of growing awareness about gender imbalances in certain fields, that most people lean towards overcompensating. As a woman, I find that almost worse. When people bend over backwards to tell me how impressed they are that I'm breaking the status quo and enthusiastically express that we need to fix the gender imbalance, then do everything in their power to support me with so  much emphasis on this issue, I start to wonder if I was ever really qualified in the first place. I start to question if I succeed because of my hard work and determination or because of my anatomy. It takes the joy out of all the wins, and I frequently feel like a fraud.
One of the best examples I can provide is that I'm often approached at conferences by recruiters, and one of the first words out of their mouths are "we're looking to hire more women". Quite frankly, it's offensive. They're not looking to hire "more qualified professionals", or "persons with my particular skill set". They're looking to meet a quota, and not knowing anything about me, they still want to hire me because they can tell from a glance what my gender is.
Now I understand there are good intentions there - they want to give me the opportunity to interview. An opportunity that women haven't been given as often in the past. But at this point, I know the opportunity is out there. I know many companies will hire you even if you're less qualified BECAUSE you're a woman and they're trying to prove just how progressive and PC they are to the world to improve their image, while others are simply motivated to fix the problem, but unaware of the best way to help.
Ranting aside, this is what I would hope for, and what has always made me happy when encountered in past interactions:
Be just as tough on her as you would be with your male students. She'll come out better for it. If she's good at her job because she truly earned her education, she'll blaze a path in the field that will change the minds of those dwindling number of sexist individuals she'll encounter in the workplace by the quality of her work. She'll inspire other women to pursue their passions because her intelligence and work ethic will speak for itself.
If you cut her slack because she's a woman, you're simply raising false idols. Other men will dislike her because she's not as competent or qualified when she graduates and you'll reinforce existing sexist views, and women who wind up working with her that did climb over obstacles to get there won't respect her, and will consider her an embarrassment to the movement.
Do your part by doing nothing.
But if you see her stress, trip or begin to falter, do what you would for any other male student - check in. Mention your office hours, suggest peer study groups, and "catch up" alternate class times if you have other open spots.
If she's worthy of her degree, she'll do what it takes to succeed.
We'll catch up eventually both in numbers in the STEM community, and in raising our glass ceiling. All we ask is to have the same opportunities. Not a leg up to reach them.

Comments are not for extended discussion; a conversation on this answer has been moved to chat. For those who want to read only, here's a transcript. Feel free to continue the discussion in that chat room. (I've moved the existing comments there, but I don't have the ability to do that more than once, so additional comments from that discussion that are posted on this answer will just be deleted, not moved.)

Your second paragraph reminds me of a time when a fellow student in my undergrad cohort, who happened to be a disabled war veteran, pulled me aside and told me how impressed he was that I was studying engineering and at the top of our class, despite being a woman! In my head I was thinking "Gee, and I'm really impressed with you for going back to college and doing ok, being disabled and all! Bravo! (Do you feel condescended to yet?)" But I try to be a nice person, so I just smiled weakly.

This is exactly why I get fed up with all these people who say 'your staff should contain x number of females'. People should be let in on merit, not because of some discriminatory 'equal oportunities' system. If there aren't enough females of high merit then that's a failing elsewhere in the system.

In addition to @ff524's excellent answer, I would recommend one other important step to take: start following the blogs and/or other social media writings of some outspoken female academics.
Despite best intentions, your perspective is likely to be limited in many ways simply because you are male and not female, and our media tends to provide us with a lot more male perspectives on science than female ones (Quick: name 10 people who write about science.  How many of the people who popped into your head were male?)
Explicitly adding more female voices to your media consumption is a good way to broaden your perspective and to decrease the likelihood that you will unintentionally do something problematic in advising your student.  For a starting point, let me recommend a few semi-arbitrarily selected blogs that I find interesting:

Scicurious
Christie Wilcox
SoapboxScience
Zuska

Happy reading---and note that you can apply a similar method to broadening your perspective on other sorts of under-represented perspectives as well.

Just as a curiosity, would specifically attempting to add female sources be the best choice? Presuming you limit the number of sources you read from, (for time, cost, etc) I don't think I would be comfortable giving up what I consider high merit sources purely because of this. Although I am certain it is correct in the scope of this answer, I just wonder about the overall effect.

@Sh4d0wsPlyr Personally, I don't treat my media consumption as a zero-sum game, nor do I attempt to rank all media onto a single scale.

For those looking for more choices of reading material in this vein, see answers here, here, and here.

What exactly is a male perspective on science?  What is a female perspective on science?  How does being a male or a female influence one's perspective on chemical reactions, or the validity of the Copenhagen interpretation of quantum mechanics, or the validity of the theory of punctuated equilibria?

@DougSpoonwood Here's a nice example for you.

"The study found that male and female science faculty ranked job applicants as more hirable if their applications featured male names".  No, it didn't find any such general conclusion.  It only addressed a laboratory manager position.
" Many of the men she passed the paper to “started picking apart the study design and the flaws they saw with the paper.”"
So when a much larger and more comprehensive study which showed a hiring bias in several fields for academic tenure in favor of women by about a 2 to 1 ratio, women didn't question it?   http://www.pnas.org/content/112/17/5360.abstract

@DougSpoonwood The prosecution rests.

One thing to watch is meeting dynamics. A level of assertiveness that would be seen as a good thing in a man may be regarded shrill or angry coming from a woman. Some of us don't care, but younger, less experienced women may try to get along by softening and suppressing their opinions. That may risk getting their opinions and ideas ignored.
Famous quotes, the way a woman would have to say them during a meeting illustrates what women do when trying to express opinions safely.
All I can suggest is to watch the dynamics of e.g. group research meetings, and make sure that all of your students, including the woman, get a proper hearing when they try to say something.

Yes, I have noticed that she was too deferential in our discussions and have told her that I expect her to speak up when she disagrees with me. It has become a little better already and I am keeping an eye on it.

That article you linked to seems obnoxious and mildly offensive to me. I realize it's meant to be humorous, but it's an exaggerated stereotype that sounds like no woman I know. The actual research shows that men use assertive speech more than women to a statistically significant but negligible degree. Per this meta-analysis "Assertive speech was hypothesized to be more likely among men than women. There was a statistically significant but negligible mean effect size of d = .09 (95% CI = .02 / .15)."

@G.L. I think it is common for many new students to be a little bit scared to disagree with their supervisor at first - see e.g. How do I stop feeling intimidated by my advisor?

The point of that article isn't how women of the exact same standing would have said them. It's how they would have to say those things to not be seen negatively by listeners, when the men who actually said them were seen positively. "I have [translated them] into the phrases a woman would have to use to say them during a meeting not to be perceived as angry, threatening or (gasp!) bitchy."

I've also observed one (out of two) female colleagues being underassertive, though not necessarily in language (unlike the article).
@ff524 Metrics are proxies for the actually interesting things, and statistics summaries. Would those proxies have detected the above anecdote, or just the caricatures in the linked WP article? Does the statistics you quote say the effect size is insignificant for each case, rather than just on average? Averages matter for general actions, outliers matter for individual corrections.

@ff524 - that's an awsome find! I'm mildly curious (and this is getting offtopic), did that research correct for general personality? I'm quite assertive (some people would call worse), but that's because I developed an assertive personality, in part consciously. First half of my life I was extremely timid and NON-assertive, both due to innate geek personality, specific upbringing, and being the youngest, smallest kid in my grade in a rather rough school. BOTH levels of assertiveness was the same me, simply shaping my personality and mindset.

@ff524 - second curiosity - did the study correct for the Autism spectrum? Clearly people higher on the spectrum (IIRC, more likely to be male), are likely to APPEAR more assertive merely by having less than "nominal" level of social/emotional cue capability. Anecdotally, being on the high-functioning Asperger's end, I had to consciously train myself to LOOK HARD for when people I'm in a meeting with appearing like they're not comfortable, male or female - it simply doesn't come naturally to me like to a normal human.

Keep an eye out for signs of impostor syndrome and be prepared to counter it*. Given that you're supervising PhD students, I'll note that this really applies to all of your advisees. However, it's more prevalent among members of underrepresented groups in any given field or community.
*I'll let others provide further advice on that latter part - I don't have any special knowledge or experience there. I'm happy to accept edits on that point, upvote comments, etc.

