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First paper, conference feedback - at all if rejected?
I'm from industry and have submitted my first article to a conference.  What can I expect from a conference?  would they give me feedback only if I'm chosen.  Will I also get detailed feedback  if I'm rejected? or will they only say "sorry in this occasion we have decided to go for other more relevant papers to your area but thanks for writing."   Does this vary significantly according to the conference, location e.g. American vs Continent?  The conference is European if that helps.
Note:
I'm from industry so unfortunately I don't have an advisor and my colleagues don't value innovation (impact for future) as much as impact for now.  So this is my best bet to get any feedback at all.

You will get feedback (sometimes not really helpful) in both cases: whether you are accepted or rejected. Usually, you will also get some scores about novelty, relevance, soundness of the study, and so on.

You can expect to get feedback in any case. Typically, more feedback is provided if the contribution is rejected, as long as it actually underwent peer review. There is the possibility of getting "desk rejected" by the organizer before even being technically reviewed. This usually happens if the paper is either clearly out of scope or very far from the standards set by the conference. However, if your advisor signed off on your paper the probability of a desk reject should be very low.
The quality of the feedback that you receive may vary quite a bit, though. This largely depends on the conference: some tend to provide pages and pages of reviewer comments, while other (typically weaker) conferences only send back a few paragraphs of, often unhelpful, generalities. In any case, you should not rely on peer reviews as your primary method of getting feedback on your work - having your advisor or senior colleagues read your manuscript and sitting down one-on-one with you will in most cases give you more direct and more actionable feedback.


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Reading & Note-taking Before A PhD
I'm currently completing a Graduate Certificate of Studies at an Australian university, taking subjects in history. I plan to apply to a Master of Arts - Thesis for January, 2024 with the eventual goal of upgrading to a PhD. I have a topic and have written a (rough draft) research proposal of 1,900 words. My field is Russian history and the Russian Orthodox Church.
Of course, 2024 is over a year away. So, I've been taking notes from monographs and trying to read numerous articles while learning Russian (and Greek). Due to my current work & study engagements, I can devote 10 hours per week to reading.
Note: I'm not looking for shortcuts. There's no plan to 'finish the PhD in one or two years.' No interest in that! But I'd like to make graduate research a positive (and intellectually stimulating) experience while writing a high-quality thesis. Would reading beforehand make a difference?
Thanks for any advice / feedback and enjoy the rest of your weekend.

What exactly is the question here? You seem pretty well organized, and you look like you know what you're doing.

@AmerAl-Amry I guess I was struck by some confusion (I'm concerned about not meeting the expectations of a potential supervisor). It's quite difficult to find advice online for pre-Phd work (beyond the usual "Can I complete in 2 years?" questions). Really - I'm not sure what level of knowledge / skills are expected of students before they commence a PhD in Australia.

I wrote a reply, but it was too long so I'll answer.

I think you're on the right track, especially in the humanities, reading is very important, and your literature review would help make up a significant part of your papers and publications eventually. Like others said in the answers, taking notes, or highlighting something you expect to eventually cite, which is what I do, is important.
Though I'd say make sure you actually have a phd supervisor in mind that you want to contact, because supervisors mainly choose their students based on a shared interest, applying randomly to history departments wouldn't help. Also, unofficially contact the professor before you apply to establish a rapport, and get accepted. Professors don't expect you to have a full idea of what you're going to do at the first day, but showing that you're excited and prepared would be a great boost for you.

Thanks - there is a supervisor I have in mind (an expert in post-Soviet Russia) as well as a secondary one, who is familiar with contemporary Eastern Orthodoxy & the legacy of Byzantium. (Unfortunately, they are from different universities but its not uncommon for a second supervisor to be from a different Aussie uni)

Reading can help, but reading without note taking and summarizing is much less effective. You need to actually force the brain to incorporate the essential points of what you read. You need active learning, not just reading, which is, in itself, passive.
And marking up a text with a highlighter isn't much better.
What you really should do is take notes on what you read. For each chapter of a book, for example, immediately summarize what you see as key points by writing them (preferably by hand) in a note book.
Then, summarize your notes by reflecting on them and, again, extracting the most important ideas. If you do the last part on note cards then you can build yourself a deck of "ideas", one per card. These cards can be referred to later. But several of them can also be carried around with you for reference and reinforcement. You will have moments during the day when you are idle. Pull out your few cards and a pen and review what you have.
Number the cards as you create them (so you can reconstruct the deck). Say which book/chapter/article they came from. Don't try to fill up the card. In fact, initially leave the back of the card blank so that you have a place for annotations later.
But the real key to all of this isn't the cards themselves, though they help. It is the mental effort you go through to create them, which is a reinforcement mechanism that reading alone doesn't provide.
The real goal is insight into a topic.

I read a lot of unimportant stuff. But most of it disappears as soon as I start the next thing. This is fine, since I have no need to remember. On the other hand, in professional work, once I'd achieved insight into a topic, I could listen to a conference speaker and mostly not take notes. The speaker would either reinforce insights I already had, so there was no need to capture the ideas, or they would challenge those insights. In the latter case I had work to do, notes to take, further explorations, summaries, revisions, new insights (hopefully).

A note on highlighters.
I've seen student texts in which nearly every sentence is marked. This is worthless. The marking was almost certainly done while the student was reading.
However, if you make highlighting a part of a secondary (or tertiary) process, after you've reviewed the entire, say, chapter, then it can have some value, especially if you limit the number of sentences that you allow yourself to mark. Now, the work has an outline if big ideas that you created after thinking about it. The printed and marked page can now be used for review. However, you can't carry a bunch of books around everywhere like you can a bunch of note cards.

Thanks - I had a look at my old notes and I was disappointed by how vague I wrote things. So I re-read parts of a monograph and fleshed out the notes a bit more. Something else I do (although it's not officially 'academic research') is share my insights in an informal setting, like a conversation with family or even online. This helps for retention and forces me to flesh out my ideas a bit more. It also helps that I'm a blogger / YouTuber as I can connect with like-minded people.

Yes, explaining something to others is a good reinforcement mechanism and also a way to weed out misconceptions in some cases.

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How does “reproducing other labs' results” work?
I don’t understand where "reproducing results from other labs" fits into the running of a given research lab.
(I'm not in academia, and I confess I only consider this function in the context where it's News due to fails - ie, "So & So breakthrough is published, but other labs were not able to reproduce …". Nor do I recall a popular science headline about a discovery, that bothers mentioning successfully reproduced results.)
Such news mention might imply a quiet ongoing process.
With limited time & resources, it seems researchers would stick to their own project, however adjacent new results may be. Rather than pause their work for a tangent, all to say "Yes, we found those same results", or "No we didn't". I don't see their benefit.
Or is "reproducing outside results" simply built into all labs' work flow, and how so?
Obviously its a needed function, but I've never heard how it's actually structured. (quid pro quo - I'll reproduce yours if you'll reproduce mine.. ?)

You may wish to specify a field or fields. Things vary wildly, especially in this case. Also, you may want to wait a day or so before awarding a checkmark — you may yet get some more answers. Finally, you may wish to check our archives for some related questions, like this one

How will you build on something without seeing that getting to where you will carry on, gives the same results as you were expecting?

There are a number of possibilities. Usually they are triggered because someone knowledgable has some doubt about published results. That might be just intuition, or it might be based on earlier work that seems inconsistent. Sometimes the author(s) are mistrusted for one reason or another, such as being employed by someone with a vested interest in certain "results".
A scientific paper will include its methodology. The usual process of checking a result is to use that same methodology with new data, perhaps a larger data set (or not), and see if the results match. Statistical studies, for example, might be like that.
Sometimes a result is based on an experiment, say in chemistry, described in the paper. The "checker" will run the same experiment in their own lab and see if the results match.
Sometimes a result is based on software and a dataset. The check could use the same software, when available, with a new data set or independently developed software built to the same specifications. Independent development guards (somewhat) against software errors.
However, the most valuable sort (IMO) is when someone takes the same research question and develops a different methodology to check the research claim and gathers what evidence is available to see if the results agree. This rules out (hopefully) some results too determined by a given methodology. For an interesting example of what can go wrong see the Stanford Prison Experiment.
Any of the above are possible, along with others.
Yes, researchers want to run their own experiments, but they also want valid results to make it to the mainstream as future work will be based on it. This is especially important in some fields, such as health, and medical research. Casting doubt or disproving a published result can be a very valuable contribution to knowledge.

I'm not a researcher myself but I can imagine that if a group wants to build upon the results of another group, the first step would be to be replicate the results of the original paper. If they can't replicate the result they can publish that too. Would this be another way in which work is checked by other researchers?

@AccidentalTaylorExpansion Depends on how they are building it, I imagine. For some fields (such as AI or chemistry?), I can see that replicating what the other team has done might be an important step to building on it, and if you can't get it to work, that is noticeable. For other fields (psychology or economics?) it might be well out of the way.

With limited time & resources, it seems researchers would stick to their own project, however adjacent new results may be.

