What you don't know can hurt you

In 1972, the U.S. passed the Clean Water Act, despite a presidential veto by Richard Nixon. Did this act also end an era of unusually high estrogen levels in the environment? (cartoon source)

There has been much concern over the presence of “environmental estrogens” in our drinking water and elsewhere in the environment. These are man-made chemicals, like DDT, PCBs, and dioxins, that mimic the effect of natural estrogens. Among other things, they’re blamed for declining sperm counts and rising male infertility.

Yet estrogen also enters our environment from a source that excites much less concern. This is the estrogen that women excrete every day in their urine. Shouldn’t that source also be cause for worry?

At first thought, no. People have been urinating for a very long time. And other animals for even longer. During that time, microorganisms have evolved to break down and feed on whatever is present in urine. Larger organisms have likewise had plenty of time to adapt to this aspect of their environment. Urine is so ubiquitous and unchanging that it could not possibly pose a danger. Or could it?

Actually, two things have changed in recent times. One is that humans have become much more numerous, with the result that much more urine is being discharged into the environment. Another is the way it is discharged.

Before the late 19th century, urine entered the environment via privies, cesspools, and ditch sewers (Rockefeller, 1996). It was thus discharged into a warm stagnant medium rich in organic matter—ideal conditions for rapid breakdown of the estrogen molecule by nitrifying bacteria (Vader et al., 2000). These same conditions, however, increasingly became a threat to public health, particularly in the ever larger and more numerous urban centers.

And so a new disposal system was developed. Human waste was now expedited via sewers to a central facility where the liquid component would be separated and rapidly discharged into the nearest cold body of water—which often doubled as the city’s source of drinking water. It was a perfect system for discharging urinary estrogen into the environment with as little biodegradation as possible … and then bringing it back into the human organism. As for urinary androgen, it was also present in wastewater but at much lower levels because of its lower solubility in water (Tabak et al., 1981).

That system survived until the late 1960s and early 1970s, when concern about pollution brought an upgrading of almost all sewage treatment facilities. If we look at the total number of Americans who produce untreated wastewater, this number peaked at 70 million in 1960 before falling to 2 million after passage of the Clean Water Act in 1972 (Copeland, 1993; US Council on Environment Quality, 1984). Primary treatment removes 35‑55% of estrogen from wastewater, and this proportion rises to 50‑70% for secondary treatment (Tabak et al., 1981). Today, tertiary treatment removes 90% of all natural and synthetic estrogenic compounds (LeQuire, 1999).

But what about the 100-year period when most wastewater went untreated? During that time, the main sources of drinking water must have been highly contaminated with estrogen. What were the effects? The most obvious ones would have been a decline in sperm counts and a rise in male infertility. But were there others? And should we soon see a reversal of these trends?

I tried to publish a paper on this subject, but the reviewers were skeptical. I was indulging in speculation that could never be proved one way or another. There simply are no records of estrogen levels in the environment for the period in question.

So I published my speculations on my blog (here, here, and here) and let the matter lie … while keeping an eye on the literature. Recently, three findings have come to my attention:

Primary treatment less effective than previously thought

A recent paper confirms that tertiary treatment of wastewater removes over 90% of all estrogen. On the other hand, primary treatment is less effective than previously thought, the removal rate being only 10% (Limpiyakorn et al., 2011).

Estrogen content of wastewater higher than previously thought

In the past, estrogen levels were measured only for the three most common kinds of estrogen: estrone (E1), estradiol (E2), and estriol (E3). Other natural estrogens, however, are present in urine. The total estrogen level in wastewater is thus 18-34% higher than previously thought:

[…] the total excretion rates of EEQ [estrogen equivalent] by estrone (E1), 17β-estradiol (E2), and estriol (E3) only accounted for 66–82% of the total excretion rate of EEQ among four different groups, and the other corresponding natural estrogens contributed 18–34%, which meant that some of the other natural estrogens may also exist in wastewater with high estrogenic activities. (Liu et al., 2009)

River and ocean sediments reveal formerly high estrogen levels in the environment

It is possible to look into the past by taking cores of sediments from the bottoms of lakes, rivers, and coastal waters. A study of the River Thames has found that estrogen levels are higher in river sediments deposited before the 1960s:

There is an indication of higher concentrations of E1 and E3 in samples deemed to be deposited before the mid-1960s, prior to the introduction of biological treatment at STWs [sewage treatment works] discharging to the estuary. […] This provides indirect evidence that historical improvements to wastewater treatment have resulted in a decrease in the concentrations of steroids in the effluent, as observed for PCBs and DDT from the same core (Gomes et al., 2011)

A similar finding comes from a study of sediment cores from Japanese coastal areas:

The concentration of natural estrogens such as 17β-estradiol (E2) and estrone (E1) in the sediment of coastal areas in Japan was determined […] Core samples were sliced every 2cm from the surface to 20cm deep for the measurement of estrogen. Although the concentrations of estrogens decreased with the depth of core samples, fairly high levels of estrogens were again noticed at the layer deeper than 16cm. (Matsuoka et al., 2005)

Conclusion

The most promising line of research seems to be the use of sediment cores to estimate past levels of estrogen in the environment. One problem will be calibration of sediment dating. Gomes et al. (2011) have pointed to a possible solution by noting that the mid-1960s correspond to the first sediment layer that contains synthetic estrogen, i.e., from birth control pills. Another problem is that estrogen seems to degrade gradually over time, even in river or ocean sediments.

