SEXUAL HARASSMENT, WORKPLACE AUTHORITY, AND THE PARADOX OF POWER

Abstract

Power is at the core of feminist theories of sexual harassment, though it has rarely been measured directly in terms of workplace authority. While popular characterizations portray male supervisors harassing female subordinates, power-threat theories suggest that women in authority may be more frequent targets. This article analyzes longitudinal survey data and qualitative interviews from the Youth Development Study (YDS) to test this idea and to delineate why and how supervisory authority, gender non-conformity, and workplace sex ratios affect harassment. Relative to non-supervisors, female supervisors are more likely to report harassing behaviors and to define their experiences as sexual harassment. Sexual harassment can serve as an “equalizer” against women in power, motivated more by control and domination than by sexual desire. The interviews point to social isolation as a mechanism linking harassment to gender non-conformity and women’s authority, particularly in male-dominated work settings.

Though the term sexual harassment was not coined until the 1970s (Farley 1978), formal organizational responses have since diffused rapidly (Dobbin and Kelly 2007; Schultz 2003). Today, sexual harassment workshops, policies, and grievance procedures are standard features of the human resources landscape, while a robust scholarly literature ties harassment to gender inequalities (Martin 2003) and other forms of workplace discrimination (Lopez, Hodson, and Roscigno 2009). Power, at work and in the broader society, pervades each of these literatures and their accounts of harassment (Berdahl 2007a; Rospenda, Richman, and Nawyn 1998; Welsh 1999). Yet, after three decades of scholarship, basic questions about whether and how workplace power affects harassment remain unanswered. Much of the evidence relies on inconsistent measures, wide-ranging time frames, and narrowly focused samples. With rare exceptions (e.g., Freels, Richman, and Rospenda 2005), this research uses cross-sectional data better suited for identifying correlates than for isolating causes. In the absence of rigorous qualitative and longitudinal designs, the dynamics of gender, power, and harassment remain poorly understood.

This paper uses quantitative and qualitative data from the Youth Development Study (YDS) to consider three hypotheses from an integrated feminist model of sexual harassment, testing whether supervisory authority, gender identity, and industry sex composition are linked to experiences of harassment. Using strong statistical controls for individual differences, our quantitative models predict whether respondents report any harassing behaviors, the number of harassing behaviors they report, and whether they subjectively interpret their experiences as harassment. After establishing the basic empirical relations using survey data, we analyze qualitative interviews with YDS respondents to delineate and explain the processes underlying these relationships. We then situate both sets of results within theories of gender and power, and extant research on sexual harassment.

GENDER, SEXUAL HARASSMENT, AND WORKPLACE POWER

Sexual harassment is classified as a form of sex discrimination under Title VII of the Civil Rights Act of 1964. The U.S. Equal Employment Opportunity Commission (EEOC) defines it as “unwelcome sexual advances, requests for sexual favors, and other verbal or physical conduct of a sexual nature” that interferes with one’s employment or work performance, or creates a “hostile or offensive work environment” (U.S. EEOC 2011). Due, in part, to varying definitions and indicators, prevalence estimates vary dramatically (Welsh 1999), leading many researchers to adopt a strategy of triangulation that considers multiple forms or measures (e.g., Houston and Hwang 1996; Uggen and Blackstone 2004).

Feminist scholarship situates sexual harassment within broader patterns of discrimination, power, and privilege, linking harassment to sex-based inequality (MacKinnon 1979). Beth Quinn’s (2002) research on “girl watching,” for example, ties patriarchal gender relations to everyday workplace interactions. Quinn argues that other men, rather than women, are often the intended audience of sexist gestures or comments. Although men often view girl watching as light-hearted and playful, and seem surprised when women take offense, such activities demonstrate men’s power to sexually evaluate women.¹ Similarly, Martin (2001) finds that men “mobilize masculinities” in ways that often exclude and cause harm to women as a group, even when this is not intended.

Raewyn Connell’s theory of hegemonic masculinity (1987), which argues that society privileges a single normative ideal of male behavior, provides a broad sociological framework for understanding harassment, gender, and power. While men may be vulnerable to harassment if they are perceived as feminine (DeSouza and Solberg 2004; Waldo, Berdahl, and Fitzgerald 1998), women may be targeted if they challenge their subordinate position in the gender system. Sexual harassment may thus act as a tool to police appropriate ways of “doing gender” in the workplace, and to penalize gender non-conformity (West and Zimmerman 1987).

Research on “contrapower” harassment suggests that gender, race, and class positions imbue harassers with informal power, even when targets possess greater organizational authority than their harassers (Rospenda et al. 1998). Women holding authority positions thus offer an intriguing paradox for theory and research on sexual harassment, with scholars advancing two distinctive positions. The first, the “vulnerable-victim” hypothesis, suggests that more vulnerable workers—including women, racial minorities, and those with the most precarious positions and least workplace authority—are subject to greater harassment. The second, the “power-threat” model, suggests that women who threaten men’s dominance are more frequent targets. Though the matter is far from settled, there has been greater support for the paradoxical “power-threat” model, in which women in authority positions are most likely to face harassment (Chamberlain et al. 2008) and discrimination (Stainback, Ratliff, and Roscigno 2011).

Women supervisors, who hold authority over male co-workers, directly challenge the presumptive superiority of men. Women continue to be underrepresented in positions of authority or relegated to the lower rungs of management (Elliott and Smith 2004; Gorman 2005; Kalev 2009; Reskin 2003; Reskin and McBrier 2000). When women are able to crack the glass ceiling and attain leadership positions, stereotypical gender beliefs about their “natural” abilities continue to shape perceptions of their job performance (Davidson and Cooper 1992; Eagly and Carli 2007). Moreover, while men in traditionally female occupations reap the rewards of a “glass escalator” to leadership positions (Hultin 2003; Williams 1992), women supervisors are often isolated and seen as undeserving of their positions (Ridgeway and Correll 2004; Ridgeway and Smith-Lovin 1999). In fact, women are unlikely to be promoted to management unless a sizeable proportion of women are already in place, highlighting the difficulty of gaining initial entry to such positions (Cohen, Broschak, and Haveman 1998). Taken together, these processes point to women supervisors as potential targets for harassment.

