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Can a professor accuse a student of cheating on an exam without witnessing it firsthand?
Can a professor accuse someone of cheating after checking his or her test? How is that possible, if the professor has not caught the student cheating red-handed?

To get more informative answers, you will have to include at least a few more details about the situation. You can edit the question freely to add them. In particular, the systems are very different in different countries, so saying which country you are interested in will give better answers.

I am referring to UK.

The general answer to the question is "Yes." There are a lot of reasons why a professor might suspect a student of cheating, some of which do not require an eyewitness. You'll have to give more details (i.e., what did the professor say/do? why does the professor suspect cheating?) in order to get a helpful answer.

oi think she suspects because people might have the same answers. but can she accuse someone if she didn't even catch them doing it? how can she accuse them when she has not even seen them doing it?

what can be the consequences of cheating on a test?

@usman: Consequences?  Anything from a zero on the exam to expulsion from the university.  You're going to have to provide more detail if you want better answers.

Is this a question, or a complaint?  Do you really want a literal answer to the "how is it possible" question?

There are certainly situations where I can be quite sure a student cheated on an exam. Two students, who sat next to each other during the exam, turn in papers containing proofs that are almost identical, except that one has correct proofs while the other has a few isolated words that are different, similar (so that they could be miscopied), and make no sense in the context.

Generally speaking, the answer to your question is "Yes."
If there is a strong similarity in answers that is highly unlikely if the students worked independently, it can raise suspicions of cheating.
For example, in Reilly v. Daly,

At the conclusion of the exam period, the professors held the exam papers of Reilly and the neighboring student in order to determine whether their answers matched. A comparison of the exams revealed that the first seven pages, which included twenty-seven multiple choice and matching questions, were identical.
...
Taking the conservative approach of comparing only wrong answers on only the multiple choice questions, the professors were advised by a statistician that there was a one in 200,000 probability that such a match of wrong answers on the multiple choice questions would occur by chance.
...
Reilly also presented her own statistical analysis of the exam and brought to the professors' attention the possibility of "lure" questions on the exam which would heighten the probability of the match occurring by chance. The professors thereafter obtained a new statistical analysis taking into account "lure" questions on the exam. This analysis demonstrated a one in 500 to one in 5000 probability of the match occurring by chance.

Whether this kind of evidence is enough to initiate disciplinary proceedings, and what the consequences could be, depends entirely on the detailed specifics of the scenario and the university policy.
For example, in Papelino v. Albany College of Pharmacy vs Union University, while similar statistical evidence raised suspicions, it was not considered sufficient to conclude that the students had cheated.

These court cases are interesting but I'm worried that focusing on the legal system might give OP the wrong impression.  My understanding is that it would be very unusual for the courts to get involved when a professor accuses a student of cheating.  (Of course the student can try to sue to school but this is almost always just a waste of time.)  Although plaintiffs won in Papelino I would guess this is not relevant to the OP because that was a Title IX retaliation claim.

@Trevor Sure. The point is that suspicions may be raised just by looking at the exam paper. The court records happen to provide several examples of this. (Generally academic dishonesty proceedings are not publicly available unless it happens to go to court.)

I'm not familiar with the case, but I'd say that there's a good chance that in, say, thirty years of US university tests you'll get a couple of 200k to 1 coincidences. It reminds me of the Sally Clark case (albeit a little less depressing).

Here is one way to catch someone cheating without seeing them do it.   Plagiarism.  You have no idea how many times in online courses I see fellow classmates simply copy paste from sources and not cite them, but in my experience, I get professors that ignore plagiarism for some reason and do not enforce the honor code.  Usually they are tenured, the adjuncts are bit more on the ball

@NZKshatriya: On the other hand I have seen documentation of identical student work in computer science being confirmed to be independent.


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Does GPA/Transcript matter for academic jobs after the PhD?
Courses taken and GPA can matter quite significantly for undergraduates, both for applying to graduate school and applying for jobs. What about courses taken and GPA during PhD? Do they matter at all for postdoc/professorship application? Do postdoc/professorship application usually ask for a transcript? What about for industry positions? Are there positions that would care about "good grades" or "advanced courses taken" during PhD?
I would guess the answer is largely negative, but I'm willing to hear other opinions.

Related (possible duplicate): How important are my grades to the rest of my PhD career?

@ff524 Thanks, I've added one aspect that I'm particularly curious about (and hasn't been addressed in the linked question.)

In my experience on many search committees I've never looked in detail at the coursework or grades of an applicant.  We have however required transcripts as proof of the academic degrees that the applicants claim.

For what it's worth, I've served on dozens of faculty hiring committees at an R1 institution and I have never had a transcript made available to me as part of the application materials. So not only do we not care, even if we did care we wouldn't have the ability to do anything about it. It's true that competition is intense and any relevant edge helps--but grades aren't even part of the contest.
Perhaps things are different in industry or possibly even at teaching institutions, though in the latter case I doubt it.

Yes, applying for academic jobs and post-docs will require your transcripts. How seriously they view the grades will vary from institution to institution. I would suggest, however, that while low grades may not exclude you from consideration, they certainly don't help. Coursework during a PhD is essentially training. You are being trained for your work as an academic. How well you fare in that training reflect something about you.
If you have a stellar publication record, fantastic references, and a killer dissertation, grades are likely not very important. But just remember, you're going to be competing against hundreds of other applicants for a job. Do you really want your transcript to be full of Bs? In a pool of candidates with 4.0 GPAs, you don't want to be the guy with a 3.0.

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How would we identify a better measure of academic productivity?
Measures of academic productivity, like the h-index, m-index, i10-index are useful but imperfect. Their imperfections are more than an abstract concern. Hiring committees consider them in determining how the applicant stands in relation to his peers. The weight committees give to these numbers varies, especially with newer metrics.
How do we know which measurement of scientific productivity is the most accurate? This question suggests that no measure is accepted as generally accurate. The h-index has a retrospective validation for some fields. Have studies tracked a cohort of scientists over time to compare the ability of these measurements to predict who received a tenure-track appointment in the next five years? (I realize that is not everyone's goal. It is one that tenure committees care about.)

If I had the answer, I would be publishing it in Nature (and collecting lots of citations, hehe). I find this question akin to ask what is the solution to Navier Stokes in Physics SE, or if P=NP in CS.

Because promotion committees use these metrics in deciding who gets promoted, you cannot disambiguate causation.

With respect to predictive validity: ability to predict what? Citations? Tenure?  Future h-index? Prizes? National Academy Membership?

@Corvus point taken, I meant tenure, edited.

Not entirely sure if Goodhart's Law applies here. http://en.wikipedia.org/wiki/Goodhart%27s_law

The question in the title and the last question in the body are totally different. My down vote is for the question in the title  which is ill posed. I would prefer the question to focus on "What metrics have been successful in predicting academic success?"

@DIrk the last question resulted from replying to Corvus' comment "ability to predict what", a tenure-track appointment is one definition of academic success, but less broad and so perhaps answerable.

I don't know that anyone has done this on a broad scale for tenure. There is a fairly recent study that used a machine learning approach to figure out what metrics are predictive of success in achieving a faculty position.
van Dijk, D., Manor, O., & Carey, L. B. (2014). Publication metrics and success on the academic job market. Current Biology, 24(11), R516-R517.
For an overview and a simplied version of the application, see this Science Careers story.
From the paper's summary:

The number of applicants vastly outnumbers the available academic
  faculty positions. What makes a successful academic job market
  candidate is the subject of much current discussion [1–4] . Yet, so
  far there has been no quantitative analysis of who becomes a principal
  investigator (PI). We here use a machine-learning approach to predict
  who becomes a PI, based on data from over 25,000 scientists in PubMed.
  We show that success in academia is predictable. It depends on the
  number of publications, the impact factor (IF) of the journals in
  which those papers are published, and the number of papers that
  receive more citations than average for the journal in which they were
  published (citations/IF). However, both the scientist’s gender and the
  rank of their university are also of importance, suggesting that
  non-publication features play a statistically significant role in the
  academic hiring process. Our model (www.pipredictor.com) allows anyone
  to calculate their likelihood of becoming a PI.

tl;dr Publish lots of papers that get lots of citations in good journals. But you knew that already.

This study, while a good descriptive work, does not separate cause and effect.  It does not actually study productivity, but rather the way that people are judged on their productivity, which just brings us back to the original question.

@jakebeal I agree one hundred percent. But in the post and my clarification comments, the OP specifies that he is interested in measuring productivity by whether or not people get tenure: "Have studies tracked a cohort of scientists over time to compare the ability of these measurements to predict who received a tenure-track appointment in the next five years? " This issue, like hiring, depends on the way that people are judged by their productivity. So I believe the study I describe is as close to what the OP seeks as one can find.

I wonder why gender is a factor. It suggests to me that the model is reflecting the biases of the data set. That's understandable, although the authors don't try to correct for that.

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Authorship - How to determine
I have a personal relationship with a psychology professor. We have 2 situations where I may have some claim on authorship but I'm not confident.

