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Gender Differences in Personality and Social Behavior
Marco Del Giudice, University of New Mexico, Albuquerque, NM, USA
!2015 Elsevier Ltd. All rights reserved.
This article replaces the previous edition article by J.S. Hyde, volume 9, pp. 5989–5994, !2001, Elsevier Ltd.
Abstract
The scientific study of gender differences has yielded a wealth of robust generalizations about the way males and females
differ across domains, cultures, and developmental stages. This article provides a descriptive overview of gender differences in
personality, social cooperation and competition (including aggression and play), and verbal and nonverbal communication.
Qualitative statements about the typical behavior of males and females are supplemented with quantitative data from meta-
analyses and other large-scale studies. Key methodological issues in the measurement of gender differences are discussed to
aid the reader in the interpretation of research findings.
The scientific study of gender differences has a long history,
spanning more than a century of research (Ellis et al., 2008).
Competing theories of gender vary in the role they assign to
evolutionary history, cultural practices, endocrine and neuro-
biological mechanisms, and individual learning; they also vary
in the extent to which they regard these levels of explanation as
complementary or mutually exclusive. While the field is rife
with theoretical debate and controversy, decades of empirical
research have yielded a wealth of robust generalizations about
the way males and females differ across domains, cultures, and
developmental stages. This process has been accelerated by the
diffusion of meta-analytic techniques over the last 30 years.
Thanks to meta-analysis, the results of multiple studies can be
aggregated and corrected for various sources of error; also, the
effects of potential moderators can be analyzed in detail.
This article provides a descriptive overview of gender
differences in personality; social cooperation and competition
(including aggression and play); and verbal and nonverbal
communication. Whenever possible, qualitative statements
about the typical behavior of males and females are supple-
mented with quantitative data from meta-analyses and other
large-scale studies. To aid the reader in the interpretation of
these findings, the initial section presents and discusses key
methodological issues in the measurement of gender
differences.
Methodological Issues
The Interpretation of Effect Sizes
In psychological research, group differences (including differ-
ences between males and females) are usually expressed in
terms of standardized effect sizes. The most common effect size
for group and gender differences is Cohen’sd, the difference
between means divided by the pooled standard deviation of
the two groups (e.g., d¼0.50 represents a distance of half
a standard deviation between male and female means).
Conventionally, positive values of dindicate that the male
mean is higher than the female mean, whereas negative values
indicate that the female mean is higher. Values of dcan easily
be translated into estimates of statistical overlap (Figure 1). For
example, d¼0.50 corresponds to a 67% overlap between male
and female distributions (assuming normality). The precision
with which a variable is measured can dramatically affect the
resulting effect size, since dbecomes artificially smaller as
measurement error increases. Many psychological variables are
measured with a substantial margin of error; thus, empirical
values of dshould be interpreted as lower bound estimates of
the actual differences. Effect sizes that have been corrected for
measurement error are explicitly flagged as such in the
remainder of this article.
Regrettably, many researchers routinely interpret effect sizes
as ‘small,’‘moderate,’or ‘large’based on the conventional
cutoffs (d¼0.20, 0.50, and 0.80) originally proposed by
Cohen (1988). This practice has little basis in statistical theory
and is discouraged by most methodologists (Breaugh, 2003;
Hedges, 2008;Vacha-Haase and Thompson, 2004). Ironically,
Cohen himself advised against using his tentative cutoffs
except as a last resort method for determining sample
size in exploratory studies (Cohen, 1988). The substantive
Figure 1 Relation between effect size (dor D) and percent overlap
between male and female distributions. The illustrative plots on the
right show two univariate distributions overlapping by 10%, 30%,
50%, 70%, and 90% of their joint area. Overlap is computed
assuming multivariate normality. See Del Giudice, M., 2009. On the
real magnitude of psychological sex differences. Evolutionary
Psychology 7, 264–279.
