What if your colleagues discriminated against you, just for being assertive? Unfortunately, gender bias is a reality in today’s workplace. This study reveals women’s perceived competency drops by 35 percent and their perceived worth by $15,088 when they are equally as assertive or forceful as their male colleagues. Assertive men are also punished, but to a much lesser degree.
Emotional inequality is real and it is unfair. And while it is unacceptable and needs to be addressed at a cultural, legal, organizational, and social level—individuals can take control. Those who use a brief framing statement that demonstrates deliberation and forethought reduce the social backlash and emotion-inequality effects by 27 percent.
We at VitalSmarts have worked for the last thirty years to help teams and organizations eradicate undiscussables. We’ve developed models and skills to help individuals voice their concerns. Over the past few years, we’ve become increasingly interested in the special challenges women face when they speak up in the workplace.1,2,3
For example, imagine you get to see a manager in a meeting, working with other managers. You already know this manager has been hired by your organization and will soon become your peer. You watch as your future colleague speaks up in a forceful way that borders on anger: “I’m not on board with the direction this decision is going—no, I’m not finished. I won’t back down from this position, and I’m not going to commit my team and resources to this project until we have more conclusive evidence to work with. Period.” It’s a bold, brash, and emotional statement that doesn’t demonstrate much listening or patience. What do you think of your new colleague?
Observers who hear this interaction think less of their new colleague. There is a social backlash against people who voice this kind of strong disagreement. But it turns out the gender of the colleague is also hugely important. This study begins by replicating what others have found: women who disagree in forceful, assertive ways are judged more harshly than men who do so.
Today’s workplaces cannot thrive if employees don’t speak up, so we need ways to decrease the social backlash people experience when they do. And, because women suffer this backlash more than men, we especially need solutions that work for women.
Ultimate solutions will require changing the cultural, legal, organizational, and social influences that make it costly for employees, especially women employees, to speak up. At the same time, people need strategies they can use today to express strong opinions while minimizing social backlash.
Silence in Crucial Moments
When employees fail to speak up, people die. Research shows there is an enormous human toll to workplace safety,4 patient safety,5 product safety,6 and consumer safety7 when employees aren’t able to raise concerns.
When employees fail to speak up, organizations fail. Evidence reveals that when coworkers can’t address their concerns, projects go over budget,8 development schedules slip,9 ethics problems proliferate,10 innovations stumble,11 and employee engagement tanks.12
Yet organizational silence continues to be a pervasive problem across all industries.13
Of course, most conversations aren’t plagued by silence. Employees aren’t challenged by ordinary discourse. The problem arises in relatively few crucial conversations—conversations that include three elements: differing opinions, high stakes, and strong emotions.14 These interactions tend to be sensitive, political, and controversial. Participants fear that sharing their views will lead others to judge them negatively. As a result, they keep their concerns to themselves.15
Paradoxically, these crucial moments when people are most likely to hold their tongues are also the times when it is most important for them to speak up and share their points of view.16 The combination of high stakes and differing opinions is precisely when diverse perspectives provide the greatest benefit to a group.17
Hazards of Speaking Up
When it comes to speaking up, people’s fears are well founded. A survey of eighty-seven whistleblowers revealed that all but one had experienced retaliation.18 But the usual punishments for speaking up are far more subtle and insidious.19 People learn to watch out for the raised eyebrow, the dismissive frown, and other signs of disapproval or loss of respect.20 These signs of social backlash warn that the working relationship or career is at risk.
For example, in an interview with The Washington Post, General Jay Garner explained his failure to share three major concerns he had with the war in Iraq during a debrief with the President by saying, “If I had said that to the President in front of Cheney and Condoleezza Rice and Rumsfeld in there, the President would have looked at them and they would have rolled their eyes back and he would have thought, ‘Boy, I wonder why we didn’t get rid of this guy sooner?’”21 A retired general with nothing to lose was silenced by the fear of an eye-roll.
