Moore & Schatz (2017) made a similar point about different meanings of “overconfidence” in their paper The three faces of overconfidence. The abstract:
Overconfidence has been studied in 3 distinct ways. Overestimation is thinking that you are better than you are. Overplacement is the exaggerated belief that you are better than others. Overprecision is the excessive faith that you know the truth. These 3 forms of overconfidence manifest themselves under different conditions, have different causes, and have widely varying consequences. It is a mistake to treat them as if they were the same or to assume that they have the same psychological origins.
Though I do think that some of your 6 different meanings are different manifestations of the same underlying meaning.
Calling someone “overprecise” is saying that they should increase the entropy of their beliefs. In cases where there is a natural ignorance prior, it is claiming that their probability distribution should be closer to the ignorance prior. This could sometimes mean closer to 50-50 as in your point 1, e.g. the probability that the Yankees will win their next game. This could sometimes mean closer to 1/n as with some cases of your points 2 & 6, e.g. a 1⁄30 probability that the Yankees will win the next World Series (as they are 1 of 30 teams).
In cases where there isn’t a natural ignorance prior, saying that someone should increase the entropy of their beliefs is often interpretable as a claim that they should put less probability on the possibilities that they view as most likely. This could sometimes look like your point 2, e.g. if they think DeSantis has a 20% chance of being US President in 2030, or like your point 6. It could sometimes look like widening their confidence interval for estimating some quantity.
Moore & Schatz (2017) made a similar point about different meanings of “overconfidence” in their paper The three faces of overconfidence. The abstract:
Though I do think that some of your 6 different meanings are different manifestations of the same underlying meaning.
Calling someone “overprecise” is saying that they should increase the entropy of their beliefs. In cases where there is a natural ignorance prior, it is claiming that their probability distribution should be closer to the ignorance prior. This could sometimes mean closer to 50-50 as in your point 1, e.g. the probability that the Yankees will win their next game. This could sometimes mean closer to 1/n as with some cases of your points 2 & 6, e.g. a 1⁄30 probability that the Yankees will win the next World Series (as they are 1 of 30 teams).
In cases where there isn’t a natural ignorance prior, saying that someone should increase the entropy of their beliefs is often interpretable as a claim that they should put less probability on the possibilities that they view as most likely. This could sometimes look like your point 2, e.g. if they think DeSantis has a 20% chance of being US President in 2030, or like your point 6. It could sometimes look like widening their confidence interval for estimating some quantity.