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This leads to another problem that we (the science community) are already facing: how should we allocate funds between older and more established researchers vs new researchers? Or, who will be the next Einsteins?

If you only fund the more established researchers, then new researchers are starved out and more likely to leave the field. However, my belief is that new researchers are more likely to develop big new innovations than (say) the really old professors that are well past their prime.

You also have another related problem: given a large pool of new researchers, who are the ones that will be really good? Plus, there are other possible goals, like spreading the money around to broaden the base of researchers.



> how should we allocate funds between older and more established researchers vs new researchers?

Reasonable question with no precise answer, but I imagine a manager would seek a balance between the two as with any company or team. Some big hitters but you've got to see where your next Einsteins are coming from.

There's nothing about this that is solved by metrics. Metrics just help you might shallow decisions quickly, and provide ways for academics to game the system by manipulating those metrics.


Einstein solved this problem by doing his best work before joining academia, and winning lifetime funding as a reward afterward.


Einstein was not peer reviewed either. Peer review became standard only later.

That is to say, whatever worked for him or that era wont work for contemporary person today.




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