Probability is easy to resolve when things have clear outcomes. I don’t find it trivial to apply it to probability distributions. Say that you belive that a coin has 50% chance of coming up heads and 50% chance of coming up tails. Later it turns out that the coin has 49.9% chance of coming up heads and 49.9% chance of coming up tails and 0.2% chance of coming up on it’s side. Does the previous belief count as a hit or miss for the purposes of meta-certainty? If I can’t agree what hits and misses are then I can’t get to ratios.
One could also mean that a belief like “probability for world war” could get different odds when asked in the morning, afternoon or night while dice odds get more stable answers. There “belief professed to when asked” has clear outcomes. But that is harder to link to the subject matter of the belief.
It could also point to “order of defence” kind of thing, which beliefs would be first in line to be changed. High degree of this kind could mean a thing like “this belief is so important to my worldview that I would rather believe 2+2=5 than disbelieve it”. “conviction” could describe it but I think subjective degrees of belief are not supposed point to things like that.
Does the previous belief count as a hit or miss for the purposes of meta-certainty?
A miss. I would like to be able to quantify how far off certain predictions are. I mean sometimes you can quantify it but sometimes you can’t. I have previously made a question posts about it that got very little traction so I’m gonna try to solve this philosophical problem myself once I have some more time.
One could also mean that a belief like “probability for world war” could get different odds when asked in the morning, afternoon or night while dice odds get more stable answers.
This could be a possible bias in meta-certainty that could be discovered (but isn’t the concept of meta-certainty itself).
“conviction” could describe it but I think subjective degrees of belief are not supposed point to things like that.
Conviction could be an adequate word for it, but I’ll stick with meta-certainty to avoid confusion. You could rank your meta-certainty in “order of defense”, but I would start out explaining it in the way that I did in my response to ChristianKl.
Well it clarifies that the first of the three kind of directions was intended.
If that is a miss what do hits look like? If I have a belief of 50%, 50% coin at what point can I say that the distribution is “confirmed”. If the true distribution is 49.9999% vs 50.0001% and that counts as a miss that would make almost all beliefs to be misses with hits being rare theorethical possibiliies. So within rounding error all beliefs that reference probablities not 1 or 0 have meta-certainty 0.
Note that in calculating p-values the null hypothesis is not ever delineated a clear miss but there always remains a finite possiblity that noise was the source of the pattern.
I was trying to convey the same problem, although the underlying issue has much broader implications. Apparently johnswentworth is trying to solve a related problem but I’m currently not up to date with his posts so I can’t vouch for the quality. Being able to quantify empirical differences would solve a lot of different philosophical problems in one fell swoop, so that might be something I should look into for my masters degree.
Probability is easy to resolve when things have clear outcomes. I don’t find it trivial to apply it to probability distributions. Say that you belive that a coin has 50% chance of coming up heads and 50% chance of coming up tails. Later it turns out that the coin has 49.9% chance of coming up heads and 49.9% chance of coming up tails and 0.2% chance of coming up on it’s side. Does the previous belief count as a hit or miss for the purposes of meta-certainty? If I can’t agree what hits and misses are then I can’t get to ratios.
One could also mean that a belief like “probability for world war” could get different odds when asked in the morning, afternoon or night while dice odds get more stable answers. There “belief professed to when asked” has clear outcomes. But that is harder to link to the subject matter of the belief.
It could also point to “order of defence” kind of thing, which beliefs would be first in line to be changed. High degree of this kind could mean a thing like “this belief is so important to my worldview that I would rather believe 2+2=5 than disbelieve it”. “conviction” could describe it but I think subjective degrees of belief are not supposed point to things like that.
A miss. I would like to be able to quantify how far off certain predictions are. I mean sometimes you can quantify it but sometimes you can’t. I have previously made a question posts about it that got very little traction so I’m gonna try to solve this philosophical problem myself once I have some more time.
This could be a possible bias in meta-certainty that could be discovered (but isn’t the concept of meta-certainty itself).
Conviction could be an adequate word for it, but I’ll stick with meta-certainty to avoid confusion. You could rank your meta-certainty in “order of defense”, but I would start out explaining it in the way that I did in my response to ChristianKl.
Well it clarifies that the first of the three kind of directions was intended.
If that is a miss what do hits look like? If I have a belief of 50%, 50% coin at what point can I say that the distribution is “confirmed”. If the true distribution is 49.9999% vs 50.0001% and that counts as a miss that would make almost all beliefs to be misses with hits being rare theorethical possibiliies. So within rounding error all beliefs that reference probablities not 1 or 0 have meta-certainty 0.
Note that in calculating p-values the null hypothesis is not ever delineated a clear miss but there always remains a finite possiblity that noise was the source of the pattern.
I was trying to convey the same problem, although the underlying issue has much broader implications. Apparently johnswentworth is trying to solve a related problem but I’m currently not up to date with his posts so I can’t vouch for the quality. Being able to quantify empirical differences would solve a lot of different philosophical problems in one fell swoop, so that might be something I should look into for my masters degree.