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interpretation of an effect size may vary dramatically depend-
ing on measurement issues, theoretical considerations, and the
scientific question being asked. For example, differences
between group means have a progressively larger impact as one
moves toward the distribution tails. Even when male and
female distributions are largely overlapping in the region
surrounding the mean of a trait, individuals with extreme values
of the same trait may still be predominantly male or female. In
the light of these considerations, debating whether males and
females are ‘more similar’or ‘more different’based on a rigid
interpretation of effect sizes (e.g., Hyde, 2005, 2013) is unlikely
to prove a fruitful strategy for understanding the meaning of
gender differences and their societal implications.
Univariate versus Multivariate Differences
The standard approach to gender differences in psychology is to
measure groups of males and females on multiple variables –
for example physical, verbal, and relational aggression –and
compute an effect size for each individual variable. This
approach becomes problematic in dealing with intrinsically
multidimensional domains such as personality and
aggression. To begin with, small differences in multiple traits
can add up to a much larger effect if the traits are considered
simultaneously. For example, facial features –nose length,
eye size, face width, and so forth –show considerable
overlap between genders when they are considered one by
one. However, their combined effect results in nearly complete
separation between male and female faces, and indeed,
human observers can classify faces by gender with more than
95% accuracy (see Del Giudice, 2013). Another limitation of
univariate effect sizes (such as d) is that they cannot take into
account the patterns of correlation between the variables that
constitute a given psychological domain.
The limitations of univariate effect sizes can be overcome by
supplementing them with multivariate effect sizes that simul-
taneously consider multiple variables and their correlational
structure. The natural extension of Cohen’sdis the Mahalanobis
D, a standardized difference between two groups in multivariate
space. When employed to measure gender differences, Dcan be
interpreted as the distance between group means on an abstract
dimension of masculinity–femininity in the relevant domain. The
interpretation of Din terms of distribution overlap is exactly the
same as that of d(Figure 1). Unlike d,Dis always positive since
the concept of a higher or lower mean is meaningless in
multidimensional space (Del Giudice, 2009). The application
of multivariate effect sizes to gender differences has been
debated by some authors (e.g., Hyde, 2013); however, the
arguments leveled against Dturn out to be either incorrect or
logically inconsistent (Del Giudice, in press). In this article,
both univariate and multivariate effect sizes are reported
whenever the latter are available.
Dimensional versus Taxonic Differences
Finding evidence that, on average, males and females differ on
a certain set of variables does not tell the whole story about the
nature of gender differences in that domain. Another important
question is whether gender differences are differences in
degree –with males and females varying along a single
continuum –or differences in kind, implying a clear-cut
discontinuity in the distribution of variables between groups.
This question is conceptually independent from questions
about the size of those differences.
Taxometrics is a set of statistical methods that attempt to
determine whether a certain group is a taxon, i.e., a clearly
demarcated category that differs in kind and not just in degree
from another group. In a recent paper, Carothers and Reis
(2013) employed taxometrics to determine whether binary
gender categories can be regarded as dimensional or taxonic in
a number of domains including personality, social behavior, and
sexuality. The results overwhelmingly supported a dimensional
model of gender, with the exception of sociosexuality (the pref-
erence for promiscuous, uncommitted sex versus monogamous,
committed partnerships). However, these pioneering findings
must be taken with caution, since taxometric methods are
unlikely to detect an existing taxonic structure if the mean
difference between groups is smaller than about d¼1.20
(Beauchaine, 2007). Since the size of gender differences in many
psychological traits falls below this threshold (see below),
taxometric results are difficult to interpret with any confidence.
Gender Differences in Trait Variability
Males and females may differ not just inthe mean value of a trait
or behavior, but also in their variability around the mean. When
such differences are found, the general tendency is for males to
display more variability than females (Archer and Mehdikhani,
2003;Hyde, 2013). The more variable gender will tend to be
overrepresented at both tails of the distribution, even if mean
differences are small or absent (see Voracek et al., 2013). The
standardmetric for gender differences in variability is the variance
ratio (VR), the ratio of male variance to female variance. VR ¼1
indicatesequality of variances, VR >1 indicateshigher variability
in males, and VR <1 indicates higher variability in females.
