Our approach is minimalist -- we code only bare causation
It follows from this that we are sceptical about the idea of more sophisticated mid-range theory with blockers, enablers etc.
Transitivity is perhaps the single most important challenge for causal mapping. Consider the following example. If source P [pig farmer] states ‘I received cash grant compensation for pig diseases [G], so I had more cash [C]’, and source W [wheat farmer] states ‘I had more cash [C], so I bought more seeds [S]’, can we then deduce that pig diseases lead to more cash which leads to more seed (G à C àS), and therefore G à S (there is evidence for an indirect effect of G on S, i.e. that cash grants for pig diseases lead to people buying more seeds)?
If termites cause a tree to fall in a forest where no-one can hear it, was it a causal event?
I found the concept of a trigger in realist evaluation totally baffling because RE is supposed to be somehow scientific, yet most forms of scientific explanation don't involve actual triggers.
The way we do causal mapping, a coded causal claim does not mean:
Irene Ng speaks for many who write about “complex systems” when she says: “What has happened in the last 50 years is that we’ve been trying to use deterministic tools to achieve emergent outcomes, essentially because those are the only tools we have learnt (systems thinkers are still a minority unfortunately). We treat complex systems like complicated systems. We try to design, specify, impose, dictate when we should be designing, enabling, intervening, stablising.”