The NAEP provides ethnic averages and percentiles in both reading and math for 8th graders in 2019. I chose 8th graders because they are the oldest age group for which they have nationally representative samples, since 12th graders only include those who have not yet dropped out of school. Note: scores are reported on 0 to 500 scale.
American Indian/Alaska native
American Indian/Alaska native
Although the NAEP is not an IQ test, the correlation between IQ tests and scholastic achievement tests is about as high as the correlation between two IQ tests, making them statistically equivalent in the general population. Further, the main reason people care about racial IQ gaps is because they translate into racial learning gaps, so converting to IQ seems appropriate and the advantage of using the NAEP to infer group IQ gaps is the excellent sampling this data has among subjects who have spent their whole lives learning these skills.
American Indian/Alaska native
For technical details on how these scores were converted to IQ, see technical note below.
The reading, math, and composite NAEP scores were converted to IQ by equating the white NAEP means with 100 and the white NAEP SDs with 15. The reading and math SDs were estimated by subtracting the 90th percentile NAEP scores from the 10th percentile scores and dividing by 2.53 (the bell curve Z score difference between these percentiles) .To determine the white mean of the composite score, we simply add the reading and math means, which gives 564. The white SD of the composite score was crudely estimated by assuming the reading and math correlation among all white 8th graders taking the NAEP is the same as the correlation among all college bound 17-year-olds taking the SAT (r = 0.67 according to Herrnstein and Murray). Using the formula for calculating the composite SD (from page 779 of the book The Bell Curve by Herrnstein and Murray):
I am extremely honored that Davide Piffer (who has a blog) was kind enough to give our community an exclusive interview. While the leading geneticists in academia have explained only about 10% of the variance in IQ (or its proxy education) at the individual level, Piffer working on his own has reported near perfect correlations between the mean IQs of entire ethnic groups and their polygenic scores, making him a rock star in the HBD community. Virtually no one else on the planet is doing this kind of cutting edge research (at least not publicly).
In retrospect it makes perfect sense that aggregated data should correlate much better than individual level data. Imagine you visited every country in Eurasia and asked only the first person you met in each country their height. Such a small sample size (n = 1) from each country would tell you nothing about which individual country was taller than which, but if you averaged all the heights from the European countries and compared them to the average heights from the Asian countries, you’d learn a lot about which continent was taller. That’s because the small sample size at the level of individual countries is multiplied by the large sample of countries in each continent.
It’s the same with genomically predicting IQ. The small sample of single nucleotide polymorphisms (SNPs) sampled in each individual is multiplied by the large number of individuals sampled in each ethnic group, so while individual predictions are weak, group predictions are strong because individual error cancels out in the aggregate.
Below is my exclusive interview with Piffer. The interview has been lightly edited to remove typos and other mistakes. I began by asking him about table 5 in a 2019 paper he wrote. My statements are in red, while Davide’s are in blue.
PP: I’m very impressed by your work. But the correlation between PG score & mean IQ is so high in table 5 of Piffer (2019) that it seems too perfect. What would you say to skeptics who think you cherry-picked SNPs or manipulated your formulas to get such perfect results?
DP: Thanks. I didn’t cherry pick SNPs. I used the polygenic score provided by Lee et al and you can see that different PGS construction methods lead to same results… I used EA, EA Mtag, etc, weighted and unweighted..they all give same results. Also my paper replicates my previous findings and what I had predicted from theory years ago. The IQs aren’t cherry picked either because I used the same as I used in previous papers to avoid post hoc results.
PP: In table 1 of Piffer (2019), Peruvians & Colombians seem to have higher polygenic scores than the black populations, yet in Figure 11, Africa scores higher than the Americas. So who has higher polygenic scores: sub-Saharan Africans or Amerindians?
