The Travelling Companions, 1862, Augustus Egg (1816-1863)
I'm now blogging at Peter Frost's Newsletter. Please drop by and offer your comments:
Peter Frost's anthropology blog, with special reference to sexual selection and the evolution of skin, hair, and eye pigmentation
The Travelling Companions, 1862, Augustus Egg (1816-1863)
I'm now blogging at Peter Frost's Newsletter. Please drop by and offer your comments:
Subjects identify the face on the left as female and the face on the right as male. The only difference is the lightness of the skin. Richard Russell, Sinha Laboratory for Vision Research, MIT.
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“The fair sex” is paler than men, who conversely are ruddier and browner than women. This sex difference seems to play a role in gender recognition and in relations between men and women, particularly in female response to darker male skin.
Women
are universally the fair sex. They are paler than men, who conversely are
ruddier and browner (Frost, 2010; Frost, 2023; van den Berghe and
Frost, 1986). This sex difference is due to the differing ways the skin’s
pigments—melanin, hemoglobin, carotene—interact with the sex hormones, either
androgens in men or estrogens in women. A hormonal cause has been shown by
studies of normal, castrated, and ovariectomized individuals, by studies of
skin reflectance at puberty, and by studies of digit ratios (Edwards and
Duntley, 1939; Edwards et al., 1941; Edwards and Duntley, 1949; Frost,
1988; van den Berghe and Frost, 1986; Manning et al., 2004).
Gender
recognition
This
sex difference is used subconsciously to recognize male and female faces
(Frost, 2011; Russell, 2003; Russell, 2009; Russell,
2010; Russell et al., 2006; Semin et al., 2018).
Specifically,
gender is identified from two aspects of facial color:
·
hue
(men are ruddier and browner)
·
brightness
(facial skin is lighter in women and contrasts more with the darker lip/eye
area).
Hue
provides the observer with a fast channel for gender recognition. If a face is
too far away or the lighting too dim, the observer will switch to the slower
but more accurate channel of brightness (Dupuis-Roy et al.,
2009; Dupuis-Roy et al., 2019; Jones et al., 2015; Nestor and
Tarr, 2008a; Nestor and Tarr 2008b; Tarr et al. 2001; Tarr,
Rossion, and Doerschner, 2002). We thus perceive skin color through the lens of
a mental algorithm that arose for gender recognition. This algorithm may
explain why lighter skin seems more feminine and darker skin more masculine
(Semin et al., 2018).
Male-female
relations
The
differing complexions of men and women play a role not only in gender
recognition but also in relations between men and women. In particular, it
seems to play a role in attraction by women to men.
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 asked to rate different levels of male ruddiness. They associated
high levels with aggression, medium levels with dominance, and low levels with
attractiveness. Unlike the participants of the first study, they may have
understood the term “attractive” in an aesthetic or even feminine sense
(Stephen et al., 2012).
Female
attraction to darker, ruddier male skin seems to be mediated by the level of
estrogen in brain tissues. This estrogenic effect is shown by two studies of
women at different phases of their menstrual cycle and by a study of preschool
children:
·
Women
were shown pairs of facial pictures that differed slightly in the lightness of
the skin, and they were asked to choose the most pleasing one. When male faces
were shown, the darker one was more strongly preferred by those women who were
in the first two-thirds of their menstrual cycle than by those in the last
third. During the first two-thirds of the cycle, the level of estrogen is high
in relation to the level of progesterone (which acts as an anti-estrogen).
During the last third, the ratio is reversed: the level of estrogen is low in
relation to the level of progesterone. There was no cyclical effect among women
judging female faces or taking oral contraceptives (Frost, 1994).
·
Women
had their brain activity measured by MRI while viewing pictures of male faces.
Their brains showed a stronger response to masculinized male faces than to
feminized ones, and the strength of their response correlated with the level of
estrogen across the menstrual cycle. In a personal communication, the lead
author stated that the faces had been masculinized by making them darker and
more robust in shape (Rupp et al., 2009).
·
Preschool
boys and girls were presented with two dolls that differed slightly in skin
color and asked to choose the “nicer” one. Their choices were recorded, as were
measurements of their body mass index and their subcutaneous fat. Doll choice
did not differ by sex. But it did differ by adiposity. Among children less than
three years old, those who chose the darker doll had significantly more body
fat than those who chose the lighter doll. In that age range, estrogen is
produced mostly in the fatty tissues, which contain an enzyme (aromatase) that
converts an androgen (androstenedione) into an estrogen (estrone) (Baird,
1976; Frost, 1989).
The doll on the right is slightly darker and ruddier than the one on the left. Among children below three years of age, those who chose the darker doll had significantly more body fat than those who chose the lighter doll. At such ages, estrogen is produced mainly in the body’s fatty tissues.
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In
other doll studies, boys and girls have similar preferences up to six years of
age (Renninger and Williams, 1966; Williams and Roberson,
1967; Williams and Rousseau, 1971). At older ages, male and female
preferences begin to diverge. When a group of American children, 3 to 8 years
of age, were presented with a white-faced puppet and a brown-faced one, the
latter puppet was more often chosen by girls than by boys, this finding being
as true for Euro-American children as for African American children (Asher and
Allen, 1969).
There
are fewer controlled studies of male response to lighter female skin. It has
been argued that the lighter skin of women mimics that of infants, whose
pinkish color is especially noticeable in darker-skinned populations and,
apparently, in other primate species. It seems to identify the primate infant
as a vulnerable being in need of protection (Alley, 1980; Booth,
1962; Jay, 1962).
In
our species, the adult female may have evolved a lighter complexion as a means
to tap into the same behavioral response, the aim being not so much to increase
male sexual arousal as to reduce male aggressiveness and stimulate feelings of
care (Frost, 2010, p. 131-136; Frost, 2023; Guthrie, 1970).
Proposed
study
First
research aim: expand on Rupp et al. (2009) by using brain MRI to
measure how women respond to male facial hue and luminosity in relation to the
levels of estrogen and progesterone across the menstrual cycle. Male facial
photos would be altered to produce different degrees of brownness, redness, and
brightness.