Subtle disparagement causes unhealthy silence and research shows that women risk this disparagement any time they open their mouths. For example, in one study, subjects were given a description of a hypothetical CEO with the surname Morgan. Morgan, they were told, “tends to offer opinions as much as possible,” and compared to other CEOs, “Morgan talks much more.” In some cases, the sketch described Mr. Morgan and in others Ms. Morgan. The exact same characterization caused observers to respect Mr. Morgan more and Ms. Morgan less.22
Speaking up in forceful, assertive ways is even more risky for women. A woman’s forcefulness is more likely to be seen as anger rather than strength. 23 This judgment costs women both prestige and influence, as showing anger in the workplace is usually seen as inappropriate for both men and women.24
Women are burdened with the additional assumption that they will conform to cultural stereotypes that typecast women as caring and nurturing.25 Speaking forcefully violates these cultural norms and women experience a more punishing backlash than men. Women suffer from emotional inequality in the workplace.26
In a landmark study, Victoria Brescoll and Eric Luis Uhlmann asked the question, “Can an Angry Woman Get Ahead?”27 Their study documented the unequal penalty women experience for showing anger at work, but then went further to explore the reasons behind this gender effect. Their results suggest that the penalty occurs because observers attribute women’s anger to internal characteristics (“she is an angry person,’’ ‘‘she is out of control”) while attributing men’s anger to external circumstances (“he was under a lot of stress,” “things were out of control so someone had to take charge”). While this bias against women is unfair, it is often unconscious or unintentional—which makes it even harder to address.28
What can be done about emotional inequality? The Research
While unacceptable, gender bias does exist, and learning more about the nuances of its pervasiveness is the first step toward igniting change. Study One of our two-part study was done with that information-seeking mission in mind. Based on our own and others’ research, we acknowledge that ultimately, eliminating bias altogether will require changing the cultural, legal, organizational, and social influences that make it costly for employees—especially women employees—to speak up. It is time these efforts were set swiftly in motion.
And while society and systems slowly turn the wheels of change, individuals can gain control by being both aware of and equipped with skills to minimize the pernicious effects of this toxic cultural norm. We believe people need strategies they can use today to express strong opinions while minimizing social backlash. Study Two of our research was done with this goal in mind—to develop specific skills anyone—especially women—can use on the job to be forceful, assertive, and honest without experiencing social backlash.
The purpose of Study One was to recreate the social backlash and emotion-inequality effects in a controlled laboratory setting. We had to demonstrate these effects in a reliable way before we could test solutions to reduce them.
We created videotaped interactions so we could control what observers would see. We hired two actors, one male and one female. They were both white, in their mid-thirties, and wore business-casual attire. They were rated within one point of each other on a ten-point scale of attractiveness.
The interactions featured either the male or female actor seated at a table in a meeting room. The camera focused tightly on the actor so that no other meeting participants could impact observers’ judgments. The actors used identical scripts and we coached them so their performances showed the same level of forcefulness and similar tone and body language.
This laboratory setting allowed us to test the following four variables:
Content: The words the actors recited. We tested three scripts that each took place during staff meetings. A “neutral” script had the actors provide a simple status update. It was not high-stakes or emotional and it didn’t voice any disagreement with the group. The purpose of this script was to get a baseline comparison of people’s judgments of the man and woman. Other subjects were asked to watch the same actors deliver one of two “high-stakes disagreement” scripts. In the “moderate” script, the actor was working with manager/peers and imposed moderate consequences (“I’m not going to commit my team and resources to this project until we have more conclusive evidence to work with”). In the “extreme” script, the actor was working with subordinates and imposed extreme consequences (“I’m going to ask that everyone on this team reapply for their jobs and submit to competency testing”).
Forcefulness: The delivery the actors used. We tested four levels of forcefulness: neutral, mild, moderate, and strong.
Reporting Relationship: The relative level between the actor and the observer/subjects. We tested three reporting relationships: actor is slated to become the observers’ boss, the observers’ peer, or the observer’s subordinate.
Gender: The gender of the actor. In this first study, 4,517 participants played the observer role. Each saw a single thirty- to forty-second performance and then rated the “manager” using a twenty-item survey.
We used the surveys to track observers’ evaluations of the actors’ status, competency, and worth (estimated salary). We calculated the difference in these evaluations between the neutral and the disagreement conditions.
