Monday, May 21, 2018

The end of Jewish achievement?



Neurons show more axonal growth when exposed to higher levels of sphingolipids (last figure) (Cochran et al. 2006)



Jewish achievement is a difficult topic. Recently, it has been addressed by Jordan Peterson, as in this interview with the Forward:

"You can assume that they [Jews] are intelligent and have a culture of learning, or you can think that there's some kind of cabal," Peterson told the Forward. "So if I'm gonna hit the hornets nest, I might as well hit it on the side that takes the wind out of the sails of far-righters and their idiot anti-Semitism." (Feldman 2018)

That quote appeared under the headline "Is Jordan Peterson Enabling Jew Hatred?" There was also a photo montage (since removed) juxtaposing his image with that of Hitler. It's hard to believe that this topic was freely discussed in the mainstream a mere decade ago. At that time Commentary ran an article by Charles Murray on "Jewish Genius":

From 1870 to 1950, Jewish representation in literature was four times the number one would expect. In music, five times. In the visual arts, five times. In biology, eight times. In chemistry, six times. In physics, nine times. In mathematics, twelve times. In philosophy, fourteen times.


[...] What accounts for this remarkable record? A full answer must call on many characteristics of Jewish culture, but intelligence has to be at the center of the answer. Jews have been found to have an unusually high mean intelligence as measured by IQ tests since the first Jewish samples were tested. (The widely repeated story that Jewish immigrants to this country in the early 20th century tested low on IQ is a canard.) Exactly how high has been difficult to pin down, because Jewish sub-samples in the available surveys are seldom perfectly representative. But it is currently accepted that the mean is somewhere in the range of 107 to 115, with 110 being a plausible compromise. (Murray 2007)

Murray then discussed a paper by Gregory Cochran, Jason Hardy, and Henry Harpending, likewise published in a mainstream journal. The authors argued that Ashkenazi Jews had historically worked in occupations that select for cognitive ability, i.e., sales, finance, and trade. Non-Jews usually worked in intellectually less demanding occupations, most often farming. Sephardic Jews were similarly selected, but not to the same extent. They tended to work in a wider range of occupations, with more emphasis on crafts than on finance. Furthermore, beginning in the 17th century, Ashkenazi craftsmen were more entrepreneurial than their Sephardic counterparts; they produced for a larger market, geographically and demographically, where the rewards for success were greater and where successful craftsmen had only one way of increasing their workforce to meet demand: marrying younger and having more children (Frost 2007).

This theory is supported by a striking piece of evidence: the high incidence among Ashkenazim of certain genetic disorders: Tay-Sachs, Gaucher, Niemann-Pick, and mucolipidosis type IV (MLIV). All four of these disorders affect the same metabolic pathway: the capacity to store sphingolipid compounds that promote the growth and branching of axons in the brain. Although these disorders are deleterious in the homozygote state, they're a net benefit in the much more frequent heterozygote state. They provide the brain with higher levels of sphingolipids without the adverse health effects (Cochran et al. 2006).

This is not to say that only these four disorders explain the higher mean IQ of Ashkenazim.  They're simply witnesses to a selection pressure that has probably acted on the many thousands of genes that in one way another influence cognitive ability.


A strange collapse

If Jewish achievement is genetically based, it should be relatively stable, shouldn't it? Yet it has been far from stable over the past forty years. Ron Unz (2012) has ably documented what he calls "the strange collapse of Jewish achievement":

- In the U.S. Math Olympiad, over 40% of the top students were Jewish during the 1970s. During the 1980s and 1990s, the percentage averaged about one-third. During the thirteen years since 2000, two names out of 78 or 2.5% appear to be Jewish. 

- On the Putnam Exam (a mathematics competition for American college students) over 40% of the winners were Jewish before 1950. Between that year and the 1990s, the percentage was 22-31%. Since 2000, it has been under 10%, without a single likely Jewish name between 2005 and 2012.

- Of the national finalists for the Science Talent Search, 22-23% were Jewish from the 1950s to the 1980s. The percentage was 17% in the 1990s, 15% in the 2000s, and 7% from 2010 to 2012. Of the thirty top students over the last period, only one seems to have been Jewish. 

- Jews were over one-quarter of the top students in the Physics Olympiad from 1986 to 1997. During the 2000s the percentage was 5%.

- From 2000 to 2012, only 8% of the top students in the Biology Olympiad were Jewish, with none from 2010 to 2012. 

- Between 1992 and 2012, only 11% of the winners of the Computing Olympiad had Jewish names, as did 8% of the Siemens AP Award winners. 

- From 2010 to 2012, none of the Chemistry Olympiad winners had a probable Jewish name.

A similar decline seems to be under way in Israel. Rindermann (2018, p. 148) cites student assessment studies that indicate a decrease in that country's IQ from 101 in the 1960s to 95 today. Yet the intervening years saw a large influx of Jewish immigrants from the former Soviet Union—about 979,000 between 1989 and 2006 (Wikipedia 2018b). The Ashkenazi proportion of Israel's population is consequently higher today than it was in the 1960s.

So what is driving this decline in academic performance? Ron Unz opts for a social/cultural cause: "today's overwhelmingly affluent Jewish students may be far less diligent in their work habits or driven in their studies than were their parents or grandparents, who lived much closer to the bracing challenges of the immigrant experience."

Hmm ...It's a bit of a stretch to say that most Jewish American kids were still the children or grandchildren of immigrants as late as the 1970s. In this, Ron is echoing the frequent claim that the immigrant experience has a transformative effect, turning slackers into strivers or at least encouraging the slackers to stay home. 

Let's take off the rose-tinted glasses and look reality in the face: most immigrants are not high achievers. Either today or back in the challenging 1970s. As for the minority who are, they typically come from groups that were already that way in their countries of origin. So the immigrant experience, in itself, has little explanatory value. The explanation is that certain cultures have selected for mental and behavioral traits that make high achievement possible.

Unz is on firmer ground when he says that over the last two decades up to half of the Jewish winners of the Math Olympiad were recent immigrants from the former Soviet Union. But why, then, did the mean IQ of Israel decline when that country took in a similar influx of Soviet Jews? That influx was much larger proportionately—almost a million in a country of eight and a half million. Today, Russian Jews number 1.2 million in Israel, if one includes non-Jewish household members (Wikipedia 2018a; Wikipedia 2018b). 

