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How to speed up the writing process?
I am the parent of an amazing and brilliant child who is also autistic / ADHD.  They are currently in college at Stanford, majoring in physics and are a first gen college student.
Writing has always been a struggle for my kiddo.  Not the knowledge part or the research part - but the ability to take all the information they have gathered and put into outline form and be able to actually turn it into narrative form for papers.  I personally believe that this is due to the "black and white", "right or wrong" way their brain functions.  With physics (math, science, etc) there is a right answer.  You get to the right answer and you're done.  Writing doesn't work that way, so they get stuck in the mud.
What they write is amazing (and even award-winning), but the amount of time that it takes them to put it all together just isn't working for college classes.  I know there have got to be tools that can help or tutors or something, but I just don't know where to start to help them get the tools they need.
Any guidance, references, referrals... anything would be greatly appreciated.

I would think that a counsellor trained in the specifics of autism etc. would be a better source of answers and finding a solution.  I worry that a general or AI "solution" would provide "answers" that kiddo would find it hard to evaluate, leading them astray. I suggest you seek a solution elsewhere. One solution I'd suggest, however, would be collaboration with those who aren't neurodivergent.

Writing is hard for many students, autism or no, ADHD or no. Universities I have attended had programs specifically for writing help, like a "writing center". I'd highly recommend your child look into writing programs at Stanford  rather than trying to do it all yourself. I would separately look at support specifically for students with autism or ADHD at Stanford: https://studentlearning.stanford.edu/neurodiversity Excellent institutions like Stanford are in part excellent because they have a lot of support programs for students.

Keep in mind that writing in humanities classes that your child will have to take to satisfy general Ed requirements is very different from writing in science (including math) classes. Does your child have trouble with former, or later or both?

With more advanced science the answers are nuanced, there isn't a strictly right answer (even for something as pure as maths). When you talk about research papers, do you mean academic research papers for journals or essays for classes? I suspect part of my confusion is due to the American system being unique with required non-specialist courses, the course I took that was least like physics during my physics undergrad was high performance computing. For general writing: "The sense of style" by pinker might be good, it goes over why we write the way we do, might illuminate assumed knowledge.

On a positive note, some neurodivergent people do well in academia. I know a few of them who are on the spectrum. They have, however, trained themselves to "seem" otherwise. But they have a great ability to focus and concentrate. They don't depend on "tools", however.

Thank you all for taking time and giving me input!
The class is this: GEOLPHYS 219 Planetary Surface Processes Shaping the Landscape of the Solar System
@MoisheKohan - they have completed all their core classes, the ones they're in now are 4th year level courses that are very specific to their degree.  I believe they call it a Science Research Paper. (?)

@BryanKrause - THANKS!  I will definitely get that information to them.  They are set up with OEA (I'm still surprised they can't give more guidance).  I think the writing center would be an amazing option!

Has your child been diagnosed by a clinician?

@Buffy: there may be a survivorship bias with your neurodivergent collaboration partners. I have to say that I'm not aware of particular tools as being actually very helpful with autism. (Except maybe things like lowering monitor contrast - which you may not count as tool. But I'd be happy to be corrected.) But assuming that no such tools are  widely used (since a long time), then of course only neurodivergent researchers who managed to cope without tools throughout their studies and professional life can be your collaborators. If there were others, they likely (and silently) dropped out: IIRC

the proportion of autists with normal or high intelligence that have (at least over here in Germany) an academic degree is higher than the corresponding proportion of the general population. Nevertheless, only 15 % are in full-time jobs. While STEM in academia may be more accommodating or suitable than other fields or industry, my guesstimate would still be that quite some did drop out.

Did you effectively disclose your child's identity and personal medical information on SE or did you use a pseudonym? ... and no, don't answer that question here.

First of all, I am a mathematician, not a physicist. However, some of the issues you are describing are common to both disciplines. The reality is that nobody (to the best of my knowledge) teaches how to write research papers or, more precisely, given the situation that you described, survey papers. The way it is usually done is that students are given several papers to read; some of these are original research papers, some are survey papers. Then students are expected to imitate the general structure that they see in the written materials to produce their own work. These materials are typically given to students by their instructors (in the case when it is a written assignment in a class) or advisors (in the case of a Master or PhD thesis). Make sure your child has access to several such papers. If not, your child should contact the instructor/advisor and ask for the materials. This might not be enough, but that's a start. If these samples are not enough, look at the list of references in the given materials and make sure your child looks at the review papers in that list. (It take some skill to identify which are review papers and which are original research articles.) The way I usually do it in the classes I teach (but I mke such assignments only in graduate classes) is to tell students that I expect them to write in their own words a description of the results in the assigned papers; I tell them the expected length of the work (about 2 pages). I also tell students to come to my office hours to discuss these assignments in case something is unclear.
Hope, it helps.

My understanding of in particular autism is that the imitation part may not work for them as is works for other students. Thus, going through papers of the kind and style that is requested is IMHO worth trying, but I wouldn't put too high expectations on it working.

First of all, your child sounds truly inspirational - to have autism/ADHD is challenging at university, so to also be a first generation student to go to university, and to go to one of the top in the whole World is an amazing achievement.
From the point of view as a mathematician, writing is something which the majority of early research mathematicians struggle with. One could speculate why - I suspect that it is partly to do with transitioning over from writing solutions and ideas for only yourself, to writing as a form of communication to others. It's a learning process which never stops, and we hope improves throughout our lifetime. Please take my suggestions with a pinch of salt as these are tips which work for me, but your child will need to find what works for them.
My first suggestion is to read physics which is well-written. For example, I often look to who are considered the greatest communicators of maths, like Milnor. For physics, I suggest Paul Dirac's writing. Whilst I haven't read all of his work, I read his paper on singularities in the electromagnetic field which I consider a great piece of scientific communication. It gave a sense of Dirac teaching you and guiding you through each step to get you on the same page as him. Search for various other examples and see what can be learnt. Stephen King once said 'If you don't have time to read, you don't have time to write' which seems applicable to writing in general.
Second, I strongly recommend breaking writing up into sections. For example, when I have written a research paper or dissertation, I don't sit down and write it out in one go. It usually involves several small problem which one works on and then aims to put it together into a piece of writing at the end. When I consider these individual problems, I try to flesh out my writing even at this stage. Don't just write workings, explain the steps. This means that when it comes to writing up into a cohesive piece, it will be far easier.
Third, if time constraints is an issue, then having a good timetable is very important. It makes a task which seems overwhelming much more doable. For example, if you have a piece of writing due in a fortnight, then split this up into small daily tasks, leaving the final few for reviewing and refining.
Also, don't be afraid to reach out to the university. My experience is that they understand scientific writing is hard, and have specialist support on hand to help with this. For example, I have seen universities before where literature students proofread science dissertations, not to check the content, but to check the readability. Plus, if enough people share that scientific writing is something they are struggling with, the university may have sufficient numbers to organise some sort of workshop.
And importantly, here are some resources which are much more knowledgable than myself:

A useful Stack Exchange post: https://physics.stackexchange.com/questions/27675/how-to-write-a-paper-in-physics

An article by N. David Mermin at Cornell: http://mermin.lassp.cornell.edu/KnightLecture.html

A paper by Igor Pac with tips on writing mathematics papers from a modern perspective: https://www.math.ucla.edu/~pak/papers/how-to-write1.pdf

Terrance Tao's blog post on writing, which has lots of links to other resourcesL https://terrytao.wordpress.com/advice-on-writing-papers/

These are all good suggestions as to how to write better, but the question is about writing faster.

@Arno Thank you for the comment, you're right I should have targeted my suggestions to be more about writing faster. To me, however, if I can write well and get a feel for what scientific writing is, then it speeds up my writing process because I'm not having to stop and start so much. But your feedback is well taken.

THANK YOU so much!!!!

Other answers have explained that the writing part is hard for almost every (STEM) student.
However, my understanding of autism suggest that there are several points that may need to be considered separately from a high level of the usual struggles.
General considerations
For the what-can-be-done parts I assume that kiddo has a proper medical diagnosis which is (or can be) registered with either the exam office or a disability office of the university (the exam office should be able to guide kiddo wherever else they need to go).
Still, it is up to kiddo to decide whether they want to communicate their condition at all. Doing so certainly has drawbacks as well, and a good overall strategy will depend on details that should not be written publicly in the internet.

Lots of thoughts I have require negotiating. While this likely poses difficulties in itself related to the autism (and possibly also the ADHD), I'd say the ability to negotiate appropriate working conditions is an even far more important professional skill for them than scientific writing.

Talk to the exam and/or disability office of the university.
Autism + ADHD is not a rare condition. AFAIK, ADHD has a prevalence in the order of magnitude of 1 in 10, autism 1 in 100 in the general population. Also they frequently co-occur (1 in 3 people on the autism spectrum also have ADHD). This means that exam/disability offices should have experience even with the particular combination of autism + ADHD. This makes them a very valuable source of information about what has helped others (or also what did not work), and of course they know what are acceptable accommodations and what would constitute an unfair advantage.