When the actor was described as “a manager who will become your boss,” the content and emotion of their statement dominated all other variables. These observers saw their boss speak forcefully to team members and tell them they would need to reapply for their jobs. In these conditions, observers punished the bosses with huge drops in perceived status, competency, and worth—regardless of whether the boss was male or female. The more forceful the boss’s statement, the greater the drop.
When the actor was described as “a manager who will become your new subordinate,” we saw mixed results. When the actors became assertive, the male and female actors were punished equally for perceived status and competency, but the female’s perceived worth was reduced significantly more than the male’s.
When the actor was described as “a manager who will become your peer,” we saw the gender effect we were expecting. When the actors moved from the neutral to the moderate script, and showed increasing levels of forcefulness, they were both punished with drops in perceived status, competency, and worth. However, observers punished the female actor far more than the male actor.
The chart below illustrates the social backlash and emotion-inequality effects we observed in the peer condition. The bars represent the percentage drop averaged across status, competency, and worth.
This final condition became our laboratory for testing new skills. We used the moderate script, the moderate level of forcefulness, the peer relationship, and the male and female actors. This combination replicated the disproportionate punishment women experience when they speak forcefully to disagree about a high-stakes, emotional subject.
Study One confirmed the risks involved in speaking up when differing opinions, high stakes, and strong emotions are involved. In every case, observers rated forceful, assertive actors as lower in status, competency, and worth.
This study also confirmed that many factors combine to determine the extent of the backlash an actor experiences. All of the factors we manipulated—the content of the statement, the forcefulness of the delivery, the reporting relationship between the actor and observers, and the actor’s gender—affected the size of the social backlash. However, sometimes a single factor would overwhelm the others—as when the actor was presented as the observers’ future boss, or when the forcefulness of the delivery was especially strong. In these cases, the impact of other variables, such as the actor’s gender, were masked.
This finding serves to warn us that many phenomena, such as the emotion-inequality effect, occur within a larger context. They aren’t uniform or always present and can be masked by other immediate concerns.
However, just because we don’t see the emotion-inequality effect in all of our experimental conditions, doesn’t mean it isn’t there below the surface. Our study is limited, in that it focuses on observers’ immediate reactions to a single interaction. And yet, we are asking observers to judge status, competency, and worth—which are broad judgments usually based on patterns of interactions over time and circumstances. In the real world, the interaction we videotaped would be one incident among many that observers would use to evaluate our actors. The emotion-inequality effect may become more pronounced over time, because, while circumstances and behaviors vary, gender remains constant.
The purpose of Study Two was to use our controlled setting to test ways to reduce social-backlash and emotion-inequality effects. Our starting point was Brescoll and Uhlmann’s (2008) finding that observers’ judgment that a person had lost control played an important role in determining the status a person was accorded. Observers were more likely to judge an angry woman to have lost control, and this difference explained the anger inequality effect.
Our data from Study One confirmed this finding. When our observers judged someone, male or female, to have lost control, they punished that person with drops in status, competency, and worth. In fact, perceived loss of control predicted social backlash better than gender did.
We decided to test whether brief, framing statements that demonstrate deliberation, forethought, and control would reduce the social backlash and emotion-inequality effects.
We tested three frames: a Behavior Frame, a Value Frame, and an Inoculation Frame. The frames were each about five seconds long and were edited onto the front of the videos from Study One that showed actors demonstrating moderate forcefulness.
Behavior Frame: The actors described what they were about to say before saying it: “I’m going to express my opinion very directly. I’ll be as specific as possible.” The intent of this frame was to make the actors appear in control—to show that the actors had thought about what to say and were acting deliberately.
Value Frame: The actors described their motivation in value-laden terms before making their forceful statement: “I see this as a matter of honesty and integrity, so it’s important for me to be clear about where I stand.” The intent of this frame was to show the thought process for the actors. It gave a positive explanation for their forcefulness.
Inoculation Frame: The female actor suggested it could be risky for a woman to speak up the way she was about to: “I know it’s a risk for a woman to speak this assertively, but I’m going to express my opinion very directly.” The intent of this frame was to prime the observers to the possibility that they would be biased against her. We were interested in whether this would impact their judgments in a positive or negative way.
