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A Facial Attractiveness Account of Gender Asymmetries
in Interracial Marriag e
Michael B. Lewis*
School of Psychology, Cardiff University, Cardiff, United Kingdom
Abstract
Background:
In the US and UK, more Black men are married to White women than vice versa and there are more White men
married to Asian women than vice versa. Models of interracial marriage, based on the exchange of racial status for other
capital, cannot explain these asymmetries. A new explanation is offered based on the relative perceived facial attractiveness
of the different race-by-gender groups.
Method and Findings:
This explanation was tested using a survey of perceived facial attractiveness. This found that Black
males are perceived as more attractive than White or East Asian males whereas among females, it is the East Asians that are
perceived as most attractive on average.
Conclusions:
Incorporating these attractiveness patterns into the model of marriage decisions produces asymmetries in
interracial marriage similar to those in the observed data in terms of direction and relative size. This model does not require
differences in status between races nor different strategies based on gender. Predictions are also generated regarding the
relative attractiveness of those engaging in interracial marriage.
Citation: Lewis MB (2012) A Facial Attractiveness Account of Gender Asymmetries in Interracial Marriage . PLoS ONE 7(2): e31703. doi:10.1371/
journal.pone.0031703
Editor: Etienne Joly, Universite
´
de Toulouse, France
Received May 25, 2011; Accepted January 17, 2012; Published February 9, 2012
Copyright: ß 2012 Michael B. Lewis. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The author has no support or funding to report.
Competing Interests: The author has declared that no competing interests exist.
* E-mail: LewisMB@cf.ac.uk
Introduction
The majority of marriages in the US and the UK are between
people of the same racial background (race is used here to indicate
a broad group of ethnicities as employed in the US census). The
incidence of interracial marriage, however, is increasing particu-
larly in the US since the repeal of the anti-miscegenation laws in
1967 [1]. In the US, over 4% of marriages can be classified as
mixed race (source: US Census Bureau, 2006). In the UK the
figure is more like 2% (source: Census UK, 2001). Of particular
interest here are the clear patterns that emerge from the analysis of
which interracial marriages occur more often than others.
A striking aspect of the data on interracial marriages is the size
of the gender asymmetries [1–3]. These asymmetries appear
robust across time and culture. Details of these asymmetries are
shown in Table 1 based on census data from the UK and USA for
White, Black and Asian racial groups. If we focus upon marriages
between White and Black people then we observe that there are
over twice as many marriages between Black men and White
women than between White men and Black women in the US. An
observed consequence of this pattern is a decline in marriage rates
for Black women, which has been described in the US as the
‘marriage squeeze’ [4]. The asymmetry is smaller in the UK but
still present.
The gender asymmetries are even larger for marriages that
include Asian and White people. In this situation, however, it is the
number of White men marrying Asian women that is over twice
the number of White women marrying Asian men. The largest
asymmetry shows that marriages between Black men and Asian
women in the US outnumber those between Asian men and Black
women by about five to one.
The current paper aims to explain the observed patterns of
gender asymmetry in interracial marriage. First, existing accounts
for the phenomenon are considered. One such account is that
there are differences in societal pressures for males and females.
Economics-based marriage models are considered but these
require different statuses for different races and it is argued that
they fail to capture the details of asymmetries. An explanation
based on height differences is also explored but it is shown through
data modelling how this can only explain part of the observed
asymmetries. Finally, a new explanation based on facial attrac-
tiveness differentials between races for different genders is
explored. For this to explain the patterns of asymmetries observed,
however, a particular pattern of facial attractiveness must be
present among the different races. An experiment is reported that
acquired the necessary facial attractiveness data to explore this
model further. From these data, the model was implemented in
order to test whether it could explain the patterns of gender
asymmetry observed in interracial marriage. A speculative
evolutionary account is also provided as to why it is the case
that differences in the perceived attractiveness of genders of
different races occur.
Societal pressures
One possible explanation for gender asymmetries in interracial
marriage is that the there are differential societal pressures upon
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the different genders to marry within their ethnic group. A
suggested example might be that males from the Indian sub-
continent living in the UK might be freer to interact with the
White community than females from the same community [5].
