I am an engineer working in molecular neuroscience field, hence getting exposure in both solving practical problems (how to image fish brain) and molecular bio questions (do neurons X connect to neurons Y?). Our field spend a lot of time highlighting reproducibility crisis but I don't seem to be able to find references or writing on the following problem of resources allocation:
- funding experiments vs
- funding better experimental design and data shepherding
As I see it today (from the perspective of R1 US institutions) most resources are given to independent professors who then give it to students to work on either novel problems (which leads to waste of time because students are not professionals yet) or well-established problems (which leads to producing a lot of new data about old molecule X that nobody cares about). Some are arguing that shepherding data is a good investment, but it is rare.
Which are the philosophers or theories discuss aspects of experimental design, particularly in regards to value-theoretic or economic considerations?