Perhaps Soviet Jews who went to the United States were somehow different from those who went to Israel.  In the U.S., about half of them arrived under the Lautenberg amendment (1990) which authorizes the entry of religious minorities "with a credible, but not necessarily individual, fear of persecution." In Israel, they arrived under the Law of Return, which lets in anyone with at least one Jewish grandparent or a Jewish spouse. 

Israel is thus more open to immigrants from the former Soviet Union ... as long as they have some sort of Jewish affiliation. The affiliation is often weak:

In 1988, a year before the immigration wave began, 58% of married Jewish men and 47% of married Jewish women in the Soviet Union had a non-Jewish spouse. Some 26%, or 240,000, of the immigrants had no Jewish mother, and were thus not considered Jewish under Halakha, or Jewish religious law, which stipulates one must have a Jewish mother to be considered Jewish. (Wikipedia 2018b)

Out-marriage has increased considerably in those countries that provide Israel with immigrants, not only the former Soviet Union but also the United States, Canada, and France. If Jews are becoming less and less Jewish by ancestry, it should be no surprise that anything specific to them genetically is likewise becoming less and less, whether they live in Israel or in the United States. This genetic change should be most noticeable on the right tail of the bell curve ... among the most gifted.


Conclusion

So the decline in Jewish achievement may be both an argument for and an argument against a genetic cause. Ron Unz sees an argument against: "the innate potential of a group is unlikely to drop so suddenly." Well, only if the group has a closed membership. According to a 2013 American survey, the intermarriage rate is now 58% among all Jews and 71% among non-Orthodox Jews. Yet 81% of all Jews still raise their children as Jewish (Goodstein 2013). It seems that "Jewishness" is increasingly self-defined and self-ascribed.

Besides out-marriage, something else may be going on. There are signs that fertility is sharply declining among the most intelligent women (Kanazawa 2014). Jewish Americans would be harder hit in this respect, but the problem may be a much larger one, as indicated by the recent slowing down and reversal of the Flynn Effect and by the steady increase in reaction time from about the year 1980 onward (Flynn 2007, pp. 143; Frost 2014; Madison 2014; Teasdale and Owen 2005).

In conclusion, the decline in Jewish achievement may have a genetic cause, a social/cultural one, or both. It nonetheless looks real. Much has been written about the bleak outlook for Jewish Americans due to their high out-marriage rate and their low fertility rate. But what if, on top of this numerical decline, there has also been a cognitive and intellectual one?

What will happen when Jewish millennials and post-millennials pick up the torch, move up in the world, and begin to make their mark? We may see another collapse: that of the remarkable Jewish presence in American life and culture.


References

Cochran, G., J. Hardy, and H. Harpending. (2006). Natural history of Ashkenazi intelligence, Journal of Biosocial Science 38: 659-693.
https://antville.org/static/sites/kratzbuerste/files/AshkenaziIQ.pdf   

Feldman, A. (2018). Is Jordan Peterson enabling Jew hatred? Forward. May 11
https://forward.com/news/national/400597/is-jordan-peterson-enabling-jew-hatred/

Flynn, J.R. (2007). What is Intelligence? Beyond the Flynn Effect. Cambridge University Press.
https://books.google.ca/books?id=qvBipuypYUkC&printsec=frontcover&hl=fr&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false

Frost, P. (2007). Natural selection in proto-industrial Europe. Evo and Proud, November 16.
http://evoandproud.blogspot.com/2007/11/natural-selection-in-proto-industrial.html

Frost, P. (2014). What happened in the 1980s to reaction time? Evo and Proud, May 3.
http://evoandproud.blogspot.ca/2014/05/what-happened-in-1980s-to-reaction-time.html

Goodstein, L. (2013). Poll shows major shift in identity of U.S. Jews. The New York Times, October 1.
https://www.nytimes.com/2013/10/01/us/poll-shows-major-shift-in-identity-of-us-jews.html  

Kanazawa, S. (2014). Intelligence and childlessness. Social Science Research 48: 157-170.
https://www.researchgate.net/profile/Satoshi_Kanazawa/publication/263666009_Intelligence_and_childlessness/links/59dc1174458515e9ab45299c/Intelligence-and-childlessness.pdf

Madison, G. (2014). Increasing simple reaction times demonstrate decreasing genetic intelligence in Scotland and Sweden, London Conference on Intelligence, Psychological comments, April 25,  #LCI14 Conference proceedings
http://www.unz.com/jthompson/lci14-questions-on-intelligence/

Murray, C. (2007). Jewish Genius. Commentary, April 1
https://www.commentarymagazine.com/articles/jewish-genius/  

Rindermann, H. (2018). Cognitive Capitalism. Human Capital and the Wellbeing of Nations. Cambridge University Press.

Teasdale, T.W., and D.R. Owen. (2005). A long-term rise and recent decline in intelligence test performance: The Flynn Effect in reverse. Personality and Individual Differences 39(4): 837-843.
https://doi.org/10.1016/j.paid.2005.01.029

Unz, R. (2012). The myth of American meritocracy. The American Conservative, November 28
http://www.theamericanconservative.com/articles/the-myth-of-american-meritocracy/  

Wikipedia (2018a). Russian Jews in Israel
https://en.wikipedia.org/wiki/Russian_Jews_in_Israel

Wikipedia (2018b). 1990s Post-Soviet Aliyah
https://en.wikipedia.org/wiki/1990s_Post-Soviet_aliyah

Monday, May 14, 2018

A new yardstick



If we look at ancient DNA from 4600 BC to 1200 AD, we see a steady increase over time in the number of genetic variants that are linked to high educational attainment (Woodley et al. 2017)



Four years ago I discussed genetic variants that seem to favor high educational attainment (Frost 2014). They’re found at single nucleotide polymorphisms (SNPs), and their incidence varies from one human population to another. In all but one case, they are specific to humans and not shared with ancestral primates. 

Davide Piffer has been interested in these SNP variants, seeing them as a possible way to measure how genes contribute to intelligence in different populations. By looking up population data, he can calculate their average incidence for a given group of people. This measure is called the “cognitive polygenic score.”

When he wrote up his latest paper (Piffer 2017a), only nine of these variants were known. For each geographic region, the scores were as follows:

Sub-Saharan Africans – 18%
Amerindians – 25%
North Africans – 30%
Oceanians (Papuans, Melanesians) – 34%
Southeast Asians – 35%
West Asians – 38%
Middle Easterners – 40%
Europeans – 41%
Siberians – 43%
East Asians – 45%

This regional breakdown is open to criticism. Sardinians (32%) were not included in the European category, and Mongolians (49%) were grouped with East Asians rather than with Siberians. The distinction between Middle Easterners and West Asians is not clear to me. The Amerindian category is based on a few small groups. And who is included in the Southeast Asian category? Only Cambodians?