Well, yep, there's the problem. Most labs have funding to perform a new project. Hence, most results are never attempted to be replicated, until it becomes of interest to someone, or easily achievable on the way to doing something "novel."
Occasionally, students, like undergrads or master's students might perform a replication as their thesis, where there is less expectation of originality.

Obviously its a needed function, but I've never heard how it's actually structured.

It's not.

Didn't expect that but it makes perfect sense and confirms my intuition about the whole process. thank you, and glad I asked.

The other answers are so far covering situations where some result is reproduced because of doubts. But there are also situations where the published result allows (is the only or presumably best known way) the other lab to obtain material they directly need for their projects. Reproducing the original paper is then no waste at all* but a by-product of using the results of the paper for other research:

Think chemical synthesis: a synthesis method or process is published which allows making substance or material X or a particular group or type of substances. Someone needs X for their synthesis of Y, and thus they start reproducing the paper, so as to actually have material/substance X.

Think of measurement methods: a paper describing new instrumentation, and then another lab realizing that the measurement problem they encounter in their work would be better met/solved/improved by the published setup.

Think of data analysis algorithms: someone publishes an algorithm to do X, with application example being the well-known benchmark data set Y (or publish code for X together with data set Y). Others realizes that the algorithm may be useful with their application problem, too. Typically, when familiarizing themselves with the algorithm, they'll start with Y, too, and thus reproduce the original paper.

* I'd like to emphasize that reproducing other findings is often not wasteful: there is actually indication in several fields that we'd need to do far more of this. But: for certain types of results there is low/no incentive to do this (or it's even outright discouraged because funding agencies and publications have novelty requirements)

This looks to be the answer most closely addressing "When in the scientific process do the results of other labs' works get replicated?". Failure of replicability at this stage in the research is often what leads to a result being flagged for the more in-depth reviews of past work described in the other answers. There's often not a lot of publicity about the process described in this answer, because you don't need nearly as much documentation when saying "we believe the results in this paper and built on them" vs when you say "we think our colleagues are at best wrong, at worst lying".

this corrects my notion that the effort would have little benefit. its a great point - if a finding has value, then of course it'd be used by other researchers - not just to verify, but because it enables something else beyond. in that context, the replication attempt might come much later.

Exactly. An important result is 'only' important if people want/can do things with it (and may it only be building other important results on top of it).

If you publish results, then at some point you would hope that someone picks it up and bases something better on your research.
So you published that if you do A, B, and C, then X happens. And I thought of a way to do Y and Z if X happens. But it doesn’t work.
At some point I suspect your results are not correct. And I start a project trying to replicate your research. Or not. Because showing your results are wrong is a good contribution to science.

Question author says the following:

I'm not in academia, and I confess I only consider this function in the context where it's News due to fails - ie, "So & So breakthrough is published, but other labs were not able to reproduce...". Nor do I recall a popular science headline about a discovery, that bothers mentioning successfully reproduced results.

In addition to the other answers, I'll try to provide some (potentially) instructive/informative examples.
Reproducibility is the hallmark and cornerstone of science!
What separates science from other forms of explanations of the world around us and for example the healing arts is reproducibility. If I explain to you how to do something in detail, all my techniques and precautions, and what results I get along with my estimated errors, then you should be able to follow my instructions and get the same result, within some range of variation that is consistent with recognized estimates of experimental error.
If I say that mixing blueberry juice and thumbtacks makes plutonium and tell you how I did it, then you should be able to try to make plutonium too. If it doesn't work for you, my results are irreproducible, and there's a journal for that.
Here are a few extreme examples that may bracket how the reproducibility (or lack thereof) of a given result was or was not confirmed in a timely way.
Alzheimers - Tragically, NOT enough effort was spent trying to verify a result, time & lives wasted?
Biology SE's Does the recent concern over several papers about Aβ*56 call into question the association of Alzheimers Disease with any amyloyd beta oligomer forms? gives more details on a really tragic failure of science to police itself.
Not enough effort was spent trying to reproduce an experiment pointing to a certain form of amyloid protein's link to Alzheimer's disease. Instead many biologists spent years doing not-so-fruitful research based on the premise that this result was correct and several pharmaceutical companies spent (essentially our1) money and (their) time developing drugs and doing drug study after drug study that did not demonstrate results.
The scientific community failed us in this case because they did not confirm that the original results were reproducible.
Several papers were retracted years later, some by the journal without the authors' input. There was plenty of damage to go around, but no way to recover the time and money misspent.
GSI positron peaks
The positron-electron peak puzzle: results from APEX (Ahmed et al (1997) Z. Phys. A 358, 235–236 (1997)) summarizes a few million dollar project at Argonne National Laboratory to try to verify some strange results seen for years by two competing groups at GSI Puzzling Positron Peaks Appear in Heavy‐Ion Collisions at GSI (Physics Today v. 38, no. 11, p. 17 (1985)) There was no room for such peaks in modern understanding of physics, they stubbornly remained at the few standard deviation level and release of specific details of analysis (and the raw) data was never completely forthcoming.
It was irritating to nuclear and particle physicists, so a clean start on a different continent by a group with no ties to GSI was initiated. A huge amount of effort went into trying to reproduce the results, including consultations with those groups to make sure nothing was omitted.
Cold fusion
This is another "irritating" result for which there was no room in Physics for the phenomenon, but the potential payoff was incredible.
Unlike the GSI positron peaks, this one was relatively easy to approximately reproduce - you could stick some palladium in water, run a current through it and put a neutron detector next to it or put it in a calorimeter and measure the heat produced compared to electrical power, but in this case due to greed the originators withheld certain specifics that made honest attempts at reproducing the results unable to implement tests that were exact reproduction.
Lack of sufficient information to test the reproducibility fed the storm and the pockets of some individuals.

1Research budgets of established pharmaceutical companies comes from revenue - i.e. how much we pay directly or indirectly for the medicines that keep us alive and healthy. This also means time and money was NOT spent on potentially more helpful drug development.

I have some divergence with the existing answers; my viewpoint is that reproduction is naturally built into the scheme of researchwork. That is to say, it is neither occasioned by suspecting some results, nor is it something that has to be additionally incorporated into workflow.
This answer is based off an engineering discipline; I find it to be valid for experimental as well as simulation groups.
Research in such fields is often incremental, which implies that each bit of research is built on some previous research and adds a small advance. In other words, previously published research becomes a starting point. It is then imperative and natural to reproduce the previous work, so that you have a known starting point. Without doing so, you would not know whether your results are consistent or not.
In materials engineering, a perennial effort is to make materials stronger. One group develops a new class of materials and shows that it is stronger than the existing materials. Another group wishes to push the envelope further and introduces some processing method which will further strengthen the material. They need to first produce and test the starting material to benchmark their results. In doing so, they are reproducing/validating the first group's results.

Or is "reproducing outside results" simply built into all labs' work flow, and how so?

It is, provided that there is some connectivity between research of different labs. In fields where each lab is producing fundamental results, I suppose this is not built in.

(quid pro quo - I'll reproduce yours if you'll reproduce mine.. ?)

No quid pro quo; it works just as citations work. If your work is important and relevant, if it prompts further research, then someone will reproduce it as part of a further study.
In my field, we informally use this as a way to test the response; if something is not reproduced in a few years, it's probably not relevant enough to pursue much further.

I want to emphasize the part that the answers that cbeleites and AppliedAcademic provided, repoduction is very often a core parts of the scientific workflow. But that part is much less obvious in the literature as it is often not explicitly published.
Any time you start a new project, odds are that you're working on top of existing results. Either the subject of your investigation, e.g. a specific protein, chemical or organism has already been studied or the methods you're using are well established. And the first step is to establish that your lab setup works how it should, and this is easiest if you only check one thing at a time.
So for example if you want to do experiments on a specific protein you need to produce it first. And once you did that you need to make sure it behaves like expected, and for that part you would usually compare it with previously published result. So you would check the structure (or rather some experiment that works like a fingerprint for the structure like an NMR HSQC) against the literature or check the function of the protein if it is an enzyme. To do that you would typically reproduce the literature, to make sure your system behaves as expected. And of course this is a bit more complex in detail, you might be interested in specific behaviour or properties of protein X under conditions Y when you add Z. There are plenty of things that can go wrong, so trying to do some experiments first where you know the expected results is usually a good idea.
The other case is when someone publishes a new method. Those are often published with data on some kind of model system first, those model systems usually are well behaved and easy to handle. If you try out that new method first you typically would do that on the same model system, to make sure it works and you're doing everything correctly.

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How to organize research notes?
Background: I'll start to write my (cumulative) dissertation in two months.
I'm currently struggeling to find a good technical solution to organize research-related thoughts for my dissertation. For each chapter, I currently have an individual Trello board with lists such as "ToDo", "Research Ideas", "References", "small thoughts / phrases / arguments for certain design choices". This seemed to work at the beginning, but now I have so many "small phrases" that I lost the overview of them.
Up until now when I was working on papers, I usually wrote all my thoughts into the corresponding sections of the papers. However, with my dissertation as a "larger paper", I don't think it's feasible to organize my thoughts this way.
How do you organize 100+ "small thoughts" about your research and still have a good overview? I know that I can use a physical notebook but I'd rather have an online solution that allows me to quickly reorganize my thoughts (which a notebook does not).
I know that Good practices for organizing notes is related but the answers were discussing online vs. offline and the general guideline was 'whatever helps you'.

