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the “6% rate of top comedians come from Ivys” is way smaller than should be expected were you to control for the selection effect of the Ivy’s (eg family wealth, health, drive) and the incidental benefits of an Ivy education (vastly enhanced social connections and opportunities). You should probably also exclude the bottom 20% in intelligence; of course the dumbest people can’t be comedians, so the negative correlation with g would only be found after a certain threshold; it’s rather a negative correlation with high g. Then you’d have to check if any of these comedians were legacy admits, which is an exclusionary criteria case. Maybe a more important argument against this data: we have to look at comedians born after, say, 1980, as it’s the Internet that has made comedy meritocratic. Your wikidata dataset premising your argument includes comedians born in 1940. But surely the world of comedy was not as meritocratic in the 60s, 70s, and 80s, when your connections with wealthy producers you went to school with had an outsize impact. In the internet age we can actually see who is funniest, they rise to the top of algorithms that are more difficult to game then 1 or 2 late night talk shows dictating the entiret of prominence.
Is this an accurate measure of prominence?
I have three points. First, I'm more concerned with how you're coming up with your objections and less concerned about the objections themselves. In general, psychological effects are linear, you get close to wanting to induce Berkson's bias just to seem more right, you move the goal posts by demanding the data be new enough by your ad hoc standard. I could give you data after 1980 and reasoning like this, you'd be sure to ignore it and demand the data be from last year and so on. It's not a very productive or rational way to approach data, basically. I'm worried it's almost entirely motivated reasoning.
Second, based on what I know off the top of my head, your points themselves are wrong. To begin with, the Ivy league does not have a monopoly on intelligence. Someone below pointed out Adam Sandler attended NYU ... which has an average SAT of 1520. Not any Ivy. 6% is about right when you consider what percent of people 120+ IQ go to Ivy Leagues. .34% of college students attend the Ivy League per google. I recall off the top of my head that the median IQ there is maybe 125. So the vast, vast majority of intelligent students don't attend the Ivy League, and it shows in the data. Second, as for family connections, maybe it doesn't matter as much as you think? Maybe it's mostly about skill, and luck in e^2 and not in c^2? That's what the twin studies say. That's what real life says to me. Do you have any special information that says otherwise? Next, linear effects, actually it's almost certainly linear because psych effects are almost always linear, just looking around the literature, there's not really a nonlinear mechanism here, but also it doesn't matter because a correlation is a correlation whether or not the actual conditional expectation function is linear. Finally, the internet and meritocracy. You seem to have not noticed experimental data which asked people to rate funniness of others who are not professional comedians. It shows much larger correlations between population variance of comedic skill and g than when looking at professionals only. This is because becoming a professional is dependent on a lot of things beyond just skill. If the internet reduces that you'd expect the g-professionalism association to increase, not decrease.
Which moves me on to my last point, which is section 6 is new and made for you. It shows what I predicted and not what you predicted, essentially.
With this stuff I think there's always another epicycle if that bothers you little enough. I could say modern physics is a conspiracy theory. Some people do that. It can always be done. I'm mentioning this because even eye witness observation, physics, whatever is not airtight. You can come back and say that the comedy-g correlation negative, but you can always do that, even if I showed you a 1,000,000 person data set showing otherwise. There is always another epicycle and in general if you fail once with the epicycle I think in a fair argument you run out at that point.
A lot of accusations here. Well, I happen to have read before that the Harvard Lampoon has a sizable nepotistic network in comedy, which is a fact, and that’s why I mention that the data should be tailored for the period in which the Internet democratized comedy. “Downey's most lasting contribution, he opened an employment pipeline, hiring and referring countless Lampoon alumni who now fill writers' rooms at shows from Curb Your Enthusiasm to Silicon Valley” […] “Once you’re there, it suddenly seems easier to get ahead. You do have an advantage. It’s just that you get some kind of contact and some sense that someone like you went there and did it. You are helped by knowing and being helped by other Lampoon people.” And then if I’m not mistaken the Lampoon movie series recruited from a Lampoon network. How will this new information update your confidence, because the accusations seem like you were quite confident?
This is a valid argument because the social network afforded by Harvard connections has nothing to do with g factor or the school itself, it’s just a random benefit that will boost the prominence of these IvyPlus grads even if their boost is undeserved. SNL has often been criticized for riding on its reputation, for instance. Few of the SNL Harvard crowd would make it as a stand-up comic, I’d wager, because… they’re not that funny. Laughs being the sole criteria of humor. These are defenses to the hypothesis because you introduced data; it’s all very reasonable.
Ah, but NYU had a 65% acceptance rate in 1990. Perhaps an 80% acceptance rate in 1984 when he applied? I can’t find the data. This is another point of evidence that, for whatever reason, the best comedians do not attend IvyPlus, though as your data found, 70% of top lawyers or so have.
Isn’t this a good argument against the method you’re using? He’s a highly prolific comic, highly relevant, but would be excluded because he’s not in other languages. Sports are different because sportsmen compete across nations.
The inclusion of the latter three surely disprove the legitimacy of this methodology. Colin Jost makes sense; Slate and Williams are just actresses who happen to be in the comedy section for some reason. I guess I’m wondering why your criteria has two famous actresses that I am supposed to believe should be considered comedians. Maybe they did comedy, but they’re known for a ton of regular media. I know Allison Williams from Girls, for instance.
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Great point. Adam Sandler went to NYU, ended up dorming with other comedians who'd blow up later in life, though not to the same degree.
Not sure which point you thought was great, but NYU is not exactly known for having braindead students.
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