There's a distinction that's probably only obvious to people with some grad-level math: Corner cases are not the same as rare cases. Neither implies the other. "Corners" are a measure-0 subset of a space where open-nbhd/non-singleton methods don't apply Ie "special treatment"
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Replying to @vgr
but there is some kind of relationship here though, right? even if its just semantics/labeling it's something. if a majority of cases of a thing were "corner" cases we would definitely not label that as the corner. corners are always some kind of minority.
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Replying to @danlistensto
Not necessarily, when the majority is corners, we switch language and start talking about how it's a diverse/varied context. Like say the food scene in a cosmopolitan city with lots of food carts.
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Replying to @vgr
I'm not convinced. to me that signals wrong-abstraction.
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Replying to @danlistensto @vgr
for example, in coding, the right abstraction (almost always) results in writing MUCH less code to solve the problem. if I encounter some code where EVERYTHING is being handled as a special case that's a huge code smell. means wrong abstraction.
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Replying to @danlistensto
You assume abstractability is entirely a function of the intelligence of the agent acting on the context. I disagree with that premise. It's fundamentally a propert of the domain. Tax law is less abstractable than classical Newtonian mechanics.
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Replying to @vgr
no way. you've got a really powerful implicit notion of "good abstraction produces good results" here and I think that's wrong. tax law is extremely easily abstractable but you make a value judgment that elegant abstractions of it are bad laws. e.g. flat tax.
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Replying to @danlistensto
You're conflating normative concerns ("good" tax laws) with phenomenological. Alt example with no normative angle: special-order catalogs are harder to abstract than combinatorial product offerings like Starbucks menu.
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I see what you mean. The normative angle is the interesting part though! the phenomenological side is just like, how much of a PITA is it to debug our models.
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