Abstract Causal Bayes nets (CBNs) provide one of the most powerful tools for modelling coarse-grained type-level causal structure. As in other fields (e.g., thermodynamics) question arises how such characterizations are related to characterization their underlying structure (in this case: token-level relations). Answering meets what is called a “coherence-requirement” reduction debate. It provi...
