Abstract
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.