Aversive Sexism & Expectancy Violation in the Evaluation of Unethical
Behavior:
Why Bad Behavior Makes Women Look Worse
Abstract
Introduction
In times where trust in the corporate world is at an all-time low (World Economic Forum, 2010), unethical employee behavior has become of growing concern. In recent years, attention has focused on the role of leadership in influencing ethical conduct (Treviño & Brown, 2004; Treviño et al., 2000; 2003; Brown et al., 2005). Managers who express ‘ethical leadership’ can shape the ethical climate in a favorable manner, especially when they are able to utilize their moral judgment capacity (Schminke et al., 2005). An implication of this finding in terms of preventing future corporate scandals is that companies will have to put more effort in shaping a business climate where employees with high moral standards are more able to climb the corporate ladder. This challenge should not be taken lightly, as business students have been found to be among those with the worst attitude toward cheating, and are most likely to continue their unethical behavior in their professional careers (Nonis & Owens Swift, 2001; Wajda-Jonson et al., 2001). Moreover, the threat of low moral standards seems to be the highest on those places where it does most damage; as the tendency to develop unethical behavior seems to grow when individuals obtain more power (Shleifer & Vishny 1986; Lammers et al. 2010). Therefore, it is important to know how people in the
business environment respond to signs of low moral standards of employees in terms of giving them career opportunities.
inclusion of more women at the top of the corporate world may function as a catalyst in the battle against costly scandals. However, as we will argue, general higher moral standards may not necessarily give women an advantage over men. On the basis of the theories of expectancy violation and aversive sexism, it is likely that the evaluation of (un)ethical behavior is influenced by the presence of implicit and explicit gender beliefs. In order to test our hypotheses, an experiment among 186 business students was conducted. Results are presented and conclusions and implications discussed.
Aversive Sexism
From a socio-cultural viewpoint, most people have experienced lifelong exposure to persistent gender hierarchies, which puts men in the role of the worker and women in charge of family life (Glick & Fiske, 1999; Ridgeway; 2001). A nasty product of this exposure is the common (implicit) belief that women are less competent (e.g., intelligent, ambitious, and assertive) than men (Cejka & Eagly, 1999; Glick et al., 1995; Heilman & Kram, 1983). However, attitudes towards women in the role of employee have certainly improved in the past two decades. An example of this development is that, in general, people increasingly support the principle that men and women should have equal pay for equal work (Bond, 2002). This growing sense of gender equality has led companies to implement work-life policies that make it possible for women to work, without having to neglect family life (Kirby, 2006). Despite these developments, we must ask ourselves why women at the top are still scarce.
Behind all good intentions and the motivation to treat people fairly, research on
aversive racism has shown that there is still an ever looming danger of implicit prejudice (cf.
influences (Devine, 1989; Gaertner & Dovidio, 2005; Greenwald et al., 1998; Greenwald et al., 2009). This tension between egalitarian goals and implicit prejudices can be traced back to the findings that implicit measures of stereotyping often show rather low correlations with explicit measures (Blair & Lenton, 2001; Dovidio et al., 2001), but are very reliable constructs when it comes to predicting behavior (Asendorpf et al., 2002; Dovidio et al., 1997; Schmukle et al., 2002; Gawronski et al., 2003). Explicitly, people will rationalize biased decisions in such a way that it does not seem discriminating. That is, implicit prejudice causes similar behavior and accomplishments to be perceived and evaluated differently. In the end, these different perceptions of the same behavior can lead to hiring discrimination (Rudman & Glick, 1999; 2001). For example, Dovidio & Gaertner (1981) found that Whites argue against affirmative action on the basis of procedural unfairness in order to decrease the likelihood that they will be subordinated to Blacks.
replicate this finding. The second aim is to test by which underlying mechanisms the effect can be explained.
Following the arguments given above, we can expect that, when behaving unethically men are discriminated against less than women. More precisely:
Hypothesis 1: Employees who behave unethically will receive less career support than employees who do not. This is less so when the employee is a man rather than a woman.
