The Pareto principle gets "interesting" when you involve hierarchical categories. For instance, the category of "researchers" is arguably arbitrary. Why not research labs? Why not research universities? If we write off 80% of universities, 80% of labs in that top 20% of universities and 80% of researchers within that top 20% of labs then actually the number of impactful researchers would in fact be .2 * .2 *.2 or 0.8% of researchers which seems extreme.

That said if we took 20% of all working people are doing useful work, then can you guarantee not all research scientists are within that category?

And indeed there are different fields and the distributions of effectiveness may be incomparable.

I think the nature of scientific and mathematical research is interesting in that often "useless" findings can find surprising applications. Boolean algebra is an interesting example of this in that until computing came about, it seemed purely theoretical in nature and impactless almost by definition. Yet the implications of that work underpinned the design of computer processors and the information age as such.

This creates a quandary: we can say perhaps only 20% of work is relevant, but we don't necessarily know which 20% in advance.