Find out exactly what knowledge and abilities are to be graded.
I suspect that the ability to wrote a scientific essay paper is part of these, but there may be sufficient other goals which are much less problematic for kiddo: subject knowledge, being able to apply the subject knowledge to new problems, being able to learn a new research topic on their own from a literature search, ....
It also may turn out that the paper-writing in itself does not rank that high in the instructors teaching goals and that it is for them mainly a convenient way of evaluation.
Once this is known, it may become possible to negotiate for accommodations that allow a fair evaluation of the relevant professional abilities. E.g., an oral exam may evaluate all points except the writing part. (As difficult as oral communication may be, it has the important advantage that misunderstandings and ambiguities may be spotted and corrected during the exam, either by kiddo or the examiner.)
It may also be possible with the help of the exam/disability office to decide that kiddo goes for a particular scientific writing course with grading on this (and thus avoid a statement that they were exempted from essay writing on their final degree), but for the scientific subject courses some form of evaluation is chosen that is more suitable.

ADHD
I have less knowledge about ADHD than about autism. That being said, I'd expect the consequence of the ADHD to be mainly inability to concentrate over sufficiently long times on a given (and uninteresting) task. Possible accommodations to ask/negotiate for may be:

Asking for a topic that is inherently interesting for kiddo. Including suggesting topics to the instructor so they can decide which would be acceptable for the course.
Getting more time, which is also an accommodation in line with the autistic needs.
There may be other accommodations such as working through the topic with a tutor who keeps kiddo from straying away with their thoughts but does not interfere with the topic-related output kiddo produces.

The first one may be negotiated with the instructor without involving exam or disability office. The latter 2 are a level of accommodation that an instructor likely cannot agree on on their own, but a disability office may decide that this is appropriate.
Specific points related to autism

Literal* understanding of language is typical for autistic people. If the task is not very precisely and unambiguously worded and explained, kiddo may spend lots of time trying to guess (i.e., thinking what may be meant and evaluating likelihood for each possibility), and maybe even writing the essay/paper to cover many possibilities.
However, IMHO asking for precise, clear and unambiguous task statement is not an accommodation since it is also better for the neurotypical students. But their guesses of what is meant are likely closer to what the instructor had in mind.

Learning from example/do-as-I-do without spelled-out explanations may not work for autistic people.
(As others have noted, it is hard also for neurotypical students. But for them it is doable, while it may not be possible for autistic students. See next point for reasons.)

I think it is worth while to put a limited amount of time and effort into getting a selection of good example papers, including good answer texts/essays/papers from previous years: kiddo may ask the instructor whether this is acceptable considering the course rules, and if so, whether instructor could please put them into contact with students who handed in very well-done solutions to previous survey topics. (Where I am, a new list of current topics to do the literature search and essay paper on is handed out every year.)

If that doesn't turn out to help, ask for specific explanations of how exactly to write. (I'm only medium optimistic that this will produce a useable result, but it is certainly worth trying.)
Personally, I think a reputable tertiary level education institution should be able to explain scientific writing in an understandable fashion. (Lately I've noticed improvements in courses about scientific writing explaining working techniques and tools that one may use.)

Discuss with instructor and exam/disability office what accommodations are appropriate. E.g.,

A literature search yielding a literature list may be graded separately from the essay paper writing part.
Result presentation format may be adapted. E.g. putting the results into a table with systematic evaluation and/or bullet point lists rather than an essay-style text may be acceptable. (If kiddo can summarize and evaluate each paper for a set of characteristics but has difficulties expressing the knowledge in sentences.)
Or a review that gives a very detailed, comprehensive and systematic compilation of the literature. (There are scientific review papers in such style)

Focus on details: Autistic people often take in huge amounts of detail, but may not be able to detect the underlying high-level structure. (My mental model is: detecting low or mid-level structure so strongly that this masks higher level structure)
I think the saying "not to see the forest for the trees" is a good description, in a literal way.
For people without this trait (instructor), this may be such a strange notion that they cannot even imagine how this would be.
In this sense, this particular trait of autism may cause a dis-ability (again, literally: lack of ability) to fulfil a "summarize knowledge gathered from the survey" task in the curriculum.
If this happens to be the main problem, it unfortunately means that the autism interferes with a very central professional ability required in STEM. Which does not mean that kiddo cannot find a professional niche where they excel. But it does mean that the course likely grades something that kiddo cannot deliver. Getting accommodation will need to involve the exam/disability office.

Focus on details together with what OP describes as black/white thinking: There may be a related, but different and lesser problem: Inability to produce rough or approximate summaries. If something is not exactly and precisely correct, it is strictly speaking not correct. In consequence, it may be difficult to express (write, say, state) it. There may be a feeling of writing falsehoods for sentences that would perfectly satisfy the correctness requirements of the instructor.
For kiddo:

Neurotypical teachers may work in a way that they omit spelling out approximations as such. When meeting statements that are false because some rare contradicting special cases exist, check whether an approximation is meant.
In addition, neurotypical teachers may expect summaries that make such approximations. This can be hard to do in itself (previous point). But if a statement is false because of a small number of contradictory findings, perfectly true and precise statements are possible: e.g., most of the findings are that ..., while a few contradict. Or: 17 out of 18 papers [Lit1 - Lit17] found that .... [Lit18] instead found .... Such statements are fine for a scientific essay.

Time requirements:  Both autism and ADHD can mean that kiddo will require more time than other students. (For the autism-related part, this additional time will also lead to vastly more detail knowledge than faster students will have.)  Giving more time to complete tasks is a common accommodation which the exam/disability office (or the instructor) can grant.
Studying part time, i.e., taking fewer courses than usual at a time may be something that kiddo can do without the need of anyone knowing their condition.

What they write is amazing (and even award-winning)

If one needs to surpass a given threshold (= passing the course), the aim is threshold + safety margin related to uncertainty. Now if the uncertainty is huge, predictably passing requires to aim very high.
Autism may cause an inability to judge what the expectation is, so much larger uncertainty than neurotypical students experience. Plus, the autism may cause an increased need for predictability. Which would call for even larger safety margin.
Kiddo lowering their standard (as some other answer suggests) may thus not be a feasible option.
OTOH, some of the writing techniques I've met in a scientific writing course deliberately aim at a rough draft which is completed before parts or sentences are refined in several rounds. If this is a feasible working technique for kiddo, a possible accommodation would be to show the intermediate stages either to the instructor or to a tutor, and stop and hand in as soon as they say it is fine.

I'm not sure whether producing the correct style of writing is a particular problem related to autism. (I'd expect it to be less problematic than the other points once the rules for the desired scientific style are known.)
But here are some bits and pieces of advise I've gathered over time. Fortunately, they suggest that there are rules that one can follow, and the actual rules may even be nice for autistic people (compared to the rules of literary writing): The essay-writing training I had was - like for all my peers - in language/literature courses in school, plus the training one gets from applying this in social science subjects. (I once had a German teacher who said that handing in 2 pages of answer when everyone else produces 8 - 15 pages is actually better if those 2 pages contain the same information.) Natural science in school asked questions where at most putting facts and logics into sentences was required. When I wrote my first papers, my prof taught me: we're in science here, not in literature. Plus we expect that for the readers (like for us), English not to be their native language. Thus, stick to short, easy, precise sentences. Do not use synonyms but stick to one term and use it in an exact and precise fashion. Also spell out this definition. (My native language favours long sentences. Heavy switching between synonym use is taught as a must in school.)

Generative AI: although its use is typically forbidden in study context, the exam/disability office could allow also this as accommodation if they think it appropriate.
That being said, I'm unsure whether it would help: while I could e.g. imagine a very long and detailed draft text by kiddo could be AI summarized into something of a suitable length for handing in, I'd also expect that the result is distastefully blah-blah and imprecise to an autistic mind.
(I expect logics to be less of a problem, since I expect an autistic user to closely stick to the requirement of personally verifying the correctness of the generated text, and an autistic physics student to spot any logical flaws immediately).

Side note about strategical decisions: I've been in a discussion lately at my professional society where we were thinking about how to deal with one's own strengths and weaknesses.
We compared focusing effort on improving the strengths to reach excellence (we called it "American-style") to focusing effort on getting rid of weaknesses ("German-style"). Both are useful, and sometimes weaknesses are so important that something needs to be done for sheer survival. Kiddo likely has put quite some effort into such topics. Otherwise, putting effort into things that one can do well is very rewarding, both mentally/psychologically and in terms of what can be achieved. It is IMHO important not to forget this.
What can and IMHO should be done as well is to look which specializations/niches exist in the professional world that suit well to one's abilities.
People on this SX tend to emphasize how important paper writing is - which is true for their daily work in academia. But niches and positions requiring more thinking and less from-scratch-writing than others do exist. So do niches where the importance less the sheer amount of output, but its precision and correctness.
While predictions are difficult, in particular about the future, I expect that during kiddo's professional life, generative AI tools will be available that are actually helpful at transforming thoughts as expressed natively by an autist into neurotypical scientific language (and the other way round as well). So it may be totally worth while to get through strenuous study requirements now, and later use tools that make every-day work easier.