Some advice on countering imposter syndrome in students you are supervising: have them read this :)

The fact this answer both subverts mentioning gender by referring to underrepresented groups and also provides general advice is impressive.

I agree that you should not treat her any differently than your male students, nor should you point this out to her. However, remember that her gender may affect how she is treated by others in your field (students or colleagues). If she raises concerns about sexism or harassment, above all, listen to her. Then find out how you can support her. As you probably know, Title IX applies to grad students and faculty, as well as undergrads.
You may also want to pay a little extra attention to how others interact with her in seminars, research group meetings, and other professional settings. If you see things that concern you, be an active bystander, and let her know you've got her back.

Thanks for making this important point, with which I agree completely.

Indeed, your advice is consistent with this post. I might go so far as to suggest that all people should really pay attention to the way people around them treat one another, and be actively supportive by calling out inappropriate treatment when they see it. (Not only advisors looking out for their students!)

Excellent. "Let her know you've got her back". That is good advice for any advisor, with any student. Because advisors are both teacher, and supporter. They criticize, and they praise. But in the end, they should have their student's best interest at heart - and that means being in their corner if the going gets tough.

For me as a female grad student in a male-dominated field it was and is very important to meet female role models. And I started to be that for younger students. So my 5 cents are to introduce her to successful (and nice ;-)) women in your field if you happen to know some and if you can do so in a natural way. I also tend to have very empathetic (male) collaborators, while this seems to be less of a criterion for my male colleagues when choosing their collaborators.
My experience is also that female students in such a field tend to need more encouragement (given the same potential/talent). For example I myself would never have started a PhD without the direct encouragement of my now supervisor (and now I LOVE research). The solution to this does not have to be gender-specific, I totally agree with
"But all that really just comes down to being communicative and supportive of your students, whatever their individual needs might be."

This gets at something you can be doing pretty generally, too, if you're not already - make a point of introducing your students to relevant people in the field, at any opportunity. Especially when they're applying for jobs later, that warm introduction from someone they know and presumably trust as a colleague might be the edge that gets them hired.

In addition to all of the excellent advice given in the other answers, you need to take extra care to not allow any hints of a non-professional relationship with her.
For example, as a male, if I had a female student visiting my office, I would never close my door, even if she asked. We never speak about our romantic lives, even though we can certainly chat about hobbies or the news. If I'm accompanying her to a conference, I never go to meals with her alone, even though I would do so with a single male student.
It doesn't even matter if I'm even heterosexual or not. But I'm in the position of power, and there needs to be no opportunities for even accusations of improper conduct. The stories of vulnerable women being taken advantage of by their professors, or flirtatious women winning favour the wrong way - society simply doesn't expect men to behave the same way.
Being over-cautious now can head off career-ending complaints later.

The fact such things are necessary just go to show what tragic times we live in.

I sharply disagree. The PhD student-advisor relationship inherently means that a whole lot of time is going to be spent together. Life and pursuit of a PhD have a strong likelihood of getting entangled somewhere in the years spent working on it. The advisor should establish a clear environment of appropriate boundaries and mutual trust. Students of any gender should (if they desire) be able to turn to their advisor as a mentor who knows them well that they can rely on. The suggested path of excluding certain kinds of interactions based on genders means missing opportunities to help students.

@Novelocrat Oh I know, and it's a crying shame - I certainly gained a lot from the relationship with my own supervisor. But it's part of the legal/social minefield at most institutions these days, particularly western academic ones. Unless you're so significantly tenured that you can handle the fallout, you really have to play it safe.

This is painful to read. I'm glad my supervisors didn't subscribe to that during my PhD -- as I feel I would've missed a lot of opportunities otherwise. But further, this implies that now, as a female academic I shouldn't provide those certain opportunities to my students (unless they're female, I guess, which is a minority in my field), or that I would have to chose between propriety and providing (what I believe) is a well-rounded supervision. And that's just sad.

There are lots of good points made in the other answers.  I have read them all, but didn't see this idea.  I did see "don't tell her", but I would suggest you do tell her.
The reason is that you want to learn and being male having worked exclusively with male students, you don't know what mistakes you may be making.  That is your point, and your female student could help.
If you tell your first female student she is your first, your intentions center on fairness and merit, and that she would be helping you improve by gently pointing out gender bias, she might be glad to help.  Otherwise, if she does see bias (which you missed), she could easily assume that's just how it is, as though you already know.

This is generally good, but your wording could use a fair bit of work. 2 comments to follow.

'Meritocracy' has become a very loaded term, usually with implications that claims of discrimination aren't credible. I would phrase that part along the lines of having admitted her because of an excellent track record to date, and an expectation that she'll continue to do good work.

@Novelocrat  Good point.  I replaced the loaded term, but need not take credit for your additional wording and idea.

Asking her to 'gently' point out gender bias is burdening her with making a complaint she felt necessary emotionally palatable to you. Turn that around. Make it clear to her that if she brings something up, you trust that she has a good reason. If it centers on something you do or have done, or someone you're inclined to stick up for, be prepared to process any tendency toward a defensive response on your own, or with someone else you can trust for advice. If you feel a need to ask for clarification on those events' practical or emotional impact, you should be trying to do that gently.

Thanks for editing :-). Fell free to directly incorporate suggestions as you see fit. I'm fine with sharing credit - after all, edit history is visible, and my comments are still here. I'd rather readers see the good stuff up front, rather than have to dig through the comments to piece it together. Upvotes on the comments wouldn't hurt, of course.

In anti-racism thinking, white folks have "white privilege." In this (by now somewhat dated) piece scholar Peggy McIntosh reflected on that privilege and what it means. http://nationalseedproject.org/white-privilege-unpacking-the-invisible-knapsack
There are similar reflections on what it means to enjoy male privilege. For example: http://amptoons.com/blog/the-male-privilege-checklist/
Setting aside racism and sexism can be quite difficult, especially for white guys. What's easier: becoming more aware of how race and sex can affect your own outlook.
I've asked people, alone or in groups, to read this kind of stuff. It helps get people ready for the kind of "first woman student" or "first black boss" change you are experiencing.

I understand I might have lost people wit the following answer. In short: the dream supervisor has many skills, a specific role, yet one goal: elevate the  skills of a PhD student to the level where she/he can fly away by herself/himself, despite three types of stereotypes: his/hers, yours, those from your (her/his+you) environment.
Warning: the following answer contains strong allegorical content. One can replace the two bird species by other animals, male/female, as well as other broad categories like majority/minority. This was partly inspired by:

a Gary Larson's Far Side cartoon (see below),
the French anime Wattoo Waatto super bird, whose music has been in m head during the whole vacations, and which depicts two fictional bird species (one being goose-like) to describe/critize human traits.

It helped me to   step aside the question, as done in some science-fiction or utopian texts.
First, to limit the standard gender biases and stereotypes, try to view the situation from  an other perspective: you are a duck, the field is 95% duckish, and you are supervising your  first  seagull student. Both are quite similar: they are birds, they fly and  dive, they are webbed-toed. But one common trait, though less visible at first glance, is more important to scholars: they can  travel thousands of miles (out of merit). The allegory  is about focusing on the most important traits in academia, not the obvious ones that matter most in society.
Yet, in this allegory,  some birds are more familiar than others in everyday life. And the others  are more prone to songs or poems.
So I am a duck, supervising a seagull student. The work place is 99% duckish. Ducks shake wings to other ducks, but they like to cheek kiss seagulls. There are other such "habits", that distinguish seagulls and ducks in workplaces.
So I told my seagull student: "I do not really like to shake wings with birds, cause wings get dirty (and you can get bird flu), but this is a habit. So I now ask people if they want to shake wings or else. With those who dislike that, we can agree on a different sign. What do you prefer?".
My intent is to show that seagulls can make their own rules in a duck world, slowly but firmly.
When I have changed some of my unconscious duck manners, I can observe other ducks behavior: do they behaved duckish? do I feel this may affect the seagull's feelings?
Then, observing  a specific behavior (daily comments in public about the seagull's feathers), I can tell the seagull (face to face, afterward): "I have seen this behavior, it seems duckish and misplaced to me. If you feel like this too as a bird (or a seagull in first place), may I suggest you to talk to the duck face to face, and tell it what happened, how you feel, and what you would like in the future (tools from emotional intelligence). If you do not want that here, or  cannot handle it right now, here is some help you can use: myself, or another trusty person (if possible, a senior seagull you know in HR department. Just tell it. You should also know that even 'talking about how duckish ducks can be' can  help".
On my own, I did tell a follow duck how duckish it was with the seagull, from my point of view, not involving the seagull, and told the duck  to think about it. I even had to make public comments about its feathers on a regular basis to ring the bell. It worked.
Finally, I confess a little  tern bias when I present scholar birds to the seagull (at meeting, conferences). Showing how other senior  seagulls perform in the field can be important for identification and future positions. But warning: you can learn that maybe your seagull student self-identifies as an eagle. You should adapt.
That is your duty as a bird advisor: help the bird students find their way. And for yourself: do the same with any other bird students, even ducks.