Second
research aim: repeat the doll study of Frost (1989) with direct
measures of estrogen and androgen levels in preschool children. This may be
difficult, given the low hormonal levels of early childhood (Baird,
1976; Klein et al., 1994).
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
Asher,
S.R. and Allen, V.L. (1969). Racial preference and social comparison
processes. Journal of Social
Issues 25(1): 157-166. https://doi.org/10.1111/j.1540-4560.1969.tb02584.x
Baird,
D.T. (1976). Oestrogens in clinical practice. In: J.A. Loraine and E. Trevor
Bell (eds.) Hormone assays and their
clinical application (p. 408). Edinburgh: Churchill Livingstone.
Booth,
C. (1962). Some observations on behavior of Cercopithecus monkeys. Annals of the New York Academy of Sciences 102(2):
477-487. https://doi.org/10.1111/j.1749-6632.1962.tb13654.x
Bruce,
V., and Langton, S. (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
Carrito,
M.L., dos Santos, I.M.B., Lefevre, C.E., Whitehead, R.D., da Silva, C.F., and
Perrett, D.I. (2016). The role of sexually dimorphic skin colour and shape in
attractiveness of male faces. Evolution
and Human Behavior 37(2): 125-133. https://doi.org/10.1016/j.evolhumbehav.2015.09.006
Dupuis-Roy,
N., Faghel-Soubeyrand, S., and Gosselin, F. (2019). Time course of the use of
chromatic and achromatic facial information for sex categorization. Vision Research 157: 36-43. https://doi.org/10.1016/j.visres.2018.08.004
Dupuis-Roy,
N., Fortin, I., Fiset, D., and Gosselin, F. (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
Edwards,
E.A., and Duntley, S.Q. (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 Duntley, S.Q. (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., Hamilton, J.B., Duntley, S.Q., and Hubert, G. (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
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. (1989). Human skin color: the sexual differentiation of its social
perception. Mankind Quarterly 30:
3-16. http://doi.org/10.46469/mq.1989.30.1.1
Frost,
P. (1994). Preference for darker faces in photographs at different phases of
the menstrual cycle: Preliminary assessment of evidence for a hormonal
relationship. Perceptual and Motor
Skills 79(1): 507-14. https://doi.org/10.2466/pms.1994.79.1.507
Frost,
P. (2010). Femmes claires, hommes foncés. Les racines oubliées du colorisme. Quebec City: Les Presses de l'Université Laval, 202
p. https://www.pulaval.com/livres/femmes-claires-hommes-fonces-les-racines-oubliees-du-colorisme
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
Frost,
P. (2023). The original meaning of skin color. Aporia Magazine, February 7.
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 Akamatsu, S. (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
Hill,
R., and Barton, R. (2005). Red enhances human performance in contests. Nature 435: 293. https://doi.org/10.1038/435293a
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
Jones,
A.L., Russell, R., and Ward, R. (2015). Cosmetics alter biologically-based
factors of beauty: evidence from facial contrast. Evolutionary Psychology 13(1): https://doi.org/10.1177%2F147470491501300113
Klein,
K.O., Baron, J., Colli, M.J., McDonnell, D.P., and Cutler, G.B. Jr. (1994).
Estrogen levels in childhood determined by an ultrasensitive recombinant cell
bioassay. Journal of Clinical
Investigation 94(6): 2475-2480. https://doi.org/10.1172/JCI117616
Manning,
J.T., Bundred, P.E., and Mather, F.M. (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
Nestor,
A., and Tarr, M.J. (2008a). The segmental structure of faces and its use in
gender recognition. Journal of
Vision 8(7): 7, 1-12, https://doi.org/10.1167/8.7.7
Nestor,
A., and Tarr, M.J. (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
Renninger,
C.A. and Williams, J.E. (1966). Black-white color connotations and racial
awareness in preschool children. Perceptual
and Motor Skills 22(3): 771-785. https://doi.org/10.2466/pms.1966.22.3.771
Rupp,
H.A., James, T.W., Ketterson, E.D., Sengelaub, D.R., Janssen, E., and Heiman,
J.R. (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.B. Adams Jr., N. Ambady, K. Nakayama, and
S. Shimojo (eds.) The Science of
Social Vision, (pp. 186-203). New York: Oxford.
Russell,
R., Sinha, P., Biederman, I., and Nederhouser, M. (2006). Is pigmentation
important for face recognition? Evidence from contrast negation. Perception 35: 749-759. https://doi.org/10.1068%2Fp5490
Semin,
G.R., Palma, T., Acartürk, C., and Dziuba, A. (2018). Gender is not simply a
matter of black and white, or is it? Philosophical
Transactions of the Royal Society B Biological Sciences 373(1752):20170126. https://doi.org/10.1098/rstb.2017.0126
Siiteri,
P.K. and MacDonald, P.C. (1973). Role of extraglandular estrogen in human
endocrinology. In: S.R. Geiger (ed.), Handbook
of Physiology, vol. II, Part 1, (pp. 615-629). Washington D.C.: American
Physiology Society, Section 7.
Stephen,
I.D., Oldham, F.H., Perrett, D.I., and Barton, R.A. (2012). Redness enhances
perceived aggression, dominance and attractiveness in men's faces. Evolutionary Psychology 10(3). https://doi.org/10.1177%2F147470491201000312
Tarr,
M.J., Kersten, D., Cheng, Y., and Rossion, B. (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., Rossion, B., and Doerschner, K. (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, https://doi.org/10.1167/2.7.598
Trivers,
R., Manning, J., and Jacobson, A. (2006). A longitudinal study of digit ratio
(2D:4D) and other finger ratios in Jamaican children. Hormones and Behavior 49(2): 150-156. https://doi.org/10.1016/j.yhbeh.2005.05.023
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
Williams,
J.E. and Roberson, J.K. (1967). A method for assessing racial attitudes in
preschool children. Educational and
Psychological Measurement 27(3): 671-689. https://doi.org/10.1177/001316446702700310
Williams, J.E. and Rousseau, C.A. (1971). Evaluation and identification responses of Negro preschoolers to the colors black and white. Perceptual and Motor Skills 33(2): 587-599. https://doi.org/10.2466/pms.1971.33.2.587
Eye colors (R.A. Sturm, University of Queensland)
Estrogen seems to favor the expression of non-black hair and non-brown eyes during fetal development. The “new” hair and eye colors are not only more frequent among women but also associated, in the case of blue eyes, with feminization of male face shape, female shoulder width, and female waist-to-hip ratio ... and with shyness in young boys.