Gender Differences in Personality
Descriptive models of personality have a hierarchical structure,
from broad and inclusive traits to narrow and specific ones.
Typically, 3–6 broad traits (‘domains’or ‘global traits’) are
subdivided into 10–20 narrower traits (‘aspects’or ‘specific
factors’); at the lowest level of description, dozens of specific
personality ‘facets’(usually 30–45) can be identified. Patterns
of gender differences are already apparent at the level of
broad traits, but become stronger and more recognizable at
afiner-grained level of analysis.
Broad Personality Traits
Big Five Domains
The most widely adopted model of personality is the Five Factor
Model (FFM), whose five domains are known as the Big Five:
neuroticism (negative emotionality and emotional instability),
agreeableness (altruism and cooperation), conscientiousness
(self-control, self-discipline, and organization), extraversion
(sociability, assertiveness, and positive emotionality), and
openness (imagination, intellectual curiosity, and aesthetic
appreciation). Across countries, gender differences in the Big
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Five are largest in agreeableness (d¼"0.40) and neuroticism
(d¼"0.34); females consistently score higher than males on
both traits. Smaller differences favoring females are found in
conscientiousness (d¼"0.09) and extraversion (d¼"0.11);
finally, there are no reliable differences in openness (d¼0.01).
There is some cross-cultural variability around these averages;
as a rule, gender differences tend to be larger in individualistic,
gender-egalitarian societies (Feingold, 1994;Lippa, 2010;
Schmitt et al., 2008). In a reanalysis of a large US data set, Del
Giudice (2009) found a multivariate difference of D¼0.98
(corrected) for the Big Five domains, corresponding to a 45%
overlap between male and female distributions.
A recent study of variation in Big Five domains (Borkenau
et al., 2013) found equal variance between genders in self-
reported traits (VR z1), but higher male variance in
informant-reported traits (VR z1.20). Neuroticism was an
exception: males showed lower variability in self-reports
(VR ¼0.89) and equal variability in informant-reports
(VR ¼1.01). Given the comparatively small size of the study,
these findings should be regarded as preliminary.
The Interpersonal Circumplex
In the interpersonal circumplex model (IPC), individual
differences in personality are mapped on two independent axes
of variation, dominance (assured-dominant versus insecure-
submissive) and nurturance (warm-agreeable versus cold-
hearted). The IPC can be regarded as an alternative
representation of the extraversion and agreeableness domains
of the FFM (DeYoung et al., 2013). The interpersonal
dimensions of the IPC bring into sharp relief a pattern of
gender differences that is partially masked by the structure of
Big Five domains: on the traits that best correspond to those
dimensions, males consistently score higher in dominance
(dz0.20–0.50) and lower in nurturance (dz"0.25 to
"1.00; Costa et al., 2001;Del Giudice et al., 2012;Feingold,
1994). Based on data for dominance and warmth reported in
Del Giudice et al. (2012), the multivariate effect size for the
IPC can be estimated at D¼1.14 (corrected).
Temperament
In infants and children, individual differences in behavior are
usually framed as ‘temperament’rather than ‘personality’;
standard dimensions of temperament overlap only partially
with adult personality traits. In a meta-analysis of temperament
ratings from 3 months to 13 years of age, Else-Quest et al.
(2006) found that females scored higher in all dimensions of
effortful control (self-control and delay of gratification;
d¼"0.05 to "1.01), whereas males tended to score higher
in dimensions of surgency (activity and sociability; d¼"0.11
to 0.55). No reliable gender differences were observed in
negative affectivity (d¼"0.17 to 0.13), a surprising finding
when contrasted with the robust gender differences in adult
neuroticism. The mean variance ratios were VR ¼1.08 for
dimensions of effortful control, VR ¼1.03 for dimensions of
surgency, and VR ¼0.98 for dimensions of negative affectivity.