Duck and seagull carry very few stereotypes to me. Those are fictional characters, an allegory. The inspiration I had in mind was  a  Gary Larson's Far side cartoon, and Wattoo Wattoo, using birds to depict human traits. You can replace the duck/seagull pair with majority/minority, male/female..., do you believe  I should mention that?

And I strongly believe it is important to take a shift on the different points of view

I meant something akin to "trading shifts", with the acception of shift as "a slight change in position", a technique used in science-fiction stories or utopian texts, to describe or criticize a given situation without refering to the actual characters involved

So we are using bird to refer to women now? ;)

@Carsten S and ducks are? ;)

I worked and studied at a predominately male institution, both staff and students, and was involved in student services.
Every year student services (counseling and representation) would get complaints from singleton female students, that they were being treated the same as other students, without regard to gender identity.
And matching complaints from other singleton female students, that they were being treated differently from other students, on the basis of gender identity.
The complaints were with regard to the behaviour of either staff or fellow students.
These female students were always the only ones in their group, and generally the only ones in the larger department/year group. There was no socially defined common behaviour that could be referenced.
All students (both genders) were generally unaware that men and women expect different language and rights. Staff were often aware, but unequipped to handle the situation -- both from lack of experience, and because the situation was inherently unsolvable.
In an ideal world, minority students would be treated equally, not identically. That requires agreement on what "equal" treatment is.
When you have a singleton minority student that is not experienced with that situation, in a society that is not experienced with that situation, you, the staff, the majority students, and the singleton student, have no common or fixed reference framework for determining "equal treatment".
We never "solved" this problem. All we could do was offer counselling, representation, and support groups.
Because they were paid to do so, staff were always willing to adjust their behavior ("OK, this one wants to go first and be addressed differently than male students/ this one wants to be addressed the same way as other students"). Female students were sometimes able to adjust their expectations ("that's inclusiveness, not rudeness") or behavior ("if you don't tell them, they won't know"), trade student classes of 10-20 members were sometimes able to adjust their behavior when given clear and simple instructions.
But the problem would be repeated next year: singleton students didn't agree about what behavior to expect, and held opposite positions.


text:
How to contact professors as a high school student?
I am a high school student who is interested in mathematics. As such I have been emailing several professors from prominent universities. I have been running into trouble when trying to figure out what their research is from their websites (it's either way too specific and jargon-filled, or so general I can't find anything good to ask them.) Would it be a good idea to just plainly say: "I see you research 'area in math.' Would you mind telling me what specifically your research entails?"?

See http://academia.stackexchange.com/questions/47148/how-can-i-earn-a-professors-attention-if-i-am-not-his-her-student-yet

What's your end goal in emailing these professors?

Join researchgate and start asking intelligent questions. When a professor answers you, reach out to them

You should find out for yourself what their research is about. That doesn't mean that you need to understand it. But asking specific well informed questions will bring you further. At least that's how it worked for me.

Did you try to read some of their papers? If you cannot understand a single word of those than you probably do not have yet the knowledge necessary to even comprehend what their research is about (which is probably normal for an high school student vs mathematics research) so you are only bothering them.

Santiago Canez   My goal is to see if they have any recommendations on resources (books, websites, etc.) where I can learn what they are researching about.

ConanG, sending professors whose work you do not yet understand blind emails is not a good strategy to learn about what mathematicians do. I would recommend taking a phrase near something that looks interesting, and googling it to see if you can find a more accessible resource. Then ask a pointed question not to a professor directly, but at a forum (or similar) where you know people are looking to help you learn math, like on math.stackexchange.com .

@Bakuriu Having read some of the papers that mathematicians and statisticians put out, I'd say it's entirely possible to even know the general field and problem and still have no idea about what they're trying to get at without staring at the math for quite a while. Math journals are often built as archival/reference resources, not well-contextualized reads.   Other outputs, such as conference presentation slide decks, are often far more accessible.

Why "prominent universities"?  Those faculty are especially busy and especially likely to have so many strangers making demands on their time that they have to ignore all emails from strangers.  You'll have much better luck if you contact people who are nearby and who are at less prominent places.  They'll still be PhDs who know a lot more math than you do and who you can learn a lot from!

Some professors are open to interested/enthusiastic students. However, they are busy people. If you want them to spend their time with you, you have to give them a starting point that gives them something specific to start from, not some generic "tell me what you do".
Better to check out what you would be interested in (e.g. robotics, quantum physics, topology, or whatever), read up on that, and then find a friendly lecturer at a local college who covers that material. If there are none, then you could contact a prof, but be specific with your question, and do not waste their time.

As part of the reading, aim to learn enough of the jargon to understand some of the websites.

+1. The correct order is (1) learn to understand what the academics (doesn't always have to be professors) are writing (or a sufficient part of it to contribute) and (2) contact them; not the other way round. Good benchmarks: Are you able to find typos in their formulas? Are you able to ask concrete questions (i.e., "I don't understand this particular 'obvious' implication", not "I don't see the forest for the trees")?

@darijgrinberg Well, if mathematicians would have to explain all "obvious implications", they would be busy a looong time. My experience is that "obvious" implications can vary from "correct, but you figure it out how I got to that and if you don't, you do not deserve to understand", via "correct, but I am too lazy to write/think out the details" or "I thought it's correct, but, ok, add required uncritical technical assumptions to make it work" to "Oops. I thought it would work, but actually it doesn't. Hmm.".

That's why I said "particular". Not "I don't understand any single sentence in the paper.".

With a little bit of poking around the Internet, you can find videos of lectures given by prominent mathematicians freely available online. For example, here is a video of Manjul Bhargava giving his Fields Medal lecture, where he gave an explanation of his work to a general mathematical audience. As another example, the Arizona Winter School is an instructional conference for graduate students, and they have posted videos of all their lectures for a long time. Most of them are quite good.
If you just want to get an idea of what leading researchers are working on, I think that watching videos might be more enlightening (and more entertaining) than trying to read papers.
In general, please don't send unsolicited e-mails to professors -- especially if you are choosing the recipients because they (or their universities) are famous. If you develop a particular interest in, and some understanding of, a subject area in contemporary research, then it may become okay to send unsolicited e-mails in certain circumstances. Also, if you want to seek a research mentor from a local university, then e-mails might get a positive response, especially if this university is not famous, and/or if you have a math teacher who is willing to write first and say you are exceptionally talented.
One famous mathematician told me that he gets a huge number of e-mails such as yours. He feels bad ignoring them, but he gets so many that if he tried to answer all of them it would leave him no time for research.

Have a look at the chair's web site. The textual content is often outdated, but the list of publications is usually very up-to-date. You can also use academic search engines, such as citeseer or Google Scholar, to search for that professor's name. The abstracts and introductions of papers usually detail the field of research.
If available, you can also read the list of supervised student theses. These are frequently about current research topics at that chair.
Look at lecture material, slides and scripts, if they put it online. Lectures are often about the fundamentals of the research field of that chair. This way it is easier to judge whether you have the necessary foundation to understand the research topics.
If you can visit that university without too much hassle and have the time, you could also just visit a lecture by that professor. This makes it way easier to get in contact in person.