The problem is "whatever helps you" might be the best answer.

@Saturnus: Yes, I already linked that article but the answers weren't discussing specific organization styles but rather online vs offline

@skymningen: True. Nevertheless, I'd like to know how others organize their research thoughts since basically every researcher has to somehow manage them. We can convert his question into a community post if that's more suitable.

Maybe notecards? I still use this system for certain things. The nice thing about notecards is that you can easily reorder them and you can easily discard no longer needed old ones or include new ones, and you still have the option of adding brief thoughts or references on the notecards.

the general guideline was 'whatever helps you'. — Well, yes.  That's also the correct answer here.

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How to publish an extended version of a Springer journal article on arXiv?
Our team successfully participated in a challenge. We are now in the process of describing our approach in a paper. Initially, each team was supposed to write a separate article which would have appeared in a special issue of a journal. Unfortunately, the editor of the issue changed his mind and there aren't enough pages in the issue to cover each team separately. Instead, the organizers are writing an overview paper where each team is allowed to append 3 pages describing their approach. This will result in one paper with ~15 authors.
We sort of anticipated to write more than 3 pages. Therefore, we are thinking about writing a more in-depth article that sort of extends our part in the joint article and publishing it on arXiv.
For the sake of not confusing anyone, let's

call the joint article A. A will be published in a Springer journal
call and the extended version intended for arXiv B

Both articles are written in English and are about the same content. We basically want the content (examples, figures, screenshots, and text if possible) from A to also appear in B.
What do you think is the best option?

Create the B first and refer to it in A? There shouldn't be any problem with blind submissions, only copyright issues
Submit the A first and publish B later.
Refuse to participate in A since we only have control over 3 of the 14 pages and cannot control what the other teams are contributing to the paper. Instead, only publish B.

For A, I think the introduction should make it clear that each team contributed to a particular part of the document, moreover, each team should have the opportunity to review/comment/improve sections by other teams, this should help address concerns regarding 3, thus, lead us to favour options 1 & 2.
Option 1 appears to be the easiest option, because problems might emerge during option 2: B might have copyright issues (because A was published first and is subject to copyright), and addressing these issues (e.g., perhaps by attributing content in B to A) is likely to be time-consuming.
On this basis, I recommend option 1.

Your situation is similar to when publishing in journals that have tight word limits. A common strategy is to put additional material in an online supplement. The idea of an online supplement is that the material does not repeat what is in the main document. Rather it adds additional information. You might want to consider adopting that paradigm. That way, there is no overlap between the two documents.

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Include author after revision in IEEE journal
I submitted a paper to a  IEEE journal. During the submission, I acknowledged a person who helped me in experiments.  Now I am getting minor revision. Is it possible to include him now?

Read the IEEE policy.  In my experience no because of people selling authorship for a price.

Yes, you can update the author list. Depending on the system, you might be able to update the authors in the submission system directly, or you may have to contact the editor to have them do it.
One caveat, there is the possibility that a new author changes the people conflicted with reviewing it.  For a minor revision, which probably only goes back to an associate editor, this may not matter much.  Plus, it's already essentially accepted.  If it were a major revision that would get reviewed again, it's possible someone who should reread it is now conflicted. (More likely if the new author is with another institution, but even if it were a student, a summer internship could have that effect.)


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What to do about collaborators & co-authors who fail to understand authorship & plagiarism?
I've been working on a research paper in the field of education with co-authors for the past year. I know both of these individuals professionally for several years. One is a more seasoned author than the other, and I am the most published author.
The manuscript is currently back from review and we are working on the revisions.  We also co-authored and presented at a national conference presentation last year. My status in both is second author. My co-authors/collaborators are newly tenured, and one is not tenured. I am a retired professor who is still active in research.
My plan was to attend this research conference and I am looking through the program and I found that  my 2 co-authors are on the program to talk about the topic of our paper! I also see that their abstract includes ideas and references from sections that I wrote in the paper.
When I asked why I was not included one responded, "so sorry, that was so unethical" while the other said she got the invitation to present and it was quick turnaround. They both offered to have me on the program but only after I found out. Both have apologized for both not inviting me, although if I hadn't found their presentation, I am not sure either would have told me.
They did not apologize for using my ideas and citations of other research in the abstract because "currently our paper is unpublished" and they did not see a need to cite our paper? Yet, my ideas were used without my consent or knowledge.
One author tried to make the claim of 'ownership,' and basically no one owns ideas. I responded it's an issue of authorship. I did 'pen' my ideas to that paper and since we formatted the paper in a dialogic format (narrative research), it's clear to see where my ideas begin and end. I see it as plagiarism.
So, there is an issue of excluding me as a co-author in a conference presentation,  not citing our paper in the abstract which I consider self-plagairism as well as not citing me-plagiarism.
What do you all think? What would provoke 2 co-authors to do this? Am I correct in my assessment of the issues of authorship and plagiarism? What strategies would you recommend for addressing co-authors and collaborators who don't understand what I consider to be basic professional etiquette, but also have a motive that appears to be more devious? One co author appears to be more sincere and apologetic but the other one, I think the one who submitted the proposal appears cold, and indifferent.

Did you come up with the idea, or did you write it up after one of them proposed it? From your question is isn't clear who said "no one owns ideas" -- whole system of academic citation is designed to give credit to the source of the idea. Obviously they are wrong to think that a presentation can't mention a paper under review (and its author list), but you appear to be overstating the importance to an oral presentation of work on the written publication -- the speaker's obligations to you are the same as if the same group had discussed these ideas in a conference room and not written anything.

The ideas and insights that I authored in our paper and that my co-authors/collaborators included in their conference proposal abstract originated with me; that is, they came from areas of the paper that were of my contribution. I of course, included citations for ideas not my own, and they took my ideas, and my citations, but did not cite the whole paper in the abstract. I am not sure what you mean by 'overstating the importance to an oral presentation." This international conference presentation is highly regarded in my field.

I fear the only way to get answers is to talk to your colleagues directly. The answers here will be speculative. They will possibly be marginally useful to you, but won't be useful to anyone else. I'm voting to close.

What strategies would you recommend for addressing co-authors and collaborators — Direct professional honesty.  Also, stop working with jerks.

What do you all think?
On the surface, I don't think this is plagiarism.  When a group of people  author a paper, imho the entire group can be considered the originators of the ideas in that paper.  Basic professional etiquette (as well as any co-author situations I've been fortunate to be in) is that each author, when speaking about the ideas, typically says, "We" did such-and-such, or "we" had this idea.  In my experience, many high quality authors, out of modesty, or an abundance of honesty, will often credit their co-authors for many of the ideas.  But unless a person specifically says "this-and-such was my idea" when indeed it wasn't, then I don't think this is plagiarism, but rather as you put it a matter of "basic professional etiquette."
What would provoke 2 co-authors to do this?
Could be anything from a simple lack of social skills and/or social awareness, to major ego subterfuge and game playing.  Depends on the personalities.
Am I correct in my assessment of the issues of authorship and plagiarism?
As I said above, I personally wouldn't label this plagiarism, but rather a lack of professional etiquette -- unless they outright state that your ideas were their own.  In my opinion, if they use the word "We" (and at some point state the names of who "we" are) then they are entitled to do that, by dint of being co-authors together, even if it was your idea.
What strategies would you recommend for addressing co-authors and collaborators who don't understand what I consider to be basic professional etiquette, but also have a motive that appears to be more devious?
Discuss with them, as you have, and if that gets you nowhere, chalk it up as a life lesson and avoid working with that person in the future.  Unless it has a true consequence of facts harming your career (in which case you may want to seek legal advice).  But if it's just your pride that has been hurt, because the other person is unprofessional or petty, then remember the phrase, "Every dog has his day."  Move on, a let fate take care of them.
One co author appears to be more sincere and apologetic but the other one, I think the one who submitted the proposal appears cold, and indifferent.  Trust your gut; perhaps avoid all interactions with the "cold and indifferent" one in the future.
One comment that you mentioned but didn't specifically ask about: You mentioned that they didn't reference the unpublished paper, but only the ideas.  Imo this is also unprofessional.  I was taught to reference every source, even if it is unpublished work (just say so).  My graduate adviser impressed this on me years ago, as a strong ethical concept.  I had made some statements in my dissertation that everyone in the field regarded as completely common knowledge (but possibly someone outside of the field would not know), and he made me go back and find the original paper from the 1950s and reference it.  So I have taken it on as an ethical imperative: don't make statements or present ideas without referencing where they came from.  If you agree, then perhaps you may want to convince the co-authors to mention the unpublished work.

