IQ is used synonymous and interchangeably with intelligence; however in this paper [pdf] Angela Duckworth et al argue that non-cognitive factors like test motivation also affect the IQ scores and have differential predictive validity.
Raven’s Progressive Matrices Example (Photo credit: Wikipedia)
Intelligence, which is the ability to flexibly adapt to complex situations, is usually measured using IQ scores on intelligence tests. IQ scores however do not measure juts the raw intelligence; they also measure how motivated someone is to take the test and achieve a high score.
Intelligence tests, that lead to IQ Scores, are supposed to measure the maximal intelligence ability that a person has and not the typical intelligence that he/she uses. In all intelligence testing it is assumed that the person will devote his entire attention and exert the maximum effort possible so as to achieve the highest score possible.
While the assumption that IQ measures maximal intelligence may be true in high-stake testing situations, where the IQ results would be used for academic admissions, job placement or promotions; in normal measurement of IQ, say in a typical school setting, the stakes are quite low (there are no real/tangible repercussions of doing bad or well on the test) and hence IQ does not typically measure the maximal intelligence, but is confounded by test motivation.
Test motivation refers to the fact that some people will be less motivated to take the test or continue with it and may display behaviors that indicate low motivation. While others may be highly motivated to take the IQ test. Thus, there would be individual differences at trait level on test motivation.
Test motivation is also a state variable that can be manipulated by incentivizing getting high scores on the tests. When such incentives are in place, the IQ score should increase from the baseline level or when the test was given under non-incentivized conditions.
Intelligence, as measured by IQ, has been associated with a number of good outcomes. Non cognitive factors as measured by test motivation are also theoretically linked to important life outcomes. For the purposes of this paper, two academic outcomes (years of education and academic achievement) and two non-academic outcomes (employment and criminal conviction) were measured and analyzed.
The study 1 performed a meta-analysis of various independent samples where a comparison was made between the IQ scores received in standardized conditions vis-a-vis under incentivized conditions. For analysis the sample was divided in high IQ (those with IQ greater than 100) and low IQ (those with IQ less than 100). The main results were that incentives did result in higher IQ scores, the effect was stringer for low IQ group and there was dose-response effect with larger incentives leading to greater IQ points gains.
Thus, for low IQ group, the lower IQ scores in standardized conditions could be due to lower intelligence or lower test motivation. If you increase the test motivation, you could bump up the IQ score of some of them. High IQ group, on the other hand had higher scores because they had both higher intelligence and higher test motivation.
In study 2, a thin-slice video of children giving the intelligence test was behaviorally rated for signs of low test motivation. This was a longitudinal study and the IQ scores, test motivation and four types of outcomes were analyzed to find the differential impact of IQ/intelligence and test-motivation/ non-cognitive factors on life outcomes.
The main finding was that test motivation had a significant impact, independent of IQ, on important life outcomes. This was specially pronounced for nonacademic outcomes like employment and criminal convictions. Intelligence as measured by IQ still had significant effect on all adult outcomes. They also found that test motivation predicted IQ scores, thus IQ score measures both intelligence and test motivation.
This is an important paper [pdf] that shows that IQ scores need to be interpreted with caution, and that both cognitive and non-cognitive factors are important for life outcomes.
Today’s research summary is about a paper co-authored by Angela Duckworth, that is at the intersection of psychology and economics. Though I have been following behavioral economics a bit, I still found the paper a bit challenging to read and comprehend and don’t claim to understand all the attached jargon, functions and mathematical formulations. The fact that the paper is 88 pages long wasn’t of help either 🙂 (the saving grace being that 20 or more pages were filled with references alone), so read the rest of the summary at your own peril!
An illustration of Spearman’s two-factor intelligence theory. Each small oval is a hypothetical mental test. The blue areas show the variance attributed to s, and the purple areas the variance attributed to g. (Photo credit: Wikipedia)
The paper aims to throw light on how personality affects (socio)economic outcomes and how concepts from personality psychology can be used in economic equations and modeling.
To start with, an important socioeconomic outcome is success in life. IQ or cognitive ability is well established as a predictor of success in life/job, and slowly but surely, a case is building up for the predictive power of personality traits like conscientiousness to predict success in life/job.