As a suggestion, when it comes to math, I would highly advise looking up other resources. A few things I could recommend:

Slide decks: How they communicate their work to peers. Or, even better, the slide decks that they use to present their work to grant sponsors who aren't necessarily experts in their field.
Websites: These should summarize their goals and general field of work, and should also be more accessible.
MS Student Theses: Masters' theses from their students will often be more accessible, since they often cover a lot of background that established experts take for granted and don't bother covering in much detail. Or, in other words, they're worse papers, but the redundant/useless information could be useful to you.
Wikis: Honestly, lots of commonly-used advanced math (at least for stats and machine learning) is on the web. While it won't show you the novel aspects that a given professor is working on, it will help fill in the baseline information. Otherwise, it would be like asking a professor who designs steering wheels what he does, but without even knowing about the existence of cars.
MOOCs: Try out EdX or other free online courses that are for introductions to advanced math that are interesting. Some of these are geared very much toward people in your position.

These are often vastly more accessible than the published papers, which tend to be for a narrow audience. For example, during grad school I once leafed through an optimization algorithm paper off and on for a few days to grasp the novelty of the approach. After a bit, I finally figured out from the math and supporting papers that the prior approach used a shrinking n-dimensional ellipse, while the new one was a shrinking rectangle.  Which was not stated outright in the text anywhere in the ~15 page manuscript. A single slide with 2D or 3D depiction of each approach would have made the concept very clear.
Finally, it seems like you would be much better off looking into high-school research experiences where you'd visit a lab for a few weeks. This would give you a much better idea about what to pay attention to.  MOOCs are also an option for this.

Regarding #1: mathematicians almost never give slide presentations to grant sponsors.

Regarding #4: Wikipedia is a surprisingly good resource for math, from undergraduate material through graduate topics and beyond. I regularly use it to learn new mathematics. (I'm a math professor.)

@TomChurch Then how do your sponsors ever communicate their findings to anyone above them? ;)  Which is a non-trivial question, because other than organizations like the NSF which have very rigid and reliable funding structures, (most?) other funding sources (defense, congressional, state, corporate) often involve different research topics competing for a shared pool of funding.  So successful or particularly interesting research is often briefed up the chain, to ensure that whole topics of research are grown or maintained each year.

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text:
How to send a research proposal to find potential PhD supervisor?
I am trying to look for a PhD position by contacting potential supervisors through email. I have made a list of professors who I found interesting through searching some papers and their department websites. Now I decide to write to them for asking opportunity and in order to show my sincerity, I would like to attach a research proposal.
I know it seems not necessary to do this if my credentials are good enough, but in order to stay out of the crowd, I don't know if this is actually a good idea to attach a research proposal. Anyway, I want to have some advice on writing a research proposal in this situation.

What should the appropriate length be? 2 pages, 20 pages? with cited reference?
How much deviation is allowed with the professor's research interest? Because if everything are the same with the current papers, it seems I am just copying its content into the proposal.
Should I include all necessary experimental steps? (I am from engineering)
Any other suggestion on writing research proposal in this situation.

I don't know if it is worth the time to do this, I would like to know if you have also some suggestions in impressing potential supervisors solely through email.

What should the appropriate length be? 2 pages, 20 pages? Maximum 2 lines in the mail body. You are vastly overestimating the patience of the average busy professor for unsolicited mail.

In most branches of engineering, sending a research proposal to a prospective PhD advisor is not particularly helpful, unless you are providing your own funding.
The reason for this is that most PhD students are funded through grants obtained by the professor, either from traditional research funding agencies (NSF/DOE/DOD/NIH and their counterparts in other countries), or through industrial contracts. In such cases, the projects that are to be worked on are well-defined, so the possibility of deviating from those projects and using the money to fund other projects—such as the one you propose—are remote.
On the other hand, if you can provide your own funding, things change significantly. Under such circumstances, you could propose a project of your own design, so long as it fits within the general scheme of the professor's existing research (or moves slightly outside of it). However, proposing a project that lies too far outside of the mainstream typically is unlikely to be well-received, since the professor won't be able to provide much useful support.
However, even under such circumstances, the initial proposal should be more like a "white paper"—a faculty member, if he or she reads such a document at all, is not going to spend more than a few minutes reading it. So the initial idea will need to be compellingly presented in a short amount of space—two or three paragraphs at most.
The best way to show your interest in a professor's group is to explain how you could contribute to ongoing research in the group—that is, do you homework before writing to the faculty member. Your email should make it clear that you are writing the specific faculty member, and addressing the concerns and interests of their group. Anything that has the whiff of being a form letter will likely be ignored, unless your CV looks like a perfect fit for the research group!

+1 for keep it short. Professors are busy and get lots of these emails.

I mostly agree, I would just like to add that "projects that are to be worked on are well-defined" may be very field and department-specific. In my experience, such projects can also be extremely vaguely defined (and intentionally written like that when the funding is applied for, to keep any options open), providing no more than a general topic of the work to be done, while the PhD supervisor actively encourages that PhD students spend as little time as possible (i.e., just as much as necessary) on concrete project tasks to avoid any restriction in research topics by the project.

I would strongly suggest not using email for your pitch until you know the professor. Use email to setup a short (make the 'short' clear in the email) meeting with the professor. Attach your CV to the email.
Think of this from the professor's viewpoint. If they give you funding and a place in their research group, they are committing to you for 3-7 years. That is a long time. Meeting in person will give them a chance to see that you can work together well.
Some professors are strict about the topic of their projects and some will go for anything. You need to ask around to see how this is for each professor. For professors with narrow topic spectrum, you'd need to show them how you could benefit what is already going on in that field and in his/her group. For professors with wide topic spectrum, come up with some topics that you'd like to work on and that are relative to that professor's area of expertise.
In the end, show the professor that you can do good research. That is really what they care about. Professors are generally good topic generators, they just need some expert researchers to do their dirty work.

Meeting in person would be the best, but many times I am looking for professors in overseas.

The proposal should not be long (1/2-2 pages), or at least should have a summary that can be read in one glance.
It should show your interest, but not be so narrow that it creates the impression that you are fixed on what you want to do. Often supervisors may have ideas which are related to what you want to do, but are better informed. If they think you have locked in on an idea, however, they may not be interested in supervising you.
Finally, if the proposal implicitly demonstrates particular skills that you have, that also may interest a potential supervisor, even if their topic is per se different.
Generally, it is a good idea, if you have a very specific supervisor in mind, to talk to them in person, or try to ask for a conversation per Skype. Don't try to do that for a generic application, academics are very busy. But, if you have a very specific topic and supervisor in mind, they may agree to that, in their own interest.

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text:
Is it appropriate to cite vulgar websites used for gathering data?
I am working on a master's thesis in natural language processing wherein I analyse various tokenisation algorithms. These algorithms keep a large fixed-size set of recognised words (more specifically, word pieces) in storage, on the order of tens to hundreds of thousands. Along the way of my analysis, I noticed in one of the non-English tokenisers I am studying that it had quite a few word pieces which could only be completed to form English pornographic terms (let's say ussy, inces, cking and so on). The reason would be that they were trained over web corpora that contain such webpages.
There exist lists of swearwords online that contain some of these words. However, there are also a bunch of words that qualify as pornographic genres (maid, POV...) that aren't inherently pornographic, were it not for the fact that they are English words appearing online in a corpus that largely consists of a different language and that has the obviously pornographic words already present in it. As further evidence, the names of some porn websites also occur in the tokeniser's vocabulary.
I find myself in a strange and slightly blush-making predicament, now: not afraid of the internet, the only place I could actually find a comprehensive list of pornographic genres and website names was, well, on websites that also host videos of those genres. Since this one experiment fits very nicely with the rest of the thesis and I find the results significant and interesting, I would like to feature it.
Proper academic methodology requires that my experiments be reproducible... but how do I cite my sources in the most appropriate way possible? I have only found one paper that speaks on this topic, which obfuscates their sourcing:

We filter out documents that have at least three types or ten tokens
from a list of words highly used in pornography.
The list was derived from the analysis of pornographic pages harvested in a previous crawl.