In this second study, 7,921 participants played the observer role. Each saw a single thirty-five- to forty-five-second performance and then rated the “manager” using the twenty-item survey from Study One.
Each of the frames worked to significantly reduce the social backlash effect. The Behavior Frame produced significant improvements over No Frame, and the Value Frame worked significantly better than the Behavior Frame. These frames worked equally well for both the male and female actor. The Inoculation Frame worked significantly better than the Value Frame. The Inoculation Frame was only tested with the female actor.
The chart below illustrates the positive impacts of the different frames. The bars represent the percentage reduction in social backlash, averaged across status, competency, and value.
Framing statements clearly have potential as partial solutions to social backlash and emotion-inequality effects. However, even the most successful frame produced only a twenty-seven percent reduction in social backlash. There is more work to be done. Fortunately, the controlled setting we’ve created will allow us to test many different frames to find the most effective approaches.
Behavior Frame: The Behavior Frame tested whether describing the statement before making it would reduce the social backlash. We think the Behavior Frame works by signaling that the forcefulness is deliberate, rather than spontaneous. It shows that the actor has considered what he or she will say and how he or she will say it. In this way, the frame may prevent the observers’ negative assumption that the actor has lost his or her temper and is out of control.
Value Frame: The Value Frame tested whether explaining and owning the forcefulness would reduce the social backlash. The actor justifies the forcefulness and makes it a virtue. The Value Frame may accomplish the same function as the Behavior Frame: i.e., show that the strong emotion is deliberate and under control.
Inoculation Frame: The Inoculation Frame tested whether warning people to watch out for their own implicit biases would cause them to adjust their judgments. We were a bit surprised at how well it worked and we are skeptical the Inoculation Frame will work if used repeatedly. It could be seen as “playing a card,” in this case the “gender card.” Our concern is that it may create short-term benefits, but damage a user’s reputation. We wouldn’t want to encourage women to use a strategy that felt manipulative or injured their reputations over the long term. More research needs to be done on this subject.
How Do the Frames Work?
We believe that social backlash and emotion-inequality effects stem from observers’ understanding and misunderstanding of their own personal safety. When an actor speaks up and voices a disagreement that is high-stakes and emotional, observers immediately assess its impact on them. They try to judge whether the actor poses a threat. The more likely and costly the threat, the more unsafe the observer feels.
The factors we manipulated in these studies had their impact because they either increased or decreased safety. For example, when we had the actor be the observers’ boss, the threat became more credible. When the actor was a peer or subordinate, the observer probably felt safer.
When we had the actor tell his/her team that they’d have to “re-apply for their jobs and submit to competency testing,” the threat became larger. The observers saw that the actor was willing and able to take away people’s jobs.
Increasing the forcefulness of the statement also increased the threat level. People who are passionate are more likely to act, and are more likely to act in ways that harm others. It makes sense that the observers in this study felt less safe.
Using a female instead of a male actor wouldn’t, in an objective world, make observers feel unsafe. And yet, in our experiment as well as in others, observers acted as if it did. We tend to agree with Brescoll & Uhlmann that observers are quick to think forceful women have “lost their temper” or are “out of control”—and this makes observers feel unsafe.
The frames we tested worked to the extent that they restored safety. The Behavior and Value Frames showed the actor as reasonable and thoughtful, rather than out of control. In addition, the Value Frame suggested the actor had integrity and had mutual purpose with the observers. The Inoculation Frame made an implicit appeal to fairness. It may even suggest that the actor is asking for the observers’ mercy, rather than threatening their safety. It is an interesting and somewhat troubling frame.
We believe that the most effective skills will include frames that deal more directly with the safety issue. These frames will need to signal respect and mutual purpose.
Speaking forcefully creates a social backlash. That backlash is amplified for women. If not managed well, this phenomenon can adversely affect an individual’s career and can prove costly to an organization’s effectiveness. We believe the implications of this research will empower individuals and leaders to engage in and encourage candid discussion while minimizing negative impacts.
When an individual expresses a strong opinion, safety may break down if the listener negatively interprets the speaker’s intent. When this happens, communication suffers and the speaker loses influence. Here are a few recommended actions:
Use a Behavior or Value Frame: Use one of these frames before stating your disagreement. The Behavior Frame demonstrates you are in control of your emotions. The Value Frame demonstrates commitment to a shared value.