Its useful to distinguish cognitive factors like Intelligence/IQ from other ‘non-cognitive’ factors like personality traits and motivation.
Perry Preschool study which enriched the environment (an intervention aimed at increasing IQ) of disadvantaged kids with subnormal IQ, found that IQ gains for treatment group (which shot up initially) and control group became equal at age 10 , though the treatment group continued to be much more successful on many socioeconomic outcomes over their life cycle. This can be only explained if we admit that something other than IQ, maybe personality factors, were changed by the intervention.
Psychologists use personality, motivation and cognitive factors to explain behavior and success of an agent. Economists however use concepts like preferences, constraints, incentives etc to explain choice/decision/ behavior and ultimately success in life.
Cognitive factors are defined as ‘‘ability to understand complex ideas,to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought’’. The various tests like IQ tests that measure cognitive ability have led to identification of a general factor ‘g’ of intelligence. The factor structure of Intelligence is hierarchical; as per one conceptualization, the second-order factors are ‘fluid intelligence’ and ‘crystallized intelligence“.
IQ test are not a pure measure of maximal intellectual performance; for those getting low scores, appropriate incentives can increase their scores. Similarly test anxiety may affect performance; thus IQ measure is affected by factors like motivation and personality.
Personality factors also have a hierarchical structure; the most common level contains the Big Five factors, below them are specific facets and above them two super factors of plasticity and stability.
The personality traits of Big Five have been arrived at using factor analysis and are more descriptive in nature, based around clustering of together of traits, adjectives or behaviors. The same can be said of ‘g’ which is again more descriptively arrived at. In contrast, economists prefer measures that have been built based around their predictive power in the real word. MMPI, Hogan personality inventory etc were on the other hand built with the specific aim of predicting real world outcomes.
Economists, try to estimate preferences of agents and thus predict/explain their behavior etc. Some of the typical preferences studied are time preference, risk aversion, preference for leisure and altruism/ social preferences. Estimating these preferences help explain and predict behavior that deviates from a purely self-interested rational agent.
Time preference is the preference for immediate reward over future reward. This is measured by the phenomenon of time discounting while making decisions. For example, what would you choose 1 $ today or 2 $ tomorrow? 500 $ this week or 1000 $ next month? based on answers to questions like these (and maybe real world behaviors/ decisions too) economists can infer what is the rate at which you discount future utility for present utility. That function is hyperbolic in nature.
Its seems “time preference is tri-dimensional, comprising three separate underlying motives: impulsivity, the tendency to act spontaneously and without planning; compulsivity, the tendency to stick with plans; and inhibition, the ability to override automatic responses to urges or emotions”. Its easy to see how the three components of time preference can be related to personality factors. Also important is to note that a person with low future vision or imagination may be constrained on this time preference dimension.
Risk aversion is the phenomenon, whereby a sure or less uncertain outcome is preferred over an uncertain outcome. For example, what would you choose 1 $ for sure or a 50 % chance of winning 2.2 $? Based on analyzing such decisions, one can again calculate, how risk averse a person is. This paradigm is however prone to framing effects.
Those who show little risk aversion, also have poor outcomes like indulging in smoking, stealing and not wearing seat belts. The personality trait of sensation seeking, as developed by Zuckerman, is related to this construct.
Preference for leisure is the preference to use time for relaxation etc over indulging in work or economic activity. Some people are driven to work hard and personality traits like Conscientiousness are really relevant here.
Social preferences are preferences like inequality aversion where a monkey would not accept cucumber pieces for the same work, if another monkey is getting grapes instead. Doesn’t make sense rationally, but economists can use social preference to get out of this hole!
The big five as well as IQ are predictive of various life outcomes like leadership, grades, longevity etc
Most personality traits as well as intelligence measures change with age- they are malleable and follow a pattern. For eg, fluid intelligence decreases while crystallized intelligence increases over the lifespan.
Environmental factors like parental investment and social roles can be the mechanisms that lead to changes and stability in these traits.
Preference factors, which are studied by economists, however are not clear as to whether they are stable or change with age and more research needs to be done there.
The real contribution of this paper is in conceiving psychological traits as constraints under which economic decisions are being made. For eg. low cognitive ability will constrain a person to figure out and get clarity about the issue at hand and he will be forced to choose in uncertainty and his risk aversion maybe causing him to make sub-optimal decisions. The intelligent person has a richer choice set and intelligence is a constrain having real world implications; same is true for personality factors.
