> In short, we over-reward those at the top and dismiss the rest.
This is standard tournament theory: big rewards at the top to provide a strong incentives for excellence. Look at the prize structure in sporting events and at the three-medal rewards at the Olympics. Paradoxically the decline in quantity and quality typically seen after tenure suggests that it works in academic circles: post-docs and assistant professors are doing outstanding work because that's what it takes to "win".
It's still early days for Julia, and performance is uneven. I wouldn't use it for serious work unless 1) an expert in your field is already using it (e.g. Udell and Convex.jl) or 2) you carefully benchmark your key computations. In my case, I wrote C++ and Python benchmarks and stumbled on a performance problem that the Julia team knew about and plans to address.
"There are more advanced languages than Haskell, they aren't ML, and PL researchers/experimenters are still working out how to make them work nicely for day to day stuff."