It's definitely a toxic part of academia. Honestly if it weren't for that I'd take an academic job over an industry one in a heartbeat.
Some irony is my PhD was in machine learning. Every intro course I now (including mine) discusses reward hacking (aka Goodhart's Law). The irony being that the ML community had dialed this problem up to 11. My peers that optimized this push out 10-20 papers a year. I think that's too many and means most of the papers are low impact. I have similar citation counts to them but lower h-index and they definitely get more prestige for that even though it's harder to publish more frequently in my domain (my experiments take a lot longer). I'm with Higgs though, it's a lazy metric and imo does more harm than good.
Some irony is my PhD was in machine learning. Every intro course I now (including mine) discusses reward hacking (aka Goodhart's Law). The irony being that the ML community had dialed this problem up to 11. My peers that optimized this push out 10-20 papers a year. I think that's too many and means most of the papers are low impact. I have similar citation counts to them but lower h-index and they definitely get more prestige for that even though it's harder to publish more frequently in my domain (my experiments take a lot longer). I'm with Higgs though, it's a lazy metric and imo does more harm than good.