When Piffer compared these scores with the results of IQ tests in these regions, he found a high correlation of 0.9. That is high, higher than what I would expect, given the quality of the data, especially for mean IQ, and the very disparate nature of the two datasets.

Over a two-year period Piffer submitted his paper to Intelligence, resubmitted it, had it rejected, and then resubmitted it to Frontiers in Psychology, where it was accepted by the reviewers before being rejected by the editor. It is now sitting in the limbo of a preprint repository (Piffer 2017a).

Meanwhile, the number of these SNPs has continued to grow. A research team led by Aysu Okbay identified 74 SNPs that are associated with educational attainment (Okbay et al. 2016). Another team led by David Hill reported 107 in their initial preprint and 187 in their published paper (Hill et al. 2018). 

Piffer (2017b) repeated his analysis, now using the 107 SNPs that Hill’s team had identified. The geographic pattern still held up but was weaker, the correlation being only 0.64. This lower score is actually more in line with what I would expect. It diverges the most from mean IQ in two geographic areas:

1. South Asia (Pakistan, India) - South Asians seem to do worse on IQ tests than their genetic endowment predicts. Why? Is it the culture? The diet? Inbreeding? Perhaps language. IQ tests are often administered in a language (English, Hindi, Urdu) that may be the second language of the person taking it. Or perhaps South Asian educational attainment is determined not only by IQ but also by qualities like the ability to sit still and not make a ruckus in class.

2. The Mende of Sierra Leone - For some reason, the Mende have a higher cognitive polygenic score than any other African population. This might be a real finding, or a typo.

Another research team, led by Michael Woodley, has compared the Okbay dataset with ancient DNA to see whether the cognitive polygenic score has increased over time, specifically between 4600 BC and 1200 AD. The DNA was retrieved from European sites and a few sites from southwest and central Asia. The result? The cognitive polygenic score did increase over time. People on average had more and more of the alleles that favor educational attainment. The authors note that IQ alone may not be responsible:

[...] While the increase in these variants over time is certainly consistent with the expectation of rising GCA [general cognitive ability], the possibility that their increase indicates a simultaneous rise in other factors that make unique contributions to educational attainment (such as 'slow' life history or 'high-K' social cognitive characteristics) cannot be ruled out. (Woodley et al. 2017; references within quote removed)

The new mental/behavioral package developed through a process of feedback with the cultural environment. This gene-culture coevolution likely continued into recent times:

This process likely continued until the Late Modern Era, where it has been noted that among Western populations living between the 15th and early 19th centuries, those with higher social status (which shares genetic variance with, and is therefore a proxy for GCA) typically produced the most surviving offspring. These in turn tended toward downward social mobility due to intense competition, replacing the reproductively unsuccessful low-status stratum and effectively 'bootstrapping' those populations via the application of high levels of skill to solving problems associated with production and industry, eventually leading to the Industrial Revolution in Europe. (Woodley et al. 2017; references within quote removed)


Conclusion

More and more SNPs are being linked to educational attainment. The total is now in the triple digits. That’s still less than the thousands of genes that influence intelligence, but there is no need to identify most of them to spot general trends. Selection acts on phenotype, not on genotype. Selection for intelligence should therefore impact all of these SNPs in the same direction. It’s like estimating the proportions of different colors in a bowl of Smarties. You don’t have to count every last one. Just pick out a handful at random and count the colors.

Four years ago only 7 SNPs had been linked to educational attainment. Now we have 187. In another four years we’ll probably have more than a thousand. All the same, I doubt that the overall geographic pattern will change much. The problems lie elsewhere:

-          Genetic data may be lacking for some unmixed groups, particularly Amerindians.

-          The relationship between intelligence and cognitive polygenic score may not be linear.

-          We may be relying too much on educational attainment as a proxy for IQ (which itself is a proxy for intelligence).

When I was in public school, girls did better than boys in almost every subject. They had good attendance, always took notes, and did their homework. Boys got bored more easily and spent more time fidgeting, daydreaming, and drawing pictures in their notebooks. This sex difference exists in all cultures, but it seems greater in some than in others.

How useful is educational attainment as a proxy for IQ? Yes, these two measures correlate highly with each other (Rindermann 2018, pp. 51-54), but this high correlation is based on studies from WEIRD countries (Western, educated, industrialized, rich, and democratic). Does it hold up on a global scale? I’m not so sure.


References

Frost, P. (2014). Population differences in intellectual capacity: a new polygenic analysis, Evo and Proud, March 8
http://evoandproud.blogspot.ca/2014/03/population-differences-in-intellectual.html

Hill, W. D., R.E. Marioni, O. Maghzian, S.J. Ritchie, S.P. Hagenaars, A.M. McIntosh, C.R. Gale, G. Davies, I.J. Deary. (2018). A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Molecular Psychiatry
https://doi.org/10.1038/s41380-017-0001-5

Okbay, A., J.P. Beauchamp, M.A. Fontana, J.J. Lee, T.H. Pers, C.A. Rietveld, et al. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533: 539-542.
http://www.nature.com/articles/nature17671

Piffer, D. (2017a) Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from GWAS Hits: A Replication of Previous Findings Using Recent Data. Preprints, June 8
https://www.preprints.org/manuscript/201706.0039/v1

Piffer, D. (2017b). Piffer's results replicated (again) by latest GWAS (N=147,194), toppseudoscience, July 21
https://topseudoscience.wordpress.com/2017/07/21/piffers-results-replicated-again-by-latest-gwas-n147194/comment-page-1/#comment-95

Rindermann, H. (2018). Cognitive Capitalism. Human Capital and the Wellbeing of Nations. Cambridge University Press.

Woodley, M.A., S. Younuskunju, B. Balan, and D. Piffer. (2017). Holocene selection for variants associated with general cognitive ability: comparing ancient and modern genomes. Twin Research and Human Genetics 20(4): 271-280.
https://doi.org/10.1017/thg.2017.37 

Monday, May 7, 2018

Outbreeding: not what you may think



Mean number of children as a function of geographic distance between Danish marriage partners (Labouriau and Amorim 2008).



Most of us know about the genetics costs of inbreeding. If you do a Google search for "inbreeding is bad," you get 35,900 hits.  "Outbreeding is bad" yields only 2.

