Rating-based compensation systems (RBCS) are a promising form of long-term compensation on intermediary internet platforms for paid digital work, namely crowdworking (CW) platforms: Crowdworkers receive an individual rating, e.g. from one to five stars, based on past performance and subjective evaluation criteria, which also then grants access to more interesting and challenging tasks and better pay for a given amount of work. Although a number of CW platforms have implemented a RBCS for years, RBCSs that potentially promoting employment relationships between CW platforms and crowdworkers play a rather minor role in CW research. This paper therefore creates the term RBCS and introduces it into the CW literature by explaining its composition, providing an overview of its distribution on German-speaking CW platforms, identifying characteristics of platforms with such a system, and reconstructing the logic of RBCSs. Evidence about RBCSs comes from a comprehensive review of 32 German-speaking CW platforms with and without a RBCS. Basically, each RBCS consists of variations of three components, namely performance and behavior thresholds, status visualizations, and incentives. Despite possible variations of RBCSs, CW platforms with a similar specialization in a task type use similar combinations of these components. Especially CW platforms for sophisticated task types such as text creation and graphic design have implemented such systems. What also stands out about these platforms is that they have a very competitive working environment and rely on skilled crowdworkers with different levels of qualification to meet clients requirements. Furthermore, this paper also reconstructs the logic of how a RBCS motivates and commits crowdworkers by drawing on extant work on regular employment from a primarily personnel economics perspective. It shows that the ...