References

Copeland, C. (1993). Wastewater Treatment: Overview and Background [93-138 ENR] Washington, D.C.: Congressional Research Service.

Frost, P. (2009). The urinary estrogen theory. Part I, Evo and Proud, March 11

http://evoandproud.blogspot.ca/2009/03/urinary-estrogen-theory-part-i.html

Frost, P. (2009). The urinary estrogen theory. Part II, Evo and Proud, March 18

http://evoandproud.blogspot.ca/2009/03/urinary-estrogen-theory-part-ii.html

Frost, P. (2009). The urinary estrogen theory. Part III, Evo and Proud, March 26

http://evoandproud.blogspot.ca/2009/03/urinary-estrogen-theory-part-iii.html

Gomes, R.L., M.D. Scrimshaw, E. Cartmell, & J.N. Lester.  (2011). The fate of steroid estrogens: partitioning during wastewater treatment and onto river sediments, Environmental Monitoring and Assessment, 175, 431–441.

http://www.springerlink.com/content/052274881l4186g5/

LeQuire, E. (1999). Something in the Water. InSites, 7(1),

http://eerc.ra.utk.edu/insites/ins7-1.htm#Something

Limpiyakorn, T., S. Homklin, & S.K. Ong. (2011). Fate of estrogens and estrogenic potentials in sewerage systems, Critical Reviews in Environmental Science and Technology, 41(13), 1231-1270.

Liu, Z., Y. Kanjo, S. Mizutani. (2009). Urinary excretion rates of natural estrogens and androgens from humans, and their occurrence and fate in the environment: A review, Science of the Total Environment, 407, 4975–4985

Matsuoka, S., R. Sakakura, M. Takiishi, Y. Kurokawa, S. Kawai, & N. Miyazaki. (2005). Determination of natural estrogens in the sediment of coastal area in Japan, Coastal Marine Science, 29(2), 141-146.

http://repository.dl.itc.u-tokyo.ac.jp/dspace/handle/2261/5593

Rockefeller, A.A. (1996). Civilization and sludge: Notes on the history of the management of human excreta. Current World Leaders, 39, 99‑113.

Tabak, H.H., R.N. Bloomhuff, & R.L. Bunch. (1981). Steroid hormones as water pollutants II. Studies on the persistence and stability of natural urinary and synthetic ovulation‑inhibiting hormones in untreated and treated wastewaters. Developments in Industrial Microbiology, 22, 497‑519.

U.S. Council on Environment Quality. (1984). Annual Report. Washington D.C.

Vader, J.S., C.G. van Ginkel, F.M.G.M. Sperling, J. de Jong, W. de Boer, J.S. de Graaf, M. van der Most, & P.G.W. Stokman. (2000). Degradation of ethinyl estradiol by nitrifying activated sludge. Chemosphere, 41, 1239‑1243. 

Too darn hot?

Does higher IQ correlate with colder temperatures? Not among people belonging to the same cultural system, such as the Chinese. (source)

Big brains are costly, not only because of their high energy consumption but also because many genes have to interact to create neural tissue. The bigger and more complex the brain, the more it is vulnerable to accidents at the gene level, like random mutations.

Mutations happen more often at warmer temperatures. In Drosophila, an increase of 10ºC will double or triple the mutation rate. Tight underwear has probably done more to harm the human genome than fallout from nuclear testing (Sutton, 1975, p. 318).

Drawing on these two points, Greg Cochran is now suggesting that large human brains are a precarious outcome of evolution (here and here). However strong the natural selection may be for a bigger brain, the mutation rate is pushing back in the opposite direction. Beyond a certain size, big brains are possible only where the mutation rate is relatively low—in cooler regions at higher latitudes.

This is a seductive way of explaining why brain size correlates with latitude. And, yes, such a correlation does exist. So thought most 19th-century physical anthropologists, notably Samuel George Morton, but Stephen J. Gould (1978) concluded otherwise after a reanalysis of Morton’s data that became the centerpiece of his book The Mismeasure of Man. A team of physical anthropologists has since located and remeasured Morton’s skulls. Their conclusion? The original measurements had few errors, and the errors were distributed randomly. There was, in fact, a non-significant tendency by Morton to overestimate African skull size (Lewis et al., 2011).

Brain size and latitude also seem to correlate among ancestral hominids from A. Afarensis to H. sapiens (Henneberg & Miguel, 2004). The correlation remains even if time period is controlled. It thus cannot be due to the overall rise in cranial capacity over time and the parallel expansion of ancestral hominids into higher latitudes.

Is this correlation adequately explained by the ‘Too Darn Hot’ theory? The main supporting evidence is the finding that ‘loss of function’ mutations are much more common in sub-Saharan Africans than in other humans (MacArthur & Tyler-Smith, 2010; Tennessen et al., 2012). Natural selection seems to have more trouble weeding them out in the tropics than elsewhere.