* unfortunately, "literally" is sometimes used to refer to a figurative meaning (As in "literatlly speaking, ..." where ... is meant in a figurative way).
I'd therefore like to clarify: I use literally exclusively refering to the direct meaning of the wording. That is, as the opposite of figuratively.

For someone in the STEM fields, one mental tip I have run across for dealing with the forest for trees problem: Look to abstraction and modeling. Is Newtonian physics wrong because it doesn't have the detail of Einsteinian relativity? Is basic arithmetic inferior to module theory? Having this conversation and exploring the idea that you can have models at multiple layers, that are 'good enough for the context'. Explicitly approximate rather than implicitly approximate maybe an acceptable compromise rather than trying to cover all the detail.

Also understand this may require a multistage process of building the mid level structure and then the high level from that. Something which unfortunately takes a lot more time and mental energy and is more vulnerable to being disrupted by learning about a subtle misunderstanding.

Oh my heck - thank you ALL so much!!!  I can't tell you how much I appreciate the information.

There is no way, I'm afraid, to speed up the writing process and still have high quality. It is a hard task.
To obtain high quality of output, for many people, maybe most at the early stages, is to get feedback on whatever you write. It is astonishingly difficult to evaluate your own work. Even proofreading for your own spelling errors is very hard. The problem is that the eyes see what you think you wrote on the page, not what you did write, so you skip over fairly obvious errors. Even "sophisticated" spell checkers can mislead you when they insert the wrong word.
For some who are neurodivergent it may be even more difficult to obtain that feedback, as some have communication issues, making it hard to find those willing and able to provide adequate feedback. Stanford might actually be a good place to find support for that.
There is also the issue, for a student, that obtaining feedback from other students might be against the rules. However, if a professor is made aware of the issues they might be able to provide some assistance. One option is to have a grad student give your kiddo feedback on their writing.
Like any skill, writing takes practice. In a complex field, it isn't a natural skill for most. That means repetition and feedback, perhaps for a long while, until it begins to feel natural.
I mentioned that I have friends (and co-authors) who are somewhat neurodivergent, but have succeeded (beyond myself, actually). One of them has his doctorate from Stanford. He is still occasionally painful to communicate with, but he does excellent and widely regarded work. He also suffered some setbacks along the way but overcame them with hard work. He is a marvelous writer.
And, a warning: having "tools" isn't going to ease the task if excellence is the goal. What "tools" will make you a world-class tennis player? The best tool is probably a coach who gives feedback on your obsessive practice.
A visitor to the city asks a native New Yorker "How do I get to Carnegie Hall". The answer is and has always been: "Practice, practice, practice."

Since comments often disappear, let me repeat Bryan Krause's link to Stanford's support: https://studentlearning.stanford.edu/neurodiversity

One thing that may be worthwhile for someone with autism: having someone who can help understand what feedback means and how to ask for it. This is where an autistic counsellor could help. Coaching given by neurotypicals isn't always easy to interpret by those on the spectrum,  and is something that may need support in its own right.

+1 for general acknowledgement that writing is hard and that practice helps - with the autism focused addition to get relevant required tutoring/feedback (and the Stanford link). Nevertheless, I'd like to disagree on the tools. On the one hand, appropriate use of tools is IMHO part of mastering one's profession. On the other hand, if there exist tools that help to overcome the specific autistic disabilities IMHO they should be used. Like a legasthenic student should use a spell-checker, someone with ADHD should take their medication, use alarm-clock and automatic calendar reminders, etc.

Producing excellent academic writing quickly just isn't a realistic goal for almost anyone. Experience can help getting faster, but that's not really applicable here. I suspect that what your child needs to do is to lower their standards for college coursework and just produce good enough stuff. The first big hurdle towards that probably is to give themselves permission to skip their own quality control process.
As far as writing tools are concerned, we've got spell checkers (very useful, can probably taken for granted), grammar/style checkers and generative AI tools. Grammar/style checkers can be useful for someone struggling with low-level language stuff, in particular if they are still learning the language they write in. I don't think they can do much to speed up writing for someone who isn't struggling with these things. Generative AI can massively speed up writing, but on the one hand is typically forbidden in a university context, and on the other hand tends to produce rather mediocre results. Gen AI output tends to look good at a first glance, but just lacks coherent logical structures.

Hmmm. Lower standards??

@Buffy Yes, lower standards. We are talking about coursework here.

Let me disagree, then.

I'm not sure the traits that cause autistic writing to be slow but meticulous allow them to lower the standard in the way appear to think. But it is certainly worth considering.


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What options one has to fight the injustice of authorship credit denial?
A graduate student left a research group after creating a novel method, and proving it for the first time. She wrote all of the code for this, and has many presentations, plots, and tested data samples proving contributions. Her work was presented at two collaboration meetings before they left, and the student was poised to be first author on a paper in the top journal in her field regarding the work. Upon leaving the group, she had an agreement with the PI to finish out this work and train incoming students on how to take over the project.
However, directly after leaving the group, the PI then withdrew this agreement, and did not allow her to finish the work. The PI rewrote the code, although it accomplishes the same method that the student created. The student has evidence of all of this.
This work was then published in the top journal in her field, without her name on the author list.
The student has talked to a few trusted professors in the field, who all agree that this was retaliation for her leaving the research group. However, due to the power dynamics between graduate students and PIs, she fears that  pursuing this publicly will damage her reputation at the moment.
Evidence of Authorship

plots proving that she made driving contributions to 1/3rd of the figures published
correspondences with the PI proving that she was prevented from finishing out her work
GitHub histories and code accomplishing the original idea that was published

Open Questions

Is the PI correct that the students name should not be on the paper, given that the code was rewritten?
The student, also, was not given the chance to contribute to the manuscript, despite her ideas and research being core components of the paper. Should her name still be on the author list, even though she did not contribute to the manuscript?
Please recommend what the best course of action is for the students future career?

I've voted to close this as the main question (Do I have a strong case here?) is impossible to answer at a distance, since we only see what you have written. You have options, but the outcome could be anything from something satisfactory to you to a lawsuit or being labelled as a crank. You need professional advice and probably supporters/advocates.

What domain is this? The customs for authorship vary wildly, from having-written-some-code-used-for-results-in-paper to having-written-substantial-part-of-paper-prose.

But, if what you say is true, and I don't doubt you, then you have been done an injustice.

What precisely has this ex-advisor told you when you met to reconcile the situation? The additional info is important.

Why did you leave the group?

No matter what else: if the idea stems from OP, what these guys did is plagiarism, plain and simple. Even if they rewrote code, that may give them copyright, but does not change the origin of ideas. As to how to proceed to safeguard your future career, that's a different matter, and there are some relevant answers. The facts remain that OP should be at the very least co-author if not first one.

I suspect that they are minimizing the extent of your contributions, and you are underestimating the negative impact of your quitting and the amount of work still to be done on the project when you left it: that seems to be the natural process of things in these situations. Even now you're only claiming ownership over 1/3rd of the figures.
I understand there was some agreement, but also you left, seemingly by your decision. I think it's not reasonable to expect that you would be as efficient working on this project before leaving as after, and hard to predict whether you would actually see it to completion, so I can very much understand your former advisor wanting to pass the project off to someone else.
That said, authorship is at least as much about ideas and approaches as it is about physical products like code, data, and words written. I think most likely you were treated unfairly and should have been offered authorship even if much of the work was redone after you left. Your advisor should have probably had another discussion with you about passing the project off that would have involved acknowledging you would no longer be a "first" author but could be a contributing author for the work you had already done at that point.
If the institution cares about these things, you could submit a complaint to them about academic misconduct; each institution will have their own procedure and initial point of contact for that procedure. But, ultimately, it's unlikely to benefit you all that much. If you're successful, probably the professor will have some admonishment placed on their record. The paper may be retracted. Neither of those things are something for you to place on your CV. There's a distant possibility the paper could be re-submitted with you as an author, but that would require cooperation with a bunch of people you will have just seriously angered: I wouldn't bet on it, and if it were it's not going to be in the same journal, and you're not going to be first author because you only contributed to at most 1/3rd of the paper.
Maybe it's worth it just to "stick it" to the boss who mistreated you, but there is also likely to be collateral damage to other students who took over the project after you left and likely were not involved in the decision to leave you off the paper.
It's also possible the institution won't want all that mess and they'll find against your complaint when given any shred of doubt in evidence and not wanting to wade deeply into technical details outside the expertise of the judging committee: it's bad press for the institution, they likely feel more beholden to the professor than you however independent the disciplinary process is meant to be.
I have to say, it's deeply unsatisfying writing this answer. I want to say that there is a way to make things fair, but often unfortunately there really is not, and yes, this does let some people get away with things who choose to take advantage. Perhaps for a serial offender some of the balance shifts. Overall, for authorship it is much easier to make things right earlier in the process; waiting until after a publication is out there in a good venue is just too late. I understand that in these circumstances you likely just weren't involved closely enough to be aware what was happening but also, that kind of hurts your case: a lot of work was done to get this paper published after you stopped working on it. Your contributions were important, but you didn't do the whole thing. In my experience it's common for the last 5% of a paper to take at least as much work as the first 50%. Hopefully you'll find some further work to do that interests you and can get proper credit for bringing that work to completion.