While there probably are some societal pressures acting against
the formation of interracial marriages, this explanation for the
observed asymmetries only works if these act differently upon male
and female members of the same racial group. It has been found,
however, that there is no evidence of differential societal pressures
on East-Asian or Black men and women regarding interracial
marriage [6]. These racial groups, together with White people,
form the focus of analysis here and so societal pressures do not
explain the patterns of data seen.
Modelling interracial marriage
Models of marriage choice tend to see partner selection as
operating within a ‘marriage market’ such that it improves each
party’s situation. Social-exchange theory of marriage proposes that
there can be a trade off between one party’s economic wealth and
the other’s status [7]. This theory has been used to explain why a
rich but less physically attractive person might marry an attractive
but poorer person [8]. Social exchange theory is used to explain
why people tend to marry people who are similar in terms of their
educational and/or socioeconomic background [9].
In relation to interracial marriage, race is often described as a
marker of status in the marriage marketplace and examples are
quoted where a wealthy Black man might marry a poorer White
woman [10]. Based on this theory, it has been argued that interracial
marriage occurs primarily were the White woman ‘marries up’ in
socioeconomic status [11]. The claim is that the social exchange that
takes place is between the woman’s racial status for the man’s
socioeconomic status or wealth. As men may be economically more
mobile than women, then this could be used to explain the gender
asymmetries in Black/White interracial marriage.
This idea of race as being a status factor in the social exchange
of marriage has been explored empirically [12]. It has been
suggested that when people are presented with mixed-race
couples, they are more willing to accept a Black man with an
unattractive White woman than a Black man with an attractive
White woman. It was concluded from this that people felt more
comfortable when the low status man (arguably the Black man
rather than a White man) was paired with the low status woman
(arguably the less attractive woman). It was argued that this
experiment supports the notion that racial status has objective
value within the marriage market and there is a clear racial
hierarchy with White people above Black people. The results of
this study, and hence the conclusions, are limited by a number of
facts: only White participants were tested on their opinions; only a
Black male was used as the male partner, and the Black male in
the experiment did not vary in attractiveness. The results,
therefore only tell us about the hierarchy of racial status as
perceived by White people when looking at Black males.
Relationships between Black females and White males were not
assessed and opinions of Black participants were not assessed.
Incorporating race as status into the social exchange theory of
marriage is problematic. The origins of this social-exchange theory
of marriage stem from caste systems of India [13]. In this system
there is an agreed hierarchy between the different castes. This
system does not translate easily to the American or British society
in which there is no clearly defined hierarchy of ethnicities.
Members of ethnic or racial groups would not consider their group
to have legitimately a lower status than any other group (or else
there would not have been the African-American Civil Rights
Movement). Explaining interracial marriage in the US or UK in
terms of social exchange, where one person’s White status is
exchanged for wealth or security, can be argued to be a White-
centric myth. Research supports this social exchange to be a myth
because interracial marriages show the same degree of similarity
between partners’ status as same-race marriages [14]. Hence,
there is no evidence for racial status to be a commodity for social
exchange in these cultures.
While it is accepted that there may be social exchange in
marriage, it is argued here that race does not need to enter into
this exchange in a hierarchical manner. As will be shown below,
the gender asymmetries in interracial marriage can be explained
without there being a racial hierarchy.
Table 1. Measuring the size of the gender asymmetries in interracial marriage.
XY
Percentage of
X
males
marrying
Y
females
Percentage of
X
females
marrying
Y
males
Size of asymmetry (largest
divided by smallest)
Average asymmetry (from both
complimentary measures)
UK (Source: Census UK, 2001)
Black White 17.60 13.27 1.32 1.46 Black Male Bias
White Black 0.15 0.24 1.60
White Chinese 0.11 0.04 2.75 2.60 White Male Bias
Chinese White 9.57 23.47 2.45
Black Chinese 0.115 0.05 2.30 2.30 Black Male Bias
Chinese Black 0.14 0.32 2.29
USA (Source: US Census, 2006)
Black White 6.61 2.85 2.32 2.38 Black Male Bias
White Black 0.23 0.56 2.43
White Asian 1.03 0.34 3.03 2.84 White Male Bias
Asian White 6.48 17.11 2.64
Black Asian 0.79 0.15 5.27 5.14 Black Male Bias
Asian Black 0.22 1.10 5.00
Each asymmetry is shown as a function of total marriages for each race involved before an average is found. Summary data were taken from Belot and Fidrmuc (2009).