Narrow Personality Traits
While broad traits such as the Big Five provide a compact
description of individual differences, they are not necessarily
the best level of analysis to investigate gender differences in
personality. In many cases, the structure of broad traits masks
the existence of lager gender differences at the level of narrower
traits. For example, comparatively small differences in extra-
version actually result from the combination of larger,
opposite-sign differences in assertiveness–sensation seeking
(higher in males) and sociability–gregariousness (higher in
females). Weisberg et al. (2011) examined the 10 aspects of
the Big Five and detected contrasting patterns of gender
differences within extraversion (d¼"0.23 for enthusiasm,
d¼0.09 for assertiveness), conscientiousness (d¼"0.18 for
orderliness, d¼0.06 for industriousness), and openness
(d¼"0.27 for aesthetic openness, d¼0.22 for intellect). At
the level of 30 personality facets, the meta-analysis by Costa
et al. (2001) found differences of d¼"0.09 to "0.44 for
neuroticism facets, d¼"0.33 to 0.38 for extraversion facets,
d¼"0.35 to 0.32 for openness facets, d¼"0.17 to "0.43
for agreeableness facets, and d¼"0.13 to 0.20 for con-
scientiousness facets.
The 15 primary factors (PF) of the 16 PF model are narrow
personality traits roughly comparable to Big Five aspects. In
a large US sample, Del Giudice et al. (2012) found differences
ranging from d¼"2.29 to 0.54 (corrected). The largest differ-
ences were in sensitivity (aesthetic, intuitive, and tender-minded
versus utilitarian, objective, and tough-minded; d¼"2.29),
warmth (d¼"0.89), apprehension (worried, insecure, and self-
doubting versus secure and self-assured; d¼"0.60), dominance
(d¼0.54), and emotional stability (d¼0.53). The multivariate
effect size for the 15 factors was D¼2.71 (corrected),
corresponding to a 10% overlap between male and female
distributions (Del Giudice et al., 2012).
Impulsivity, Risk-Taking, and Sensation Seeking
Impulsivity, risk-taking, and sensation seeking are a group of
correlated traits that deserve special consideration in virtue
of their social and clinical implications. In a meta-analysis of
risk-taking that employed a broad definition of the term and
a wide range of indicators –including for example ‘smoking’
and ‘guessing’–Byrnes et al. (1999) found that overall levels of
risk-taking were higher in males (d¼0.13). Cross et al. (2011)
employed a narrower definition of risk-taking and found even
stronger gender differences (d¼0.37 across methods). In the
same meta-analysis, males also showed higher levels of
sensation seeking (d¼0.22). Gender differences in impulsivity
were considerably smaller (d¼0.08). This finding can be
contrasted with the robust gender differences in effortful
control (the reverse of impulsivity) found in studies of infant
and child temperament. Males displayed more variability in
risk-taking (VR ¼1.10) and sensation seeking (VR ¼1.08), but
not in impulsivity (VR ¼1.00). Gender differences in risk-
taking are not limited to stable dispositions, but extend to the
role of contextual factors in determining moment-to-moment
attitudes toward risk. For example, several studies have shown
that acute stress tends to increase risk-taking in males, but
decrease it in females (Mather and Lighthall, 2012).
Summary
The typical personality profiles of males and females differ in
a number of ways. On average, males are more dominant,
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assertive, risk-prone, tough-minded, cold-hearted, emotionally
stable, utilitarian, and open to abstract ideas. Females are more
nurturant, warm, altruistic, submissive, risk-averse, tender-
minded, emotionally unstable, and open to feelings and
aesthetic experiences. These differences tend to be larger in
more gender-egalitarian countries, and together define
a global dimension of personality masculinity–femininity.
The global overlap between adult men and women in the
distribution of personality traits can be estimated at about
10% –close to that between male and female facial features
(Del Giudice, 2013). In addition, men are somewhat more
variable in most (but not all) dimensions of personality.
Gender differences in temperament are already apparent in
infancy and childhood, but correspond only in part to those
in adult personality. In particular, early differences in
impulsivity seem to dissipate in adults, while differences in
negative emotionality emerge during development.