DP: Peruvian and Colombian aren’t pure. They are substantially mixed with Europeans. The groups in figure 11 are natives, so they better reflect the unadmixed population. Also the latter are from low coverage genomes with fewer markers so less reliable. I am working on a high coverage version of same datasets but it will take a while due to my limited funds.
Do you have some basic experience in bioinformatics? I am just looking for someone who could run the code on their laptop because it’s taking me a week to impute each chromosome. So I need to run it on multiple computers. But hey no bother…I will do it myself, it will just take it longer.
PP: No sadly I do not have experience with bioinformatics. But I can ask my blog & twitter readers if anyone has such experience and is willing to volunteer their time.
On table 5 of Piffer (2019) the African American PGS (GWAS sig) is 1.836 lower than the NW European PGS. But since African Americans are only 76% non-white (Bryc et al. 2015), can we roughly infer that un-mixed blacks would be 1.836/0.76 = 2.416 below NW Europeans, giving them a PGS score of 46.834?
DP: yes…also you have unmixed native Africans in the other tables. Kenyans, Yoruba, Mende Sierra Leone, etc
PP: In table 5 Latinos have a PGS (GWAS sig.) of 48.654. Do you think this could be used to estimate the PGS of unmixed Amerindians because according to Bryc et al, 2015, Latino Americans are 65.1% white (mostly southern European), 6.2% black, 18% Amerindian, and 11% unassigned, though the unassigned is broader East Asian/Amerindian so should probably be counted as Amerindian. Since you report the PGS for Southern Europeans and since I estimate the the PGS for pure blacks at 46.834, using simple algebra, I estimate unmixed Amerindians would have a PGS of 47.510.
DP: yes, but you should also cross-check these with the other table with scores for Peruvians and Mexicans and see if they converge.
PP: Good point. In one of your data sets you find a 0.57 correlation between PGS and latitude. Do you agree with Lynn’s cold winter theory of how racial differences in intelligence evolved?
DP: in part, yes. but it doesn’t explain the low Amerindian IQ because Native Americans were in Siberia during the Last Glacial Maximum and then they moved to North America at the end of it, which is also a cold region…So I think most of the differences are due to farming and civilization
PP: Well Lynn argues the anomalies can all be explained by population size. Low population races like Arctic people, Amerindians, Australoids, Bushmen, & pygmies have lower IQs than their climates predict because there weren’t enough positive mutations. Meanwhile high population races like East Asians, whites, South Asians, and West Africans have higher IQs than their climates predict. This would also explain why Neanderthals had lower IQs than their climates predict.
DP: but these SNPs are common among the races..the differences are explained by these common SNPs, not pop specific mutations. pop size is probably related to it through higher competition for resources selecting for higher IQ.
PP: I see…so then it was probably farming and civilization as you say. Just as cold climate boosted IQ because it was a novel environment to adapt to, so was farming, civilization and the literacy and numeracy requirements it imposed. Of course Amerindians also independently created civilization but most remained hunter-gatherers.
DP: yes… plus we don’t know how many of these SNPs are just life history or personality traits like C. stuff that farming selected for. most of them are related to g but a subset will also be related to conscientiousness. Emil et al in their Psych paper vetted their association with g in a sample though so I guess they must be genuine associations with IQ for the most part.
PP: Yes, because no one has given a huge sample (n = 1 million) of genotyped people a highly g loaded test. A perfect study would get a sample of 1 million people (from all over the world) and give them an extremely culture reduced test with many subtests to maximize g loading (i.e. block design, draw a person in the sand, name as many body parts as you can in 1 minute in your own language, pictorial oddities etc) and then enter the composite score, DNA and human development index of each person into a computer and have machine learning create a multiple regression equation predicting IQ using HDI & genomic variants as independent variables. By using such a diverse and global sample, one finds the genomic variants that correlate with IQ everywhere and thus are most likely to be causal.
