I think that the really problematic edge cases are not questions but users. Many questions will tend to average out over all users and just influence the average accept rate, which will just change the definition of a "good accept rate", and not really causing a problem unless someone is adamant that it must. be. 70%.
.
But then you will also end up with people who tend to do lots of research before asking questions, and consequently end up asking almost, or perhaps entirely, exclusively tough questions that there may not even be answers to.
And then it gets trickier: People will post answers to these questions that are best-guesses, but wrong, and people will upvote them because they are the closest thing to an answer for the question. This means that even a proposed scheme to base the percentage of acceptable questions on the number of upvotes to the answers of these questions won't necessarily work.
So the situation is that there's an unclear definition of a 'correct answer': does this mean "the definitive answer to the question" or just "the closest thing that we have to a correct answer"? Until this is clearly defined and agreed on by both the poster and the voters (for all possible values of poster
and voter
BP) it's very difficult to quantitatively assess whether someone is responsibly accepting correct answers.
A different, and perhaps more effective, tactic would be to provide a way for people flag a given answer as the correct one, and to show the percentage of those that exist for a given user. This is not foolproof either: for example, people may misunderstand the user's original question.
It seems appropriate, though perhaps impractically long-winded, to allow up- and down-voting on {the flagging of an answer as inappropriately non-accepted}. The question at that point becomes one of determining what the relevant level of precision is.
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