Europeans
have a surprising variety of hair and eye colors. Their hair is not only black
but also brown, flaxen, golden, or red. Their eyes are not only brown but also
blue, gray, hazel, or green (Frost, 2006; Frost, 2022). This
differentiation from the original black hair and brown eyes seems to have begun
among women and gone farther among them.
Hair
color - Women more often have the new hair colors, particularly red and
blond. Conversely, their hair is less often black—three to five times less
often. This sex difference is natural (Hysi et al., 2018; Shekar et al.,
2008). Among Czechs, 19% of women and 11% of men have the highest gradation of
hair redness (Frost et al., 2017).
Eye color - Women more often have the new eye colors, particularly green and hazel (Frost et al., 2017). Conversely, their eyes are less often brown. The first new eye color seems to have been blue, which then differentiated to create gray, green, and hazel. Thus, “blue” in its narrow sense has lost ground among women to the derived variants of green and hazel.
Population frequencies of eye colors, for men and women (Frost et al., 2017)
The
new hair and eye colors are unusual in two ways. First, they are brighter than
the original black and brown. They thus reflect more light and have a higher
chance of standing out against the visual landscape. Second, they are
“purer”—they occupy thinner slices of the visible spectrum than the original
black and brown. In nature, pure colors are typically found in situations where
an animal or a plant has to catch attention, such as to get pollinated, to warn
predators, or to attract a mate.
This
need for attention may explain how a single hair or eye color evolved into a
diverse palette of hues. A color gets noticed not only for its brightness and
purity but also for its novelty. The last quality is frequency-dependent. If a
noticeable color becomes too frequent in a population, it thereby becomes less
noticeable and, hence, less novel. The desire for novelty is now reoriented
toward less frequent colors, including those that have recently appeared
through mutation. Thus, over successive generations, the population will
accumulate more and more color variants. This is likely how hair and eye color
became polymorphic (see Note #1).
Again,
the evidence seems to point to women being the main target of this selection
for brighter, purer, and more novel colors. One piece of evidence is the higher
frequency of the new hair and eye colors in the female population. Another is
the role of estrogen in this sex-linkage. The female hormone seems to favor the
expression of non-black hair and non-brown eyes during fetal development.
Red
is the hair color that differs the most in frequency between women and men. Red
hair should therefore be most clearly associated with increased exposure to
estrogen during fetal development. This hypothesis is supported by the higher
incidence of estrogen-dependent diseases in redhaired women. According to a
health survey of over seven thousand people, male redheads are as healthy as
other men, doing better on average in three categories and worse in three.
Female redheads, however, do worse on average than other women in ten
categories and better in only three. They are especially prone to four types of
cancer: colorectal, cervical, uterine, and ovarian—three of which are
estrogen-dependent (Frost et al., 2017). Being both female and red-haired
therefore generates the highest level of risk for estrogen-dependent diseases,
probably because of the combined effect of these two risk factors.
In
sum, the new hair and eye colors were favored by a selection pressure that
acted primarily on European women, with European men acquiring them as a
side-effect (since the new alleles are only partly sex-linked). The selection
was specifically for eye-catching qualities—brightness, spectral purity, and
relative novelty.
This
looks like sexual selection, but why would women have a greater need to get
noticed on the mate market? Usually, it is the other way around, both for
humans and for mammals in general. Females are less available for mating
because of the limitations of pregnancy, lactation, and early infant care.
Conversely, males are more available, and thus often have more than one mate at
any one time. That was, in fact, the situation of most humans in prehistory.
But that situation changed as they expanded their range out of the tropics and into
more seasonal environments. At higher latitudes, proportionately fewer men were
available for mating at any one time. There were two reasons:
·
Polygyny
was more costly for men. With men specializing in hunting and women in
gathering, women became dependent on men during winter—since there was little
food to be gathered. Men thus had to bear a greater share of food provisioning,
with the result that polygyny became impossible for all but the ablest hunters.
·
Death
rates were higher for men than for women. Because men had to hunt for more food
and over longer distances, they suffered a higher death rate at younger ages.
They were thus fewer in number overall.
Male
scarcity was most acute in an environment that no longer exists: the
steppe-tundra of the last ice age, essentially the vast plains stretching from
the Baltic to western Siberia. That environment supported large herds of
reindeer and other herbivores, which could in turn support a large human
population. But at a cost: women depended almost entirely on their hunting
husbands for food, and those hunters had to cover long distances without
alternative food sources, thus risking death from starvation or exposure. The
result was an imbalance in the operational sex ratio: too many women for too few
men, and strong selection for women with eye-catching features (Frost,
2006; Frost, 2022; Frost, 2023).
Proposed study
The
aim here is to determine whether the ratio of estrogens to androgens in fetal
tissues influences the development of hair and eye color. One way would be to
measure the “digit ratio”—the length of the index finger divided by the length
of the ring finger. This measure of fetal exposure to the sex hormones is
relatively inexpensive, though disputed by some researchers. The lower your digit
ratio, the more you have been masculinized by androgens during fetal
development; the higher your digit ratio, the more you have been feminized by
estrogens during fetal development. The left-hand digit ratio is associated
with prenatal and postnatal exposure to the sex hormones. The right-hand ratio
is associated much more with prenatal exposure (see Note #2).
An
unpublished study, using a sample of 644 British participants, found that the
left-hand digit ratio was significantly higher on average among individuals
with blond hair than among those with brown, red, or other hair colors. For eye
color, there was a similar but weaker relationship: the left-hand digit ratio
was higher on average among individuals with blue eyes than among those with
other eye colors.