Expectancy Violation
Above we argued that the consequences of behaving unethically are less serious for men than for women and that this may be due to aversive sexism. However, aversive sexism may not be the only explanation. When focusing more strongly on the female consequences, another explanation for the harsher response women may receive when behaving unethically is that they violate people’s expectations more than unethically behaving men. As we mentioned above, women generally have higher moral standards than men do (Borkowski & Urgas, 1998; Franke et al., 1997). Research on social and individual psychological variables affecting ethical decision making suggests that gender plays an important role in the moral reasoning of employees (Robin et al., 1997; Roxas & Stoneback, 2004). Several studies have suggested that men are more likely to engage in unethical behavior, because they possess more agentic traits than women do, such as a strong sense of independence and competitiveness, (Grimshaw, 1999; Hunt, 1997; Weeks et al., 1999). In contrast, the stereotypical woman is communal (i.e. kind, thoughtful, and sensitive to others).
expectancy violation, people evaluate others more extremely when their behaviors violate stereotyped expectations (Burgoon & Hale, 1988). For example, the results of Tainor & Deaux (1973) indicated that women who showed courage in an emergency situation were evaluated more positively than men. The author’s explanation for this result was that courage is generally seen as a masculine trait, and it would therefore be even more admirable coming from a woman. Vice versa, unexpected negative behavior leads to more extreme negative evaluations. Several studies have shown how white participants who spoke in broken English were evaluated more negatively than black applicants who spoke in broken English, as they violated the stereotype of a white man speaking his mother language correctly (Jackson et al., 1993; Jussim et al., 1996).
The same process may take place when people encounter a woman behaving unethically. As this is a clear violation of the communal female stereotype; unethical behavior of a woman can be seen as an example of unexpected negative behavior. Therefore, also according to expectancy violation theory, we can expect women who behave unethically to be evaluated more negatively than men who behave in a similar manner. Indeed, research reports that a violation of communal female expectances has negative consequences. For example, although agentic behavior makes women look more competent, agentic women suffer from a so called backlash effect of social repercussions, because their behavior is viewed upon as insufficiently nice (Eagly et al., 1992; Rudman, 1998).
Underlying Stereotypes
As argued above, both the theory of aversive sexism and expectancy violation lead to the same hypothesis; namely that the consequences of unethical behavior are more negative for women than for men. An important goal of this research is to test the predictive power of each of these theories. Even though both aversive sexism and expectancy violation lead to the same prediction, the stereotypes that can be seen as the underlying mechanisms for our hypothesis differ for these theories. The stereotype responsible for aversive sexism is the implicit belief that women are less competent, whereas the prediction of expectancy violation is based on the communal female stereotype. The amount of support for either one of the theories lies in the predictable power of their matching stereotypes. If aversive sexism is the underlying mechanism which can explain the relationships of hypothesis 1, than we can expect that these effects will be stronger for people with strong implicit gender beliefs of women being less competent than men. However, if expectancy violation is the underlying mechanism, than we can expect that the effects of hypothesis 1 will be stronger for people with strong gender beliefs about women being more communal than men.
Hypotheses 2A: the relationships of hypothesis 1 are stronger for people with strong implicit beliefs of women being less competent than men.
Methods
Participants &Design
One hundred and eighty six business students (135 male, 51 female; M age = 20.12) participated in the experiment, either in exchange for course credit or 4 EUR. In total, all tasks related to our experiment took approximately 35 minutes to complete. All participants completed the experiment; however, 18 participants forgot to fill in either the first or the second page of the explicit stereotype survey, probably due to double sided prints. This resulted in data consisting of 180 participants for testing the expectancy violation hypothesis (130 male, 45 female) and 175 participants for testing the prescriptive gender beliefs hypothesis (130 male, 50 female).
The study had a 2 (gender of colleague: male vs. female) x 2 (behavior of colleague: ethical vs. unethical) between participants design with communal and competency -related stereotypes as additional continuous independent variables. Participants were distributed (almost) equally amongst the four conditions (N = 47; 44; 46; 50).
Procedure
To manipulate gender, this scenario starred either a male (i.e, Marc) or a female (i.e., Suzan) colleague. The scenario represented a situation where Marc or Suzan went on a business trip to China and had dinner with three business partners in a restaurant. The total costs of this dinner were 100 EUR. Afterwards, the bill was split between the four so that Marc or Suzan paid 25 EUR.