This is a good answer, but in this case OP has lots of evidence to back up their claims, so there is a reasonable chance the institution's complaint procedure will work properly and things will be made fair. And if I was a student who took over the project after OP left, I would not be angry at OP at all for making a formal complaint. When the PI decided to exclude OP, I might even have strongly objected to this. So the PI will be seriously angered but the other authors might not be.

This is a good answer, but I don't really see the need for so much emphasis on the point in the first two paragraphs. Yes, having someone leave might cause all sorts of problems the OP might not be aware of, but so what? It's still misconduct to cut them out of the authorship, the circumstances don't offset that at all.

@N.Virgo They shouldn't have been left out of authorship, no, I think I made that clear, but they also didn't stick around to finish the project and the lab decided to redo everything instead. Maybe they did that just to spite OP. Probably they did it because it wasn't anywhere near done.

@toby544 How do you think it will be made fair? What will fair look like? It doesn't just involve the institution it involves the journal too. The journal isn't likely to go along with retracting the old and accepting automatically a new version of the paper, it's just going to be retracted, still without OP's name on it.

I don't know exactly. Maybe the journal might publish a note. I just had in mind the institution judging that OP was wrongly excluded. As you say, maybe that won't result in the wrong being fully put right.

I am sorry to hear it happened to you. Academia can be cruel, toxic and unfair, both due to personal egos and external pressures. From what you describe, it's clear that your contribution has not been acknowledged and that the PI treated you unfairly and used their more senior position unethically and in bad faith. I hope it won't prevent you from continuing your research elsewhere.
Academia is very hierarchical, and many critical decisions are made behind closed doors. It is not uncommon to hear that universities protect the wrong-doers because they are more concerned with maintaining the status quo than with improving the environment for everyone. If you decide to take on this fight, keep in mind, that it might damage your future academic career, even though you are right and have sufficient proof of this fact.
You have the following options:

Do nothing, leave it behind, continue your research elsewhere.
Inform the University research ethics team and provide them with the facts of the matter. You have been sidelined for the authorship you deserve, promises were broken and your research ideas have been effectively stolen.
Inform the  Head of the Department (School) the PI belongs to.
Inform the funders of the research (grant awarding bodies), who may "encourage" the University to conclude investigation properly.
Inform the journal that your research has been effectively plagiarized by the PI. The fact that the code has been rewritten is not very relevant --- the ideas behind research matter much more than the code itself.

I do not think that taking this case to a court of law is a good idea. If you do this, the University's first priority will be protecting itself, rather than investigating the case. Considering that your research ideas have not been published, you probably do not have formal rights that are protected by law (IANAL though). This does not, however, mean that you have not been wronged here --- stealing ideas is unethical and wrong, but this is something the University will be able to investigate much better than the court of law.

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Find information about research grant calls from around the world
I am based at a southern European university where little local research funding is available. Other than Horizon 2020, how can I find out about programs designed to sponsor research in any country?

Here are several options:

Research Raven. This site focuses on calls for papers and conferences, some of which include funding. Most of the listings relate to medical and healthcare related opportunities.
ScanGrants. This is a sister site to Research Raven, and is "designed to facilitate the search for funding sources to enhance individual and community health....
Funding sources most frequently listed here include those of private foundations, corporations, businesses, and not-for profit organizations. Finding and listing less traditional funding opportunities is also a priority. Federal and state funding sources are typically not included on ScanGrants™ because they are readily available on other sites." Their listing are somewhat US-centric, though.
European Research Council. I am not very familiar with ERC.  The website states "ERC grants are open to researchers of any nationality in the world, any scientific field, any age. ". It seems well worth checking out.
The Wenner-Gran Foundation suppports collaborative research with a focus on anthropology. You have not specified your field, but depending on your circumstance this may be worth looking at.
Conference Alerts will provide you with a free alert system for conferences in your field, for any or all countries. Although this is not a grant-finding/listing service, the individual conferences may have funding available to you.
Finally, this Google search may bring some useful results.

One possible resource is EURAXESS. I know this agency because they run the EURAXESS-japan network to promote exchange between European countries and Japan. In their bulletins there is always plenty of information on grant opportunities.
In the "Services" section there is various information, including a section for funding. In this section there are links to several funding agencies. Well, there is a lot of information in this portal but this may be a good starting point.

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Looking for specific examples of University spin-offs where the researchers can earn part of the benefits
I have demonstrated that some of the technologies derived from our research are marketable; I have offered services based on them to industry customers and have been paid for that. So as academic research group, I have received income, but which can only be used to buy lab equipment mostly and not for personal use (salary complement, a new mobile phone, etc). Therefore I am thinking to create a spin-off, but the policies of our university in that case do not allow income to go directly to the researchers, so that I feel a bit frustrated about that. From the other side, I can not create a company and manage it in my free time since my contract does not allow to do that, and all technology derived from my research belong to the company. This is a private university and very young (15 years) and there are not many cases like mine. So my plan is to go and talk directly with the main head and tell them I want to create this spin-off, since this will be good for the university, its reputation, and so on, but that I want to receive some part of the benefits in terms of personal (for me) income. For doing this I would like to give them concrete examples that this works in other universities, since I have heard this situation is typical in other academic contexts, etc. Therefore I wonder if you know of concrete and specific examples of spin-offs from universities, where the university allows the researchers to earn some money derived from the incomes.

I have workaround: Incorporate a company and appoint a CEO other than yourself, retain some of the shares yourself.

that is very interesting but not what I was asking, thanks

The policy at my university for managing patent licensing fees and the like, which is somewhat distinct from a spin-off but somewhat conjoined - for example, you could start a spin-off that then licenses the patent, or find a company interested, etc.

Division of Patent Royalties

a) All monetary proceeds from the commercialization of University-owned inventions are the property of the University or its assignee. The University or its designee will collect and distribute royalties, fees, equity interests, or dividends to inventors and the University in accordance with the procedures established by the University.
(1) The University or its designee will deduct the costs of obtaining and maintaining legal protection, for each invention, to arrive at “adjusted income” unless other arrangements, agreed to by all parties that share in the income, are made by the relevant branch campus, research unit or program in advance of the expense and agreed to with the OC. Such arrangements may include contracted marketing, licensing and business development. In such cases, any agreed upon expenses will be deducted to arrive at adjusted income.
(2) The Office of Commercialization will deduct twenty percent (20%) from adjusted income and the remainder will be “net income.” This deduction is directed toward covering the expenses (excluding direct patent expenses) for administering the OC and provides initial funds for patent prosecution for other inventions without obvious commercial partners.
(3) Net income will be distributed according to the following schedule.
University’s portion of the share will be distributed as follows: 30% to the University, 20% to the college and department (or relevant branch campus, research unit, or Program when appropriate) to be equally split between the two
Cumulative Net Income Inventor/Contributor University
$1-$10,000                    100%
Above $10,000                 50%              50%

thanks, can we know which university is this? (since I am looking for concrete examples). and in summary, which percentage of net income can then receive the researcher?

Washington State University. What percentage of net income will depend on the amount in question, as in the bottom table. I believe the total amount is uncapped.

ok, and this 50% for the inventor, goes directly to the personal bank account of the inventor and he/she can do whatever he/she wants with the money or can only be used for lab equipment ?

University spinoffs are quiet common, although setting them up can be quite complex. There seem to be reviews of the process and lists of successful ones. Some of the benefits are described in this Nature article. Spin offs are not just limited to the US, UK spinoffs have also been very successful.
As an example, Herbert Boyer progressed up the academic ranks at UCSF from 1966 to 1991. He also co-founded Genentech in 1976 and served as its vice president. While I cannot easily dig up anything that says he received a salary, royalties, or a stake in the company, he did donated $10,000,000 to Yale in 1990.
Michael Mauldin developed Lycos while at CMU. He left his faculty position to become the founder and chief scientist at Lycos, but maintained an adjunct position. Again I didn't find anything about his ownership stake or salary, but most adjunct professors do not retire to their own cattle ranch at age 50.

yes, that is a very interesting list, but can one there find information about whether researchers involved can earn part of the benefits?

@flow yes, you just need to look a little. I provided two examples.

thanks, but I need solid examples that I can show to my employer

@flow what do you want? I don't think you are going to find copies of contracts...

Just to add another university to the list, Carnegie Mellon University has an entire department dedicated to managing spinoffs. The previous link (here again) lists a number of successful spinoff companies, as well as a brief blurb on each, with occasional links to more detail. They also have an extensive list of forms, policies, disclosures, and other resources that you may want to reference when speaking with your university. You may find that you can save a lot of time by simply using these forms and procedures rather than starting from scratch.

I think this one should count: It's called Ant-Optima and, as the description suggest, is a spin-off of a rather well known AI research lab affiliated with the University of Lugano, Switzerland.

but do you know if there the researchers earn part of the benefits?

@flow Good point. I do not (and cannot) know for sure. My guess would be "yes" (where else the benefits would go?) But it's not more than a guess.