doi:10.1371/journal.pone.0031703.t001
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Another model of interracial marriage is the equilibrium sorting
explanation [15]. Applying game theory, people select mates such
that they maximise their productivity and, through equilibrium
sorting, they maximise the productivity of the system. On this
model, there is a cost associated with interracial marriage, but this
can be outweighed by the gains of having a partner with high
human capital (e.g., wealth or potential for wealth). A consequence
of this is that individuals who choose to marry outside of their race
will, on average, be more highly educated [1]. While this model is
useful for explaining some of the data, there are two problems with
this model. First, the data from education levels do not show
interracial marriage to be more common among more educated
people either in the US [14] or the UK [16]. Second, as the cost of
interracial marriage applies across men and women, it does not
explain the large asymmetries observed for interracial marriages.
As we will see later, however, a variation of this explanation is able
to capture the observed patterns of interracial marriage if we
incorporate facial attractiveness into the model.
Is it just height differenc es?
In spite of the decades of modelling of marriage data, none of
the traditional economic models deal unequivocally with the issue
of gender asymmetry in interracial marriage. One recent proposal,
however, has been offered that does provide a possible
explanation. This explanation is simple, elegant and is based on
differences in the human anatomy between the races concerned.
It has been proposed that the gender asymmetries in interracial
marriage can be attributed to differences in average heights of the
race-by-gender groups [6]. It has been observed that Blacks, on
average, are taller than Asians (based on the health survey for
England, 2004) and this may affect mate choice. It is proposed that
there is a socially imposed ‘male-superior norm’ such that the male
should not be shorter than the female in a marriage and this factor
alone can affect the patterns of intermarriage. For White females,
this norm will not have much of an effect on their choice of White
or Black partners, but, as Asian men tend to be shorter, the male-
superior norm will reduce the number of potential Asian partners.
This means that, all other things being equal, height will discount
more potential Asian partners than either Black or White partners.
There would, therefore, be a bias against White women marrying
Asian Men that is not present for Asian women marrying White
men. The same norm could also explain the Black/White
asymmetry if Black women were taller than White women. The
consequence would be that height would act to discount more
Black than White women as potential partners for White men
leading to the observed asymmetry.
Although this is an elegant explanation, there are limitations to
how well it can explain the gender asymmetry in terms of height
alone. There is little difference in the height of Black and White
males or Black and White females and even the difference between
heights between White and Asian people cannot explain all of the
asymmetry. This can be demonstrated using Monte Carlo style
analysis of population patterns.
To show the limitation of the height explanation, statistical
modelling of the height data from the Health Survey for England
(2004) was carried out. Random pairs of males and females were
generated according to their height distributions for Black, White
and Chinese people. Comparing these random pairs found few
occasions when the women is taller than the man. Table 2 shows
that the woman being taller than the man does occur more often
when looking at Chinese men paired with White women: In this
case, 18% of pairings would violate the male-superior norm. Given
that in the UK there are two and a half times as many White males
marrying Chinese females than the other way around, a reduction
of 18% cannot entirely explain this pattern.
The comparison between the Black and White pairings is also
difficult to reconcile with the observed data. A typical White man
is shorter than a typical Black woman 10.4% of the time whereas a
typical Black man is shorter than a typical White woman 10.0% of
the time. In this case, the male-superior norm can only explain a
tiny proportion of the gender asymmetry observed in intermar-
riage between Black and White people.
While difference in height between the different races can
explain some of the observed gender asymmetry in interracial
marriage, it does not explain the strength of the patterns observed.
Height may certainly have a role to play but there must be other
factors also contributing to interracial partner choice patterns.
