Leaning back: an experiment on cooperation and communication in mixed-gender teams
Olga Stoddard1 and Joseph Price2
April 2015
Abstract
Women are increasingly more likely to pursue education and careers in historically maledominated professions, increasing the amount of mixed-gender interactions in organizational
settings. While gender diversity in teams provides an important benefit to the workplace, it may
also lead to lower levels of cooperation as individuals may treat members of the out-group less
favorably than members of the in-group. In this study, we assess the effect of priming a gender
identity on cooperation and communication in mixed-gender teams through a laboratory
experiment with a real-effort task. We find that priming gender identity seems to invoke
stereotypes about men and women’s roles in communication, causing men to be more vocal and
women to communicate less. Notably, these imbalances in communication patterns of men and
women lead to a significant increase in inefficiency in mixed-gender groups, suggesting that
making gender differences more salient diminishes subjects’ ability or motivation to remain taskoriented.
JEL codes: D7
Key words: gender, cooperation, mixed-gender teams, laboratory experiment
1
(corresponding author) Department of Economics, Brigham Young University. 149 FOB Provo, UT.
84602. Email: [email protected]. The authors would like to thank Rebecca Jack, Theresa Boyd,
Matthew Hubbard, and Brandon Betz for their outstanding research assistance. They would also like to
acknowledge the research support of the Women’s Research Initiative, the Emmeline B. Wells Scholarly
and Creative Works Grant, and a Mentored Environment Grant at Brigham Young University
2
Department of Economics, Brigham Young University.
Teams are a common feature of the modern workplace. Teams provide an efficient and flexible
way to complete tasks that require a diversity of skills, talents, and information (Eckel and
Grossman, 2005). Teamwork represents one setting within the firm where cooperation in the
form of communication and exchange of ideas is extremely important. Organizations are filled
with such settings: company boards, committees, and councils, as well as group and department
meetings. A lack of cooperation in these environments leads to a less efficient outcome for the
firm (Tjosvold, 1984; Hoegl and Gemuenden, 2001).
Another common feature of the workplace is increasing gender diversity. Women’s labor force
participation rates have been steadily rising relative to men’s, with women rising from 34 percent
in 1950 up to 57 percent in 2013 while men dropped from 86 percent down to 69 percent during
the same time period (Bureau of Labor Statistics, 2014). The share of women pursuing higher
education has also increased drastically. In 2012, the immediate college enrollment rate for
females was higher than males, 71 percent versus 61 percent (U.S. Department of Education,
2013). By 2019, women are projected to account for nearly 60 percent of total undergraduate
enrollment. This trend is not limited to the United States. In 2010, OECD reported that women
earned on average 58 percent of undergraduate degrees conferred in OECD countries (U.S.
Department of Commerce, 2011).
This increasing demographic diversity in higher education and in the workforce can be a source
of strength, but may also serve as an impediment to cooperation as it may trigger certain genderbased stereotypes and biases, as well as outgroup discrimination. Social identity theory suggests
that members of a team that is heterogeneous with respect to social categories may find it
difficult to integrate their diverse backgrounds, values, and norms to work together (Jehn et al.,
1999). In general, people feel more comfortable working with and are more likely to trust and
cooperate with those who they identify with, and they are more likely to identify with members
of their own group (Chen and Li, 2009, Chen et al. 2014, Eckel and Grossman, 2005).
In this paper, we explore whether cooperation and communication suffer in mixed-gender groups
if gender differences are made more salient. We assess the effects of priming a gender identity
on cooperation and communication through a laboratory experiment with a real-effort task. We
2
find that priming a gender identity activates gender-specific stereotypes, which leads to
unbalanced communication (men become more dominant and women more shy) resulting in
lower levels of cooperation and less efficient communication.
We recruited an equal number of male and female college students to participate in the
experiment. Subjects were randomly assigned to two-person teams and engaged in a real-effort
task of answering trivia quiz questions. All subjects had the same set of trivia questions and
subjects on the same team were allowed to send messages to the other person on their team to
provide assistance or advice. This created a potential trade-off between answering the questions
on your own screen and providing assistance to your teammate. Prior to the real effort task, we
used a standard priming methodology to make participants’ gender identity salient and then we
compare the degree to which gender priming affects individuals based on their own gender and
the gender of their teammate.