The idea of “masculine overcompensation”—where men react to threats to their manhood by enacting an extreme form of masculinity (Willer 2005)—also helps explain why men may harass women in power. Maass and colleagues (2003), for example, find that male participants in a computer image-sharing task sent more pornographic and offensive images to females identifying as feminists than to females adhering to more traditional gender roles. Along similar lines, Das (2009) concludes that women who are “too assertive” threaten the gender hierarchy and are denigrated through harassment. Correspondingly, De Coster and colleagues (1999) find that females with greater tenure, independent of age, were more likely to view sexual harassment as a problem for them at work, concluding that the practice is used instrumentally against powerful females who encroach on male territory. Each of these findings suggests that women supervisors may be more likely to experience sexual harassment than other working women.

It is also possible that supervisors report greater rates of harassment simply because they are more aware of the phenomenon. Supervisors’ advanced education and training likely increase their overall legal consciousness and understanding of sexual harassment. As a result, supervisors, who are often responsible for fostering a professional work environment free from harassment and discrimination, may be more likely to recall sexualized workplace interactions and to label such experiences as harassment.

Supervisory authority and expressions of gender are also tied to other forms of sex-based discrimination (Stainback et al. 2011). Berdahl reconceptualizes sexual harassment as sex-based harassment, defined as “behavior that derogates, demeans, or humiliates an individual” based on sex (2007a:644). Sex-based harassment is driven by a motivation to protect sex-based social standing. As a result, targets are most likely to be females who threaten males’ status. For example, Berdahl (2007b) finds that females who perform gender in stereotypically masculine ways (assertive, dominant, and independent) were more likely to experience harassment. She argues that harassers reinforce masculine dominance by relegating women to the “low status of being a means to a man’s sexual ends” (2007a:649). And when men are targeted by other men, harassers “prove” their own manhood by undermining their targets’ masculinity.

Apart from supervisory authority and expressions of gender, the demography of a workplace also influences harassment experiences. While sexual harassment occurs across a diverse range of job settings (e.g., Collinson and Collinson 1996; Dellinger and Williams 2002; Giuffre and Williams 1994), a large literature debates the importance of numerical sex ratios (Welsh 1999). Nevertheless, the weight of the evidence suggests that harassment, of both men and women, most often occurs in male-dominated work settings (Fitzgerald et al. 1997; Mansfield et al. 1991; Rospenda et al. 1998; Uggen and Blackstone 2004). Based on the dynamics of sex, gender, and power in the workplace, we form three primary hypotheses:

Hypothesis 1: Females holding workplace authority positions (i.e., those who supervise others) are more likely to experience sexual harassment than females who do not hold such positions.

Hypothesis 2: Gender non-conformity (i.e., more feminine behavior for males and less feminine behavior for females) is associated with an increased risk of sexual harassment.

Hypothesis 3: Sexual harassment will be greater in industries and occupations characterized by a higher proportion of male workers.

After testing these hypotheses in our quantitative analyses, we turn to qualitative interview data to understand the underlying process behind these patterns. By probing the experiences of our survey participants, we are better able to explain why and how gender, sex, and power shape harassment experiences and workplace interactions more broadly.

DATA, MEASURES, AND METHODOLOGY

We analyze longitudinal data from the Youth Development Study² (Mortimer 2003). The study began in 1988, when participants were ninth graders in St. Paul, Minnesota public schools. The sample was comprised of 1,010 youth, who have since been surveyed regularly. For this paper, we analyze the 2003 and 2004 surveys, when participants were approximately 29 and 30 years old. Survey retention was 73 percent in 2004, and our analytic sample (N=522) is comprised of all working participants who responded to sexual harassment items in both waves.

Quantitative studies are sometimes criticized for assuming that all sexuality in the workplace is harmful to women, or that women who do not label their experiences as harassment are suffering from false consciousness (Williams, Giuffre, and Dellinger 1999). Because some sexual behavior is experienced as tolerable or pleasurable by workers (Dellinger and Williams 2002; Giuffre and Williams 1994; Lerum 2004; Schultz 2003; Williams 1997), YDS respondents were asked about sexual behaviors that they considered offensive or made them uncomfortable. While this wording admits a range of conduct that may fall short of legal definitions of harassment, it clearly eliminates sexualized interactions that respondents would consider pleasurable. Finally, to avoid potential biases associated with behavioral indicators, we also ask respondents directly whether they would classify their own experiences as sexual harassment.

Relative to surveys, however, qualitative research is often “better suited to discovering how the meaning of sexual behaviors varies in different organizational contexts” (Dellinger and Williams 2002:244). Dellinger and Williams (2002), for example, powerfully contrast the “locker room” culture of a male pornographic magazine with the “dorm room” atmosphere of a feminist magazine, showing how organizational culture shapes workers’ definitions of harassment. While our survey results reveal patterns of association, they cannot speak directly to the more subtle and specific mechanisms linking group membership to opportunities and outcomes (Gross 2009:375; Reskin 2003:8). As such, we also conducted interviews with 33 YDS respondents (14 men and 19 women) to more closely examine the processes linking power and gender and to better contextualize harassment experiences.³ Of the interviewees, all but 7 identified as white, most self-identified as “straight,” and they reported a range of supervisory and non-supervisory jobs. We asked interview participants a series of open-ended questions about their work histories and interactions, inviting them to share what they felt was most important based on our interest in harassment, workplace problems, and workplace sexuality. All interview participants’ names are pseudonyms.

Quantitative Measures: Sexual Harassment

In 2003 and 2004, YDS participants reported whether they had experienced eight harassing behaviors in the past year and whether they considered their experiences to be sexual harassment. Behavioral indicators were modeled after the Inventory of Sexual Harassment (Gruber 1992) and the Sexual Experiences Questionnaire (Fitzgerald et al. 1988). Taking advantage of the longitudinal nature of the survey, we estimate models that statistically control for respondents’ harassment experiences in the prior year. The measures capture very similar experiences across the two waves, though the wording differs slightly between 2003 and 2004.⁴

We adopt a strategy of triangulation to capture both behavioral and subjective dimensions of sexual harassment. First, we consider whether respondents reported any behavioral indicator (36 percent did in 2004). Second, we predict a count of the four “core” indicators asked in both 2003 and 2004 (offensive material, staring or leering, attempts to discuss sex, and inappropriate touching). Third, we assess subjective harassment using respondents’ self-reports, rather than the behavioral indicators. Gender plays an important part in the process of subjectively defining behaviors as sexual harassment, with men less likely than women to apply the term to their experiences (Marshall 2005; Uggen and Blackstone 2004). We therefore model this outcome for females only. As shown in Table 1, 11 percent of females reported subjective harassment.

Table 1.

