Easy To Hard Discipline Academic Careers Paths
Tasks often vary along a dimension where some tasks matter more, yet are also harder to judge for quality of performance. This spectrum appears in org management, where it is harder to judge the quality of higher level more important decisions. It also appears in academia, where STEM tasks tend to be less important but easier to judge, compared to those in humanities.
In management, the usual strategy is to first test people at lower level, less important, easier to judge tasks. Then as some folks prove themselves, slowly move those folks up the ladder to similar but more important but harder to judge tasks. Somewhat emphasize looking at the easier to judge tasks that each person does wherever they are, and moving them from orgs and divisions where it was easier to judge similar-level performance. And supplement all this with ratings of potential by people at similar levels.
It would be possible instead to place people in high org positions on the basis of their having been a good executive assistant, or having been a good biographer or historian of top executives, or having made popular books, podcasts, or videos on top management. But such moves are pretty rare.
In academia, the analogous strategy would be first have people do relatively unimportant but easier to judge tasks, and slowly move them up to the more important but harder to judge tasks. So first have them do many simple homework problems, then fewer harder problems, then replicate prior actual research, then do original research.
First work in topic areas with more math, faster feedback, easier replication, easier measurement, more data to test against, better organized concepts, lower dimensionality of concepts, more causal identifiability, more stationarity, less observer dependence, more decomposability, less interpretive dependence, less value dependence, weaker desires of funders and researchers to believe particular claims, and less adversarial sources with incentives to deceive researchers. Then more to harder topics. Supplement with ratings of potential by nearby folks.
Within disciplines, we do often follow similar strategies, starting with easier to judge tasks, emphasizing easier to judge aspects like writing quality, and relying on adjacent ratings of potential. But this tendency mostly stops at disciplinary boundaries. People who end up doing the most important hardest to judge tasks in the humanities didn’t start by proving themselves in STEM and then slowly moving to harder disciplines. They instead start with the easier to judge tasks in the humanities. Which often consist of the history of, commentary on, interpretation of, and popularization of famous prior writers in those same humanities areas.
While it is possible that this just happens to be the best way to train and select people for such roles, the usual tendencies of academic disciplines to create and protect their “turf” seems to me a more likely explanation. The top people in the humanities want to feel more in charge of choosing their successors, and to teach more classes on their topics, both of which are threatened by the STEM to humanities career pathway I outline above.
The intellectuals that I’ve been most impressed by have often trained and proven themselves first on easier to judge problems, and then gradually took on harder problems. So I suspect academia is making a big mistake here.


I’m not sure. By the time the humanities person gets to be in influential positions, writing stuff that people take to be addressing harder and more important questions, aren’t they already being judged on the quality of their current output, which can be evaluated on their own?
Like your co-podcaster, Agnes Callard, did a lot of her early training on reading, interpreting, and commenting on historical figures. But now, she’s influential largely because people find what she writes on questions they care to be insightful and useful. Isn’t the fact that people read and reward what they find insightful already a sufficiently selective filter?
Or is your claim simply that academics are leaving money on the table? That would get even more insightful things if they had scholars follow a STEM to Humanities pipeline? If so, this is empirically testable; check if the those humanities scholars who came through STEM are more insightful on average (though you’d have to control for intelligence to see the training effects).