Gender Differences in Cooperation and Competition
Cooperation and competition are the basic polarities of social
life; their constant interplay provides the background for the
rich tapestry of human relationships. From childhood to
adulthood, cooperation and competition outside the family
occur with particular frequency and intensity between same-
gender individuals (Benenson, 2013;Geary, 2010;Geary
et al., 2003). Both one’s closest friends and allies and one’s
fiercest adversaries are likely to be other individuals of the
same gender. The dynamics of same-gender relations are an
essential aspect of human social behavior, and tend to carry
over into mixed-gender interactions.
Cooperation and Competition in Males
While both genders participate in many kinds of social inter-
actions, ranging from dyadic friendships to large groups, large-
scale cooperation is a distinctive attribute of male sociality
across the life span. Males are more likely to engage in
cooperative group activities, form larger groups than females,
and engage in frequent and intense between-group
competition against other male groups. Male groups are
characterized by stable internal hierarchies of status and
dominance; within groups, competition tends to be
individualistic or one-on-one (Benenson, 2013;Geary, 2010;
Geary et al., 2003). A meta-analysis of cooperation in
experimental games played between strangers (Balliet et al.,
2011) showed that male–male interactions tend to be more
cooperative than female–female interactions (d¼0.16).
At the same time, males tend to show less altruistic and
prosocial behavior across a range of domains, from sharing
possessions to organ donations (Ellis et al., 2008). This is
consistent with males’lower levels of agreeableness and
nurturance (see above); the main exception to this pattern is
‘heroic’helping behavior, especially when directed toward
women (Eagly and Crowley, 1986). In group settings –
including mixed gender groups –males display higher levels
of task-oriented behavior and lower levels of social-
emotional behavior (d¼0.59 and "0.59 in the meta-analysis
by Carli, 1982).
Cooperation and Competition in Females
The dynamics of cooperation and competition in females are
more complex and nuanced than their male counterparts.
Female friendship tends to be more complex and less
focused on shared activities than male friendships. Starting
from middle childhood, females are more likely to form
dyadic relationships characterized by high levels of intimacy,
emotional support, exclusivity, and reciprocity. In turn,
dyads are embedded in larger social networks in which
hierarchies tend to be more fluid than those of male groups
(Ellis et al., 2008;Geary, 2010;Geary et al., 2003). Peer
relations in females are strongly influenced by norms of
caring and equality. Superiority and overt competition are
discouraged, and –unlike in male groups –high-status peers
are often the target of dislike and denigration. Accordingly,
female competition is often indirect and balanced by
egalitarian concerns; displays of overt competitiveness are
usually restricted to high-status females (Benenson, 2013).
In group settings, females display higher levels of social
emotional behavior focused on maintaining and managing
personal relationships (d¼"0.59 in Carli, 1982). This
pattern is consistent with females’higher levels of
agreeableness and nurturance and lower levels of
dominance and assertiveness (see above). A prominent
feature of female social relationships is social exclusion, an
indirect aggression tactic in which a target individual is
ostracized by the others. Both threats of social exclusion
and actual episodes of ostracism are more common in
female groups, especially in childhood and adolescence
(Benenson, 2013).
Aggression
The existence of gender differences in aggression is one of
oldest and most robust findings in this area. In psychology, the
standard distinction is that between physical,verbal, and indirect
(or relational) forms of aggression. Indirect aggression is used to
damage another individual’s social standing by ostracizing,
gossiping, spreading malicious rumors, and so forth. In
a comprehensive meta-analysis,Archer (2009) found that,
across age groups, males engage in more direct aggression,
both physical (d¼0.58) and verbal (d¼0.29), while females
tend to engage in more indirect aggression (d¼"0.16). A
meta-analysis of studies of children and adolescents (Card
et al., 2008) showed similar results for physical and verbal
aggression (d¼0.73 and 0.38, respectively), and a smaller
effect for indirect aggression (d¼"0.06). Gender differences
in aggression –especially physical aggression –peak between
adolescence and young adulthood (Archer, 2009). Overall,
the multivariate effect size for male versus female patterns of
aggression can be estimated at about D¼0.89–1.01
(corrected; Del Giudice, 2009).
