┌───────────────┬───────────┬──────────────┐
│ │ iteration │ no iteration │
├───────────────┼───────────┼──────────────┤
│ informative │ pragmatic │ subjective │
│ uninformative │ - │ objective │
└───────────────┴───────────┴──────────────┘
My main disagreement with this model is the empty bottom-left box - in fact, I think that's where most self-labeled Bayesians in industry fall:- Iterating on the functional form of the model (and therefore the assumed underlying data generating process) is generally considered obviously good and necessary, in my experience.
- Priors are usually uninformative or weakly informative, partly because data is often big enough to overwhelm the prior.
The need for iteration feels so obvious to me that the entire "no iteration" column feels like a straw man. But the author, who knows far more academic statisticians than I do, explicitly says that he had the same belief and "was shocked to learn that statisticians didn’t think this way."