Yet outbreeding does incur genetic costs. It can reduce fitness either by introducing alleles that are unsuited to the local environment or by disrupting co-adapted gene complexes. When a native trout species was hybridized with non-native trout, fertility fell by half with as little as 20% admixture (Muhlfeld et al. 2009).

Fertility is the canary in the coal mine. A measurable decline is a sign that some genes are malfunctioning, either at the time of fertilization or during embryonic development. A malfunction can occur because the genes from the mother and father are too similar—the risk is higher that both copies of a gene will be defective. It can also occur because one copy is too different—incompatibilities may develop with other genes.

That's what we know from data on fish and other animals. But what about our species? At what degree of relatedness do the costs of human outbreeding start to exceed the benefits? When you marry a Neanderthal? The answer may surprise you. An Icelandic study found that fertility peaks at marriages between third or fourth cousins. Fertility is lower when the prospective parents are more closely related ... or less.

Our results, drawn from all known couples of the Icelandic population born between 1800 and 1965, show a significant positive association between kinship and fertility, with the greatest reproductive success observed for couples related at the level of third and fourth cousins. Owing to the relative socioeconomic homogeneity of Icelanders, and the observation of highly significant differences in the fertility of couples separated by very fine intervals of kinship, we conclude that this association is likely to have a biological basis. (Helgason et al. 2008)

The data come from a time when birth control was not widely practiced. Nonetheless, there may have been something different about Icelanders who married beyond their fourth cousins. Perhaps they were more likely to go to university, meet someone from the other side of the country, and eventually settle down and have children late in life. 

These socioeconomic factors were controlled in a Danish study that measured geographic distance between marriage partners: 

The Danish study was based on the cohort of all women born in Denmark in 1954 who were alive and living in Denmark in 1969, totaling 42,165 women. This cohort was followed up to the end of 1999. The number of children born to each mother between the ages of 15 and 45 years old was determined and is referred to as fertility. The mean marital radius (MR) associated with each mother in the cohort was estimated using the distance between the centroids of the parish where she was born and the parishes where the partners with which she had children were born. (Labouriau and Amorim 2008)

Fertility peaked at around 75 km. This relationship between fertility and marital radius was not explained by education, family income, urbanicity, or mother's age at first birth. The authors concluded that their findings were consistent with those of the Icelandic study, the cause being the same in both cases: fertility rises with decreasing relatedness up to a peak level and then starts to fall. Inbreeding depression then gives way to outbreeding depression.

How exactly does outbreeding reduce fertility? Joffe (2010) points to the steady decline in sperm quality since the early 20th century, suggesting it may be due to an increase in outbreeding. He rejects the usually cited cause: the rising level of estrogenic compounds in the environment, e.g., dioxin, DDT, PCBs, PBBs, phthalates, etc. This proposed cause fails to explain why the sperm quality decline has varied so much spatially, even within the same country. Why, for instance, has it been steep in Paris and nonexistent in Toulouse? Why is it nonexistent in domestic animals that are just as exposed to estrogenic compounds? Finally, the decline seems to have begun before most of these compounds began to be commercially produced. 

Joffe (2010) also suggests that there may be a parallel decline in egg quality. We don't really know because sperm is much easier to collect than eggs for large-scale study.


Do we now have outbreeding depression?

Today, inbreeding depression has largely disappeared throughout the Western world. For a long time the beneficial effects of outbreeding were shown by a steady increase in height and a steady decrease in the age of menarche. Both trends have now ground to a halt:

In Northern Europe, adult height has largely stabilised, and the age of menarche has also settled at around 13 years, while weight continues to increase due to obesity. (Cole 2003)

The steady rise in IQ, known as the Flynn Effect, has sometimes been attributed to outbreeding, although this explanation has been challenged (Flynn 2007, pp. 101-102; Woodley 2011). In any case, the Flynn Effect, too, is slowing throughout the West (Flynn 2007, p. 143). In Scandinavia, mean IQ peaked during the late 1990s and has since declined (Teasdale and Owen 2005).

Has outbreeding become more problematic than inbreeding? That's what the latest findings suggest, yet that doesn't at all seem to be the current wisdom.


References

Cole, T.J. (2003). The secular trend in human physical growth: a biological view. Economics & Human Biology 1(2): 161-168.
https://doi.org/10.1016/S1570-677X(02)00033-3

Flynn, J.R. (2007). What is Intelligence? Beyond the Flynn Effect. Cambridge University Press.
https://books.google.ca/books?id=qvBipuypYUkC&printsec=frontcover&hl=fr&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false

Helgason, A., S. Pálsson, D.F. Guðbjartsson, þ. Kristjánsson, K. Stefánsson. (2008). An association between the kinship and fertility of human couples. Science 319(5864): 813-816.
http://facelab.org/debruine/Teaching/EvPsych/files/Helgason_2008.pdf

Joffe, M. (2010). What has happened to human fertility? Human Reproduction 25(2): 295-307.
https://doi.org/10.1093/humrep/dep390
https://academic.oup.com/humrep/article/25/2/295/671754

Labouriau, R., and A. Amorim. (2008). Comment on "An Association Between the Kinship and Fertility of Human Couples" Science 322(5908): 1634
https://doi.org/10.1126/science.1161907
http://science.sciencemag.org/content/322/5908/1634.2.full

Muhlfeld, C.C.,  S.T Kalinowski, T.E. McMahon, M.L. Taper, S. Painter, R.F. Leary, F.W. Allendorf. (2009). Hybridization rapidly reduces fitness of a native trout in the wild. Biology Letters, March 18
http://rsbl.royalsocietypublishing.org/content/early/2009/03/13/rsbl.2009.0033.short  

Teasdale, T.W., and D.R. Owen. (2005). A long-term rise and recent decline in intelligence test performance: The Flynn Effect in reverse. Personality and Individual Differences 39(4): 837-843.
https://doi.org/10.1016/j.paid.2005.01.029

Woodley, M.A. (2011). Heterosis doesn't cause the Flynn effect: A critical examination of Mingroni (2007). Psychological Review 118(4): 689-693.
http://dx.doi.org/10.1037/a0024759 

Monday, April 30, 2018

The original meaning of skin color



Averaged female face (left) and averaged male face (right). (Dupuis-Roy et al. 2009)



At puberty the skin differentiates between the sexes, including its color. Men are browner and ruddier, having more melanin and blood in their skin. By comparison, women are "the fair sex" (Edwards and Duntley 1939; Edwards and Duntley 1949; Edwards et al. 1941; Frost 1988; Frost 2010; Frost 2011; Kalla 1973; Manning et al. 2004; Mazess, 1967; van den Berghe and Frost 1986). Women also display a higher luminous contrast between their facial skin and their lips and eyes (Dupuis-Roy et al. 2009).

