[hablog]

Every single bayesianism advocate is aware of this. It's so obvious that it's implicit - there's simply no need to state "95% of crime is committed by men"; this is completely uncontroversial and does not need to be discussed. The controversial part is applying bayesianism to other, more politically sensitive predictors.

[pdonis]

The proper Bayesian response would be to look for factors that are better predictors, since both "being male" and any race are very weak predictors (see my other comment upthread).

[hablog]

> The proper Bayesian response... since both "being male" and any race are very weak predictors (see my other comment upthread).

I saw your comment - you don't understand how bayesianism works. Look up "odds ratios" for the most salient concept that you're missing here.

If P(x|!y) = 0.0000001 and P(x|y) = 0.01, this relationship is extremely powerful even though it's "weak" in the sense you're using.

[pdonis]

> Look up "odds ratios"

Sure, compute the odds ratio for committing a violent crime due to being male. It is large, which in plain English means "most violent criminals are male".

But that doesn't mean the probability of a randomly chosen male being a violent criminal is large. It's still small, because you have to multiply the odds ratio by a very small prior (since the prior probability of a randomly chosen person being a violent criminal is very small). So if all you know about a person is that they are male, you still have only a very weak prediction that they might be a violent criminal. In other words, in plain English, "most males are not violent criminals".

What you need to have a strong predictor is some factor X for which not just the odds ratio but the posterior probability of being a violent criminal, conditioned on X, is large, i.e., for which you can say "most X's are violent criminals". Being male is not such a factor.

[tomlockwood]

Excellent! I hope the premises lead to the correct conclusions rather than ones ignorant of the premises.