Here is the Duke Policy:
https://provost.duke.edu/wp-content/uploads/FHB_App_P.pdf
Relevant exerpts:
Section IV, Part C: "Inventions resulting from research or other work conducted by University employees in whole or in  part  on  University  time  or  with  significant  use  of  University  funds  or  facilities  shall  be  considered the property of the University."
Section V, Part C: All  income  derived  from  inventions  falling  within  Article  IV, Section C  shall  be  distributed  in  accordance with the following rules:

...
The University  will  then  pay  and  distribute  the  income  remaining  after  payment  of  direct expenses in the following manner:
a. income from $0 to $500,000:

(1) fifty percent (50 %) thereof to the inventor;
(2) ten percent (10 %) thereof to the inventor's laboratory until, in the discretion of the President after consultation with the Chancellor   or   the   Provost, this distribution equals the maximum amount which can reasonably be expended in that laboratory, after which any excess shall be added to and distributed as a part of share in accordance with V.C.2.a.(4) below;
(3) ten percent (10 %) thereof to the inventor's department/organizational unit;
and
(4)  thirty  percent  (30%)  thereof  to  be  directed  to  the  school  of  the
inventor’s primary appointment.

thanks this is kind of what I was looking for. Last question is, this 50% for he inventor, goes directly to the personal bank account of the inventor and he/she can do whatever he/she wants with the money or can only be used for lab equipment ?

I don't know personally, but the language suggests 50 percent personal bank account, 10 percent lab (only lab-related expenses).

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Is it illegal or unethical for a publishing company to pay in exchange for including a co-author?
Some weeks ago a company contacted me via email. In summary, they offer to pay you if you include a co-author. They also need you to sign an agreement with your University and them. So, from one side, it seems kind of legal (since in the agreement they state "sponsorship"), but from the other side, these practices, I am afraid could lead to unexpected retractions, due to the likely unethical side of the business.
Is this kind of service illegal or unethical?

I have no experience of this, but reading this reminds me of the services that allow students to buy an essay to 'look at'. It is possible to use the service for legitimate purposes, which means it can't really be shut down. On the other hand, there is a very clear opportunity to use it for illegitimate ends. Oxford Uni responded by banning anyone there from working for such companies. I think that gives you an idea of how this would be viewed.

Pretty clear from an ethics point of view. Don’t do it.

Definitely feels and sounds pretty sleazy.  Though, it seems like a good answer would elaborate on any issues it might have.

See Authorship For Sale. Papers For Sale. Everything For Sale.

It sounds not ethical to me; if it is legal or not you should ask a lawyer;
Consider the following point: This is definitely at least borderline to scientific misconduct (depending if the co-author actually contributed anything at all), and either you will have to publish in a journal with bad reputation or risk retraction if you publish in any journal caring about it's reputation.
And if your PHD gets delayed (and possibly stalls as a consequence of resulting bad relationships with your team/university), anything which you possibly got from it will turn out not to be worth it.
(As a small side remark: Academic life often forces you to walk the line between ethical and not ethical very carefully. But don't participate in anything like this on your own will)

If the object of this is just to buy somebody a co-author credit without doing the work, that is obviously unethical, but for me that would be one of the least worrisome scenarios...
By academic convention, all co-authors must agree to the content of a paper published under their names. If you make a binding commitment to co-authoring with Bob Corporate without agreeing on the parameters for what is to be published, that puts you in a very precarious position.
Suppose Bob wants the conclusion to say "Our findings show that smoking is beneficial for children's health, and should be made mandatory", and refuses to sign off on any text that doesn't contain that statement. Does the contract then require you to refund their money if you (and the reviewers) can't agree with Bob on what to publish?
But in my experience from a previous career in research, it's not so much the blatant stuff that's a problem. It's the subtle pressures: you have two options for data analysis, both defensible, but Bob wants to use the one which (by coincidence) happens to make your sponsor look better.
The pressure doesn't even need to come from the sponsor. In my case, I never felt any direct pressure from our funders, but I felt considerable pressure from within my institution to produce results that were favourable to our sponsor. When somebody is paying you money, it's only natural to want them to feel like they got their money's worth, especially if you're hoping for repeat business. Nobody needs to say anything out loud, they don't even need to acknowledge to themselves that they're biasing the work. Human beings are fantastically good at finding ways to rationalise choices that happen to support their own interests.
As Sascha's commented, purity is difficult to attain in academia; it's hard to work without money, and money always comes with strings. But at the very least, you should know in advance what the company is hoping to get in return for their money, and think about whether you have sufficient leverage to protect the integrity of whatever's published with your name on it.
If you do go through with it, make sure that the contract covers how disagreements about content will be handled, and make sure that things like data analysis methods are agreed on in advance of data collection (if relevant to your work).
Also, make sure everything is agreed in writing...


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Ways to manage something like a 'work-life balance'?
According to a recent international study on work-life balance within academia

"a majority of researchers and scientists had conflicts between their work schedules and personal lives at least two to three times a week."

Nevertheless,

"about 60 percent of scientists were happy with their work-life balance. The rates for women were lower, at 52 percent."

I wonder what differentiates these 60 percent 'happy people' from the remaining 40 percent. What do you think are good strategies for a healthy work-life balance? How do you balance your academic work/life with your personal life?

My personal take: http://scienceinthesands.blogspot.com/2011/08/academic-work-life-balance-at-kaust.html

The neighbor a few houses down drives a truck regionally during the week and watches the little ones on the weekend. His wife mainly takes care of the kids but frequently drives Uber at night and on the weekends. They'll be interested in how they might strike a better work-life balance, so I'll upvote this question. For them it would be a nice problem to have.

Disclaimer 1: I know the two worlds : academia and the outside world ;) I worked in public and private universities, and in a consulting firm.
Disclaimer 2: I can only speak about life for people involved in theoretical areas, I know that science involving living things / big experiments has real constraints.
I heard a lot of people in academia complaining about the conflicts between their work schedules and personal lives (me included, because I'm grumpy). But we have to face it, most of the time there is nothing to complain about it.

"I have a deadline today at midnight" : I do that all the time, but the calls for papers are out several months before the deadlines, so the problem here is planning, not the nature of the work.
"I have to finish this grant application before midnight" : hum, grant applications and conferences deadlines seems to be of the same kind.
"It's 3 AM, I just got that email that needs an answer" : I don't think this email is that urgent. An BTW, if something is really urgent, phone still exists for that matter.
"Someone (supervisor, head of the team, dean, etc.) wants me to work more/at night/etc." : Slavery has been abolished. If you have good results, the thing is that in academia you are master of your schedule.
"I cannot stop thinking about that problem" : yep, here this is true, we bring our work everywhere. If a researcher cannot live with that aspect of the work (which can be quite stressful), then he should probably consider finding an other job.

My point is that working in academia is working in one of the most flexible field.
This is where there is a big difference with the "outside world".
This flexibility is the problem: many people have difficulty dealing with it, and thus are giving themselves very strong constraints, so strong that they cannot handle them.

I agree fully with you; a friend of mine even said that academia helped to balance work and life because of this flexibility: he is able to take care of his newborn son at night because he can afford to get late to the lab (he probably works a little bit when feeding its son, as I know him).

In my experience, there's less distinction between work life and personal life than in other jobs. If you're teaching, you'll get emails from students on the weekend and late at night. A paper deadline at midnight doesn't care that you're supposed to finish at 5. If you're working on an interesting problem, you're going to think about it at home.
I think the way to be happy with that is to simply accept it. If you're counting on having a 9-5 job if you're paid for working 9-5, then you're not going to be happy in academia. If you're uncomfortable with the line between work and personal life being blurred, you should perhaps consider a different job.

Lars, I don't think that's necessarily true. Having seen both sides of the fence, I know it's common for folks to be expected to work longer hours outside of academia too, and I know some people who do research who do achieve a work-life balance. I don't think saying "Find another career" is really a factual or constructive answer to this question.

I'm only speaking from my personal experiences in both academia and industry. It's certainly true that in industry you might be expected to work longer hours as well, but in my experience, this is more prevalent in academia.

I'm curious if working long hours in academia is something that is self-inflicted (poor planning, overcommitting, passion) or if it's something that is primarily external (chairs want you do do more courses and you can't say no, University wants you to attend more meetings and you can't say no, people want you to get more research funding and teaching and service or else you lose your job). Any perspectives?

Both from what I'm seeing. If you're junior, it's mostly self-inflicted (although you're expected to do this to some extent to get ahead) and later it's because of commitments you can't turn down.

Academia, despite talk of positions being "full-time" or "part-time," really doesn't work according to a fixed schedule. It's one of the "perks" of academia—the ability to maintain your own schedule, so long as you get approval from your bosses (if you're a student or postdoc) or from your institute (if you're a professor or higher up).
Of course, the downside is that not everybody is on the same schedule as you are—or cares what your schedule is supposed to be. (Grant agency deadlines, for instance, don't pay any attention to what's going on in your life at the same time!) So, that might mean there will be times when you have to really put the nose to the grindstone.
The key to having a successful balance is to make sure that everybody involves knows what's going on, and so appropriate accommodations can be made.

