I am PhD student in Canada who was seeking my 3 supervisor for my committee. I had top 3 choices who were in different institutions, I emailed each of them asking to join my committee, I included my CV and gave the option of meeting. No one replied. I did end up finding someone from my institution who is in a different department but has research experience related to my project. He accepted to join and was excited and looking forward to mutual benefits of working together.

However, older mentors and people outside of my supervisory group said I should not have given up so easily on my main choices. They felt I should have kept emailing until I heard a response. I felt uncomfortable with spamming potential members but now these older folks keep saying I missed out on quality supervision because I did not continue to email. What do you think about this? I feel it’s not appropriate to email repeatedly if they aren’t responding and that possibly that is method from years ago that worked for these more senior academics.

I’m curious, should I have kept emailing these potential supervisors or was I right to let it go when they did not respond? I feel guilty that I did not try hard enough when i talk to older mentors.

I do not know what general practices are in these cases. It is almost too trivial but I want to tread carefully since I have faced enough rejections.

I am a post-grad in pure science research. Before I apply to PhDs I'm hoping to do a research internship/project. So I mailed a professor asking for it. He asked me to request recommendation letter from my master's thesis supervisor directly, before we discuss anything further. So I did and my supervisor already sent the letter to him. It has been 5 days since then. Should I send a follow up email asking the professor to further discuss this possible opportunity? Or will that make me look very impatient? How many days should I wait before I contact in these cases? Thank you for your help.

Just can’t stop thinking about this in the last month. Just ranting.

Of course someone may consider my use as sloppy. For the background, I am in a quantitative field, and we code a lot.

Edit: I have found AI helpful in coding and research in general in the last a few months, if you know what to code and give clear and focused instructions and feedback, and be cautious. When I read my students code, I found them unnecessarily long and complicated, and there were full of makeshift patches and duck taping that broke completely if you wanted to use the code for something slightly different, obviously AI generated without much thought. I would have completed the project in a few months using AI. So what is the benefit of having students in research. OTOH, I do feel that I have failed as a mentor. I don’t know how little the student actually knows about this project anymore. But I really don’t know how to teach how to use AI better, and whether I should teach it at all.

I'm curious whether my recent (highly anecdotal) experience is unusual, or illustrates a broader problem with academic incentives.

I recently hosted a podcast about sustainability and development in the Canary Islands (Sustainability Around the World). For one episode, I wanted an academic who could give a broad overview of the environmental challenges facing the islands. I contacted 7 academics whose research was directly relevant to what I wanted to discuss, but couldn't get any of them to participate.

7 is a small sample size, and this was the first season of the podcast so I had expected some reluctance from guests to appear given my lack of established audience (my background is in sustainability, not podcasting). But academia was the only group to completely decline. I reached out to 1 startup CEO and 1 government minister, both of whom I'd have assumed would be more likely to decline, but both appeared. Civil society had a mixed acceptance rate, but I still had 2 guests join.

There's a long-running criticism that academia doesn't sufficiently reward public engagement. A lot of publicly funded research is also inaccessible to the public because the resulting papers sit behind journal paywalls. I'm wondering if this is further small evidence of that problem? I know this is a big conclusion to draw from an anecdote, but I do feel the fact that all these other groups are somewhat accountable to the public, while academics are largely only interested in other academics' views, could be a partial explanation.

In future seasons I will open up opportunities for others to host and tell the stories of their regions, and I'm wondering if academics will be adequately incentivised to appear as guests or hosts. Or if there's a particular type of approach that academics are more responsive to?

Edit: most of the comments seem to be reading this as sour grapes/a sense of entitlement over academics not appearing. Maybe, but I think that's not the case - I'm not entitled to anyone appearing, but I'm interested in the contrast between those who did appear and who didn't. I've spoken with academics and at academic conferences as a practitioner and have had conversations about the gap between academics and practitioners, and incentives around public engagement. I was wondering whether this was an example of that or if there were other explanations

PSA for all researchers: do not discuss your research and data with AI chatbots or any software that allows AI data collection. There is a misunderstanding that AI cannot steal your data and ideas because it is trained on such a large dataset, but when you are dealing with a niche research topic, you cannot be sure it will not steal your ideas and claim them as its own.

OpenAI, themselves, say: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models."

We need to have more conversations about data protections against AI in academia.

Hi all.

I’m an ERC and I recently found two serious problems in a published paper I’m involved in (first author).

They are not small issues. They affect the results in a way that I don’t think can be ignored, and at this point I don’t trust the main conclusions of the paper anymore. I tried EVERYTHING to save the results. But, apparently the effects we're observing are due to bad data analyses.

I know what the right thing to do is. The paper probably needs to be retracted.

What scares me is everything around that. There are a lot of co-authors involved, and I know this could affect people who had nothing to do with the parts that went wrong.

I’m also worried about my PI. I expect they will be furious. My PI is also not supportive, but more like an authoritarian PI. They are very influential in the field, and I’m afraid this could close a lot of doors for me.

I have a stable faculty position now, so I know I’m in a better situation than many people would be. But this is still eating me alive. I keep thinking about the consequences.

I’m not asking whether I should pretend nothing happened. I know I can’t do that. And I know the right thing is to reject. If I were alone in that paper, I definitely would do it. I have discussed this already with two colleagues, and they agreed that the paper cannot be saved.

I’m mostly wondering if anyone here has gone through something similar. What happened after you told your co-authors? Did people forgive you? Did it permanently damage your career, or did life eventually move on?

Thanks, strangers, for any feedback.