A recent body of literature has documented that individual behavior is significantly affected by
gender-contextual environmental factors. Females have been shown to exhibit significantly more
risk aversion in mixed-gender groups than in single-gender interactions. Booth and Nolen (2009)
find that adolescent girls from single-sex schools take significantly more risk than those educated
in mixed-gender schools. Similarly, Lindquist and Save-Soderbergh (2011) analyze the data
from the Jeopardy game-show and find that women play a more conservative wagering strategy
when they are in a male-only group compared to a female-only or a mixed-gender group.
Prior experimental studies have attempted to estimate gender differences in cooperation in
groups with different gender compositions. Eckel and Grossman (1996) find that men and
women are both more likely to accept an offer from a woman in an ultimatum game, IvanovaStenzel and Kubler (2011) observe that men exert more effort in a task when they are paired with
a woman, and Solnick (2001) finds that women receive lower offers from partners of both
genders in the ultimatum game, suggesting that participants expect women to cooperate more
frequently and with less of a monetary incentive. Contrary to this expectation, however, women
chose higher minimal acceptable payments in the context of this experiment. Thus, women were
expected to settle for less, when in reality they required more than men did. In the context of the
3
prisoner’s dilemma game, Charness and Rustichini (2011) find that, when individuals are playing
with an audience, men tend to signal to other men that they are competitive, while women tend
to cooperate more when being observed by other women. Ortmann and Tichy (1999), however,
observe that women cooperate slightly less and men cooperate slightly more in single-sex
pairings than in mixed-sex groups in a prisoner’s dilemma game.
In our experiment, individuals participate in a real-effort task (a trivia quiz) that is similar to the
ones used in Hoffman et al. (1994), Eckel and Wilson (2007), and Morita and Servatka (2013).
While real-effort tasks have the potential to yield important insights into people’s economic
behavior, few studies have used such tasks to measure cooperation. These tasks have been used
to determine initial status in a later game (Burrows and Loomes, 1994), to measure the effect of
different payment schemes on competitiveness (Gneezy et al., 2003), and to test the effect of
teamwork on productivity (Munro et al., 2013). The specific task of answering trivia quiz
questions has often been used to determine initial status in games (Visser and Roelofs, 2011) or
initial endowments for another part of the experiment (Balafoutas et al, 2013), or to encourage
relationship building among subjects (Morita and Servatka, 2013). Our study is one of the first
to use a real-effort task to measure cooperation and communication patterns in the context of
same-gender vs. mixed-gender groups.
I. Research Hypotheses
In this section we present our research hypotheses regarding subject behavior in the group realeffort task as related to gender, as motivated by the theoretical and empirical findings, which we
discuss below.
Hypothesis 1 (In-group bias). Subjects are more likely to cooperate with a same-gender partner
than with an opposite-gender partner in the absence of any priming.
We expect that even in the absence of gender priming, subjects will be more likely to cooperate
with the in-group members. While experimental evidence on in-group gender bias is somewhat
mixed in the context of an ultimatum game (Eckel and Grossman 1996; Solnick 2001), Ortmann
4
and Tichy (1999) find that, in a prisoner’s dilemma type game, men cooperate slightly more
when paired with another man, while women cooperate slightly less when paired with another
woman. In the context of our experiment where we will measure cooperation a real effort task,
we hypothesize that the tendency to exhibit in-group favoritism will lead to higher levels of
cooperation in the same-gender groups relative to mixed-gender pairings.
Hypothesis 2 (Gender priming). Subjects are more likely to cooperate with the same-gender
partners when we prime their gender identity.
