If you take a pair of variables which are correlated r>=0.25, you have, pretty much by definition, found that one >variable ‘matters’ more than any other single variable can, simply because it has explained/predicted the majority of >the variance (sqrt(0.25)=0.5). Another variable can’t explain more of the variance.
I agree that g is probably more predictive of success than any other single variable. Cumulatively, other factors may matter more. But it is likely true that no one factor matters more. But I think that debate is tangential to the original post.
The original post had two points.
The “first thesis” was to argue that intelligence is more like athleticism than height.
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 have not been dissuaded on either thesis.
The more I read about this, the more I believe that both of these theses are supported by CHC theory, which, according to a 2005 paper by Alfonso, Flanagan, and Radwan, is, “the most comprehensive and empirically supported psychometric theory of the structure of cognitive and academic abilities to date.” (Thanks, 9eB1!) The paper goes on to say:
Others, however, believe that g is the most important ability to assess because it predicts the lion’s share of the >variance in multiple outcomes, both academic and occupational (e.g., Glutting, Watkins, & Youngstrom, 2003). >Notwithstanding one’s position on the importance of g in understanding various outcomes (particularly academic), >there is considerable evidence that both broad and narrow CHC cognitive abilities explain a significant portion of >variance in specific academic abilities, over and above the variance accounted for by g (e.g., McGrew, Flanagan, >Keith, & Vanderwood, 1997; Vanderwood, McGrew, Flanagan, & Keith, 2002).
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.
With thesis 1, I think CHC theory provides further support for my belief that athleticism is a much better analogy for intelligence than a simple variable such as height. According to the paper, “CHC theory currently consists of 10 broad cognitive abilities and more than 70 narrow abilities.” These are all subsumed in two strata below the general factor.
To me, it would be very easy to imagine breaking down athleticism into 10 general categories and 70 narrow abilities as well. I think by breaking down athleticism into those subcategories, you could explain a significant portion of variance in specific athletic outcomes, over and above the variance accounted for by athleticism generally.
But how could you possibly break down height into 10 general categories and 70 narrow abilities? Trying to break down height into 70 sub-categories would be equal parts useless and meaningless. What could you explain or predict by breaking down height into 70 subcategories?
I think the answer is nothing.
Of course, since IQ is relatively easy to measure via SATs and grades (look at how easy TIP/SMPY were to do - >picking out future movers and shakers from millions of kids using just a cut-down SAT—please appreciate how >astounding it is that you can just administer a short pencil-and-paper test to millions of kids and taking the top >thousand or so, get such an incredible enrichment, with huge odds ratios for accomplishment), it is easy to create >these selected extremes, and so we have a pleasant problem:
I don’t disagree with any of this.
Openness and Conscientiousness do not outpredict IQ, and are not causally more important for accomplishment.
I’m not arguing that, either.
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.
Since we’re all NBA fans here, I’ll continue working with that theme. If you look at any given player in the NBA, it’s obvious why they are there. 5’11” Allen Iverson had one in a billion-ish speed and agility. Yao Ming had one in a billion-ish height and coordination. Lebron James has a one in 10 billion-ish combination of strength, speed, size, and coordination (there may never have been anyone in human history with his combination of those talents). They’re all Hall of Famers or will be eventually. They’re all genetic freaks. But they are very different kinds of genetic freaks.
Just as the sub-categories of athleticism will predict whether someone will be better suited to point guard or center, so, too, will sub-categories of intelligence better explain whether someone will be better suited English literature or chess. And that sub-categories may even be capable of predicting prodigies, savants, and geniuses in given fields.
As we break down the top tiny fraction of 1% of the population, those nuances in what constitutes their sub-categories athleticism and intelligence are what makes them interesting and likely to accomplish extraordinary things at any given task.
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.
