Strong Priors Resist Falsification Via Tweaks

When a prediction fails, a sufficiently strong prior lets a modeler add a new assumption or tweak the model to explain away the contradiction and preserve cherished assumptions; doing this every time a large natural experiment fails violates scientific method and means the view is unfalsifiable.