<anchor xmlns="http://www.tei-c.org/ns/1.0" xml:id="id_docs-internal-guid-8bd8e8a2-7fff-317f-f5bd-4eeed432713f" />This paper started out as a report on the state of the art in text classification, but over time it became much more a reflection on the pitfalls in modeling genre using classification. The start of our research was motivated by developments in text classification: Recent years have seen new approaches like gradient boosting and deep neural networks. Our initial goal was to inform about these approaches, which are seldom used yet in the digital humanities. But this proved to be only a starting point for a deeper exploration of genre structures of our collection of dime novels (‘Heftromane’, ‘Groschenromane’).