But do these mutations need to be weeded out? Are they in fact deleterious? Some authors think so. Most don’t, including the ones of a study that Greg cites:

[…] the implicit assumption that LOF variants (and indeed other changes predicted to be damaging to the protein) are necessarily deleterious to human health is a dangerous one, especially when such an assumption is used to infer disease causality for a novel variant. In fact, the studies reviewed above demonstrate that healthy humans carry many dozens of LOF variants, most of which have little or no effect on health (at least in the heterozygous state). (MacArthur & Tyler-Smith, 2010)

In general, these mutations seem to involve genes of very low selective value, so they could very well hang around indefinitely if natural selection against them is weak enough and if the population is large enough.

Here we come to the usual explanation for Africa’s large number of ‘loss of function’ mutations. There are so many of them because Africans have largely stayed put in the same place with the same population base. In contrast, non-Africans are descended from small founder groups that took only a small portion of this junk variability on their way out of Africa:

The gene-diversity results presented here are consistent with one another and with those of many previous studies in showing higher levels of diversity in African populations than in non-African populations […] A higher level of African diversity supports the hypothesis that modern humans first arose in Africa and then colonized other parts of the world (Stoneking 1993), but genetic diversity is related not just to a population’s “age” but also to demographic events in a population’s history, such as bottlenecks and effective population size. (Jorde et al., 2000)

Alternate theories

Do we have other theories for latitudinal variation in brain size? To date, there seem to be three:

Need to reduce heat loss at higher latitudes

According to Beals, Smith & Dodd (1984), heads have grown larger at higher latitudes as a way to reduce heat loss. An object will lose less heat if it has a high ratio of volume to surface area. Natural selection has thus favored more globular heads at higher latitudes. The increase in brain size is thus incidental.

This explanation was challenged in the comments section of the above paper. Iwatoro Morimoto pointed out that "in recent centuries, brachycranic skulls show a considerable increase in frequency in Eurasian populations, including the Japanese." Since mean temperatures have changed little in recent centuries, there must have been another factor at work.

Another commenter, Erik Trinkaus, similarly pointed out that Neanderthal cranial capacity was no bigger during glacial periods than during interglacials. The same was true for early modern humans. For populations already established at northern latitudes, cranial capacity shows no evidence of rising and falling with mean temperature.

Finally, if the increase in brain size was driven by the need for a more globular head, that goal can be met by filling the extra head space with non-neural tissue, like bone or cartilage. Neural tissue has a high maintenance cost. Why maintain something at great expense if you don’t really need it?

Increase in visual cortex at higher latitudes

Pearce and Dunbar (2011) argue that bigger brains are an adaptation to lower levels of ambient light. Specifically, dimmer light requires larger eyes, which in turn require larger visual cortices in the brain. Using 73 adult crania from populations located at different latitudes, the two authors found that both eyeball size and brain size correlate positively with latitude. The correlation was stronger with eyeball size, an indication that this factor was driving the increase in brain size.

How credible is this explanation? First, visual cortex size was not directly measured. The authors inferred that this brain area was responsible for the increase in total cranial capacity. Of course they couldn’t have done otherwise. They were measuring skulls, not intact brains.

To date, the best map of human variation in brain size is by Beals et al. (1984). If dimness of light is the main determinant, brain size should be highest in northwestern Europe, northern British Columbia, the Alaskan panhandle, and western Greenland. These regions combine high latitudes with generally overcast skies. Yet they are not the regions where humans have the biggest brains. Instead, brains are biggest among humans from the northern fringe of Arctic Asia and from northeastern Arctic Canada. These regions are, if anything, less overcast than average. They often have high levels of ambient light because of reflection from snow and ice.

Increase in cognitive demands at higher latitudes

Finally, brain size may have increased at higher latitudes because of an increase in cognitive tasks, specifically foresight. As ancestral humans spread out of the tropics and into latitudes with a predictable summer/winter cycle, it became much more advantageous to simulate the future consequences of present actions.

This point is discussed by Hoffecker (2002, p. 135). Among early modern humans, tools and weapons were more complex at arctic latitudes than at tropical latitudes. “Technological complexity in colder environments seems to reflect the need for greater foraging efficiency in settings where many resources are available only for limited periods of time.” Arctic humans planned ahead to cope with resource fluctuations and high mobility requirements, such as by developing untended devices (e.g., traps and snares) and means of food storage.

Colder environments imposed even higher cognitive demands when hunting and gathering gave way to agriculture. Food had to be grown not only for present needs but also for the next cold season. As late as the 18th century, farm families often faced starvation in early spring—when their winter provisions had run out and their spring crop had not yet come in.

The yearly cycle and the need to plan ahead thus preadapted early non-tropical humans for later cultural developments, such as invention of writing and bookkeeping, complexification of social relations, creation of towns and cities, systems of military defense, roads and highways, etc. At that point, cognitive demands were no longer driven by the yearly cycle, at least not primarily. They were now being driven by an increasingly complex cultural environment—what we call ‘civilization.’

