The Thesis to End all Thesis

AN EXPLORATION OF GROUP GENDER COMPOSITION:
ATTRIBUTIONS MADE FOR SUCCESS AND FAILURE
by
Rebekah C. DeVore
© 2015 Rebekah C. DeVore
A thesis
submitted in partial fulfillment
of the requirements for
the degree of Master of Arts
Steinhardt School of Education, Culture, and Human Development
Department of Applied Psychology
May 2015

ATTRIBUTIONS FOR SUCCESS AND FAILURE IN GROUPS 2
AN EXPLORATION OF GROUP GENDER COMPOSITION:
ATTRIBUTIONS MADE FOR SUCCESS AND FAILURE
by
Rebekah C. DeVore
__________________ Date___________
Research Mentor
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Program Director

Acknowledgements
First and foremost, I am grateful to my family for their consistent love, support, and
encouragement, their belief in me helps me to achieve more than I thought possible. I
would like to express my sincere appreciation to Lindy Gullet and Tessa West for sharing
their expertise, guidance and encouragement each step a long the way. I am also thankful
to the HDSI Department Faculty for their help and support. I deeply appreciate Nathan
for his consistent encouragement at times when I felt I wanted to give up. My gratitude
extends to all who directly or indirectly helped me accomplish this venture. Without the
help of many this would not have been possible, and for their support I am grateful.

Table of Contents
Acknowledgements……………………………………………………...3
List of Illustrations……………………………………………………...5
Abstract………………………………………………………………….6
Literature Review……………………………………………………….7
Methods………………………………………………………………….13
Results…………………………………………………………………...18
Discussion………………………………………………………………..21
References……………………………………………………………….27
Appendices………………………………………………………………32

List of Illustrations
1. Performance Attribution by Gender……………………………….32
2. Example Vehicle Grid……………………………………………..33
3. Example Waiting Room…………………………………………...34
4. Success Manipulation…...…………………………………………35
5. Failure Manipulation………………………………………………35

Abstract
Team-based work is becoming increasingly popular in the workplace. Recent research
shows that members of groups with more females than males perceive their group as less
competent and effective, regardless of their performance ability. The present research
examines how a group’s gender composition affects group members’ attribution
evaluations (i.e. explanations of whether the group’s performance was due to effort, luck,
skill, or task difficulty) and domain specific self-esteem (i.e. how participants feel about
themselves within the group). Participants completed a male-typed group task in a virtual
setting. Groups each included five members. Participants were randomly assigned to a
group of five that included either three females (female dominant) or two females (male
dominant). At the end of the task, participants were told that their group either succeeded
(performed better than average) or failed (performed below average) at the task, and
evaluated their group’s performance. Participants in the success condition evaluated their
group as performing significantly better than participants in the fail condition. Results
suggest that group gender composition affects how people use effort to explain
performance. However, the interaction between success versus failure and group gender
composition was not significant for any of the attributions (i.e. effort, luck, skill or task-
difficulty). The results are inconsistent with previous research on attribution and no
significant effects were found based on the predicted hypotheses. Working in groups is a
vital part of most careers; implications of gender-biased attributions in the workplace are
discussed.
Keywords: gender, attributions, group-gender, gender bias, gender discrimination, group-
gender composition.

An Exploration of Group Gender Composition:
Attributions Made for Success and Failure
This research explores how group gender composition affects attribution
evaluations (i.e. explanations of whether the group’s performance was due to effort, luck,
skill, or task difficulty) and domain-specific self-esteem (i.e. how participants feel about
themselves within the group). Gender discrimination is a persistent challenge in the
workplace (Corbett & Hill, 2012; CAWP, 2014; Catalyst, 2013; Office of Science and
Technology Policy, 2014), and there is a substantial lack of women in roles that are
considered to be traditionally male-typed, (e.g. engineering or math related roles) (Lyness
2002, Powell 1999). Attributions made for success and failure (i.e. inferences made about
why people succeeded or failed) play an important role in future expectations and
motivation (Weiner, 1985, 2001, 2013). Attributions are evaluations that attempt to
explain the cause of an event. The four causal attributions most widely recognized are
effort, luck, ability, and task difficulty (Weiner, 1985, 2001, 2013). There are certain
gender biases found in the attribution process when evaluating success or failure. For
instance, people tend to explain why a woman succeeds differently than how they explain
why a man succeeds (Deaux, 1987; Dickhäuser and Meyer 2006; Jacobs and Eccles
1992; Swinton et al. 2011).
For example, if a woman is successful in math, people are more likely to explain
her success as being due to her effort; if a man is successful in math, people are more
likely to explain his success as being due to his innate ability. However, researchers have
not yet explored whether group gender composition, rather than a target’s gender, can
affect attributions made about a task groups’ success or failure. Therefore, the present

