Thursday 19 October 2017

An Attempt to Reconcile the Group Differences in IQ

A thorny and often avoided topic is the reported difference in average IQ scores between groups. This article aims to postulate a unifying hypothesis, based on careful observation, data from various researches, and views and reasonable persuasions from notable academic researchers and psychology bloggers. Some elements of the hypothesis about to be put forward draw from critical reasoning common to quantitative fields, and mathematical induction.

For a summary of the current state of affairs, see the wikipedia article Race and intelligence.

Various factors have been hypothesized as the reasons for the differences, but this article takes a different approach by watching for 'capacity' from an academic achievement standpoint, using this achievement as proxy for intelligence.

On the assertion that environmental factors are the sole or most important contributor to group differences in IQ, Gregory Cochran and Henry Harpending present a powerful counter argument on their blog post The Great IQ Depression:

We hear that poverty can sap brainpower,  reduce frontal lobe function,  induce the  fantods, etc.  But exactly what do we mean by ‘poverty’?  If we’re talking about an absolute, rather than relative, standard of living,  most of the world today must be in poverty, as well as almost everyone who lived much before the present.  Most Chinese are poorer than the official US poverty level, right?  The US had fairly rapid economic growth until the last generation or so, so if you go very far back in time, almost everyone was poor, by modern standards. Even those who were considered rich at the time suffered from zero prenatal care, largely useless medicine, tabletless high schools,  and slow Internet connections.  They had to ride horses that had lousy acceleration and pooped all over the place.

In particular, if all this poverty-gives-you-emerods stuff is true, scholastic achievement should have collapsed in the Great Depression – and with the miracle of epigenetics, most of us should still be suffering those bad effects.


But somehow none of this seems to have gone through the formality of actually happening.


The Bell Curve has been observed even within groups. Genetics appears to be the most important contributor to the differences.

Do the scores between groups point to difference in intelligence? I would not want to use the g factor, as its definition in the context of cognitive tests may expose it to relative interpretation. I will propose a new term called 'capacity' or c for short. Capacity is the 'absolute' ability of an individual to acquire an academic achievement, assuming the absence of abnormalities such as a learning disability. Therefore, c is a proxy for intelligence. Why use academic achievement instead of current cognitive tests? We need an alternate measure to study our current realities.

Charles Murray, via Gene Expression,offers this insight on what fraction of the (US) population is capable of absorbing a university education or mastering college-level material:

To have an IQ of 100 means that a tough high-school course pushes you about as far as your academic talents will take you. If you are average in math ability, you may struggle with algebra and probably fail a calculus course. If you are average in verbal skills, you often misinterpret complex text and make errors in logic.

These are not devastating shortcomings. You are smart enough to engage in any of hundreds of occupations. You can acquire more knowledge if it is presented in a format commensurate with your intellectual skills. But a genuine college education in the arts and sciences begins where your skills leave off.


In engineering and most of the natural sciences, the demarcation between high-school material and college-level material is brutally obvious. If you cannot handle the math, you cannot pass the courses. In the humanities and social sciences, the demarcation is fuzzier. It is possible for someone with an IQ of 100 to sit in the lectures of Economics 1, read the textbook, and write answers in an examination book. But students who cannot follow complex arguments accurately are not really learning economics. They are taking away a mishmash of half-understood information and outright misunderstandings that probably leave them under the illusion that they know something they do not. (A depressing research literature documents one's inability to recognize one's own incompetence.) Traditionally and properly understood, a four-year college education teaches advanced analytic skills and information at a level that exceeds the intellectual capacity of most people.


There is no magic point at which a genuine college-level education becomes an option, but anything below an IQ of 110 is problematic. If you want to do well, you should have an IQ of 115 or higher. Put another way, it makes sense for only about 15% of the population, 25% if one stretches it, to get a college education. And yet more than 45% of recent high school graduates enroll in four-year colleges. Adjust that percentage to account for high-school dropouts, and more than 40% of all persons in their late teens are trying to go to a four-year college--enough people to absorb everyone down through an IQ of 104.


It is then expected that there is a minimum c, statistically, for which an engineering or math degree can be achieved -- and it is not usually possessed by US White population with IQ of 100. What happens in other parts of the world? Considering the research by Rushton, et al. Construct validity of Raven's Advanced Progressive Matrices for African and non-African engineering students in South Africa, how can we reconcile the outcomes?

One reviewer suggested that it seemed unlikely that Africans with so low an IQ could complete engineering school and then practice the profession, and so these lower scores cannot mean the same as they would for students in the US.

Two possibilities were proposed. The first is that the low African mean IQ score does accurately represent the probable level of cognitive performance for the population and that, indeed, commensurate work performance is predicted (see Lynn & Vanhanen, 2002). The second is that although individual differences in IQ score within populations are predictive of individual differences in various criteria within that population (as in Figures 3 and 4), differences between populations are attributable to such factors as poverty and cognitive deprivation so that high motivation is able to outweigh their predicted role in determining performance. According to this view, Euro-American test norms are not valid for Africans. And it adds that, future research, especially longitudinal studies using some of the real-life criteria identified by Gottfredson (2003) could be undertaken to better resolve this enigma.

Now, considering the view that a person of average of intelligence would struggle at a tough high school course, not to mention a college engineering or math degree, how can we reconcile the fact that the math and science students at the University of the North had an average IQ of 100, and African cognitive elite engineering students at the University of the Witwatersrand had an IQ of 103 (Rushton et al., 2003)?

If we use academic achievement as proxy for intelligence, many modern sub-Saharan Africans (arguably from pools similar to those in the research) have come to US universities and have studied engineering courses and have come out with good grades, and have been gainfully employed in the US. It appears to follow that these students possess the minimum c for these achievements, yet clocking in at such comparatively low scores. It is important to mention that these population subsets are also those at a higher IQ percentile for their populations.

What about the academically high-achieving Pakistanis in the US? Can the average Chinese achieve the engineering degrees despite having a higher average IQ score? Perhaps it is that persons of similar or equal IQ scores from different groups do not possess equal c. But I theorize that persons of different groups at equal percentiles of IQ within their respective groups may possess similar c. Hence, between-group differences in test scores could be merely a constant in a biological equation, where the constant does not add to intelligence, but is merely a biological marker k for the different groups.

IQ = k + c

Could this really be a possibility? Let us see how it attempts to solve another anomaly. Some countries in Africa have an average IQ of 70. This would be mental retardation by US norms with all its blindingly visible symptoms. But alas! This does not happen. These countries have their own scores for their own lows!

Some have argued that these groups have a high motivation that help them achieve more than their white counterparts of similarly average scores. The counter argument is that they do not have a monopoly on motivation, and this kind of ability statistically comes at a threshold as observed even within groups. As stated earlier, these population subsets are also those at a higher IQ percentile for their own populations.

IQ = g ignores the possibility of k, and assumes that between-group persons of equal IQ scores must have equal g, and appears to suffer the contradictions of the reality observed.

[Pseudo representations have been used to describe complex biological functions]

But could there be any such biological equations affecting cognitive ability? Reaction time (RT). Several studies have found differences between races in average reaction times. These studies have generally found that reaction times among black, Asian and white children follow the same pattern as IQ scores. Rushton & Jensen (2005) have argued that reaction time is independent of culture and that the existence of race differences in average reaction time is evidence that the cause of racial IQ gaps is partially genetic instead of entirely cultural.

Do we have more data to corroborate the possibility of high academic performance at seemingly low IQ scores? See "Wisconsin Men's Henmon-Nelson IQ Distributions for 1992-94 Occupation Groups with 30 Cases or More" for a range.




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