Daniel, Thank you so much for your very thoughtful and insightful response to my question. drk

Authorship is such a tricky issue, which is why it is helpful to determine authorship (inclusion, order, future papers/presentation etc.) ahead of time and to work with individuals who you can talk to about authorship frankly. My ongoing co-author and I can tell each other, "You can have first author on this paper, but I'm going to do the next one."
That being said, academics with less experience can make mistakes with authorship, which can lead to rocky collaborations. It is awkward and I'm sorry you had to go through this with BOTH of your co-authors.
Your main questions is "Am I correct?" in regards to the assessment of the situation. In this specific situation, the co-authors are wrong IF they were presenting content that included your ideas, which is what you imply. If they were presenting on a similar, but different topic, I do not feel the need to include you as a co-author, though professional courtesy would recommend doing so.
The fact that the paper is not currently published does not matter, because (and this almost happened to me), "If the co-authors use your ideas to publish work (manuscript B) from an unpublished work (manuscript A) and manuscript B is published before A, then you would be considered the one to plagiarize, even if the ideas were you in the first place.
I ran into this problem with a co-author. We were working on similar papers with a group of several co-authors and each of us were first author for our own paper. I finished my draft first and sent to him for review. What I didn't know is that he copied a lot of my content into his first-authored paper and tried to submit it before me. I informed the lead person on the project about this and we confronted him to make sure he edited my copied work heavily. If he published his paper first, mine would have been flagged as plagiarized by the journal (for my own work!!!). I do not work with him anymore.
My suggestion? Give your co-authors the benefit of the doubt unless you have other reasons to think they were malicious. Be clear that on future presentations and papers you expect to be a co-author, or at least informed about their submissions so that you can discuss further. You may also choose not to work with either of them anymore, which may not be bad for you, since you are the most published. Good luck!

Nicole,Thank you so much for your advice and insights. Very, very helpful!

How much time do you have before the presentation? If there is some time, you can discuss with the conference organiser about the issue and let your coworkers know about it. How often do you work with these co-authors and do you plan to work with them in the foreseeable future? That might affect how do you want to pursue the discussion with the conference organiser. In any case, don't miss attending the presentation as a contributor so that the audience remembers you when the paper is published.

About one month to the presentation (May 2017). I discussed it with my collaborators but not the organizer of the conference. I didn't think this was necessary at this point. I don't see myself working with these two collaborators again. Thanks for the advice about attending the session.


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Can a student with a weak or average undergraduate math GPA realistically become a professor?
I just finished my second year of undergraduate studies as a double major in computer engineering and mathematics at the University of Iowa. Although I came in believing that I wanted to become a software engineer, I've become more interested in pursuing math as I learn more about it.
To be completely honest, I was somewhat directionless and unmotivated when I started my studies and I didn't quite achieve the grades that I wanted. I finished my first year with a GPA somewhere around a 3.45 on a 4.0 scale. However, I managed to put forth a lot more effort into my coursework this year, pulling my overall GPA up to a 3.60 (and achieving a 3.8 this last semester).
The problem is that my mathematics GPA is still somewhere around a 3.48. The graduate school at my university requires a 3.4 to pursue doctoral studies in math and (assuming that my grades continue to stay on track) I know I will be able to satisfy that.
My question is, are my grades able to become competitive enough to reasonably pursue a career as a tenure-track professor in math at a state university? I still have two years of undergraduate coursework plus all of graduate school and post-doc studies to make myself more appealing, but if I've already caused too much harm to repair then I'll probably skip graduate school altogether and go into industry as a software engineer.
I don't know all that much about expectations and qualifications for becoming a mathematics professor so I was hoping that somebody who might be a little more knowledgeable here could help give me some guidance.

Past grad school admissions, nobody cares about your undergrad GPA.

My question is, are my grades able to become competitive enough to reasonably pursue a career as a tenure-track professor in math at a state university? — Perhaps it wouldn't hurt to point out that getting good enough grades etc. to get into a grad program and securing a tenure-track job are many, many orders of magnitude apart on the achievability scale.

This is me.

You shouldn't give up hope yet, and you should follow your dream while having a backup plan or two in case things don't work out.
Nothing that you've written rules out the possibility of your going on to graduate school, but it also isn't sufficient to ensure that you will be adequately prepared for admission to graduate study in mathematics.  What you do in the next few years will determine whether or not this is possible.
There are many more steps beyond simply getting admitted to a graduate program and it's way too early to predict things will ultimately work out for you.  Take it one step at a time, and be prepared to reassess your goals in light of your future successes and failures.

FWIW, I completed my undergraduate degree in computer science and worked as a software/firmware developer for several years before returning to graduate study in mathematics- people often take round-about paths in their careers.


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How will taking upper level undergraduate courses online affect graduate admissions?
My dilemma: I'm interested in potentially going to graduate school to obtain my PhD in math with an ideal career as a professor at a research university. I entered undergrad as a computer engineer and didn't add a math major until the end of my third semester. In my school, you have to select electives to satisy an "elective focus area" (cohesive plans of study in fields such as data mining, signal processing, applied physics, etc). My field of study is currently software engineering, something that still interests me. I'm still early enough in my undergraduate career (going into my fifth semester) where I could alter my focus area to include many more upper-level and graduate math courses instead of continuing on the software track. However, I'm hesitant to do so because I know that software engineering is a lucrative field with significantly more job availability than math academia and I would likely enjoy my work as a software engineer.
My inclination: Given that software engineering is something that I'm interested in (although not as much as math) and the job market isn't quite as cutthroat, I'm inclined to continue on my path while trying to sneak in a couple upper-level math courses that have crossover -- large data analysis, numerical methods -- where I can. I could work in industry for a few years after graduating. Ideally, I would be able to take one or two courses a year throughout this period, most likely online, that would solidify my mathematical background and make me a more desirable student when applying for grad schools.
My question(s): Would taking a solid portion of my post-calculus mathematics coursework online have any adverse affect on my graduate admissions? Would it matter if the coursework came from my undergraduate university or from a variety of institutions? Are there other unconsidered obstacles in my inclined path?

For PhD admissions, you need strong reference letters. In online classes, there is often much less interaction with the instructor, so it might be hard for you to make the impression that you need to in order to get those strong reference letters.

Small correction: In online classes, there is often no interaction with the instructor

Are you working full-time while taking the coursework? Because you talk a lot about software engineering but don't indicate what you're currently doing. Realistically speaking, whether or not you can dedicate time to drive to campus while working full-time could potentially impact what you should do.

@Compass I'm currently a third year student but in this theoretical situation I would be working full-time in industry while taking one or two courses a semester (most likely online).

I wouldn't recommend a part-time Master's program unless it was specifically for industry advancement, i.e. EMBA or MS Computer Science.

Given your terminology (you wrote "research university"), I'm going to assume you're in the US.
This is a bad idea.  Admissions committees will have no idea how to evaluate the online classes, and will probably not put very much weight on them.  As @ff524 notes in his comment, you will not have any good letters of recommendation, which are essential for an application which is a bit outside the norm. You are incredibly unlikely to get a spot in a graduate program that is likely to result in a becoming a professor at a research university if you depend on online classes instead.
So, what should you do instead?  Well, first reconsider if being a math professor is what you want.  You're absolutely right that there's a real risk of it not working out, and a lot of competition.  But if by trying to keep your options open, you do less to make yourself a qualified candidate (both on paper, and in actual point of fact), then you're just putting yourself at a disadvantage, and making your chances that much worse.   You will be in very bad shape if you don't get a BA which includes a math major, and take a lot of advanced math courses (more than the bare minimum required for a math major!) in person with faculty at a well-respected research university.  Note, that doesn't necessarily preclude getting another major.
On the other hand, there is good news.  The people who get BAs in math, or start mathematics grad school and don't finish, or who finish but don't get an academic job (or one they want) do find other things to do.  If you have complementary skills in computer programming, then you will be very well set up to do a lot of things.  I don't suggest starting a math PhD as preparation for a job at Google, but I do know several math PhD's who do have such jobs.  So, if getting a BA in math and then perhaps a PhD in math feels like what you want to be doing in the moment, then I think you can reasonably do it, and figure you will find a job if the academia thing doesn't work out.

I'd strongly second all of this answer. In particular, doing half of one thing and half of another, unless you're twice as able as all those very able people around you, will most likely lead to inadequate outcomes in both. Maybe not "failure", but almost surely substantially compromised outcomes. That is, yes, trying to hedge one's bets in the academic math game is mostly infeasible. Yet, as Ben Webster notes, people who have good PhD's in math, or even part of one, do not usually have much difficulty finding other opportunities, especially if they have computing chops. So...

... figure out what you want to do, and don't do it half-way.


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Tips on choosing a research topic with little relative background?
I know this might seem like I'm worrying about something too early, but I am a rising sophomore (undergrad) that is anxious about independent research. I am currently in a physics lab right now that I think is decently interesting. However, my current role is helping out the grad students and postdocs with their projects, whatever they need me to do.
Part of the reason that this is my job right now is because I haven't come up with an idea for my own project. I have lots of things that I think are interesting regarding this field (optics/quantum), but the physics being done is way above the level that I can understand in my current year of schooling. Although I just started here, there will come a time where the professor will approach me and ask if I want to start something on my own, and I just don't know what to do. Should I be asking people now? Trying to learn these things on my own? Or is this common in physics labs?
To put it in perspective, I am the only undergrad in the lab, so I'm not sure anyone really knows how to deal with me either.

