> isn't the implication that the distance between the two lines is the metric of interest?
That's more or less what D-K are saying, yes. That doesn't necessarily mean it's the best metric to use for understanding what the data is saying.
Also, "distance between the two lines" is misleading because the data is bucketed--on the x axis by quartiles, on the y axis by percentiles. In other words, the actual data is the circles/triangles/squares, not the lines. When put that way, "distance between the lines" looks a lot less like an actual metric and a lot more like an artificial one.
You seem to be first correcting the statement made by D-K in a way so compatible with this article that it is literally their example and then claiming that this corrected statement is correct so the article is wrong... the actual statement--as you even admit--was wrong, and that their data was fine was not being questioned by the article: it was their interpretation, which is what the D-K effect actually is... an inverse correlation between skill and perceived skill. Yes: if you choose to read their graph in a way which D-K didn't consider you can see the correct statement, but D-K didn't do that, and that isn't what anyone--but I guess you--means when they reference the conclusions of the paper and the resulting "effect", which purports to explain "why people tend to hold overly optimistic and miscalibrated views about themselves".
No, it isn't. The article is claiming that the D-K effect doesn't actually exist; actually all that is going on is "autocorrelation". That claim is wrong. The D-K effect does exist, but it isn't what D-K said it was: it's not that there is an inverse correlation between perceived skill and actual skill; it is that there is no correlation (or at best a weak positive correlation) between perceived skill and actual skill (when we would intuitively expect a fairly strong positive correlation between them). That is what D-K's actual data shows; but neither D-K themselves in their paper, nor this article, correctly describe that.
> The D-K effect does exist, but it isn't what D-K said it was...
You are claiming an effect exists, and no one--and certainly not the author of this article, who seem to be fully bought into your very different statement of the effect (and so maybe we shall call it "the pdonis effect")--is disagreeing with you on that point; however, your insistence upon calling this effect "the Dunning-Kruger effect"--while simultaneously admitting that Dunning and Kruger described a different incorrect analysis as their "effect"--is what is unreasonable. Put simply: "the Dunning-Kruger effect" is the thing that Dunning and Kruger claimed to be true, not some other random property of the data that their same experiment could have backed up, if only they had realized; and it is this effect--the actual Dunning-Kruger effect, as described by Dunning and Kruger in no uncertain terms--which does not seem to exist.
That's more or less what D-K are saying, yes. That doesn't necessarily mean it's the best metric to use for understanding what the data is saying.
Also, "distance between the two lines" is misleading because the data is bucketed--on the x axis by quartiles, on the y axis by percentiles. In other words, the actual data is the circles/triangles/squares, not the lines. When put that way, "distance between the lines" looks a lot less like an actual metric and a lot more like an artificial one.