PP: Now that the neanderthal genome has been published, why haven’t you tried to estimate their polygenic score? Richard Klein argues that before about 50 kya, modern humans and neanderthals had similar intellect, but suddenly around 50 kya there was a genetic brain change that allowed modern humans to leave Africa, colonize every continent, replace neanderthals & invent art & complex technology. Testing this hypothesis was the main motivation to sequence the neanderthal genome so there’s enormous interest in their intelligence, even in mainstream science.
DP: yes that’s the next step…we’re analyzing genomes from Bronze age now, but Neanderthal would be good. But funds are limited for this kind of research and I am not working in academia.
PP: Above you rejected Lynn’s population size mutation theory on the grounds that all races have all the known IQ related genomic variants, however it also seems you have no high coverage genomes from low population isolated groups like pygmies, bushmen, australoids, arctic people & pure Amerindians. Is it plausible that high coverage genomes of these groups would show they are missing some of the IQ enhancing mutations that appeared in the last 15,000 years?
DP: What I am saying is that you can see a difference even at the common SNPs in their frequencies. I cannot rule out that they are also missing these mutations but that would be an additional factor.
PP: Do you agree with John Hawks’s theory that positive selection in the last 5000 years has been a hundred times faster than in any other period of human evolution because of the explosion of new mutations & environmental change? This is the exact opposite of Gould who argued we have the same bodies and brains we’ve had 40,000 years ago and all subsequent change has been cultural not biological.
DP: from a purely theoretical point of view, yes, but one would need to study ancient genomes to empirically vet that hypothesis.
PP: Is there any strong evidence in support of Michael Woodley’s theory that white genomic IQ has declined by 10 or 15 IQ points since the Victorian era?
DP: I computed the decline based on the paper by Abdellaoui on British [Education Attainment] PGS and social stratification and it’s about 0.3 points per decade, so about 3 points over a century.
It’s not necessarily the case that IQ PGS declined more than the EA PGS..if anything, the latter was declining more because dysgenics on IQ is mainly via education so I think 3 points per century is a solid estimate
Thank you Davide Piffer for this interview. As mentioned above, you can find more of Davide’s thoughts on his blog.
Davide Piffer looked at 2,404 genomic variants found to predict education (a rough proxy for IQ) and used these to create polygenic scores of eight ethnic groups reared in First World conditions. He then compared the polygenic scores with the mean IQ of each group and found a 0.979 correlation.
The line of best fit allows us to predict the mean IQ of any group from their PGS (GWAS sig.):
Mean IQ = 9.31(PGS (GWAS sig.)) – 358
Given the 0.979 correlation, genotype predicts IQ remarkably well: Finnish 102, Ashkenazi 108, Southern Europe 99, Estonia 100, NW European 100, African American 83, Latino 95, East Asians 105.
So while our genomic predictions of IQ remain poor at the individual level, Piffer is showing we can predict the mean IQs of ethnic groups with incredible precision, at least when they’re all reared in similar countries.
Because we have only found a tiny fraction of the genetic variants associated with IQ (or its proxy education), the margin of error for predicting any one person’s IQ remains high. But when you try to predict the average IQ of an entire ethnic group, the overestimates and underestimates cancel each other out, and there’s a near perfect correlation between the mean polygenic score and the mean IQ.
A 2015 paper by Kate Cockcroft et al., compares the scores of 349 British middle class university undergrads to 107 lower class black South African undergrads on the WAIS-III (UK edition).
The results were as follows:
The UK students averaged a full-scale IQ of 106.95 (UK norms) while the South Africans averaged IQ 93.27. However because this study was published 18 years after the UK WAIS-III was published, we should adjust for the Flynn effect.
The single best source on recent Wechsler Flynn effects is Weiss et al., 2015 which found that full-scale IQ has been increasing by 0.31 points per year, at least in U.S. children. If we assume it’s the same for UK adults, then the UK students have an adjusted IQ of 101 and the South African students have an adjusted IQ of 88.
What’s more interesting to me is how they did on the culture reduced tests since that’s the more fair comparison.
