I'm not sure what work the word "sophisticated" is doing here.

Let's say the Greens advocate dispersing neurotoxins to eradicate all life on earth, and the Blues advocate not doing that. Is it "sophisticated" to say, "Well, there are certainly good arguments on both sides, for example if you assume this specific twisted utilitarian framework, or assume values that I don't possess, then the Greens have some good points!"? That doesn't seem sophisticated. That just indicates a pathological inability to "join a side" even when one side is the one you should join by your own ethical compunctions, you want to join, you would benefit from joining, and you would cause others to benefit by joining.

Also, what if you arrive at the party partway through, and the Green and Blue have already spoken, and also another Sophisticate has spoken and indicated that "both sides have some good points, perhaps the answer is in the middle". Are you allowed to just say, "I agree with the Sophisticate!" or does that make you a "sophisticate partisan" meaning you are obligated by the laws of being/appearing "sophisticated" to say, "Well, actually, the answer can't be in the middle, a 50-50 split just seems improbable, the Greens are probably 25% right and the Blues are probably 75% right."?

What I'm getting at is I'm not sure what the difference is being your usage of "sophisticated" and just being a contrarian.

You mention the attitudes implicit in certain styles of debate. I've written before about the dangers of certain styles of policy debate taught in American schools. I've always seen it as damaging that the point of US policy debate is to be able to argue from any position and against any position. It implicitly teaches the young mind that you can "win" an argument through cleverness and rule-lawyering without regard to whether your position is actually superior. The whole framework actively undermines the truthseeking mindset, because in a policy debate, you're not truthseeking, you're trying to obfuscate the opponents' inconvenient truths and distort facts that support your own argument to appear more important than they are. In short, I think there's definitely such a thing as "too much sophistication", and I blame this type of sophistication on why many of my former high school friends are now effectively insane.

Obviously I agree that it's dangerous to identify with a school of thought. Political parties in particular are coalitions of disparate interest groups, so the odds that a group of people who are only aligned for historically contingent reasons are going to come up with uniformly correct conclusions is near zero. That doesn't mean you can never be confident that you're right about something.

Additionally, I think to the degree that LWers identify as Bayesian, they are mostly just acknowledging the superiority of the Bayesian toolkit, such as maintaining some notion of a probability distribution over beliefs rather than exclusive and inviolable belief-statements, updating beliefs incrementally based on evidence, etc. None of us are really Bayesians anyway, because a thorough and correct Bayesian network for computing something as simple as whether you should buy Hershey's or Snickers would be computationally intractable.

You seem to fail Bildung as you contrast AngloAmerican and German ways of doing things. A true sophisticate would know the truth is not in picking one side and sticking to it :-P

I am also not sure why should I care about what's high-status in Germany (other than being Dr. Dr. Dr. Lumifer, of course).

This seems like a desirable feature of German culture. Have Germans always been like this? Do you know where this aspect of German culture might have originated? The closest thing I can think of in American culture is the satirical TV show South Park, which is known for lampooning both sides in political debates. Unfortunately, the show is not strongly associated with intellectual sophistication.

I dunno, man. What are you gonna do if a school of thought is right? It seems dumb to precommit to being too cool to agree with them, but surely you would lose your GERMANWORD if you credulously accepted their conclusions.

To sum up: invent a single sentence to summarize your opponent's position so that you condemn them as naive. For example, what you did to Phil Goetz.

I don't know German, but it sounds like the thing you mean by "Bildung" is something like "self-development".

Let me know if this sounds like the right idea:

If you want to be an excellent person, strong in various capacities, mature and able, then you want to think for yourself, and always keep looking for deeper/subtler/more powerful insights. There's a mental move of "yes, okay, but it could be even better" or "this is too easy, it's boring" that makes it seem unappealing to remain stuck in dogma. You don't want to flatten yourself or reduce yourself to a stereotype; you want to broaden and deepen your capacities.

The opposite mindset would be something like "I want to be Done, with all the thinking, forever, please don't make me get up from where I've plopped down. I'm on the side of the angels, and That is That."

Does that seem like the thing you're pointing at?

I suspect there is a trade-off between partisanship and "deep wisdom". You can make status moves of both kinds, you just have to choose the move that fits your audience.

Displaying sophistication by saying things like "there are also some interesting arguments against the statement 2+2=4" at every opportunity can perfectly kill any momentum. (Even if those arguments are technically valid, for example "there is no such thing as '4' in base 3; it's called '11' instead", as long as they don't contribute to solving the problem, only to signal the scholarship of the speaker.)

To the extent that using prior information about the world is useful in understanding the future, it's sort of nonsensical to say someone shouldn't think of themselves as Bayesian. To the extent someone is perhaps ignoring a correct methodological approach because of a misguided/misunderstood appeal to Bayesianism, that's fine.

For example, back in the academic world I worked on research forecasting the U.S. yield curve. We did this using a series of non-linear equations to fit each day (cross-section), then used filtering dynamics to jointly capture the time-series. Figuring out a way to make this already insanely complex model work within a Bayesian framework wouldn't only be perhaps too hard, but not particularly useful. There is no nice quantifiable information that would fit in a prior, given the constraints we have on data, math, and computational ability, that would make the model formally Bayesian.

Having said that, to the extent that we tweaked the model using our prior information on less structured scientific theories (e.g. Efficient market hypothesis) -- it certainly was Bayesian. Sometimes the model worked perfectly, computed perfectly, but something didn't match up with how we wanted to map it to reality. In that sense we had our own neural-prior and found the posterior less likely.

It's really hard for me to see under what model of the world (correct) Bayesian analysis could be misleading.

One classic example of an unsophisticated position that's common in analytic philosophy is the idea that all intellectual discourse is supposed to be based on logic. In Is semiotics bullshit? PhilGoetz stumbles about a professor of semiotics who claims: "People have an extra-computational ability to make correct judgements at better-than-random probability that have no logical basis."

I think the claim that people can make correct judgements at better-than random probability that have no logical basis is nonsensical. Lots of this sort of writing and theorizing of the world is from a time, and from people, who existed before modern computational powers and machine learning. In the past the view was that the human mind was this almost-mystical device for processing reality, and we had to ground our beliefs in some sort of formal logic for them to follow. At least in my experience from working with stuff like neural-nets, I only see vast amounts of information, which our brains can filter out to predict the future. To reason from analogy, sometimes when doing some sort of ML problem you'll add a bunch of data and you have no logical clue why it would improve your model... But then your predictions/classification score increase.

In this context what does it even mean to call this logical or non-logical? It's nothing more than using past observed information patterns to classify and predict future information patterns. It's strictly empirical. I can't think of any logical decomposition of that which would add meaning.