Priming subjects’ gender identity will likely fragment participants along gender divisions. Thus,
we expect a greater degree of in-group favoritism and out-group discrimination in the gender
priming treatment compared to the control. Previous research focusing on priming fragmenting
identities finds similar results. Specifically, Stoddard and Leibbrandt (2014) find that subjects are
less likely to coordinate on a payoff-dominant equilibrium with non-compatriots when their
partner’s nationality is salient. Similarly, Chen et al. (2014) finds that Asian participants are
significantly less likely to cooperate with their white counterparts in a prisoner’s dilemma game.
Hypothesis 3 (Stereotype threat). Gender priming leads women to communicate less and men to
communicate more.
There is a substantial body of evidence showing that both men and women are susceptible to
gender stereotype threats. Shih, Pittinsky, and Amady’s (1999) find Asian-American women
perform better on math tests when their ethnic identity is primed and worse when gender is
primed. Similarly, Shih, Pittinsky, and Trahan (2006) find that Asian-American women perform
better at verbal tasks when their gender is primed, compared to when their ethnicity is
primed. Coffman (2014) finds that individuals are not as likely to contribute ideas when asked
about subjects that are stereotypically not their gender’s expertise. Rosenkrantz et al. (1968)
identify additional traits that are commonly perceived as stereotypically male (such as
aggressiveness, dominance, logic, directness, leadership, and self-confidence) and stereotypically
female (such as being quiet).
5
We predict that priming gender identity will make those stereotypes more salient and cause men
to communicate more and women to communicate less. This can be compared to a body of
literature in which researchers have found that increasing gender salience through varying group
gender composition causes both men and women to act more in accordance with stereotypes of
women's passivity and male dominance (for examples, see Aries, 1976; Craig and Sherif, 1986;
Johnson and Schulman, 1989; Karpowitz, Mendelberg, and Shaker, 2012).
II. Experimental Design
We used a between-subject design and each participant was randomly assigned to either a control
or a treatment group in which we prime subjects’ gender identity before they make decisions. We
prime subjects’ gender identity by introducing stimuli through a pre-experimental questionnaire
based on the approach used by Shih et al (1999). The questions prompted subjects to reflect on
their every-day interactions with the same and the other gender and consider whether they
preferred spending time with one gender over the other and why. The subjects in the control
group answered the same number of questions, but the questions were identity neutral, such as
questions about their activities in leisure time.
The main experiment involved students engaged in a real-effort task (answering trivia questions)
across four different rounds. The first time, each subject had five minutes to answer twenty
multiple-choice trivia questions on their own. Subjects saw ten questions on each screen and
could move freely between the two screens and change their answers before the time was up.
They did not receive any feedback until the end of the task. Subjects earned $.30 for every
question that they answered correctly.
During the second round, subjects answered a new set of multiple-choice trivia quiz questions.
This time, however, they were randomly paired up with another person in the room. Each person
in the pair had an identical quiz and each subject’s payment was now $.30 x the average number
of questions that both partners answered correctly. During this task, each subject could
communicate with their partner through a chat box on their screen. As part of the instructions,
6
subjects were informed about the higher expected earnings of those who cooperated with their
partner on the quiz.
We recruited a total of 216 students (106 women and 110 men) across 10 experimental sessions
(approximately 22 students in each session). Students were recruited through email
announcements. Each subject only participated in one experimental session lasting
approximately 45 minutes and earned an average of $9. Participants also received extra credit in
selected classes in the business school.
We assigned 126 subjects to the control and 92 to the treatment group. In addition to behavioral
outcomes from the real-effort task, we also collected information on their age, gender, race,
grade point average (GPA), and major field of study as part of a post-experimental questionnaire.
The characteristics of our control and treatment group are relatively well balanced across gender
(50% female vs. 48% males), age (22.5 vs. 21.5), GPA (3.45 vs. 3.46), married (22% vs. 19%),
and business major (65% vs. 60%), with age being the only characteristic with a statistically
significant difference between the control and treatment group.