Thus personality traits may be a form of constraints/ preferences and research in either psychology or economics around this shroud inform each other.
Overall, despite its challenging economics jargon, I found this really useful; as someone interested in personality psychology, this provided a new perspective.
There is long-standing debate in psychology regrading whether ability is inborn or a result of environmental interactions? Whether it is fixed and constant over time or malleable and subject to interventions.
We have also looked at research by Dweck et al that say that no matter whether ability be actually fixed or malleable, the belief that it is fixed and malleable has important consequences. We are better off believing that ability is malleable as that enables us to be more persistent in face of obstacle , more creative and engaged while solving problems and enables us to to tackle hard problem as we are in a learning mindset and not in a proving ourselves/ validating ourselves mindset.
However the issue still remains as to whether ability is inborn or learned? whether genius is 99 % perspiration and 1 % inspiration or whether one can will oneself or choose to be a genius.
Like the other false dichotomies of psychology this one as to whether genius are born or made is not only false by pitching 2 things against each other where both have a role to play but also misses on the other aspects of being a genius like it being a result of sheer will power or the attitude that one has to see thins in a creative light.
While one group claims that talent/IQ is all that is there is to the genius story, the other camp is equally adamant that the 10,000 hours of practice rule suffices to explain genius. To some other genius is all about determination or grit; while still others think that optimism, positive framing and attitude and how we deal with ‘lucky’ breaks is all it takes to become a genius.
There are truths to each of the story, but by focusing on one aspect to the exclusion of others they all miss the point. Its only when you see a genius as a combination of these can you really appreciate the complexity and multiple facets of being a genius.
To give us a framework of reference I refer readers to myABCD model of psychology where A is Affect(genetics) , B is Behaviors (actions and environment) , D is Desire (developmental unfolding of motivation) and C is Cognition ( Conscious decisions and manifestations) .
To see a genius in the light of ABCD model is to see him/her as consisting of talent/IQ (largely genetic and inborn), hard work (need to put the 10,000 hours pf practice to achieve domain mastery), grit (motivation and determination , maybe unconscious , to succeed and overcome obstacles) and attitude (positive re-framing, optimism and choosing to see things in a creative/positive light) .
Out of these talent /IQ is something that we can least work on while positive and creative attitude and mindset is what we can easily change by changing our conscious thought and thinking styles and patterns alone. Hard work (related to conscientiousness) or grit (related to how intrinsically motivated and determined we are) are also more or less in our control . Thus to me becoming a genius is both a choice, that is within everyone’s reach, and a difficult journey that one has to necessarily undertake (a quest that challenges you to self-actualize)
Genius both become what they want to and manifest what their hidden potentialities are . to state otherwise or to assert that they are either born or made is to continue paying homage to a false dichotomy that has longed outlived its usefulness.
A reader of this blog wrote to me recently regarding a series of posts I have written regarding IQ,SES and heritability, and I thought it would be good to share the comments with the rest of the mouse trap community and to delineate my position on the matter (and what I believe the studies show the relation is). First I’ll like to quote extensively from the comment (private mail):
Let me start with my belief that I think we share the same idea about IQ and its origins.
That is, genetics endows each and every person with a maximum IQ that can be achieved if and only if the environment is perfect for the development of this IQ.
Agreed!
Consequently, in identical twins, environment is the only cause of differences in IQ; IQ differences between persons that are not identical twins must be related to both environment and genes.
There are subtle nuances here. (no I’m not being pedantic, the importance of these will become clear in the course of this post). First if MZ twins are raised in the same family, they share the same genotype (A), they share the same ‘shared environment’ (C), so the difference is due to the non-shared environmental factor (E) only. In case of DZ twins raised in the same family, they share half the genotype (A), they share the same shared environment (C) and the difference in say IQ, is due to both genotype (A) and non-shared environmental factors (E). Twin studies with MZ and DZ twins (and in some cases siblings, half-siblings etc ) raised in the same family are used to tease apart the contribution of shared environmental factor, as opposed to genetics and non-shared environmental factors and can be used to find at a broad level if the trait is highly ‘genetically’ heritable (correlation between MZ>>DZ>>siblings), has high ‘shared environmental’ factors operating (MZ~DZ~sibling , but correlation still high) or is largely controlled by random non-shared environmental influences (low correlation in DZ/MZ/siblings). Please see accompanying Wikipedia figure.