In most Western societies this sex difference is scarcely noticeable, being overwhelmed by the much larger differences of race and ethnicity. It has been further obscured since the 1920s by the popularity of tanning among many Western women (Segrave 2005). Nonetheless, for most of human history and prehistory it has been the main reason why skin color varies in our immediate visual environment.

The human mind tends to hardwire any mental task that comes up repeatedly. It thereby shortens response time and eliminates learning time. One such task is to identify whether a person is a man or a woman by examining certain features, such as face shape and properties of the skin, including pigmentation. So when we see the minor pigmentary differences that distinguish men and women, does an innate mechanism process that visual information? This question takes us to research on the best-known example of hardwiring.


Face recognition, gender identification, and facial color

We have an innate ability to recognize human faces. This is shown by a form of brain damage called prosopagnosia, where one may seem normal and yet be no better at recognizing a face than any other object (Farah 1996; Pascalis and Kelly 2008; Zhu et al. 2009). At the other extreme are "super-recognizers" who are as good at face recognition as prosopagnosics are bad (Russell, Duchaine, and Nakayama 2009). 

This mental mechanism is sexually differentiated to some degree. It encompasses several neural populations, some of which specialize in male faces, others in female faces, and others in both kinds indifferently (Baudouin and Brochard. 2011; Bestelmeyer et al. 2008; Jacquet and Rhodes 2008; Little et al. 2005).

To tell male and female faces apart, this mechanism seems to use facial color (Bruce and Langton 1994; Hill, Bruce, and Akamatsu 1995; Russell and Sinha 2007; Russell et al. 2006; Tarr et al. 2001; Tarr, Rossion, and Doerschner 2002). The criteria are hue (brownness and ruddiness) and luminosity (lightness of the skin versus darkness of the lip/eye area). Hue is a fast "channel" for gender identification (Dupuis-Roy et al. 2009; Nestor and Tarr 2008a; Nestor and Tarr 2008b; Tarr et al., 2001; Tarr, Rossion, and Doerschner 2002). If the observer is too far away or the lighting too dim, the brain switches to the slower but more accurate channel of luminosity (Dupuis-Roy et al. 2009).

When shown a human face, subjects can tell its gender even if the image is blurred and differs only in color (Tarr et al. 2001). Indeed, facial color seems especially crucial under conditions of poor visibility when face shape is uncertain (Yip and Sinha 2002). 

The existence of a hardwired mental mechanism may explain not only why a certain schema of facial color is unthinkingly identified as female but also why women seek to accentuate this schema in a wide range of cultures. Thus, in different parts of the world, female cosmetics have shared the same aim of increasing the contrast between facial color and lip/eye color (Russell 2003; Russell 2009; Russell 2010). In a similarly wide range of cultures, women have tried to lighten their color by avoiding the sun and wearing protective clothing (Frost 2010, pp. 120-123). Going back to earliest times, we see that lighter skin was a female norm wherever the visual arts had developed—in ancient Greece, in ancient Egypt, in ancient China and Japan, and in Mesoamerica. All of these artistic traditions systematically gave a lighter coloring to female figures than to male figures (Capart 1905, pp. 26-27; Eaverly 1999; Soustelle 1970, p. 130; Tegner 1992; Wagatsuma 1967).


A cue for sexual interest

In addition to identifying gender, facial color can arouse sexual interest, being linked to gendered notions of attractiveness. In one study, women were asked to optimize the attractiveness of facial pictures by varying the skin's darkness and ruddiness. They made the male faces darker and ruddier than the female faces (Carrito et al. 2016). In another study, women were shown pairs of facial pictures where one face was slightly darker than the other, and they had to choose the most pleasing one. When male faces were shown, the darker face was more strongly preferred by women in the first two-thirds of their menstrual cycle (high estrogen/progesterone ratio) than by women in the last third (low estrogen/progesterone ratio). There was no cyclical effect if the women were judging female faces or taking oral contraceptives (Frost 1994).

The above findings are consistent with the results of a brain-imaging study: the female subjects had a stronger neural response to pictures of "masculinized" male faces, and this response correlated with their estrogen level across the menstrual cycle (Rupp et al. 2009). In a personal communication, the lead author stated that the faces had been masculinized by making them darker and more robust in shape.


A cue for modifying emotions and behavior

Facial color can elicit other responses. In word-association tests, the lighter complexion of women brings to mind such words as innocence, purity, peace, chastity, modesty, femininity, and delicacy (Gergen 1967; Wagatsuma 1967). This sort of response likewise emerged during interviews with Japanese men: "Whiteness is a symbol of women, distinguishing them from men." "Whiteness suggests purity and moral virtue." "One's mother-image is white" (Wagatsuma 1967, pp. 417-418).

Infants too are lighter-skinned (Grande et al. 1994; Kalla 1973; Post et al. 1976). They also share other visual, auditory, and tactile cues with the adult female body: a smaller nose and chin; a higher pitch of voice; and smoother, less hairy, and more pliable skin. This is what Konrad Lorenz dubbed the Kindchenschema, which seems to have the property of reducing aggressiveness in adults and eliciting care and nurturance (Frost 2010, pp. 134-135; Grande et al. 1994; Lorenz 1971, pp. 154-164). 

Infants are light-skinned in other primates. This is particularly so with langurs, baboons, and macaques, whose skin is pink in newborns and almost black in adults. The distinct infant coloration not only helps parents find wayward offspring but also elicits caregiving and defensive reactions. As it disappears with age, infants no longer attract the same interest and are less often sought out and held by adult females (Alley 1980; Alley 2014; Blaffer-Hrdy 2000, pp. 446-448; Booth 1962; Jay 1962). 