The lists of swearwords are all Node.js packages, so citing those is no problem. For the rest of the list, concretely, how does one cite porn.com in a scientific work, as appropriately as possible? Hyperlinking to it seems like a bad idea, and showing the URL to me seems "tasteless", although not showing the URL feels too handwavy and might raise even more eyebrows ("I use a list compiled from a variety of websites known to me").

This is at a Western-European university, so there won't be a moral inquisition if I include these results, but that doesn't mean it's not something to be nonchalant about. I want to respectful to the reader but academically precise.

"(let's say ussy, inces, cking and so on). The reason would be that they were trained over web corpora that contain such webpages." Hmm, I happen to know a French environmental activist and Star Wars fan who lives in Ussy, seriously dislikes fracking and seriously likes princess Leia... Ok, that's not quiet true, but maybe the creator of the dataset parsed a newspaper article about my imaginary friend. (Sorry, just couldn't resist. ;-) )

fussy, winces, checking, lacking and so on.

@JochenGlueck Unless there were many, many news articles that used the English words "princess", "fracking" and Ussy, I will have to disappoint your friend.

@JochenGlueck I don't know, sounds a bit sussy.

Some colleagues of mine do research on web security. They routinely scrape and refer to porn or darknet sites. I don't think they have ever seen this as problematic.

Going beyond what @EthanBolker says, even considering only the words we can assume you mean, the context is key.  It would be easy to make **cking stupid assumptions.

@EthanBolker another example (and a known old problem).

@Mew I bet there are a fair few articles mentioning baby cats, and perhaps the odd one referring to Debussy or to pussyfooting around or people being fussy… I bet there's lots of references to attacking and backing and mocking and blocking and hacking and knocking and nitpicking and… And certain newspapers are obsessed with princesses!  — Does it say more about the data set, or more about OP, that they see so many pornographic associations in it?? (Does this belong in the Psychology & Neuroscience stack?!)

@gidds I'm going to assume this is a late April Fools, but for those still confused: wouldn't you think it to be peculiar seeing a bunch of English morphemes appear as highly frequent patterns in a corpus whose texts were automatically filtered to only keep non-English texts? And would it not be especially peculiar that most of the full-length English words are unambiguously pornographic, with the partial words also overlapping with them? I'm curious why, out of all webpages on the internet, innocuous English news articles would be the ones overrepresented in the set of misclassifications.

@Mew Wouldn't names like Debussy and Princess  would be nearly as llikely to appear in non-Engish texts as in English ones?  And aren't there foreign words containing some of those seqeuences?

@gidds I know my own language pretty well, but in your honour, I consulted the whole-word count statistics I have for the corpus that was used to train the model I am investigating. incest has 17 116 occurrences, princess has 2 379. pussy has 36 249, Debussy has 4 946. For comparison, the translation of princess (which doesn't contain -inces-) has 63 606 uncapitalised and 44 648 capitalised.

Pussy is an especially problematic one to exclude because plenty of people like pussy cats.  Incest is likewise problematic because that's the non-profane term.  Just because these words can be used in a pornographic context doesn't mean they always will be.

I will also add that the reality is there are many words that are objectionable in one language but have a completely different and innocent meaning in another.  You deal with multiple languages, you'll hit them.

Citation is not the same thing as describing your methods. It sounds like you need to describe your research methods, not use citations. Those research methods may include listing URLs that you accessed to gather data.
You will want to make sure that your methods are not against the terms of service of any of those sites you used. Just because you are able to view certain content does not mean you can do whatever you want with it; some uses may fall under the concept of "fair use" or similar depending on what legal jurisdictions apply to you.
I'm not familiar with your field, but I've certainly seen popular press that makes reference to well-known pornographic websites, and they do not bother to obscure anything about their names. These are big businesses, and you'll find them referenced in newspapers and news television.
I think there is a certain level of advice that I want to give along the lines of "grow up and get over it". If your research is going to involve pornography, you're going to have to get a lot more comfortable with your research involving pornography. Urologists, gynecologists, and obstetricians can't get all giggly every time someone refers to genitals, they work there.
If you have a reasonable research question that involves pornographic language and you've used pornographic websites in work towards those questions, you need to be sufficiently explicit about it to allow someone else to recapitulate your work. That's the standard in research. Long lists might make more sense in an appendix or similar data supplement, but if you got your list of naughty words from "porn.stackexchange.com", and you think your work is rigorous enough to be published, then mentioning that your words came from "porn.stackexchange.com" should be just fine. You can try searching Google Scholar even for the specific websites you have in mind to see how others have referred to them.

I do want to note that this is only one aspect of a dozen-or-so hypotheses about tokenisers that the thesis covers; it was really an accident that this one became about pornography. If I would have noticed an overrepresentation of words that could have only originated in Star Wars scripts, then I would have investigated that instead. The field is, very generally, about parsing any text from any domain, which is rarely the websites in question.

@Mew Sure, but at least the impression I got from your post, possibly not the correct one, was that at some point you felt it was necessary to find a comprehensive list of pornographic genres and that this was important for some aspect of your research. If it wasn't important, why do it? If you want to study language in specific contexts that exclude pornography, why use a corpus that includes them?

Yes, your impression is correct, I did need such a list. All I'm saying is that I'm not writing a thesis about pornography, so the comparison to e.g. urologists gives undue weight to it. The thesis is about tokenisation -- splitting words into pieces -- and one section of it is "overrepresentation of certain parts of the internet corpus people have used to train these machines in the past". In a parallel universe, I might have asked for the best way to cite a list of medical terms instead (and the thesis wouldn't have been in medicine).

Urologists sometimes work there--they are concerned with the whole plumbing chain, not merely the emitter.

There is no room for bashfulness in research
As the other answers here point out: (a) if you require information for your research that can only come from pornographic websites, then you are going to have to source that information from pornographic websites; and (b) if you source information from pornographic websites then yes, you either need to cite those websites or at least record their use as relevant sources in the information in your methodology.  In some cases where you are sourcing large numbers of individual webpages you might just cite the general sites themselves and have supplementary materials setting out all the specific links, etc., for the data sources (as opposed to listing them in the bibliography).  In any case, the rule is that your reader should be able to track your data back to its original source to verify the accuracy of your work.
Beyond the academic requirement to show your sources, good data science practice is to save your data/sources locally if possible (within reason) and have a good system for tracking your data back to its original source.  This might even mean that you would be well advised to save some pornographic pages or search outcomes in your local data folders to ensure that you can demonstrate the source of the raw data (in cases those pages change or become unavailable later).
Here I think you have actually identified an opportunity for some useful additional research that could form a separate paper.  The predicament you describe seems to be one that many researchers examining language models would run into, and if you are correct that there is a sparsity of existing research on pornographic terms then you have a golden opportunity to be the one to do that research and write a useful paper with supplementary materials giving a list of terms that other researchers could use in the same situation you are facing.  If you were to do this then you would need to wade through some pornographic pages for the initial project, but you would save later researchers the trouble of doing this.  It would also mean that your existing language-modelling paper (and any other language-model papers in the future) could directly cite your other paper on the analysis of pornographic terms without having to cite any pornographic websites itself.

Good suggestions. I hadn't thought of saving these particular sources locally (but that folder will be a conversation-starter for sure!). The result could indeed fit in an ACL shortpaper, but considering this thread has been viewed >2500 times already, the odds of somebody plagiarising the idea are now non-zero.

ideas cannot be plagiarized, texts and work can. Don't overestimate the size of your research field and don't underestimate the head start you have because of your existing work.

The basic rule in research is that if you use it, you cite it.
So, if you use data taken from a site, you should, indeed, cite that site.
I'll guess, however, that the basic structure of your research (vulgar words) will lead people to expect that you didn't find them in "proper" places. And, those places/people that would object to such a citation will object to your work in any case, unless you avoid using those words, even if obfuscated, in publications.
And, you are using such sites not for pornographic purpose, but for analysis of language. Those sites aren't secret from the public in any case.

Do you have suggestions as to the format of the citation? As I raised in my question, it seems bad taste to hyperlink the URL, for example, lest someone actually click on it. An inline URL? A footnote without further explanation or NSFW warning? A BibTeX citation?