An explanation based on facial attractiveness
There exists a lay understanding that choosing who we marry is
related to physical attraction. This relationship is supported by
psychological research into physical attraction on mate selection
particularly with reference to identifying good genes [17]. There is
clear and unequivocal evidence that physical attractiveness is the
primary mating asset for women such that attractive women are
preferred over unattractive women [18]. For men however, status
is an important mating asset although physical attractiveness can
still carry some weight [19]. Much of the evidence for the
differences in preferences between men and women, however,
comes from self reports and reflections rather than actual
preferences at the point of marriage. Where marriage couples
are asked about their important considerations in marriage
partners, terms such as romantic love and a desire to set up
home are more important and there is little difference between the
sexes [20]. In fact, men and women may be behaving very
similarly in terms of their marriage partner selection.
The focus here is facial attractiveness of both the males and
females. Facial attractiveness of a person is indicated by the rated
attractiveness of a person from a portrait. A person’s facial
attractiveness is typically the first judgement that another person
makes of them from which it can be judged whether they are likely
to ultimately enter into a relationship with them. These kinds of
Table 2. Explaining the interracial marriage gender asymmetries using height.
White Male 175.3 cm (7.3) Black Male 174.4 cm (7.2) Chinese Male 170.8 cm (7.4)
White Female 161.6 cm (6.8) 8.6% 10.0% 18.1%
Black Female 162.9 cm (6.6) 10.4% 12.0% 21.4%
Chinese Female 157.9 cm (6.0) 3.3% 4.0% 8.8%
The table headings show the average heights (and standard deviations) for the difference racial-by-gender groups. The entries in the table show an estimated
percentage of pairings that would result in the male being shorter than the female, hence violating the proposed male-superiority norm.
doi:10.1371/journal.pone.0031703.t002
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portraits are widely used by dating agencies as a method for people
to select potential partners and so have face validity in terms of
being used to select marriage partners.
Facial attractiveness is not necessarily the same as physical
attractiveness. The latter may include measures of bodily
attractiveness such a waist-hip-ratio for women. Further, facial
attractiveness, as derived from a natural portrait, may contain
status information or information about the person’s personality or
at least the personality the person wishes to portray. In this way,
facial attractiveness appears to capture elements of the reported
preferences for both males and females.
Facial attractiveness receives little attention in models of the
marriage market in favour of more tangible assets. Here, it is
proposed that measurable facial attractiveness differences between
different races can be used to explain the interracial marriage
gender asymmetry. Further, it can do so without treating males
and females differently and without enforcing a racial hierarchy.
Studies suggest that there is considerable agreement regarding
what makes a face attractive [21]. Much of this agreement is
common even across cultures [22]. Further, just as not all races are
equal in terms of their average height, not all races of people are
equal in terms of their average rated facial attractiveness. Such
differences may affect any model of marriage but here a simple
model is presented in order to further investigate the effects that
differences in attractiveness might have.
The model of marriage proposed here is based upon contact, cost
and chance. The first principle is that people tend to marry people
that they come into contact with. The degree of separation between
races, therefore, explains why the majority of marriages are
intraracial. This contact principle also accounts for why married
couples tend to have a similar economic status or educational
background to each other [14] as such people are more likely to
come into contact with each other. The second principle is that,
although marriage is desirable, there is a degree of cost associated
with any marriage. There are two parts to this cost: First there is the
exclusivity of the relationship meaning that other marriages are no
longer possible (at least in the short term). The size of this cost will be
a factor of the attractiveness of the potential partner such that the
cost is lower if the potential partner is more attractive as there will be
fewer more attractive partners that the person will be missing out
on. The second part of the cost comes from the racial or ethnic
difference between the potential partners. This is similar to the cost
in the equilibrium sorting model and is related to the degree of
dissimilarity between the racial or ethnic backgrounds of the two
potential partners. This racial difference cost will be related to the
acceptability of the racial pairing for that culture. This cost principle
can account for the increasing trend in interracial marriage in the
US during the latter part of the twentieth century as racial distance
decreases [23]. The final principle is that there is an element of
chance in any pairing becoming a married couple. That is, given
that two people have come into contact, there is a chance that they
will get married and this is a probabilistic function influenced by the
cost of that marriage to each partner.