I was a participant in a research project in the spring semester. Due to my performance, I was asked to continue. The theory behind the research is that getting 2 types of training will improve learning of a specific task. Each session, I received both types of training.
He wasn't happy with the data from the spring semester. After spending hours looking at the data, he found some way to eek out an abstract. As we continued, I started to realize that although my performance varied from session to session, I either increased or decreased on both tasks. In other words, I thought that if I did better with Training A on Tuesday, I also did better on Training B. If I did worse on Wednesday, I would do worse on both tasks.
I told him about this. He looked at those particular data and I was right. There was a clear correlation. Within a few hours, he was saying it would be publishable.
My contention is that he provided the theory for the study but I proposed the hypothesis. He said "You don't think I would have eventually looked at that?" Then I pointed out that he hadn't looked at those data when he was struggling for an abstract. He says I'm just a subject who provided feedback but I did more than that. I predicted the correlation between specific data.
He's been working on a book chapter. His original plan was to write about his subject from the perspective of a different branch of psychology, one in which I hold a masters. His original interpretation was not good and I told him. We spent hours discussing this. I found the main reference on which he is basing this claim. Also, I spent hours teaching him the principles of my area. I gave him the interpretation from the perspective of my discipline which is the point of that section of the chapter.
He had me read the relevant part of the chapter. I found it confusing. He failed to explain some things and implied information that was incorrect. Also, he explained things in an order that would leave the reader confused. He was frustrated because he had not planned to rewrite that section but said "You're right." To be helpful, I sat down and wrote that section myself. Initially, I had given him an example that I'd heard elsewhere. This time, I included a new example that explained things more clearly. I shared the document online and he continued working.
A few hours later we were discussing it and I asked if he was using my new example. He said "No, because I don't want to give you a co-authorship." I was stunned. It's one thing not to give me credit but he is going to a great deal of trouble to avoid crediting me. Later he said he was excited for me to see the acknowledgement.

Yes, I should have discussed authorship with him before making these contributions. Setting that aside, do I have a claim to anything beyond an acknowledgement? I feel like I made "significant intellectual contributions" to both. The study has not been written but I provided a lot of the material for the chapter.

Are you also a member of the same university (as a undergraduate or graduate student, employee, professor, etc.)? If so, is the relationship known to others? I thought he may not want to reveal your relationship by putting you as co-author. Also, if you're a co-author, I would imagine that it's problematic if you're also a study participant.

Maybe the author of the question does not know what "personal relationship" implies.

This sounds very odd to me.  You were a participant of the research group or of the study, meaning you were actual a human subject in a research study, who then analyzed your own data.  It seems that IRB should have defined this line already.  If not, from a personal perspective, psychological tests performed by someone on themselves should not be published as scientifically valid.

Personal relationship is correct and it's public.
I admit that the study is a bit odd. It was afterward that I realized it. Loads of data were collected so it was just one of many possible findings.
My real beef is with the chapter. What about that?

And I have no affiliation with the university.

I don't know about psychology, but in my field experiments on oneself are not publishable. I think the NIH has regulations about that although I can't find the article right now.

This is one of the most singular situations I have ever encountered on this site.  In general, having multiple relationships with the same person can makes things complicated unless the parties are on especially good terms and/or are especially good at setting and respecting boundaries.  Academically collaborating with someone with whom you're romantically involved is not (inherently) a conflict of interest, but it is a source of potential complication for both relationships.  (I say this as someone who has never had both kinds of relationships with the same person, but who has found successfully navigating one or the other type of relationship separately to be complicated enough!)
I am simply bowled over by the fact that you are in a situation where the above two relationships are joined by yet a third: that of a participant in a psychological study.
My academic field (mathematics) is pretty far removed from psychology, so please discount accordingly, but my strong suspicion is that being romantically involved with someone in your psychological research study is already a potentially fatal (to the academic project, I mean!) conflict of interest.  My understanding is that this is the sort of thing that should be cleared with IRB in advance, and in the absence of compelling reason to experiment on you and not someone else the practice looks iffy.  When you compound that with the fact one of the subjects has a personal relationship with the psychologist and that personal contact led to a discussion of the study while the study is ongoing....holy moley.  I think the professor should either submit the entire case to a body who is competent to authoritatively advise on the ethics of the situation or -- and I think this is better -- drop you from the study, remove all data which pertain to you, and consider whether it is worthwhile to try to replicate "your data" on a new and unrelated party.  Continuing on to try to publish in this situation seems like such a bad idea, in which full disclosure and resulting failure to publish in a reputable journal is one of the better-case scenarios.
Having accomplished this, you will have reduced to the only ordinarily complicated double relationship that I mentioned at the beginning: being in a romantic relationship and a possible academic collaboration.  I think you and your psychology professor friend are well overdue for a general talk about the boundaries between your personal and professional relationship.  You don't list your own professional identity, and somehow I gather that you are not a psychology professor.  Nevertheless you have a master's degree in psychology, which is more than enough for conversations about your friend's work to have a potential professional component.  Your interactions with your friend about his work go way beyond the norm for "off-the-job" conversations with friends and significant others.  Namely you:

analyzed his data (from the inside!) in a way that he regarded as making the transition to publishability
gave critical feedback on a subject in which (from the sound of it) you have more expertise than he does
read his writing in detail and gave critical feedback, both on the content and the presentation
rewrote a section of the work, changing the content to what you thought was superior

As it sounds like you know, any one of these contributions could be held up (and has been, at least once on this site) as being sufficient for coauthorship.  In the confluence of all of them -- or let's say the last three, since the first pertains to something which may be to problematic to see the light of day -- I think it would be unethical not to have a conversation in which the coauthorship is carefully discussed and analyzed.  Some may view your contributions as being essential to the point that it could be ethically problematic even for the two of you to agree not to list you as a coauthor: academics are not supposed to get substantial, expert help in their academic work "under the table".

He said "No, because I don't want to give you a co-authorship." I was stunned. It's one thing not to give me credit but he is going to a great deal of trouble to avoid crediting me.

Unfortunately I agree completely.  It's unfortunate because this is really a tough situation: even from a professional ethics standpoint there is nothing to do other than to have the coauthorship conversation with someone who doesn't want to have it.  If I were you I would plan this very carefully in advance.  It may be that you will not be able to salvage both the personal relationship and the academic work you've both done, so it could be helpful for you to go into the situation knowing clearly which one is your priority.  Good luck.

Without delving into the particulars of your case, the IMCJE has suggested four criteria that stipulate who should and who should not be considered an author.

Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND

Drafting the work or revising it critically for important intellectual content; AND

Final approval of the version to be published; AND

Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

They also happen to be supported by COPE, who helpfully also has supplied these guidelines: How to handle authorship disputes: a guide for new researchers


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I found a huge error in my master's thesis which I defended a year ago
I defended my Master's thesis last year and continued on to pursue PhD in the same university under a different adviser. My Master's thesis adviser and I were getting ready to present a paper pertaining to the MS thesis at a conference in two weeks. The paper is already accepted.
Earlier this week, in preparation of showing reports at the conference, I started re-running my Master's thesis code to obtain fresh reports. The results gave me the nastiest shock of my life. The new results I was getting were a magnitude off from the results I had before. I could not believe the new results. Thinking that I had done something wrong in the current run, I re-ran my previous projects which I had used to obtain the results for the thesis document and defense. Even these runs gave me the same results as the new results I was getting. When I dug into it further I realized that I had misinterpreted the value of a single variable which changed all my result values by a magnitude. This reverses half of the conclusions I made and slightly alters the rest. I immediately emailed my adviser for a meeting to discuss this issue. I am meeting with her next week.
In the meantime I am panicking that my adviser or the school board might think that I deliberately presented the wrong values since I was getting better results. I am scared that they might not see my mistake as a mistake or even if they do see it as a mistake, they might take some strict action like revoking my MS degree or suspending me from school or even expulsion. I am panicking. Please advise. Thank you.

"I am panicking. Please advise.": You're doing everything right so far, except for one: Don't panic. Sadly, I regret to inform you that you most likely are human, indeed, and not a robot with no imperfections besides the inability to know you are a robot.

That's unfortunate, but an honest mistake. You won't be "punished" for an honest mistake.

... no biggie ...

Theses are not revoked for honest mistakes. Nor have I seen honest mistakes in academic work leading to expulsion. What you should do? Post an erratum if there is a reasonable place for that. (If it's a maths or CS thesis, I'd consider the arXiv.)

Welcome to the club! Just do your best to "fix" it (erratum/etc) and done. Research isn't sales, the actual numbers don't matter that much, especially in master's level. At this point the "procedure" of science is far more important, and you are experiencing another facet of it now :)

Thank you everyone for the support. I had been freaking out ever since I found out. I am going to take Bryan's advice and calm down.
It's good to know that my mistake might not cost me my thesis, although I am ready to re-defend it with the new results if my adviser deems it necessary. Anyway thank you for the support. I will report back as to how my meeting with my adviser goes.