work examines how the gender composition of a group influences group members’
explanations of their group’s success or failure (e.g. my group success was due to ability;
my groups failure was due to effort), and the way members feel about themselves in the
group (e.g. I am unable to do my best in this group).
Attribution
Attribution theory has been a dominant concept in social and educational
psychology for the past three decades. The present research pulls from the causal
attribution model based on Bernard Weiner’s approach to attribution achievement and
motivation (1985, 2001, 2013). This theory assumes that people infer causes of behavior
and events (e.g. when a student fails a test they ascribe a reason for why they believe that
happened). According to the theory, there are three causal dimensions: locus of causality
(internal vs. external), stability (stable vs. unstable), and controllability (control vs. no
control).
Expectancy
Research specific to the effect of gender and attributions shows that gender tends
to affect how attributions are made on the dimension of stability. Because females are not
expected to do well on male-typed tasks, people tend to explain a woman’s success using
unstable attributions (i.e. effort or luck). In contrast, when a woman fails at a male-typed
task, people tend to explain her failure using stable causes. Because males are expected to
perform well on male-typed tasks, the reverse is true; when a man fails, people tend to
explain his failure using unstable causes (i.e. effort or luck). When he succeeds, people
will tend to explain his success using stable causes (i.e. ability). Deaux (1984, 1987)
explains this phenomenon by using the expectancy model; when performance is

consistent with expectations, outcomes will be attributed to stable causes (ability or task
difficulty) and when they are inconsistent with expectations, they will be attributed to
causes that are unstable (effort or luck). Because careers related to math and engineering
have been traditionally male-typed, it is unexpected for women to succeed and excel in
them. Based on Weiner’s theory of attribution and Deaux’s expectancy model,
expectations for women to be unsuccessful in male-typed careers influences attribution
and future motivation, making it more difficult for women to succeed and excel in male-
typed careers even though they are able.
In an experiment, Deaux and Emswiller (1974) had males and females observe
and evaluate a confederate’s performance on a task. The task was a male-typed memory
recall task. The confederates were comprised of both males and females, all confederates
performed above average on every task. When participants were evaluating male
confederates on the recall task they tended to report that his success was due to ability
more so than luck. When both female and male participants were evaluating a woman
confederate on the same task, (who performed equally as well), participants rated her
success as being more based on luck.
Similar findings occur in educational fields of research. Math in educational
settings, for example, is recognized as male-typed. Even though there are not gender gaps
in math achievement, males tend to dominate occupations that are math related (Eccles
2007, Halpern et al. 2007; Hyde and Mertz 2009; Scafidi and Bui 2010). Educational
research, pertaining to attributions and gender bias, consistently show the tendency for
boys success in math to be attributed to ability and girls success to effort, while boys
failure is attributed to a lack of effort and girls failure to a lack of ability. Gender biased

attributions have been demonstrated in a variety of empirical studies among parents
(Jacobs and Eccles 1992; Yee and Eccles 1988), students (Bornhold and Möller 2003;
Dickhäuser and Meyer 2006; Jacobs and Eccles 1992; Ryckman and Peckham 1987;
Stipek and Gralinkski 1991; Swinton et al. 2011), and teachers (Fennema et al. 1990;
Räty et al. 2002; Tiedemann 2002). Based on research in both social and educational
psychology, attributions made for an individual’s success and failure vary based on their
gender (see Appendix A for table of attribution by gender).
Group Gender Composition
Although research on attributions has only examined success and failure in
settings where men and women are evaluated independently (i.e. not as part of a group),
there exists a small body of research that suggests how attributions of success and failure
may occur within group settings. West et al. (2012) discovered that when people are in
gender diverse groups, the more women there are, the less competent the group is rated.
Five-person task groups worked together to complete a male-typed task. Groups varied in
gender composition; they either had two, three, or four women. The male-typed task was
to build a replica of a complex model made of Legos™. All members had to work
together to complete the task. When groups completed the task they brought their replica
to a judge. The judge would reject the replica if it did not match the model and the group
would have to figure out what needed to change. They would bring the replica to the
judge until it matched the model correctly. After the replica was accepted participants
evaluated the task contributions of other group members, and rated the overall
effectiveness of their group. Participant’s evaluated group members’ task contributions
and the overall effectiveness of their group. Ten weeks after the study, participants were