In humans, this infant coloration is striking in dark-skinned peoples. In Kenya, newborn children are often called mzungu ("European" in Swahili), and a new mother may tell her neighbors to come and see her mzungu (Walentowitz 2008). Among the Tuareg, children are said to be born "white" because of the freshness and moisture of the womb (Walentowitz 2008). The cause is often thought to be a previous spiritual life:

There is a rather widespread concept in Black Africa, according to which human beings, before "coming" into this world, dwell in heaven, where they are white. For, heaven itself is white and all the beings dwelling there are also white. Therefore the whiter a child is at birth, the more splendid it is. In other words, at that particular moment in a person's life, special importance is attached to the whiteness of his colour, which is endowed with exceptional qualities. (Zahan 1974, p. 385)

Another Africanist makes the same point: "black is thus the color of maturity [...] White on the other hand is a sign of the before-life and the after-life: the African newborn is light-skinned and the color of mourning is white kaolin" (Maertens 1978, p. 41).


Evolution of women's lighter skin

The above suggests that lighter coloration, as a social signal, went through four stages of evolution:

1. Initially, newborn primates were light-skinned because they had no need for pigment in the womb.

2. Adults recognized light skin as a mark of infancy. Selection then favored hardwiring of certain behavioral and emotional responses, particularly by females and to a lesser extent by all members of the local group. This mechanism could nonetheless be overridden by strange males that invade the group and kill the young (Alley 1980).

3. The same selection pressure caused infants to remain lighter-colored until they no longer had to be cared for. This was particularly so in those species where care of offspring was greater and lasted longer.

4. In humans, slower maturation, higher paternal investment, and longer-lasting pair bonds increased the risk of male neglect and aggression, thus creating a similar selection pressure and causing women to mimic key features of the Kindchenschema.

This evolutionary path was described by the ethologist Russell Guthrie:

I believe the sexual differences in skin color resulted from female whiteness being selected for because it is opposite the threat coloration, although the selection pressures may have been rather mild. Light skin seems to be more paedomorphic, since individuals of all races tend to darken with age. Even in the gorilla, the most heavily pigmented of the hominoids, the young are born with very little pigment. [...] Thus, a lighter colored individual may present a less threatening, more juvenile image. (Guthrie 1970)

From this perspective, women acquired a lighter color to modify rather than arouse sexual interest. This hypothesis is supported by a two-part study where men were first shown pictures of women and asked to rate their attractiveness. Lighter-skinned women were not rated more attractive than darker-skinned women. In the second part, eye movements were tracked, and it was found that lighter-skinned women were viewed for a longer time than darker-skinned women. The longer duration may indicate a slower rise and fall in sexual interest (Garza et al. 2016). 

By altering the trajectory of sexual interest, women's lighter skin may modify male behavior by dampening strong emotions, like aggression, and inducing feelings of care. This is perhaps a clue to why many women embraced the tanned look during the 20th century, in defiance of older norms of femininity. The new look enabled them to exploit an erotic sensibility that had earlier been stigmatized. In Victorian-era novels the "dark lady" is an "impetuous," "ardent," and "passionate" object of short-lived romances (Carpenter 1936, p. 254). Similarly, in French novels of the same period "[t]he love incarnated by brown women appears as the conceptual equivalent of a devouring femininity, thus making them similar to the mythical figure of Lilith" (Atzenhoffer, 2011, p. 6).This motif goes back at least to the Middle Ages in various European cultures and highlights an alternate form of eroticism:

[...] dark girls [...] are inevitably imagined as sexually more available than their fairer sisters, with whom they are implicitly or explicitly contrasted. In addition, the change of a girl's complexion, such as being burned by the sun, is to be understood as symbolic of her having crossed a sexual threshold without the benefit of marriage. (Vasvari 1999)


Identifying the brain regions that process facial color

There is a large body of research on the processing of facial color in the human mind, particularly on the brain regions involved. Thorstenson (2018) has reviewed the literature:

[...] there is considerable evidence suggesting that color is not merely an accessory of faces, but is rather a complex and crucial feature in facial processing. While classic  work  on  neural  processing  has  suggested  a  primary  cortical  area  responsible for face processing (FFA; Kanwisher, McDermott, & Chun, 1997) and a primary cortical area responsible for color processing (V4; McKeefry & Zeki, 1997), more recent work has revealed several areas in the temporal lobes specialized for face processing (Moeller, Freiwald, & Tsao, 2008; Tsao, Moeller, & Freiwald, 2008). Further, recent work has revealed consistent patterns of connected face and color selective cortical areas (Lafer-Sousa & Conway, 2013), possibly reflecting a shared overlap of visual processing between faces and color (Nakajima, Minami, Tanabe, Sadato, & Nakauchi, 2014; Stephen & Perrett, 2015). Additionally, the N170 component,  which  reflects  the  neural  processing  of  faces  in  event-related  potential  (ERP) studies, has been shown to respond to facial color information (Nakajima, Minami, & Nakauchi, 2012), but not to non-faces (Botzel & Grusser, 1989).

Thorstenson (2018) also reviews the possibilities for social signaling. Facial reddening is associated with anger and other intense emotions. Facial color can indicate certain disease states. Finally, there is a rise and fall in facial ruddiness and darkness over the menstrual cycle, with female facial color being lightest at ovulation.

Though providing a good review of the literature, Thorstenson should have mentioned three studies on female skin pigmentation over the menstrual cycle. McGuiness (1961) and Snell and Turner (1966) observed that facial skin darkens near the end of the cycle, particularly the peri-ocular skin of brunettes. Edwards and Duntley (1949) found that the buttocks visibly redden over the cycle, being lightest on the 13th day and darkest on the 25th day.


Conclusion

Today, skin color is seen through the lens of ethnic and racial conflict, yet this is not the sole meaning it has had for humans. For most of history and prehistory it was seen through a sexual lens, as a mark of masculinity or femininity.

This older meaning has received much less interest, even from academics. It is perhaps no coincidence that interest has come disproportionately from non-Western scholars like Hiroshi Wagatsuma, Kenichi Aoki, Mikiko Ashikari, and Aloke Kalla. In contrast, Western scholars, and Americans in particular, generally view the psychological meaning of skin color as a legacy of slavery.