Share Your Good Intent: Quickly and clearly explain your positive intent before you share your strong opinion. It may also be useful to explicitly state what you do not intend. For example, “I came to speak with you to try to find the best way to solve our inability to match specs. I didn’t come here to finger point or blame.”
Learn Additional Skills to Create Safety: High-stakes, emotional, disagreements require special skills, but these are skills anyone can learn. Begin by reading a book, participating in a webinar, or taking a course. Make sure to build in realistic practices so you’ll learn how to use your skills under pressure.
Social backlash can shut down even the best and bravest in your organization. Leaders need to make it safe for employees to speak boldly for what they believe. And leaders need to acknowledge that women experience this social backlash more than men, especially when they are forceful.
Our study focused on specific actions a speaker can take to reduce the backlash. We did not address the deeper problems—why observers punish forcefulness as strongly as they do, or why observers judge women behaving forcefully more harshly than men who behave similarly. However, leaders will need to address these deeper problems. Otherwise, they place the burden entirely on the speaker—disproportionately women—and this could perpetuate the deeper problems, or even make them worse.
With these caveats in mind, here are actions leaders can take:
Open the Discussion: Shine a spotlight on the problems of social backlash and emotion inequality. Discuss the implications this research has for the day-to-day operations in your workplace. Identify times, places, and circumstances when these problems are likely and cue people in those moments to guard against them.
Lead the Way: Take concrete actions that show commitment to counteract the implicit bias women face in the workplace. For example, while we have reservations around using the Inoculation Frame discussed in this study, one tech company leader we interviewed thought it was an excellent tool for women leaders to use to combat bias. When expressing a strong position, this executive suggested, leaders might say, “I know I’ve said this before, but I’m going to say it again. It can be risky for women to speak assertively in many environments. I don’t want that to be the case here, so I’m going to lead out by expressing my point of view directly and I hope others will do the same.” Reciting such a statement would send a clear message: be aware that an implicit bias against women likely exists, it has no place in our organization, and I’m committed to eradicating it.
Change the Norm: The norm in most organizations is to focus on the content of what people are saying and to avoid discussing any strong emotions they are showing. The problem with this norm is that, even though people don’t discuss the emotions, they guess at what the emotions mean and assume the worst—that the person is out of control. A healthier norm is to ask about strong emotions whenever you see them. The results of this study suggest that when a person explains his or her forcefulness, it prevents observers from assuming the worst.
Create Times and Places: Create times, places, and circumstances where speaking forcefully is expected—even required. For example, have an agenda item that asks people to speak forcefully—from their hearts—about the issue being discussed. This approach provides a clear external reason for speakers’ passion and thus reduces observers’ tendency to assume they’d lost their tempers.
Invest in Skill Building: Training can be a powerful way to help others learn the skills they need in order to create conversational safety. This benefits both sides in a conversation and allows individuals and teams to discuss tough issues that affect organizational results across the board—from quality to safety to employee engagement and morale. We’ve distilled the high-leverage skills for speaking up and holding others accountable into our award-winning training programs Crucial Conversations and Crucial Accountability, and the New York Times bestselling books of the same titles. These resources have a proven track record of eliminating cultures of silence and leading organizations to results.
Visit www.vitalsmarts.com for more information.
About the Authors
David Maxfield is the Vice President of Research at VitalSmarts, a global training and consulting firm headquartered in Provo, Utah. He is also a New York Times bestselling author, keynote speaker, and leading social scientist for organizational change.
Joseph Grenny is a four-time New York Times bestselling author, keynote speaker, and social scientist for business performance. His work has been translated into twenty-eight languages and has generated results for three hundred of the Fortune 500. He is the cofounder of VitalSmarts, an organization committed to teaching others how to effectively change human behavior.
Chase McMillan is a Master Trainer at VitalSmarts where he trains Crucial Conversations Training and leads large-scale research projects to uncover communication breakdowns that negatively impact organizational results.
Sheryl Sandberg, Lean in: Women, Work, and the Will to Lead, New York: Alfred A. Knopf, 2013.