In the ethical behavior condition, the following line concluded the scenario: Back in
Holland, Marc/Suzan claims one-fourth of the expenses presented on the dinner bill (25 EUR). In the unethical manipulation, the scenario was concluded with: Back in Holland, Marc/Suzan claims the full expenses presented on the dinner bill (100 EUR).
Finally, various questions were asked on a 7-point Likert scale (1 = very much
disagree; 7 = very much agree). Then, participants were thanked and paid.
Measures
Career support. The dependent variable in our study is Career Support. Career support
was assessed with the use of eight items on a 7-point Likert scale. Participants were asked: ‘to what extent would you; 1) have no obligations to hire Marc/Suzan, 2) make sure Marc/Suzan is in your project team, 3) help Marc/Suzan when he/she asks you, 4) be willing to cooperate with Marc/Suzan, 5) give Marc/Suzan a positive referral, 6) promote Marc/Suzan when he/she functions well, 7) trust Marc/Suzan with leadership responsibilities, 8) inform Marc/Suzan when there is a higher job opening’. These items formed a reliable scale (α = .94).
Gender of Colleague manipulation. Participants who filled in the scenario survey with
Behavioral manipulation. Participants who filled in the scenario survey in which
Marc/Suzan behaved ethically were coded as -1, and participants who filled in the scenario survey in which Marc/Suzan behaved unethically were coded as 1.
Competency Gender Beliefs. The Implicit Association Test (IAT), a computer-administered response time task, was used to measure implicit gender beliefs. The IAT is a widely validated and increasingly popular measure of implicit attitudes (Greenwald et al., 2003; Hofmannet al., 2005; Rudman et al., 2001). In order to assess measures of implicit gender beliefs regarding competency, stimuli were adopted that have already been used and validated by a previous study (Logel et al., 2009)1. The competency IAT used 10 common Dutch male names (e.g., Michiel, Wouter, Niels, Joris), and 10 common Dutch female names (e.g., Margriet, Emma, Femke, Maaike), 10 words that reflected ‘competent’ (e.g., capable, efficient, expert, intelligent, rational), and 10 words that reflected incompetent (e.g., helpless, illogical, inept, irrational, slow).
The IAT procedure in this study followed the dominant procedure in the field (Greenwald et al., 1998). Instructions were given on the computer screen. Participants were asked to distinguish male and female names and words reflecting (in)competency by pressing a key on the far left or right side of the computer keyboard. Participants were instructed to respond as quickly and as accurately as possible. The categories for the classification were shown on the left and right sides in the bottom of the screen. Each stimulus was shown in the middle of the screen until a response key was pressed, followed by a 500ms blank screen. After the names (n = 10) and words (n= 20) were practiced separately, participants categorized a stereotype congruent or incongruent combination of names and words. A congruent combination was a male name and a competency word to which participants responded with the left key and a combination being a female name and an incompetency
1
word to which participants responded with the right key. In the incongruent block, the competency and incompetency words switched sides, while the male and female names remained left and right. The actual testing Blocks (n= 40 trials) are preceded by identical practice blocks (n = 20 trials) to marginalize the influence of the order of Blocks. The order of the congruent and incongruent stereotype Blocks was randomized across participants. Post analyses showed that the order of the Blocks did not affect the results.
The IAT effect in this study was computed by calculating the difference between mean response latencies in the stereotype congruent and stereotype incongruent testing Blocks, using the scoring algorithm recommended by Greenwald et al, (2003). This resulted in a D score, which has a theoretical minimum of -2 and maximum of 2. Positive difference scores reflect an automatic association between men and competency, and women and incompetent (i.e., congruent stereotypes), whereas negative scores reflects a stereotype incongruent implicit association.
Response latencies from error trials were not included in the calculation of D score. Furthermore, to correct for attention loss and anticipatory guesses, latencies over 3.000 ms and under 300 ms were recoded as 3.000 and 300 ms. Participants with more than 10% trials that were erroneous or beyond the temporal boundaries were excluded. This resulted in a loss of 14 participants (5 female, 9 male) for competency D scores.