One observation about this model is that racial distance is
always symmetrical and is not affected by gender. The racial
distance will be the same regardless of whether a Black man is
paired with a White women or a White man is pair with a Black
women. In this way, it overcomes the problems of the social-
exchange theory in which a particular hierarchy of races is
required because all races and both genders have equal status. The
implementations of the model reported here also used a fixed cost
for all interracial marriage regardless of which racial boundaries
are crossed. In the general form of the model, the cost could be
related to how dissimilar the racial groups are.
A second observation is that a person’s own attractiveness does
not affect their decision to marry another person. A consequence of
this is that an attractive person paired with an unattractive person
will be more likely to marry than two unattractive people. From the
point of view of the attractive person, however, they will still be
more likely to marry an attractive person given the probabilistic
nature of the chance part of the model. Unattractive people will still
be able to marry but it would require more pairings, each pairing
having a particular probability of success – albeit, a probability that
would always be higher if they were more attractive. In this way, a
degree of attractiveness sorting would take place. Evaluations of the
marriage photographs shows that the correlation between the
attractiveness of married couples is around r = 0.34 [24] and below
it is demonstrated how the model predicts similar correlations.
Importantly, the model can account for the gender asymmetries
because those individuals who are more attractive are more likely
to be able to overcome the cost associated with interracial
marriage. If there are differences between the relative attractive-
ness of the genders between different races then asymmetries in
interracial marriage will follow. If Black men are perceived as
being more attractive than White men and White women are
perceived as more attractive than Black women then the type of
asymmetry observed in interracial marriages would be a direct
consequence of the model. Of course, the explanation only works
if the pattern of attractiveness is as described.
Data from previous studies support the required pattern of facial
attractiveness over different racial groups. Black men were rated as
being significantly more attractive than White men; however, little
difference was found between women [25]. A follow-up study
found that White women were rated as more attractive than Black
women although this was not significant once a conservative
Bonferroni correction had been applied [26]. Further experimen-
tation is required, therefore, to clarify these findings.
The model of gender asymmetries in interracial marriages can
also be applied to marriages involving Asians as well as Black and
White people. The asymmetry here is that there are more female
Asians than male Asians involved in the interracial marriages. This
could be explained if it transpired that female Asians were more
attractive than female Black or female White people on average
and if male Asians were less attractive than Black or White males.
This kind of data does not currently exist (although one study did
show a difference in attractiveness but this was based on a single
female example of each racial group [27]). If the attractiveness
explanation for gender asymmetries is to stand, then it is necessary
to determine whether there really are differences between average
attractiveness for people of different races.
Methods
The current experiment aimed to establish the relative
attractiveness of individuals of three broad racial groups. These
attractiveness ratings were made by people of a similar age to the
individuals and of an opposite sex. The raters came from a range
of different ethnicities and any differences in their ratings of
different races were considered separately.
Ethics
The research was approved by Cardiff University School of
Psychology research ethics committee. Informed written consent
was obtained from all participants.
Participants
Forty undergraduates studying at Cardiff University took part as
face raters either for course credit or for a small cash payment.
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Twenty were female and twenty were male and all were between
the ages of 18 and 30 years. Of the male raters, 15 were White, 2
were Black and 3 were Asian. Of the female raters, 14 were White,
3 were Black and 3 were Asian.
Stimuli
Images of 600 people were used. Half were male. The images
were collected from the social-networking website Facebook.com.
Images were selected from people who were members of groups
associated with further and higher education bodies either in the
UK (for White faces), sub-Saharan Africa (for Black faces) and East
Asia (for Asian faces). These images were collected by a naive
research assistant who selected images according to a set of
criteria: Images had to show a clear view of a single person that
was of sufficient quality such that it would be recognisable by a
friend. If the face in the image had a weird expression or was
possibly of a race other than the main race for the region then it
was rejected. The face was also rejected if the person depicted
looked to be under 18 or over 30 years old.
This method of stimulus generation was employed as being the
best of those available to produce a representative set from each
population. By using images that the individual freely posted on
the internet to represent themselves, we avoid many of the
problems associated with self selection had we used standardised
photographs: that is, individuals who are particularly self conscious
about their appearance will not volunteer. Selection bias is likely to
be less true for facebook images as posting an image of oneself is
what everyone else is doing. There would, of course, be a bias to
select a photograph that presents one’s most positive image but
this bias would be present across all races and genders. One might
assume that if these people were to use online dating websites then
they would use an image similar to their facebook image in their
profile. As such, this means that the stimuli employed are similar to
the information presented during courtship, which is appropriate
as marriage is the focus of the research.