Conclusion

How does the ‘Too Darn Hot’ theory stack up against these alternate theories? The main contender seems to be the last one, i.e., the increase in cognitive demands at higher latitudes. According to that theory, the yearly cycle has given way to gene-culture co-evolution as the main driving force behind increases in intellectual capacity.

Thus, if people live within the same cultural system and are exposed to similar cognitive demands, they should on average have the same intellectual capacity … regardless of the mean temperature of their particular locality.

Conversely, the ‘Too Darn Hot’ theory would predict the existence of a north-south cline in IQ even among people of a similar cultural background, since people at more tropical latitudes should have a higher incidence of deleterious mutations.

China, for example, covers a wide range of latitudes from the sub-Arctic to the tropics. Although the Chinese have occupied this latitudinal range for some 2,500 years, i.e., about 100 generations, their mean IQ doesn’t seem to vary along a north-south cline (see above map).

Perhaps 100 generations isn’t long enough. But what about the Amerindians? They’ve inhabited a full range of latitudes from the Arctic to the equator for some 12 to 15 thousand years. That’s 480 to 600 generations. Is there a difference in mean IQ between the Naskapi of northern Labrador and the Yanomamo of Amazonia? I’d be surprised.

References

Anon. (2011). IQ geography in China, November 19, The Slitty Eye,

http://theslittyeye.wordpress.com/2011/11/19/iq-geography-in-china/

Beals, K.L., C.L. Smith, and S.M. Dodd (1984). Brain size, cranial morphology, climate, and time machines, Current Anthropology, 25, 301–330.

Cochran, G. (2012). Changes in attitudes, West Hunter, July 18

http://westhunt.wordpress.com/2012/07/18/changes-in-attitudes/

Cochran, G. (2012). Too darn hot? West Hunter, July 14

http://westhunt.wordpress.com/2012/07/14/too-darn-hot/

Gould S.J. (1981). The Mismeasure of Man. New York: W. W. Norton and Company.

Gould , S.J. (1978). Morton’s ranking of races by cranial capacity: unconscious manipulation of data may be a scientific norm, Science, 200, 503–509.

Henneberg, M. and C. de Miguel. (2004). Hominins are a single lineage: brain and body size variability does not reflect postulated taxonomic diversity of hominins, Journal of Comparative Human Biology, 55, 21–37

Hoffecker, J.F. (2002). Desolate Landscapes. Ice-Age Settlement in Eastern Europe. New Brunswick: Rutgers University Press.

Jorde, L.B., W.S. Watkins, M.J. Bamshad, M.E. Dixon, C.E. Ricker, M.T. Seielstad, & M.A. Batzer. (2000). The distribution of human genetic diversity: a comparison of mitochondrial, autosomal, and Y-chromosome data, American Journal of Human Genetics, 66, 979–988.

Lewis, J.E., D. DeGusta, M.R. Meyer, J.M. Monge, A.E. Mann, R.L. Holloway. (2011). The Mismeasure of Science: Stephen Jay Gould versus Samuel George Morton on Skulls and Bias, PLoS Biology, 9(6) e1001071

MacArthur, D.G., & C. Tyler-Smith. (2010). Loss-of-function variants in the genomes of healthy humans, Human Molecular Genetics, 19, R125-R130.

Pearce, E. and R. Dunbar. (2011). Latitudinal variation in light levels drives human visual system size, Biology Letters, doi: 10.1098/rsbl.2011.0570

Sutton, H.E. (1975). An Introduction to Human Genetics, New York: Holt, Rinehart and Winston.

Tennessen, J.A., A.W. Bigham, T.D. O’Connor, W. Fu, E.E Kenny, et al. (2012). Evolution and functional impact of rare coding variation from deep sequencing of human exomes, Science, 337, 64-69.

More on Race, IQ, and Wealth

Cover page of American Conservative, a megaphone for dubious science? (source)

My comments on Ron Unz’s article “Race, IQ, and Wealth” have led to further exchanges between myself and Ron. There seem to be two sticking points:

1. Ron is more like a military strategist than an academic. In other words, the goal is already decided on, and all that remains is to work out the best strategy for reaching that goal. For him, the optimal strategy is to find the weakest point in the enemy’s defenses and to hammer away at it relentlessly. Once that soft spot is breached, the entire defense line will collapse.

2. Ron sees only “perfect” evidence and “imperfect” evidence (which must be discarded).  This may be just naiveté on his part. Actually, there is no such thing as perfect evidence. There is only evidence with varying degrees of imperfection, and a good academic should view all data with a wary eye, even "Gold Standard" stuff. By the same token, one should not dismiss data that have a high degree of “noise,” unless a better dataset is available.  Such evidence is still useful for picking out general trends and formulating hypotheses for further study.

The following is our exchange of views:

Ron Unz here,

Let me focus upon a single experimental datapoint, of which there actually exist a considerable number. Lynn provides three Irish IQ samples: a 1972 sample of 3,466 yielding an IQ of 87, a 1993 sample of 1,361 yielding an IQ of 93, and another 1993 sample of 2,029 yielding an IQ of 91. These are all very large samples. There is also another minuscule 1979 sample of 75 which (unsurprisingly) yields an outlying value. All these results are Flynn-adjusted by Lynn.