Correct the mistake for any peer-reviewed publications (journal, conference, etc). Don't worry about the thesis published at your institution.
Reason being, your committee signed off in the work as a whole as fulfilling the merits of the degree. Yes, it's unfortunate, but theses often aren't indexed by journal searches, and even when they are, they are generally interpreted with less weight.
On the bright side, you recognized an error others might not have. Apply this lesson moving forward. In any other case, you'd have to retract.
PS - I did the same thing during my masters thesis. Didn't sleep for a week.

Thank you HEITZ. I am going to discuss this with my adviser and see how she wants me to proceed. Luckily the paper does not need many changes. I checked on the IEEE website and for the conference I submitted to, the papers don't get published till next year; so I hope the editor will let me make changes to the paper.

These things happen. It's unfortunate, but as Bryan said in his comment on your question, we're all only human. You're doing exactly what you should be doing, and now you just have to wait to hear how your department asks you to proceed.
To put things into perspective, the concept of austerity cuts as a method for bolstering economic growth stemmed from an error in a Microsoft Excel spreadsheet. Whoops. Be glad this is just your thesis and not an internationally-recognized research effort that drove over a decade of global economic policy.

Thank you @eykanal. I am going to discuss all options with my adviser and see how she want me to proceed.


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How to survey recommended course readings?
I am interested in analysing the selection and distribution of course readings given to students of middle eastern studies in universities internationally.
By course readings I am referring to subject bibliographies given to students as background reading to accompany lectures, etc. I suspect this would be difficult to investigate, since most course readers are not available online.
Does anyone know of lists, bibliographies, methods or other resources which may help to conduct such a survey of course readings?

Isn't this an xy question ( http://meta.stackexchange.com/questions/66377/what-is-the-xy-problem )? If you want to find bibliographies for a specific topic, why not directly ask that question?

Thanks Silvado, I completely agree. I have rephrased my question accordingly.


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How can I find papers that are not sponsored by industry?
Are there any databases or search filters for published peer-reviewed articles, particularly concerning environmental issues, that are neither affiliated with nor funded by corporate interests?
I am trying to find peer-reviewed articles on the history and impact of plastics pollution. Most articles I have found either have authors affiliated with petroleum/packaging/fast-moving consumer good companies, were commissioned by those companies, or received funding influenced by those companies.
I am not asking whether industry-sponsored papers are less accurate, as this has been asked before. I understand that high-quality independent research can emerge from (and be enabled by) corporate funds, and that every funding source has biases of some kind.
I would just like to know how to find articles whose authors and funding have no corporate ties.
Additionally, I understand that not all connections with industry are apparent. As an example, one article encouraging plastics packaging had no author affiliations but received funding from a major English research council. Although this council describes itself as independent, its directors' declarations of interest contain many corporate ties, including to petroleum giants. Since this is indirect, I would not expect it to qualify as "industry-sponsored."

If you have access to Web of Science, there is an option to sort by funding agencies. Clicking the "more options" link also allows you to exclude funding agencies. It's not perfect since the last time I used it there were quite a lot of false positives & negatives, but it's better than nothing.

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Publishing research using outdated methods
I'm currently an Economics MA student doing a referee report on a paper that employs a dated empirical method. This particular method was originally created in 1980 but then improved upon in 1998 by other researchers, after they had discovered certain issues with it.
This got me thinking about how exactly those on the cutting edge of research seem to lag behind by over a decade (or more) in method and still manage to get published.
This is concerning because it shows that published researchers make mistakes and don't review all relevant research before publishing. I can imagine that in the hard sciences and medicine this would happen also, which is especially concerning knowing that those on the cutting edge could be decades behind in knowledge which has been around for a while.
Is this acceptable? If so, why?

It's not clear to me why the method is "outdated" in this specific case. Could you elaborate on this? So far you only mention that it is from 1998, that means it is 21 years old, but that does not mean that it is outdated.

@holla, the question does not clearly state that the method is outdated. It is implied in the title, but this could be simply a personal opinion. The relevant part in the question itself does not give a reason why the method is outdated, which is why I have asked for clarification. It's really easy to clarify this by adding either "I think the method is outdated because it's so old" or "The method is definitely outdated because there has been a new method that leads to much better results".

Discussion on the general quality of research and researchers moved to chat. Please read this FAQ before posting another comment.

What you call "an outdated method" another may call "the well-understood method".
In neuroscience, this is a very common occurrence. There are new techniques for analyzing different types of neural recordings coming out each month in a number of journals, and each one aims to improve on a specific aspect of a predecessor. Unfortunately, the new techniques are exactly that—new—and therefore untested against lots of data with different initial conditions. There are a good number of researchers who will simply ignore all the new techniques until people have developed them to a place of comfort. Even for those that do gain acceptance, they may not be appropriate for every type of analysis1.
I'm unfamiliar with your specific case, but I have seen similar concepts elsewhere in Econ, where older published techniques remain highly popular because (1) they're well-understood and (2) the new techniques were created to fix problems that not present in all databases, or not relevant for a given analysis. The old fogies sometimes do have something to offer.

1 In one case, a technique called DCM became widely popular in a very short period of time, and consequently was very quickly becoming widely misused. It got so bad that the authors actually published a paper titled "Ten simple rules for dynamic causal modeling" with the goal of educating researchers how to use the technique. (Biomed researchers in general don't have a great track record of performing world-class data analysis, but thats a separate story...)

@holla: The question asks why it would be acceptable to use older methods. This answer says why it is acceptable to use older methods. How does it not answer the question?

@holla, see my other comment, but the question does not state what you are saying it does. It does not describe a "dated method with known issues", it describes a "dated method with known issues that were then fixed in 1998". That's a huge difference and makes it very ambiguous what the actual problem is here.

@Spectrosaurus When I first read the question, I understood it to mean that the paper in question used the 1980 method, despite the availability of a better method from 1998. But on re-reading the question, I see that it could just as easily mean that the paper uses the 1998 method.

What you are describing is not uncommon. In my field people still use methods developed 50 years ago. Some of these methods are still valid and have proven to be robust, some of these are flawed with known improvement, and some of these are down right logically inconsistent but people still use them because of inertia.
Whether using an outdated method is a critical flaw in a paper depends on many factors. But it eventually comes down to whether the flaw in the method invalidates the main conclusion. For example, if the main result is qualitative, and the improvement from the  new method is incremental, then it's not a big deal. If the result is supported by multiple lines of evidence, then the fact that one of them is flawed is then less severe of a problem. If the method is known to fail in special cases and it is clear that the data do not fall into such cases, then it is also not a big concern.
Overall, for better or worse, people are going to be more forgiving if the newer method is not well known or the improvement is marginal.

This reminds me of an occasion where a university Vice Chancellor told a department head that they need to update their programme and not continue teaching concepts that are hundreds of years old... such as the methods developed by Newton, Fourier, Leibniz, etc.

Using 50-year-old methods that work well is not so bad as publishing papers that claim to have rediscovered them. I've seen that more than once in my own field. It's easy to "forgive" students for not accessing literature that was only ever published on physical paper, but referees should know better IMO.

@alephzero You mean like this paper which invented integration in 1994?

@Mick Please tell me you're joking. OT: The validity of research is not necessarily dictated by the up-to-dateness of the methods. A lot of current research in natural sciences is based on methods from the 60's which were deemed unfeasible but are now used because raw comp. power is available which makes them feasible (and the methods are easy to comprehend).

I'm currently ... doing a referee report on a paper...  [Author did X]  Is this acceptable?

You're the referee, so you tell us!
As a referee you have the authority to use your discretion here and decide what kind of recommendation you want to give to the editor.  You have identified that the authors use an outdated method of analysis that has some problems highlighted in later literature.  You should point this out in your review, and you will then need to decide how big of an issue this is.  Is the old method sufficiently poor that the method should be revised to the improved method from 1998?  If so then perhaps a revise and resubmit might be appropriate (assuming other aspects of the paper are okay).

This got me thinking about how exactly those on the cutting edge of
  research seem to lag behind by over a decade (or more) in method and
  still manage to get published.

This is not at all uncommon. It happens to many well-known techniques too.
Symbolic execution was invented in 1976. But it had been dead for decades until being resurrected around 2005 (thanks to significant advances in constraint solving). Now, it is popular, used in Google, Microsoft, NASA etc. All winning teams in DARPA Cyber Grand Challenge used it, the top team was bought by the Pentagon. What a comeback.
Similar story about neural network, it was crashed to dead by SVM (with kernel methods) years ago. It is now resurrected with a new fancy name: deep learning.

@holla, I don't think that's fair, I have never read a paper that doesn't endorse the method they use. The question is whether it really is good. OP says the trend has moved on and the method in question is accepted as not interesting anymore. As qsp points out if this was cause to prevent publication we wouldn't get revived methods, but we do!

I would say that in it's own right, that a better method exists does not, and should not, invalidate research.
It might be worth noting that if: a better method exists, has been used, and provides strictly better results that an outdated method does little or nothing to improve upon, then that's a different story.
To reiterate, I would be very uncomfortable citing "could have done better", on it's own, as a rebuttal.
For what its worth, my field mostly involves computational modelling and new methods are a frequent occurrence. The entire field only ever publishing with the latest and greatest methods would be almost inconceivable, and perhaps that effects my opinion more than it should in other fields.

