We posit that this perspective is too limiting, especially with respect to linguistic data, where each individual's idiolect and linguistic background can give rise to many different -and yet equally valid -truths.
in highly subjective annotation tasks, the differences between annotators cannot be captured by simple models such as scaling all instances of a certain annotator by a factor.