Descriptive Statistics of Youth Development Study Analytic Sample

Variables	Description	Coding	Mean	SD
Sexual Harassment
Any Harassment 2004	experienced at least one behavioral indicator 2004	0=No, 1=Yes	.356
Any Harassment 2003	experienced at least one behavioral indicator 2003	0=No, 1=Yes	.368
Total Harassment 2004	total number of behavioral indicators 2004	Min: 0, Max: 4	.481	.836
Total Harassment 2003	total number of behavioral indicators 2003	Min: 0, Max: 4	.450	.708
Subjective Harassment 2004	defined any behavior as sexual harassment 2004 (females only)	0=No, 1=Yes	.111
Subjective Harassment 2003	Defined any behavior as sexual harassment 2003 (females only)	0=No, 1=Yes	.117
Workplace Power
Supervisor	supervise others (full sample)	0=No, 1=Yes	.318
Supervisor*Male	supervise others (males only)	0=No, 1=Yes	.366
Sex and Gender
Male	self-reported sex	0=Female, 1=Male	.429
Femininity	self-reported femininity (full sample)	0=Low, 1=High	.594
Femininity*Male	self-reported femininity (males only)	0=Low, 1=High	.130
Individual Characteristics
White	self-reported race	0=Non-white, 1=White	.826
Born in the U.S.	non-immigrant	0=Immigrant, 1=Non-immigrant	.939
Partner	married or cohabiting	0=Single, 1=Married or cohabiting	.713
Children	at least one child	0=No, 1=Yes	.600
Years Education	years of education completed	Min: 8, Max: 20	14.676	1.927
Household Income	total household income in thousands of U.S. dollars	Min: 0, Max: 423	$61.772	$36.781
Work Characteristics
Work Hours	weekly work hours in primary job	Min: 4, Max: 70	38.603	8.872
Log Employees	Log number of employees at workplace (at your location)	Min: 2.5, Max: 9.2	4.269	1.824
Job Satisfaction	satisfaction with job as a whole	1=extremely dissatisfied, 6=extremely satisfied	4.285	1.126
Job Security	security of primary job	1=not at all, 4=very	3.002	.855
Technical/Craft	technicians, craft workers, operatives, and laborers/helpers	0=No, 1=Yes	.188
Professional	professional job category	0=No, 1=Yes	.276
Official/Managerial	official/managerial job category	0=No, 1=Yes	.142
Service	sales workers, administrative support workers, and service	0=No, 1=Yes	.395
Proportion Female in Industry	proportion of females in primary job industry	Min: .091, Max: .955	.498	.216

Note: N=522 for all variables unless sample is limited to males (N=224) or females (N=298) only.

Subjective appraisals involve “naming” an experience as sexual harassment, or labeling a particular experience as injurious (Felstiner, Abel, and Sarat 1980–81:635). This process is partly a function of legal consciousness – individuals’ awareness, understanding, and response to law and legality (see, e.g., Ewick and Silbey 1998; Blackstone, Uggen, and McLaughlin 2009; Hirsch and Lyons 2010). Authority position and other independent variables are likely tied to both legal consciousness and sexual harassment. If supervisory status is related to subjective harassment but not the behavioral measures, this might indicate greater consciousness of harassment and legal rights among supervisors. If supervisory status affects both indicators, however, this would suggest differences in actual targeting as well as consciousness.

Quantitative Measures: Independent Variables

Workplace Power

We measure workplace power as supervisory authority in 2004. To model sex differences in the influence of organizational power, we created an interaction term between sex and supervisory authority. As shown in Table 1, 37 percent of males and 28 percent of females supervise others (a difference that is significant at p<.05).

Sex and Gender

Sex is measured with a self-reported dichotomous item (male is coded as 1). Clearly, questionnaire items on femininity are subject to gendered social desirability biases, such that some men may be reluctant to report that they are feminine at all. Nevertheless, a direct measure of participants’ perceived femininity provides an important starting point for distinguishing sex and gender in our analyses. To measure gender identity and performance, we use responses to the question, “How feminine would you say you are?” with scores ranging from 1 (“not at all feminine”) to 5 (“extremely feminine”). Responses were recoded into a dichotomous indicator of femininity, with “not at all feminine” and “somewhat feminine” coded as 0 and “about average,” “very feminine,” and “extremely feminine” coded as 1.⁵ Most females (94 percent) identified as “very feminine” or “extremely feminine,” compared to only 13 percent of males.⁶

Race and National Origin

Given the limited racial and ethnic diversity of the YDS, we use simple dichotomous measures of race (83 percent white in our analytic sample) and national origin (94 percent U.S. born). Some studies show that women of color are more likely targets, or experience more virulent forms of harassment (Mansfield et al. 1991; Ortiz and Roscigno 2009; Welsh et al. 2006), while others find few racial differences in harassment (e.g., Das 2009; De Coster et al. 1999). Qualitative studies considering the intersection of multiple roles, however, suggest that women of color are subject to a racialized form of sexual harassment that may be distinct from that experienced by white women (Buchanan and Ormerod 2002; Texeira 2002).

Life Course Characteristics, Education, and Income

With regard to family status, single women tend to be targeted more than married women (De Coster et al. 1999; Ragins and Scandura 1995). De Coster and colleagues (1999) theorize that single women are perceived as challenging traditional family structures, and are viewed as less protected and more sexually available. As shown in Table 1, 71 percent of our respondents were married or cohabiting, and 60 percent had children. We also include indicators of educational attainment (mean = 14.7 years) and self-reported household income. De Coster et al. (1999:29) find that more educated females, who challenge the “economic and status resources traditionally monopolized by males,” are more likely to report harassment (see also, Das 2009).

Work Characteristics

Respondents reported their number of weekly work hours and the number of employees in their workplace. People employed in large establishments are likely to encounter a broader range of individuals at work, and potential harassers may be more inclined to act inappropriately due to the anonymity of large organizations (Chamberlain et al. 2008; De Coster et al. 1999). On the other hand, larger organizations are also most likely to have formal harassment policies in place (Hirsh and Kornrich 2008). Some studies also report a negative correlation between job satisfaction or job security and harassment, although the temporal ordering of these phenomena has not been firmly established (Fitzgerald et al. 1997). Job satisfaction ranges from 1 (“extremely dissatisfied”) to 6 (”extremely satisfied”), with a mean of 4.3 corresponding to a response of “somewhat satisfied.” Job security ranges from 1 (“not at all secure”) to 4 (“very secure”). We measure job satisfaction and job security in 2003, rather than 2004, as experiencing harassment may affect both measures. We also include dummy variables for primary occupation based on the Census 2000 Special EEO Tabulation (U.S. Census Bureau 2006).7 Finally, the proportion of female workers in respondents’ industry is derived from 2004 U.S. Census estimates (U.S. Department of Labor 2009).