asked to report how interested they were in working with their group again on a graded
project. Measures of task contributions, overall group effectiveness, and desire to work
with the group in the future were reported on 7-point likert scales, 1 (disagree strongly) to
7 (agree strongly). The number of times a model was rejected was used to measure
objective performance. The extent to which an individual group member contributed to,
was focused on, was competent at, and helped the team complete the task was used to
measure the construct of task-contribution. The measure of group effectiveness included
three questions: the team as a whole worked well together, my team was good at
coordinating the work of all members, and I would like to work with the team in the
future. Results showed that as the number of women in the group increased the
judgments of the members’ task contributions, and the overall group effectiveness ratings
decreased, and when asked 10 weeks later, groups with more women had less desire to
work with their group again. The findings show that gender did not predict performance
on the task, but it did predict people’s opinions of their groups.
Although West et al. (2012) did consider evaluations made about individual group
members’ task contributions, the groups’ overall effectiveness, and desire to work with
the group in the future; explanations made for success or failure were not considered.
Some of the individual items used in measurement align with effort and others align with
skill. For example, within the task contribution construct, the extent to which a member
contributed to, was focused on, or helped complete the task would align with an effort
attribution; the question asking about a member’s competence would align with an ability
attribution. As such, the current research will consider the different dimensions on which
an individual can be evaluated. In addition, the current research will investigate how the

group’s actual performance moderates the relationship between group gender
composition and attributions about group members. I hypothesized that when evaluating
the group as a whole, members of a female dominant group would attribute their group’s
success to unstable causes (effort or luck) and failure to stable causes (ability or difficulty
of task), and the opposite would be found in male dominant groups; group’s success
would be attributed to stable causes and failure to unstable causes.
Domain Specific Self-Esteem
The way group gender composition interacts with success and failure attributions
may affect domain specific self-esteem. Research reveals that self-esteem can fluctuate
based on the context a person is in (Kernis, 2005), and that self-esteem measures are
sensitive to context (Bosson, 2000). A considerable amount of work has been directed
towards understanding self-esteem within organizational contexts. A meta-analysis of
organization-based self-esteem found: the way a person feels within an organization
significantly affects job satisfaction, commitment to the organization, motivation,
performance in-role, intentions of turnover, and other organization related behaviors and
attitudes (Pierce, 2004). There is also a considerable amount of work showing that
domain specific self-esteem varies significantly depending on gender (Gentile, 2009).
Because group work is becoming increasingly popular in the workplace and organization
based self-esteem predicts behavior and attitude outcomes, looking at how participants
feel in a group is important. In this paper, domain specific self-esteem is used to define
how the participant feels about being a member of their group, this is specific to the
domain because it is not attempting to measure how the person feels about themselves
overall (global self-esteem). If biases occur based on gender composition, success versus

failure, and the attributions made, it will be interesting to see if and how domain-specific
self-esteem is affected.
Based on the previous research I predicted that when evaluating the group as a
whole, members of a female dominant group would attribute their group’s success to
unstable causes (effort or luck) and failure to stable causes (ability or difficulty of task),
and the opposite would be found in male dominant groups; group’s success would be
attributed to stable causes and failure to unstable causes. A second prediction was that the
interaction between the condition of success or failure and the attribution made would
predict domain-specific self-esteem (e.g. if the group is female dominant and success is
attributed to unstable causes the participant would report a relatively lower domain
specific self-esteem).
Methods
Participants
Participants were 366 (189 female) Mechanical Turk users (Mage= 33.54, age
range: 18-70 years; 67% white, 23% Asian, 6% Latino, 6% Black, 2% Native
American/Alaskan Native, 1% multiracial, and 1% reported other). Participants were
Mechanical Turk users who chose take part in the study. The study was made using
Qualtrics and uploaded to Mechanical Turk. Participants were compensated with $1.00 if
they completed the study. They were randomly assigned to a female dominant (three
females: two males), or a male dominant (three males: two females) group, and a success
or fail condition.