@holla I didn't say it shouldn't be a factor. It may well not be interesting, I think I made that caveat clear, but it doesn't make it not interesting either. It's necessary to exercise judgement.

@holla The research can well be interesting, even ground-breaking. The methods are just a tool. If you are using the tool to find out interesting stuff in your subject, the tool can well use older methods. In urban climate and wind engeneering many use computational methods for solving fluid flow developed in the 1970s to 1990s. There is huge iterature threafter, but you don't need the most recent methods of computational  fluid dynamics to find out interesting results. The older ones still work and often converge to the correct result.

authors: Vladimir F Героям слава


text:
asking professor to fund Master's student
I am a graduate Masters student from one of the top-tier universities in the US. I have been working closely with a Professor and two of his Ph.D students on a Research Project for the past two months. I approached the Professor out of my interest, hoping to gain some research experience. I have plans of pursuing a Ph.D. in the near future, and I am totally enjoying this research experience under his supervision.  Quite recently he told me that he would add me as one of the co-authors if I completed an analysis for the work I have been working on.
It's a well-known fact in my university that usually Masters students are not funded. I expressed my interest to continue working with him right through the next few semesters, and he replied back saying he was glad to supervise me, adding that he has been enjoying my enthusiasm and productivity. On an average, I spend ~30 hours every week on Research and to my knowledge, my Professor has a lot of funding. I was just wondering if I could request him for any possible funding, such as a standard 20-hour student worker position, if not a tuition waiver because it's very expensive here. Doing other on-campus job besides all this to manage my monthly living expenses, might get too hectic (heavy coursework next semester+research+20 hours on-campus job). I am so hesitant to ask him this, fearing that he might start thinking I have been doing all this for the sake of getting funded, which has not been my intention.
Should I just refrain from asking him about funding as a Masters student to maintain this healthy student-supervisor relationship that I have with him, or is it ok to ask him about funding me?

You might be mistaken about your professor having funding in abundance. Even if he has managed to bring in a lot of funding, he might be spending it all on research and researchers.
One possible way to address this might be to approach your professor at an appropriate time and gently bring up the possibility of receiving funding for your work. I would even leave it up to him how many hours per week should be paid.
As a matter of fact, you might mention immediately that you also keep working if there is no pay. It might seem that you will not receive anything when you mention this, but your professor might feel that it is morally right to provide some funding, and it will make the conversation less awkward.

You are hesitating to bring this up directly with this professor.  The relationship is going well, but is not completely consolidated yet.  I can understand your feeling of uncertainty.
The solution might involve switching programs.  It really depends on the institution and the department.  I suggest starting by having a confidential conversation with an administrator or academic advisor in your department that you think is student-centered, positive and discreet.

authors: สุทธิสาร ปานสัสดี


text:
I received an acceptance letter. Before publication the EIC rejected!

March 2018: I submitted my paper in a Q2 journal. The Editor in Chief (EIC) approved for peer review. He sent it to Editor for Europe.
April 2018: I was asked by the Editor for Europe to re-submit it with changes.
May 2018: I re-submitted the paper. The EIC approved for review. The Editor for Europe sent out for peer review.
September 2018: I received a positive feedback by the reviewers. The Editor for Europe asked me for minor changes.
Early October 2018: I submitted a revised manuscript.
Mid-October 2018: I received an acceptance letter by the EIC and a congrats email by the Editor for Europe asking me to wait for the proof to check before publication.
End of October: I received a new reject letter by the EIC!

I asked for clarification. The EIC said that my response rate was low. He did not even apologize for the frustration they caused me for a long 8-month process and an amateur treatment. Nevertheless, I re-submitted the paper correcting a number that dropped the response rate; as he suggested. I received another reject letter.
My final response to the EIC: "I can accept nothing less than proceeding to the publication of my paper as it was accepted by you (reviewed by the Editor for Europe and by two reviewers); " The acceptance letter was attached with my letter. I am now waiting for his response within 48 hours" although I am not waiting for any change in his decision.
My questions:

Did this happen to anyone of you? If yes, what was the final outcome?
Is there a legal path to ask for my right to publish my paper?

I also worry for my data; it took me 6 months to finalize emails with repondents' list.

Why do you think you can force them to publish?

What is a response rate in this case?

What is, and what is the significance of, "response rate"? Is it a statistic that you develop in the paper? Is it something you cite? Is it something about other peoples' response to your paper? Specifically, what is it that it could cause rejection? What does "correct" response rate mean? Factually accurate? An assumption? Something you cited correctly/incorrectly?

So the editor noticed that the response rate was too low for the conclusions, then when this was pointed out you changed the reported response rate to the "correct" number? You don't see that this appears suspect?

I also worry for my data; it took me 6 months to finalize emails with repondents' list. It must be nice to work in a field where 6 months is a long time to work.

I am voting to close this question as "Unclear what you're asking". It could also be closed as "Opinion-based".  At present the question seems like a rant that is looking for sympathetic answers rather than asking for a specific and objective answer. If you have a specific question, please edit the question so that's clear. "Did that happen to you?" is not a useful question; and the answer to "Is there a legal path to force someone to publish your paper?" is so obviously "No" that it's not worth asking.


text:
Graduate students funding availability in Pure vs Applied Math
Universities in the U.S. are sometimes limited in how many students they can accept by the available funding. How does funding compare in Pure vs. Applied departments? Is one generally more funded than the other? Is this less of an issue the higher ranked a university?

Most math "funding" in the US is in the form of TA, or, less likely, RA funding. Since TA funding is paid back to the university by participation in assisting (or even teaching) courses, it isn't really a big "expense". Without TAs, lower level courses would need more faculty participation - smaller classes in most places.
So, the number of slots is less determined by some "funding" available than by the sheer size of the department and its need for assistants in lower level (and especially service) classes. Math needs a lot of this since the math department also commonly services most of the rest of the university in its need for some specialized math and maybe statistics courses.
I don't know current statistics, but I'd guess that if a university has separate pure and applied math departments, that the pure math side is bigger, hence more need, hence more slots.
But it also used to be the case that such departments were unified with pure and applied math in one department. In that case, it is immaterial what a student wants to study for the purpose of funding. A TA will still assist in first year courses offered, so the overall size of the department and the number of courses/sections it offers in the lower division is the dominant factor.
And this is independent of the "rank" of a university, though a few top places might have more RA slots that are grant funded rather than coming out of the instructional budget.

And, funding in the sense of "come and study here for free with no obligations or duties" is pretty rare.

I agree that math departments might have more funded slots than applied math departments, but it might be that some applied math departments bring in bigger grants and offer higher stipends.  Though this is just speculation.

@Kimball It can go either way, but it's roughly true that the top-ranked pure math departments and the top-ranked applied math departments are at different schools.

Undergraduates students majoring in STEM fields (science, technology, engineering, and mathematics) typically take more required math courses than students in other fields.  At a STEM focused institution you're likely to find a bigger math department (relative to the overall size of the institution) and more teaching assistnat slots.  At institutions without engineering schools you'll see the opposite effect.

@Kimball  TA/RA funding is often standardized across an institution.  Students in applied math are certainly more likely to get research assistantships, but that doesn't mean that they'll be paid better.

@BrianBorchers I wonder how common that is.  At my university, there are minimum standards, but the actual grad salaries vary by department (and possibly type of appointment)---I think the pay is highest in engineering or business and probably lowest in the humanities.


text:
How are MS and MA programs in Mathematics different?
Most graduate programs in Math only offer a PhD program, but some provide either an MS or MA in Math. Are there any significant differences I should be aware of between the two, or are they practically identical?
Does an MS provide better preparation for PhD while an MA provides a better teaching experience? Does it depend on the university and course requirements?
Also, is there a general perception from academic or industry employers on one being better than the other?

This likely varies a lot from one institution to another, but at the institution where I earned my bachelors and masters degrees, the difference between a BA and BS, (and the difference between an MA and an MS) came down to whether or not you took a foreign language.  If you had sufficient foreign language hours, you could get a BA/MA.  Otherwise, you took CS classes, and got a BS/MS.

There might not be any difference at all. My masters is an MA from an R1 university. I had the choice of degrees just by applying for one or the other. There was no difference in requirements. I took the MA since my math undergraduate was a BA, and again, I had the choice, but only there because I'd taken various humanities courses as well as math.
It might also just be up to the university what to call the degree and how the university is organized. In many, maybe most, US universities, the math department is in the Liberal Arts division or school. So MA might be more common there, where if it is part of the Engineering school an MS would be more natural.
It might also be reasonable to make a distinction for pure math (MA, perhaps) and applied math (MS). Applied math can depend on use of the scientific method as found in science, where pure math seldom does.
But, the requirements are likely to be very similar, if not identical. No one ever blinked at the titles of my degrees: BA, MA, PhD.
Some schools might differ from this of course and want some way to distinguish between a degree with thesis and one without. But you can still be a success with either option.

