Finance scene is upstream of tech, which is upstream of media. Fin tech is post-tech and ironically-fin.
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It’s a partial order so you can move to any scene that is not-upstream. Even reactionary moves are fundamentally ironic. Tech to trad is not the same as just being trad. So not-upstream.
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I’m currently very curious about “post-tech” scenes. I have an inventory but not a map: crypto, entertainment, trad, waldenponding, neoreaction, local politics, biotech. Each is post in a different way.
Tech is a bottleneck scene. Everything is either pre-tech or post-tech.
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It is locally total order. Only 1 scene at a time is the bottleneck usually. Other scenes don’t induce total pre/post cuts.
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Well if there’s a net direction locally (A to be is more likely than B to A) for every pair with significant flow, you’ll get at least a local order. I suspect if you impose a minimum net flow threshold to filter random noise you’ll get a proper DAG.
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Yeah, the overall graph of all flows, including both low absolute and net levels, probably has no structure, since almost any pair in any direction will have *some* flow due to pure randomness. The question is how to threshold to get to robust flow patterns.
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Example of the sort of thing you mean? Mac vs PC might be one. I went PC to Mac but have no strong sense of one being “later” evolutionarily. But then again, that’s more consumption choice than scene. It’s not like I party with Mac types and used to party with PC types.
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Is there significant exit activity in either direction though? Or just tourism of sorts?
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