Procedure
Participants worked in an “online group” attempting to obtain the fastest group
score while playing the game Rush Hour®. Groups all included five members; one was
the participant; the remaining four members were computer bots (i.e. computer-simulated
confederates) created for the study. The participant was led to believe the other members
of the group were other Mechanic Turk users who were taking the study. The computer-
simulated confederates were created so that all conditions were constant and controlled.
The two types of groups were male dominant (three males, two females) and female
dominant (three females, two males). The computer bots’ gender was manipulated such
that participants were either in a male dominant or female dominant group. The gender
was manipulated by using a female or male icon next to a gender specific name. The
names used for the computer bots were dependent upon the condition: Member 1 =
Michael/Emily; Member 2 = Matthew/Jessica; Member 3 = Jacob/Ashley; Member 4:
Participant; and Member 5 = Christopher/Sarah. Names were chosen based on the most
popular baby names in 1991 list, a year when a lot of potential participants were born. It
was programmed so that the groups’ dominant gender was randomized and dependent on
the participants’ specified gender, so that there was never only one female or one male in
the group.
After consent, participants were asked to give their first name and demographic
information. The participants were told they would be working on a task called Rush
Hour® in a group with four other members. They were informed the task would require
them to use their spatial reasoning to free vehicles from a traffic jam and told the five
participants with the best performance ratings would receive a $4 bonus. The participant

was shown a square grid with cars and trucks in a randomized pattern (see Appendix B
for an example vehicle grid).
Participants were instructed that the goal of the game was to free the specified
vehicle from the traffic jam and through the exit as quickly as possible. Vehicles were
each assigned a number (one through five). Each member was assigned to a number to
specify the order in which they took their turn and the vehicles they were allowed to
move during their turn. The participant was always group member four, and the other
members names were altered based on the group condition. All comments and
performance strategies of computer bots were constant, except for the change of name
and icon (i.e. female or male). Each car or truck could only move horizontally or
vertically based on the positioning and had to be moved one at a time in order to get the
specified vehicle out of the traffic jam. They were instructed that they could only move
vehicles with their assigned number. Afterwards participants entered an “online” waiting
room and were led to believe others who joined the waiting room were also participants
who would be their group members. They were shown other group member’s names and
an image signifying their gender (see Appendix C for an example of the online waiting
room). Once all five members (confederate computer bots plus the participant) arrived in
the waiting room participants were automatically directed to the next page to begin the
task.
There were two rounds, each with a different grid and car to free. Both rounds
included a planning period and an action period. Participants were shown the grid at the
beginning of each round then given one minute and 30 seconds to type their strategy to
share with their group during the planning period. After time was up they were

automatically directed to the next page. The page contained all of the group members’
strategies. They were given two minutes to read their group members strategy responses.
After two minutes they were automatically directed to the next page to begin the action
period. During this period the participant was only able to move their assigned vehicle(s),
when it was their turn to do so (e.g. Group member one was only able to move vehicles
labeled with the number one, and this member went first). Each member of the group had
their sequential turn to move their specified vehicle (participant was always fourth). The
participant saw each member’s board during that members turn, they also saw how long
it took members to complete the turn, what they decided to do, and if they wrote any
comments to the group. During the participants turn they were given 20 seconds to
choose how they wanted to move their specified vehicle(s) and an option to write a
comment to their group. Turns continued until the specified vehicle was freed through the
exit. After both rounds were completed the participant was moved into the evaluation
period. During this time, participants were shown an analysis of their group’s
performance. The times were manipulated so that if they were in the failure condition the
average time of other groups was below their group’s performance average, and in the
success condition the average time of other groups was above their groups performance
average. The group’s performance time average was held constant, and the average they
believed were other groups was manipulated for the failure or success condition.
Numbers used were based on how long the different computer bot members were
programmed to take during their respective turns plus the planning periods and the
estimated time it would take participants. For the success condition participants were
shown that the average time of the groups who had already completed the study was 9