But note, also, that "most graduate programs in Math only offer a PhD program" is probably incorrect. Some_ might not accept students for only a masters (US perspective), but doctoral students may still be able earn a masters along the way, sometimes just by asking, sometimes by writing a separate thesis (my personal case), and sometimes as a consolation prize for those who drop out.
Of course in those places that require a masters for entry into a doctoral program, that might be the only option.

Indeed, seems mostly a university-specific thing. Princeton's CS department offers both an AB and BSE degree in computer science. As it says on their FAQ page, "Should I choose one degree over the other depending on what I want to do after graduation?
Our experience is that employers and graduate schools do not care whether you're an AB or a BSE (and most don't understand the distinction)."

At least one university I'm familiar with, secondary teachers got MAs in math, and the rest MSes.

I believe that at my university, the general education requirements are different between BS and BA degrees. BS degrees have to have a certain number of "hard sciences" classes (physics, chemistry, biology) whereas that number is smaller for a BA where instead the number of social sciences credit hours is larger.

@WolfgangBangerth, as it was at mine. I'd just fulfilled requirements for both so got to choose either.


text:
Is it ethical to withdraw a paper after reviews?
I have a submitted a paper to a IEEE letter. Unfortunately, at a later stage I noticed that letter is still in process to have an impact factor.
I already received reviews from reviewers and the journal is willing to
accept the paper after minor revision.
Is it ethical to withdraw the paper at this stage?

Pretty-much-duplicate: How to withdraw an under review manuscript from a journal when you decide you want to submit to another journal with a higher impact factor? See in particular the top voted answer.

Another quite similar question: https://academia.stackexchange.com/questions/21742/is-it-ethical-to-withdraw-a-paper-after-acceptance-in-order-to-resubmit-to-a-bet

It is fine (and ethical) to withdraw your paper at any stage. Also, you have no obligation to justify the withdrawal (but the editor will be curious, of course). The reviewers have put in work so it may not be NICE, but that is another story. In the end it is YOUR work and your paper, and you can decide what to do with it. If it deserves to be published in a (much) better journal: go for it.
On the other hand, if the journal is not a "predatory journal", your paper is close to being accepted, and the possible increase in impact factor is minor, it may not be worth the extra work to change the formatting and go through the whole review process again.

I think it is not ethical to retract if the reviewers already have done the job (and a proper job, as befits a solid journal). Reviewers already have the unpleasant job of filtering out papers, and if I were a reviewer that has seen already a paper submitted somewhere else, and would be expected to re-review it, I would be wondering what the reason for rejection was.

If I learned that I had invested some hours' work to review a paper, only to have the author retract it because he is not happy with the journal, I would feel rather pissed indeed. If the review is open and I know the author's name, I would consider refusing to review any more of this author's work, because there are few things more disrespectful of an academic than wasting his time. No, retracting after reviews is not ethical. -1.

@StephanKolassa Stated better than I did. Definitely disrespect for the time of the academics.

The few hours of work the reviewers did are nothing compared to the possible effect on the author's career when the paper is published in a journal of lower quality. The paper may for example not be counted for a grant proposal because its impact factor is below a threshold. Being disrespectful and making reviewers "pissed" is not good, but it is definitely NOT unethical. People make mistakes and have the right to correct them, even if this causes others to do more (unnecessary) work.

I do agree with you. But i would disagree with being pissed. @StephanKolassa

@louic Other researchers have a career, too. They put their own work at the back burner and invest several valuable hours to review the paper, and they get, sorry to say, a "slap in the face". If they are serious researchers who have agreed to review for an even not so good journal or paper, OP has now deprived them of several hours of productive work for absolutely nothing. And frankly, if impact factor hunting is a sufficient motive for a retraction, it is even worse; it is applying the wholly wrong principles. Some of the best (and most cited) papers are in low-impact factor outlets.

I perfectly understand. It is annoying. But changing journal because a genuine mistake was made is NOT unethical. It may be unethical to submit to a low-ranked journal with the purpose to get reviews, improve the paper, and then retract and re-submit to a better journal. Also, your "valuable" work is not wasted, it improved the paper and contributed to better science. You did your contribution to science as a reviewer. Great, well done. If you don't want to "waste" your "valuable" time maybe you should stop reviewing altogether.

@louic True, a good review might be able to help the author improve the paper, no matter where it is published - so far I agree with you (although the review mechanism is defanged by switching journals). You suggest that, as a response to journal switching, to not waste valuable time I should stop reviewing altogether? I disagree with your logic: rather what OP and you implicitly imply is that one should stop reviewing for lesser known journals, because chances are that the review might be wasted. Perhaps you are right, but I believe in supporting serious, even if less elitist, journals.

I have neither said nor implied that one should stop reviewing for "lesser" journals. As for the retraction being ethical or not: let's agree to disagree; ethics is by definition subjective.

There is nothing to do with ethics as question asks. This is simple professionalism. The journal has devoted enough time for reviewing the manuscript. The reviewers have put in their efforts.
If you are really fixed about not go ahead with submission of revised manuscript, then do the following:

Don't submit the revised manuscript to the journal.
If the journal editor asks about the revision, then say that you are extending the article in various ways and would not submit the manuscript. But, thank them for their efforts.

But, I would suggest that you had made a mistake not looking at the journal statistics, you should go ahead with this journal with the publication.

Yes, I made a mistake as I mixed up the name of journal while look for impact factor.

So you are stating that (1) The submitter should delay the process by not submitting a revision without notifying the editor, and (2) The submitter should lie to the editor by stating that they are extending the article, and (3) The submitter should not be allowed to correct their mistake. I wish I could downvote three times.

When you submitted the paper, you entered into an informal contract. Based on this contract, the journal expended resources as did others. Ethically, you are bound by the contract unless the contract is invalid. A possible reason for being invalid is deception (The journal pretends to be another journal, but this is not likely with IEEE). Another reason is disproportionate bad consequences (E.g. you need a publication in an approved journal for the Ph.D. , but the journal is not approved by your graduate school.) In the latter case, the damage done to the journal is minor compared to the damage it does to yourself. You would still need to explain this to the editor and apologize. A third reason is that the journal did not treat you with respect.
The contract is informal because it cannot be enforced. But if you get a reputation of violating these types of informal contracts repeatedly, you might find that your career has become much more difficult.


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How acceptable is it to copy and paste a certain structure and some particular sentences in letters of recommendation?
I hope this isn't a silly question, but I was wondering how acceptable it'd be to copy and paste a certain structure and some particular sentences in letters of recommendation.
Of course, I'm not thinking of copying and pasting anything very specific about the candidate, but there are certain traits that are shared among students and I also have a certain structure that I like and ties nicely with particular sentences (e.g., when talking about the student as being collegial, responsible, always meeting deadlines etc.). I'm not good with words so the truth is that the more I can reuse the phrases that I like, the faster I can write it and the quality of the text will likely be better as well.
Would this be flagged by some review software? If it is, would one regard it as unethical to reuse stretches of previous letters? I should clarify that all the particular strengths, projects etc. of the student won't be copied and pasted, just sentences about general traits and so forth, or greetings, paragraph transitions, all the repetitive stuff. I guess my real question is: is it ok to use a standard template and just make the required adjustments? Or do I need to keep rephrasing the same points?

At one point I was on a master's admission committee at a specific state school which always got applications from the various smaller state schools. One professor at a very tiny school kept sending nearly identical recommendation letters to us for students each year. It did not help the students very much. And it especially did not when part of their boilerplate language was the same extreme praise.

Using a template is totally fine. I do that, as does every professor I know. In fact, I shared a chunk of my template in an answer to another question. A lot of those sentences get reused in letters I write, and tailored to the individual person. It's usually a good idea to start with a letter you wrote for a similar student applying to similar things (e.g., PhD programs vs REUs).

Would this be flagged by some review software?

There is no review software designed to prevent this practice, because it's so widespread.

If it is, would one regard it as unethical to reuse stretches of previous letters?

It's not unethical.

I guess my real question is: is it ok to use a standard template and just make the required adjustments? Or do I need to keep rephrasing the same points?

It's fine to use a template and make the required adjustments. There are more important things to spend your time on than writing every letter of recommendation from scratch!

@Fe2O3 It's hard to imagine a less useful activity than wordsmithing a letter of recommendation so that no words/sentences in it have ever appeared in another LOR I've ever written. I've written around 100 in my life. There's only so many ways to say "Student X took course Y with me and was a top student..." Certainly I think sharing my experience and advice with people here is more useful than such wordsmithing.

What is a good use of time is to write about the specific project student X did, why it was impressive, and why it shows they will be successful in grad school. And I do that. But, having a template for the standard stuff means I can write a letter of recommendation in 1 hour instead of 4 hours if I was writing it entirely from scratch.

@Fe2O3 It's not fluff. If it's missing it says a lot.

