Evaluators are interested in capturing how things causally influence one another. They are also interested in capturing how stakeholders think things causally influence one another. Causal mapping, the collection, coding and visualisation of interconnected causal claims, has been used widely for several decades across many disciplines for this purpose. It makes the provenance or source of such claims explicit and provides tools for gathering and dealing with this kind of data, and for managing its Janus-like double-life: on the one hand providing information about what people believe causes what and on the other hand preparing this information for possible evaluative judgements about what actually causes what. Specific reference to causal mapping in the evaluation literature is sparse, which we aim to redress here. In particular we address the Janus dilemma by suggesting that causal maps can be understood neither as models of beliefs about causal pathways nor as models of causal pathways per se but as repositories of evidence for those pathways.