I think you should do all, start an independent work, and also collaborate with others. There is no unique way, each has its original way. You can start by reading papers in some direction and when you come across something you have a familiarity with, then approach more in this direction.

There is no sure path to research. And it is never too early  to think about it.
A colleague on another side of SE claims:

Spending two days in a lab can easily save you up to one hour reading
  literature

You are lucky enough to be in the right place. Start asking people, be gently curious. Some won't answer, some will. Some may begin to give you more and more interesting tasks. And on the side, read. Some books won't tell you anything. Some will.
There is no sure path to research. But doing nothing is unlikely to help.

I can't comment on your specific field1, but you should understand that there are fields where there is absolutely no chance for an undergraduate to come up with a good research idea on their own, however strong their commitment is. And sometimes it might be hard even for a graduate student toward the end of their studies.
However, you are in a perfect position to rapidly improve your knowledge, discuss your ideas and understanding with others, listen to other people's idea and get the gist of what research is. When you will integrate this hands-on experience with a sound theoretical background, you will be ready to start your first steps on your own.
Be patient, then, and take profit as much as possible of this experience.
1 I had been in love with quantum optics for a long time when I was a student, but too much time has now passed to comment on the current situation.

I disagree, and you are not correct. T. Padmanabhan was an undergraduate when he published his first paper see here and also E. fermi as well. I can find many contra examples.

@MikeyMike And so? I neither say that there's no chance in all fields nor that there is no chance in the op's specific field.

First of all, let me start by saying that you are currently doing EXACTLY what you need to be doing to put yourself in a fantastic position to do research as a graduate student: in particular, working with graduate students in whatever capacity you can and regularly working in a lab. You are learning the skills necessary to perform the job while developing a professional network. Stay inquisitive and engaged and you will be fine. Your future research project will most likely be from an area where you are interested. In a nutshell, here's my advice: keep doing what you are doing (working in a lab), keep asking questions (on stack exchange and in person), and begin reading articles in your subject area that you have an interest in. You are on the path to becoming a great researcher by being exposed to great resources (stack exchange, your professors and co workers) and by starting early.


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Is it my responsibility to point out that a paper has been plagiarized from another researcher's blog?
While reading a series of blog posts on a sub-field in TCS (theoretical CS), I came across a paper recently published by a group of students/faculty that has literally copy-pasted large sections of a blog post, and made it into a journal paper thats available online. My question(s) are about what I should do about it:

Do I point it out to the author of the blog, and leave it to him
about how to handle the issue?
Contact the journal in question - but since its not my work, I'm hesitant that whether I have a case
Leave it alone, finish reading the blog posts, and add the journal to my private list of journals to completely ignore?

The third option is most hassle-free for me, but I wondered if it'd be ethical to know about plagiarism and not point it out!

Added links to original blog and journal paper in question for better context!

@Suresh: Isn't this your blog?

Nice catch! If I were the author I would probably want to know.

well it appears you inadvertently notified them by asking the question on this site. lol.

@nathanhayfield: By they, if you meant the authors of the journal paper, how so? None of the answerers seem to be them :)

see the comment by @AnonymousMathematician

@nathanhayfield - Ah, I thought you meant the authors of the journal paper (hence them :)). Seems like the blog author hasn't been online since I posted this question!

Do I point it out to the author of the blog...? — I think you just did.

I haven't had internet for the last week. only seeing this now. It's an impressive bit of plagiarism, especially since the tone of the writing changes so dramatically. Time for a letter to an editor.

@JeffE - That was intentional, as I know Suresh is an active member at Academia.SE :)

I just sent off a letter to the editor of the journal. What a way to get back online ! Thanks @TCSGrad for spotting this. The funniest thing about this is that my post is hardly original research. They could have read the references and cited them instead.

@Suresh - Its the least I could do :) I was googling for more instances of similar papers for further reading, when I came across this! (Your blog post and their paper are the top two pages that come up for "Voronoi trick"!)

For what it's worth, the offending paper appears to be gone—and in fact, the entire issue is currently "password protected." That's a pretty clear sign that this is a journal that you want to stay away from—preferably with a pole about a million miles long! (That, and the fact that there are a number of other articles "removed due to copyright" issues!)

Seems like its back up, with the same content as before!

Ignoring the journal in question is probably an overreaction.
However, the best route to take is the first one—the author of the copyrighted material is the one that has the most responsibility to assert her rights. Your duty is to notify the person whose work has been infringed upon that the violation has taken place. Once you've done that, you've achieved what's ethically required of you. You are not obligated to take the matter up directly with the journal. (However, you may do so if you so choose.)

This is really the correct approach as you don't know for certain that the copying wasn't authorized. Leave it up to the original author to decide how to proceed.

If the copy was authorised, I believe the sources should be in the references, which is not the case in the paper.

That being said, personally, I would contact the journal in question and inform them of the suspected plagarism. They may not be aware of the issue, as it's hard to be on top of all possible literature on a topic. The post may have been guest-posted from the original authors on the blog in question. There may be actual plagarism, and it would have to be dealt with. However, any solution relies on the journal being made aware of the problem. To paraphrase a famous quote, "Never attribute to malice that which is adequately explained by lack of effort."
If you are for some reason worried about your being identified as the "whistleblower", so to speak, use an anonymous email address when you contact the journal.

Also, I've a separate query - how does one argue that the blog came first, as one can modify a blog content any number of times, and there's no formal date-stamp to signify the sanctity of the content?

Basically, you'd need to have some means of verifying the prior publication in order to prove your claim. Usually there's a log of changes to a blog, so you'd have to be able to show that the blog hasn't been edited to add or remove content. So it's tricky, but not impossible.

The Internet Archive/ Wayback machine might be useful, too.

Indeed: here it is in 2008 http://web.archive.org/web/20080127013756/http://geomblog.blogspot.com/2007/09/voronoi-trick.html

Seems the blog owner (http://academia.stackexchange.com/users/346/suresh) is also a mod on Academia.SE!

This is very common among obscure journals. I have come across papers copy-pasting entire paragraphs from my papers and not even getting a citation.
It is possible to do something about it, but it is usually worthless since many of these journals even accept randomly generated papers (see).
In this case, I would go for 1., the second option might be too risky. Recall:

The road to hell is paved with good intentions.

The third one might not give you peace of mind.

Incidentally, the publisher here, Cosmic Journals, is on Beall's list of Predatory Publishers.  (And thanks for the shout-out!)

I would start with option 4 (loosely based on Matt. 18:15-17, a principle of giving maximal opportunity for people to correct their own goofs):

Privately contact the apparent plagiarist(s) and point the problem out to them. Most likely, knowing that the plagiarism has been discovered, they will want to fix it ASAP before it becomes public knowledge. It's always conceivable that there has been an honest mistake, at least honest on the part of some of the group of faculty and students. And in that case it would be best to let those in the group address the problem. That's how I would want to be treated if I were in that group (whether I was guilty or not).
If they don't listen (e.g. if they make excuses) - contact their department or employer.
If they don't correct the situation, contact the journal, since they've published the material, and have a responsibility toward the copyright holder even if the plagiarists won't do the right thing.
I would contact the copyright holder only as a last resort, if the plagiarists and the journal both ignore the problem. Or, you could contact the copyright holder after the problem has been addressed.

How do you "fix" a plagiarized paper? Retraction seems to be the only way, and that would be done anyway if the problem is brought to the editor's attention!

You forgot "Contact the plagiarists' department/employer".

@TCSGrad: Retraction, yes, but it's a lot better for a retraction to come from the plagiarist if possible. Then a journal editor would have to retract it as well, but it would be at the request of the plagiarist, not forced upon them.

@JeffE: Where would you put that in the sequence - before contacting the journal?

Concurrently.  If everyone is playing by the rules, the journal and the department would contact each other, so you'd only have to contact one of them.  But I wouldn't count on that.


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Is it possible for a student in first year of Ph.D to secure funding for attending conferences?
Note: I'm primarily interested in answers relevant to Computer Science (Theory), but answers in different areas in CS / totally other disciplines are equally welcome.
In most (if not all) PhD programs, incoming grad students are supposed to take relevant courses and fulfill their TA-ship duties (I'm assuming not everyone gets a RA from the 1st semester itself). During that time, they are also expected (and highly encouraged) to keep reading on their chosen research field, to have a concrete idea of where all the focus in that field is at that moment.
In my opinion, I would consider that attending important conferences and interacting with leading researchers in their field would play a very important role in the development of a young researcher, as he/she would have the chance to get motivated by the best brains in the business! But, it is unlikely that he/she would have publishable results at such venues within such a short time, and if he/she doesn't have a fellowship/travel scholarship, it is unlikely that he'd be able to afford the registration/travel/accommodation expenses from his own stipend.
So, what are the options in front of such a student to make attending such events possible:

Do advisers cover the expenses for their incoming grad students, for
attending such talks/conferences, or is there a provision for such
funds from the department ?
How much does the answer to the above question vary between different colleges - I've heard (unconfirmed) reports that
higher-ranked institutions have more funds to burn, and as such
students in such departments can afford to attend talks without
publishing in them (at least for the first 2 semesters) ?
Are there specific scholarships/fellowships that exist to primarily cater to conference related expenses for students? If so,
it would be great to get some leads on where to look, and what are
the primary qualifications (>90% of fellowships in US require the
applicant to be an US citizen, making it extremely difficult for
international students to get one!) ?