III. Results Women scored significantly lower on the individual quiz than men in the control (7.83 vs. 8.95
correct answers), and about the same as men in the gender treatment (8.42 and 8.48). Men did
slightly worse on average and women did slightly better on average when their gender identity
was primed, relative to the control, though neither difference was statistically significant. In the
group quiz, the number of correct answers was significantly lower for women relative to men
(14.82 and 15.71, out of 40 possible), and it appears to be driven entirely by the control
treatment, where women scored almost 2 points less than men (the difference is significant at the
1 percent level). In the gender treatment, men and women’s group quiz scores are not
significantly different from each other (15.27 for men and 15.11 for women).
By analyzing subjects’ chat communications, we find that in the group quiz, across both the
control and the treatment, women wrote fewer words than men (73.96 vs. 77.74, not statistically
different). In comparing the control and treatment groups, we observe that this difference is
7
driven entirely by the gender treatment. Women in the treatment sessions wrote significantly
fewer words (66.45) when compared to the women in the control (83.5), men in the control
(74.53), and men in the treatment (79.96). The same pattern emerges when comparing
communication behavior using the average number of chat entries. Men become significantly
more “vocal” (23.28 entries in the treatment compared to 19.23 in the control) and women
significantly more “quiet” (17.48 entries in the treatment compared to 21.02 in the control). This
causes a significant imbalance in communication between men and women in the gender priming
treatment, with women making almost five entries fewer than men (17.48 and 23.28, p<0.01).
This result is further confirmed when breaking down chat entries based on the number of
statements (text messages that didn’t involve a question). Women made significantly fewer
statements than men in the gender priming treatment (12.51 and 18.42, p<0.01). Figure 1
illustrates these differences in chat communications graphically.
[Figure 1 Here]
As shown in Figure 1, these communication imbalances lead to a sizable decline in chat
efficiency. While men and women make about the same number of inefficient chat entries in the
control (1.78 and 1.71), men make significantly more inefficient chat entries than women in the
gender priming treatment (1.97 and 1.35, p =0.023).
For the remainder of our empirical analysis, we control for the observed demographic
characteristics3 of the subjects as well as other covariates, such as university major and GPA. To
test our hypotheses, we perform the following regressions analyses:
(1) Yi = β0 + β1 x Femalei + β2 x Treatmenti + β3 x Treatmenti x Femalei + β4 x Ingroupi + β5
x Ingroupi x Femalei + β6 x Ingroupi x Treatmenti + β7 x Femalei x Treatmenti x Ingroupi
+ β8 Xi + εi .
(2) Yi = β0 + β1 x Femalei + β2 x Treatmenti + β3 x Treatmenti x Femalei+ β8 Xi + εi .
3
Demographic characteristics include age, ethnicity, and marital status.
8
In these equations, Yi represents one of our four outcome variables for individual i: a continuous
variable of the subject’s trivia quiz score; subject’s score on the group quiz; the number of words
written in a group quiz; and the number of chat entries. Treatment is a dummy variable for our
gender priming treatment, Female is a dummy variable for female gender, Ingroup is a dummy
variable indicating the same-gender pairing, and Xi is a vector of demographic characteristics and
other covariates for each individual i. In all our analysis, we compare the effect of the treatment
(gender priming) to the control (no-priming condition).
Since model 1 includes several interaction terms, β0 represents our mean outcome variable for
men in the control; β2 is the effect of the treatment on men, while the total effect of the treatment
on women is represented by (β2 + β3 ). The effect of being in a same-gender group is given by β4
for men and (β1 + β4 + β5) for women in the control. Our in-group bias hypothesis (H1) then
predicts that β4 > 0 and (β1 + β4 + β5) > 0 for all outcome measures, except individual quiz score.
We can also use model 1 to test the gender priming hypothesis (H2). H2 predicts that subjects
are more likely to cooperate with partners of their same gender in the treatment than in the
control group. This would mean that (β2 + β4+ β6) > 0 and (β1 + β2 + β3 + β4+ β5+ β6+ β7) > 0
for all outcome measures except individual quiz score.
Model 2 allows us to test the stereotype threat hypothesis (H3). H3 predicts that β2 > 0 and β1+
β2+ β3 < 0 for outcome variables which measure communication behavior (i.e., words written
and chat entries). We report the results of our regression analysis in Tables 2 and 3. All of the
regressions control for the observable demographic variables and report robust standard errors.
