I don’t think it’s just a social effect. There’s an epistemological component. Situationist models have salient local contextual data that might be intractable to make consistent beyond a “it depends” or “case by case” vacuous ensemble consistency.
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Replying to @ghuubear
Depends on the scope, doesn't it? If our belief set consists of 1 belief like "all traffic offenders should be given a ticket" you might hit 90%. If it consists of a looser meta belief like "treat people kindly" that stands in for a dozen conflicting behavior norms, it gets messy
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Low-paradigm fields like modern anthropology have a particularist bias and suspicion of even empiricist triage theorizing of the "90%" type, let alone grand conceptual theories. While naive economists often have unreasonably consistent belief in market efficiency.
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A good way to consider ergodicity potential here is to simply think of case space as a different kind of time. You have a belief B on day t, based on case k. B(t,k) might need an update both for B(t+1,k) and for B(t, k+1).
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Is the situation more stable in time or case-space? It is not clear to me that different default assumptions for time/case-space are warranted. Your original heuristic amounts to "beliefs are more likely to be invalidated by new data over time than by new cases in scope"
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Replying to @ghuubear
Yes, so it gets tricky, depending on how exploratory in case space the time behavior is, and what additional sources of invalidation there are besides case variety. So I do think time is probably a richer source of invalidations than case space, but it's not trivial to separate
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My initial skepticism to the proposition came from my sense that for most people "ensemble consistency" actually tends to be "stereotype consistency" across a subset of cases *already* in scope. Like ignoring exceptions you might already know of rather than give up consistency.
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Interesting connection to distributed computing and CAP theorem (consistency, availability, partition tolerance -- pick 2 of 3). Truth maintenance in case space is a distributed computing problem and consistency might be the leg of the triad to fail.
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