As Willie Wong says, it depends on your school and your advisor.  As an obvious general rule, departments and advisors with more research funding are more willing to spend it.  (As a reference point, my department does not offer such funding, because individual faculty generally have enough money to support their students' travel.)
A significant number of CS theory conferences have external support for student travel; see, for example, SODA 2012 and STOC 2012.  These grants usually require a letter of support from your advisor, so you at least need an advisor.  (In many PhD programs, including mine, PhD students do not necessarily have formal advisors for the first year; students are admitted to the PhD program, not to any particular research group.)

So, students who have yet to decide on an adviser would not be able to avail of external support (from the conference), and by the time they do, they may not need to (as their adviser would be able to support them), isn't it?

Even without an official advisor (for departmental purposes), first-year students can usually convince faculty to act as an advisor for purposes of applying for funding.  Advisor(x,y) is not a boolean function.

@shan23: and in the slightly better endowed departments/universities, graduate students are often offered some fixed annual amount of travel funding. When I started as a graduate student we were told that the department would sponsor around USD 700 per annum for research and conference travels. Of course, YMMV.

For questions 1 and 2: it depends: you have to find out from your individual advisor/department/university. Furthermore, you characterisation

In most (if not all) PhD programs, incoming grad students are supposed to take relevant courses...

is certainly not true internationally. Many PhD positions in Europe, for example, expect the student to already have had a Masters degree and to start doing research the minute they arrive. For those positions attending conferences starting in the first year is almost a must.
For Question 3:
The best place to look is the conference organisation itself. Often funding is given to students to encourage participation. A lot of professional organisations also offer funding for full time graduate students to travel. (But note that preferences for grants maybe given to those individuals presenting [either orally or at a poster session] at the conference.) Some examples:

The American Mathematical Society offers travel grants for any full time graduate student in mathematics to go to one of their sectional meetings, and for any last year graduate student in mathematics to go to the Joint Mathematics Meetings.
The American Geophysical Union has a host of various travel grants available. And I want to especially outline their Lloyd V. Berkner Travel Fellowship which is designed to be given only to 'AGU members under the age of 35 who are residents of countries designated by the World Bank as “low” or “lower-middle"  income per capita.' In particular, the opposite of the US citizen requirement you quoted.
Conferences like the Association for Computing Machinery's CCS also offer student travel grants. The website states: "Any graduate student in good standing, regardless of nationality, or any other criteria, except as noted, may apply."

In fact, aside from actual full graduate student fellowships, and some scholarships directly sponsored by the US government, many travel funding opportunities do not have the US residency requirement. (What they may have, however, is a pesky requirement for you to travel on US flag airlines.)

As others have said, it depends on your school, department and advisor.
There are a couple ways a first-year student might be able to secure funding:

If you're already tied to a project with an advisor, they may have travel funds as part of their grant support for some of their graduate students.
Some conferences have small amounts of awards for graduate students to help pay for the conference - you can apply to these, in hopes of getting them. Some of these do require you be presenting a presentation there.
Some universities have one-time or (in rare cases) multiple-time travel scholarships for graduate students. In my experience, these tend to be enough to soften the blow of paying for a conference out of pocket, but not enough to pay for it entirely.

The good news is I think the pressure you might be feeling to go to a conference your first year is a little off. I got very little out of conferences (including the all-important networking) until much later in my program, when I both understood what was going on better, and had more interesting things to say.


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How to Politely Decline Sharing My Research Proposal with a Fellow Student?
I recently finished my masters program and for my thesis, I was able to do something that not many people in my department had done before which was be able to conduct my research in Malawi (my school is in Taiwan). Another student a year younger than me (from the same program) showed a lot of interest in going to Malawi, too, and decided she wanted to do her research there as well.
She’s been asking me a lot of questions which I didn’t mind answering before, but recently it feels like she’s trying to take shortcuts, asking to see my proposal before she even chose her topic, asking what scales I used (even though her original topic was completely different) and then suddenly she decided to try to do a similar study to mine (and asked for my participant contact list!). Recently she’s been bugging me a lot to see my proposal and because of her earlier comments and behavior I don’t feel comfortable sharing it with her (especially because I’m trying to publish as well).
Am I overthinking things? I wonder because I am also a little annoyed because I think she’s trying to use my writing and long hours of work to choose her own topic instead of doing a proper literature review. How do I tell her I don’t want to share my proposal or give her all the answers to designing her ‘own’ study?

Which disadvantage(s) for you do you fear if you share your proposal with the other student (or answer her further questions)?

Is there a reason that it would not make sense to collaborate with this other student? Maybe suggest that she does something that builds on what you did, and the the two pieces combined could be a stronger paper. In general, collaboration is a good thing.

@JochenGlueck For instance that the other student will try to submit that work as their own and the OP will find themselves scooped or, worse, accused of plagiarism of their own work, perhaps? Just a guess.

@Dawn, I’ve already graduated and moved back home. It would be one thing if she was interested in expanding on my topic but she wants to do what I did (since it was feasible) and change one small aspect so it’s not exactly the same. I think that’s why she’s asking about my methodology and which scales I used.

@DahyeLim Why can't you collaborate with someone after you've graduated?

It’s for her master thesis, not really sure that’s a thing you do. Nobody in my dept or program has done that. We’ve only ever collaborated before for papers our professors are the lead PI on.

I am confused: you finished your thesis and went back home. She can read about your methodology & co in the thesis. If the methodology is not in the thesis then isn't this a problem? What is the "hidden" part of your work that you do not want to share because (I am not sure what)?

I would be particularly careful with your participant contact details list. Usually participants have not given consent for researchers to freely share their contact details.

You are not overthinking.
You need to be very careful. The other student seems to become your "shadow".
In the best case, they will just be a time sink. In the worst case, a degree doppelgaenger. The other person is obviously not capable or willing to take the risk of their own path and ideas and lets you go ahead. They might scoop you, presubmit, with you ending up being the 'plagiariser' of your own work or, simply, their workhorse where they will ride on your efforts.
In contrast to what others seem to think, this does not look like a collaboration on equal footing which would consist of a give-and-take.
From what you describe, I personally would be very careful to share anything and disengage, politely, if possible, but unambiguously if necessary.

Disclaimer: I overlooked the OP's remark that they already finished. This tempers my response. Still, it is valid for an ongoing candidate.

Part of being a researcher is having integrity about your research and trusting your own judgment on research conduct. If you are suspecting she will use your work in ways that will pass it of as her own work or as a shortcut in other ways, you are free to say no to sharing it.
It also takes up valuable time and energy to explain things to others, so you are also free to simply state that you need to focus on other things, or stop replying.
I was many times excited about getting to discuss research with older academics when I was a younger student, and several simply stopped replying after a while. I accepted that as them being kind enough to answer my initial questions, but not interested in the following continued discussion that I was interested in.
If I was in your situation, I would ask the intended supervisor for the other student about your conserns and let them help you make a judgment about how much is reasonable to share and about the intentions of the other student.

Without knowing more about the situation, it is impossible to say whether your concerns are valid or not. Yet, you are under no obligation to share your proposal and other advice and you do not need to provide a reason for doing so. Having said that, you may still want to give some reason for your refusal in order to keep your professional relation with the other student in good state.
The fact that you were, and the other student still is, a masters student provides a different angle to your concerns which you could use. Your thesis fulfilled (part of) the criteria needed to obtain a degree and so will that of the other student. Theses are often assessed using a wide range of criteria that go well beyond the research results presented in the thesis. Most commonly, the process of developing research questions and study design also significantly feed into the final grade of a thesis. Therefore, if the other student followed your approach too closely, they may have difficulties in convincing the markers of the thesis that they developed the research questions addressed in the thesis, and designed the study to answer these questions themselves.
I also suggest to consult your (former) supervisor about this. They will know best whether closely following a previous thesis' approach may get a student into trouble. In that case, they might even have a word with the other student.

It’s hard for me to tell the entire situation because I already graduated and moved back home (was studying in Taiwan, originally from the US). I’ve been avoiding reaching out to my advisor because these are just observations and suspicions of mine and it’s not easy to bring it up without proof.

Is this new student supervised by the same person who supervised you? I don't think you need to "prove" anything. You would only be sharing your concerns. If I was your supervisor, I would like to know about such concerns, especially since you are planning to publish your results.

She is. It’s just hard to for me to bring it up with him

This discussion progressed from "politely refuse" to "share suspicious with supervisor so he can make a judgment call". If it's the same supervisor wouldn't he realize that student #2 is proposing exactly the same research you did? You may be underrating the discernment of your supervisor in this situation.

