But I think that debate is tangential to the original post.
I don’t think it is. You spend all this time hammering on how ‘the top performer X in field Y doesn’t have the top IQ’, yet, this is exactly what you would expect for even a causal variable of unimpeachable status which causes the majority, or even almost every last bit of variance, in X performance. You seem to think it’s extremely important, and tells us something very important about the nature of IQ, yet, I’m pretty sure it doesn’t. Why you discuss it so much if it is so ‘tangential’?
The “second thesis” was to focus on the sub-components of intelligence as better predictors of domain-specific high-level success than the general factor..> ..
I’m not sure whether you would disagree with the last sentence of that paragraph, but that’s really what I was trying to get at with thesis 2.
But they’re not! This is exactly what I was talking about! Yes, additional incremental variance after explaining g—but less variance. They’re not “better”.
But how could you possibly break down height into 10 general categories and 70 narrow abilities?
Certainly. As I said, height is mostly generalist genes, but there are also specific variants for parts of the body. Haven’t you ever noticed how some families have different body proportions, with different leg:arm ratios, or longer necks, etc? You absolutely can measure arm length, head volume, leg length etc in all sorts of anatomic detail and (if anyone wanted to waste money on doing the measurements) do a GWAS on height and then specific body parts. You can also measure genetic correlations between body part sizes; for an example, look at Black 1982 https://en.wikipedia.org/wiki/Genetic_correlation#Anthropometric That height can be broken down into both the general height and narrower variables shouldn’t be too surprising; consider Marfan syndrome.
What could you explain or predict by breaking down height into 70 subcategories?
Well, you could predict each individual measurement better from genes. Obviously. As for explanations, that will depend on the ingenuity of embryologists and endocrinologists and anatomists in nailing down the biological pathways from genetic variants to greater or less growth of forearms etc.
What I am arguing, is that by breaking down intelligence into various subcategories, researchers are better able to predict who will do well at what specific tasks. That the breakdown of the subcategories of Carlsen’s intelligence would likely provide much better insight into his abilities than his raw IQ.
Sure. No one is going to object to the claim that ‘after you explain the majority of the variance in performance by the general factor, you can get additional incremental variance explained by focusing on narrower factors which weight more heavily on that particular field’. SMPY has demonstrated that very nicely by showing that verbal scores are overweighted for STEM achievement and one should emphasize more spatial/mathematical questions. But then you go and again claim that they are better predictors, which is either probably wrong or meaningless (wrong, if you mean they should be used in place of general intelligence, or meaningless, if you are referring to using them in addition to general intelligence). As I said, I feel like you are constantly moving the goalposts and redefining your terms in the OP and your comments and I’m having a hard time figuring out what you are really arguing.
Ultimately, I would guess that further exploration of the sub-categories of intelligence are likely to reveal much more about Einsteins, Musks, Carlsens, and Mozarts. And that improved understanding and modeling of the sub-categories will eventually enable us to have a much better understand about what makes them who they are—and perhaps predict future versions of them. But I think it will be the more nuanced understanding of these sub-categories, not further emphasis on the general factor, that will enhance this understanding.
Possible but I think this over-rates how much we understand about general intelligence. I would argue that general intelligence is far more important to understand and increase if we want to understand or create more Einsteins. What is more valuable, some better testing to guide highly intelligent people (<1% of the population) into subfields using tailored tests and maybe increase their lifetime productivity 10%, or understand general intelligence somewhat better via GWASes, and get genetic engineering to increase population mean IQ by 5 points and increasing the fraction passing that cutoff by 500%? Considered as a leaky pipeline, optimizing the general population case is more effective than tweaking the few elites. (This is similar to something I found in my embryo selection analysis: even great interventions against rare diseases aren’t very cost-effective compared to tiny interventions for intelligence or height, because the very rarity neutralizes the greatest and makes the absolute benefit small.)
I don’t think it is. You spend all this time hammering on how ‘the top performer X in field Y doesn’t have the top IQ’, yet, this is exactly what you would expect for even a causal variable of unimpeachable status which causes the majority, or even almost every last bit of variance, in X performance. You seem to think it’s extremely important, and tells us something very important about the nature of IQ, yet, I’m pretty sure it doesn’t. Why you discuss it so much if it is so ‘tangential’?
But they’re not! This is exactly what I was talking about! Yes, additional incremental variance after explaining g—but less variance. They’re not “better”.
Certainly. As I said, height is mostly generalist genes, but there are also specific variants for parts of the body. Haven’t you ever noticed how some families have different body proportions, with different leg:arm ratios, or longer necks, etc? You absolutely can measure arm length, head volume, leg length etc in all sorts of anatomic detail and (if anyone wanted to waste money on doing the measurements) do a GWAS on height and then specific body parts. You can also measure genetic correlations between body part sizes; for an example, look at Black 1982 https://en.wikipedia.org/wiki/Genetic_correlation#Anthropometric That height can be broken down into both the general height and narrower variables shouldn’t be too surprising; consider Marfan syndrome.
Well, you could predict each individual measurement better from genes. Obviously. As for explanations, that will depend on the ingenuity of embryologists and endocrinologists and anatomists in nailing down the biological pathways from genetic variants to greater or less growth of forearms etc.
Sure. No one is going to object to the claim that ‘after you explain the majority of the variance in performance by the general factor, you can get additional incremental variance explained by focusing on narrower factors which weight more heavily on that particular field’. SMPY has demonstrated that very nicely by showing that verbal scores are overweighted for STEM achievement and one should emphasize more spatial/mathematical questions. But then you go and again claim that they are better predictors, which is either probably wrong or meaningless (wrong, if you mean they should be used in place of general intelligence, or meaningless, if you are referring to using them in addition to general intelligence). As I said, I feel like you are constantly moving the goalposts and redefining your terms in the OP and your comments and I’m having a hard time figuring out what you are really arguing.
Possible but I think this over-rates how much we understand about general intelligence. I would argue that general intelligence is far more important to understand and increase if we want to understand or create more Einsteins. What is more valuable, some better testing to guide highly intelligent people (<1% of the population) into subfields using tailored tests and maybe increase their lifetime productivity 10%, or understand general intelligence somewhat better via GWASes, and get genetic engineering to increase population mean IQ by 5 points and increasing the fraction passing that cutoff by 500%? Considered as a leaky pipeline, optimizing the general population case is more effective than tweaking the few elites. (This is similar to something I found in my embryo selection analysis: even great interventions against rare diseases aren’t very cost-effective compared to tiny interventions for intelligence or height, because the very rarity neutralizes the greatest and makes the absolute benefit small.)