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What should raise red flags to detect fabricated data
In academia, there has been recently some cases that came to light of very well known scientists that have fabricated their data out of thin air.
In some instances these papers have been cited many times by other researchers and some of them have even been praised. Thus, when the truth came to light, it also appears to the  public that scientists have bad peer-review processes.
In light of the presented reasons, how can a reviewer make at least some sanity test that the data is (most likely) not fabricated? Suggesting so could come as a great injury to the researcher, but I think there should be some kind of mechanism to control this.

I am not sure how to detect fabricated data without reproducing the data by the same methods suggested by the paper authors. I think the sanity test you mention depends on the field and the complexity of the experiments.

Indeed, but for example, one friend once told me to just take their results and see how well the fit normal samples.

@Leonpalafox that only works if their results might reasonably be expected to have a Normal distribution. Lots of things do not have a Normal distribution.

Indeed, if their results follow a normal distribution always, it might raise some questions.

I know some famous retractions incidents (nature and science level journals) are all the published results can't be reproduced.

There is only one reliable way to do it, which is to try to replicate their results.
The unreliable, but not completely useless way, is to see if the numbers fit Benford's Law.
Benford's Law describes the distribution of the first digit of many very diverse data sets. This is the distribution:

(public domain chart from Wikipedia)
Andreas Diekmann describes this further, in Not the First Digit! Using Benford's Law to Detect Fraudulent Scientific Data, a paper in the Journal of Applied Statistics from 2007

Sweet, this was something in line with I was looking for

For that to work, you need large batches of raw data (and they need to be expected to follow normal distribution). Most papers only include curated/analyze/post-processed data, for the sake of clarity.

I would perhaps amend this to be clear that the actual notion of Benford's law can be applied to any digit (not just the first! - its distribution just changes depending on the characteristics of the data). The citation you provide makes this clear right in the title, and some papers examine the trailing digits, not the leading digits.

So you admit that your avatar picture is fraudulent, then?

Not fraudulent, just dyslexic.

@Andy W In fraud detection, it's actually common to use the second digit. The reason is that it's considered that people who are faking data are quite likely to get the first digits about right, for example they might change "16" to "15", but they are less likely to pay attention to second digits. Nevertheless, some people claim that Benford's Law is pretty useless, for example: http://vote.caltech.edu/content/irrelevance-benfords-law-detecting-fraud-elections

I think I agree with the first statement: "There is only one reliable way to do it, which is to try to replicate their results." I'm much more skeptical about the broad usefulness of Benford's law for the reasons laid out in @jwg's post.

Quite frankly, I see Benford Law as close to useless in detecting fraud, both because of false positives and because of false negatives. In the cases of fraud (or gross mistakes, I am not sure) I have seen, Benford Law would not have been  useful: The article reported the results of computer simulations, with one important parameter not taken into account, and reported the data as if that parameter was irrelevant. So the data measured "something", but not what the paper claimed it did, and there's no reason the incorrect results would be less likely to follow Benford's law than correct ones.

@F'x following a normal distribution is not a condition for Benford's law. In fact a standard normal distribution does not obey Benford's law.

Edit
After thinking about some of the points raised in the comments, I would like to expand on my answer, but also defend its form against the criticism that it is so vague as to be unhelpful. [In case you are wondering what the original answer was, it is roughly the sections 'Looking for mistakes' and 'Trusting your feelings'.]
Benford's law
This was mentioned by @EnergyNumbers. The answer is very popular; however I don't think that it is particularly helpful.
Benford's law is only one of many statistical techniques that can be and have been used to detect fraud or bias. It has become widely known, probably partly because it is simple to apply, but also simple to justify in a 'hand-waving' way.
However, its validity is much more limited than @EnergyNumbers (who calls it the unreliable way) implies. As originally formulated, Benford's law said that if you take a large range of numbers which have different sources, contexts, meanings or units, the logarithmic distribution emerges. This is a very interesting statement, but has little utility in detecting fraud. The statement that Benford's law, whether applied to first or second digits, should apply to a particular set of observations of a single variable, is an extremely strong statement. There are many, many natural examples of well-formed non-fraudulent datasets to which Benford's law does not apply. Several other digit distributions could reasonably arise in bona fide data. You may or may not be able to justify the assertion for your own data, however what you should not do is blindly apply Benford's law to various sets of numbers, and start forming opinions about their reliability.
It is a serious statistical technique and requires non-trivial statistical understanding to apply. The same thing applies to checking for normality. Unless you have a good understanding of how normal distributions arise, you will not be able to form a theory as to why some distribution should be normal. If this is the case, then any test for departure from normality will be useless.
A paper that really examines this for Benford's law is The Irrelevance of Benford's Law for Detecting Fraud in Elections. [Hat-tip to @Flounderer who linked this in his comment.]
Why this answer doesn't go into any statistical detail
The original answer I gave, below, tries to err on the side of not handing 'formulas' over to people who possibly don't understand their use. I tried, perhaps not very successfully, to suggest starting places for thinking about how and maybe why people either fake results or unconsciously introduce bias.
This kind of forensics is in some ways very similar to other stats, but has some very important differences. If you are looking for a signal in some noise, you might form two hypotheses, both of which imply that data is random, but with say different means or distributions. If you are looking for cheating, you have to remember that fraudulent data is not in any sense random. Spotting it involves teasing apart (possibly) three elements: the real numbers, the deliberate adjustment, and any pseudo-random perturbation that might have been made to mask the adjustment.
I believe that in order to properly apply some forensic test to a set of data, you need to first develop a proper theory of why the test might be meaningful. This entails hypothesing about exactly how the data might have been manipulated. For example, Benford's law was successfully used to investigate whether China's GDP growth in % was being rounded up if it had a high second digit: http://ftalphaville.ft.com/2013/01/14/1333552/chinas-non-conforming-gdp-growth/ (registration required).
Taking a whole battery of tests and applying them to some data might allow you to get to the stage of theorizing, but it can't get you any further. This is why in the first few paragraphs of my original reply, I talked in very general terms about how faked data might differ from genuine data. These are supposed to give you places to go looking for anomalies, which you later investigate rigorously.
Looking for mistakes cheaters might make
Starting points can be things like testing to see if the numbers fit the conclusion too closely. If an experiment was done on several groups of test subjects, all of which are supposed to be identical, then you would expect the success rate in each group to be close to the overall average, but not too close. Some researchers who have made up their results had all group success rates equal to the average success rate to the nearest integer.
If you get someone to make up the results of 20 successive coin tosses, they deviate from statistical likelihood because they don't put eg. enough sequences of 5 heads in a row. People usually think things like this are less likely than they are. Look out for things which are 'too random' or 'too regular'.
Researchers into election fraud have had some success looking at the last two digits of numbers to see if double sequences like '11' or '22' occur less than they should, because humans who make up 'random' numbers tend to avoid them. This applies in the specific case where you have enough digits that the trailing digits should be uniform, but that no rounding should have been applied. This test wouldn't have detected the Chinese GDP rounding, or manipulations where leading digits are adjusted.
The mathematician Borel weighed the loaf of bread that his baker gave him each day and decided that the average was too far below the standard weight of a loaf to support the hypothesis that the baker wasn't making underweight bread. He confronted the baker, who promised that he would make the loaves heavier. After that Borel continued to weigh his bread. The average weight was now high enough, but he studied the distribution of weights and realized it corresponded to that which you would get if you always took the maximum of several observations of a normal distribution. He concluded that the baker always gave him the biggest loaf from those on the rack, but that the average was still below spec.
This is a classic illustration of how someone might falsify results - by taking the best result from several runs. In order to reason about the distributions, it was first necessary to understand how this method of cheating works.
Or suppose that someone had a bunch of results but threw out those which they didn't like. Has this introduced unlikely biases in the selection of the original test subjects? Eg if patients are supposed to be chosen at random but there are fewer old people than one might expect. In general if any data were rejected you should test for dependence between rejection and other variables.
Sometimes real data has a particular bias or noise which is lost in faked data. In the Simonsohn paper cited below, he looked at a psychological study where subjects were asked to say how much they would pay for a T-shirt. Unlike other, genuine studies, the results didn't cluster around multiples of $5.
Another thing which can be hard to look for but which is very damning is to figure out what the results might be if no effect was present and see if eg a single digit has been changed, or a round number has been added.
Sometime people genuinely do introduce biases unconsciously because they believe in their theories or want to succeed. This could mean that they make very small adjustments which can have a large cumulative effect, such as rounding up numbers which should be rounded down.
Trusting your 'feelings'
The other thing you need to try, is to get a 'feeling' for something dodgy, outside of the actual numbers. Again, all this does is give you a place where you try and build a proper statistical hypothesis and then test it against the data.
A mathematics professor once said to me that you can spot false proofs by two things: either the work becomes very complicated at the point where it is wrong, or the wrong step is skipped over as obvious. Not quite the same situation I know, but very complicated data handling procedures could be designed to be difficult to replicate (or could be the point where the researcher manipulated data until she got what she wanted). Saying something like 'cleaning' or 'normalization' without explaining exactly what was done could also be a red flag.
If there's a very very standard source of data of a particular type and someone didn't use it, or used it but not in its original form, why not? People often give a citation justifying some supposedly straightforward manipulation they perform on the data to clean it or get it in a more convenient form. Usually but not always, this reference should be to a standard textbook on stats or experiment design, or to some paper which everyone in the field knows. If it's to something extremely obscure is this justified by the obscurity of the topic? Does the cited work actually say what they claim it does?
How to proceed
I have tried to promote the general skill of trying to understand how people fake things, why and how they mix the truth with fabrication (or sometimes are subject to unconscious bias), and what constitutes strong evidence of anomaly. Looking at case studies, of which Simonsohn's paper is a great example, can help. Stephen Jay Gould's famous book 'The Mismeasure of Man', on the face of it a political tract critical of biological determinism, is also a collection of many case studies of deliberately or accidentally biased scientific work.
If you think that something is fishy, but you don't have the analytical tools you need to prove it, then you need to do research into specific statistical tests that apply to those cases. Among academics, most stats isn't done to detect fraud, and even if you have good quantitative skills you might not have this knowledge. The example of Borel is a good one in that many of us don't know offhand what the distribution of the 'biggest loaf to hand' should be, given some reasonable assumptions for the distribution of the loaf sizes.
However, as a researcher you should definitely have the skills to go and find this out from a book. Asking a statistician is a very important technique which may or may not be a last resort, depending on how friendly your statistician is.