minutes and 24 seconds; their groups average time was shown as 8 minutes and 14
seconds; the individual group members times were shown as follows: Member One, 1
minute and 10 seconds; Member Two, 1 minute and 0 seconds; Member Three, 0 minutes
and 57 seconds; Member Four, 1 minute and 3 seconds; Member Five, 0 minutes and 50
seconds. Each group member’s number, name, and then completion time were shown on
the group’s analysis. For the failure condition all numbers were shown the same as the
success condition, the only number that changed was the average completion time of
other groups who had previously completed the study. The number shown for the average
of all the groups who had completed the study in the failure condition was 7 minutes and
10 seconds. See Appendix D for examples of each condition. Participants were expected
to believe that their group did relatively better or worse than the average performance of
other groups. Participants evaluated their group’s performance and member’s
performances individually. Throughout the evaluation period a transcript of the groups
analysis was available for viewing, so that participants had the option to use the analysis
to help them evaluate their group.
Measures
Groups were manipulated to either fail or succeed. The manipulation was based
on the groups timing. Groups that were manipulated to fail had a completion time that
was slower than the reported average of all that groups that had participated. Participants
in groups that were manipulated to succeed were shown a completion time that was faster
than the reported average. The times used were
Participants evaluated themselves, and the group as whole. The attribution measurement
consisted of four items about why they believed their group succeeded or failed

(effort/luck vs. ability). The attribution measurement was based on success and failure
attribution questions used in previous research (Räty et al., 2002; Deaux & Emswiller,
1974). There were four attribution questions. The questions were each on a seven point
likert scale, ranging from not at all due to (skill, effort, luck, or task difficulty) to purely
due to (skill, effort, luck or task difficulty). The questions asked were: (a) to what extent
was your group’s performance due to skill; (b) to what extent was your group’s
performance due to effort; (c) to what extent was your group’s performance due to luck;
and (d) to what extent was your group’s performance due to the difficulty of the task?
Participants then answered four self-evaluation items about how they felt about
themselves in their group. Items were based on the Rosenberg Self-Esteem Scale and
altered to be specific to the group context (Rosenberg, 1987). The questions were on a
five-point likert scale ranging from strongly disagree to strongly agree. The questions
were: (1) In this group I was able to do my best; (2) I was able to share a number of my
good qualities with this group; (3) I feel I do not have much to be proud of in this group;
and (4) I have a positive attitude towards myself in this group. Question three was reverse
coded after the data was collected. To check the success versus failure manipulation, the
question: “In terms of performance, how well has your group done on the task?” was
asked. Findings should show a significant difference between the success and failure
condition. Participants should have felt that their group did not perform as well if they
were in the failure condition.
Results
Simple linear regressions were run on group gender, participant gender, success
versus failure, and the interactions between the variables. Regression analyses were run

using SPSS statistical software. The dependent variables were effort, skill, luck, task-
difficulty, and domain-specific self-esteem. A manipulation check was run to ensure
participants were experiencing the success and failure conditions differently.
Effort
If a participant was in a female-dominant group and the group succeeded, a
trending effect showed participants were more likely to attribute that success to effort, but
this finding was not significant, t(358) = 1.558, ps > .120. Participants were significantly
more likely to attribute their group’s performance to effort if they were in the success
condition, t(358) = 3.704, p < .001. Participants reported their group's performance as
more due to effort if they were in a male rather than a female-dominant group, but this
effect was not significant, t(358) = -1.629, ps > .104.
Skill
Participants in a male-dominant group were not significantly more likely to
attribute their success to skill if they succeeded, t(358) = -.032, ps > .975. Participants did
not view their group’s performance as being more due to skill if they were in a male,
rather than a female-dominant group, regardless of the success or failure condition, t(358)
= -.083, ps > .934. The way participants reported their group’s performance as being due
to skill did not vary significantly between the success and failure conditions, t(358) =
.208, ps > .208.
Task-Difficulty
Participants in female-dominant groups that succeeded were not significantly less
likely to attribute their group’s performance to task difficulty than participants in male-
dominant groups who succeeded, t(358) = .392, ps > .695. Difficulty of task evaluations