One potential problem with this set of stimuli is the possibility
that one group might be more reluctant to post images of
themselves if they are less attractive than another. If this were the
case then we would expect to see more facebook images that do
not contain a face of the person (it might be left blank, be a scene
or a cartoon character). Re-examination of the sources of the
images used revealed that less than 1% of facebook accounts did
not include a face of a person.
Procedure
Participants were presented with 300 opposite-sex faces, one at
a time via a computer monitor. They rated each of these faces on
their attractiveness. The faces were presented in a random order
and the rating scale went from 1 (unattractive) to 10 (attractive).
Results
The responses of all participants to all of the faces are available as
a supplementary file called Data S1. Table 3 shows the summary
means and standard deviations for the sets of faces. For the female
faces, Asian faces were rated as being most attractive followed by
White and then Black. A three-way ANOVA showed these
differences to be significant (F(2,297) = 11.861; p,.001) with all of
the comparisons significant ( p’s,0.05). For the male faces, Black
faces were rated as being most attractive followed by White and
then Asian. A three-way ANOVA showed these differences to be
significant (F(2,297) = 63.305; p,.001) with all of the comparisons
significant (p’s,0.05).
It may be the case that the ethnicity of the raters influenced
their ratings. This was investigated using a by-subjects analysis.
Figure 1 shows that the same ordinal pattern was found when the
data were split according to the participants’ ethnicity. Two
ANOVAs were conducted on the data sets in order to explore the
possibility of there being an interaction between race of the rater
and race of the face being rated. These interactions were not
significant (female faces: F(4,34) = .403; p..05, male faces:
F(4,34) = .175; p..05).
Discussion
The results replicate earlier findings that Black men are rated as
more attractive than White men. It was further found that Asian
men were rated as less attractive than either other race. For
women the pattern was reversed with Asian women being rated as
most attractive followed by White women and then Black women.
The patterns observed occurred regardless of the race of the
person doing the ratings.
It is argued here that this pattern of attractive ratings is sufficient
to explain the gender asymmetries in interracial marriage. In order
to explicitly explain this argument, a model of marriage based on
attractiveness was tested using the attractiveness data acquired
here.
Data modelling
An implementation of the attractiveness-based marriage model
was carried out in which the 10,000 individuals (half female and
half male) were randomly assigned to being Black, Asian or White.
The attractiveness of each group of individuals was randomised
such that they had the same mean and standard deviation as
observed in the experiment above.
During an iteration of the model, a random unmarried male
and a random unmarried female were selected. If these were of
different races then a racial distance value was subtracted from
their attractiveness to indicate the cost of crossing racial
boundaries. The probabilistic function association with the chance
element of the model was implemented by subtracting the
attractiveness of another random unmarried person of the same
gender from the resulting values. If the resulting values were
greater than some arbitrary threshold for both the male and the
female then the marriage was considered to take place. A new pair
of individuals would then be considered in the same way for the
next iteration. The model was iterated until 90% of the individuals
were married. At this point the model was assessed as to how many
interracial marriages had occurred and what patterns were more
common when they did occur. From this information, the
asymmetries of interracial marriages were measured for the model.
The model was implemented several times with varying values
taken for the threshold (varying between 0 and 2) and the racial
distance (varying between 0.01 and 2). The parameters were
Table 3. Findings from the current research.
Male faces rated by females Female faces rated by males
White 4.568 (0.869) 5.065 (1.347)
Black 4.994 (0.798) 4.720 (0.732)
Asian 3.781 (0.653) 5.511 (1.104)
The means (and standard deviations) for the attractiveness ratings for the sets
of 100 faces from each group. The scale ranged from 1 (unattractive) to 10
(attractive).
doi:10.1371/journal.pone.0031703.t003
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optimised to account for the patterns of asymmetries found in the
UK population. A threshold of 0.65 and a racial distance of 0.65
gave the following pattern: the Black/White asymmetry was 1.41;
the White/Asian asymmetry was 2.59, and the Black/Asian
asymmetry was 2.35. These figures compare well with those in
Table 1 for actual asymmetry in the UK.