Adoption studies are another method that is used to tease apart the shared environmental factors from genetic factors in calculating the heritability of a trait. Thus, even if correlation in MZ twin IQ is high, the effect could be due to shared environment factors (if say both MZ and DZ twin show similar correlation) , or it may be largely genetic (if MZ>>DZ when it comes to correlation between the trait in affected twins.
So it is necessary to qualify your statement: In identical twins, raised in the same family, , non-shared environment is the only cause of differences in IQ. IQ differences between persons that are not identical twins must be related to both shared environment , non-shared environment and genes.
I fully back up this citation:
“suffice it to say that I believe (and think that I have evidence on my side) that shows that in low SES conditions, a Low SES does not lead to full flowering of genetic Intelligence potential and is thus a leading cause of low IQ amongst low SES populations.”
In this case, I think that the problem starts only with your following comments; while you write “a leading cause”, I think that, by yourself, you mean “way more important than genetics”. If this is the case, would you explain to me why you think that?
Here goes. Consider a large sample of children in say low SES populations. IQ may be represented by a formula IQ= aA+cC+eE; where A reflects genotype, C shared environment and E non-shared environment. Here we are assuming no interaction of IQ with SES, so this equation (given values of a, c, e ) should hold for all SES data (both high as well as low SES cohort) . Unfortunately, life is not that simple, and one can not fit the same equation to low SES as well as high SES data set without changing the slopes of variables involved. Thus, Turkheimer and colleagues in two sets of studies have shown that there is an interaction of IQ and SES and there is direct affcet (SES mediated by s) and indirect interaction effects mediated via effects on A(a’), C(c’) and E(e’). Thus our equation becomes
IQ= sSES+(a+a’SES)A+(c+c’SES)C+(e+e’SES)E.
This equation, with suitable values of s, a, a’, c, c’, e and e’ now holds for all values of SES and IQ and the data fits nicely and can be interpreted. Remember that a+a’SES is sort of indicative of contribution of genetic factor to IQ and the proportion of variance due to genetic factor(at any given SES) can be found by squaring this and dividing this by sum of all other variances .
Var(A) =SQR(a+a?SES)
Similarly heritability or proportion of variance due to A :SQR(h)=SQR(a+a?SES)/(SQR(a+a?SES)*SQR(c+c?SES)*SQR(e+e?SES))
Turkheimer have plotted nice plot of their data which sows clearly that in LOW SES situations, the proportion of variance in IQ is largely due to shared environmental factors (C) , while in HIGH SES situations, the proportion of variance in IQ is largely due to genetic factors (A). the figures (in the free PDF available at Turkheimer’s side) is a must see to grasp the significance of this. I am quoting a bit from the paper:
Figure 3 shows the FSIQ variance accounted for by the three components, with 95% confidence intervals. In the most impoverished families, the modeled heritability of FSIQ is essentially 0, and C accounts for almost 60% of the variability; in the most affluent families, virtually all of the modeled variability in IQ is attributable to A.
Let us pause here and reflect on what this means. This means that in low SES families, IQ is independent of genotype and is mostly dependent on the SES status. Let us take some concrete examples. Say the mean IQ of low SES sample (income as a proxy for SES ranging from 1000-5000 rs p.a.; mean 2500 and variance 250)) is 80 with mean variance of 20. Thus, in this sample a typical child has IQ in range 80 +-20 or between 60 and 100. Suppose further that there are 5 alleles that confer differential advantage for IQ on a locus thus representing 5 genotypes, then having either of the genotype will essentially give us no predictive power to say whether the IQ of a particular sample is 80 or 60 or 100. Also, let us assume that there are 5 classes of C and they are highly correlated with SES. First class of C (is 1000-1500 SES range) and so on and so forth. Then knowing whjat kind of family (C) the child grew up in we could easily predict his IQ (if he is of class C where SES ranges from 1000-1500), his IQ is most probably 60. This is what I mean when I say that in low SES environments IQ is largely determined by environment and not by genetics. Now , I have taken a jump here and equated C with SES, but that is a justified leap in my opinion (more about that later).
