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by aborsy
1937 days ago
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There is a lot of politics in academia, but it’s mostly between professors, not professors and students. Frankly I have seen it’s mostly students who abuse the system. There are a lot of goof-offs who are paid by taxpayers and just want to party, have fun and get a degree. This is just my own observation. Why should a supervisor neglect a student if student is doing an OK job? What’s the motivation here? I am not saying either side is always at fault. Rather, the person in power should not automatically be blamed. |
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Pretty complex, and I don't think I can even do the full issue justice, but from my observations it comes down to:
1. Egos - some advisors get their nose out of joint when students start to surpass them in knowledge or ability on a certain topic (this hasn't been my issue, but I've witnessed it).
2. Boredom with a project - YUP - my advisor regularly gets 'bored' by a project because it isn't producing the data he wanted (he likes to create stories instead of seeing what story the data tells) or because it isn't moving fast enough for his desires.
3. Personality clashes/issues with management - this has been an enormous issue for most of the students in my lab, save for a couple of male students over the past two decades. When issues are brought to my advisor's attention, he will say the right things, apologize, and then amend his behaviour by wholly ignoring and avoiding the student for weeks or months on end. This is to the tune of cancelling in-person meetings, invalidating their opinions during lab meetings, avoiding them when they approach his office, etc. etc.
4. Cheap labour - students in their upper years, particularly those who are productive and successful - are great work horses. Why would you want to let go of a cheap and productive employee just when they start to churn out lots of great data for you? Casually ignoring or constantly expecting more before they can defend is a slimy way of using a student to generate more data (and therefore more revenue) for your lab.
I can't comment on comp sci situations, but in life sciences, particularly those requiring wet lab bench work, point #4 is a _very_ common issue in PhD years 5+.