did not vary based on the group gender composition, t(358) = -1.144, ps > .253.
Participants did not vary in their task-difficulty attributions based on the success or
failure of the group, t(358) = .884, ps > .378.
Luck
Participants in female-dominant groups that succeeded were not significantly
more likely to attribute their group’s performance to luck, t(358) = .-.809, ps > .419. Luck
evaluations did not vary based on the group gender composition, t(358) = -.307, ps >
.759. Participants did not vary in their luck attributions based on the success or failure of
the group, t(358) = .237, ps > .813.
Domain-Specific Self-Esteem
Participant domain-specific self-esteem did not vary dependent on the interaction
between group gender composition and the success versus failure condition, t(358) = -
.434, ps > .665. There was no significant effect of group gender composition on domain
specific self-esteem, t(358) = -.265, ps > .792. Participants in the fail condition reported
significantly lower domain specific self-esteem, t(358) = 2.330, p < .05
Overview
There were no significance effects on attribution evaluations of luck, ability, or
task difficulty. Participants reported their group's performance as being more due to effort
when they were in male-dominant rather than female-dominant groups, but the effect was
not significant. Participants were more likely to attribute success to effort in a female
dominant group, but the effect was not significant. Participants were significantly more
likely to attribute success to effort when they were in the failure condition. Being in a
female or male dominant group did not have a significant effect on domain-specific self-

esteem. Participants reported significantly lower domain-specific self-esteem if they were
in a group that failed. A manipulation check revealed participants did feel differently
about their team’s performance based on the success or failure condition. They felt their
team did significantly worse if they were in the fail condition, t(358) = 4.76, p < .001.
This was expected, and demonstrates the manipulation was effective.
Discussion
Although there were significant effects found in the results, there was no evidence
in this study to support the central hypotheses; female dominant groups would be more
likely to attribute their group’s success to unstable factors (effort or luck/chance) and
their group’s failure to stable factors (ability or task difficulty), and male groups would
be more likely to attribute their group’s success to stable factors and failure to unstable
factors. Among the differing performance attribution outcomes, evaluations based on
effort showed the most movement within the data. Trending effects revealed that overall
male-dominant group performance was more due to effort; in the success condition
female-dominant group performance was more likely to be attributed to effort than male
dominant groups. Being in a female group and attributing success to effort is in line with
previous research and the main hypotheses, because effort is an unstable attribution, and
it is unexpected that females should succeed at a male-typed task, but this effect was only
trending and not significant. The trend showing that regardless of success or failure male-
dominant groups’ performance is more likely due to effort is unexpected and not
supported by previous attribution research. Pertaining to effort there was a significant
effect showing that participants were more likely to attribute performance to effort if they
were in the success condition. Performance attribution results suggest that effort

attributions are used for failure in a male-dominant group, more so than in female-
dominant groups who fail. Because effort was significantly more likely to be attributed in
successful groups, trending in female-dominant groups who succeeded, and in male-
dominant groups for both success and failure. Attributing effort to male-dominant groups
who failed is in line with the main hypotheses because effort is an unstable attribution,
and it is unexpected that males would fail at a male-typed task.
Even though the results for skill, task-difficulty and luck were not significant,
they are still informative. It is possible that those concepts should be captured in a
different way. The results suggest that people in groups use effort to explain success and
failure more so than they use any other attribution explanation (i.e. skill, luck, or task
difficulty). People in groups use effort to explain both success and failure, if there are
more males in a group it is more likely that both success and failure will be attributed to
effort. This is helpful because if the group fails they are able to just blame it on not
putting in enough effort. If there are more females in the group and the group succeeds it
is likely that it will be attributed to effort, but if there are more females in the group and
the group fails it is less likely that the performance will be attributed to effort. It is
inconclusive how groups with more females explain their failure. It is unfortunate that
groups with more females do not explain failure as due to lack of effort, because using
effort to explain failure makes it more probable for future motivation to achieve at the
task.
The effect of group gender composition and attribution on domain specific self-
esteem was not explored because there was no main effect found in the interaction
between gender composition and attributions for success or failure. It is still possible that

domain specific self-esteem is affected by differing attributions for group success or
failure, but this study was unable to capture an interaction between group gender
composition and attributions for success or failure. Domain specific self-esteem was
reported as significantly less in groups that failed. This supports previous research
claiming that the context influences self-esteem. This result suggests future research
could explore workplace interventions based on resilient responses to lowered self-
esteem due to group failure. Previous research shows that employees who feel better in
their work environment produce more; interventions aimed at learning from failure
instead of becoming defeated by it could help alleviate turnover and under-productive
employees.
Limitations
The study had limitations that should be discussed. Because there is extensive
research supporting individual attribution gender bias; when women perform a male-
typed task, attributions made for their successes are more likely to be unstable and males
successes more likely to be stable; it is possible that participants did not view the task in
this study as male-typed. Therefore, the attributions made for success or failure would not
have any predicted effects.
In previous attribution research there are considerable inconsistencies found in
measurement. Studies use a variety of measures to capture attribution effects. There are
measure that ask direct questions about each attribution and measures that ask indirectly
to capture the idea of each attribution. There are measures that use likert scales for each
individual attribution and bipolar likert scales with the attributions paired against one
another (e.g. skill on one end of the scale and ability on the other). There are also