From the same Alfonso paper:
Future research will probably continue to examine the importance of specific cognitive
abilities in the explanation of academic outcomes, above and beyond the variance explained by g. Also, it is hoped >that future research in the field of learning disabilities will be guided by CHC theory, and that the
search for aptitude–achievement interactions will be revisited using CHC constructs as opposed
to Wechsler’s traditional clinical composites (i.e., Verbal and Performance IQs)
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.)
As stated, yes, but once you get to “70 narrow abilities” of intelligence, my bullshit-o-meter starts to make excited noises… Though I haven’t looked at the paper, so maybe it’s excited for no good reason.
I agree, but unless I’ve misunderstood ragintumbleweed is citing CHC theory (the thing with the 70 narrow abilities) not as their main thesis but just to say “see, here’s some mainstream academic work on this stuff, and it fits well with my account!”. If it turns out that the 70 narrow abilities are entirely the product of fitting models to noise, or even that CHC theory as a whole is bullshit, that doesn’t make much difference to the claims ragintumbleweed has actually made.
I agree that g is probably more predictive of success than any other single variable. Cumulatively, other factors may matter more. But it is likely true that no one factor matters more. But I think that debate is tangential to the original post.
The original post had two points.
The “first thesis” was to argue that intelligence is more like athleticism than height.
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 have not been dissuaded on either thesis.
The more I read about this, the more I believe that both of these theses are supported by CHC theory, which, according to a 2005 paper by Alfonso, Flanagan, and Radwan, is, “the most comprehensive and empirically supported psychometric theory of the structure of cognitive and academic abilities to date.” (Thanks, 9eB1!) The paper goes on to say:
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.
With thesis 1, I think CHC theory provides further support for my belief that athleticism is a much better analogy for intelligence than a simple variable such as height. According to the paper, “CHC theory currently consists of 10 broad cognitive abilities and more than 70 narrow abilities.” These are all subsumed in two strata below the general factor.
To me, it would be very easy to imagine breaking down athleticism into 10 general categories and 70 narrow abilities as well. I think by breaking down athleticism into those subcategories, you could explain a significant portion of variance in specific athletic outcomes, over and above the variance accounted for by athleticism generally.
But how could you possibly break down height into 10 general categories and 70 narrow abilities? Trying to break down height into 70 sub-categories would be equal parts useless and meaningless. What could you explain or predict by breaking down height into 70 subcategories?
I think the answer is nothing.
I don’t disagree with any of this.
I’m not arguing that, either.
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.
Since we’re all NBA fans here, I’ll continue working with that theme. If you look at any given player in the NBA, it’s obvious why they are there. 5’11” Allen Iverson had one in a billion-ish speed and agility. Yao Ming had one in a billion-ish height and coordination. Lebron James has a one in 10 billion-ish combination of strength, speed, size, and coordination (there may never have been anyone in human history with his combination of those talents). They’re all Hall of Famers or will be eventually. They’re all genetic freaks. But they are very different kinds of genetic freaks.
Just as the sub-categories of athleticism will predict whether someone will be better suited to point guard or center, so, too, will sub-categories of intelligence better explain whether someone will be better suited English literature or chess. And that sub-categories may even be capable of predicting prodigies, savants, and geniuses in given fields.
As we break down the top tiny fraction of 1% of the population, those nuances in what constitutes their sub-categories athleticism and intelligence are what makes them interesting and likely to accomplish extraordinary things at any given task.
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.
From the same Alfonso paper:
(emphasis added)
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.)
I’m not sure either thesis is very controversial.
As stated, yes, but once you get to “70 narrow abilities” of intelligence, my bullshit-o-meter starts to make excited noises… Though I haven’t looked at the paper, so maybe it’s excited for no good reason.
I agree, but unless I’ve misunderstood ragintumbleweed is citing CHC theory (the thing with the 70 narrow abilities) not as their main thesis but just to say “see, here’s some mainstream academic work on this stuff, and it fits well with my account!”. If it turns out that the 70 narrow abilities are entirely the product of fitting models to noise, or even that CHC theory as a whole is bullshit, that doesn’t make much difference to the claims ragintumbleweed has actually made.