That
study was not published because of two objections from the referees: hair
dyeing could not be excluded as a possible factor; and identification of hair
and eye color was too subjective. Yet it is difficult to see how hair dyeing or
misidentification can explain the digit ratio differences. Such methodological
problems would introduce more noise into the data and make any differences less
significant.
I
wish to see that study replicated with a more rigorous experimental design,
specifically a larger sample and narrower age range. Age interacts with the
effects of the sex hormones, i.e., prenatal effects on hair color are the
opposite of pubertal effects. Whereas women are lighter-haired than men from 17
onward, they are actually darker-haired up to the age of 14 (Steggerda, 1941).
The right-hand digit ratio should thus be better at predicting the darkening of
hair color before puberty, and the left-hand digit ratio better at predicting
the lightening of hair color after puberty.
In
addition, I wish to see whether the relationship between fetal estrogenization
and eye color explains three other relationships between non-brown eyes and
certain behavioral/physical traits:
·
Blue-eyed
boys tend to be shy. This is the “little boy blue” effect. A study of
preschoolers found more social wariness in blue-eyed boys than in brown-eyed
boys. The difference was greatest at the extremes of wariness. Among the very
inhibited boys, 13 out of 14 were blue-eyed. Among the very uninhibited, only 4
out of 10 were. There was no such relationship among the girls, whose eyes were
blue in 5 out of 9 among the very inhibited and in 6 out of 11 among the very
uninhibited (Coplan et al., 1988).
·
Blue-eyed
women tend to have narrower shoulders and lower waist-to-hip ratios. A Latvian
study found small but significant correlations between female eye color and
certain sexually dimorphic features. Shoulders were narrower and waist-to-hip
ratios lower in blue-eyed women than in brown-eyed women (Kažoka and Vetra,
2011).
· Blue-eyed men tend to have more feminine faces. This was an unintended finding of two Czech studies whose participants were asked to rate male and female facial photos. Initially, the brown-eyed male faces were rated as more dominant than the blue-eyed male faces. When, as a control, the brown-eyed faces were photoshopped to make them blue-eyed, they were still rated as more dominant. On careful examination, the originally brown-eyed faces were found to be more masculine with broader and more massive chins, broader mouths, larger noses, larger eyebrows, and closer-set eyes. The originally blue-eyed faces had smaller and sharper chins, narrower mouths, smaller noses, and greater distance between the eyes. Blue eyes were associated with a more feminine face shape only in male participants. This is perhaps because a male fetus normally does not have enough estrogen to feminize the face. If enough estrogen is present to feminize the face, there is probably enough to influence the development of eye color (Kleisner et al., 2010; Kleisner et al., 2013).
Were brown eyes associated with a different face shape because some of the brown-eyed men were partly Jewish or Roma and had a more Mediterranean appearance? In that case, face shape would have been more variable in the brown-eyed men. It was not. This explanation also fails to explain the effect of gender: why were blue eyes associated with facial feminization in men but not in women?
Averaged faces: blue-eyed men (left), brown-eyed men (right), Czech population (Kleisner et al., 2010).
The above studies suggest that the association between the "new" colors and physical/behavioral feminization is largely confined to men. (There is only a weak association between them and shoulder breadth or waist-to-hip ratio). This is probably because the feminization effects are triggered when the estrogen level has risen above a certain threshold. That threshold would already be surpassed by almost all female fetuses.
Notes
1.
Preference for rare hair colors was demonstrated by Thelen (1983), who
showed pictures of attractive women to male participants and then asked them to
choose the one they most wanted to marry. There were three series of pictures:
the first had equal numbers of brunettes and blondes; the second had one
brunette for every five blondes; and the third had one brunette for every
eleven blondes. The scarcer the brunettes were in a series, the more attractive
they seemed, i.e., each brunette had a better chance of being chosen.
Thelen’s
findings were not replicated by Janif et al. (2015), whose male
participants made their choices online, i.e., in private and on their home
computers. There was thus no control over the female images they may have
previously viewed on the same computer screen or might still be viewing on an
alternate screen or split screen. This source of unwanted female imagery
introduces noise into the data, thus increasing the minimum number of online raters
to produce replicable ratings of female facial attractiveness. Devcic et
al. (2010) report that their mean ratings of facial attractiveness did not
become stable until they had recruited 857 online raters. Popenko et al.
(2012) state that they needed a minimum of 992 online raters to achieve
stable ratings. By comparison, Janif et al. (2015) used 658 male
raters, while making their data even noisier by recruiting an ethnically
diverse pool of raters, i.e., over a third were of non-European descent. Those
raters would have tended to perceive female faces with black hair as ethnic
insiders and female faces with non-black hair as ethnic outsiders.
2.
Using a meta-study, Sorokowski and Kowal, 2023) concluded that the digit
ratio indicates only an individual’s prenatal exposure to testosterone (and
only in amniotic fluid, not in core blood). The authors, however, did not look
at the ratio of estrogens to androgens. Their exclusion of data on estrogen
levels is puzzling, since fetal exposure to estrogens is no less important than
fetal exposure to androgens.
References
Coplan,
R., B. Coleman, and K. Rubin. (1998). Shyness and little boy blue: Iris
pigmentation, gender, and social wariness in preschoolers. Developmental Psychobiology 32(1):
37-44. https://doi.org/10.1002/(SICI)1098-2302(199801)32:1<37::AID-DEV4>3.0.CO;2-U
Devcic,
Z., Karimi, K., Popenko, N., and Wong, B.J.F. (2010). A web-based method for
rating facial attractiveness. Laryngoscope
120(5), 902-906. https://doi.org/10.1002/lary.20857
Frost,
P. (2006). European hair and eye color - A case of frequency-dependent sexual
selection? Evolution and Human
Behavior 27(2): 85-103. https://doi.org/10.1016/j.evolhumbehav.2005.07.002
Frost,
P. (2022). European Hair, Eye, and
Skin Color: Solving the Puzzle. Washington: Academica Press, 169 pp., ISBN
9781680538724 https://www.academicapress.com/node/549
Frost,
P. (2023). A people of many colors. Peter
Frost’s Newsletter. January 24. https://peterfrost.substack.com/p/a-people-of-many-colors
Frost,
P., K. Kleisner, and J. Flegr. (2017). Health status by gender, hair color, and
eye color: Red-haired women are the most divergent. PLoS One 12(12): e0190238. https://doi.org/10.1371/journal.pone.0190238
Hysi, P.G., A.M. Valdes, F.