Digit Span scaled score
Flynn adjusted Digit Span scaled score
Flynn adjusted Digit Span IQ equivalent
Block Design scaled score
Flynn adjusted Block Design scaled score
Flynn adjusted Block Design IQ equivalent
Compoite IQ based on adjusted scores on both tests
Black South African undergrads
So on a composite score of the most culture reduced spatial & non-spatial test (Block Design & Digit Span), Black South African undergrads average IQ 91. This is 11 points higher than the average Black South African seems to score on the same culture reduced tests.
As of 2013, only 16% of South Africa’s black young adults were attending higher education (compared to about 55% of whites, 47% of Indians and 14% of Coloureds). Thus, simply attending university puts one in the top 16% of this demographic, with the median South African university student being in the top 8%. If there were a perfect correlation between IQ and education, the median South African black university student would have an IQ 21 points higher than the average black South African. In reality his IQ is only 11 points higher, suggesting a correlation of 0.52 (at least on the most culture reduced tests).
This is similar to the 0.57 correlation between IQ and education observed in the United States.
Principal Component Analysis (PCA) is a mathematical technique by which many data points get reduced to a smaller number of more manageable data points.
Cavali-Sforza lumped humans into nine major populations. The following shows his phylogenetic tree of these nine populations followed by a matrix showing the genetic distance between them:
Because I wanted to see if these nine populations could be objectively reduced to a smaller number, I made all the distances negative and then entered the genetic distance matrix into a minitab spread sheet.
The reason I made the distances negative is because PC analysis is usually done on correlation matrices where the higher the value, the more similar. In a genetic distance matrix, it’s the opposite, hence the negative signs I added.
The principal component analysis gave the following result.
To determine how many principal components to retain, mathematicians use what’s called the eigenvalue > 1 rule, which in this case means only three components.
The first component explains 54% of genetic variation and since Northeast Asians have the highest loading on this component (0.432), it can be thought of as a measure of Northeast Asianness. Africans are the only group to load negatively on Northeast Asianness (-0.376).
The second component explains 26% of the variation and since Europeans have the highest loading on this (0.526), it can be considered a measure of whiteness.
The third component explains 12% of the variation and since Native Americans have the highest score on this (0.527) it can perhaps be considered a measure of “New Worldliness”.
Now when I plot each of the nine populations in three-dimensional space (x axis = Northeast Asianness, y axis = whiteness, z axis = New Worldliness) with their loadings multiplied by 10 to make differences visible, we find all of the nine populations fit into three major clusters.
These three clusters are extremely similar to the three major races of physical anthropology: Mongoloids on the back wall, Negroids on the side wall, and Caucasoids on the floor.
No disrespect to Caucasoids (I’m 100% pure Caucasoid myself). The graph can be reoriented so any group is on the floor.
One anomaly is that New Guineans & Australian aboriginals cluster with Mongoloids, even though they are morphologically closest to Negroid. Of course such anomolies are not uncommon in taxonomy. Birds for example genetically cluster with reptiles, even though they’re not reptiles. Humans cluster with apes, even though we’re not apes.
Such anomalies occur because most of our DNA is junk, so it groups us based on how recently we share common ancestors, not by how much of that common ancestor we shared.
The following chart (created by some scientist(s) led by David Reich) shows the genetic divergence between hominin samples as a fraction of the human-chimp difference. So for example, all the human groups have just over a 0.12 genetic divergence with Neanderthals, meaning that the genetic difference between humans and Neanderthals is only 12% as great as the genetic difference between humans and Chimps (source: supplement of Genetic history of an archaic hominin group from Denisova Cave in Siberia.)
The purpose of the chart is to estimate how long ago the different populations diverged from a common ancestor. So since the fossil record tells us that Neanderthals and chimps diverged about 6.5 million years, then humans and Neanderthals should have diverged roughly 0.8 million years ago (12% of 6.5 million) assuming genetic divergence maps to chronological divergence in a linear way.
