Another thought: every individual may be involved in many projects. So if you look specifically at their most well-known project, then that’s somewhat of an unfair advantage for the project. Whereas if you were looking at a randomly selected project that a person published, then it may well be that that one’s less well-known than the person themselves.
E.g. the study you (OP) linked says:
Pair a well-known artifact with the person who built it and, in 7 of 10 pairs, the artifact wins. The reinforcement-learning library Tianshou scores 0.78 while its sole author Jiayi Weng sits at 0.22 — the work propagated; the name behind it did not.
I’d say this is not surprising, as when you condition on “well-known artifact”, you should expect something like regression to the mean in well-known-ness when you move on to another entity.
Another thought: every individual may be involved in many projects. So if you look specifically at their most well-known project, then that’s somewhat of an unfair advantage for the project. Whereas if you were looking at a randomly selected project that a person published, then it may well be that that one’s less well-known than the person themselves.
E.g. the study you (OP) linked says:
I’d say this is not surprising, as when you condition on “well-known artifact”, you should expect something like regression to the mean in well-known-ness when you move on to another entity.