Generic and boilerplate text has the property that it comes across as, well, generic and boilerplate. For this reason, an effective letter of recommendation will contain descriptions of an individual that are specific to that person. People simply do not find generic praise compelling or persuasive. So if you want to make your description of someone as collegial or responsible convincing, it's pretty essential to give some specific details of actual behavior that gave you that positive impression. That's what I try to do when writing letters of recommendation; it's basically the show, don't tell principle of writing.
Coming back to your question: if your letter conforms to the principle of containing a good amount of details specific to the person you are writing about, but also contains some boilerplate/copied-and-pasted language, I think that's fine. But if your idea was that through reusing content from past letters you could escape the need to formulate a coherent description of a specific individual and why they need to be hired/admitted/given a fellowship/etc, I think that's a very misguided idea, as a letter without those kinds of details will simply be completely ineffective and won't provide any benefit for the student's applications. Whether it's ethical to write such a letter becomes the question of whether it's ethical to write a useless letter, knowing that it's useless. I think the answer is pretty clear.

On the one hand, you're copying from yourself, so there's no issue of plagiarism or copyright violation or anything like that. I don't see any legal or ethical issue.
I don't know if job recruiters use plagiarism detection software. Would they do some sort of automated review that would spot the repetition? I don't know. I'd guess not. No one is concerned about plagiarism in a letter of recommendation. Even if it was true that someone copied a letter of recommendation off the Internet and then edited it up, so what? The HR department isn't grading the letter of recommendation for originality. They're evaluating the job candidate.
What WOULD concern me is if the HR department got two letters from you for two different students and noticed they were almost identical. At that point they might conclude you weren't really writing about the individual student but just had a stock letter of recommendation that you sent out for anyone who asked for it.
If the template part is truly only the most generic stuff, "I am a professor at Foobar College and ____________ asked me for a letter of recommendation" or some such, I doubt anyone would worry about it. But if you had standard phrases that you used for every student, "_______ is very hard-working and intelligent", etc, that might make an HR person think that you really didn't put any thought into this.


text:
Author refuses sharing his "open access" code/data
My doctoral project required me to learn a whole new method from zero. My advisor had another student who mastered the technique since his BA studies, and so was much more advanced than me. I asked this student several times to share his code with me, but he claimed that his research was "classified" (No, it was not), so he is not allowed to share it.
Now his papers are published in open access journals under the statement

Scripts using the R and MATLAB programming language are provided to produce figures and extract data from external databases. Additional code and related files are available from the corresponding author (him) upon request.

Only that now he is ignoring my emails.
Is there anything I can do? The truth is I want to use his codes simply because I want to learn from him.

You should discuss this with your advisor and have them determine the best approach.

Yes, I've considered doing this. I'll try to write to him once again and, if still no reply, I'll ask our advisor

I wouldn't share my code if I expect you to learn the basics, or that giving you my code means I now have to spend time teaching you.  I had students asking me for source code so that they can complete their assignment.  I suggest that you learn to code the method yourself, and only ask for specific advice or missing steps or tips when you are truly stuck.  Do not ask for the whole source code.

@Prof.SantaClaus some people including myself can learn by reading code.

@FranckDernoncourt sure.  Many students prefer to do that because that's what they are familiar with.  For example, in my area, most concepts are described mathematically, and students prefer to read source code as opposed to mathematics.    However, from my perspective, they cannot run away from mathematics.

Here are the typical steps to follow until you got the code:

Email the student who has the code. Send a reminder after a few days.
Email the student who has the code and CC the student's advisor and/or co-authors. Send a reminder after a few days.
If you can meet either student or better the student's advisor face-to-face, try it.
If none of the co-authors is your advisor or close to you, email the journal to raise a formal complaint that the author didn't send you the code. Attach your previous emails to the student who has the code as a proof. If one of the co-authors is your advisor or close to you, explain the situation and get them to put pressure on the student who has the code, to comply with the open access requirement of the journal.

That should resolve the issue in most cases.

PS:

His papers are published in open access journals.

Note that "open access journal" doesn't entail open source code. Neither the journal nor the student who has the code has any legal obligation to share their code (unless some special cases, e.g. if the student's funding agency forces them to do so in their funding clauses).

Step 4 is interesting; would a journal be obligated to intervene in such a case? Especially because the complainant can't attach proof of not having received the code (only of having asked). This would mean that the journal needs to arbitrate and spend resources on ascertaining if the code has been shared in full etc.

@AppliedAcademic no legal obligation, but it's rather fast for them to email the authors with complainant in CC asking for the code. At the end of the day,  the student who has the code has no legal obligation to share their code (unless some special cases eg if their funding forces them to do so).

+1 for open access journal doesn't entail open source code

Makes sense. This would not be grounds for the journal to issue a retraction, IMO.

Thanks a lot! Indeed, I prefer not to write to the journals, and also not to get our advisor involved. Pay attention that he is signed on "Additional code and related files are available from the corresponding author (him) upon request.". That means he is suppose to share it if requested

Two nits on this answer: (1) This would work for a general case of getting code, but in this case it appears that the student is a former lab mate under the same advisor. This is overly formal for that situation. (2) Your step #4 seems a bit much. As a journal editor I would probably ignore such an email as code sharing is good but not required. (Obviously this would change if it were a requirement.)

@eykanal why are steps 1 to 3 too formal? step 4 is last resort, better than giving up and coding for 2 months imho.

@FranckDernoncourt I view the OP's situation in the class of "problems with lab mate", rather than "problem with random other researcher." Getting co-authors involved is a bit much. Of course emailing and meeting is fine, but the overall described progression feels heavy to me.

@eykanal what would you do if step 1 fails?

Talk to my (and his) advisor, who managed the project, and get his take on how to proceed.

@eykanal I see, so basically removing step 2 and go straight to step 3. I agree, that makes sense too in this case if the advisor is easy to meet.

I interpret the question as "I need code to do stuff, how?".

The classic option, the one that you are doomed to use if everything fails, and the way things were before open code repositories, is: just hire / take a BSc student. They would need to implement that thing from scratch using papers / books on the topic as a part of their job / BSc thesis.
Ask the PI on the project / the corresponding author of the paper, if they would share the code with you. They might not agree. I am sure, other answers will detail on the open access and availability bit, I suspect some internal shenanigans.

Basically asking for code is not the best way to do it in my opinion. You do not want to study the code, you want to do stuff, right? Then ask about it. There are multiple options.

"I need your code, because I want to understand how it works / reproduce the results in the paper." That's what the availability thing is for, officially.
"I want to build upon your code to produce new research results." This is the most favourable version. Mostly implied with it (but it does not hurt to state it explicitly) is: "you get to be a coauthor on the new paper".
"I want to apply your method to my data and to use the results in my paper." It is a milder version of the above. Some authors are not inclined / not allowed to give the code to anyone. (This behaviour becomes less frequent, for good, but is still present.) Still, they might be interested in a collaboration. A possibility is to give them your data (if you, on your end, are comfortable with it), let them process it, obtain the results. Again, it implies "you get to be a coauthor", as they do work for your new paper.
"I want to compare your method to mine." It is a valid concern, in most of the cases it produces just a citation of the others' paper.
"I want to do some statistics / automatic code analysis on your code." That's a citation, I'd say.

I'd say that people are in generic more inclined to provide data or to collaborate on one of the above terms that are more exact and clear than just "let me see your code".
I would assume that the most frequent "fears" that lead to not giving code to other people are: "they might 'steal' it" – i.e., an idea that someone would build upon your code and not acknowledge you; and "legal" limitations, ranging from "I have transferred the copyright to my research unit and they don't share" to "my supervisor said 'no'". (Again, I am not discussing here, how the data availability statement of the publication agrees with those.)

Thanks a lot for your detailed answer. The actual email I recently sent him said "I actually try to learn from you, and this could be a huge help". He is just not willing to share. During all these years I made it very clear that all I want is to learn from him.

You are welcome. Well, you'd get code from me with such a mail, but it's little you can do, if they do not agree. The big gun of the availability statement might help, but it is not the focus of my answer.


text:
Decision time on a postdoc offer while applying for other positions
I have recently applied for several postdoctoral positions as well as a lecturing position. A week ago I had an interview for one of the postdoctoral positions and I should know the outcome of this interview by the end of next week. During the interview I was asked if I was applying for other positions, to which I said yes and briefly described what these were.
The project is a very interesting one but I also want to consider the other positions I applied for (especially the lecturing one) if I were to be the preferred candidate. However, I will have to wait until the end of February or so to hear about these other positions.
So, if I was chosen for this postdoc I was interviewed for, I was wondering how long it is acceptable/customary to make them wait until I give them a final response.
I'm sure they would be ok with a couple of weeks, 1. because moving overseas can be a bit of a change from a personal perspective and 2. because considering other potentially interesting opportunities makes sense at this stage in my career, but I was wondering if making them wait for a month or so was too long.That being said, I heard about people making an employer wait four months or so but I would find it rather impolite.
Thanks for your input!