Not really. An active link certainly isn't required, but it needs to be specific. And any online resources need to list the date of last access, since things online change.

Not claiming that this answer is canon or anything, but, if it were me, I would go for a solution that allows me to cite/link to the resources (for verification/reproducibility purposes), without necessarily including any of the vulgar content to the paper directly.
In other words, something along the lines of what you see in websites/tv shows when you try to enter and they warn you of potentially offensive content, e.g. something like this at the end of your bibliography:

[28-35] Please note: some of the resources used for this research unavoidably contain content that may offend readers, therefore citations to these resources are provided as a separate bibliography section. Readers wishing to access this for verification and reproducibility purposes can do so here: http://link.to.some.textfile.online

(where 28-35 refers to the citation number in the text, and where you make sure to lump all the 'risky' citations under those numbers at the end of your bibliography)
Furthermore, you could probably consult the journal editor on this issue; they may have a policy on this already, or advise you of their preferred solution (e.g. a particular repository to upload your bibliography section to).

Don't
If I was doing a computer analysis of language from novels from the 1850s I would not include the list of titles in the paper itself. I would include it under supplemental material.
Since you are doing a crawl, I presume you are using a large number of websites. If there is a large list of websites then it is appropriate to not name them in the paper itself, but to just describe the websites, and include the list of domains or whatever in the supplementary material.

I'm not doing the crawl. Someone else did a crawl, then trained a model over the resulting corpus, and this model is the standard of its kind for its language.

Then I'd just direct the reader back to the someone else for the details. "We use XXX corpus gathered and used in YYY from a web crawl of pornographic web pages. For details see the supplementary material in that paper."

But I'm not the one using the corpus. Imagine you are using a language tool like ChatGPT, about which you are told that it was trained on general German text. Does it speak English? Not inherently, but you notice that any time you ask it to produce an English answer, it strings together a bunch of pornographic words each time. You hypothesise that this is due to an overrepresentation in the training data, but all you have access to are the internals of the model (and even if you have access to the training data, you want to know the fraction of the model focused on these data). That's me.

Why not? I work in econometrics. Causal inference, specifically. There are two quasi-experimental papers I've wanted to do that directly or indirectly involve PornHub. So long as your work is academic, then this shouldn't matter if the question matters. Moreover, we're all adults. So, it's okay.

Some people earned their PhD at age 17 or younger. See this. Your assumption "we're all adults" may not be valid.  I do agree with this answer, though. +1

Yep they did. I know it's invalid. I wanted to add this qualification. So, I guess 99.9% of us are adults. But yeah, either way, even if we're not all grown, we all are expected to be mature.

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text:
Two-author paper with thesis mentor, but the idea is entirely mine
I recently defended my master's thesis in artificial intelligence. Among other things, I invented a new algorithm that I would like to publish. The domain is natural language processing, with papers viewable for free on ACL Anthology.
For backstory: I developed my thesis almost entirely by myself. I only saw the professor who commissioned the proposal 4 times (which includes the final defence) as she resides in a different country, and although I had weekly meetings with my mentor (one of her PhD students), he was always behind on my research and hence he mainly helped with e.g. stylistic choices. I don't blame him for not having made deep contributions, since (1) it wasn't his thesis and (2) he wasn't as deep into the literature as I was throughout the year.
Now, although I included numerical experiments in my thesis, he correctly pointed out that my algorithm should be tested as part of a computationally heavy model using industry-standard metrics if I were to publish it in a paper. Being a PhD student, he has access to computational resources I don't as a mere alumnus. So, it made sense to let him collaborate on this paper.
We started a shared LaTeX document a while back, and unsurprisingly, the vast majority of all the text (intro, related work, theory, algorithm, discussion ...) will have been written by me, since I developed my thesis and hence I know both the algorithm and the literature thread that led up to it best. I also wrote all the code for my algorithm, because I needed it in my thesis. His contribution will be general remarks about the text, and providing me with the computational resources and interfaces to run large-scale experiments, so I expect that he will likely be writing that section.
I don't blame him at all for this distribution of the work; it is natural given the backstory. He's not freeloading, because his access to more, bigger experiments is a valuable addition.

My issue is that I want to ensure that I, a fresh graduate with zero publications, get maximal public recognition for the year-long independent work I did to reach this literary thread and this novel algorithm. If this paper is ever cited, it will be cited as Mew & Him (2023), and to be honest, it breaks my heart just seeing it that way. It is my brainchild. I rarely see a paper cited for its numerical experiments rather than the theoretical idea presented by it, and hence I lament that such a citation only seems to give me half the credit. That does feel like freeloading, even though it isn't his intention nor his fault that citations work that way. It feels like I'm selling half my credit for a single (useful and hopefully interesting) section.
He and I are are amicable, and I'd like to keep it that way. However, since my thesis was quite large (170+ pages), more than one paper can be distilled from it, and he has already made it clear that he would want co-authorship on all such papers since it is supposedly customary to give one's thesis advisor co-authorship, even though him and I both know that the content of the thesis was entirely my own doing. Whilst I respect this -- and furthermore, he did have to sit through weekly meetings with me mostly failing to articulate mathematical ideas orally -- I feel like I'm being partially robbed of making a name for myself for a unique contribution to the field. For him it seems like a closed case, and I'm not sure how to handle peddling it back. He finds my ideas valuable and has interest in them, but being interested and receiving recognition (as one of the 2 authors) are quite opposed. What should I do?
If he becomes co-author of these papers, then at the very least, I would like to somehow indicate to the reader that I was responsible for the idea and he was responsible for the experiments. Otherwise, since he already has publications, it might even seem to the reader like I am the novice freeloading off the master, and that the order of authors should secretly be reversed. How can I handle this as neutrally as possible to the reader, and communicate my desire about this to my mentor?

Perhaps I'm just insecure about lack of recognition from past experiences, or perhaps I'm insecure about possibly being a one-trick pony... but that pony still deserves proper credit for its one trick.
There is a similar thread on the site here, but quite a large emphasis is placed there in the answers on the fact that the paper has already been submitted, and also, the author is a PhD student publishing with higher-ups. In my case, the first paper has largely been written -- except for the experiments -- but has not been submitted for review, and I'm no longer a student (but might start a PhD in the near future), making my mentor moreso my colleague than my boss -- but obviously, he did have power over me when he was in charge of overseeing my thesis backed by the professor.

Edit: Apparently people are missing the part where I state that I already did my own numerical experiments to verify my work. Mea culpa, I shouldn't have made the post so long. What I contributed is the literary background, the idea, the mathematical formalisation, the formal algorithm, the practical algorithm, and the small-scale testing.
It might also be relevant to stress that the small-scale testing was intrinsic, i.e. it measured the effectiveness of the algorithm using metrics made to do exactly that. The large-scale testing would be extrinsic, i.e. measuring its effectiveness using metrics to evaluate the large-scale system, merely as a proxy for my one component. So yes, I already know my idea works, formally and empirically. The extra experiments would be just that: extra.

If you do not know whose idea it was to write the proposal, you cannot possibly know whether this other person should (ethically, not just by convention) be on the paper or not. It is difficult (and thus valuable) to identify problems that could be solved. Put bluntly, you executed someone else's plan, as almost every student does initially.

In my field it is very uncommon to have single author papers and even less common to have single author papers from students. I do not think that being the sole author would in any way increase your cerdibility or standing, rather people might wonder why a student did publish research without any of their supervisors (and many of the scenarios that spring to mind are not very positive). I feel like you have a skewed view of how publishing with co-authors is perceived. And from what it sounds like (although hard to tell for sure) the contributions of the PhD student do merit co-authorship.

You write that “it is supposedly customary to give one's thesis advisor co-authorship.” My advisor didn’t request—and likely would have refused—credit for a paper I published from a chapter of my dissertation in comp. sci. Granted, he’s a really good guy.

There is more to mentoring a student through a project than typing stuff and doing the specific work on the paper.

I've seen several posts where the author thinks too highly of coming up with an idea, say, for an experiment. Everyone should get credit for what they do, be it writing, proofreading, theorizing, experiential setup or design, or just getting lab work. Give credit precisely as it is due. Often journal have a section for detailing each author's specific role.