[…] However, in America Irish these days have IQs slightly above the white average, and in Europe the recent PISA scores for Ireland are also right around those for Germany, France, and Britain.

Now my hypothesis is that the huge recent rise in Irish IQs is probably due to changes in urbanization and socio-economic factors. But perhaps I'm entirely wrong. So, then, what is the alternate hypothesis explaining these wildly different Irish IQ scores across  just a 35 year period?

[Answer to question about how one defines “American Irish” ]

Being "Irish" is based on self-identification and reporting, so I'd certainly expect that most of the "American Irish" aren't "pure Irish."

But none of that makes a difference. If the Irish had an actual, innate, genetic IQ of 87, and this figure was not subject to rapid change under socio-economic influences, there would be *massive* evidence of this in American society.

For example, something like 15% of all the Irish in America would have IQs below 70, and would be subject to clinical mental retardation. Do you really believe that 15% of all American Irish are mentally retarded?

Okay, maybe lots of those Irish aren't pure Irish, and are part German or Italian or something. Well, according to Lynn the (South) Italian IQ is around 89, so that wouldn't really help much. But anyway, we'd still be seeing millions of mentally-retarded Irish-Americans. Do you believe that?

Here's another point. During the 1970s, the Wordsum-IQ gap between rural whites and urban/suburban whites was almost exactly the same as the black/white gap. Again, that implies that something like 10% of all white farmboys during the 1970s were mentally retarded. Do you really believe that?

Finally, as I've pointed out, between the 1980s and the 2000s, roughly 61% of the Wordsum-IQ gap between white Americans and American-born Mex-Ams disappeared due to an enormous rise in the Wordsum-IQ of the latter group. These are hard, empirical facts. Perhaps my explanation is entirely wrong. But what is your alternate explanation?

Ron,

You're pointing at weak evidence as a way to undermine strong evidence. A single IQ test, even with a large sample, is at best a rough indication. The main problem is sample bias. Is the sample truly representative? If the sample comes from a school classroom, you have the problem of absenteeism. Truants tend to be problem students, so the higher the rate of absenteeism, the higher will be the IQ score.

Even if the sample is representative, there are other sources of bias: the amount of coaching for the test and the way the test is presented. These sources of bias may cancel each other out. Or maybe not. One thing is sure: they increase the amount of noise in the data. In your case, you had three data points: 87, 91, and 93. You focused on the lowest of the three figures. How come? Why not take an average? Even then, I would still be skeptical.

I am even more skeptical of your recent data on "Irish Americans." There is no such population. There are simply a lot of people with varying amounts of Irish ancestry. "Irish Americans" are increasingly people who take an interest in Irish music, culture, and history, and such people tend to be more educated than average. Another factor is that people tend to identify with the branch of their family tree that has a stronger sense of ethnic identity. If a person is part English and part Irish, they tend to identify as Irish. But if a person has equal contributions of African and Irish ancestry (like Mariah Carey), they tend to identify as African American.

Finally, Wordsum is not IQ. It has a correlation of 71% with standard IQ tests, which in turn have a correlation of 50 to 75% with innate intelligence. So we are already two steps removed from any genetically transmitted factors.

This is a recurring problem with your line of argument. You present "A" and try to pass it off as "B", hoping that no one will notice the difference.

Ron Unz here:

Don't be ridiculous, Peter. Please do read my arguments more carefully.

(1) The PISA tests are very widely regarded as one of the best current means of estimating the IQs of European countries, certainly by my sharpest critics. If you look at the PISA scores for Ireland, they are almost exactly the same as those for Britain, Norway, Denmark, France, Sweden, and several other European countries. That almost certainly implies that Ireland's current IQ is quite close to 100.

Now an enormous IQ sample provided by Lynn placed Ireland's 1972 IQ at just 87, and Lynn has explicitly confirmed this by stating that his years of late 1960s personal research in Ireland convinced him that the Irish were a low-IQ people, whose only hope lay in a heavy eugenics program. So unless a huge sample and Lynn are both wrong, this is probably correct.

Therefore, some unknown factor—I strongly suspect urbanization—apparently caused a massive rise in Irish IQ between 1972 and today. Further evidence for this rise is shown by the fact that at the half-way point—the early 1990s—two additional huge IQ tests provided by Lynn placed the Irish IQ at around 92, exactly half-way between those two endpoint values.

Bear in mind, that all of these Irish results are about as "Gold Standard" as you can find anywhere—huge IQ samples, Lynn's years of personal research, and PISA. None of it has anything to do with partial Irish ancestry or Wordsum. But the fact that these Ireland Irish results are totally consistent with the separate Irish-American Wordsum results certainly doesn't weaken my case.

(2) Here's another example: Poland. The 1989 Polish IQ results quoted by Lynn are based on the largest sample he's found anywhere, over 4000 individuals. The Flynn-adjusted Polish IQ was 92. Yet just 20 years later, Poland had precisely the same PISA scores as Britain, France, Norway, Sweden, etc, all which Lynn claims have IQs of around 100. How do you explain this?