I transformed the genetic distance matrix into a dendrogram, which looks at all the distances and creates the most parsimonious family tree:
What’s cool about dendrograms is they let you determine the number of categories and subcategories in a very objective way.
Of course dendrograms are only as good as the data you put into them, and I don’t endorse basing taxonomy simply on genetic relatedness, but if I did, here’s how I’d interpret the above tree:
The first major split is between chimps & everyone else. This is consistent with two well recognized genera of hominins : Pan (i.e. chimps) and Homo (humans and near-humans).
Now within the Homo genus, we see another major split in the tree. Anatomically Modern Humans (AMH) vs Archaic Humans. Thus we can divide the homo genus into at least two major species.
Within the Archaic Humans we can further subdivide into major races: Denisovans and Neanderthals.
Now within our own species, AMH, the dendrogram shows three major races: Capoids, Congoids and Non-Africans.
I’m not saying I agree with this taxonomy since it was only based on genetic distance (much of which is junk DNA) but what’s great about using dendrograms is almost everyone looking at them will assign groups to the same categories and subcategories, even if they don’t use the same words (race, species, genus) to describe them. It’s wholly objective.
But what is needed is a dendrogram based on polygenic scores of actual phenotypes. That way people who have the same phenotypes caused by the same genomic architecture could be grouped together.
Unlike the above dendrogram, which groups based on how recently we share a common ancestor, we need to group based on how much of the common ancestor we share.
[update may 26, 2019: an earlier version of this article misspelled dendrogram]
[2nd update may 26, 2019: an earlier version of this article contained bragging that has since been removed]
It’s common knowledge in psychometrics that U.S. whites average about one standard deviation (15 IQ points) higher than U.S. blacks and have done so since the first mass tests were administered in WWI.
But could the gap extend much further in space and time? Tens of thousands of years further.
At first it sounds absurd: there were no IQ tests 15,000 years ago, and there weren’t any white people. The earliest Europeans had dark skin, and they were largely replaced by Middle Easterners spreading agriculture.
Nonetheless, there were people living in Europe 15,000 years ago and to the degree they resemble today’s Europeans (phenotypically and genetically) they’re a proxy for archaic whites.
Similarly, the oldest lineage in Africa are Bushmen, and to the degree they resemble modern Africans, they’re a proxy for archaic blacks.
The archaic whites left the following rock art over 15,000 years ago.
The archaic blacks left the following rock art, perhaps much more recently.
When I asked readers to rate the two archaic white paintings using the quality scale of the Dale-Harris Draw-A-Man test, the median votes were 3 and 11, giving the archaic whites a mean score of 7.
For archaic blacks, the median votes were 3 and 8, giving archaic blacks a mean score of 5.5.
That’s a difference of 1.5 points. Since the standard deviation for incipient adults (age 15) on the Goodenough-Harris quality scale is 1.7, archaic whites over 15 thousand years ago were already nearly one standard deviation (15 IQ points) higher than archaic blacks living later.
Of course with such a tiny sample size, this conclusion is EXTREMELY tentative and requires far more research.
In the Minnesota Transracial Adoption study, white babies, black babies, and mixed babies (biological father black; biological mother white) were adopted into white upper middle-class homes when they were 19 months, 32 months, and nine months respectively. The purpose of the study was to determine how much of the 15 point black-white IQ gap in the United States is genetic.
In 1975, the children and adoptive parents were IQ tested on at least an abbreviated versions of the Stanford Binet/WISC/WAIS (depending on age), and then retested in 1986 on the WISC-R/WAIS-R depending on age. Here are the results:
Because the norms on all the tests were out-dated at the time of testing (especially in 1975), John Loehlin attempted to correct all scores for the Flynn effect.
