I've seen this, and it's happened to me. I'm at a much lower ranking uni and we partner with higher ranking unis and I can tell you that I know quite a number of people at top 5 universities that do not know what an expectation value, probability density, or covariance is. They get attached to my papers but I do not get attached to their papers, even if I put in more work than the reverse situation (I can't tell you what some of my coauthors did). I wrote an entire NSF grant, that we won, and my advisor told me I only played a small role. Even if true, that should be a red flag that the system is broken. Why is this so much about politics?
What we're seeing is the meritocracy-metric paradox. Where metrics are literally the biggest killers of any meritocracies. Every metric can be hacked and the more reliance you place upon them, the more they will be. The problem is people think metrics perfectly align with objectives and that this alignment is static throughout time. Neither of those is true and it is baffling to me that people either aren't willing to admit it or are willing to and then just continue as if it didn't. The world is fuzzy and metrics are just guides. I thought the difference between humans and machines was that we could generalize instructions to the intent and not the letter.