anyway, my basic beef w/ g is: i think a lot can go wrong when you do stats w/o an underlying causal model
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...like "IQ plus cube root of height" if they turned out to correlate w irl stuff (as that one likely would)
and i think the "not a nonsense variable" criterion is hiding some casual theorizing on our part
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correlation between a "nonsense var" and (say) income would be uninteresting bc we'd know it wasn't causal
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so when we grant "existence" we're saying "this seems like a good candidate for a node in a causal model"
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if we go from pure descriptive stats to "this exists," we've smuggled in some causal claims under the radar
End of conversation
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