Method of Analysis

We first present results from logistic regression models predicting any sexual harassment. Second, we use negative binomial regression to predict the number of harassing behaviors. We apply a count model because this outcome is highly skewed (and a negative binomial rather than a Poisson because of overdispersion in our sample). Next, we use logistic regression to predict subjective harassment, contrasting these results against the preceding behavioral models.

Each equation includes a lagged dependent variable for prior sexual harassment. This approach provides a strong control for stable, person-specific characteristics (such as family origins) that may influence both the independent variables and sexual harassment. Our models take the following form:

$$log[\text{P}({\mathit{Harass}}_{\text{i}2004}=1)/\text{P}({\mathit{Harass}}_{\text{i}2004}=0)]=\alpha +{\beta }_1{\mathit{Supervisor}}_{\text{i}2004}+{\beta }_2{\mathit{Harass}}_{\text{i}2003}+\dots +{\beta }_k{X}_{i2004}+\epsilon$$

where i represents individual respondents, Harass indicates the probability of experiencing harassment in 2004 (and the corresponding lagged item from 2003), Supervisor represents the dichotomous workplace authority measure, X denotes other explanatory variables, β signifies the effects of the independent variables, α represents a constant term, and ε the error.⁸ Our negative binomial models adopt a parallel strategy, assessing more varied, frequent, or severe harassment.

A total of 582 working respondents answered our sexual harassment questions in both the 2003 and 2004 waves of the YDS. To minimize missing data for independent variables, we substitute responses from up to two prior survey waves (2002 and 2003).⁹ Although this method of addressing missing data relies upon a stability assumption (see Allison 1995:147–150; 2002), it is preferable to imputation-based approaches when the time between observations is relatively short. This strategy resulted in a final analytic sample of 522 cases.

After discussing our regression results, we turn to respondents’ own accounts to detail the processes linking harassment, gender, and power. Our survey data cannot show how manifold and mutually reinforcing identities intersect, as it is difficult to keep sight of respondents as a whole when controlling for individual characteristics (Shields 2008; see, also, Choo and Ferree (2010). Careful qualitative research can reveal how identities intersect, the social structures within which they are performed and created (e.g., Bettie 2003; Gonzalez-Lopez 2005), and the mechanisms linking cause and effect in the social world (Gross 2009). We statistically model some of these intersecting relationships, but our qualitative data are better suited to this task.

To analyze our interview data, we use the data management and analysis program NVivo. We initially coded the data according to the themes outlined in our interview guide. After completing the first round of coding, we reviewed each transcript, looking for common themes and coding like categories of data together. We labeled these passages or “meaning units” (Weiss 2004) with names denoting the themes present within each. The first author then re-read all 33 transcripts to ensure that the excerpts chosen accurately reflected the interview sample as a whole, with a special focus on themes bearing on our major hypotheses: women in authority positions, gender identity, and male-dominated industries and occupations.

SURVEY PREDICTORS OF SEXUAL HARASSMENT

Table 2 shows estimates predicting the likelihood of experiencing any sexually harassing behaviors (in Models 1 and 2), the number of harassing behaviors experienced (in Models 3 and 4), and the likelihood of subjectively defining these experiences as sexual harassment (in Models 5 and 6). Although YDS respondents self-report harassing experiences, there is great ambiguity in the meaning and interpretation of these events. While the first four models identify those most likely to experience harassing behaviors, they do not tell us whether targets themselves consider these to constitute sexual harassment. Over one-third of our sample reported at least one behavioral indicator of harassment in 2004, yet only 7 percent subjectively reported experiencing sexual harassment (11 percent of females but only 1 percent of males). The final two models in Table 2 concern subjective harassment, which represents a higher threshold than the behavioral measures. Here, we can be confident that the reports do not reflect desired sexual banter or behavior that was reciprocated by targets. Because the process of defining and labeling behaviors as sexual harassment varies by sex (Uggen and Blackstone 2004) and few males reported experiencing harassment, we focus this analysis on females only. We also exclude nativity from these models because the small number of female immigrants led to unstable estimates.

Table 2.

Logit and Negative Binomial Models Predicting Three Measures of Sexual Harassment

	Any Harassing Behaviors (Logit)		Number of Harassing Behaviors (Negative Binomial)		Subjective Harassment: Females Only (Logit)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Workplace Power
Supervisor	.833** (.289)	.868** (.317)	.642** (.221)	.547** (.207)	1.112* (.440)	1.245** (.463)
Supervisor* Male	−.938* (.416)	−1.030* (.461)	−.624 (.344)	−.566 (.325)
Sex and Gender
Male	−.948 (.570)	−1.139 (.617)	−.991* (.389)	−.522 (.374)
Femininity	−1.176* (.544)	−1.336* (.595)	−.772* (.350)	−.389 (.336)	1.261 (1.103)	.995 (1.111)
Femininity* Male	1.690* (.690)	1.826* (.754)	1.122* (.511)	.673 (.485)
Industry Sex Composition
Proportion Female	−.336 (.512)	−.475 (.561)	−.702 (.426)	−.634 (.402)	−2.501* (.977)	−2.540* (1.029)
Past Sexual Harassment
Sexual Harassment (2003)		1.887** (.214)		.614** (.088)		1.944** (.489)
Individual Characteristics
White	−.444 (.269)	−.255 (.292)	−.436* (.208)	−.399* (.193)	−.078 (.515)	.260 (.550)
Born in United States	.998* (.482)	.855 (.506)	.359 (.367)	.337 (.347)
Partner	−.221 (.241)	.021 (.266)	−.311 (.200)	−.210 (.188)	−.037 (.485)	.040 (.508)
Children	.005 (.221)	−.008 (.243)	.196 (.186)	.191 (.175)	−.061 (.448)	.166 (.468)
Years Education	.022 (.058)	.036 (.063)	−.015 (.047)	−.020 (.044)	−.137 (.128)	−.117 (.128)
Household Income ($1000s)	−.001 (.003)	−.002 (.003)	.001 (.002)	.000 (.002)	.005 (.005)	.005 (.005)
Work Characteristics
Work Hours	.006 (.012)	.016 (.013)	.005 (.010)	.007 (.009)	.005 (.024)	−.004 (.025)
Log Number of Employees	.090 (.053)	.048 (.058)	.055 (.043)	.049 (.040)	.040 (.101)	.064 (.107)
Job Satisfaction	−.164 (.085)	−.136 (.094)	−.087 (.070)	−.083 (.066)	−.116 (.164)	−.027 (.179)
Job Security	−.038 (.115)	−.067 (.126)	.001 (.093)	.007 (.088)	−.029 (.226)	−.101 (.245)
Professional (v. Tech/Craft)	−.256 (.345)	−.205 (.373)	−.152 (.282)	−.099 (.266)	.307 (.892)	.364 (.922)
Official/Managerial (v. Tech/Craft)	−.353 (.373)	−.467 (.407)	−.393 (.314)	−.384 (.298)	−1.101 (1.034)	−.937 (1.056)
Service (v. Tech/Craft)	.124 (.300)	−.012 (.326)	.041 (.245)	−.040 (.230)	.247 (.837)	.315 (.882)
Constant	.005 (1.255)	−1.008 (1.361)	.543 (.974)	−.308 (.920)	−.580 (2.709)	−1.280 (2.802)
Log Likelihood	−323.957*	−281.255**	−469.897*	−446.395**	−97.092	−89.492**
Number of Observations	522	522	522	522	304	304

