The place to start is by having far fewer PhD students, but more masters students and technicians. A 60% reduction in PhD student numbers would reflect job opportunities, and student aptitude, more accurately.
The place to start is by having far fewer PhD students, but more masters students and technicians. A 60% reduction in PhD student numbers would reflect job opportunities, and student aptitude, more accurately.
E.g. there’s increasingly an expectation that students should come into a PhD program with one or more publications already under their belt. For top programs ideally these should be first author (not yet an absolute requirement but it’s more important each year).
So you better get a good research assistant job as an undergrad so you can do that. It has to be early enough in undergrad that you have time to get the paper out before applying to grad school. So you need to be prepared to get a professor to work with you freshman/sophomore year…
So you have to have evidence of skills basically coming in to undergrad. Either be really brilliant and stand out in class, or, better, have some experience in high school to make you credible…
These pressures would only increase with fewer PhD slots. Maybe that’s fine long term but it does have a distorting effect on people’s lives if you have to make high stakes decisions that early.
There is such a lack of permanent research positions compared to postdocs and PhD students that I'm not even sure it's selecting for the best people.
on top of this you also filter out anyone who doesn't perfectly stay on this high-stakes pipeline from age 14 to tenure, which is probably not good overall for science.
economics is actually pretty close to working this way already. indeed, the job market for economics PhDs is much less dystopian than say life sciences. but there are tradeoffs.
1. The institution in question evaluates candidates as either a fit or not a fit. 2. The candidates who fit are the pool from which the positions are filled at random.
Obviously it's gameable as stated, but I think if I spent a day or two designing a better mechanism with the same premise, we'd end up with great candidates but without the hyperoptimization trap.
This is something I discovered pretty late in my life. The web pages maintained by profs barely have any info.
I have come to hate the whole "everybody looks for different things" type of answer when it comes to PhD apps. I wish profs would just spell it out on their site in concrete terms what they personally look for.
In other fields and lower ranked programs, again I wish profs would be explicit (since publications might not be expected).
Like this guy:http://math.stanford.edu/~vakil/potentialstudents.html
"So before I take you on as a new student, you should be comfortable with the foundations of the subject, which means having done the majority of the exercises in Hartshorne or my course notes, and being able to explain them on demand."
That is very explicit and sets clear expectations.
Academia isn't the only career path for those with a PhD (I worked in industry and at NASA as well), and I think students should be taught that early on. I think we deny the opportunity to learn how to conduct research to too many people due to limited resources.
Regarding student aptitude, that's hard to measure. Already we highly prioritize students who have already published as undergraduates. If we do more to ensure student aptitude, it would hurt those who may excel but were held back by a lack of mentorship during their undergraduates in how to get into a PhD program. This would also negatively impact efforts to increase diversity in science as well.
The problem is the gatekeepers such as journal corps profit from the artificial scarcity they create. There's no reason for them to only publish a certain number of "papers" in the paperless world.