(Read from the bottom up)
Some blacks have low IQs, some have very high IQs (Walter Williams, Thomas Sowell)
ON AVERAGE, Orientals have the highest IQs, whites are intermediate, and blacks have the lowest IQs. This is pretty well established through lots of research, empirical data. It is not politically correct to even say this, let alone attribute anything else to this fact, but I’m not PC. In my view, if we want to help African-Americans, and I do, we cannot at the outset ignore relevant facts.
I also think that ON AVERAGE, men are taller and heavier than women, even though there are plenty of women who are taller and heavier than some short, skinny men. This is pretty well established through lots of research, empirical data. Does saying this make me a sexist? If so, I embrace that description.
Blacks are more given to sickle cell anemia; Jews to Tay-Sachs disease. Suppose there were a medical researcher who refused to acknowledge this claim, also based on lots of research, empirical data. We wouldn’t think too much of him as a medical researcher; we wouldn’t think he’d be successful in curing either disease. Similarly, for a social scientist who ignores research in IQ. We wouldn’t think too much of him as a social scientist; we wouldn’t think he’d be successful in helping the downtrodden.
It is my policy to publicly blog all such communication, keeping my correspondant totally anonymous. Bob has a similar policy, I think
Sent: Sunday, February 03, 2019 11:40 AM
To: ‘Walter Block’ <email@example.com>
Subject: RE: Spurious correlations
So you think that blacks are dumb?
From: Walter Block [mailto:firstname.lastname@example.org]
Sent: Sunday, February 03, 2019 6:02 PM
Subject: RE: Spurious correlations
Racism of this sort is what (social) science is all about
Walter E. Block
Sent: Saturday, February 02, 2019 8:46 PM
Subject: RE: Spurious correlations
Now this is Racism.
While I agree that Political Correctness is junk, so is summing up any “race” – judging any individual by race or the race itself. The bell shaped curves , at their worst, show – clearly – that 1/3 of the supposedly “inferior” race is smarter than 1/2 of the supposedly “smarter” race. At the end points, A person of any race can be the smartest or dumbest. Then there are the “tests” and sampling methods – all questionable.
This is why it is dumb to judge people by race. This is why dumb, good ol’ boys of every race and nationality are racists – they want someone to look down on – to feel superior since they know they are not!
“When you call yourself an Indian or a Muslim or a Christian or a European, [white] or anything else, you are being violent. Do you see why it is violent? Because you are separating yourself from the rest of mankind. When you separate yourself by belief, by nationality, by tradition, it breeds violence. So a man who is seeking to understand violence does not belong to any country, to any religion, to any political party or partial system; he is concerned with the total understanding of mankind.” J. Krishnamurti, Freedom from the Known, pp.51-52
Sent: Sunday, February 03, 2019 3:43 AM
Subject: Re: Spurious correlations
The page is an embarrassment to those supporting your view.
There is this on the page :
“Height is correlated with intelligence.”
There go Ashkenazy Jews.
“Jews are everywhere from 1 to 3 cm. shorter than the Gentiles.”
Your referenced page also says:
“The predictive validity of g is most conspicuous in the domain of scholastic performance.”
It could thus be very easily argued that “the domain of scholastic performance” conspicuousness points to what Taleb charges: It measures the ability of exam-takers, paper shufflers, obedient IYIs (intellectuals yet idiots).
The Wikipedia page you reference also includes:
“Critics of g have contended that an emphasis on g is misplaced and entails a devaluation of other important abilities, as well as supporting an unrealistic reified view of human intelligence.”
” Some critics have gone so far as to argue that g ‘…is to the psychometricians what Huygens’ ether was to early physicists: a nonentity taken as an article of faith instead of one in need of verification by real data.’”
” John Horn argued that g factors are meaningless because they are not invariant across test batteries, maintaining that correlations between different ability measures arise because it is difficult to define a human action that depends on just one ability.”
“Both Deary et al. (1996). and Tucker-Drob (2009) have pointed out, dividing the continuous distribution of intelligence into an arbitrary number of discrete ability groups is less than ideal for examining (SLODR).”
“Some researchers have warned the existence of statistical artifacts related to measures of job performance and GCA test scores. For example, Viswesvaran, Ones and Schmidt (1996) argued that is quite impossible to obtain perfect measures of job performance without incurring in any methodological error. Moreover, studies on GCA and job performance are always susceptible to range restriction, because data is gathered mostly from current employees, neglecting those that were not hired. Hence, sample comes from employees who successfully passed hiring process, including measures of GCA.”
“One criticism that has been made of studies that identify g with working memory is that “we do not advance understanding by showing that one mysterious concept is linked to another.”