(3) Essentially, your perspective seems to be that we should just throw away all the Lynn/Vanhanen IQ tests which you don't like---many of which tend to be the largest ones---and keep the ones you do. Or perhaps you're just suggesting we should bite the bullet and throw away ALL of the Lynn/Vanhanen data, and therefore base all our estimates of European IQs on "personal intuition." If that's not what you're saying, please do clarify.

Ron,

A PISA test suffers from the same problem I pointed out earlier. It's based  on students in a classroom. It excludes those students who weren't around on the day of the test. I'm not talking about a small proportion of the youth population either.

And a PISA test is not an IQ test. Like WordSum, its results correlate with those of IQ tests, which in turn correlate with genetic factors that influence human intelligence. Again, you're trying to pass off "C" as "A" by using the argument that C correlates with B and B correlates with A.

The IQ data compiled by Lynn provide weak evidence for heritability of IQ.  There is a lot of noise in that kind of data.  And much of that noise will not be squeezed out by large sample sizes. If there is a bias in participant recruitment, that bias will distort a big sample as surely as it will distort a small one.

With respect to the Polish data, we have the same phenomenon that we see with the East German data. IQ scores were lower during the Communist era than they are today. The most likely explanatory factor is truancy. It is much easier for problem students to skip classes today than it was back then. During the communist era, truants were sent to detention centres that were little more than prisons. No one wanted to go to those places. If you were a pretty boy, you would have to become a "wife" for one of the alpha males.

You ask me:

Your perspective seems to be that we should just throw away all the Lynn/Vanhanen IQ tests which you don't like---many of which tend to be the largest ones---and keep the ones you do. Or perhaps you're just suggesting we should bite the bullet and throw away ALL of the Lynn/Vanhanen data, and therefore base all our estimates of European IQs on "personal intuition." If that's not what you're saying, please do clarify.

Gladly. Lynn's IQ data are useful for picking out general trends that should be confirmed by more controlled studies. Unlike certain people, I don't ignore evidence that doesn't fit my preconceived ideas. I try to explain it as best I can, or I simply describe it as an unresolved problem.

As I said earlier, I view Lynn's work with some caution. This doesn't mean I reject it out of hand. Nor do I accept it uncritically. I do the sort of things that most academics do. I check the sources, I look at related studies by other authors, and I examine the data from as many angles as possible.

Ron Unz here:

Look, Peter. I don't claim to be an IQ expert. I'm just someone who looks at the data reported by the people who supposedly ARE IQ experts and then applies a little common sense and pattern-recognition.

Everyone seems to say that Lynn is one of the biggest IQ experts, and his book is filled with IQ studies.  Perhaps the ones with tiny sample sizes shouldn't be taken seriously, but the Irish and Polish ones are among the *largest* studies he reports.  If I can't believe any of his large IQ studies, or what he concluded from his years of personal research in Ireland, then maybe I should just throw away all his books and say that IQ obviously doesn't exist.

Well, you say I shouldn't trust any of Lynn's IQ studies.  Fine, so then I'll look at the Wordsum-IQ data from the GSS.  But then you say I shouldn't use Wordsum, because it's not really IQ, just (supposedly) has a 0.71 correlation with IQ.  Everyone else discussing IQ tends to use Wordsum as a rough proxy, but you say I shouldn't.

Okay, then maybe I'll use the international PISA results. Volkmar Weiss, who's supposedly another very big IQ expert, wrote a whole article in which he discussed PISA scores as useful proxies for IQ:

http://www.v-weiss.de/calibration.html

But you say I shouldn't use PISA.

So now I can't use Lynn's IQ studies, I can't use Wordsum in the U.S., and I can't use PISA worldwide.  Then what's left?  Suppose I ask you the simple question "What's the estimated IQ of Ireland?"---how would YOU figure out the answer...

Ron,

I would answer: "I don't know." I would also point out that none of the existing data on Irish IQ involve twin or adoption studies. All we have is data from classroom IQ tests and more distal sources like PISA. The existing evidence is nonetheless interesting and I would like to see more controlled studies done.

In any argument, there will always be weaker evidence and stronger evidence. A common debating tactic is to focus on the weaker evidence and create the impression that it is somehow central to the entire argument. With enough hand-waving, one might win the debate. This was, in fact, your line of attack in the American Conservative article:

Yet an objective review of the Lynn/Vanhanen data almost completely discredit the Lynn/Vanhanen "Strong IQ Hypothesis." If so many genetically-indistinguishable European populations—of roughly similar cultural and historical background and without severe nutritional difficulties—can display such huge variances in tested IQ across different decades and locations, we should be extremely cautious about assuming that other ethnic IQ differences are innate rather than environmental, especially since these may involve populations separated by far wider cultural or nutritional gaps.

In my opinion, this kind of debating strategy is unworthy of you. We're not here to engage in courtroom theatrics. We're here to find out the truth.

Reference

Unz, R. (2012). Race, IQ, and Wealth, The American Conservative, July 18. http://www.theamericanconservative.com/articles/race-iq-and-wealth/

Ron Unz on Race, IQ, and Wealth

Former juvenile detention center in Torgau, East Germany. Was truancy treated the same way in West Germany and the DDR? (source)

Ron Unz has come out with an article on “Race, IQ, and Wealth” in the latest issue of the American Conservative. He had earlier sent me a draft copy and asked for my comments. I did as best I could, not considering myself to be an authority on IQ.

