(I continue to regret my slow reply turnaround time.)
But there are times when it’s not a dishonest rhetorical move to do this, right?
Right. In Scott’s example, the problem was using the “eargrayish” concept to imply (bad) inferences about size, but your example isn’t guilty of this.
However, it’s also worth emphasizing that the inferential work done by words and categories is often spread across many variables, including things that aren’t as easy to observe as the features that were used to perform the categorization. You can infer that “mice” have very similar genomes, even if you never actually sequence their DNA. Or if you lived before DNA had been discovered, you might guess that there exists some sort of molecular mechanism of heredity determining the similarities between members of a “species”, and you’d be right (whereas similar such guesses based on concepts like “eargrayishness” would probably be wrong).
Since it doesn’t seem to make sense to never use a word to point to a cluster in a “thin” subspace, what is your advice for when it’s ok to do this or accept others doing this?
Um, watch out for cases where the data clusters in the “thin” subspace, but doesn’t cluster in other dimensions that are actually relevant in the context that you’re using the word? (I wish I had a rigorous reduction of what “relevant in the context” means, but I don’t.)
As long as we’re talking about animal taxonomy (dolphins, mice, elephants, &c.), a concrete example of a mechanism that systematically produces this kind of distribution might be Batesian or Müllerian mimicry (or convergent evolution more generally, as with dolphins’ likeness to fish). If you’re working as a wildlife photographer and just want some cool snake photos, then a concept of “red-‘n’-yellow stripey snake” that you formed from observation (abstractly: you noticed a cluster in the subspace spanned by “snake colors” and “snake stripedness”) might be completely adequate for your purposes: as a photographer, you just don’t care whether or not there’s more structure to the distribution of snakes than what looks good in your pictures. On the other hand, if you actually have to handle the snakes, suddenly the difference between the harmless scarlet kingsnake and the poisonous coral snake (“red on yellow, kill a fellow; red on black, venom lack”) is very relevant and you want to be modeling them as separate species!
(I continue to regret my slow reply turnaround time.)
Right. In Scott’s example, the problem was using the “eargrayish” concept to imply (bad) inferences about size, but your example isn’t guilty of this.
However, it’s also worth emphasizing that the inferential work done by words and categories is often spread across many variables, including things that aren’t as easy to observe as the features that were used to perform the categorization. You can infer that “mice” have very similar genomes, even if you never actually sequence their DNA. Or if you lived before DNA had been discovered, you might guess that there exists some sort of molecular mechanism of heredity determining the similarities between members of a “species”, and you’d be right (whereas similar such guesses based on concepts like “eargrayishness” would probably be wrong).
(As it is written: “Having a word for a thing, rather than just listing its properties, is a more compact code precisely in those cases where we can infer some of those properties from the other properties.”)
Um, watch out for cases where the data clusters in the “thin” subspace, but doesn’t cluster in other dimensions that are actually relevant in the context that you’re using the word? (I wish I had a rigorous reduction of what “relevant in the context” means, but I don’t.)
As long as we’re talking about animal taxonomy (dolphins, mice, elephants, &c.), a concrete example of a mechanism that systematically produces this kind of distribution might be Batesian or Müllerian mimicry (or convergent evolution more generally, as with dolphins’ likeness to fish). If you’re working as a wildlife photographer and just want some cool snake photos, then a concept of “red-‘n’-yellow stripey snake” that you formed from observation (abstractly: you noticed a cluster in the subspace spanned by “snake colors” and “snake stripedness”) might be completely adequate for your purposes: as a photographer, you just don’t care whether or not there’s more structure to the distribution of snakes than what looks good in your pictures. On the other hand, if you actually have to handle the snakes, suddenly the difference between the harmless scarlet kingsnake and the poisonous coral snake (“red on yellow, kill a fellow; red on black, venom lack”) is very relevant and you want to be modeling them as separate species!