The parameters of the model were also optimised to account for
the patterns of asymmetries found in the US population. A
threshold of 0.45 and a racial distance of 1.00 gave the following
pattern: the Black/White asymmetry was 1.67; the White/Asian
asymmetry was 3.57, and the Black/Asian asymmetry was 5.41.
While these numbers are similar in relative order and approximate
size to those in Table 1 for US data, there remains considerable
difference that could not be reduced by further changes to the
parameters of the model.
There are at least three possible reasons why the model fits the
UK data better than the US data. First, the ratings used were from
people based in the UK and there could be cultural differences in
ratings between the UK and the US. Second, the US values in
Table 1 are calculated using figures for all Asians whereas the data
used in the model was based on East-Asians. Third, many of the
Black people that make up the samples in the US data may have
been mixed-race (the US census does not offer a mixed-race
category). It has already been demonstrated that mixed race
people are rated as more attractive than Black or White people
[25] and so this could affect the fit of the model. Regardless of the
mismatch between the model and the US data, it remains the case
that a model of marriage based just on race and attractiveness is
able to capture the general patterns of gender asymmetry in
interracial marriage observed in the US.
The model could be further interrogated with regards to the
nature of the pairs in made. The correlation between the
attractiveness of the pairs of partners put together by the model
was found for the different implementations. An implementation
with no racial differences (and a threshold set to zero) found a
correlation of r = 0.32. In the model of the UK data, it was r = 0.49
whereas for the model of the US data it was r = 0.40. These are all
similar in scale to the actual correlation (r = 0.34) observed in
wedding photographs [24] and therefore the model shows a degree
of attractiveness sorting.
The pattern of attractiveness seen in mixed-race and non-
mixed-race couples also leads to a series of predictions for this
model. These predictions come from finding the relative
attractiveness, within each group, of those engaging in mixed-
race or same-race partnerships (see Figure 2). For White and Black
men, it was observed in the model that those engaged in mixed-
race couples tend to be more attractive that those engaged in
same-race couples, whereas for Asian men, the more attractive
men married same-race women. For White and Asian women, it
was observed that those engaged in mixed-race couples tend to be
more attractive than those in same-race couples (except for White
women marrying Black men). Finally, Black women engaged in
Figure 1. Findings from the current research. Patterns of perceived attractiveness ratings for faces of different races and different genders split
according to ratings by participants of different races. Error bars show standard errors by faces.
doi:10.1371/journal.pone.0031703.g001
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same-race couples tended to be more attractive than Black women
married to Asian men. It is a prediction of the model, therefore,
that similar patterns will be observed in attractiveness patterns of
real couples. This will be the focus of future research as such
patterns could be assessed by obtaining ratings for individuals in
wedding photographs published in newspapers.
Why do the differences exist?
So far it has been shown that the patterns of perceived
attractiveness for people of different races are different for males
and females. It was also demonstrated how these differences could
explain observed patterns of gender asymmetries in interracial
marriage. What is not explained is why the different patterns of
attractiveness occur for different races. Here, some speculative
evolutionary ideas are reviewed that can explain the patterns.
First, it has been demonstrated that skin colour is a sexually
dimorphic characteristic. Men tend to have darker skin than women
[28,29]. Further, in the majority of cultures that have been tested,
there is a bias that lighter skin pigmentation is considered more
attractive in women [28]. This sexual dimorphism can explain why
Black men and White women are considered more attractive than
White men and Black women respectively. The former represent
highly positive sexually dimorphic patterns. This does not, however,
explain the findings with regards to Asian attractiveness measures as
their skin tones tend to be between those of Black and White people.
