While academic fields can create their own algorithms for field-specific problems, they are all joined together by the same basic concepts about finding the best and most quantitative ways to tie causes to effects.

Just as "most perfect" or "most square" are nonsensical, does "most quantitative" make any sense?


It depends on whether this source is using the strict dictionary definition of "quantitative", or some field-specific usage with a nuanced meaning

quantitative (adj): relating to an amount that can be measured

This is a binary, yes/no condition. Something either is quantitative or is not quantitative, with no need for comparative or superlative.

However, it may be that there is a kind of spectrum between quantitative and qualitative algorithms, and it is possible to define an algorithm that leans more towards the quantitative side of things -- ergo, one that is "more quantitative" than other algorithms.

It's the same with "perfect" and "square". Yes, as a mathematical concept, something either is square or is not square -- but in the real world, where nothing is actually square, it's fine to say some shape is "more square" than others.

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