I'll give you the chaotic-neutral advice: add a 3rd author so it gets cited as "Mew et al" (yes, I'm joking. Although technically it'd work)

@ThomasBakx I know whose idea the proposal was: it originated as an idea for a hobby project of the PhD student. I figured out after a month of reading literature that the proposal would go nowhere, and hence the overlap between the proposal and the resulting thesis was approximately 0%. I did stick to the same field, but came up with my own topic (which is allowed and not uncommon).

tl;dr:
Remove all contributions of your co-author from your paper. What is left of your paper? no correct mathematical formalization of your idea, no testing of the algorithm, just an idea and an algorithm applying it. Treat your algorithm as an experimental apparatus. Without a rigorous formal mathematical description, you are bound to err (see this dramatic example of how dangerous is an idea alone).

My issue is that I want to ensure that I, a fresh graduate with zero
publications, get maximal public recognition for the year-long
independent work I did to reach this literary thread and this novel
algorithm.

You can show it at due time: conference and when you give a talk. But please say explicitly "I had this idea and my co-author did have to sit through weekly meetings with me mostly failing to articulate mathematical ideas orally".
It will be then clear who had the idea and who formalized it (please note: I am being a bit tongue-in-cheek).

If this paper is ever cited, it will be cited as Mew & Him
(2023), and to be honest, it breaks my heart just seeing it that way.
It is my brainchild. I rarely see a paper cited for its numerical
experiments rather than the theoretical idea presented by it, and
hence I lament that such a citation only seems to give me half the
credit.

Without the numerical experiment, your paper will be perceived like "yes, crazy idea, how did this unknown crank published it on a peer-reviewed journal without presenting serious testing, let's wait for someone to perform proper tests on it" which means no one will test it, no one will prove it, no one will cite it, maybe 2-3 years down the line some master thesis will prove it and publish and cite your precious idea.
With the numerical experiment it will be perceived like "yes, crazy good idea, this unknown person published it on a peer-reviewed journal with a good set tests, relevant, I may build on it with citation". The work can then enter in the flow of citations of your field.
The numerical large testing experiment is then necessary. Would you have done without your advisor? no. Therefore it was their idea to perform them and they deserve recognition for that, so a co-authorship seems to me relevant.
Having an idea is a necessary, but not sufficient, requirement to publish a paper.

I don't understand where you are getting the impression that I didn't formalise my idea. Communicating mathematics orally is extremely difficult because mathematics revolves around manipulating written symbols. My mentor did not formalise my ideas, I did all of that work myself; like I said, his only contribution in a paper describing, formalising and algorithmising the idea is providing access to indirect empirical verification. I already provided the direct empirical verification in my thesis because that was possible on a small scale, and it checks out.

For your TL;DR to be accurate, it would have to read: "Remove all contributions of your co-author from your paper. What is left of your paper? An idea with backing in literature, a correct mathematical formalisation of your idea, an algorithmic implementation, results from small-scale testing of the algorithm, but no large-scale high-resource tests." This is almost the polar opposite of how you wrote it.

dear OP, you wrote this: he did have to sit through weekly meetings with me mostly failing to articulate mathematical ideas orally.
Me and everyone that thought my answer is relevant understood that you were failing in articulate mathematical ideas orally. If you meant differently, then you failed in communicating it. I understood wrong? ok, my fault. Many people understood it wrongly, ok, your fault.
This is only one anedoctal point, but based on your question I invite you to think carefully about how you communicate with people:.d

I didn't mean differently. I meant it exactly as I wrote it, hence orally. Nowhere did I say that I failed to communicate them in writing. I'm not a mathematician, but I have an inkling that they too would rather have a piece of paper or a blackboard at hand to explain their ideas than to handwave, resulting in their peers failing to understand their in principle correct train of thought.

@mew why were you torturing your advisor with these weekly meeting in their format, then? Were you prohibited from bringing a paper and a piece of paper? Anyway, it looks like you can publish the paper on your own, go on and be happy!

Because the university mandated periodic updates. With a mentor in the loop, it is more difficult to slack off for those students who are inclined to do so. In any case, as I mentioned in my post, I used these one-hour meetings mostly to discuss the meta (writing style, depth, markup...). The reason why discussions about content fell flat was the same reason why the final product ended up being 177 pages long: there was a lot to be aware of -- too much to communicate orally in one meeting, and the written notes I sent to my mentor in advance were never read.

If you want a career in academia, I think you are making a serious mistake by focusing too much on a single paper, especially if you reject the contributions of a collaborator.
Long term, you are probably better off being generous than selfish about such things as they can lead to the next paper and the one after that and additional people to share ideas with, extending your field and boosting your career.
How often does a paper come along that a career is "made" based on a single paper by a single author? Even Einstein had a lot of collaborators and a difficult time starting his career. It is easy to look back on AE and forget how difficult it was for him.
Also, note that "ideas" aren't enough. It is in the verification of those ideas that value is assigned. Often said that "ideas are free", though some would disagree.

wrt to Einstein, it is worthwhile to note that some autorship of his first papers is still debated (was the wife working with him?) and plenty of people had the same ideas as Einstein:
https://en.wikipedia.org/wiki/Criticism_of_the_theory_of_relativity#Accusations_of_plagiarism_and_priority_discussions
The paper from Einstein however. although it shares the same idea as those previous paper, is the most complete and coherent formal description, maybe he missed some citations, but for sure his work is the most complete and remembered.
OP may rethink about uniqueness of ideas ...

(1) It's not a single paper, it's multiple papers. (2) It is a luxury to be generous. It's easier said than done when 100% of your net worth is in the balance. (3) I'm not asking to make a career from a single paper. I'm asking to capitalise the most possible off of it in order to maximise the opportunities to make a career afterwards. (4) As stated in my post and re-iterated in the edit, I already explicitly verified the idea.

There is such a thing as the contributions section where the contribution of each other is specified. In some journals such a section is already mandatory, exactly for the purpose to provide the reader with the information which author was responsible for what.
So asking for such a section to be added to your paper is not only reasonable, but also not that unusual.

I also did research in NLP for quite a number of years, and at least in NLP specifically, single author paper is rare, and, to cater your worry, in a two-author paper people never think "oh, the first author must be freeloading off the more capable second author".
In NLP, so far I've seen only long-term professors who have published as solo author. It's completely normal and extremely common to have two-author paper in NLP. And when that paper is good, so far I've seen that the NLP community is giving credits to the first author.
tl;dr It's fine to publish a two-author paper in NLP, first author still gets the recognition.

A professor in AI and ML here with years of experience evaluating CVs, people, reviewing papers, editing journals etc.
It is extremely rare to see single authored papers these days, unless the author stems from a theory setting. I know even within ML different corners treat authorship differently : for example in theory all others must have contributed to the idea, the development, independently if they have funded the people involved to be called co authors whereas other corners will be more generous in offering co-authorship.
Nobody will think less of you for having two authors or even three authors. To the contrary it shows your willingness to collaborate, to offer credit where credit even if tiny is due. Science is not an "I" business anymore but a team affair. Learn how to develop a family around you that can help you in the future.
Now, I am surprised that you don't mention the MSc advisor at all. Have you consulted with them? Are they happy to not be a coauthor?
In my book not adding the PhD student who helped is not fair. If you want to be truly open as to the contributions of each author you can add an author contribution paragraph or footnote.
Unless you have a very exotic last name, I wouldn't worry about how it appears in citations. In some referencing styles, it would come as a plain number.

Welcome to Academia.SE! I do think of myself as theory-oriented, hence why I'd need external support to run experiments on a supercomputer rather than my small-scale verifications. With respect to single-author papers, this one is quite recent yet renowned in NLP, cited as Kudo (2018). To answer your question: no, I have not contacted the professor under whom I did the thesis. She is acknowledged at the end for assessing the thesis from which the paper came, but she was uninvolved in any of the research (since I only saw her 3 times for the whole year).

