There are no frequencies in this problem; it is a one-time experiment.
One can do things multiple times.
See my response to Dacyn below (“Classical propositions are simply true or false...”). Classical propositions do not change their truth value over time.
I tried to get at this in the big long paragraph of “‘Monday’ is an abstraction, not a fundamental.” There is no such thing as a measurement of absolute time. When someone says “no, I mean to refer to the real Monday,” they are generating an abstract model of the world and then making their probability distributions within that model. But then there still have to be rules that cash your nice absolute-time model out into yucky relative-time actual observables.
It’s like Solomonoff induction. You have a series of data, and you make predictions about future data. Everything else is window dressing (sort of).
But it’s not so bad. You can have whatever abstractions you want, as long as they cash out to the right thing. You don’t need time to actually pass within predicate logic. You just need to model the passage of time and then cash the results out.
It’s also like how probability distributions are not about what reality is, they are about your knowledge of reality. “It is Monday” changes truth value depending on the external world. But P(It is Monday | Information)=0.9 is a perfectly good piece of classical logic. In fact, this exactly the same as how you can treat P(H)=0.5, even though classical propositions do not change their truth value when you flip over a coin.
I dunno, putting it that way makes it sound simple. I still think there’s something important in my weirder rambling—but then, I would.
One can do things multiple times.
I tried to get at this in the big long paragraph of “‘Monday’ is an abstraction, not a fundamental.” There is no such thing as a measurement of absolute time. When someone says “no, I mean to refer to the real Monday,” they are generating an abstract model of the world and then making their probability distributions within that model. But then there still have to be rules that cash your nice absolute-time model out into yucky relative-time actual observables.
It’s like Solomonoff induction. You have a series of data, and you make predictions about future data. Everything else is window dressing (sort of).
But it’s not so bad. You can have whatever abstractions you want, as long as they cash out to the right thing. You don’t need time to actually pass within predicate logic. You just need to model the passage of time and then cash the results out.
It’s also like how probability distributions are not about what reality is, they are about your knowledge of reality. “It is Monday” changes truth value depending on the external world. But P(It is Monday | Information)=0.9 is a perfectly good piece of classical logic. In fact, this exactly the same as how you can treat P(H)=0.5, even though classical propositions do not change their truth value when you flip over a coin.
I dunno, putting it that way makes it sound simple. I still think there’s something important in my weirder rambling—but then, I would.