But many people ignore the IQs themselves, and instead just focus on the IQ differences. They see that at age 17, adopted whites scored 7.1 points higher than adopted mixeds in the unadjusted data, and 16.2 points higher than the adopted blacks, and conclude that the 15 point black-white IQ gap in the United States is roughly 100% genetic.
One problem with this is that black babies were adopted later than the non-black babies. Another problem is they were born to black mothers, while the non-black babies were all born to white mothers, so the prenatal and perinatal environments may have been quite unequal.
Thus I have always been more intrigued by the 7.1 IQ gap between the adopted whites and adopted mixeds. Since the adopted mixeds presumably had only half as much black ancestry as the typical U.S. black, it’s interesting that there’s roughly half the infamous 15 point black-white IQ gap, despite being gestated in white wombs and raised in white homes. Does this point to the importance of genetics?
Physicist Drew Thomas argues that the comparison between the adopted whites and adopted blacks is misleading because in the tables posted above, at both ages we only see data for the adopted kids who remained in the study for the follow-up testing in 1986. He argues that several low IQ adopted white kids dropped out of the study, and had they remained, the IQ gap between the adopted whites and adopted mixeds would have perhaps been only 3.5 points at age 17.
However this argument is starting to feel a little post-hoc. When you do a study, your data is what it is. You can’t adjust it for what it would have been had people you wished remained in the study. Almost any study can be debunked if we imagine how it would have turned out in a parallel universe where different people took part.
That’s not to deny that adjusting for attrition can be important in some cases, but in this study, Thomas argues attrition only increased the IQs of adopted whites and not the adopted non-whites. An effect that only affected one demographic sounds to me like random error, not a systematic bias that needs to be adjusted for. And if the error was random, one could just as easily argue the IQs of adopted whites were too low before the attrition rather than too high after the attrition.
Indeed if the adopted white sample is so easily skewed by a few kids dropping out of the study, then maybe that sample is too small to begin with, and instead we should compare the much larger sample of adopted mixeds not to the adopted whites, but to the general U.S. white population.
At an average age of 17, the adopted mixeds took the WISC-R and WAIS-R depending on age, and averaged 98.5 (93.5 after adjustments for the Flynn effect, since WISC-R and WAIS-R norms were 14 and 8 years old respectively at the time of testing).
However some top-secret research I’ve been slowly doing over the past decade suggests the Flynn effect has been wildly exaggerated, so while I don’t think their average IQ was as high as 98.5, I also doubt it was as low as the Flynn corrections say. Let’s split the difference and say 96 (U.S. norms).
By contrast, the whites in the WISC-R and WAIS-R standardization samples averaged 102.2 (standard deviation (SD) = 14.08) and 101.4 (SD = 14.65) respectively. Let’s split the difference and say 101.8 (SD = 14.4).
Thus converting to the more traditional scale where the U.S. white mean and SD are set at 100 and 15 respectively, the adopted mixed mean of 96 becomes ((96 – 101.8)/14.4)(15) + 100 = 94.
In other words, despite being gestated in white wombs and raised in upper-middle class white homes, having just one U.S. black biological parent appears to have reduced IQ by 6 points, suggesting that having two U.S black biological parents would reduce IQ by 12 points, suggesting that 80% of the 15 point black-white IQ gap in the U.S. is genetic. 80% squared is 0.64 which is similar to the 0.69 heritability of the WAIS full-scale IQ found in Thomas Bouchard’s study of identical twins reared apart, consistent with Jensen’s default hypothesis which claimed that IQ gaps between U.S. races are caused by the same nature-nurture mix that occurs within them.
To paraphrase President Obama, there is no black America or white America; from a nature-nurture perspective, there’s just America.
While this analysis seems to have controlled for the prenatal and family environment, it’ does not control for peer groups. Maybe as mixed kids raised in white homes, they were unmotivated on IQ tests because of the racist stereotype that being smart = acting white. On the other hand, they did better on scholastic tests than they did on formal IQ tests, suggesting motivation was not a problem.