In order to provide a possible explanation for the pattern of
attractiveness for Asian people, one can look to the evolutionary
impact of the environment in which the races developed. Frost
hypothesised that many of the visual features that distinguish
White from Black people are a result of differences in patterns of
sexual selection [30]. Further from the equator (for example in the
arctic tundra of Europe 10,000 years ago), men would be less
available for two reasons. First, they would have to hunt over
greater distances with increased mortality. Second, polygamy
would be less common due to having to provide over a longer
winter. As a result, away from the equator, there would be greater
competition between women for mates. This competition would
lead to sexual selection for more feminine characteristics. While
the sexual selection would be driven by competition between
females, it would act upon both the males and females making
them both more feminine. At the same time in the agricultural
parts of Africa, females could contribute more to food production
and so could be more easily supported. Men would be able to take
more than one wife and so women would be competed for by
males. Competition between males for mates would lead to sexual
selection of masculine traits. Again, these traits would carry over
into both the males and the females. This pattern of evolutionary
development, therefore, provides an explanation for why White
females and Black males are perceived to be more attractive than
Black females and White males.
Although not specifically considered by Frost, this geographic
evolutionary explanation can be extended to explain the findings
regarding the perception of attractiveness of Asian people as well.
We can do this if we assume that, just like the arctic tundra
Figure 2. Predictions of the marriage model regarding the mean attractiveness of groups involved in marriage to same or different
ethnic groups.
doi:10.1371/journal.pone.0031703.g002
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conditions of Europe, the mountainous expanses of Asian lead to a
lifestyle of difficult agriculture. Several males may be required to
support a single female as is currently the practice in the
polyandrous Tibetan culture [31]. Such a society would show
sexual selection for feminine features as a highly feminine female
would be able to attract the support during child rearing of one, or
more, productive partners. In this case, however, it is not the
lighter skin tones and fairer hair that were selected for but the
rounder, more feminine face structure. In this way, competition
between females for mates leads to a population that is more
feminine in its facial characteristics. These feminine facial
characteristics mean that Asian women are perceived as being
more attractive whereas the same features affect the attractiveness
of Asian men in a negative manner.
Conclusion
The results of the experiment demonstrated that there are
robust differences in the relative perceived attractiveness of
different racial groups. Further, these differences are affected by
the gender of the person being rated. Among males, Black faces
were rated as the most attractive followed by White faces and then
Asian faces. For the females, Asian faces were seen as the most
attractive followed by White and then Black faces. The same
pattern was found regardless of the ethnicity of the person doing
the ratings.
A model of marriage is put forward in which facial
attractiveness and race affect whether or not a couple marry.
Facial attractiveness increases the chance of marriage whereas a
difference in racial background will decrease the chance. It follows
from this model that differences in patterns of interracial marriage
will be a consequence of differences in average attractiveness of the
gender-by-race groups: In general, more attractive the person is
the more likely they are to be involved in an interracial marriage.
Black men and Asian women (the most attractive groups) occur
within interracial marriages more often than Asian men and Black
women (the least attractive groups).
The results and model presented here represent a significant
advancement in understanding the gender asymmetries in
interracial marriage. Previous explanations have required a
social-exchange of racial status [7], which implied a hierarchy of
races. The current model of interracial marriage does not require
this hierarchy but treats all races as equal except in terms of
subjective ratings of attractiveness. Further, unlike the equilibrium
sorting explanation [15], the attractiveness account does not
predict that people in interracial marriages will be better educated
than those not, although it does predict differences in their
attractiveness. Finally, there may be a role for differences in height
to play in marriage particularly as the perceived attractiveness of
males may be related to their height, but the data and analysis
presented here tells us that rated attractiveness alone can account
for the patterns of data observed.
It is clear that physical attractiveness is not the only feature that
people use in making a decision about the person they marry. The
research reported here, however, indicates that attractiveness
patterns across different races are sufficient to account for why
such large gender asymmetries exist when people of various races
marry.
Supporting Information
Data S1 The raw attractiveness responses for the 40
participants for the 600 faces. The information includes the
race of the raters and the race of the faces being rated.
(XLSX)
Acknowledgments
The author thanks Etienne Joly and two anonymous reviewers for their
valuable observations on previous versions of this paper. Thanks also go to
Simon Rushton for his guidance and to the research assistant who collected
the many images used in the experiment.
Author Contributions
Conceived and designed the experiments: MBL. Performed the experi-
ments: MBL. Analyzed the data: MBL. Contributed reagents/materials/
analysis tools: MBL. Wrote the paper: MBL.
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