Note: Standard errors in parentheses.

^**p<.01

^*p<.05 (two-tailed tests).

Consistent with our first hypothesis, supervisory authority has significantly different effects for males and females. Under the interaction coding in Models 1–4, the main Supervisor and Femininity coefficients indicate effects for females, while the Supervisor*Male and Femininity*Male interactions show the difference in effects for males and females. In all models, workplace power is a significant predictor of harassment for females. Even with the strong control for past harassment, female supervisors are 138 percent more likely to experience any harassing behaviors (e^.868= 2.38 in Model 2), they report a rate of harassment that is 73 percent greater than that of non-supervisors (e^.547= 1.73 in Model 4), and they are nearly three and a half times as likely to subjectively interpret these experiences as sexual harassment (e^1.245= 3.47 in Model 6). The interaction of sex and supervisory authority (Supervisor*Male) is significant in Models 1 and 2 but falls just short of standard significance levels in Models 3 (p=.070) and 4 (p=.066). Taken together, these results suggest that not only are female supervisors more likely to experience harassing behaviors (Models 1 and 2) and to label them as such (Models 5 and 6), but they also report a more varied and sustained form of harassment (Models 3 and 4).¹⁰ [See Appendix Table A1 for a descriptive comparison of females and males by supervisory status.]

Table A1.

Descriptive Statistics by Sex and Supervisory Authority

	Female Respondents		Male Respondents
	Supervisors (N=84)	Non-Supervisors (N=214)	Supervisors (N=82)	Non-Supervisors (N=142)
Sexual Harassment
Any Harassment 2004	.476*	.318	.329	.359
Total Harassment 2004	.738*	.472	.402	.387
Subjective Harassment 2004	.179*	.084	.000	.021
Expressions of Gender
Femininity	3.548	3.598	1.610	1.451
Industry Sex Ratio
Proportion Female	.563	.570	.404	.407
Individual Characteristics
White	.845	.799	.829	.852
Born in the U.S.	.964	.953	.890	.930
Partner	.738	.682	.780	.704
Children	.464**	.673	.610	.563
Years Education	15.298**	14.612	14.659	14.415
Household Income	72.504**	57.118	67.081	59.373
Work Characteristics
Work Hours	39.440**	35.897	43.177**	39.546
Log Employees	4.070	4.379	4.108	4.315
Job Satisfaction	4.310	4.327	4.317	4.190
Job Security	3.083	2.949	3.159	2.944
Technical/Craft Occupation	.024	.079	.42	.310
Professional Occupation	.321	.285	.207	.275
Official/Managerial Occupation	.286**	.084	.146	.141
Service Occupation	.369**	.551	.220	.275

Note: t-tests for differences between supervisors and non-supervisors, separately for males and females.

^**p<.01

^*p<.05 (two-tailed tests).

We find mixed support for our second hypothesis regarding gender conformity. In Models 1–3, more feminine females are less likely to report harassment. The Femininity*Male interaction also signals a significant sex difference in the effect of femininity. The addition of the lagged measure in Model 4, however, reduces the estimated effects below standard significance levels.¹¹ This pattern could indicate a spurious relationship in Model 3 or it could be indicative of statistical overcontrol in the lagged models. Either way, the effect of femininity and its interaction with sex is less robust than the effect of authority position and its interaction with sex.

Industry sex ratio, however, emerges as a significant predictor of subjective harassment in Models 5 and 6, lending support to our third hypothesis. Moving from an industry that is 0 percent female to one that is 100 percent female would decrease the odds of “naming” harassment by 91 percent (e^−2.540= .09). This finding may reflect, in part, the different nature of harassing behaviors in male-dominated work settings. As suggested by our interview data (below), behaviors such as suggestive stories or inappropriate comments about women’s bodies may be interpreted as more menacing, malicious, or degrading at a jobsite where women are socially and numerically isolated. As industry sex ratio was predictive of subjective harassment only, it is also plausible that women may interpret behaviors differently when surrounded by men, and are more likely to label sexualized behaviors as harassment as compared to women in more gender-balanced settings.

Our statistical control for whether respondents experienced sexual harassment in the previous year is a strong and significant predictor in all models, which likely captures stable individual differences in legal consciousness as well as stability in targeting. Those who reported any harassing behaviors in 2003 were over six and a half times as likely to report harassing behaviors in 2004 (e^1.887=6.60 in Model 2); those who were subjectively harassed in 2003 were seven times as likely to report subjective harassment the following year (e^1.944= 6.99 in Model 6). This lagged measure is perhaps most important in models predicting subjective harassment, as the lag effectively controls for stable within-person characteristics that may influence whether a person interprets an event as sexual harassment or dismisses it as sexual banter.

Moving to discussion of individual characteristics, we observe little difference in the likelihood of reporting any harassing behaviors by race, although the rate of harassment among whites was lower than for persons of color in Models 3 and 4. Those born in the United States are also more likely to experience harassment in Model 1, though this effect diminishes with the introduction of the lagged dependent variable. In separate analyses, we examined how sex, supervisory authority, and race intersect to shape harassment experiences (see Table S2 of the online supplement). Among white females, 47 percent of supervisors and 29 percent of non-supervisors reported at least one harassing behavior (p<.01). While workplace power does not significantly increase the odds of harassment for females of color, it does not serve as a protective factor either: 43 percent of supervisors and 45 percent of non-supervisors experienced harassing behaviors. No significant differences were observed among males. These results suggest that harassment is not a unidimensional experience, shaped by just one aspect of a person’s identity. Instead, as demonstrated by intersectionality scholars such as Crenshaw (1991) and Collins (2004), these dimensions operate simultaneously to produce inequalities.