[Table 2 and 3 Here]
To test our in-group bias hypothesis (H1), we examine the degree to which communication and
performance differs in same-gender groups compared to opposite-gender groups. We find that
men write 5.02 more words (p=0.181) and send 1.14 more chat entries (p=0.248) when matched
with other men, compared to when they are matched with women. For women, the differences
are even larger with women writing an additional 28.04 more words (p=0.000) and 2.57 more
9
chat entries (p=0.000). However, when we look at team performance, we find that men in samegender pairings scored 3.39 points worse (p=0.017) and women in same-gender pairings scored
2.68 points worse (p=0.000), compared to mixed-gender pairings. These two results among the
participants in our control group highlight two potential tradeoffs of gender diversity: increased
performance and reduced communication. The higher performance among mixed-gender groups
in our experiment may be particularly large since the real-effort task that we use draws on the
different relative strengths among men and women.
Our second hypothesis (H2) predicts that the gender priming treatment will increase subjects’
likelihood of cooperating with same-gender partners. We find mixed support for this hypothesis
in our analysis. When compared with their counterparts in the control group, men in same-gender
pairings in the treatment group write 13.65 more words (p=0.312), and make 5.4 more entries
(p=0.121). Women in same-gender groups, on the other hand, seem to be affected quite
differently by the treatment, writing 3.55 fewer words (p=0.753) and making 2.31 fewer entries
(p=0.392). Here the gender priming seems to increase male cooperation, supporting our
hypothesis, while it decreases female cooperation. This could be in part due to the effects of H3,
which we explore below.
Though cooperation levels vary by gender, both groups experience a decrease in efficiency.
While men communicate more in same-gender pairings in the treatment, they score 0.14 points
lower on average (p=0.001). Women also perform significantly worse on the quiz in samegender groups when primed, scoring 4.02 lower on the group quiz (p=0.014). With both shifts,
we find that communication becomes more inefficient in the treatment, as evidenced by the
lower quiz scores in both groups.
To test the stereotype threat in communication (H3), we use the coefficients in model 2. When
gender identity is primed, men write 4.05 more words (p=0.755) and make 3.75 more chat
entries (p=0.254). Women in the treatment write 8.76 fewer words (p=0.441) and make 2.07
fewer chat entries (p=0.480). Though not statistically significant, these results support the
proposition that stereotype threat is a factor in communication patterns in this experiment, as
women become quieter and men become more vocal when gender identity is primed.
10
IV. Conclusion
This paper investigates the effects of priming gender identity on cooperation and communication
patterns in same-gender vs. mixed-gender groups in a controlled laboratory experiment. Our
results contribute several findings to the literature on identity priming. First, women appear to be
more responsive to priming than men. Even in the control sessions, information on the partner’s
gender can produce significant in-group favoritism among women. We find significantly higher
levels of cooperation in the real-effort task among women in same-gender groups relative to
mixed-gender groups. Similarly, our analysis of chat communications reveals significantly
higher number of chat entries and words from women when they are matched with other women
relative to when they are matched with men.
We also find that priming gender identity seems to invoke stereotypes about men and women’s
roles in communication, causing men to be significantly more vocal, and women to communicate
less. In particular, we find that when gender is more salient, men tend to become more dominant
in the conversation, taking on a trait that is stereotypically male, while women assume a
stereotypical more passive, quiet role. This appears to hold true even in same-gender pairings,
since women communicated less in the treatment regardless of whether they were in-group or not.
Notably, these imbalances in communication patterns of men and women lead to an increase in
inefficiency in mixed-gender groups. As communication patterns changed during the treatment,
quiz scores dropped as well leading to higher level of inefficiency, compared with the control.
This holds true especially for men in our study and suggests that making gender more salient
diminishes subjects’ ability or motivation to remain task-oriented.