Communal-Agentic Gender Beliefs. Participants completed an explicit self report
measure of communal-agentic gender beliefs. Participants had to indicate to what extent they thought certain traits were generally more present in men or women (Eagly & Karau, 2002). These 7-point scales were anchored by the endpoints of 1 (more true of women) and 7 (more
true of men). The gender-communal-agentic stereotype measure assessed six agentic traits
judgments of communal concepts were subtracted from mean judgments of agentic concepts. This yielded scores from -6 to 6. Thus, high scores indicated more traditional gender beliefs.
Manipulation Check. After the experiment, participants were asked if Marc/Suzan claimed more, less or exactly the amount spent in the scenario. Ten participants (5.3%) answered this question not in correspondence with the condition they were presented in the scenario. Excluding these participants from the analyses did not affect the outcome, so we decided to keep them in.
Results
Table 1 presents the means for both sexes on implicit competency gender beliefs and communal-agentic gender beliefs. Even though the general implicit competency gender belief scores of men and women were not significant individually, men had generally stronger implicit beliefs that women were less competent than women. Furthermore, both male and female participants reported non traditional gender beliefs regarding communality/agency; meaning that they generally believed that women had more agentic traits than men. In the analyses, we tested whether the gender of participants influenced our hypothesis, but no further significant gender effects were found.
In Table 2, the intercorrelations of all variables are presented. The ethical behaviour manipulation was negatively correlated with career support, meaning that participants in the unethical condition evaluated the character in the scenario more negatively in terms career support. No other significant effects were found.
gender beliefs (h2a), and communal-agentic gender beliefs (h2b). We conducted a hierarchical regression analysis, in which the standardized implicit competency gender beliefs variable and the Gender of Colleague and Ethical Behavior manipulations were the independent variables; and career support was the dependent variable. We entered all independent variables in step 1 and in step 2 the interaction variables were added. The results are presented in Table 3. As expected, we found significant negative effects for the ethical behaviour manipulation (b = -0.60, p <.01), indicating that participants gave less career support to the colleague in the unethical condition than in the ethical condition. The Gender of Colleague manipulation and the implicit competency gender beliefs variable showed no significant effects in both step 1 and 2. None of the interactions showed any significant effects. Therefore, we have to reject hypotheses 1 & 2a.
Conclusion & Discussion
The main aim of this study was to explore how people in the business environment respond to signs of low moral standards of an employee, and how these responses affect the career opportunities of the employee. More specifically, we investigated how the gender of an employee affects the way people respond to his or her (un)ethical behavior. To this end, the two theoretical perspectives (aversive sexism and expectancy violation) that would underlie this situation were tested.
We hypothesized that employees who behave unethically will receive less career support than employees who do not, but that this is less the case when the employee is a man. Also, we hypothesized that this relationship would be moderated by communal-agentic and implicit competency gender beliefs. The results of this study first show that unethical behaviour decreased career support behaviours. This is in itself a reassuring result. Apparently, when employees show unethical behaviour, they are given less career opportunities. Therefore, we can expect a decrease of unethical behaviour in the top levels of an organization as long as it gets noticed in the lower levels. However, one of the problems with unethical behaviour is that it often does not gets noticed. As unethically behaving employees will attempt to escape the consequences, they try to make sure their bad behaviour remains below the surface. Thus, managers will have to stay alert in order to spot the rotten apples in the organization. Furthermore, companies may be wise to invest in enhancing the transparency of employee behaviour within their organization.