WHY AND HOW AUTHORITY, GENDER, AND COMPOSITION MATTER

While our quantitative analyses establish the basic empirical relations, we turn to qualitative interviews with YDS participants to delineate why and how these relations matter. To learn more about the processes connecting gender and power, we present respondents’ accounts of harassment in the context of our three hypotheses: (1) experiences of women in positions of authority; (2) experiences of workers who do not conform to culturally dominant expectations of gender; and, (3) patterns of harassment in male-dominated industries and occupations.

Women in Authority

Consistent with our quantitative analyses, female interview participants provided concrete examples of how their supervisory status led to harassment. Marie, a project manager on a construction site, felt she was targeted because she worked as a supervisor in a male-dominated industry. She told us she needed to tolerate some harassment to keep her job and maintain working relationships with colleagues, saying, “If you wanted to leave, sure, you could file a claim or do whatever…but if you want to stay at the job…you kind of feel like you have to put up with [it].”

Several women told us that men questioned their ability to effectively supervise others, and Marie was no exception. One older subcontractor explicitly told her, “This isn’t the job for a woman.” Having just walked him through the requirements of some complex paperwork, Marie said, “I think he just thought I was being a nag and that I didn’t know what I was doing.” Later, she observed, “Just being a female in management is difficult, and guys don’t like it--especially the guys that work in the field. They think that women should be secretaries” (emphasis added). Marie’s experiences echo findings by previous researchers (e.g., Eisenberg 2001; Quinn 2002) – that men’s harassment of women has more to do with keeping women “in their place” and marking their own turf than with sexual attraction or arousal.

Holly, the first woman in upper management at her manufacturing firm, also heard derogatory remarks from men at work. Her subordinates sometimes joked, “If we had somebody with balls in this position we’d be getting things done.” Holly was sexually harassed by a client at a company dinner, being groped throughout the evening by the vice president of an influential firm. She explained, “I didn’t know who this guy was, I had no idea. I’m just sittin’ next to him and I’m the only girl at the table….And he’d put his arm around me and pull me towards him and, kind of uncomfortable, and I’d push away. And he kept saying… ‘Oh, I love her. She’s beautiful.’” Holly continued, “He just kept going on and touching me and put his hand on your leg very forcefully and then he was playing the game of trying to unhook the bra with two fingers, which he did after I tried to get up and get away.”

If Holly had not been a supervisor, she would not have been invited to this evening event. Management positions in many manufacturing industries continue to be dominated by men (Hultin 2003; Williams 1992) and supervisors like Holly are often the only women in the room. Holly explained how she was targeted because “I was the only girl there. There were no other girls. Like I said, there’s a female in management in customer service but there’s always been a girl in management in customer service. But many of the positions above that, which are directly below our owner, there’s not been a woman in any of those positions in eons” (emphasis added).

Holly suggests her isolation as a woman in management may have been a key mechanism linking her supervisory status to her harassment. Her story also shows how hegemonic masculinity may operate through collective practice (Connell 1987; Martin 2006; see also Pascoe 2007 on “compulsive heterosexuality”). While her co-workers noticed the harassment, it went on for hours before anyone took action to stop it. Even after others stepped in, it was only to encourage Holly, and not her harasser, to leave the event.

Somebody from our company noticed that [the client] had his hands all over my lap and [my co-worker] goes, ‘Where are his hands?’ and I go, I was sitting like this [shows her legs crossed tightly] and I go, ‘Exactly where you think they are.’ And I pushed [the client] away and so that’s when [my co-worker] realized and motioned and said, ‘I want the bill. We’re outta here.’

No one other than Holly directly confronted her harasser that evening. While several colleagues made it clear to Holly that they did not condone the client’s behavior, they did not speak out against it. Instead, they privately and individually took her aside and urged her to leave. To the extent they played the role of protectors, Holly’s colleagues further undermined her authority.

Several other participants told us of contrapower harassment from subordinates and clients that similarly undermined their authority. Jordan, a police officer, was subverted by another officer when they were dispatched to a loud party. Her colleague was demeaning to women in addressing the young men at the party: “Kinda talking bad about women, you know, referring to them as broads…and here I’m the only woman, I’m a cop, and it’s like you know, you’re not really giving these college kids any reason to show me any respect.” Other participants witnessed or experienced contrapower sexual harassment against women in diverse work settings. Jerry, a correctional officer, told us how male prisoners would stand naked at the front of their cells and masturbate in front of women officers. While working as a youth counselor, Cam told us that a teen ejaculated in a condom and then threw it at a woman counselor who “cried a lot and she quit the job.” Similar experiences were reported by Janice, a high school teacher who was targeted by a student, and by Nate, who told us of a woman produce manager targeted by a delivery person.

Both interview and survey data suggest that experiences of harassment are far more varied than the “typical harassment scenario” of a male boss and female subordinate. Although data on harassers are notoriously difficult to obtain and analyze, our surveys provide some insight into the relative power of both parties in the harassment dyad. To illustrate, Figure 1 reports the number of YDS survey respondents who experienced “staring or leering” by a supervisor, co-worker (of equal or subordinate status), and customers or clients. The most common scenario involved male harassers and female targets, followed by male harassers and male targets. The figure also reports the percentage of supervisors, co-workers, and clients within each harasser/target dyad, although we caution that the percentages are based on a small number of cases (as indicated on the y-axis). In all scenarios, staring and leering by co-workers and clients, rather than supervisors, make up the great majority of these accounts. This general pattern holds across most of the other harassing behaviors, though frequencies vary widely.

Figure 1. Characteristics of Harassers and Targets for Staring or Leering Item.

Note: As workers may experience harassment from multiple parties, some reported multiple scenarios for each behavior.

In supplementary analyses (see Table S3 of the online supplement), female supervisors are consistently more likely than female non-supervisors to experience harassing behaviors, whether from male or female supervisors, co-workers, or clients. This difference is especially pronounced for harassment by male co-workers (p<.05). Male supervisors, in contrast, were no more or less likely to experience harassment than other male workers. Different dynamics could be driving the behavior of various categories of harassers, depending on their structural location relative to female supervisors. Nevertheless, women in authority appear to elicit a power-threat response – especially from below, but perhaps more generally as well. The same forces that exclude women from management positions continue to operate even after they have obtained supervisory authority. Both our qualitative and quantitative data suggest that the robust differences in harassment between women supervisors and non-supervisors are largely driven by harassment from co-workers or subordinates.

