Theory 19/Refinement
Learning Rates Fall With Scale
The claim
Observed learning rates for energy technologies fall once deployment scale is controlled, because early gains came from factory learning rather than cumulative output.
01Mechanism
Cumulative capacity correlates with time; the true driver is process improvement.
02Prediction
Rates should fall in models that separate the two.
03Refutation
Stable rates would remove the confound.