While males and females tend to display similar levels of
indirect aggression (especially compared with the much larger
difference in physical aggression), the finer-grained dynamics
of aggressive behavior differ between male and female
groups. In particular, attractive females are the target of more
indirect aggression by other females, whereas attractive males
tend to receive less indirect aggression from their peers
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(Vaillancourt, 2013). Also, experimental studies show that
males tend to engage in unprovoked aggression more
frequently than females (d¼0.33; Bettencourt and Miller,
1996).
Social Play
Social play is a universal feature of human development, and –
like many other social activities –involves a complex balance of
cooperation and competition. Gender differences in social play
can be summarized as follows. Across cultures, girls engage
more frequently in cooperative, nonaggressive social play,
whereas boys show a higher frequency of play fighting and
‘rough-and-tumble’play (about 3–6 times as much as girls;
Geary, 2010), as well as higher levels of between-group
competition. Both genders engage in sociodramatic play, in
which social episodes are enacted based on everyday or
fantastic themes. However, boys’themes more frequently
involve power, dominance, and aggression, whereas girls’
themes tend to involve interpersonal and family relationships
(including play parenting). Gender differences in play
behavior peak in middle childhood, around 8–10 years of
age (Ellis et al., 2008;Geary, 2010).
Summary
Males tend to formlarger, activity-oriented, competitive groups in
which hierarchies tend to be stable and individual relationships
require comparatively little emotional investment. Competition
often involves direct forms of aggression. Intimate, high-
intensity dyadic relationships play a bigger role in female social
networks. Female groups are more emotion-focused and are
characterized by unstable hierarchies and strong egalitarian
norms; competition is often indirect and less openly
confrontational. Aggression shows robust patterns of gender
differences. Direct aggression –especially physical aggression –
is higher in males; indirect forms of aggression are higher in
females, though the size of the effect is considerably smaller.
Gender differences in play behavior peak in middle childhood
and mirror the broader pattern of gendered social dynamics:
males engage in more play fighting and between-group
competition, while females engage in more cooperative play
centered around relational themes.
Gender Differences in Communication
Social behavior would be all but impossible without commu-
nication. In humans, the interplay between language and
nonverbal behavior forms the background for an exceedingly
complex communication system. Research on gender differ-
ences in linguistic communication has focused mainly on
verbal ability (e.g., vocabulary, reading ability), language use
(e.g., assertive communication), and conversational style (e.g.,
interruptions). Gender differences in nonverbal communica-
tion have been extensively studied, and include both the
production of nonverbal displays –such as gestures and facial
expressions –and the ability to accurately decode other
people’s nonverbal behavior.
Verbal Ability
In a classic meta-analysis, Hyde and Linn (1988) found a female
advantage in general verbal ability (d¼"0.20). Specific abilities
showed a more nuanced pattern of results: females performed
better on measures of speech production (d¼"0.33) and
anagram solving (d¼"0.22); smaller differences were found
in writing and reading (d¼"0.09 and "0.03, respectively),
while males showed an advantage in verbal analogies
(d¼0.16). No reliable gender differences were detected in
vocabulary skills (d¼"0.02). The size of gender differences
was largely independent of age, and showed no clear
developmental trend from childhood to adulthood.
Language Use and Conversational Style
Given the robust gender differences observed in dominance-
and nurturance-related dimensions of personality (see above),
it is reasonable to expect males and females to differ in their
typical patterns of language use and conversational style.