@DahyeLim You don't need to make an accusation or bring proof. "I've been giving (new student) some advice about doing research in Malawi but I'm concerned about there being too much overlap between our projects or that giving too much help will prevent her from developing an independent thesis project." As this answer points out, there are reasonable concerns from this other student's perspective, too, not just yours. Just like giving someone all the answers for their math homework might ultimately hurt them when they haven't practiced enough for the test.

tl;dr: Diplomatically get her supervisor involved.
OP wrote in a comment that:

... she wants to do what I did (since it was feasible) and change one small aspect so it’s not exactly the same. I think that’s why she’s asking about my methodology and which scales I used

Given that this is what you experience, I suggest you bring this student's supervisor into the picture. This would not be intended to badmouth or shame her: You and her supervisor are now (supposedly) at a higher level of experience than her, including your ability to understand ethnical or pedagogical considerations.
So, suggest that, if she is interested in doing "Malawai things" for her Master's research project, you would like to discuss this in a chat with her supervisor. If she agrees, you can bring up your concern of avoiding a "shortcut", and making sure that the work she undertakes is not a trivial tweaking of your own work, but rather something commensurate with the intended breadth and depth of a Masters' research project.
If she disagrees, just declare you refuse to entertain her requests without supervisor involvement.
Remember (and you can also remind her) that she can always read your published thesis.

The benefit of this approach is, that you don't have to decide apriori whether she's making a legitimate request or not. And she doesn't even have to have decided whether she intends to act legitimately or not.

I don’t feel comfortable sharing it with her (especially because I’m
trying to publish as well).
Am I overthinking things? I wonder because I am also a little annoyed
because I think she’s trying to use my writing and long hours of work
to choose her own topic instead of doing a proper literature review.
How do I tell her I don’t want to share my proposal or give her all
the answers to designing her ‘own’ study?

Your general concerns are founded, but even more you should put a big red warning disclaimer on whatever "results" you tell her: the results have not yet been peer reviewed, so everything you did it may be 100% wrong.
Said otherwise: you can confidently tell the fellow student that you are fine with sharing your experience and know-how, but what regards the proposed research content and the scientific output of your proposal is confidential and under review, so you cannot share it until the peer-review is completed and succesful. And warn her that it may take years (unfortunately)...
To be open, but to set boundaries, you can ask the student that she writes a 5-page document on what they would like to do, where and with whom, with a bullet point lsit of the methodology/approach to her research, at the same time offering yourself to internally review it.
However, please be very careful in what "review" means.
Reviewing means "bringing out the best of what is in the document and finding flaws" and not "adding content to the document and correcting flaws".
The boundary is thin, stay on the "less time-commitment for yourself" side.
tl;dr: you did a lot of work, you may have been lucky, but to have a lucky chance you have to prepared for that lucky chance as well. Let the student do their own preparation. You can review what the students does, you cannot provide her shortcuts, but you can surely provide a feedback on what she does.

Why make up reasons about data integrity and correctness?  What's particularly wrong with "I'm sorry, but I don't want to share this before it's published?

@ScottSeidman publication is not a simple "stamp" on the document.

yes, the results of the OP have not yet been peer-reviewed. However, the OP states that they have obtained these results for their masters thesis and that they have finished the masters. Therefore, the results have at least gone through one stage of reviews (marking) within the university. Thus, the results should have at least some credibility.

OK, then go with "I'm not comfortable sharing this" without further explanation (though there are reasons why data sharing for published material is important, and increasingly required by funding institutions).  It's not the publication red line I have issues with (though the downvotes aren't mine) -- it's the false justification.  The important thing is to let the requester know where their request stands.  "...the scientific output of your proposal is confidential and under review, so you cannot share it until the peer-review is completed and succesful." is generally not true

She never even asked about results or seeing my final paper, just my proposal (that I sent in to the ethics review board). That’s why I’m a bit worried she’s going to try to copy parts of my study instead of expanding on what I did and the results I found

I am used to proposal being confidential.
@ScottSeidman what is the false justification you talk about? unreviewed pre-reviewed research should be shared with co-authors of the said research at maximum, surely not with the random student asking for "hints" in writing a proposal...


text:
What's the current state of play of efforts to reform academic publishing to more open source like inclusion of non-significant results?
My understanding is that publishing model of academic research (i.e. publishing in journals) is a bit broken mostly in the sense that non-significant results are not published.
Key factors are:

Journals have a monetary incentive to publish 'exciting' results
Researchers can be unwilling to share non-significant results early for fear of having credit for their idea stolen.

This seems to be a bit at odds with the scientific method where by results of a experiment should be reproducible, but if non-significant results are being ignored then, then many published results may just be a p-value hack (obligatory xkcd). This does seem to be a real problem - ie. The Replication Crisis.
On the other hand, I'm very impressed with the state of open source software - particularly within web development, (it seems that) the vast majority of modern web dev tooling is created openly and transparently via the open source model.
The question is - are there attempts to develop an alternative publishing model for scientific experimentation?
Key features I'm particularly interested in, is the ability to express an experiment in a machine readable format, and have similar experiments be discoverable.

I think RSOS is an example. https://royalsocietypublishing.org/rsos/replication-studies

"ability to express an experiment in a machine readable format" - how?! I work on somewhat related things for a number of years now, and this proposal sounds waaaaay overly ambitious. paperswithcode exist in the field of ML, but it is just a collection of github repos - running the code is a massive, hard-to-automate effort. Or did you mean something like Zenodo, just with more granular tags?

"more open source" and "like inclusion of non-significant results" don't really seem compatible to me - the latter is not an example of "open source".

@BryanKrause This!  One could actually argue very very  many non-significant results are constantly being published (and not necessarily in bad journals).  I fail to see what this has to do with reproducibility...

@ZeroTheHero Eh, not sure I follow you, either; pretty much every meta analysis ever performed shows evidence of publication bias - that is, evidence that studies that return p-values that are not significant are not published as often as studies that return p-values that are significant, even though one would expect a mixture of both if effects were real (but small), as expected for most tested hypotheses. The issue with reproducibility is that for effects that are actually zero, this publication bias means that the spurious non-zero results are published and contradictory ones are not.

@Lodinn You might be right, and that's exactly what the question is. I'm curious if any real efforts have been made for this concept. The ideal state would be some perfect representation of experiments in a machine readable format. But presumably still workable would be a searchable solution where humans have to manually link experiments.

The biology journal eLife, which is regarded as a very good journal, is experimenting with a model where papers are published alongside the peer reviews, irrespective of what the reviews say. This should allow the publication of results which the reviewers don't view as novel or significant.
https://elifesciences.org/about
Once upon a time they talked about publishing executable articles, but I don't see anything about that after a quick glance at the website, so perhaps that experiment wasn't a success.
UPDATE:
This was just announced https://elifesciences.org/labs/dc5acbde/welcome-to-a-new-era-of-reproducible-publishing
The idea is to make the paper a sort of notebook, comparable to Jupiter or RMarkdown, allowing the reader direct access to the code and data, allowing the change and reexecute the code etc. I assume is runs on some sort of firewalled, managed VM system, like mybinder.org

The possibility of malware imbedded in executables probably discouraged "executable articles".

I think the idea was to make use of infrastructure simlar to that of https://mybinder.org/ to run computational notebooks in non-connected virtual machines. But to be honest, I suspect that was too limiting to be useful.

This just announced https://elifesciences.org/labs/dc5acbde/welcome-to-a-new-era-of-reproducible-publishing

@IanSudbury, probably you should incorporate these update-comments into your answer, so that they don't get lost if/when comments are purged?

