In digital humanities research operationalization often only means (a), i.e. that in the research design some kind of workflow or pipeline is developed, that is used to automatically extract some features from the empirical material (text). Often literary concepts are adopted uncritically, when, in fact, critical reflection on the usage of the concepts in the sense of (b) is needed to guarantee that the workflow returns results that (c) are actually valid. The last point holds even then, when statistical validity metrics are incorporated in the workflow, since those tests can only answer how good the machine learning model or the algorithm worked, but not, if the quantified results translate back to literary concepts. This objection follows the main line of argumentation of Pichler and Reiter (2022), who argue for the importance of validity while maintaining its untenability for many real-world scenarios in the digital humanities.