“Raymond Cattell, a student of Charles Spearman’s, rejected the unitary g factor model and divided g into two broad, relatively independent domains: fluid intelligence (Gf) and crystallized intelligence (Gc). Gf is conceptualized as a capacity to figure out novel problems, and it is best assessed with tests with little cultural or scholastic content, such as Raven’s matrices. Gc can be thought of as consolidated knowledge, reflecting the skills and information that an individual acquires and retains throughout his or her life. Gc is dependent on education and other forms of acculturation, and it is best assessed with tests that emphasize scholastic and cultural knowledge. Gf can be thought to primarily consist of current reasoning and problem solving capabilities, while Gc reflects the outcome of previously executed cognitive processes…Cattell, together with John Horn, later expanded the Gf-Gc model to include a number of other broad abilities, such as Gq (quantitative reasoning) and Gv (visual-spatial reasoning). While all the broad ability factors in the extended Gf-Gc model are positively correlated and thus would enable the extraction of a higher order g factor, Cattell and Horn maintained that it would be erroneous to posit that a general factor underlies these broad abilities. They argued that g factors computed from different test batteries are not invariant and would give different values of g, and that the correlations among tests arise because it is difficult to test just one ability at a time.”
” Howard Gardner has developed the theory of multiple intelligences. He posits the existence of nine different and independent domains of intelligence, such as mathematical, linguistic, spatial, musical, bodily-kinesthetic, meta-cognitive, and existential intelligences, and contends that individuals who fail in some of them may excel in others.”
“Sternberg equates analytic intelligence with academic intelligence, and contrasts it with practical intelligence, defined as an ability to deal with ill-defined real-life problems.”
Can you refute these or are you just buying into a bunch of stuff you don’t understand?
On Sat, Feb 2, 2019 at 3:31 PM M> wrote:
B, To answer your question, I’m not saying a high IQ will result in a high income.
To illustrate, if we measure the IQ score of 10,000 individuals, the 1,000 with the highest IQs will probably have a higher group average income than a lower IQ group. This is not to deny that some poor people may have high IQs, since we’re looking at group averages. That IQ scores are associated with a variety of factors makes less spurious the notion of a general factor, called g, underlying intelligence.
“The practical validity of g as a predictor of educational, economic, and social outcomes is more far-ranging and universal than that of any other known psychological variable. The validity of g is greater the greater the complexity of the task.” https://en.wikipedia.org/wiki/G_factor_(psychometrics)
Please read the wikipedia article for a more sophisticated analysis than I’m able to offer.
I hope I’ve answered your question adequately.
On Feb 2, 2019, at 11:01 AM, Robert wrote:
You miss my point.
All the original correlations listed in the link you provided are in fact correlations as they stand.
Then you write on about your IQ correlation:
“IQ and success have been correlated on a variety of measures.”
But this is somewhat of a difficult thing to test, and what is success?
But the correlations originally listed are all much easier to test. They are correlations. They become spurious because there is no necessary relation between them and many would believe when there is a correlation there is also a necessary relation.
I believe your assertion has hidden necessary relation claims along this line of thinking.
Best example, you assert there is a correlation between IQ and income. Am I incorrect in thinking that you believe this shows that high IQ will result in high income? And you probably think that low IQ means low income prospects.
But just looking at this correlation tells us nothing. Maybe likely future income influences IQ instead of the other way around.
Or maybe there is no necessary relation at all.
I recall, Murray Rothbard in one of his taped lectures uses the example of a dumb monk that is so dumb he gets kicked out of the monastery. Wandering the streets he decides to get a cigar but cannot find a cigar stand thus he decides to open a cigar stand and makes a fortune. His point was that you don’t need a high IQ to make a high income.
I suspect the truth is very complex here, and the correlations you trot out are even more spurious in that the correlations are a lot less tight than the original list of correlations.
It’s the necessary relation correlations that are most interesting but they must be explained outside the correlation data.
Just throwing out correlations doesn’t do that—especially in the social sciences, where experiments cannot be controlled the way they can in the physical sciences. It spurious correlationism.
Further to another point I made, if a third factor is a primary driver, it doesn’t mean that other factors correlate in a necessary way.
Take the NBA, we can certainly see that NBA players are both tall and have high endorsement incomes. Does this mean that we can take any tall person put him in the NBA and he will be paid multi-millions for endorsements? Of course not, the driving necessary factor is basketball skill.
In the same way, maybe the primary driver to high income is alertness and drive. Thus, Murray’s dullard monk can have a high income if he is only alert to the cigar opportunity and the drive to open a cigar stand, whereas a lazy high IQ person won’t have a high income. High income might follow for the high IQ person if most of them have strong alertness and drive. The driving factor being the alertness and drive.
To argue just on correlation that high IQ is important to high income probably suffocates the drive of low IQ people to seek out income opportunities and is, thus, a terrible thing to argue.
On Fri, Feb 1, 2019 at 9:02 PM M> wrote:
If they all covary and could be explained by a fundamental causal factor then they would not be considered spurious. For example job success, academic success, health, income, and life expectancy all are covariates of IQ scores.
Warm regards, M
On Feb 1, 2019, at 4:51 PM, Robert wrote:
But couldn’t they all be correlated by a third causal factor?
On Fri, Feb 1, 2019 at 3:27 PM M
IQ and success have been correlated on a variety of measures, whereas these are have not been.
Warm regards, M
On Feb 1, 2019, at 1:58 PM, Robert wrote:
Why do you not include IQ and success as a possible spurious correlation?
On Fri, Feb 1, 2019 at 11:18 AM M
2:05 am on May 15, 2019 Email Walter E. Block
Please follow and like us: