Upvoted. This article makes an extremely important point.
I use correct/incorrect to refer to ‘prediction and outcome coincided’/‘made what turned out to be the most favourable choice’/etc.
I use right/wrong to refer to ‘made the best prediction’/‘chose the outcome that, as far as could be told, would be most favourable’/etc.
Smith was correct and wrong.
Although one might expect ambiguity to be a problem with these terms (e.g. ‘right’ becoming overloaded to the point of equivocation), in my experience it hasn’t been one once they have been explained.
The thesis of the right/correct distinction is defying the data.
The antithesis is regret of rationality, i.e. predictably losing due to a flaw in a model. This is a hazard that arises from devotion to a theory or undervaluing data, which lead to insistence one is still right even as the defeats pile up.
As for the No True Fencing Victory thingy: that’s simply insufficient correspondence between one’s internal understanding (e.g. one visualises winning in a fifteen-point whitewash, specifies ‘winning’, and is saved from the jaws of defeat by a technicality.) Such cases are of being too imprecise or inaccurate. I generally lean very heavily towards ‘a win is a win’, because anything else often seems to stem from an unrealistic expectation of perfect specification.
Upvoted. This article makes an extremely important point.
I use correct/incorrect to refer to ‘prediction and outcome coincided’/‘made what turned out to be the most favourable choice’/etc.
I use right/wrong to refer to ‘made the best prediction’/‘chose the outcome that, as far as could be told, would be most favourable’/etc.
Smith was correct and wrong.
Although one might expect ambiguity to be a problem with these terms (e.g. ‘right’ becoming overloaded to the point of equivocation), in my experience it hasn’t been one once they have been explained.
The thesis of the right/correct distinction is defying the data.
The antithesis is regret of rationality, i.e. predictably losing due to a flaw in a model. This is a hazard that arises from devotion to a theory or undervaluing data, which lead to insistence one is still right even as the defeats pile up.
As for the No True Fencing Victory thingy: that’s simply insufficient correspondence between one’s internal understanding (e.g. one visualises winning in a fifteen-point whitewash, specifies ‘winning’, and is saved from the jaws of defeat by a technicality.) Such cases are of being too imprecise or inaccurate. I generally lean very heavily towards ‘a win is a win’, because anything else often seems to stem from an unrealistic expectation of perfect specification.