What this also means is that given the right type of environment (say class C with SES in upper range of 3500-5000 rs p.a.) , all children (irrespective of their genotype (any 5 variants of genotype) can still achieve an IQ in the upper range , say 100 as the environment is the only predominant factor operating at this level and the impact of genetics is still not felt. Thus, if we do increase SES and provide the right C, then every child in this group can have mean IQ of 100.
Contrast this with the case at the upper end of the strata (SES). Here most of the variation in IQ is predominantly due to genetics (A) and shared environment C does not seem to play a big factor. Thus, knowing a genotype of a child has greater predictive power in this sample, than knowing his C (or family income or SES). Thus, evenif we provide a very enriched environment to all children (increase their C to the highest percentile), it would have no effect on increasing the mean IQ of the sample as now the IQ is mostly under genetic control.
This in a nutshell, is what I mean when I claim that low SES is the leading cause of low IQ in low SES families.
Before I rest, some objections might be readily apparent to a keen observer. First is the assumption inherent that SES and C are the same. I would like to propose here a new shared and universal sub-threshold environmental factor and would like to elaborate with a couple of examples. Let us say that those below poverty level do not have access to iodized salt and are thus prone to goiter and also mysteriously to low IQ as there is a module of brain (5 diff alleles at a particular locus leading to differences in abilities using this module) that needs iodine for its flowering and in absence of iodine, none of the alleles have any effect whatsoever- the module itself does not develop, so there are no questions of differences in ability or IQ due to differences in genotype etc. Now, given this state of affairs and also the fact that low SES families do not have access to iodine, when IQ is measured (then because of absence of this factor X), all children in this proband will have an IQ that does not measure abilities of this module (say this module adds 20 points of IQ) and thus all of them will have an IQ less by 20 points than was actually possible.Say the mean IQ measured is 80. Given the fact that some of the higher SES within this low SES group may have partial and sporadic access to iodine , the variance will be entirely environmental and no genetic variance would be found with some people having IQ close to 100 , who are in relatively upper start and have decent access to iodine. Contrast this the higher SES proband all of whom have access to iodized salt and thus can use their additional 20 points advantage on IQ tests. It would not be surprising if most of the variation here was genetic based on factor X allele) rather than due to income level or SES.
Another example to ruminate on is another universal and shared sub-threshold factor like having a golf course in the house. Let us assume that within higher SES group, this environmental enrichment factor plays a role, with some lower strata of higher SES (the middle class) not able to afford a golf course, while the higher higher SES strata (the upper class) abvle to afford a golf course and expose their children to them . Further, suppose that there is a module in the brains and genes switched on only if exposure to golf course takes place. Then within this higher SES group, what we will observe is that though the genetics plays a good role (due to factor X-iodine: remember, which is available to all in this group) ; still there would also be variation due to environment (golf course exposure) and that a full 20 points more can be added to all people of this group (with mean IQ 100 raising their IQ to 120), if all were exposed to a golf course and a intelligence-module-dependent-on-golf-course-exposure was allowed to develop. And on the higher end of IQ (and SES) what we would find is that most of the variance now is genetic (due to this golf-course module coming into play), while at the lower end, most of the variance is still environmental within this ‘high’ SES group.
If the above seems far fetched this is exactly what Turkheiemrs et al found in their follow up study focusing on mid to high SES children. I quote from it (again the pdf has beautiful figures and you should see them) :
Figure 2 illustrates the relations between income and genetic and shared environmental proportions of variance, as implied by the parameters estimated in Model 3. Genetic influences accounted for about 55% of the variance in adolescents’ cognitive aptitude and shared environmental influences about 35% among higher income families. Among lower income families, the proportions were in the reverse direction, 39% genetic and 45% shared environment. Although the shared environmental proportion of variance decreased with income, shared environmental variance per se did not decrease. The interactive effect was driven entirely by the increase in genetic variance. Genetic variance in cognitive aptitude nearly doubled from 4.41 in families earning less than $5000 annually to 8.29 in families earning more than $25,000 annually.