References

Alley, T. R. (1980). Infantile colouration as an elicitor of caretaking behaviour in Old World primates. Primates 21(3): 416-429.
https://doi.org/10.1007/BF02390470   

Alley, T.R. (2014[1986]). An ecological analysis of the protection of primate infants. In V. McCabe and G.J. Balzano (eds). Event Cognition: An Ecological Perspective. Routledge.
https://books.google.ca/books?id=YPTpAgAAQBAJ&printsec=frontcover&hl=fr&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false 

Aoki, K. (2002). Sexual selection as a cause of human skin colour variation: Darwin's hypothesis revisited. Annals of Human Biology 29(6): 589-608.
https://doi.org/10.1080/0301446021000019144   

Ashikari, M. (2005). Cultivating Japanese whiteness. The 'whitening' cosmetics boom and the Japanese identity. Journal of Material Culture 10(1):73-91.
https://doi.org/10.1177/1359183505050095    

Atzenhoffer, R. (2011). Les hommes préfèrent les blondes. Les lectrices aussi. Effet de psychologie, horizons idéologiques et valeurs morales des héroïnes dans l'œuvre romanesque de H. Courths-Mahler, Colloque national (CNRIUT), Villeneuve d'Ascq, 8-10 juin 2009,
http://cnriut09.univ-lille1.fr/articles/Articles/Fulltext/10a.pdf   

Baudouin, J.-Y., and R. Brochard. (2011). Gender-based prototype formation in face recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition 37(4): 888-898.
http://dx.doi.org/10.1037/a0022963    

Bestelmeyer, P.E.G., B.C. Jones, L.M. DeBruine, A.C. Little, D.I. Perrett, A. Schneider, L.L.M. Welling, C.A. Conway. (2008). Sex-contingent face aftereffects depend on perceptual category rather than structural encoding. Cognition 107(1): 353-365.
https://doi.org/10.1016/j.cognition.2007.07.018    

Blaffer-Hrdy, S. (2000). Mother Nature: Maternal Instincts and How They Shape the Human Species. New York: Ballantine Books.

Booth, C. (1962). Some observations on behavior of Cercopithecus monkeys. Annals of the New York Academy of Sciences 102: 477-487.
https://doi.org/10.1111/j.1749-6632.1962.tb13654.x   

Bruce, V., and S. Langton. (1994). The use of pigmentation and shading information in recognising the sex and identities of faces. Perception 23(7): 803-822.
http://dx.doi.org/10.1068/p230803   

Capart, J. (1905). Primitive Art in Egypt. London: H. Grevel.

Carpenter, F. I. (1936). Puritans preferred blondes. The heroines of Melville and Hawthorne. New England Quarterly 9(2): 253-272.
https://doi.org/10.2307/360391   

Carrito, M.L., I.M.B. dos Santos, C.E. Lefevre, R.D. Whitehead, C.F. da Silva, and D.I. Perrett. (2016). The role of sexually dimorphic skin colour and shape in attractiveness of male faces. Evolution and Human Behavior 37(2): 125-33.
https://doi.org/10.1016/j.evolhumbehav.2015.09.006    

Dupuis-Roy, N., I. Fortin, D. Fiset, and F. Gosselin. (2009). Uncovering gender discrimination cues in a realistic setting. Journal of Vision 9(2): 10, 1-8.
https://doi.org/10.1167/9.2.10    

Eaverly, M.A. (1999). Color and gender in ancient painting: A pan-Mediterranean approach. In N.L. Wicker and B. Arnold (eds). From the Ground Up: Beyond Gender Theory in Archaeology. Proceedings of the Fifth Gender and Archaeology Conference, University of Wisconsin-Milwaukee (pp. 5-10). Oxford (England): British Archaeological Reports.

Edwards, E.A., and S.Q. Duntley. (1939). The pigments and color of living human skin. American Journal of Anatomy 65(1): 1-33.
https://doi.org/10.1002/aja.1000650102    

Edwards, E.A., and S.Q. Duntley. (1949). Cutaneous vascular changes in women in reference to the menstrual cycle and ovariectomy. American Journal of Obstetrics & Gynecology 57(3): 501-509.
https://doi.org/10.1016/0002-9378(49)90235-5    

Edwards, E.A., J.B. Hamilton, S.Q. Duntley, and G. Hubert. (1941). Cutaneous vascular and pigmentary changes in castrate and eunuchoid men. Endocrinology 28(1): 119-128. https://doi.org/10.1210/endo-28-1-119    

Farah, M. J. (1996). Is face recognition 'special'? Evidence from neuropsychology. Behavioural
Brain Research 76(1-2): 181-189.
https://doi.org/10.1016/0166-4328(95)00198-0    

Frost, P. (1988). Human skin color: A possible relationship between its sexual dimorphism and its social perception. Perspectives in Biology and Medicine 32(1): 38-58.
https://doi.org/10.1353/pbm.1988.0010    

Frost, P. (2010). Femmes claires, hommes foncés. Les racines oubliées du colorisme. Quebec City: Les Presses de l'Université Laval, 202 p.

Frost, P. (2011). Hue and luminosity of human skin: a visual cue for gender recognition and other mental tasks. Human Ethology Bulletin 26(2): 25-34.
https://www.researchgate.net/publication/256296588_Hue_and_luminosity_of_human_skin_a_visual_cue_for_gender_recognition_and_other_mental_tasks    
Garza, R., R.R. Heredia, and A.B. Cieslicka. (2016). Male and female perception of physical attractiveness. An eye movement study. Evolutionary Psychology 14(1): 1-16. https://doi.org/10.1177/1474704916631614    

Gergen, K.J. (1967). The significance of skin color in human relations. Daedalus 96: 390-406.
http://www.jstor.org/stable/20027044  

Grande, R., E. Gutierrez, E. Latorre, and F. Arguelles. (1994). Physiological variations in the pigmentation of newborn infants. Human Biology 66(3): 495-507.
http://www.jstor.org/stable/41465000
Guthrie, R.D. (1970). Evolution of human threat display organs. in T. Dobzhansky, M.K. Hecht, and W.C. Steere (eds). Evolutionary Biology 4: 257-302. New York: Appleton-Century Crofts.

Hill, H., V. Bruce, and S. Akamatsu. (1995). Perceiving the sex and race of faces: The role of shape and colour. Proceedings of the Royal Society B: Biological Sciences 261(1362): 367-373.
https://doi.org/10.1098/rspb.1995.0161    

Jaquet, E., and G. Rhodes. (2008). Face aftereffects indicate dissociable, but not distinct, coding of male and female faces. Journal of Experimental Psychology: Human Perception and Performance 34(1): 101-112.
https://doi.org/10.1037/0096-1523.34.1.101    

Jay, P. C. (1962). Aspects of maternal behavior among langurs. Annals of the New York Academy of Sciences 102(2): 468-476.
https://doi.org/10.1111/j.1749-6632.1962.tb13653.x   

Kalla, A.K. (1973). Ageing and sex differences in human skin pigmentation. Zeitschrift für Morphologie und Anthropologie 65(1): 29-33.
http://www.jstor.org/stable/25756080   

Little, A.C., L.M. DeBruine, and B.C. Jones. (2005). Sex-contingent face after-effects suggest distinct neural populations code male and female faces. Proceedings of the Royal Society of London, Series B 272(1578): 2283-2287.
https://doi.org/10.1098/rspb.2005.3220    

Lorenz, K. 1971. Studies in Animal and Human Behaviour, vol. 2. London: Methuen & Co.