Sexual Orientation and Expressions of Femininity

The survey results above suggest a less consistent link between gender non-conformity and the three harassment outcomes. This provides partial support for Connell’s theory of hegemonic masculinity, which emphasizes the significance of gender performance and the negative sanctions elicited by departures from gender expectations. As Marie’s experience on the construction site, Jordan’s work in law enforcement, and the following interviews with male participants demonstrate, sexual harassment often occurs in group settings where “boys will be boys” and workers are targeted for gender non-conformity.

Seth, a journalist who rated himself as more feminine than most other male respondents on our survey, described a “news guy” who targeted him for not behaving more aggressively. He also recalled a restaurant job where sexist comments were part of everyday interaction: “I can remember [the owner] kind of ribbing men, gay men that were working there, in sort of a patronizing way….With men his attitude was sort of manifest as a sort of dominance thing.” Similarly, Cam told us of a co-worker harassed “because of the way he moves, the way he dress, they call him [a] faggot, and they spit on him, they manipulate him.”

Dan, who also reported being more feminine, was taunted about his sexuality by coworkers at a post office. Though he identified as heterosexual, they would say “’you’re gay’ and stuff like that.” When sexual material came through the mail, his co-workers would make inappropriate comments and “they’d cut photos of some of the post office guys and put the heads on the bodies of models and stuff like that.” Dan told us about a co-worker who was targeted because “he had tendencies, and I think they kind of focused on him because they thought ‘okay, you like men.’” While Dan was unaware of this worker’s sexual orientation, he told us his coworker was “more feminine” and isolated, since he “hung out with women more than men.”

Men’s collective practice of masculinity similarly undermined women’s authority during Lisa’s time working in an advertising agency. Like the fictitious ad agency portrayed on the television series Mad Men, “the boys” would exclude women from creative decisions, “drink the afternoon away,” and visit strip clubs after hours, leaving the lion’s share of the day-to-day work for women staff members. When an “obviously gay” temp worker arrived at the agency, he was immediately labeled as an outsider. The top three men at the firm were taken aback by the worker’s arrival, and Lisa could tell they were thinking, “Oh my god! There’s a gay man in my office!” She added, “I had seen those guys drunk so many times and they were so macho and so misogynistic that I didn’t doubt for one second that they’d take him out and beat him up. I thought they were fully capable of doing that.” Later, Lisa’s boss told her, “That guy – get him outta here or someone’s gonna break his legs.” Lisa explained the situation to the temp worker, who later sued the company for wrongful termination. After the case was settled, Lisa believed she was held responsible for the lawsuit. She described how “my responsibilities slowly eked away from me … Number one, I’m sure some of it was, well, we just can’t trust her.”

These accounts reveal how putatively “effeminate” men, those perceived to be somehow weak in character or womanlike in their presentation of self (Hennen 2001), are targeted in some work settings. Gender and sexuality were often erroneously conflated in these reports, as men were identified as gay simply because of their gender performance. Research on the multiple masculinities enacted by gay men (Connell 1992; Hennen 2008) calls such assumptions into question, of course, as do broader critiques of heterosexuality as an institution (e.g., Ingraham 2008). More generally, our participants’ accounts comport with those of previous research (Quinn 2002; Tallichet 1995). Social isolation and what Lisa called a “macho and misogynistic” workplace culture serve as key mechanisms connecting gender performance and harassment – concerns discussed below in reference to our third hypothesis.

Male-Dominated Professions and Occupations

Above, we found only mixed support for our third hypothesis regarding differences across occupational and industrial sectors. Females in predominantly male industries reported significantly greater subjective harassment, with industry composition also approaching significance in the behavioral count models (p<.10). While the occupational variables were not predictive in the multivariate models, we observed somewhat more harassment in service work for males and in technical and craft occupations for females.¹²

As Dellinger and Williams (2002) suggest, qualitative work is well-suited for analyzing how the meaning of sexual behaviors varies in different organizational contexts. Like Tallichet’s (1995) study of coal miners, our interviews show how some men use harassment and discrimination to diminish women employed in masculine occupations. For example, Jordan experienced gender-based discrimination before officially beginning her security job. A coworker refused to issue her a uniform, saying, “There’s no way they hired you for security.” Despite this early setback, Jordan eventually became a police officer, describing a work environment that “non-police personnel would maybe consider inappropriate. You know everybody probably sees on TV how a lot of the jokes and a lot of the way police officers act can be real callous and can be offensive…There’s probably a lot of sexual joking.” Jordan encountered co-workers who believed women did not belong in law enforcement. This led to serious and potentially life-threatening discrimination, when a policewoman did not receive the necessary “backup” from other officers when she responded to calls for service:

She’d get a call and nobody would go to assist….[T]here would be a few people that were okay with her or whatever that would come and assist her but you know for the most part nobody would answer up to go and eventually the dispatcher will assign somebody to go.

Other participants shared similar accounts of male-dominated settings, as when Jenna’s manager at a gas station made comments about her body and, the same day, a coworker told a customer, “we’ll send Jenna to blow your car.” Jenna chose not to confront her co-workers, telling us: “I was the only female there….So it’s kinda like they work on the buddy system, you know? So the more you say the more you get yourself in trouble” (emphasis added). Some women felt that sexual harassment came with the territory, tolerating such behavior while attempting to prove themselves as women in these fields. Marie, for example, encountered “constant” sexual advances and frequent catcalls, staring, and inappropriate sexual questions while working in construction. She told us, “Knowing I was going to be at a company like that, I kind of expected it.”

Some men we interviewed also experienced sexually harassing behavior in male-dominated firms. Rick reported hearing many gay and sex jokes at a printing company. He told us, “I would just sit there and grin but it’s just the fact that [the jokes] were so awful that I do remember them.” Rick believed the working conditions would have been “less, you know, college dorm room” had women been present. Similarly, John described co-workers’ interactions during his military service as “pretty unprofessional” and “inappropriate,” adding “You could open up a drawer and there would be a bunch of [Playboy] magazines in there.”