Our investigation supports our hypothesis that the magnitude of genetic influences on cognitive aptitude varies with socioeconomic status. This partially replicates the results presented by Turkheimer et al. (2003); however, no shared environmental interaction effects were demonstrable in the current study. Genetic influences accounted for about 55% of the variance in adolescents’ cognitive aptitude and shared environmental influences about 35% among higher income families. Among lower income families, the proportions were in the reverse direction, 39% genetic and 45% shared environment. This pattern is similar to the pattern seen in Turkheimer et al. (2003), although less marked.
So, I want you to pause here and grasp the significance of this- at every level of IQ-SES, there may be threshold factor that giverns whether IQ modules flower to full potential and this is the putative mechanism that leads to SES causing low or high IQ directional and causal relation. At each level, as the threshold factors become available,. more and more IQ starts coming under genetic control, but , and this is important, for jumps in IQ to take place , increasing SES (removing the sub-threshold conditions) is VERY important.
I mean “not following up on the ‘a leading cause'”, because in a later post, you write:
“Now, I have shown elsewhere that low SES causes low IQ”
Here, there is no mention of any other possible cause besides the environment anymore.
Yes, because as shown very strongly by Turkeihems and team , at low SES, shared environment/SES is the putative mechanism and genetics has no/negligible role to play. So for low SES, low SES causes low IQ. period.
in another post, you write
“A series of studies that I have discussed earlier, clearly indicate that in the absence of good socioeconomic conditions, IQ can be stunted by as large as 20 IQ points. ”
This same post also contained this citation “Children of well-off biological parents reared by poor/well -off adopted parents have Average IQ about 16 point higher than children of poor biological parents”
In my opinion, the latter would indicate the approximate range of genetic IQ differences for the samples in this study, while the former would indicate the approximate maximal environmental gain that can be hoped for in the environments that were encountered in these studies.
No they don’t. They talk about different SES groups, so as shown findings from one cannot be extrapolated to the other. In the low SES group, there is no genetic variation. We can thus not conclude that that (16 points diff.) is the ‘average’ genetic component taken the entire sample together. what one can say is that if mean IQ of high SES children was 100, the mean IQ of low SES children was 84 . Period. The difference is likely due to the fact, that the module X has not developed in low SES people (more later) .
Regarding the former, yes I agree that that is the maximum gain that one can hope for if all children of low SES were given the right environment (raised to high SES). Put another way, if mean IQ of poor/low SES children is 84 , then given the right conditions the mean of the low SES children can be raised to 104 (greater than high SES children’s mean :-).
As both of them do cover the same IQ range (10-20), the logical consequence for a broad statement on IQ and genetics seems therefore to be, that these studies may say that overall, IQ changes can be expected to be determined to approximately equal parts by genetics and environment, with environment being responsible for a typically larger part in low SES families, and genetics playing a relatively larger part in high SES families.
Agreed partially, but that glosses over the fact of sub-threshold universal shared environments and the fact that the role of genetic and environmental component varies with SES, an therefore an ideal statement would be IQ is under gentic controltolarge extent, but that gentics needs threshold environments to flower and thus the importance of environment component- not in explaining variance , but by its direct effect on IQ enabling/flowering.
This same post also contained this citation “Children of well-off biological parents reared by poor/well -off adopted parents have Average IQ about 16 point higher than children of poor biological parents”
In my opinion, the latter would indicate the approximate range of genetic IQ differences for the samples in this study, while the former would indicate the approximate maximal environmental gain that can be hoped for in the environments that were encountered in these studies.
As both of them do cover the same IQ range (10-20), the logical consequence for a broad statement on IQ and genetics seems therefore to be, that these studies may say that overall, IQ changes can be expected to be determined to approximately equal parts by genetics and environment, with environment being responsible for a typically larger part in low SES families, and genetics playing a relatively larger part in high SES families.
There also is this citation:
“The normal observation that identical twins belonging to well-off/middle class families have IQ rates similar as compared to fraternal twins, thus indicates that for children from well-off background (biological/adopted), the IQ (observed phenotype) is mostly due to genetic factors (underlying genotype) and environmental factors are not a big determinant.
The paradoxical observation that identical twins belonging to poor families have IQ rates as varying as compared to fraternal twins, should indicate that for children from poor background (biological/adopted), the IQ (observed phenotype) is mostly due to environmental factors and genetic factors (the underlying genotype ) are not a big determinant.”