Liu, N.A. Furlotte, D.M. Evans, V. Bataille, et al. (2018).
Genome-wide association meta-analysis of individuals of European ancestry
identifies new loci explaining a substantial fraction of hair color variation
and heritability. Nature Genetics 50(5):
652-656. https://doi.org/10.1038/s41588-018-0100-5
Janif,
Z.J., R.C. Brooks, and B.J. Dixson. (2015). Are preferences for women's hair
color frequency-dependent? Adaptive
Human Behavior and Physiology 1(1): 54-71. https://doi.org/10.1007/s40750-014-0008-y
Kažoka,
D. and J. Vetra. (2011). Variations in some anthropometrical parameters of the
women with the different iris color in Latvia. Papers on Anthropology XX: 160-170. https://doi.org/10.12697/poa.2011.20.17
Kleisner,
K., T. Kocnar, A. Rubešová, and J. Flegr. (2010). Eye color predicts but does
not directly influence perceived dominance in men. Personality and Individual Differences 49(1): 59-64. https://doi.org/10.1016/j.paid.2010.03.011
Kleisner,
K., L. Priplatova, P. Frost, and J. Flegr. (2013). Trustworthy-looking face
meets brown eyes. PLoS One 8(1):
e53285. https://doi.org/10.1371/journal.pone.0053285
Popenko,
N.A., Devcic, Z., Karimi, K., and Wong, B.J.F. (2012). The virtual focus group.
A modern methodology for facial attractiveness rating. Plastic and Reconstructive Surgery
130(3), 455e-461e. https://doi.org/10.1097/PRS.0b013e31825dcb48
Shekar,
S.N., D.L. Duffy, T. Frudakis, G.W. Montgomery, M.R. James, R.A. Sturm, and
N.G. Martin. (2008). Spectrophotometric methods for quantifying pigmentation in
human hair-Influence of MC1R genotype and environment. Photochemistry and Photobiology 84(3):
719-726. https://doi.org/10.1111/j.1751-1097.2007.00237.x
Sorokowski,
P., and M. Kowal. (2023). Relationship between the 2D:4D and prenatal
testosterone, adult level testosterone, and testosterone change: Meta-analysis
of 54 studies. American Journal of
Biological Anthropology. 183(1): 20-38. https://doi.org/10.1002/ajpa.24852
Steggerda,
M. (1941). Change in hair color with age. Journal of Heredity 32(11): 402-403. https://doi.org/10.1093/oxfordjournals.jhered.a104977
Thelen,
T.H. (1983). Minority type human mate preference. Social Biology 30(2): 162-180. https://doi.org/10.1080/19485565.1983.9988531
Drainage basin of the Niger River (Wikicommons - Wizardist)
Social
complexity was more advanced, and cognitive demands higher, in West African
societies that benefited from trade via the Niger River. This was especially
true for the Igbo of the Niger Delta, who dominated trade between the coast and
the interior.
We
have identified thousands of genes whose alleles are associated with cognitive
ability, i.e., the capacity to process information, to recognize patterns, and
to solve problems (Lee et al., 2018). By finding out which alleles are present
on an individual’s genome, we can make an estimate of that person’s cognitive
ability, and that estimate will show a high correlation with performance on
tests in mathematics, reading, and science (r = 0.8). The same method can
provide an estimate of a population’s mean cognitive ability, and that estimate
will show a high correlation with the population’s mean IQ (r = 0.9) (Piffer,
2019).
Using
this method, the anthropologist Davide Piffer has estimated the mean cognitive
ability of several West African populations. Mean cognitive ability seems to
increase as you go from west to east, being lowest among the Mende of Sierra
Leone and progressively higher among Gambians, the Esan of Nigeria, and the
Yoruba of Nigeria. The Yoruba have almost the same mean as do African
Americans, who are nonetheless 20% European by ancestry (Piffer, 2021, see
Figure 7).
This
geographic pattern seems to reflect differences in societal development. From
the fourth century onward, West African societies became more complex in the
north and the east, i.e., within the drainage basin of the Niger. As trade
along that river increased in volume and value, villages grew into towns, and
social relations became more varied and complex. This social complexity was
both a cause and effect of trade. As powerful individuals acquired the
materials they needed to erect buildings, create works of art, and hold
ceremonies to legitimize their rule, they became even more powerful and, thus,
better able to purchase such materials. Social complexity was thus driven by a
positive feedback loop: elite buying power led to an increase in trade, which
in turn led to an increase in elite buying power (Frost, 2022; McIntosh
and McIntosh, 1988, p. 123).
As
social relations became more varied and complex in settlements along the Niger,
those populations had to cope with a heavier cognitive workload. The demands of
farming were giving way to those of craft production, urban architecture, and
long-distance trade. Numeracy and literacy were becoming important, as were
skills for manipulation and assemblage of various materials. Did that new
social environment select for an increase in cognitive ability?
Evidence
of high cognitive ability is especially strong among the Igbo people (formerly
the Ibo), who live at the Niger’s mouth and who have historically dominated
trade between the coast and the interior (Frost, 2022). Their children excel at
school not only in Nigeria but also in overseas communities, such as those of
the United Kingdom. They do exceptionally well on the GCSE (Chisala, 2015).