I don't think If an experiment was done on several groups of test subjects, all of which are supposed to be identical, then you would expect the success rate in each group to be close to the overall average, but not too close. is very useful advice. For instance Fisher's critique of Mendel was based on the data being to similar than would be expected by chance, and Uri Simonsohn's recent work is based on similar observations of data being less random than one would usually expect.

@AndyW I don't understand your objection, aren't these examples of exactly what I am talking about?

Not at all! In the quoted section in my comment you suggest to be suspicious of results that are too variable, but give no conditions for evaluating the variability. The two examples I refer to provide evidence that the results of papers are less variable than would be expected by chance (which chance defined explicitly through hypothesis testing). IMO this response is just too long winded and unorganized to be useful, and statements like Look out for things which are 'too random' or 'too regular'. are so vague as to be worthless.

At a minimum it would be nice to supplement the answer with actual citations to support the statement is just one of many statistical techniques that can be and have been used to detect fraud or bias. This is certainly true, but pointing to some examples would at least provide the reader a means to make progress on his own.

@AndyW, what is your understanding of the words but not too close? If you need 'conditions for evaluating the variability', you should ask a statistician. As for providing examples, I tried to write something that would be a decent starting point for someone who isn't an expert. I did provide one (simple) example, that of Borel. The paper you cite is excellent, you should add it as an answer, otherwise I am happy to edit and mention it.

There are enough answers here already, and I would happily upvote yours if you add the Simonsohn paper (please provide reference to Borel as well - I'm not familiar with that and the wikipedia page did not mention it)! My point was that the quoted statements provide no effective way to evaluate results because statements like too close are so ambiguous, it can mean anything to anyone. Taken literally the statement about too random or too regular applies to every set of numbers (because if it is not random it has some regular structure).

I don't really know how to further explain the word 'too' to you.

@jwg: I think Andy's objection is precisely that you really don't know how to explain the word "too".  Don't just say "ask a statistician".  Any academic working in an experimental discipline needs a strong enough statistics background to give, understand, and apply a precise definition of "too close".

@jwg I read your answer. I believe it's excellent. My serious concern is that people now know how to fake data with less chances to be caught after reading your answer.

@JeffE, I do have a sufficiently strong statistics background (I am a probabilist). However, this knowledge isn't something that can be briefly communicated in the format of an answer. As explained above, this is why I have tried to give pointers to someone to explore this themselves.

It depends on the nature of the data. If the data presented is in form of pictures (such as photos of biological experiments, like Western blot), you can check for traces of image manipulation. Guidelines to examine photographic data are available from the Council of Science Editors.

Fabrication of data is not easy to find out as a reviewer. You may try tricks for raw numerical data, if they come in large numbers and can be expected to have normal distribution. But even if the tests say there is some likelihood the data was fabricated, it is still not "proof". You would need at least strong likelihood to prevent publication. That is not easy to find.
If you look at accounts of retracted papers and retraction process, you will find out that the culprit is usually identified not by the numbers alone but other facts: he has very rapid publication rate compared to field studies, he has weird behavior and does not allow coauthor to see raw data, things like that. In most cases there was nothing a very diligent reviewer can do. Taht is sad, but that is the truth of it in most cases.

This is an example of selection bias - the fraudsters who were found out published too frequently or behaved secretively. Nothing about this tells you that there aren't many papers out there by people who are more cautious about how they fabricate results, but which could still be discovered by careful examination of the papers by the reviewer. If there isn't enough detail in the paper to check for fabrication, or if there is a strong likelihood without proof, you should reject the paper and explain this in the review.

Sometimes, too good to be true is true not only in academia but also in sports.

@jwg I wouldn't agree with you last sentence. In fact, that's not the editorial policy of most journals I know: raw data is simply not required for review and publication. As a reviewer, you should definitely follow the journal policy…

@F'x I didn't say raw data but enough detail. The editorial policy of most journals includes the idea that the reviewers should make a reasonable effort to advise the editors whether or not the papers are bogus.

@jwg well, without raw data I don't know how you can feel “strong likelihood” of data fabrication or not. So what I'm saying is: if the paper seems dubious, I'll say so, but I'm not going to ask for every bit of data to check that it seems legit.

Again, I didn't use the words every bit of data but enough detail. If you don't know whether there is a strong likelihood of data fabrication or not, then you probably don't have enough detail.

As a reviewer, you should definitely follow the journal policy… — But reviewers don't decide; they only recommend.  I think it's perfectly reasonable for a referee to recommend rejection on the grounds that raw data is unavailable, as long as they also give the editor enough information to make a decision if by journal policy those grounds are insufficient to reject.  With enough recommendations from the community, the journal policy might change.

There has been related work in survey research on how to detect interviewer falsification of survey responses, sometimes referred to as curb-siding (when an interviewer is allegedly sitting on the curb next to the house where they were supposed to be doing an interview). See a collection of practices from the Survey Research Methods Section of the American Statistical Association, and a system for detecting interviewer falsification from RTI, one of top 3 US survey research organizations.
The general findings usually run along these lines: interviewers are OK with getting the first moments (means, proportions) about right, but are lousy in the second moments (variances and correlations): they avoid extreme answers, thus reducing variance, and are lousy at correlations (may not know well enough how things go together).
Not much of that may be applicable to natural sciences, though. I would suggest enlisting a local statistician. Many stat departments run consulting courses for their grad students that welcome requests for expertise from other disciplines.


text:
Should one submit to a workshop and a conference at the same time, typically ACL and EMNLP?
I am currently a PhD student in NLP. Say that I submitted my work to ACL, where my paper was rejected for the main conference. Then I submitted to a workshop attached to ACL, for a deadline of June 1st.
However, I worked more on the topic and wish to publish the revised version at EMNLP, whose deadline is on June 16th. After contacting the ARR supports (ACL double submission policy), I have two options:

Submit to the workshop in a non-archival way so that the paper is not included in the proceedings
Withdraw the paper from the workshop if the revised version is accepted at the later conference

For the second option, the notification of acceptance of EMNLP is September 20th. Meanwhile, the ACL workshop is held on August 16th. Then it would be impossible to withdraw the paper from the workshop if it is accepted at EMNLP since it will have been presented.
Does submitting to both venues violate the policies or cause ethical issues? What should I do? What if both the original paper and the revised paper were accepted respectively at the venues?

How different will the EMNLP submission be? Would you have enough new material that you could make it a follow up work (and cite the workshop paper it builds upon)? And why not submit to the workshop in a non-archival way as the organizers suggest?

The revised version should improve the method to the reviewer's concern about the practicality of the proposition. In addition, comparison to more recent methods will also be addressed.

You need to check the specific rules of the specific ACL workshop and EMNLP, the problem is generally during the review process (waste of reviewer time if paper is reviewed concurrently at multiple venues) and paper being accepted (same exact paper cannot be published twice).
If your paper is accepted at the archival track in an ACL workshop, then it cannot be submitted to EMNLP, because it will be published at the ACL workshop and it will be part of the proceedings.
If you submit to a non-archival track, then this is more flexible and opens the chance that you can submit to EMNLP, you just need to confirm that the review process dates do not intersect between both venues (unlikely but still you should check).
I have seen workshops that specifically accept (for non-archival tracks) papers being submitted to other specific conferences, that is why it is important to check the rules of each venue and try to see if a common ground is found.

Thank you for your answer, but what do you mean exactly by "confirm that the review process does not intersect between both venues"

@NguyễnQuangAnh Corrected, I mean that the dates of the review process do not intersect.

As stated the review process for the workshops ends on June 20th and for the later conference, the review process is from June 15th. So this overlapping means that the paper cannot be submitted to EMNLP if the reviewing for the workshop has not ended, even as a non archival submission?