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


text:
Would it be acceptable to write a paper in dark mode?
To those who don't know what dark mode is, it's basically using a black background, and for a paper it would mean that the background is black while the words are white.  I noticed that most papers tend to be written with a white background and black words.  I know one disadvantage of using dark mode would be that it would make it more expensive to print as the most of the printed paper would be covered in ink, but one advantage of using dark mode would be that it could reduce eyestrain on the people reading the paper as well as making it easier for a reader to go to sleep after reading the paper late at night.
So could I submit a paper in dark mode?

Why are you worried about this? Dark mode is not a property of a document but an individual viewing preference. Also, formal publication venues have strict formatting requirements that will almost certainly not allow it. If you really want to give this option and if allowed, you could upload the contents of your paper on a web page that has light text on dark background or that allows toggling between dark and light modes.

Well I’ll say it first: If this isn’t a ASE-generated trolling question it’s a damn silly-but-fun one, bless you for that. I suggest proceeding in ‘dark mode’ in the near future with the proviso that you report back here in a year on your success. This is data the rest of us would benefit from! Best of luck!

@Aruralreader OP has an active worldbuilding.se account, and apparently the imagination to go along with it…

If the publication is delivered as a .pdf, then check your pdf reader to get into dark mode instead of the document.  As an example, zathura offers the switch by Ctrl + R.  This leaves the user the liberty to choose if/when this is useful instead of imposing it and remains reversible.

Dark mode is not set by the author, it is set by the reader. That makes the question kind of moot - you can use whatever floats your boat to prepare your paper, and the reader can use whatever floats their boat to read your paper.

Well put. This raises the interesting question of whether an author’s intentional choice to set their paper in dark mode can be easily undone by a reader by setting their own reader software to dark mode. In other words, does dark mode simply invert the colors or does it do something more sophisticated?

"Dark mode is set by the reader" -- not if you're reading the print version of an article :-)


text:
Planning for a faculty position in the USA
I have a PhD in education from a US university (ranked within top 20 public universities) in 'mathematics education'. Because of my scholarship requirements, I had to come back to my country. However, I am seriously thinking about going back to the USA (or an English speaking country) within 4-5 years.
As far as I understand, publishing 2-3 peer-reviewed journal articles per year will create a good resume (in total, 15-20 articles). I will hopefully apply to 1-2 grants for my projects, too.  I am currently an educator (educating math teacher candidates) at a university in my country. When the time comes, I am planning to apply to a faculty position at an average university in the USA (preferably a research university).
What do you think about my chances to get a faculty position if I accomplish these goals? How much advantage will my diploma give me?
Do you have any recommendations to increase my chances? and What kind of universities would likely accept my application?
I know it is a little early but I want to make sufficient preparations. Thanks for your answers!

I did not vote to close... but I don't have any good advice, and I doubt that there is any genuinely good advice that can be given. Namely, the academic job market in the U.S. is currently very bad/tight, the Covid pandemic is making economics worse, and it appears not to be over... And competing with people in the U.S. with U.S. academic experience is an up-hill battle. Your U.S. PhD helps... If you can publish in journals that U.S. people publish in... you'd almost be on a level playing field. But the number of colleges and universities that are willing to consider...

... interviewing/considering international candidates who are not physically present in the U.S. (and dealing with visa issues) is not large. These comments are not an "answer", because I don't know what to recommend to have any reasonable hope of this working out for you, unfortunately. People have terrible difficulties in the academic job market when they're already here, etc. So, I'd worry about your chances, but you may as well attempt it, if that's what you want, unless there's a way that a failed attempt will upset your bosses there... Sorry, no good advice.

Thanks @paulgarrett. I don't know what the situation of job market will look like after 4-5 years but I want to work in an English speaking country anyway, preferably USA. Getting a job at a teaching-based university seems relatively easier to get an acceptance but the university must provide a rationale about why they want a foreigner. Considering tons of PhD graduates who can teach, I guess a low-ranked research-based university will be a better option in that regard.

@paulgarrett, on the contrary, I think it is very good advice, though not an answer. Times are hard, but that doesn't mean you don't try.

Check CVs of people who have the type of job you want.  I suspect you will find most education faculty in the USA have experience teaching in primary or secondary schools in the USA.

"competing with people in the U.S. with U.S. academic experience is an up-hill battle." Could you explain why? I was considering taking a postdoc overseas but since I want to ultimately live in the US maybe I should reconsider.


text:
How to use the IMRAD paper structure correctly?
I am a little confused about the following structure which is now demanded by many journals: Introduction, Methods, Results and Discussion (IMRAD).
It seems difficult to use. For example, equations. If I write some equation stuff, showing the derivation of a formula from the motivation to the goal, this is not compatible with either the Methods section (what I am doing) or the Results section (what have I found). The derivation of equation is both, it shows the way how to get the results, you can not simply divide this into what I have done and what have I found. How should I include these?
I think I am more in line with older paper style, that does not bother about a specific structure.
Also, what about multiple experiments? Should I really use "method A, method B, method C" and then "result A, result B, result C" for the experiments A, B, C? This completely destroys the reading flow.

Yes, they actually demand it as far as I can tell.

So, IMRAD is for experimental research.  Not for mathematical research.  Nor for other, similar, research.

tl;dr: Make IMRaD per-experiment/section, not overall, with an overall introduction and conclusion/discussion.
I think you are overly strict in your interpretation. The form given is for papers with a simpler structure in which there is a single methodology leading to a single result. Putting a lot of separate methodology "sections" at the beginning makes no sense to a reader and complicates understanding. It would also be contrary to the stated purpose of IMRaD, which is to follow the normal process of experimental science.
One solution is to split the paper in to several so that it is easier to achieve the form. That makes sense for a lot of work.
But if the various experiments need to be collected together in a singe paper, then a section of the paper for each experiment can follow the form, rather than the overall paper. That is to say IMRaD is per section, not for the paper as a whole. Or per-experiment, if you like, which is the intent of it all.
Still better, perhaps, but depending on the work, is a single introduction for the whole and a final discussion bringing it all together, with the sections independently discussing individual research question/hypothesis, methodology, results, and conclusions.
Also, don't forget that you need to say something about the execution of the methodology for each individual hypothesis.
See the caveats here.


text:
Do I have a right to ask for co-authorship for the projects that I helped in fieldworks knowing the professor is not willing to provide it?
I have a question. I am a master's student and I worked on several projects while I was working on my master's project. Those were beyond assistantship duties. I helped in every step of implementing the sensors in the field for one year. I collected the data for them. They are not putting my name on it. For another project, I helped analyze the data and a lot of field works for two years. They haven't finished the project yet but I guess I will not get the authorship. Do I have a right to ask for co-authorship knowing the professor is not willing to provide it?

Yes, you have the right to ask, but you may or may not have the right of authorship. If the intellectual content, the ideas, come from others, and you work at their direction then acknowledgment is appropriate, but probably not authorship.
But if you know that the professor is unwilling to provide it, I wonder whether you help or hurt yourself by even asking. It might be worth it in a clear case, but not so much in a marginal one.
Authorship is about the ideas, the intellectual content, not about the "effort".

Just wanted to add: we work with various sensors all the time and even have a couple of engineering teams for that; just deploying off-the-shelf solutions surely does not constitute "ideas/intellectual content", even when some difficulties are encountered. But it is usually reasonable to recognize a student who say took a RPi and wrote some code for it as a proper coauthor. This depends on the OP's situation, of course. "Helped analyze the data" is an even bigger deal, long as this help was a cut above a data entry job.


text:
Why are my referenced papers not identified by Semantic Scholar and ResearchGate?
My paper lists 83 articles in the reference section. However, Semantic Scholar only identifies 5 of them. One of the 5 identified references, Jae S. Lim (1986), does not even appear in my article. ResearchGate only identifies 4 references. There is only Prophy that is successfully parsing all my references.
I'm so confused. I'd appreciate it if someone could help me to get my reference identified by Semantic Scholar and ResearchGate.

While the question is somewhat different, I think this answer https://academia.stackexchange.com/a/173339/69838 also answers your question.

As far as I understand it, Researchgate only identifies (and links) references that are also on Researchgate.

You can report issues to semantic scholar here, under the bibliographic data section: https://arxiv.org/abs/2109.13731

Well, there is clearly some cutting edge ML at work here.