how men and women were evaluated. A possible explanation for these results is that it is simply not true that people treat men more lenient than women when they behave in unethical ways. This would indicate that the preliminary results of Mulder & Rink (2010) do not reflect an existing phenomenon and can be interpreted as coincidental. If so, than both aversive sexism and expectancy violation have no big role in the evaluation of unethical behaviour. The underlying mechanism of both theories relied on the general existence of traditional gender beliefs regarding competency and communality. In contrast, the business students who participated in the experiment generally did not show a significant implicit competency gender belief. This result indicates that, in general, aversive sexism did not manifest itself, as the supposed tension between egalitarian goals and traditional gender beliefs was not apparent for most participants. Also, both male and female participants showed non-traditional communal-agentic gender beliefs; meaning that they generally believed that women had more agentic traits than men. Consequently, the communal female expectations were not present for most participants and could thus not be violated. It is important to note that these findings may only be representative for business students in the Netherlands and may be very different for the average manager in charge of Human Resources. Firstly, traditional gender roles are not as apparent as they were a couple of decades ago (Bond, 2002; Kirby, 2006). As such, we can expect students to have internalized far more egalitarian values than managers from another generation. Secondly, Dutch egalitarian culture may have played an important role. In a study among American business students that used the same IAT to measure implicit competency gender beliefs, both male and female participants showed significant traditional implicit competency gender beliefs (Rudman & Glick, 2001).
to disconfirm gender stereotypes (Wiley & Eskilson, 1985). For example, agentic behaviour, which is traditionally masculine, makes women look more competent (Glick & Fischke, 1999; Heilman, 1983). As unethical behaviour is a masculine trait (Borkowski & Urgas, 1998; Franke et al., 1997), it may have disconfirmed people’s association between the woman behaving unethically and the female stereotype of incompetency and communality. If so, both types of gender beliefs did not function as an underlying mechanism and people reacted in a straight forward manner towards unethical behaviour, regardless of the person’s gender.
Alternatively, the lack of support for our hypotheses may be due to two important limitations of the present study. Firstly, the IAT preceded the scenario study, and because of this, participants could have become aware that they were participating in a study that investigated gender stereotyping. Moreover, having difficulties with the incongruent blocks may have confronted participants with their implicit gender beliefs. Consequently, in an attempt to compensate their implicit beliefs, especially participants in the female condition may have answered in a socially desirable manner (cf. Moss-Racusin et al. 2010). In order to avoid this problem, it would be better to split the IAT tasks and the scenario study in future experiments.
manipulation check with regard to the gender manipulation, which could have shown to what extent the gender of the employee was salient for participants. Future research could focus more on the gender condition by extending the profile of the character. When doing this, the femininity or masculinity of the lead character should be primed, while direct or indirect references to the competence of the character should be avoided. For example, the male scenario could include references of the lead character being interested in masculine sports and cars, while the female scenario could include references of the lead character being interested in fashion and dancing. Another possible method for priming masculine and feminine associations uses schematic drawings of men and women (Fazio et al., 1995).
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Table 1
Percentage Scores for Men and Women Separately on Implicit Competency Gender Beliefs and Communal-Agentic Gender Beliefs (N=186)
Variables Mean (SD) Differences (t-test)
Table 2
Correlations between All Variables by Gender
1 2 3 4 5
1. Gender of Colleague X
2. Ethical Behavior -.02 X
3. Implicit Competency Gender
Table 3
Gender, Ethical Behavior and Implicit Competency Gender Beliefs predicting Career Support
Career Support
Step 1 Step 2
b SE b SE
Gender of Colleague Manipulation .03 .06 .02 .06
Ethical Behavior Manipulation -.60** .06 -.60** .06
Implicit Competency Gender Beliefs -.06 .06 -.07 .06
Gender of Colleague x Ethical Behavior -.02 .06
Gender of Colleague x Implicit Competency Gender Beliefs
-.01 .06
Ethical Behavior x Implicit Competency Gender Beliefs
.11 .06
Gender of Colleague x Ethical Behavior x Implicit Competency Gender Beliefs
-.01 .06
Adjusted R2 .359 .359
Table 4
Gender, Ethical Behavior and Communal-Agentic Gender Beliefs predicting Career Support
Career Support
Step 1 Step 2
b SE b SE
Gender of Colleague Manipulation .04 .06 .04 .06
Ethical Behavior Manipulation -.58** .06 -.57** .06
Communal-Agentic Gender Beliefs -.07 .06 -.09 .07
Gender of Colleague x Ethical Behavior -.04 .06
Gender of Colleague x Communal-Agentic Gender Beliefs
0 .07
Ethical Behavior x Communal-Agentic Gender Beliefs
.07 .07
Gender of Colleague x Ethical Behavior x Communal-Agentic Gender Beliefs
.06 .07
Adjusted R2 .340 .334