Sheryl Sandberg and Adam Grant, “Speaking While Female,” The New York Times, January 12, 2015.
Catherine Hill, Christianne Corbett, and Andresse St. Rose, Why So Few? Women in Science, Technology, Engineering, and Mathematics, Washington, D.C.: American Association of University Women, 2010.
Nadine Bienefeld and Gudela Grote, “Silence That May Kill,” Aviation Psychology and Applied Human Factors, 2, no. 1 (2012): 1-10.
Kerm Henriksen and Elizabeth Dayton, “Organizational Silence and Hidden Threats to Patient Safety,” Health Services Research, 41, no. 4 pt. 2 (2006): 1539-1554.
Vanessa O’Connell, “U.S. Suit Alleges Philip Morris Hid Cigarette-Fire Risk,” Wall Street Journal, April 23, 2004.
Scott Sonenshein, “Business Ethics and Internal Social Criticism,” Business Ethics Quarterly, 15, no.3 (2005): 475-498.
Mark Keil, Ghi Paul Im, and Magnus Mähring,“Reporting Bad News on Software Projects: The Effects of Culturally Constituted Views of Face-Saving,” Information Systems Journal, 17, no. 1 (2007): 59-87.
ChongWoo Park, Ghiyoung Im, and Mark Keil, “Overcoming the Mum Effect in IT Project Reporting: Impacts of Fault Responsibility and Time Urgency,” Journal of the Association for Information Systems, 9, no. 7 (2008): 17.
ChongWoo Park, and Mark Keil, “Organizational Silence and Whistle-Blowing on IT Projects: An Integrated Model*,” Decision Sciences, 40, no. 4 (2009): 901-918.
Amy C. Edmondson, Richard M. Bohmer, and Gary P. Pisano, “Disrupted Routines: Team Learning and New Technology Implementation in Hospitals,” Administrative Science Quarterly, 46, no. 4 (2001): 685-716.
Maria Vakola and Dimitris Bouradas, “Antecedents and Consequences of Organizational Silence: An Empirical Investigation,” Employee Relations, 27, no. 5 (2005): 441-458.
Chad T. Brinsﬁeld, Marissa S. Edwards, and Jerald Greenberg, “Voice and Silence in Organizations: Historical Review and Current Conceptualizations,” in Voice and Silence in Organizations, ed. Marissa S. Edwards, and Jerald Greenberg (Bingley, UK: Emerald Group Publishing, 2009) 3-33.
Kerry Patterson, Joseph Grenny, Ron McMillan, and Al Switzler, Crucial Conversations, New York: McGraw-Hill, 2012.
Frances J. Milliken, Elizabeth W. Morrison, and Patricia F. Hewlin, “An Exploratory Study of Employee Silence: Issues that Employees Don’t Communicate Upward and Why,” Journal of Management Studies, 40, no.6 (2003): 1453-1476.
Elizabeth Wolfe Morrison and Frances J. Milliken, “Organizational Silence: A Barrier to Change and Development in a Pluralistic World,” The Academy of Management Review, 25 no. 4 (2000): 706-725.
Daphne Gottlieb Taras, “Breaking the Silence: Differentiating Crises of Agreement,” Public Administration Quarterly, 14, no. 4 (Winter 1991): 401-418.
Karen L. Soeken and Donald R. Soeken, A Survey of Whistle-blowers: Their Stressors and Coping Strategies, Laurel, Maryland: Association of Mental Health Specialties, 1987.
Derald Wing Sue, Microaggressions in Everyday Life: Race, Gender, and Sexual Orientation, Hoboken, New Jersey: John Wiley & Sons, 2010.
Paul Ekman and Wallace V. Friesen, “The Repertoire of Nonverbal Behavior: Categories, Origins, Usage, and Coding,” Semiotica 1, no. 1 (1969): 49-98.
Bob Woodward, “Secret Reports Dispute White House Optimism,” Washington Post, October 1, 2006.
Victoria L. Brescoll, “Who Takes the Floor and Why: Gender, Power, and Volubility in Organizations,” Administrative Science Quarterly, 56, no. 4 (2011): 622-641..