@qan In this case I would ask the workshop organizers if they are ok with this due to the non-archival track.

Even though the conferences ask the authors for to check for double session, it is very rare they practically check that. As there is no way to check where the paper has been submitted before the conference date or when it appears online. So, even if both papers are accepted, you are in a better position to choose to publish in a better conference and withdraw from another one. This is what most of MS/PhD students do in the academic world.

This is highly unethical and directly violates dual submission policies of most venues, and not at all "what most of MS/PhD students do" in my experience.

The academic world is not so fair and transparent as it should be. I don't know where on Earth you are and what practices are followed in your region. But I have spent more than a decade in academia and am well aware of such (mal)practices. Most MS/PhD students are after getting more and more publications in their resumes, and, they want to try their luck everywhere if they are not well guided by their supervisors. I know this "highly unethical" but this is the reality.

Do not follow this advice, it is terrible, reviewers and organizers are very common between both conferences, so if reviewers or organizers notice the double submission, the punishment will not only be rejection in both venues, you could get banned from future conferences. This is not a common practice in NLP/ML as this answer is suggesting. I have noticed double submissions to conferences I have reviewed for.


text:
Can one freely add an explanation to a quotation in square brackets?
The following is a quotation in which something ("[an angel, for example]") is added by the writer who quotes. This added part, is it only an explanation of the writer, by which they make the quotation more easily understood, or should it be at least something mentioned by the one they quote in the context of the text?

The translation that I call motion, is not something with less being than ﬁgure has, that is, it is a mode in body. But the moving force can be that of God, conserving as much translation in matter, as he placed in it in the ﬁrst moment of creation, of that of some other created substance, such as our mind, or some other thing [an angel, for example] to which he gave the force for moving a body. . . . I consider “matter left free and having no other impulse” as plainly at rest. Moreover, it is impelled by God, conserving as much motion or translation in it as he placed there in the beginning.

The question in the title is clear, but the question just before the quotation is not. Are you asking whether it is OK for the quoting writer to add extra information that was not mentioned by the original quoted writer?

@toby544. I think that the title and the content are in accord. Square brackets can be used to add clarifications, examples, and explanations, but can those be freely added? Can the angel be mentioned here if it is not directly lifted from an adjacent paragraph?

Words in square brackets in a quote are words added by the quoting author.  When the square brackets are in the original quote, sic is used to so indicate.
See The Skidmore Guide to Writing.

That's it, @minseong

@minseong I have to say, I would probably be confused reading that. Sure, I would probably understand it because it's the only reasonable thing that the [sic] could refer to, but it would take a bit fo "huhh?". I'd prefer just a statement outside the quote saying that the part in brackets was in the original quota.

@JiK same. It also more closely conforms to other instances where formatting of a quotation and formatting within the quotation itself (e.g. emphasis of certain words or phrases)

In the example you give, I would say "no". It isn't clear to the reader whether the bracketed words come from the original source or were added by someone else. If it is in quotes, then it should be literal. The exception being a phrase that clearly clarifies the original authors intention. This can be made clear in the surrounding context of the quote.
But "freely adding content" is problematic.
However, some have made it clear that "explanatory" words have been added by  using a formulation like:  [an angel, for example: ed.] indicating that it has been added by an "editor". Another form might be to put the addition in bold face and follow the quote with an explanation that the bold has been added.
A third possibility is to use something like a superscript asterisk at the point of the "needed" insertion and put the "explanation" in a footnote.
There is nothing per se that implies that square brackets necessarily imply an out of quote addition.
Also, in your example, there is nothing to suggest that "an angel" was in the mind of the original writer. It isn't "clarifying" the meaning.

there is nothing to suggest that "an angel" was in the mind of the original writer  Taking the text literally and with no extra knowledge, you are right. But I think the quoting writer knows about theology and the writing of this historical period, so he or she is adding an explanation to help modern readers.

@toby544, yes, the surrounding text in the original can supply necessary context to make such a thing valid. And that might need to be explicitly expressed in the text surrounding the citation as well.

Not just the surrounding text, but all sorts of knowledge about what is meant can be used by the writer to decide what extra information to put

+1 for noting that "an angel" is not clarification. I am of the opinion that square brackets are appropriate to clarify a pronoun or another reference that may confuse the reader. Or to insert a word in a quote to make it conform to the rules of grammar. Editorial comments such as a "for instance" should be in a footnote.

Text added in square brackets should not change the original text. You are still quoting. It isn't a quote anymore if you freely add stuff.
Examples for square brackets would be grammar:
Original: The sky being green is the only truth.
Quote: The author in xyz makes a contrafactual statement by saying that "the sky [is] green is the only truth."
Or omissions:
Original: The sky as seen by looking up (i.e. turning your head towards the sky) is blue.
Quote: The author claims that "[t]he sky as seen by looking up [...] is blue." (Important: no change in meaning of the quote, you may only leave out something that does not change the perception of the content).
Or additions:
Original: The bear eats fish. He likes fish.
Quote: "He [the bear] likes fish."

Are you saying these three are all OK? The first one is unclear, as you have changed green to blue and the quote is barely correct grammatically

@toby544 that was a mistake, thank you for noticing it. The grammar ... I had a hard time finding a good example ;)

All your examples are good and typical. But I'm not sure whether it is an ironclad rule that text added by the quoter in square brackets should never contain anything beyond these narrow adjustments. Your argument "you are still quoting" does, in my opinion, not hold entirely because the square brackets explicitly exempt their contents from the quote; that is their very meaning. As long as any remarks are clearly recognizable as such, I don't think they violate academic standards and are a mere matter of taste and style (in the OP's example I'd move them past the quote in an explanation).

@Peter-ReinstateMonica I disagree. If something changes the meaning, it does not belong in square brackets between the quotation marks. Editorial remarks that are more than an explanation can go anywhere outside the quotation marks.

You can't add content completely freely, as it would be confusing. But it is OK to add a few words to clarify something, or to add one
or two words to make the quotation grammatical, etc.
In your example the original text looks like it was written several hundred years ago. Most readers will not know what "some other thing" could refer to, so the quoting writer is adding an explanation to help them. Angels might not be explicitly mentioned by the original writer, but the quoting writer has enough expertise to know that that is what was meant.
It might have been clearer if they had said something like "[this means angels, for example]", or made it a footnote.

"Freely adding" might be something of an overstatement, but adding an explanation of quoted material is most definitely an acceptable thing to do. This is made quite clear, for example, in section 8.31 of the 7th edition of the APA Publication Manual "Inserting Material. Use square brackets, not parentheses, to enclose material such as an addition or explanation you have
inserted in a quotation." No limitation is stated by the APA on the nature of the provided explanation; instead, the reader is warned by the presence of the square brackets, that the material has been inserted by the quoter, and not by the author of the original.


text:
“Ability to solve problems through the standard application of theoretical principles” in a position description?
I am trying to apply for a job in a university research office, administering honour’s, master’s and PhD thesis submissions. The selection criteria are:

Demonstrated ability to apply theoretical knowledge, at degree level, in a straightforward way.

Ability to solve problems through the standard application of theoretical principles and techniques at degree level.

Can anyone tell me what they are asking for, and give examples of how one could  demonstrate these skills?

My interpretation is that they simply want someone intelligent, with an academic level of thinking but not necessarily an academic degree. But I think they also need someone capable of writing better selection criteria.

They are using annoying job description language but basically they are saying "we want someone who has some general understanding of the subject matter associated with these theses, in contrast to a position for an administrative assistant who has office skills but not necessarily technical knowledge"


text:
How frequently should PhD students update their advisor?
I'm a 1st year phd student in math. My advisor adopts a more ambiguous meeting policy that I approach him whenever I want to talk. So I was sending him long emails on a biweekly basis with updates of what I read and thought about in that duration, out of my own initiative. Of course, a lot of it is not substantial progress and probably doesn't even worth reporting. I do this because the actual meeting is sporadic and the frequency is definitely below once per several months. So I feel that I should update him on a regular basis. My advisor didn't say stop sending the updates but just stopped responding to them. I guess it is kind of annoying seeing a lot of stuff from your students without actual breakthrough. Before I ask him anything, I just wonder what would be the norm of phd student updating their advisors regarding frequency and whether they should update without any actual progress.

You should ask other students of your advisor or in your program. I think the consensus on this site would be anywhere from once weekly to once a month. Once per several months is low, IMO, especially for a first year

I work full-time and am a CS PhD student (work and research overlap). Since I make less progress than full-time PhD students, I usually send a weekly or bi-weekly email letting my advisor know I'm still doing stuff and meet when needed. Regarding your emails, professors get a lot of it. It may be worth condensing your emails to the important updates/questions and use the meetings for things that are more easily verbally discussed.

I think it depends on many variables and the field. I see you are from Maths. But even though, is hard to think of an answer. We were basically on everyday contact.

Even as a postdoc, I update my PI weekly. Even if the update is "no progress this week". It helps build a good working dynamic and can show the advisor if you are stuck or need more help.

As often as a new version of your advisor is published.

It completely depends - you will get 10 different answers - speak to your supervisor and iterate on a solution that works for YOU!