These are extremely nice observations. I would be interested in the conclusions one might be tempted to draw from them. Reading the latter part of this sentence, one might come to the following conclusion (conclusion 1): “if in low-SES families the variations in IQ are largely determined by environmental factors, then providing a positive environment for the development of IQ would increase the IQ levels in these families impressively (up to 20 points; but, this is an up to value, means would be more interesting).”
While I completely agree with this thinking, one might also be tempted to draw the conclusion that (conclusion 2) “As IQ variations in low-SES families are largely due to environment, providing an IQ-stimulating environment in low-SES families might completely eliminate the IQ differences between low-SES families and high-SES families”
At the least, a non-cautious reader might understand your words as such. I am not sure whether you think that way or not. I would like to hear your opinion on that. I think that this citation “Children of well-off biological parents reared by poor/well -off adopted parents have Average IQ about 16 point higher than children of poor biological parents” provides an argument that precludes conclusion 2. It would rather say that (conclusion 3), ” providing a perfect IQ-stimulating environment for low-SES families as encountered in these studies, one should think that their offspring would achieve an IQ level that is 16 points lower than that of the offspring of high-SES families.”
I would like to hear your opinion on my conclusion 3.
I agree with conclusion 1. I also agree with conclusion 2 (not based on political correctness, but hard data). The paper on which these figures are based can be found here. The mean IQ of high SES persons is 113.5 and the mean IQ of low SES children is 98.00, thus a difference of ~16 points. The variation in IQ of high SES children raised in high SES families is 12.25; as shown this variance is likely due to genetics (say hundred percent is due to genetics); then changing the SES within the given range should have no effect on average IQ and it would remain 119 (for this high +/high+ group). On the other hand, the variance in low SES, reared by low SES families is 15.41 and mean is 92.40;thus if all were given enriched environment, their mean IQ would become 92.4+ 15.4 = ~ 108 . We still have a 10 point difference which can be accounted for by the fact that genetics had not come into play for low SES , low SES group yet and as genetics enters and increases the variance due to genetic flowering,, their IQ would be in the same league as high IQ/High IQ children.
So definitely the conclusion 3 is flawed- the difference would not be close to 16 points, but negligible, as the 16 points nowhere measures gentic difference in abilities, but reflects the genetic factor not yet active in low SES, due to improper environmental exposure.
I think that this is a rather important conclusion, as it tells us something about the differences in IQ that can be expected to exist between distinct population stratums (don’t know whether this is an appropriate word for what I try to say; I hope you understand what I mean).
If this is the ballpark of figures that we can expect between low-and high SES IQ differences, this would have important effects on future IQ-distributions. Population-wide stability of IQ-performance, if measured in a saturated environment (maximum stimulation of all members of society), can then only be achieved if all stratums of society have the same number of offspring per individuum. If low-SES families have more children, we have to expect that the 16-point lower IQ will decrease the whole-population IQ.
Here, the 16 points only apply to the sample as measured in your example; the true value of the saturated stratum-dependent-IQ together with stratum-dependent birthrates will determine the shift of the saturated IQ-distribution for the generations to come.
Do you agree with this point of view?
To use a very strong and negative connotation word, the above smacks of eugenics. And I wont comment further on this. Each according to his own philosophy, but beware that science does not support your conclusions. Instead of population controlling the poor, please try to elevate their vicious loop of undeserved poverty, low IQ and harmful stigma.
Turkheimer, E., Haley, A., Waldron, M., D’Onofrio, B., & Gottesman, I. (2003). Socioeconomic status modifies heritability of iq in young children Psychological Science, 14 (6), 623-628 DOI: 10.1046/j.0956-7976.2003.psci_1475.x
Harden, K., Turkheimer, E., & Loehlin, J. (2006). Genotype by Environment Interaction in Adolescents’ Cognitive Aptitude Behavior Genetics, 37 (2), 273-283 DOI: 10.1007/s10519-006-9113-4
Capron, C., & Duyme, M. (1989). Assessment of effects of socio-economic status on IQ in a full cross-fostering study Nature, 340 (6234), 552-554 DOI: 10.1038/340552a0
You must be logged in to post a comment.