- Susan Choi, Heather M. Gray, and Nalini Ambady, “The Glimpsed World: Unintended Communication and Unintended Perception,” in The New Unconscious, ed. Ran R. Hassin, James S. Uleman, and John A. Bargh (New York: Oxford University Press, 2005) 309–333.
Costrich, N., Feinstein, J., Kidder, L., Marecek, J., & Pascale, L. (1975). When stereotypes hurt: Three studies of penalties for sex-role reversals. Journal of Experimental Social Psychology, 11, 520–530.
Alice H. Eagly and Steven J. Karau, “Role Congruity Theory of Prejudice Toward Female Leaders,” Psychological Review, 109, no. 3 (2002): 573.
Laurie A. Rudman and Kimberly Fairchild, “Reactions to Counterstereotypic Behavior: The Role of Backlash in Cultural Stereotype Maintenance,” Journal Of Personality and Social Psychology, 87, no. 2, (2004): 157.
Victoria L. Brescoll and Eric Luis Uhlmann. (2008). “Can an Angry Woman Get Ahead? Status Conferral, Gender, and Expression of Emotion in The Workplace,” Psychological Science, 19, no. 3 (2008): 268-275.
Joel T. Nadler, “Explicit and Implicit Gender Bias in Workplace Appraisals: How Automatic Prejudice Affects Decision Making,” (Doctoral dissertation, Southern Illinois University Carbondale, 2010)
Appendix – Statistical Analyses
Questions and Scales used in both studies: Survey items were combined into scales to assess perceived Status, Competence, and Attribution.
Status – Averaged the following four questions.
How much status does Sharon deserve in her job? (or Trent in his job?)
How much power does Sharon deserve in her job? (or Trent in his job?)
How much independence does Sharon deserve in her job? (or Trent in his job?)
Would you like to work for Sharon? (or Trent?)
Note: This question was modified depending on whether the actor was presented as their new boss, peer, or subordinate.
The status scale was reliable. Cronbach’s alpha = .95
Competence – Averaged the following five contrast statements.
Ineffective Manager/Effective Manager
Poor Leadership Skills/Good Leadership Skills
The competence scale was reliable. Cronbach’s alpha = .96
Salary – Salary data was collected using a single question.
What salary do you feel Sharon deserves? $50,000 – $170,000 is the range for their position (also asked for Trent)
Attribution – Averaged the following five questions.
Sharon asked the employee to reapply for their jobs because she is a harsh person. (also asked for Trent)
Note: This item was reversed
Sharon asserted herself because of her personality. (also asked for Trent)
Note: This item was reversed
The situation Sharon found herself in with her team members caused her to act the way she did. (also asked for Trent)
The employee’s behavior left Sharon no choice but to penalize them. (also asked for Trent)
How in control was Sharon during the interaction? (also asked for Trent)
The attribution scale was not reliable. Cronbach’s alpha = .39.
Study One Results
Below are the results from our evaluation of the participant surveys for each of the twenty unique participant groups in Study One.
All of our analyses showed a main effect for gender. The female actor was preferred overall to our male actor. This preference may be due in part to the fact that she was rated one point higher on a ten-point scale of attractiveness. Other considerations might include differences in facial expressions, eye contact, and other subtle elements of the performance that we tried to manage.
Actor will become the observer’s boss. (Observers are viewing the Actor from a subordinate’s perspective)
|Neutral||5.4 (1.75)||6.2 (1.60)||5.9 (1.45)||6.5 (1.49)||$87,272 ($28,203)||$105,203 ($30,162)|
|3.3 (2.07)||3.9 (1.85)||3.7 (1.95)||4.3 (1.77)||$78,979 ($30,293)||$83,692 ($29,610)|
|3.3 (1.58)||3.4 (1.88)||3.4 (1.50)||3.8 (1.62)||$77,777 ($29,694)||$74,444 ($27,642)|
|2.4 (0.89)||3.1 (1.59)||2.9 (1.14)||3.5 (1.54)||$61,739 ($28,676)||$73,904 ($31,985)|
Status: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,986) = 69.0, p = .000. There was no forcefulness/gender interaction effect, F(3,986) = .585, p = .625.
