I am bemused that the vagueness of "non-core work" means everyone can consider this topic and imagine entirely different stories. As a computer science type peering into biology research with respect to bioinformatics, I have found it distressing how much biology researchers can treat their own experimental data and metadata management as "non-core work" to be avoided.

Some biology students and postdocs have described to me an antagonistic relationship to the funder or PI goals where they dismiss their responsibilities for data quality and reuse. For them, it isn't on the critical path to their paper and their career. Or, having data in disarray is, in their minds, giving them an edge to not be "scooped" in the lab. These cynical attitudes are almost subversive, in how the junior worker tries to evade or sabotage aspects of their job responsibility which do not serve them personally. I also see some who seem to engage in magical thinking, as if some other staff or informatician should come by later and clean up their mess of data, without the researcher putting in the effort. I often wonder whether they really misunderstand the problem so severely, or merely use this fig leaf to avoid feelings of shame.

I know that lines should be drawn between different roles, but there are inappropriate expectations on both ends of a spectrum. PIs should not treat junior researchers like assistants to get coffee, run personal errands, etc. But neither should junior researchers believe that the day to day grind of the scientific process is beneath them. At the scales that most labs work, there are many essential yet mundane tasks that need to be shouldered by "core" participants. The overhead of trying to delegate these tasks to a different person would either require more time than doing the task oneself, or result in abysmal quality when the hand-off is made with insufficient supporting effort.

I think that people exposed to the pop culture of startups and large corporations can absorb a mistaken idea of how easily human organizations scale. With vast numbers of skilled staff, you can create processes which scale beyond the capabilities of a typical small lab or group. These tend to develop lots of specialized roles to support that process. But, I think there is a huge inflection point between the efficient small group and the scalable large organization, where the marginal value of adding another staff member can be very small, or even negative. Many (most?) grant-funded research groups exist only because they can function in that small team mode, with relatively thin budgets and the need to wear many hats.

The only safe way to scale work under these grants is what we see already: schools expand to have additional PIs running their own small, independent labs. These eventually compete with each other almost as much as they compete with outside labs. From the host school, they get actual "non-core" services like building facilities, human resources, payroll, contracts and legal support, etc. But, no one group can really scale to have more staff and specialization focused on a single research effort. There is a reason that "big science" projects are few and far between and are mired in much more politics---the granting agencies have to be motivated to write different kinds of funding opportunity to bootstrap such projects and to continue their operation. The budgets and timelines are vastly different.