> Second thing. The best way to get tenure is to have such a huge group working for you (e.g. 30 grad students), because the provost will be terrified there isn't room for other grant writers in the department to get the money to support them and the lab you've built.
There's another factor too. More students means more papers and your h-index goes up. Were we to suppose that all students were equal and that there is a noise associated with the likelihood of publication and another noise with the number of citations then if either of those noise variables are large, you should maximize quantity over quality. Because you're simply increasing the odds that you'll hit a jackpot.
In fact, if you pull the data from csrankings.org you'll find that the first 30 (all I pulled because I'm lazy and not a web person) school's rank is practically a function of the number of publishing professors at that university. So the "more workers = more better" tactic actually scales from lab to department. If we look a little harder, I think we can all see the limitation of the metrics being used here and why they're so easy to hack. More importantly, why these metrics result in a dominating momentum force (aka. rich get richer). Maybe we should start reevaluating how we are evaluating systems. After all, it is neither fair nor an efficient usage of resources. If we're going to continue the trend though, the only solution is to allocate more resources... (which to be fair the pool of available resources is increasing year over year, but the allocation isn't)
There's another factor too. More students means more papers and your h-index goes up. Were we to suppose that all students were equal and that there is a noise associated with the likelihood of publication and another noise with the number of citations then if either of those noise variables are large, you should maximize quantity over quality. Because you're simply increasing the odds that you'll hit a jackpot.
In fact, if you pull the data from csrankings.org you'll find that the first 30 (all I pulled because I'm lazy and not a web person) school's rank is practically a function of the number of publishing professors at that university. So the "more workers = more better" tactic actually scales from lab to department. If we look a little harder, I think we can all see the limitation of the metrics being used here and why they're so easy to hack. More importantly, why these metrics result in a dominating momentum force (aka. rich get richer). Maybe we should start reevaluating how we are evaluating systems. After all, it is neither fair nor an efficient usage of resources. If we're going to continue the trend though, the only solution is to allocate more resources... (which to be fair the pool of available resources is increasing year over year, but the allocation isn't)