Most likely, you won't be able to "make" them wait at all.  If they give you an offer, they will also give you a deadline to decide whether to accept it.  You can ask for an extension of this deadline, but there are no guarantees that they will agree to extend it.  The power here is mostly on their side, not yours, unless you are really a superstar, or are the one and only qualified candidate.
For a position like a postdoc, the employer typically has a fixed number of positions available (often just one).  Commonly (especially for a field with an academic-year hiring cycle) they interview a number of people and then make offers made serially.  Every day that they wait for you to make a decision is a day in which the next person on their list might take another job, reducing their options if you turn them down.  So it's not in their interest to give you an indefinite amount of time to decide, since that could result in them hiring someone not as good, or not being able to fill the position at all.  They don't want to rush you into declining, but they also can't wait forever.
It's hard to predict what kind of deadline they might give you.  Some employers will give a candidate a very short deadline (a few days) if the candidate is a "reach" - the employer doubts that the candidate will accept, but wants to at least try to get them.  This way, in the likely case that the candidate says no, not much time has been lost.  More commonly, the deadline would be on the order of a week or two.  Having as much time as a month seems unlikely, but there are a lot of factors that could affect it, and if they are not tied to the academic year there may be more flexibility.
What "makes sense" to you from a personal perspective (pondering an overseas move, exploring options, etc) is not really the employer's concern.  Even before receiving the offer, it would be a good idea to carefully consider all the pros and cons, and come to a tentative decision about whether you would take the job if offered (including scenarios about other offers received or not received).  Between the interview and your own research into the institution, you should have almost all the information you're going to get; the only extra information in the offer itself would be the salary (and other benefits).  So ideally, as soon as you get the offer, you should know how you intend to decide, or what other offers you need to wait for.
It's entirely possible that you may have to make a decision on this position before hearing about the others.  That's just how it goes.

It also is entirely possible that the funding is flexible and the PI is willing to wait for a decision. It can never hurt to ask, just be up front about it.


text:
Are there guidelines for choosing colors in figures?
Are there guidelines how to choose colors for figures in papers? I know that about 5-10% of the population see colors differently. How do I create a figure that has to have at least 4-5 different colors in it and make sure everyone will be able to see it and distinguish between the components.

On Graphic Design SE there are many questions and answers that address this issue.

Second on colorbrewer2.org as it also has a function to filter out color blind friendly scheme. This page also introduces a color blind simulator which allows you to upload an illustration and look at how it appears for people with different color perceptions. And lastly, if you can do it with just grey scale or other design, I'd suggest go without color.

Choose colours that can still be distinguished when printed black and white, or go old-school and introduce different patterns/shapes, if possible.

This question already has an answer on TeX.SE

@koalo: Since it's on another SE site, and the question is particularly relevant in academia, I'd say it's on-topic here.

The problem of different color perception (at least with respect to climate science) was pointed out 2004 by Light and Bartlein in EOS. With a strong emphasis on climate science the blog "Climate Lab Book" discusses the problem of the so called "rainbow color scale". As mentioned in the comments they recommend "Color brewer 2" to create color palettes. (There are packages for MATLAB, Python and R. The link to R includes some more advice.) Already pre-defined palettes (again with a strong emphasis on climate science) are presented by the Department of Geography of the University of Oregon. This palettes include color-blind safe ones, as well as palettes useful for specific associations.
For example when displaying temperatures blue is often associated with "cold", while red is associated with "hot". Diverting from similar common associations may prevent an more intuitive understanding of your figures.
Another reason for caution regarding color palettes: "Rainbow" (and similar ones) may distort your perception of boundaries.
To conclude: There appears no easy way to select an appropriate color palette for your figures, but there is plenty of advice.

Different screens may display colors differently due to different color curves (or even display settings). And colors don't scale linearly on most screens, so you can't just use RGB values (not to mention RGB is a poor color space in relation to human perception). Just because it displays well on your screen doesn't mean that it will display the same way for everyone else, regardless of disability. The other issue is that some people print out papers, and may not use color.
To help reduce these problems, you should use a contrast checker. If you have to choose between 4-5 colors, pick colors that each differ enough on this color checker. There are also established standards at least in the web development community, but they should be reasonable that they apply to this as well. Among these guidelines are color contrast requirements.
There are alternatives to using colors to differentiate though. You could also use different shapes or different border designs, etc. Preferably, you could use these in addition to smart color selection, but if your colors have poor contrast, then these can help to further distinguish the various elements in the figure.
Just from personal preference, but colored text (not white or black) almost always looks bad because the characters end up being pretty narrow, and subpixel coloring to avoid anti-aliasing doesn't help here.


text:
Non-consensual authorship order change after paper submission?
After submitting a paper to a conference, my advisor told me that he was going to change the authorship order (putting him as first author, me as last) because he contributed more to the final manuscript, even though I conducted all the experiments. He proceeded to change the order without my consent.
Is this common in academia? I'm a new master's student and I'm not sure if I should just get used to it or change advisors.

Did you agree upon the initial order together or did you just submit it? Normally it's NOT okay to change the order afterwards, especially not without approval of all contributing authors. At least in journal papers, though some fields treat conference contributions in a similar way as other fields (mine) treat journal papers.

We agreed on the initial order together. He did all of the theoretical work and I did performed all experiments. How should I proceed in this situation?

What is the position of your advisor, is he PhD student, postdoc, faculty, professor? Is he independent or are you both working in some other professors group? How much of a role do conference papers play in your field?

He is a tenure-track professor, and we are working on a project that is not part of any group or lab. Conference papers are crucial in my field (Machine Learning).

The review is double-blind, meaning that the pdf does not have authors listed. The final order is chosen when we send the camera-free paper, with the authorship listing. So there is no final author order until the final version of the pdf is sent to the conference.

So you did the experiments based on the theory developed by the professor? Was this the plan from the beginning? And is performing experiments considered a substantial contribution to a paper in your field?

Related: Can a supervisor extend the paper and change the order of authors?

You agreed on something, worked together and he then changed the conditions without your consent. That is not ok in all, neither in academia nor in any business.
However, both in academia and everywhere else, it happens. The question now is: What can you do? Ultimately, you have to decide for yourself. To help you with that, here are some ideas:

He might actually be right that you contributed less than anticipated. Still, changing the order in the last second without giving you the chance to earn first author is not a nice move.
You can simply accept it and be happy to have a (maybe even the first?) publication, even if not at first author. On the other hand, this might mean that he will try the same thing next time.
You can confront your advisor about it. Depending on how he answers, you might decide how to proceed.
You can contact and notify the conference about it. This might mean that you loose the publication and get on your advisors bad side, though.
You can ask others at the institute what they think about it. Maybe they already know the tricks your advisor plays? This might also backfire if you badmouth him to much.

As you see, all options also have drawbacks. Personally, I would try to get a detailed explanation out of him. Don't blame him, rather try to make clear that you want to know your mistakes, want to know how you could have contributed more, to work better on your next paper. If you are lucky, he will point out your weak points, you will agree that you could have done better and everything gets resolved.

Changing authorship order without consent is not common in academia, and this should not have happened. However, rather than asking yourself “what can you do”, as @Dirk Liebhold pointed out, I would ask “what do I want”. Are you going to keep on working with your advisor for a long time or are you leaving immediately after? Is he/she reasonable? If you do not plan on publishing with him, do you really care about pointing out his misconduct?
Keep in mind that last author is not so bad: first author carried out the experiment, but last author is the one who designed or had the idea for it, and possibly the one who found the money to fund it.
In my opinion it is not very important if you are first or last, given that this is only a conference paper , but you should make it clear who is actually going to the conference! Also, if a paper is going to follow on this work, decide the author list in advance with him.

Edit: In some fields (such as computer science), conference papers are peer-reviewed and are at least as important as journal articles, and last authorship carries no prestige.

"given that this is only a conference paper" Nope. In some areas of computer science, a paper at a top conference can make or break an academic career.

Do you mean that being first or last author of a conference paper can make or break a career? And do you mean that conference papers and full peer-review articles have the same weight in computer science? I do not work in this field so I am genuinely curious.

Not sure about that. My point is that the situation is not less bad because it's "only a conference paper". In some fields, conference papers are equally or more important than journal papers.

Thanks for your edit. Just for maximal clarity: in the fields where my comment applies, conference papers are peer-reviewed, too.

@ JeffE Edited accordingly

@JeffE for early career scientist I would argue that it is better to be first author, some people might question why you were the last author and senior authors were first authors.

@user4050 The importance of author order varies by subfield.  Authors of theoretical CS papers always appear in alphabetical order, so there is no prestige attached to first authorship.  In other parts of CS (like machine learning, the topic of OP's paper), it's definitely better to be first author.

@Zep Fixed your edit. CS conference papers are peer-reviewed, sometimes more stringently than journal papers, especially in machine learning.


text:
An author of a paper included a blank supplementary file. Is it possible to make the journal correct this?
The authors of a paper explicitly wrote that they included their code as a supplementary file, and the file is actually available, however, it only includes the header and no code whatsoever. Is it possible to make the journal take notice and correct this issue?

Are you asking as a reviewer, or just as an interested reader?

As a reader. I want to test the methods used by the authors in my own data.