Indeed, meta-analytic data in both children and adults show
that, averaging across contexts, males tend to use more
assertive speech (dz0.10) whereas females tend to use
more affiliative speech (dz"0.10). In addition, girls are
more talkative than boys (d¼"0.11), but the difference is
reversed in adults (d¼0.14; Leaper and Ayres, 2007;Leaper
and Smith, 2004). A related finding (Leaper and Robnett,
2011) is that females use more tentative speech, including
more tag questions, e.g., “isn’t it?”(d¼"0.23) and hedges,
e.g., “I think”(d¼"0.15). A conspicuous aspect of gender
differences in language use is their strong dependence on
contextual factors such as group size, age and gender of
conversation partners, and familiarity. Depending on the
specifics of the conversational setting, these differences can
easily increase, decrease, or even change sign (Leaper and
Ayres, 2007;Leaper and Smith, 2004). On average, males
interrupt their conversation partners more than females do
(d¼0.15); gender differences are especially large in the use
of intrusive interruptions (d¼0.33), which can be
unambiguously interpreted as a form of dominant behavior
(Anderson and Leaper, 1998).
Nonverbal Communication
Nonverbal Behavior
A consistent finding in nonverbal behavior research is that
females are generally more expressive than males. A meta-
analysis by Hall (1984) found an overall effect size d¼"1.01
for facial expressiveness and d¼"0.58 for bodily
expressiveness, even if males tend to adopt more expansive,
open postures (d¼1.04). Females are also better at
deliberately expressing emotions (d¼"0.52). Gender
differences in expressiveness show a clear developmental
trend from childhood to adulthood (Chaplin and Aldao,
2013). In children, a smaller female advantage is found on
positive emotions (dz"0.08) and internalizing negative
emotions such as sadness and anxiety (dz"0.10); at the
same time, boys tend to be more expressive on externalizing
negative emotions such as anger (dz0.09). By adolescence,
however, females become more expressive across the board
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and effect sizes increase (dz"0.35 for negative emotions and
"0.28 for positive emotions).
Smiling and crying are two prototypical manifestations of
expressive behavior. A meta-analysis of smiling from
adolescence to adulthood showed that females tend to smile
more frequently across contexts and cultures (d¼"0.41).
Average differences peak in adolescence (d¼"0.56) and
decrease with age (d¼"0.11 in seniors); also, effect sizes are
especially large in North American countries (LaFrance et al.,
2003). As with language use, gender differences in smiling
are highly contingent on contextual factors; for example,
males and females differ more when they believe they are
being observed than when they believe they are alone
(d¼"0.46 vs "0.19). Gender differences in crying are larger
and more robust than those in smiling. Across cultures,
females show a stronger tendency to cry (d¼"1.11) and cry
more often than males do (d¼"0.94). Also, gender
differences in crying tend to be larger in more individualistic,
gender-egalitarian countries (van Hemert et al., 2011).
Nonverbal Decoding
In addition to being more expressive, females are generally
better at processing and decoding other people’s nonverbal
behavior. In her meta-analysis,Hall (1984) found an overall
effect size d¼"0.43 for nonverbal decoding skills across
communicative modalities. The female advantage in
processing facial expressions tends to be smaller in childhood
and adolescence (dz"0.20; McClure, 2000). There is some
evidence that gender differences in expression processing may
peak in infancy, decrease in early childhood, then peak again
in middle childhood (McClure, 2000).
Summary
Females enjoy a general advantage in communication skills,
both in the verbal domain (with the exception of verbal anal-
ogies) and in the production and decoding of nonverbal
displays. The higher expressiveness of females is reflected in
a higher frequency of both smiling and crying; gender differ-
ences in crying are especially robust, and tend to increase in
more gender-egalitarian countries. Consistent with the data on
personality and social relations, males tend to use more
assertive speech and interrupt their conversation partners
more often, while females tend to use more affiliative and
tentative speech. However, gender differences in language use
are highly dependent on contextual factors, testifying to the
remarkable strategic flexibility of human communication.
See also: Crime and Gender; Evolutionary Social Psychology;
Gender Development: Cultural Differences; Language and
Gender; Personality Development and Temperament;
Personality, Evolutionary Models of; Psychometrics;
Systematic Reviewing and Meta-Analysis.
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