In
addition to high cognitive ability, the Igbo are said to have a certain
mindset: “the Ibo have a greater achievement motivation and are more willing to
explore new avenues of power than either the Yoruba or the Hausa.” They have “a
general belief in the possibility, indeed necessity, of manipulating one’s
world; of determining one’s own destiny; of ‘getting up’ in the world” (Slater,
1983). The earliest European observers, from the eighteenth century,
described them as “competitive, individualistic, status-conscious,
antiauthoritarian, pragmatic, and practical—a people with a strongly developed
commercial sense” (Mullin, 1994, p. 286).
Trade
thus seems to select for higher cognitive ability, either directly through new
cognitive demands (i.e., pricing, bargaining, accounting) or indirectly through
a resulting increase in social complexity. This has been the case not only
among the Igbo but also among the Ashkenazi Jews, the Parsis, and other trading
peoples (Cochran et al., 2006; Frost, 2012; Frost, 2021). As these
peoples became specialized in trade, over the past millennium or so, they
appear to have experienced a sharp rise in mean cognitive ability. These
examples of recent evolutionary change support the view that mental and
behavioral evolution did not stop back in the Pleistocene, anymore than the
evolution of outward physical traits like skin color or body shape. Cognitive
ability continued to evolve into the time of recorded history, albeit to
different extents in different human groups (Cochran and Harpending,
2009; Hawks et al., 2007; Rinaldi, 2017).
Shell vessel with leopard from Igbo-Ukwu, Nigeria, ninth century (Wikicommons). This bronze artefact, like others from the same site, has an unusually high silver content with only traces of zinc, an alloy not used in Europe or the Middle East at that time. Ancestral Igbo thus seem to have developed metallurgy on their own (McIntosh and McIntosh, 1988, pp. 120-121).
Proposed
study
The
aim is to test the hypothesis that mean cognitive ability increased to a
greater extent in those populations that were closer to the Niger, particularly
the Igbo at the Niger’s mouth, where trade led to greater social complexity and
higher cognitive demands during precolonial times.
For
this study, mean cognitive ability can be estimated from genomic data,
specifically from alleles associated with educational attainment (Edu PGS). The
alleles identified to date are only a fraction of all those that play a role in
cognitive ability, but we have identified enough of them to produce reliable
estimates of mean cognitive ability within a population. With the help of data
from history and prehistory, we could then outline the trajectories that mean
cognitive ability has followed in different West African populations.
Finally,
these hypothetical trajectories could be verified by retrieving and examining
aDNA from archaeological sites throughout West Africa. It would be particularly
interesting to determine when mean cognitive ability began to increase among
ancestral Igbo, and how fast it increased. That research aim may be
unrealistic, however, given the degradation of DNA in hot climates.
References
Chisala,
C. (2015). The IQ gap is no longer a black and white issue. The Unz Review, June 25. http://www.unz.com/article/the-iq-gap-is-no-longer-a-black-and-white-issue/
Cochran,
G., J. Hardy, and H. Harpending. (2006). Natural history of Ashkenazi
intelligence. Journal of Biosocial
Science 38(5): 659-693. https://doi.org/10.1017/S0021932005027069
Cochran,
G. and H. Harpending. (2009). The
10,000 Year Explosion: How Civilization Accelerated Human Evolution. Basic
Books: New York.
Frost,
P. (2012). Tay-Sachs and French Canadians: A case of gene-culture
co-evolution? Advances in
Anthropology 2(3): 132-138. http://dx.doi.org/10.4236/aa.2012.23016
Frost,
P. (2021). Commentary on Fuerst et al: Do Human Populations Differ in Their
Mental Characteristics? Mankind
Quarterly 62(2). http://doi.org/10.46469/mq.2021.62.2.9
Frost,
P. (2022). West Africa and recent cognitive evolution. Peter Frost’s Newsletter, November
14. https://peterfrost.substack.com/p/west-africa-and-recent-cognitive
Hawks,
J., E.T. Wang, G.M. Cochran, H.C. Harpending, and R.K. Moyzis. (2007). Recent
acceleration of human adaptive evolution. Proceedings of the National Academy of Sciences (USA) 104:
20753-20758. https://doi.org/10.1073/pnas.0707650104
Lee,
J. J., R. Wedow, A. Okbay, E. Kong, O. Maghzian, M. Zacher, et al. (2018). Gene
discovery and polygenic prediction from a genome-wide association study of
educational attainment in 1.1 million individuals. Nature Genetics 50(8): 1112-1121. https://doi.org/10.1038/s41588-018-0147-3
McIntosh,
S.K., and R.J. McIntosh. (1988). From stone to metal: New perspectives on the
later prehistory of West Africa. Journal
of World Prehistory 2(1): 89-133. https://doi.org/10.1007/BF00975123
Mullin,
M. (1994). Africa in America: Slave
Acculturation and Resistance in the American South and the British Caribbean,
1736-1831. University of Illinois Press.
Piffer,
D. (2019). Evidence for Recent Polygenic Selection on Educational Attainment
and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings
Using Recent Data. Psych 1:
55-75. https://doi.org/10.3390/psych1010005
Piffer,
D. (2021). Divergent selection on height and cognitive ability: evidence from
Fst and polygenic scores. OpenPsych.
April 3 https://doi.org/10.26775/OP.2021.04.03
Rinaldi,
A. (2017). We're on a road to nowhere. Culture and adaptation to the
environment are driving human evolution, but the destination of this journey is
unpredictable. EMBO reports 18:
2094-2100. https://doi.org/10.15252/embr.201745399
Slater,
R. (1983). Bureaucracy, Education and the Ibo: A Review. Journal of Educational Administration and
History 15(1): 46-49. https://doi.org/10.1080/0022062830150106
The State consolidates its power by monopolizing the use of violence. To this end, it will eliminate those men who use violence for personal ends. The gene pool is thus changed: directly, through the execution of violent men; and indirectly, through a new environment that makes it harder for them to live and reproduce.
What do I get for Christmas? Usually a box of chocolates. Or socks. If I had the choice, I’d rather get new scientific findings that interest me. Here is the first of several research proposals I hope will come to fruition in 2024.
Violence for me but not for thee
The State consolidates its power by monopolizing the use of violence. To this end, it will eliminate those men who use violence for personal ends, thus creating a new environment where social relations are peaceful and where disputes are normally settled through nonviolent means.