Reading through the published article, I can see that very little was modified. The only real change was that he toned down his anti-Gould rhetoric at the beginning of the article. In general, the introduction seemed to be written in such a way as to “hook” HBD-oriented readers and get them to read the whole thing. Judging by the comments at iSteve, his strategy worked …

While I don’t disclose criticisms of unpublished drafts, I feel free to criticize the published versions. The following text is the one I had sent Ron, minus my comments on certain words and sentences he later removed. The quotes from his article have also been updated to reflect the article as actually published.

If I could rewrite this text, I would point out more clearly that the IQ difference between West Germany and East Germany probably reflected differences in truancy. The more leniently a school treats absenteeism the higher it will score on IQ tests, since the truants tend to be problem students. But the higher IQ score is illusory.

I would also add that IQ may indeed differ between European countries. The existing data, however, are compromised by problems of comparability. Europeans are separated not only by national boundaries but also by different political systems. These differences create differences in sampling bias, in ways of conducting IQ tests, and even in the test itself.

Comments on “Race, IQ, and Wealth”

When I read the first two pages of your article, I got the impression you were trying to get on the good side of HBD readers, as if you wanted to be treated as “one of us” and not “one of them.” If so, you’re overdoing it. Why not forget the reader and concentrate on presenting your argument to a naïve version of yourself?

Your main argument

Your main point is that the variability in European IQ over time and space suggests that most of this variation is environmental in origin and not genetic. By extension, this point casts doubt on the genetic origin of larger-scale IQ difference, particularly those between White Americans, on the one hand, and Black and Hispanic Americans, on the other.

This argument is hard to reconcile with the evidence from twins and/or adopted children. In the Minnesota Transracial Adoption Study, for instance, racial differences in IQ remained unchanged even within a shared family environment overseen by liberal-minded parents. Could differences in uterine environment have been responsible? This is unlikely, since the biracial children among the adopted had probably come from white mothers.

You acknowledge this problem when you refer to studies on adopted twins:

These individual results, usually based on relatively small statistical samples of adopted twins or siblings, seemingly demonstrate the extreme rigidity of IQ—the "Strong IQ Hypothesis"—while we have also seen the numerous examples above of large populations whose IQs have drastically shifted over relatively short periods of time. How can these contradictory findings be squared?

There is an answer. In adoption or twin studies, the data are produced by a single research team who use the same methodology, the same sample of subjects, and the same context of data production. In contrast, your analysis involves studies that differ in all three:

Differences in methodology

You cite several studies that were done in Eastern Europe before the collapse of communism. Eastern bloc countries, however, never used Western-designed IQ tests. Even the term “IQ” was avoided. I suspect those countries were using an older type of test that was less culture-free than modern IQ tests.

Sampling bias

IQ tests are usually performed on students in a classroom. They thus exclude those students who are (a) truant, (b) currently expelled from class, or (c) have parents who can’t or won’t pay certain mandatory fees. There is thus a sampling bias that tends to exclude lower-performing students. More to the point, this bias varies from one time period to another and from one jurisdiction to another.

Differences in context of data production

In some cases, the IQ test is administered after the students have had some experience doing sample questions. In other cases, the test is administered unannounced. In some cases, the test is administered in the native language or dialect of the students. In other cases, it isn’t. This is a problem in many European countries where the official written language differs from the normal spoken language. The Greek language, for instance, comes in two versions, and the version used in the schools has varied according to the dictates of the party in power.

Other criticisms of your paper

Lynn and Vanhanen draw the conclusion that intelligence leads to economic success and—since they argue that intelligence itself is largely innate and genetic—that the relative development ranking of the long list of nations they analyze is unlikely to change much over time, nor will the economic standing of the various groups within ethnically mixed countries, including the United States.

No, this isn’t their argument. Intelligence leads to economic success only in a system where people can accumulate wealth by working and by keeping the fruits of their labor. If people accumulate wealth mainly through pillage and tribute, there will be a selection for a different package of mental and behavioral traits. For this reason, Lynn and Vanhanen argue that market economies tend to outperform State-run economies if innate intelligence is held constant.

[…] although Greeks and Turks have a bitter history of ethnic and political conflict, modern studies have found them to be genetically almost indistinguishable

Two populations can be almost indistinguishable on some genetic traits, yet very different on others. It depends on the intensity of selection. Selection is typically weak and slow-acting because most genetic traits are of low selective value. This may be seen in the large genetic overlap that exists between any two human populations.

When the early waves of Catholic Irish immigrants reached America near the middle of the 19th century, they were widely seen as particularly ignorant and uncouth and aroused much hostility from commentators of the era, some of whom suggested that they might be innately deficient in both character and intelligence. But they advanced economically at a reasonable pace, and within less than a century had become wealthier and better educated than the average white American, including those of "old stock" ancestry. The evidence today is that the tested IQ of the typical Irish-American-to the extent it can be distinguished-is somewhat above the national white American average of around 100

In the 19th century, Irish immigrants were perceived as being uncouth largely because American moral and behavioral norms were much stricter than they are now. Dancing, for instance, was banned in many communities. So there has been convergence in both directions. Immigrants have assimilated to American norms, but those norms have also become more liberal.