Research in social sciences provides several potential explanations for our findings. In addition
to facing external barriers in the workforce, women are affected by internal barriers significantly
more than men (Sandberg 2013). For example, women are shown to lack self-confidence and
internalize negative societal cues about gender stereotypes and what defines “appropriate”
behavior. Similar to the results reported in this paper, Karpowitz and Mendelberg (2014) show
that women are less likely than men to talk and to influence others when discussing matters of
common concern in a series of experiments involving a deliberation task.
11
Our findings are also largely consistent with the social-psychological phenomenon of “stereotype
threat.” Making gender more salient in our experiment makes subjects more likely to perform in
accordance with the gender-specific stereotype. While the relationships we document in this
specific sample and environment may not be immediately generalizable to broader populations
and settings, the conclusions we draw are novel and should motivate researchers to explore
further the role of gender and other identities in organizational settings, particularly as the
workforce is becoming increasingly diverse.
12
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Table 1: Mean cooperation and communication behavior by treatment and gender
Male
Female
Control
Treatment
7.83
8.42
[2.53]
[2.37]
Control
8.95
[2.25]
Treatment
8.48
[2.29]
Group Quiz Score
16.35
[4.98]
15.27
[4.94]
14.45
[4.51]
15.11
[4.83]
Words Written
74.53
[39.18]
79.96
[42.64]
83.5
[46.52]
66.45***
[32.66]
Chat Entries
19.23
[8.95]
23.28***
[10.88]
21.02
[9.60]
17.48***
[9.45]
Observations
88
127
92
117
Individual Quiz Score
Notes: Standard deviations are in square brackets. Observations shown are for the quiz rounds.
Some observations were dropped from quiz variables because of a technical error that caused the
screen to freeze during the quiz. Individual quiz scores are based on a sample of 110 men and
106 women. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels,
respectively.
Table 2: Impact of gender priming on performance and communication
Individual Quiz
Group Quiz
Words Written
Chat Entries
Score
Score
Female
-1.25***
-1.61
9.50
1.76
(0.18)
(0.98)
(8.27)
(1.70)
Priming
-0.50
-0.83
4.05
3.75
(0.58)
(0.95)
(12.58)
(3.07)
Female *Priming
1.00***
1.46
-22.31**
-7.58**
(0.22)
(1.31)
(9.50)
(2.62)
Sample mean
8.42
15.27
75.88
20.35
R2
0.049
0.078
0.058
0.065
N
216
424
424
424
Notes: Robust standard errors are given in parentheses. All regressions control for age, GPA,
marital status, race, and university major. ***, **, and * indicate statistical significance at the
1%, 5%, and 10% levels respectively.
16
Table 3: Impact of gender priming and gender composition on performance and
communication
Variable
Female
Priming
Female *Priming
Ingroup
Individual Quiz
Score
-1.25***
(0.18)
-0.50
(0.58)
1.00***
(0.22)
--
Female *Ingroup
--
Ingroup*Priming
--
Female*Priming*Ingroup
--
Group Quiz
Score
-1.97**
(0.69)
-1.37*
(0.68)
2.04
(1.19)
-3.39**
(1.15)
0.71
(1.29)
1.23
(1.31)
-1.27
(1.72)
Words Written
Chat Entries
-2.04
(7.78)
-1.54
(12.65)
-5.52
(9.80)
5.02
(3.46)
23.02***
(2.83)
10.17
(7.13)
-32.66***
(7.76)
1.05
(1.41)
3.09
(2.67)
-4.82*
(2.22)
1.14
(0.92)
1.43
(0.91)
1.17
(1.72)
-5.37**
(1.74)
Sample mean
8.42
15.27
75.88
20.35
R2
0.0490
0.1563
0.0964
0.0782
N
216
424
424
424
Notes: Robust standard errors are given in parentheses. All regressions control for age, GPA,
marital status, race, and university major. ***, **, and * indicate statistical significance at the 1%,
5%, and 10% levels respectively.
17
Figure 1: Chat communications by treatment and gender
83.5
80
80
74.5
Average statements/words
66.5***
60
40
20
15.2
18.4***
15.8
12.5***
0
Men
Statements
Women
Men
Control
Women
Words Written
Treatment
18