measures that ask open-ended questions and code the answers to gauge which attribution
it was most in line with. The lack of a valid, reliable measure used across many studies is
a critique of the theory. It is possible that the lack of an accurate measure has made it
difficult to capture the effect of group gender composition on attributions in this study.
Wording the questions as “how much was your groups performance due to
effort…” (for both the success and failure conditions) makes the question symmetrical,
but it does not accurately reflect the concept of the attribution. If, on the failure condition
the question was formatted as “how much was your group’s performance due to lack of
effort,” it more accurately describes the concept but cannot be used as the same question
in the success condition. This presents a conceptual problem; some previous research
uses a bi-polar scale with effort at one end and ability or skill on the other. This more
accurately captures the theoretical concepts but is not as accurate of a measurement. If
participants rate a high score on effort they are automatically rating a low score on effort,
capturing an effect that may not be accurate. These conceptual problems in previous
research make it difficult to identify and explain attribution bias outcomes and processes.
Participants in this study evaluated their group mates with a very limited amount
of information. During evaluation, participants were shown only a numerical datum about
each group member. Having a transcript of each member’s comments throughout the
study available to view during the evaluation period could have made a difference in the
participant’s evaluations of the group. Evaluation based on viewing members’ comments
would be closer to real life; people evaluate group members based on comments made
and not just data output.

Having the sample limited to those who are working in male-typed careers might
reveal different trends. This study did not ask about the participants’ career fields. The
possible effects of this study are directed towards those working in traditionally male-
typed careers, limiting the sample to those who are already in this field may prove more
productive.
Future Research
Research exploring group gender composition and its effect on success and failure
attributions are influential in understanding how to eliminate gender bias in the
workplace. Because there is extensive research exploring and defining the processes of
gender bias on an individual level, and the context is instrumental in producing different
effects; the context of being in a group with differing amounts of males and females
could have processes unique to being in a group.
Future research could explore, more in depth, how effort attributions are affected
by the interaction between group success versus failure and gender composition. The
interaction between individual gender, group gender, and company gender (proportion of
males to females in the entire company) and how success or failure on all three levels
(individual, group, company) changes attributions or motivation within individuals,
would be interesting to explore. If gender biased attributions differ dependent on the
overall companies’ gender, the task groups’ gender, and the individual gender, it would
be helpful to know why and how so future research would be able to develop productive
interventions aimed at changing systemic gender bias.
Qualitative research about women in traditionally male-typed careers that
explores how women and men feel when task groups succeed or fail could provide deeper

insight and understanding in the processes that occur within group work. Having in-depth
interviews with men and women before, during, and after they have worked within task-
groups that have either succeeded or failed, could reveal processes and trends that were
not suggested in this paper. It would also provide understanding into the ways attributions
change over time and if they vary based on individual and group gender.
If a group’s gender composition has different effects and processes than merely
the summation of the individual gender effects and processes, then the way we study and
attempt to change gender bias in the workplace should be adjusted accordingly. Group
work is an inescapable part of most workplaces and women are still having a difficult
time moving up the ranks within traditionally male-typed careers (even though research
shows women to be equally capable). Therefore, focusing attention on how groups think
about success or failure based on group gender could reveal new conclusions;
conclusions necessary to relieve unfounded bias and allowing women to be successful in
traditionally male-typed careers because of their ability.

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Appendix A
Performance Attribution by Gender
Success Failure
Male Ability
Lack of Effort, bad
luck
Female Effort, Chance/Luck Lack of Ability

Appendix B
Example Vehicle Grid

Appendix C
Example Waiting Room

Appendix D
Success and Failure Manipulations
Figure 1. Success Manipulation. This figure is an image that illustrates what a participant
saw if they were in the success condition.
Figure 2. Failure Manipulation. This figure is an image that illustrates what a
participant saw if they were in the fail condition.

The Thesis to End all Thesis

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