Being practical, and understanding the gamification of citation counts and research metrics today, instead of going for a replication study and trying to prove a negative, I'd instead go for contrarian research which shows a different result (or possibly excludes the original result; or possibly doesn't even if it does not confirm it).

These probably have bigger chance of being published as you are providing a "novel" result, instead of fighting the get-along culture (which is, honestly, present in the workplace as well). But ultimately, they are (research-wise! but not politically) harder to do because they possibly mean you have figured out an actual thing.

Not saying this is the "right" approach, but it might be a cheaper, more practical way to get a paper turned around.

Whether we can work this out in research in a proper way is linked to whether we can work this out everywhere else? How many times have you seen people tap each other on the back despite lousy performance and no results? It's just easier to switch private positions vs research positions, so you'll have more of them not afraid to highlight bad job, and well, there's this profit that needs to pay your salary too.

Most of these studies get published based on elaborate constructions of essentially t-tests for differences in means between groups. Showing the opposite means showing no statistical difference, which is almost impossible to get published, for very human reasons.