I would like to see your sources for Irish American IQ. In Canada, most people of Irish origin are only part-Irish (including myself). Yes, one can find people who are sure of their Irish ancestry and who can produce genealogical records to prove that their ancestry is entirely Irish. But such people would tend to be better educated as well as more interested in history and genealogy. If that isn’t a biased sample, I don’t know what is.

(last two pages)

I realize you feel passionately that Mexican Americans are getting bad press. I also realize that the conclusions from your analysis of European IQ may have implications for the American immigration debate. Unfortunately, you tend to go off on a tangent and discuss points for which the implications are far from evident.

As you note, WordSum has a correlation of 71% with standard IQ tests, which in turn have a correlation of 50 to 75% with innate intelligence. So we are already two steps removed from any genetically transmitted factors. I’m not surprised that Mexican-American performance on WordSum has improved over time. But does this improvement rule out innate differences in IQ between Mexican Americans and White Americans? Is that your argument?

With regard to Hispanics, you also note that from 1994 to 2006 the poverty rate dropped by one-third and that household income rose by 20%. Most of this rise can be traced to the boom in construction, as well as to the generally good economic climate of that time. But what does this factoid tell us about IQ? You’re going off on a tangent.

[…] it seems likely that the tens of millions of Hispanics living in America in the early 1990s probably advanced more rapidly in economic and educational terms than had any of America's large European immigrant groups of the past, such as the Irish, the Italians, the Jews, or the Slavs.

Steve Sailer would argue otherwise. Several intergenerational studies have shown that Mexican Americans have lagged behind Americans of other ethnic origins.

Reference

Unz, R. (2012). Race, IQ, and Wealth, The American Conservative, July 18.

http://www.theamericanconservative.com/articles/race-iq-and-wealth/

Are male and female homosexuality inversely correlated?

U.S. General Social Survey (analysis by Jason Malloy),
- only groups of 40 or more individuals included
- homosexual category includes bisexuals

Jason Malloy has looked into the U.S. General Social Survey for rates of homosexuality by national origin and by gender.  Not surprisingly, he found that different national origins have different rates of homosexuality, given their different levels of sexual permissiveness. Surprisingly, however, there is an apparent inverse correlation between male and female homosexuality. If sexual permissiveness were the causal factor, shouldn’t it increase the numbers of both gays and lesbians? Perhaps not to the same extent, but the effect should at least be in the same positive direction.

This finding is in line with the one discussed in the last post. Although female homosexuality is becoming more common among younger age cohorts, these same cohorts show a stable or even decreasing rate of male homosexuality.

Again, what is going on? When cultural constraints are weak or absent, it may be that the upper limit for expression of homosexuality is higher in females than in males. But that in itself wouldn’t produce an inverse correlation. Perhaps different national groups, for reasons of genetics or family environment (e.g., diet, early childhood upbringing), have different susceptibilities to male and female homosexuality.

For instance, Chinese Americans may be highly susceptible to male homosexuality but only weakly susceptible to female homosexuality. This particular finding might be related to the community’s higher birth ratio of males to females and its corresponding wife shortage. Yet that kind of explanation still rings a bit hollow.

Any ideas?

Born this way?

Lady Gaga on the Monster Ball Tour, 2010
Note: Post has been updated with new data from Jason Malloy

“Why not? It will leave more women for the rest of us.” I remember hearing that argument for gay rights while in high school, the assumption being that gays greatly outnumbered lesbians. There was some exaggeration in both directions. Gays have never made up 10% of all males and lesbians have never made up only 1% of all females. Even so, the former seemed to outnumber the latter. Back then.

Today, the tables have turned. If we look at General Social Survey data (2010) from the United States (analysis by Jason Malloy), the proportion of gay or bisexual men has held steady at 5 to 6%, although there seems to have been a decline among men born since 1980. Meanwhile, the proportion of lesbian or bisexual women has risen from a low of 4% in the oldest cohort to a high of 9% in the youngest one.

Percentages of men who have had a male sex partner, by birth cohort:

1900-1919  =  6.0
1920-1939  =  5.7
1940-1949  =  5.1
1950-1959  =  6.4
1960-1979  =  6.4
1980-1992  =  5.0

For a better look at what's been going on among males born since 1980 (who are still young adults), the last two cohorts are compared only for the 18-23 age bracket:

1960-1979  =  6.0
1980-1992  =  4.6

Percentages of women who have had a female sex partner, by birth cohort:

1900-1919  =  3.9
1920-1939  =  3.5
1940-1949  =  3.7
1950-1959  =  5.8
1960-1979  =  7.4
1980-1992  =  8.9

This upward trend seems to be continuing among the youngest females (18 to 23 year-olds only):

1960-1979  =  6.5
1980-1992  =  9.2

What is going on? It looks like male homosexuality is much more hardwired than female homosexuality. As our social environment becomes more liberal, fewer gays are coming out of the closet—probably because so few are left there. In contrast, the number of potential lesbians seems much more open-ended. Is there an upper limit?