With some clarifications obtained from the comments, I would now attempt to answer. Brace yourself for a long and, perhaps, a bit controversial post.
Some efforts are made to make science more reproducible and transparent. But I believe that what you are hoping to achieve here is fundamentally incompatible with science as we know it. And the key reason for that is that (applied) science is not the most rigorous activity on the face of the planet. Perhaps it is a bit ironic given that it is used as a standard of rigor and thoroughness, but the industry might actually have an edge over it.
Scientists' job is to find new things that might be useful. It is unrealistic to expect them to be able to make things ISO-compliant and provide installation instructions for half a dozen of distros and fix every bug arising from an update in an external dependency. Some fields do better in this regard, some worse, but without serious industry backing, the resources required for this level of coverage and continuous support are just not there. The same argument can be made for open source software. The way the whole system is currently set up is that scientists do curation and heuristics, and only then some serious engineering effort is poured in. I would expect the bottom line to rise over time, but still be consistently behind that in the industry. It is, and will be for foreseeable future, a tooling problem: most scientific software can produce, say, r^2 values, but that would be far behind what is actually required. As soon as you know the requirements and specification in enough detail, it is not science, it is engineering, and not the most creative part of the latter, either. We will not have nearly enough people and money to do bleeding edge research with full reproducibility - instead, the best studies will eventually stand out and grow, while the worse ones will be buried under the sands of time. Like in many things in life, it is often more efficient to invest $1000 in one idea than $1 in a 1000 ideas each. And the balance is generally somewhere in between, some ideas will get $500, some $100, some $1. Scientists generate lots of ideas, so naturally, most of them would not be getting $1 in this example just to keep going. What that $1 gets you changes over time, but it is never much.
As an anecdote, I once sat down with people from a big IT company who were giving us a product presentation for a joint project and describing roles for a team of 7-10 people who were supposedly doing the technical part of this project. That felt utterly out of touch, I could feel schizophrenia kicking in, as I was literally the only person covering all these roles on our side. And every time I configure iptables or Docker containers or figure out JWT authorization, I am hurting my research career (and, arguably, wasting taxpayers' money). There are better examples of academia and industry working together: if you look at some of the foundational works in machine learning or some branches of computer science, the code is very poorly written. There are no automatic tests - this is another huge problem, by the way: to write tests, you need to know the answer already. Early internet name resolution system in a form of a plain text file was maintained by just one amazing gal before someone finally decided to invest resources for a proper overhaul. All these things were solved, just not by the academia alone.
Another problem to consider is a socioeconomic one. You have citizens paying taxes, and they are ultimately interested in consumer goods and well-being of the industry. Being an average Joe who can't do much of rocket science but, you know, comes to the factory five days a week and produces parts for Quantum Superiority™ 3000. Prestige is fine and well, but the reason many people care about it is not having to pay triple for Quantum Leap™ 2 produces in some other country because they do not have a comparable technology. Scientists are generally more liberal and cooperative people than average, but for a government, 100% reproducibility with minimal effort in all but the most fundamental sciences means securing international cooperation and playing the centipede game on a global scale. Scientists may strive to benefit all of the humanity, but funding agencies operate differently, and there are lots of politics involved in these decisions (say, NSF would strive to reduce the friction and waste domestically while benefitting scientists from Russia and China as little as possible).
You list web dev tooling as an example, but it only became open and any good at all when companies started competing on something else. At first, the concept of the wheel is a closely guarded secret, but then it is out, you are building cars, and finally may agree to come together and standardize wheels and roads.
All that is to say that we are not getting zero-effort full reproducibility anytime soon, if ever. One could define some arbitrary standards and develop tooling to easily achieve them, but that would just move the goalposts. Science keeps self-correcting to stay one hit ahead of the flock, and paradoxically that means striving for making our lives just hard enough to stay busy. As soon as something "just works", we would move on to the next thing that still does not. This is just our human condition.

People absolutely try. I can't name the journals that try these off the top of my head, but as you can see from that Wikipedia section, there are journals that:

Do double-blind peer review (authors don't know who the reviewers are, and vice versa)
Do triple-blind peer review (authors & editors & reviewers don't know who each other are)
Do open peer review (everyone knows who everyone else is)
Do open peer reports (reviews are published together with the paper)
Do open participation (reviewers self-select to review the paper)
Do post-publication peer review (every paper is published, reviews are done after publication)
Do results-blind peer review (reviewers receive a manuscript where the results & conclusions are omitted)
Do two-stage results-blind peer review (review done in two stages; in the first stage reviewers don't know the results/conclusions, in the second stage they do)
Do novelty-blind peer review (reviewers are specifically instructed not to comment on whether the paper is novel, only if it is correct)

The fact that the traditional model has endured is a sign of how robust it is. Everyone knows it is flawed, but nobody has been able to come up with a better model.

Which of these are relevant in encouraging publication of "non-significant results"?  Isn't the OP mostly about that?

@GEdgar Do results-blind peer review (reviewers receive a manuscript where the results & conclusions are omitted) <--


text:
Are academic salaries in Belgium always based on the number of years completed since PhD?
I've read that in Belgium academic salaries are based on years since PhD. If this is the case, is this always the case? Are there special cases where someone would be paid more than their "years since" rate? Like, for example, if an early career scholar brings in a very large research grant: still the "years since" rate? It would seem difficult to keep talent with such a system so perhaps I am misunderstanding something.

I work at a major Flemish institution (but am not local). Here there are different salary scales, depending on your rank.
You start as faculty as a "ZAP" (tenure track Assistant Professor). It is true that your salary increases every year. But that is normal I guess. To keep track of inflation I guess.
In order to have a more significant pay rise you need to advance through the ranks, get tenure, become associate, become full professor, etc.

Thanks for this but I am not quite sure it answers the question. Perhaps to clarify just a bit more: in the UK, where I am currently based, one's salary is roughly based on experience but is not tied to how many years you are post PhD. Doing things like, say, getting a major research grant allows you to gain promotions more quickly and often skip over ranks or points on the salary scale and so on. If you are being hired from another institution you can negotiate what your salary and, at times, what your rank is. Is this the case in Belgium?

I ask because I am starting talks about moving to a Belgian institution. If I was moving in the UK I would be going in to the discussion saying "I want to be X rank at Y salary" and go from there. That doesn't seem to be allowable in Belgium...

I too moved from the UK to Belgium. I managed to have my starting salary raised but not my rank. I was a Senior Lecturer in a non Russell group university and I had to "restart" as a tenure track Assistant Professor. Still worth it.

It might be possible to rise more quickly, but there are some hoops you have to go through. Do you speak Dutch already? At what level will you start? Here for example to go from associate to full there have to pass 3 years they say. It seems there might also be an unwritten rule sadly that you must have c1 in Dutch to go to the next rank after that.

I'm senior lecturer at a Russell Group Uni and I'd be bringing a €1.5mil ERC starting grant with me (thanks Brexit), so I would be expecting tenure wherever I go. If that isn't possible in Belgium I probably need to keep looking. I don't speak Dutch, no.

Well if I were you, once they make you an offer, I would say that you are only coming if they offer you tenure already. It'd be hard to say no to 1.5M€. Also see if you can get out of having to learn dutch. If you are going to KUL, they really mean that you have to learn it. It's really a problem for some of them to have to speak another language.

Thanks for your help with this, it gives some good perspective! We'll see what happens.

The answer by TheWanderer is extremely useless and full of errors. You do not start "as faculty as a "ZAP" (tenure track Assistant Professor)." ZAP means that you are senior faculty member: AP, Assoc. Prof., Prof., Full Prof. If you start at AP level then you are referred to as ZAP tenure track (Assistant Professor).The "AP" in "ZAP" has nothing to do with Assistant Professor. ZAP is "Zelfstandig Academisch Personeel." Now regarding salary increases, every year you advance along the salary steps. Every three years there is a salary increase. This increase has nothing to do with inflation. This is a salary progression: the longer you work for a given university the more money you get (up to a limit of course). Then on top of that there is also inflation indexation. It takes place conditional on inflation index--thus no predetermined paths. Just google for example "KU Leuven salary" -- and you will find official salary tables on the website. As an AP you would normally start at step 7-9 t KU Leuven, for example.


text:
Should I email the same professor about supervision this year, If I failed in his interview previous year
I had the opportunity to interview with a professor and two of his PhD students for potential supervision in the mm-wave circuits group. Unfortunately, during the initial interview, which focused on the bioelectronics group, I struggled with some basic electronics questions that I had not revised thoroughly. As the interview progressed and delved deeper into the topic, I found it challenging to provide satisfactory answers, leading to a less-than-optimal outcome.
The second interview, which was more aligned with my interest in microwave circuits, took place the following day. Despite my efforts to study microwave concepts in preparation, my undergraduate-level knowledge in this area proved limited. While I managed to satisfy the interviewer with my understanding of microwave circuits, the conversation eventually shifted to circuits and communication aspects, where I once again struggled to perform well. As a result, I did not hear further from the professor or the research group.
I want to emphasize that I am not seeking justification for my performance during those interviews. I understand the importance of having a strong grasp of electronics and microwave circuits when pursuing this field. I simply wanted to share my experience.
Now, as I plan to reapply to the same research group this year, I have been working on three patents, which I hope to disclose during the interview period. Additionally, I am committed to thoroughly revising my knowledge of electronics and circuits concepts.
Here comes my question: Would it be a good idea to email the professor now, before the start of the application/intake period, to express my continued interest in the research group? Or should I wait until the application period begins? Or perhaps, is it not advisable to email the professor at all?

where in the world. Different cultures have different customs.

How long ago was the first interview?

first interview was 20 to 25 minutes whereas the second interview was 30 to 35 minutes long

You can certainly send the email, now or later, but I'm not sure why you expect a different outcome. The patents won't (I'd guess) compensate for not doing well answering relevant questions. If you can find reasons to think it would have a different outcome this time, then you can ask about it. Otherwise, you might better spend your efforts elsewhere.
But if you send an early email, include something about why you think things are different now. What have you done about the specific knowledge needed by this group?
Simply applying again during the normal process would might not even get you an interview if there is memory in the system about the previous outcome.

I did not apply through university portal, It was only email conversation and interview with PhD students, not with professor himself.
I wanted to say that these patents (a journal paper can be published by combining the three of them but first we have to wait for them to be filed) would somehow justify what I have been up to for this past year and would highlight my research potential, however the patents are not related to field of this professor which is the area I want to apply to.
What do you think, would this be any helpful ?

Interviewing with the same investigator would suggest to that investigator that you really want to be in that lab, perhaps connoting very strong motivation that might make the investigator take a second look.
That said, my though process would be "this is a two-way street", and I'd want some hard evidence that you've spend real effort making yourself a better candidate for that lab, minimally selecting coursework that would shore up the weaknesses that were noted during your first interviews.  This doesn't mean that your chances are zero if you haven't done any work in that direction -- but that's how I would approach the situation as an investigator.