So, what doc on the web would most concisely rid me of exactly my misunderstanding?
I do not know the answer to you question. Here is my best guess after a couple minutes of trying to answer the question.
Short answer: Bayesianism is not about priors, it is about how evidence should change priors.
The Bayesian approach is all about evidence. Bayesian probability theory is the math of evidence. It needs a prior to work, because evidence is all about how much beliefs should change, so you need a prior to change. You could also do a lot of the Bayesian analysis without choosing a prior, and just write it down as "how much your beliefs w...
After the terrorist attacks at Charlie Hebdo, conspiracy theories quickly arose about who was behind the attacks.
People who are critical to the west easily swallow such theories while pro-vest people just as easily find them ridiculous.
I guess we can agree that the most rational response would be to enter a state of aporia until sufficient evidence is at hand.
Yet very few people do so. People are guided by their previous understanding of the world, when judging new information. It sounds like a fine Bayesian approach for getting through life, but for real scientific knowledge, we can't rely on *prior* reasonings (even though these might involve Bayesian reasoning). Real science works by investigating evidence.
So, how do we characterise the human tendency to jump to conclusions that have simply been supplied by their sense of normativity. Is their a previously described bias that covers this case?