Pacification occurred slowly in Western Europe during the early Middle Ages. The obstacles were many: the rudimentary nature of law enforcement; the belief in a man's right to settle personal disputes as he saw fit; and the Church's opposition to the death penalty.
Those obstacles began to disappear in the eleventh century, when Church and State agreed on the need to punish the wicked so that the good may live in peace. Courts imposed the death penalty more and more often. By the late Middle Ages, 0.5 to 1.0 per cent of all men were put to death in each generation, with perhaps just as many dying at the scene of the crime or in prison while awaiting trial. Meanwhile, the homicide rate fell from a high of 20 to 40 homicides per 100,000 in the late Middle Ages to a low of 0.5 to 1 per 100,000 in the mid-twentieth century. The pool of violent men dried up until most murders occurred under conditions of jealousy, intoxication, or extreme stress (Frost and Harpending, 2015).
Did the high execution rate remove not only violent men but also their propensities for violence? Did the gene pool actually change? That scenario is plausible, given the moderate to high heritability of aggressive/antisocial behavior. Heritability is estimated at 40% by a meta-analysis of twin and adoption studies (Rhee and Waldman, 2002) and 96% by a twin study of 9 to 10 year-olds of diverse ethnic backgrounds (Baker et al., 2007). The higher figure has been attributed to the narrow age range and the use of a panel of evaluators to rate each subject. According to the latest twin study, the heritability is 40% among twins with different evaluators and 69% among those with the same evaluator (Barker et al., 2009). Finally, a review paper concludes that about half of the variance in aggressive behavior is genetic in origin (Veroude et al., 2015).
To what degree, then, could the high execution rate of late medieval and early modern times reduce the average man’s propensity for personal violence? I and Henry Harpending tried to model the impact of this selection pressure over successive generations. We concluded that the execution rate could explain a little over half of the decline in the homicide rate (Frost and Harpending, 2015). The rest could have less direct causes. Cultural norms must have shifted toward a more negative view of violent men, causing them to suffer rejection as marriage partners, discrimination in employment, exclusion from community activities, and “accidents.” By confining such men to the lower classes of society, which reproduced at a below-replacement rate in premodern times, this social exclusion would have reduced the propensity for male violence from one generation to the next.
It is possible that we underestimated the direct impact of the death penalty on homicides. Specifically, we may have erred in assuming that a propensity for homicide would cause a man to murder only once in his lifetime. It is more likely that the average executed offender had already killed more than one person and would have gone on to kill even more if allowed to live. Bandits often killed not only their victims but also any witnesses (Frost, 2015).
On the other hand, it is also possible that we overestimated the direct impact of the death penalty on the gene pool. Many violent men would have reproduced before running afoul of the law. Furthermore, men were not executed solely for acts of personal violence (Frost, 2015).
On this last point, we should understand the logic of medieval justice. The aim was not so much to find culprits for specific major crimes as to profile the criminally minded, often on the basis of minor offences. If you had crossed the behavioral threshold for a petty crime, it was assumed that you would more easily commit, or may have already committed, a crime of greater importance. Qui vole un œuf vole un bœuf.
In Western Europe, the homicide rate fell dramatically during late medieval and early modern times (Wikicommons - Max Roser, 2003)Proposed study
The aim is to verify the above model of “genetic pacification” by examining existing data on human DNA retrieved from medieval and post-medieval sites. The datasets would be examined for changes over time in the gene pool, specifically changes in the population frequencies of alleles associated with aggressive male behavior. This evolution would be charted from the eleventh century to the early twentieth for Western Europe or for a more limited geographic area within Western Europe, such as England.
There would be three tasks:
- locate relevant aDNA datasets (Western Europe, 11th century to early 20th)
- identify alleles that are associated with male violence, e.g., alleles at MAO-A, DAT1, DRD3, DRD4, etc. (Waldham and Rhee, 2006)
- identify changes over time in the population frequencies of such alleles
The last task would have two lines of enquiry:
How did genetic pacification relate to social class?
Today, personal violence is associated with low SES, but that association seems to be relatively recent. At first, the lower classes were the ones pacified through frequent use of the death penalty. Only later, as the death penalty gained public acceptance, did the courts impose it more and more equally on the entire population.
Initially, the courts were hindered by a widespread view of male violence as normal and virile. It was nonviolence that seemed abnormal and unmanly. Thus, in fourteenth century England, jurors were reluctant to convict murderers despite good evidence of guilt:
Because they preferred direct action and applauded self-help as a way of settling disputes, jurors were willing to acquit murderers even more freely than thieves. Most murders grew out of arguments that the villagers knew about. They assumed, along with the participants in the homicidal drama, that a good fight was an acceptable way of resolving the conflict. If someone got killed, that was understandable. (Hanawalt, 1979, p. 269)
The death penalty fell overwhelmingly on the poor and on outsiders without friends. Prominent people were more often prosecuted for homicide but seldom hanged (Hanawalt, 1979, pp. 53-54).
A similar situation prevailed in early Renaissance Venice, where noblemen felt entitled to use violence. They were the ones most likely to commit speech offenses, assaults, and rapes. Though making up only 4% of the population, they committed nearly a quarter of the recorded assaults. This positive correlation between SES and violent crime has been noted elsewhere in late medieval and post-medieval Europe (Eisner, 2003; Recueil, 2023; Ruggiero, 1980).
It is only from the nineteenth century onward that we begin to see a negative correlation between SES and violent crime, apparently due to in-migration from less pacified societies. With the shift from family workshops to industrial capitalism, the workforce was no longer confined to family members or even local people. Employers could cut labor costs by recruiting farther afield, typically from regions of labor surplus on the periphery of the Western world … or outside it entirely. Such workers came from regions where men had to use violence on a regular basis because the State was weak or nonexistent.
If the aDNA datasets include information on social class, it would be interesting to see how and when the correlation between SES and violent crime “flipped.”