If a file is missing or appears to be missing, then the editor in charge of the paper should obviously be notified, since he or she is the person responsible for managing communications between the authors and the reviewers. (I have done this before when there was an obvious missing document.)

Well, the file is available for download but seems to have been left blank intentionally.

@Lumimoto: "Never attribute to malice that which can be adequately explained by stupidity."  I would proceed under the assumption that it is a mistake that the editors/authors will happily correct when they are informed about it.  Why would the authors write that the code is included if they didn't intend to do so?  If the authors really don't want to share the code, you are out of luck anyway; see https://academia.stackexchange.com/questions/96356/can-one-demand-to-see-code-used-to-generate-an-article/96358#96358.

Is this an old or a new paper - if it is old you may not be the first and, effectively, it won’t happen, but if new, you may be lucky...
Of course, it could be a new paper and they have changed their minds, which leaves you the choices of finding the code elsewhere or coding it yourself...

Obviously the suggestion to produce the code yourself is not well received...


text:
What does "the manuscript has been removed from your Associate Editor Center" mean?
I received the following email:

Dear Prof. X:
  You are no longer assigned to manage the review of Manuscript ID #####. The manuscript has been removed from your Associate Editor Center.

What does it mean? I sent the paper 2 months ago and just today I got the email above. Do I have to wait long as a new editor will check the manuscript?

Is this in response to a paper you submitted, or one you were supposed to referee?

Also, are you Prof. X? Does the manuscript ID match yours?

This question is highly unclear. It seems like this message got into your mailbox by mistake.

From its wording this e-mail is intended for the associate editor managing the manuscript in question. Thus unless you are an associate editor of said journal and were the editor assigned to the paper in question, this mail is not intended for you. Therefore you should not have received this e-mail. That you did receive it anyway means that something went wrong. Contact the journal and tell them what happened.


text:
Where can I publish corrigenda for a conference paper?
I am wondering where I should publish a corrigendum. The paper, which has some wrong numbers in it (nothing major but it still is not correct), has been published in conference proceedings. I don't think a journal would publish a corrigendum for a mere conference article, submitting to the same conference next year does not seem to be the right way to do it either (takes too long, I don't know if they would accept it since there would be not much of a presentation). So I am thinking of a technical report. Would that be a correct way to do it?

If the proceedings is one that was issued by the conference at the same time as the conference (or shortly thereafter), you may be stuck with just publishing it on your website, which is presumably what you meant by a tech report. If the conference was run by a major society, you may at least be able to get the online version of the proceedings updated. You should get in touch with the program chair for the conference at the very least.


text:
Is it better to have just two good letters of recommendation, or two good letters and one bad letter, if three are expected?
Some universities say that "The minimum number of letters of recommendation are 2 but we highly encourage 3". If I know that I can get 2 good letters of recommendation but they "highly encourage 3", should I send in a third?

"Bad" or just not stellar? A letter that says you are a terrible person, have no work ethic, and are as dumb as a post, i.e. one that actively disparages you, could certainly kill your application. A mediocre letter is a somewhat different story.

I was thinking more of "not stellar". Just a so-so letter.

Two and a half is more than two.  :)

@BobRodes That's almost certainly not the right way of looking at this.

A mediocre third letter is generally worse than no third letter, (when a third letter is not required).

@xLeitix Quite so--there's almost certainly no such thing as half a letter.  :)

Is it better to have 2 good letters or recommendation or 2 good and 1 bad letter?

Definitely, it's better to have two good letters.  A bad letter is a very, very bad thing.
They're not counting -- they're reading for understanding.

"They" will also wonder why there weren't 3 letters, since other applicants have 3... "Cherry-picking" faculty contacts suggests itself, etc.

@paulgarrett "The minimum number of letters of recommendation are 2."

@paulgarrett Isn't selecting your letter writers by definition "cherry-picking"?

@xLeitix, sure, selecting 3 is ... selecting... but only being able to come up with 2, instead of 3, is an indicator that one's fan base is 33% smaller, etc.

@paulgarrett On reading the quoted instructions, someone might think, "I have 2 strong letters and one positive but not so strong letter, I'll stop at 2."  Or "I have 2 good letters, and my third reference is in a dig in Asia at the moment, so I'll stop at 2."  Or "I am a returning student and I could only find 2 references after my childrearing gap."  If they require 3 letters they should ask for 3 letters.

@aparente001, "strongly suggested/encouraged" is a pretty strong hint. Not making it a "rule" simply gives flexibility for the decision-makers, but should not be viewed as being "unclear" about what is wanted.

@paulgarrett - How about putting your point of view in an Answer?  (I am not really sure exactly what your point of view is....)

If you can't feel assured that that third letter writer will write a positive letter, forget it.  Don't risk having a negative or even so-so letter in your file.

There are three different dimensions of the value of a recommendation letter that are relevant here:

The quality ascribed by the writer to the recommendee.
The certainty or itensity of that statement.
The reputation of the letter writer himself/herself.

A letter that scores high in the first category, but is less persuasive on the other ones, should not be detrimental. A typical example would be "CANDIDATE attend my course on X, participated well and scored top grades in the exam." This won't get you far, but also shouldn't hold you back.
A letter that is not good because of the first criterion is problematic. A letter which scores very low on the first and very high on the third will probably kill of an application regardless of most other circumenstances.

They may count, or not, depending. My department would count because every application had to qualify for submission for graduate fellowships (policy decision), where 3 means 3. (There was also a quota of "exceptions", they could spend an exception if the candidate was worth it). Not all departments will care. Not all faculty and disciplines have fallen victim to praise-inflation, so a simple letter stating that you did a competent job in your work could be good enough, especially if the writer is known for being conservative in praise.

If only to clarify my comments to other answers: if the "instructions" say "minimum 2 letters, 3 strongly suggested", or similar, it means that the admissions committee reserves the right to consider situations with only 2 letters... but certainly not that it hardly matters. It matters. A solid 3rd letter is fine, and infinitely better than no third letter, for at least two reasons. One is the mere "strongly encouraged" message, which, if effectively disregarded, amounts to a "failed diagnostic". The other is the subtler issue about appraisal of a student's potential: as it happens, it seems possible to get one super-enthusiastic letter, and one more "pretty good", ... but it's hardly to bluff to a third that is "ok". Further, and perhaps surprisingly to students, the "second excellent letter" is very often not-so-sterling-after-all, and this unexpected loss can be compensated by hearing from a third, "disinterested but informed" party, that the student has good chops. So... everyone, including the student, wants that third letter.

Thanks for clarifying your position.  "A solid 3rd letter is fine, and infinitely better than no third letter" is a good point in response to a different question!


text:
Is it appropriate to describe our methodological mistakes in manuscript?
I work outside academia, but am working on a project with a master's student. During data collection, we had some skip-logic errors pop up while administering the survey online and it resulted in some superfluous data. She and her adviser decided to throw out all affected data and only analyze open-field text, and outlined these mistakes in great detail on her master's paper. While writing our joint manuscript for publication, is it appropriate to outline these programming errors?

What's a "skip-logic error"?  What does it mean for them to "pop up"?  What do you mean by "programming error"?  I'm trying to understand better the nature of the error, the cause, etc.

It would be inappropriate not mention the mishaps in my opinion. But there is no need to document this in great detail, as you mentioned. I would comment during the revision process that you feel the description of the "skip-logic section" is too wordy, and it should be trimmed to be more concise.
Keep the focus on the positive findings as opposed to mishaps.

Another option would be to include a brief summary of the error/resulting data loss in the main text and provide more extensive details to interested readers in a Supplementary Info section (if the journal allows this).

I would also mention significant failures in the methodology because it can serve as an important warning for future researchers. For instance, needing to change the number of samples or the testing period because of experimental (or computational) difficulties may be necessary, and it would be helpful for others to know why you needed to change the protocol. In addition, reporting such issues is important for purposes of reproducibility.
However, as the others have posted, there is absolutely no need to spend huge amounts of space discussing such issues, unless your paper is attempting to correct the methodological mistakes of others in the literature.

In the Methods section we detail the process of obtaining data to analysis. Errors resulting in loss of data is a deviation from the said protocol and hence should be reported. The details need not be excruciating fine; a sentence to explain the skip logic pattern and that affected subsections were not analyzed should be sufficient. This is by no means an uncommon practice: there are generic missing, loss of data storage media, biological samples expired, or even contamination in lab. If any of these activities can potentially bias your end result or lower your statistical power, then they should be reported.
Judging from what you said that the student and the supervisor had to throw away all multiple choices and only kept open-ended question, I am guessing the skip pattern problem was extensive? If that's the case, you should try to gain full understanding of the error and carefully decide if any of the data are actually salvageable. For instance, if the skip pattern problem had made the survey questions appear to be illogical, would you still expect the respondents to be in their right mind when filling in the open-ended questions?
The master's paper needs to happen probably because the student has done the due diligence and finished a project, despite with technical errors. But data mishap that is sufficient for a master's thesis does not imply the data are fit for publication. As your name will be on it, if you feel uncomfortable, request to be removed from the author list. You may opt for acknowledgement or even no relationship.