Here I’m using “Bayesian” as an adjective which refers to a particular interpretation of the probability calculus, namely one where agents have credences about an event and they are supposed to set those credences equal to the “physical probabilities” coming from the theory and then make decisions according to that. It’s not the mere acceptance of Bayes’ rule that makes someone a Bayesian—Bayes’ rule is a theorem so no matter how you interpret the probability calculus you’re going to believe in it.
With this sense of “Bayesian”, the epistemic content added by a probability measure to a theory appears to be normative. It tells you how you should or should not act instead of telling you something about the real world, or so it seems.
The use of the word “Bayesian” here means that you treat credences according to the same mathematical rules as probabilities, including the use of Bayes’ rule. That’s all.
Here I’m using “Bayesian” as an adjective which refers to a particular interpretation of the probability calculus, namely one where agents have credences about an event and they are supposed to set those credences equal to the “physical probabilities” coming from the theory and then make decisions according to that. It’s not the mere acceptance of Bayes’ rule that makes someone a Bayesian—Bayes’ rule is a theorem so no matter how you interpret the probability calculus you’re going to believe in it.
With this sense of “Bayesian”, the epistemic content added by a probability measure to a theory appears to be normative. It tells you how you should or should not act instead of telling you something about the real world, or so it seems.
The use of the word “Bayesian” here means that you treat credences according to the same mathematical rules as probabilities, including the use of Bayes’ rule. That’s all.