How did genetic pacification relate to other trajectories of mental/behavioral evolution?
In this line of enquiry, the aim is to determine whether genetic pacification went hand in hand with other mental/behavioral changes, particularly an increase in cognitive ability (as measured by alleles associated with educational attainment - Edu PGS). Cognitive evolution may have required the establishment of social peace, notably to facilitate trade and other aspects of social complexity. Alternatively, the relationship may have been less direct, with social complexification acting as a shared selection pressure.
This subject has already attracted the interest of at least four researchers:
Davide Piffer
This archaeogeneticist is examining aDNA to reconstruct the cognitive evolution of Western Europe during medieval and post-medieval times (Kirkegaard, 2023).
Gregory Clark
This economic historian has documented the growth of the English middle class, which, from the twelfth century onward, made up a growing proportion of the English population. He argues that this demographic change led to a behavioral change: "Thrift, prudence, negotiation, and hard work were becoming values for communities that previously had been spendthrift, impulsive, violent, and leisure loving” (Clark, 2007, p. 166; Clark, 2009; Clark, 2023; Frost, 2022).
Georg Oesterdiekhoff
This sociologist has argued for a similar mental and behavioral evolution across Western Europe during late medieval and post-medieval times. He believes that this evolution recapitulated Jean Piaget’s stages of cognitive development:
Medieval times - most people fail to develop mentally beyond the stage of preoperational thinking. They can learn language and social norms but their ability to reason is hindered by cognitive egocentrism, anthropomorphism, finalism, and animism.
Sixteenth century onward - more and more people reach the stage of operational thinking. They can better understand probability, cause and effect, and the perspective of another person, whether real or hypothetical (Oesterdiekhoff, 2023).
Université catholique de Louvain
A research team at this institution is seeking to “determine the role of elite knowledge and upper-tail human capital in the rise of the West between the period 1000 and 1800 CE.” During that period, the smart fraction grew in size until it reached a critical mass where thinkers were no longer isolated individuals but rather communities of people who could interact in clubs, salons, coffeehouses, and debating societies. This intellectual ferment, “the Enlightenment,” occurred across all domains of intellectual production, not only the sciences but also literature, music, and the arts (de Courson et al., 2023).
The above research team “will study a variety of published source materials to create a geographical grid of the density, composition and quality of upper-tail human capital across time. [The team] will also develop a new theory to understand how codified knowledge and practical skills interact and how ideas spread” (Université catholique de Louvain, 2023).
References
Baker L. A., K.C. Jacobson, A. Raine, D.I. Lozano, and S. Bezdjian. (2007). Genetic and environmental bases of childhood antisocial behavior: A multi-informant twin study. Journal of Abnormal Psychology 116: 219–235. https://psycnet.apa.org/doi/10.1037/0021-843X.116.2.219
Barker E. D., H. Larsson, E. Viding, B. Maughan, F. Rijsdijk, N. Fontaine, and R. Plomin. (2009). Common genetic but specific environmental influences for aggressive and deceitful behaviors in preadolescent males. Journal of Psychopathology and Behavioral Assessment 31: 299–308. https://doi.org/10.1007/s10862-009-9132-6
Clark, G. (2007). A Farewell to Alms. A Brief Economic History of the World. Princeton University Press: Princeton.
Clark, G. (2009). The domestication of man: the social implications of Darwin. ArtefaCToS 2: 64-80.
Clark, G. (2023). The inheritance of social status: England, 1600 to 2022. Proceedings of the National Academy of Sciences 120(27): e2300926120 https://doi.org/10.1073/pnas.2300926120
de Courson, B., V. Thouzeau, and N. Baumard. (2023). Quantifying the scientific revolution. Evolutionary Human Sciences, 5, E19. https://doi.org/10.1017/ehs.2023.6
Eisner, M. (2003). Long-term historical trends in violent crime. Crime and Justice 30: 83-142. https://doi.org/10.1086/652229
Frost, P. (2015). Supplement to: Western Europe, State Formation, and Genetic Pacification. March. https://www.researchgate.net/publication/274251025_Supplement_to_Western_Europe_State_Formation_and_Genetic_Pacification
Frost, P. (2022). Europeans and recent cognitive evolution. Peter Frost’s Newsletter, December 12.
Frost P., and H. Harpending. (2015). Western Europe, state formation, and genetic pacification. Evolutionary Psychology 13(1): 230-243. https://doi.org/10.1177%2F147470491501300114
Hanawalt, B.A. (1979). Crime and Conflict in English Communities 1300-1348. Cambridge (Mass.): Harvard University Press.
Kirkegaard, E.O.W. (2023). Ancient genomes discussion with Davide Piffer and Emil at Lake Como. YouTube
Oesterdiekhoff, G.W. (2023). Was pre-modern man a child? The quintessence of the psychometric and developmental approaches. Intelligence 40: 470-478. https://doi.org/10.1016/j.intell.2012.05.005
Recueil, C. (2023). Jailbirds of a feather flock together. Aporia Magazine, October 5.
Rhee S.H., and I.D. Waldman. (2002). Genetic and environmental influences on antisocial behavior: A meta-analysis of twin and adoption studies. Psychological Bulletin 128: 490–529. https://psycnet.apa.org/doi/10.1037/0033-2909.128.3.490
Ruggiero, G. (1980). Violence in Early Renaissance Venice. Rutgers University Press.
Université catholique de Louvain. (2023). Did elite human capital trigger the rise of the West? Insights from a new database of European scholars. European Research Council. Grant agreement ID: 883033 https://doi.org/10.3030/883033
Veroude, K., Zhang-James, Y., Fernàndez-Castillo, N., Bakker, M.J., Cormand, B., and Faraone, S.V. (2016). Genetics of aggressive behavior: an overview. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 171(1): 3-43. https://doi.org/10.1002/ajmg.b.32364
Waldman, I.D., and S.H. Rhee. (2006). Genetic and Environmental Influences on Psychopathy and Antisocial Behavior. In C. J. Patrick (Ed.), Handbook of psychopathy (pp. 205–228). The Guilford Press.