Most (all?) predictions are actually conditional. A prediction about the next election is understood to be conditional on “assuming the sun doesn’t go supernova and kill us all first”, the same supernova-exception applied to the pendulum, along with a host of others.
The professor, doing Newtonian mechanics, didn’t just make a prediction. They presented a derivation, where they made many assumptions, some explicit (ignoring air resistance) others implicit (the hook holding the pendulum was assumed stationary in the diagrams/explanation, no supernova was represented in the diagram). The pendulum falling over violated the assumptions that were made clear (beforehand) in the explanation/derivation. So the Bayesian has data something like “Newtonian says P(period =~ 3.6| these assumptions) is high”. “these assumptions” was not true, so we can say nothing about the conditional.
The explanation is where the professor committed to which things would be allowed to count against the theory. A prediction based on this model of what happened is that pseudo-scientific theories will very often engage in explanations that lack clarity and precision, in order to sweep more genuine failures into the “assumptions didn’t apply” bucket.
Most (all?) predictions are actually conditional. A prediction about the next election is understood to be conditional on “assuming the sun doesn’t go supernova and kill us all first”, the same supernova-exception applied to the pendulum, along with a host of others.
The professor, doing Newtonian mechanics, didn’t just make a prediction. They presented a derivation, where they made many assumptions, some explicit (ignoring air resistance) others implicit (the hook holding the pendulum was assumed stationary in the diagrams/explanation, no supernova was represented in the diagram). The pendulum falling over violated the assumptions that were made clear (beforehand) in the explanation/derivation. So the Bayesian has data something like “Newtonian says P(period =~ 3.6| these assumptions) is high”. “these assumptions” was not true, so we can say nothing about the conditional.
The explanation is where the professor committed to which things would be allowed to count against the theory. A prediction based on this model of what happened is that pseudo-scientific theories will very often engage in explanations that lack clarity and precision, in order to sweep more genuine failures into the “assumptions didn’t apply” bucket.