Today’s Inkhaven post is an edit to yesterday’s, adding more examples of legitimacy-making characteristics, so I’m posting it in shortform so that I can link it separately:
Here are some potential legitimacy-relevant characteristics:
The reasoning is logically valid.
The assumptions of the argument are credible (this splits into many characteristics we can name:)
Today’s Inkhaven post is an edit to yesterday’s, adding more examples of legitimacy-making characteristics, so I’m posting it in shortform so that I can link it separately:
Here are some potential legitimacy-relevant characteristics:
The reasoning is logically valid.
The assumptions of the argument are credible (this splits into many characteristics we can name:)
The assumptions are simple.
There are few assumptions.
The assumptions have very few degrees of freedom.
The assumptions are agreed upon by many humans.
The assumptions are a strong consensus in the relevant field(s).
The assumptions are very probable according to best existing models.
The assumptions have high-quality citations backing them up.
The assumptions have been very useful (EG productive axioms in mathematics).
The assumptions are not jointly contradictory.
The reasoning is probabilistically valid.
The reasoning is not Dutch-bookable.
The reasoning is very difficult to Dutch-book (bounded cognition).
The reasoning is accuracy-maximizing.
The reasoning is a plausible extension of logic.
The reasoning employs credible priors.
The prior is close to human priors, or priors humans justifiably endorse.
The priors have rigorous frequentist justification (EG probability of a prime number based on the prime number theorem).
The priors have empirical validation.
The priors have a maximum-entropy justification.
The priors are dominant over other priors one might want to use.
The probability of the conclusion is very high.
The argument is very strong as a statistical test.
The bias is low.
The variance is low.
Confidence intervals are small.
The test has a low false positive rate.
The test has a low false negative rate.
The test is the best test to use out of alternative tests.
Robustness to outliers.
Robustness to a variety of distributions.
Good rate of convergence.