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2 sayings i like (relevant to the nerd issue) are ‘I love humanity, i just hate people’ and (for those of use who could be called ‘elites’ as distinct from the commoners ) ‘I wouldn’t me a member of any group that would me as a member’ (Mark Twain). I’m not that convinced of the ‘broken brain theory’. I tend to think in terms like ‘frequency dependence’ in biology or ‘division of labor’ in economics. Not everyone is the same, and there are reasons for that. (This is related also to the ‘pigeonhole principle’ and things like the existance of ‘runts’ in dog litters, various forms of hierarchies----in the real world, not everyone is in reaching distance of the same set of resources. Some don’t get to sit in a warm place next to the fire, and so adapt to the cold. (And, very often, when occassionaly they get invited to be in the heat, since they have learned to live in, and even enjoy the cold, they are considered antisocial, rude and disturbed if they don’t accept the invitation (eg ‘you can take this job, or seat, and shove it’). Or if you invite people to consider coming into the cold, that will be considered insanity.
(This goes for other things too—if you decide religion is very narrow, boring, intolerant etc. but then one day the confgregation decides that, since they are losing members and tithes, they will ‘lighten up’ and invite you back (but again on their slightly revised terms—eg they won’t preach that you are going to hell, but will still tell you to shut up why they preach to you the truth which you know nothing about). If you decide your peer group who does nothing but bar hop is boring and find new activities, when they see you again and say ‘hey come on, lets party’ they will say ‘you’ve really changed and are no fun anymore, unlike us party animals’. Darwin was probably a nerd and didnt attend church (or half heartedly, mostly for show). Einstein wasn’t a big zionist type studying the torah and waiting to return to the promised land, but was interested in larger parts of the space of possibilities. He also wasn’t much of a family man it seems, preferring to do stuff like EPR rather than like mowing the lawn, going to July 4 fireworks etc. (He did sign a letter written to Joe McCarthy (congressman) supporting Paul Robeson who was being accused of being a communist, and he helped get Godel citizenship, so that may have some relation to being a patriot).
To me the ‘dull prior’ is similar to the ‘maximum entropy’ postulate in statistical mechanics (which Jaynes i think identified with bayesianism). There are (as a caveat) in my view many ways of applying this postulate, so there can be a hierarchy of ‘dullness’—its what you call dull, or what your information is. (This is why i personally don’t really consider bayesianism distinct from frequentism, any more than i consider so called ‘linear’ sciences as distinct from ‘nonlinear’ ones. (The former just comes usually by truncating your equation, or changing coordinates,, or aggregating). This is also why I am highly skeptical of many applications of maximum entropy especially in fields like economics or other social sciences. The formalism is so general that you can find any result you want, or fit any distribution (with your prior ‘principle of impotence’—equal a priori probability—like ‘overfitting’ (eg Norbert Weiner on elephants) .). EG just because someone fits the description, doesn’t mean they did the crime though this sort of ‘prior’ is often used since it seems to work (eg you solve the crime, case closed, god said it, i believe it and that is all there is to it, qed.).
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The idea that iq predicts income, life expectancy, criminal justice record, etc. depends on what you mean by ‘predicts’ (eg conjunction fallacy). I and many others suggest these are correlations, and many argue instead things like income (of parents), social environment, etc predict iq, crime, health, etc. (of children, via a kind of markov process). (Also, if you look at income/iq correlations, I wouldn’t be surprised that it is quite different for different kinds of income—those who made money via IT or genomics, versus those who made it via Walmart, or sports. One may actually have a mixture distribution which only appears ‘normal’ because of sufficiently large size. )
The scatter plots are interesting, and remind me of S J Gould’s (widely criticized ) discussion of attempts to define G, a measure of general intelligence, using factor analyses.
I think the general conclusion before the analyses is the right one—there are multiple factors. I would say many of the ‘smartest’ people (as measured by say, iq) end up in academic fields in math/science/technology rather than in business with the aim of making money. There are so many factors. Some academics later on do go into business, either working in finance or genomics industries, but many don’t. One reason academic economics is criticized is because it follows the pattern of this post—it starts with general observations, comes up with tentative conclusions, and then goes into highly detailed, mathematical analyses which doesn’t really add much more insight, though its an interesting excercize.