Maertens, J-T. (1978). Le dessein sur la peau. Essai d'anthropologie des inscriptions tégumentaires, Ritologiques I, Paris: Aubier Montaigne.

Manning, J.T., P.E. Bundred, and F.M. Mather. (2004). Second to fourth digit ratio, sexual selection, and skin colour. Evolution and Human Behavior 25(1): 38-50.
https://doi.org/10.1016/S1090-5138(03)00082-5  

Mazess, R.B. (1967). Skin color in Bahamian Negroes. Human Biology 39(2): 145-154.
http://www.jstor.org/stable/41448835    

McGuiness, B.W. (1961). Skin pigmentation and the menstrual cycle. British Medical Journal 2(5251): 563-565.
http://www.jstor.org/stable/20354588   

Nestor, A., and M.J. Tarr. (2008a). The segmental structure of faces and its use in gender recognition. Journal of Vision 8(7): 7, 1-12,
http://journalofvision.org/8/7/7/   
https://doi.org/10.1167/8.7.7   

Nestor, A., and M.J. Tarr. (2008b). Gender recognition of human faces using color. Psychological Science 19(12): 1242-1246.
https://doi.org/10.1111/j.1467-9280.2008.02232.x   

Pascalis, O., and D.J. Kelly. (2008). Face processing, in M. Haith and J. Benson (eds), Encyclopedia of Infant and Early Childhood Development. (pp. 471-478), Elsevier.

Post, P.W., A.N. Krauss, S. Waldman, and Peter A.M. Auld. (1976). Skin reflectance of newborn infants from 25 to 44 weeks gestational age. Human Biology 48(3): 541-557.
http://www.jstor.org/stable/41462904

Rupp, H.A., T.W. James, E.D. Ketterson, D.R. Sengelaub, E. Janssen, and J.R. Heiman. (2009). Neural activation in women in response to masculinized male faces: mediation by hormones and psychosexual factors. Evolution and Human Behavior 30(1): 1-10. https://doi.org/10.1016/j.evolhumbehav.2008.08.006   

Russell, R. (2003). Sex, beauty, and the relative luminance of facial features. Perception 32(9): 1093-1107.
http://dx.doi.org/10.1068/p5101   

Russell, R. (2009). A sex difference in facial pigmentation and its exaggeration by cosmetics. Perception 38(8): 1211-1219.
https://doi.org/10.1068/p6331   

Russell, R. (2010). Why cosmetics work. In R. Adams, N. Ambady, K. Nakayama, and S. Shimojo (eds.) The science of social vision. New York: Oxford.

Russell, R., B. Duchaine, and K. Nakayama. (2009). Super-recognizers: People with extraordinary face recognition ability. Psychonomic Bulletin & Review 16(2): 252-257.
https://doi.org/10.3758/PBR.16.2.252  

Russell, R. and P. Sinha. (2007). Real-world face recognition: The importance of surface reflectance properties. Perception 36(9): 1368-1374.
http://dx.doi.org/10.1068/p5779   

Segrave, K. (2005). Suntanning in 20th Century America. Jefferson (North Carolina): McFarland & Company.

Snell, R.S., and R. Turner. (1966). Skin pigmentation in relation to the menstrual cycle. The Journal of Investigative Dermatology 47(2): 147-155.
https://doi.org/10.1038/jid.1966.119  

Soustelle, J. (1970). The Daily Life of the Aztecs. Stanford, California: Stanford University Press.

Tarr, M.J., D. Kersten, Y. Cheng, and B. Rossion. (2001). It's Pat! Sexing faces using only red and green. Journal of Vision 1(3): 337, 337a.
https://doi.org/10.1167/1.3.337   

Tarr, M. J., B. Rossion, and K. Doerschner. (2002). Men are from Mars, women are from Venus: Behavioral and neural correlates of face sexing using color. Journal of Vision 2(7): 598, 598a, http://journalofvision.org/2/7/598/   
https://doi.org/10.1167/2.7.598   

Tegner, E. (1992). Sex differences in skin pigmentation illustrated in art. The American Journal of Dermatopathology 14(3): 283-87.
https://doi.org/10.1097/00000372-199206000-00016  

Thorstenson, C.A. (2018). The social psychophysics of human face color: Review and recommendations. Social Cognition 36(2): 247-273.
https://doi.org/10.1521/soco.2018.36.2.247   
https://www.researchgate.net/publication/324145494_The_Social_Psychophysics_of_Human_Face_Color_Review_and_Recommendations   
van den Berghe, P.L., and P. Frost. (1986). Skin color preference, sexual dimorphism and sexual selection: A case of gene-culture co-evolution? Ethnic and Racial Studies 9(1): 87-113. https://doi.org/10.1080/01419870.1986.9993516  

Vasvari, L.O. (1999). A comparative approach to European folk poetry and the erotic wedding motif, CLCWeb. Comparative Literature and Culture 1(4)
https://doi.org/10.7771/1481-4374.1050  

Wagatsuma, H. (1967). The social perception of skin color in Japan. Daedalus 96(2): 407-443.
http://www.jstor.org/stable/20027045   

Walentowitz, S. (2008). Des êtres à peaufiner. Variations de la coloration et de la pigmentation du nouveau-né, in J-P. Albert, B. Andrieu, P. Blanchard, G. Boëtsch, and D. Chevé (eds.) Coloris Corpus (pp. 113-120), Paris: CNRS Éditions, 2008.

Yip, A.W., and P. Sinha. (2002). Contribution of color to face recognition. Perception 31(8): 995-1003.
https://doi.org/10.1068/p3376  

Zahan, D. (1974). White, Red and Black: Colour Symbolism in Black Africa, in A. Portmann and R. Ritsema (eds.) The Realms of Colour, Eranos 41 (1972), 365-395, Leiden: Eranos.

Zhu, Q., Y. Song, S. Hu, X. Li, M. Tian, Z. Zhen, Q. Dong, N. Kanwisher, and J. Liu. (2009). Heritability of the specific cognitive ability of face perception. Current Biology 20(2): 137-142.
https://doi.org/10.1016/j.cub.2009.11.067