If the genetic part of the U.S. black-white IQ gap is indeed 12 points and black Americans are only about 74% black on average it implies that 100% West African ancestry would reduce IQ by 16 points below the U.S. white mean (at least if we assume U.S. black ancestry is representative of West African ancestry).
And at least if we assume the Phenotype = Genotype + Environment model
Some readers invoke a reaction norm model where genotype A is higher IQ than genotype B in environment A, but lower than genotype B in environment B. Assuming such norm crossing occurs with IQ, my sense is that it would be limited to individual cases and cancel out in group level comparisons like the black-white IQ gap.
Some might argue that it’s inappropriate to compare adopted mixeds to the general U.S. white population because adopted mixeds might not be genetically representative of their parent populations. In The g Factor, Jensen states that the parents of the mixeds averaged 12.5 years of schooling (page 473) while just the mothers averaged 12.4 (page 478). From here we can deduce that the fathers averaged 12.6.
In 1975 America, white women and non-white men age 25+ had a median of 12.3 and 11.3 years of schooling respectively (see table 4 of this document). Comparable figures in 1986 were 12.6 and 12.5. So using education as a proxy, there’s no reason to think the mixed kids were selected to have lower IQs than the mean of their parent races. If anything, their biological fathers averaged more education than age 25+ non-white men throughout the full duration of the study and their biological mothers averaged about the same education as age 25+ white women.
Of course it would help to know the exact ages of the parents, rather than just lumping them in with everyone over 25. I can’t find the age of the biological parents of the mixeds specifically, but the bio moms and dads of all the kids who took part in at least part of the study (see table 3 of this paper) averaged 21.6 and 26.3 at the time the kids were born, and thus were about 29 and 33 in 1975 and about 39 and 43 in 1986, thus they were likely near the median age of the 25+ cohort by the end of the study.
Although this study shows the black-white IQ gap is highly genetic, several similar studies beg to differ. Tizard (1974) compared black, white and mixed-race kids raised in English residential nurseries and found that the only significant IQ difference favored the non-white kids. A problem with this study is that the children were extremely young (below age 5) and ethnic differences in maturation rates favor black kids. A bigger problem with this study is that the parents of the black kids appeared to be immigrants (African or West Indian) and immigrants are often hyper-selected for IQ (see Indian Americans).
A second study by Eyferth (1961) found that the biological illegitimate children of white German women had a mean IQ of 97.2 if the biological father was was a white soldier and 96.5 if the biological father was a black soldier (a trivial difference). Both the white and mixed kids were raised by their biological white mothers. One problem with this study is that the biological fathers of both races would have been screened to have similar IQ’s because at the time, only the highest scoring 97% of whites and highest scoring 70% of blacks passed the Army General Classification Test and were allowed to be U.S. soldiers. In addition, 20% to 25% of the “black fathers” were not African-American or even black Africans, but rather French North Africans (non-white caucasoids or “dark whites” as they are sometimes called). In addition, there was no follow-up to measure the adult IQ of the children.
A third study by Moore (1986) included a section where he looked at sub-samples of children adopted by white parents. He found that nine adopted kids with two black biological parents averaged 2 IQ points higher than 14 adopted kids with only one biological black parent but the sample size was quite small, I don’t know anything about the bio-parents and again, no followup when the kids were older.