Competency: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,986) = 81.5, p = .000. There was no forcefulness/gender interaction effect, F(3,986) = .108, p = .956.
Salary: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,986) = 16.6, p = .000. There was only a marginal forcefulness/gender interaction effect, F(3,986) = 2.29, p = .077.
Actor will become the observer’s peer. (Observers are viewing the Actor from a peer’s perspective)
|Neutral||5.9 (1.53)||6.8 (1.45)||6.3 (1.39)||7.1 (1.31)||$97,456 ($26,275)||$106,516 ($31,241)|
|5.3 (1.83)||5.3 (1.53)||5.9 (1.53)||5.7 (1.29)||$92,432 ($29,288)||$98,048 ($31,001)|
|4.7 (1.48)||5.0 (1.78)||5.2 (1.38)||5.5 (1.49)||$90,000 ($25,819)||$100,755 ($31,675)|
|4.4 (1.52)||4.0 (1.44)||4.9 (1.42)||4.6 (1.15)||$90,909 ($30,846)||$91,428 ($32,054)|
Status: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,1549) = 73.1, p = .000. There was also a forcefulness/gender interaction effect, F(3,1549) = 5.12, p = .002.
Competency: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,1549) = 81.1, p = .000. There was also a forcefulness/gender interaction effect, F(3,1549) = 6.02, p = .000.
Salary: Our 2 (actor’s gender: male or female) X 4 (forcefulness levels: neutral, mild, moderate, or very) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(3,1549) = 5.12, p = .000. However, there was no forcefulness/gender interaction effect for salary, F(3,1549) = .481, p = .695.
Actor will become the observer’s subordinate—a direct report. (Observers are viewing the Actor from a boss’s perspective)
Status: Our 2 (actor’s gender: male or female) X 2 (forcefulness levels: neutral or moderate) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(1,1915) = 591.9, p = .000. We did not find a forcefulness/gender interaction effect, F(1,1915) = 1.61, p = .205.
Competency: Our 2 (actor’s gender: male or female) X 2 (forcefulness levels: neutral or moderate) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(1,1915) = 685.5, p = .000. We did not find a forcefulness/gender interaction effect, F(1,1915) = 1.28, p = .259.
Salary: Our 2 (actor’s gender: male or female) X 2 (forcefulness levels: neutral or moderate) analysis of variance (ANOVA) conducted on the status scores revealed a significant main effect for forcefulness, F(1,1915) = 85.2, p = .000. We also found a forcefulness/gender interaction effect for salary, F(1,1915) = 7.53, p = .006.
Study Two Results
This analysis compares the three frames, averaged across degrees of emotion, the reporting relationship, and gender. Below are the results of the post-hoc t-tests.
|3.5 (1.60)||3.5 (1.60)||3.2 (1.42)|
|3.8 (1.87)||3.8 (1.87)||3.6 (1.68)|
|3.7 (1.80)||3.7 (1.80)||3.6 (1.65)|
|4.0 (1.99)||4.0 (1.99)|
(standard deviations are provided in parentheses)
Behavior Frame: The Behavior Frame created significant improvements over no frame for perceived status, t(4880) = -2.49 p = .013, and for perceived competency t(4880) = -3.84 p = 000. However, it did not create significant improvements over no frame for salary t(4880) = -.967 p = .333.
Value Frame: The Value Frame created significant improvements over no frame in perceived status, t(3110) = -5.19 p = .000, perceived competency t(3110) = -6.10 p = 000 and in salary t(3110) = -2.77 p = .006. It also created significant improvements over the Behavior Frame in perceived status, t(5498) = -3.94 p = .000, perceived competency t(5498) = -3.62 p = 000 and in salary t(5498) = -2.52 p = .012.
Inoculation Frame: The Inoculation Frame created significant improvements over no frame in perceived status, t(2769) = -14.01 p = .000, perceived competency t(2769) = -15.83 p = 000 and in salary t(2769) = -10.78 p = .000. It also created significant improvements over the Value Frame in perceived status, t(3387) = -9.97 p = .000, perceived competency t(3387) = -10.79 p = 000 and in salary t(3387) = -9.00 p = .012.