Because historically, craniometry and Social Darwinism were used to diminish women, blacks, and the lower classes, I have long found it incredibly inspirational that Oprah (a poor black girl from the rural South) grew up to rank so high on the two most Darwinian correlates of intelligence: brain size and money/power. And with the recent release of Forbes annual ranking of the 400 richest Americans, she is once again the only African American on the entire list, and with a net worth that briefly hit $3 billion, the first multibillionaire black in North American history. Don’t get me wrong, there have been two other black billionaires in North American history: BET founder Bob Johnson became a billionaire in 2001 when he sold BET though lost his Forbes billionaire status when a divorce reportedly split his fortune with wife Sheila Johnson and has almost never made the Forbes 400 since. Meanwhile here in Canada, we are all extremely proud of Michael Lee Chin who Forbes has ranked as a billionaire many times on their international rich list, though not lately. Although Lee Chin has two Chinese grandparents, he can be socially classified as black because his other grandparents are Jamaican. But neither Johnson or Lee Chin ever hit or exceeded the $3 billion mark on any of Forbes lists as Oprah just has. I figure $3 billion is the minimum net worth you need to be a multibillionaire. Dictionaries define a multimillionaire as someone having several million, so by extension, a multibillionaire is someone who has several billion.
If one excludes socially classified black billionaires, who are perhaps less than 50% sub-Saharan at the genetic level, Oprah was the only black billionaire on Earth from 2004 to 2006, in addition to being the most influential woman in the world according to Time magazine. However with rising oil prices, black billionaires and even multibillionaires have been emerging in Africa, so Oprah is no longer richest black black on Earth (even when “black” is defined narrowly).
The blogger destructure recently implied on this blog that I am too liberal, which he attributed to my putative sheltered life as a Canadian. I don’t consider myself liberal at all, but I think I seem so liberal because my path to HBD (i.e. behavioral genetics) was very different from that of many HBD people. I would imagine that many people get interested in HBD because they have certain right-wing politics (maybe anti-affirmative action, anti-immigration) and hijack HBD to push their political agenda, much like the peaceful religion of Islam is hijacked by violent extremists pushing agendas. In both cases, a burden is placed on all the millions good HBD people (and millions of good Muslims) to defend their ideology from those who would want to twist it.
For me, HBD was never about politics, but started when a babysitter rented the movie Quest for Fire when I was five. This movie was set 80,000 years ago and depicted a tribe of cavemen who have their most valued resource (fire) destroyed by a violent tribe of primitive monkey-men who brutally slaughter most of the cavemen. Amazingly, a few of the most adventurous surviving cavemen walk from Europe to sub-Saharan Africa where they find a tribe of behaviorally and anatomically modern gracile humans, one of whom was a beautiful young African woman, who falls in love with one of the cavemen and teaches him to be fully human. Til this day this remains one of my all time favorite movies and makes me nostalgic for life 80,000 years ago.
But at age five, this wasn’t just a movie, it was an obsession. Every time I would go camping, I would look for a pile of ashes to roll around in, because the advanced African tribe I worshiped were covered from head to toe in ashes giving them a completely grey skin color.
The advanced Africans colored grey by ashes make fun of less advanced caveman for falling into their trap. Image found here
As a child I remembered thinking how boring life was in the modern era because all living human populations were at the same level of evolution. Things seemed so much more exciting 80,000 years ago in the movie Quest for Fire when you had three different levels of evolution competing in a struggle for survival.
But then I began hearing about the theories of scientists J.P. Rushton who argued that there were indeed three different levels of evolution coexisting at once, except instead of Africans being the most advanced people, Rushton put “mongoloids” at the top of his nice neat pyramid, arguing that they were more advanced than other humans because they evolved most recently, having split-off caucasoids in a bigger brained, less sexual form. When I first heard this theory I was absolutely fascinated because it was as though the movie that had dominated my early childhood had been true all along, but because Rushton’s theory was condemned as racist, I felt great shame and guilt for liking his theory so much.
Luckily, as I grew older, I came to realize there was absolutely nothing racist about such theories because virtually the entire range of intelligence, personality, sexuality, and athleticism exist in every race, and there’s an evolutionary trade-off, such that races that are higher in some traits (brain size, IQ, mental stability) are lower on other valued traits (sexual anatomy, rhythm, sociability, artistic creativity). I don’t think one should have to deny science to prove they’re not a racist. It’s very easy to spout politically correct platitudes about all races being the same in the abstract; but the real test of character is whether you treat everyone as an individual, regardless of race.