Marie, Holly, and other women we interviewed pointed to the particular difficulties they experienced as supervisors in male-dominated industries. In light of these comments, we returned to our survey data to learn how workplace sex composition might affect harassment among supervisors and non-supervisors. Figure 2 shows the proportion reporting harassment by supervisory status in predominantly male and female industries (with predominance defined as 50 percent or more workers). Our sample contains too few female supervisors in male-dominated industries to detect a significant interaction in the models shown in Table 2, but the data show a consistent pattern: female supervisors are more likely to experience harassing behaviors in predominantly male industries (58 percent) than predominantly female industries (42 percent).¹³

Figure 2.

Percentage Reporting Any Harassment by Sex, Supervisory Authority, and Industry Sex Ratio

GENDER, POWER, AND BEYOND

This multi-method analysis offers the strongest evidence to date on the interaction of sex, gender, and power in predicting sexual harassment (Berdahl 2007a; Connell 1987; Quinn 2002; Uggen and Blackstone 2004). While the “vulnerable victims” perspective suggests that authority might act as a protective factor, exempting women from the suggestive gaze or unwelcome touch of co-workers, we find that supervisory status actually increases women’s harassment, in keeping with the “power threat” perspective. Though other research has suggested this counter-intuitive result, this study is the first longitudinal investigation to clearly reveal the pattern.

Could this finding be a product of the greater sensitivity or legal consciousness of supervisors? If so, we would have expected to observe stronger effects of supervisory status on subjective harassment (in Models 5 and 6 of Table 2) than on the behavioral indicators (in Models 1–4). By every measure, however, female supervisors are more likely to report harassment. Moreover, although supervisors may have greater awareness of sexual harassment law and policy, most individual differences in consciousness should be absorbed in the lagged dependent variable measured just one year prior. While legal consciousness undoubtedly evolves over the life course, it is unlikely that supervisors’ consciousness changed so dramatically over a 12-month period. In addition, there is no evidence to suggest that either consciousness or the lagged dependent variable would operate differently for male and female supervisors. Instead, our survey and interview data extend and confirm research connecting sexual harassment with women’s workplace power (Berdahl 2007a; Quinn 2002; Willer 2005).

Within the supervisor category, there may be important differences in harassment by level of workplace authority. For example, women in upper management, or in organizations with few women in supervisory roles, may experience more harassing behaviors (Cohen et al. 1998). When we distinguished between females who supervised only 1–3 workers and those who supervised a greater number, we found larger positive effects of supervisory authority on harassment for those supervising a larger number of workers. Further research is needed, however, to move beyond a simple supervisory/non-supervisor dichotomy and to better locate workers in hierarchies of authority. Studies of harassment in the armed forces, for example, could more clearly speak to finer-grained differences by rank (Miller 1997).

Regardless of their organizational rank, sexual harassment objectifies workers and reduces women to sexual objects in ways that “may trump a woman’s formal organizational power” (Quinn 2002:392). Indeed, our qualitative interviews help to explain why women in authority positions are targeted for harassment. Women supervisors repeatedly spoke about feeling isolated, and of harassment by co-workers and subordinates directed toward putting them “in their place.” Still, they tolerated such harassment to keep their jobs. Social isolation may also represent an important mechanism linking expressions of gender and industry sex ratios to harassment, in keeping with our second and third hypotheses. Whether attempting to prove they could lead a team of workers or prove themselves as women in masculine fields, women’s isolation in these positions repeatedly left them vulnerable to harassment. Women supervisors were told “this is no place for women,” while men and women who diverged even slightly from rigid gender expectations elicited taunts and more menacing responses.

Although our longitudinal approach is well-suited to testing our hypotheses, we must note several caveats. First, the YDS is based on a Minnesota sample that is not nationally representative. Second, our quantitative analysis is based on harassment occurring when respondents were 29 or 30 years old. While analysis of a single cohort is advantageous in distinguishing authority effects from age effects, supervisory authority and gender may operate differently in other phases of the life course. Further research is needed to consider potential interactions between age, gender, and power, as well as changing definitions of harassment over time. Third, although we measure harassment both behaviorally and subjectively—increasing confidence in our findings—we rely on self-reported accounts by targets. There is a large difference between the percentage of respondents who report harassing behaviors relative to the number who define their experiences as sexual harassment. This discrepancy is attributable, in part, to differing definitions of harassment among respondents, a reluctance to label oneself as a target or victim, and differences in organizational cultures and norms regarding workplace sexuality (see Dellinger and Williams 2002; Ewick and Silbey 1998). Finally, the vast majority of our YDS sample self-identified as “straight.” More qualitative and large-scale survey research on the harassment experiences of workers expressing other sexual identities is clearly needed.

Despite these caveats, this study provides clear evidence on the effects of workplace authority on sexual harassment, with consequential implications for theories of gender and power. In particular, we find that female supervisors are more, rather than less, likely to be harassed, supporting the notion that interactions between workers are not driven strictly by organizational rank. Instead, co-workers’ relative power is also shaped by gender. While women supervisors’ authority is legitimated by their employer, sexual harassment functions, in part, as a tool to enforce gender-appropriate behavior. Formal lines of authority are established to maximize efficiency and help organizations run more smoothly, but tensions surrounding gender or other forms of inequality will likely manifest in other ways (Roscigno 2011). When women’s power is viewed as illegitimate or easily undermined, co-workers, clients, and supervisors appear to employ harassment as an “equalizer” against women supervisors, consistent with research showing that harassment is less about sexual desire than control and domination (Berdahl 2007a; 2007b; Schultz 2003).

While sexual harassment policies are put in place to protect workers, organizational practice is often misaligned with formal policies or grievance procedures, calling into question fundamental assumptions many sociologist make regarding organizational constraint and agency (Roscigno 2011). Take, for instance, the sexual harassment of Holly at a company dinner. Her co-workers’ concern led to her removal from the situation rather than the punishment of her harasser. While her colleagues ended Holly’s harassment, they did so in a way that would not jeopardize their profitable business relationship with the client. Holly’s harasser was quickly labeled by her co-workers as a “bad apple,” but the organizational contexts that allowed the harassment and broader gender inequality to occur remained unquestioned.

Many of our interviewees experienced wide-ranging forms of sex-based discrimination as well as sexual harassment. These findings may thus extend more broadly to workplace bullying, intimate partner violence, and other forms of discrimination and harassment. For example, Johnson (1995:284) identifies “patriarchal terrorism” as a form of intimate partner violence that reflects “patriarchal traditions of men’s right to control ‘their’ women.” Similarly, Macmillan and Gartner (1999) direct attention to dyadic power relations, finding that women’s employment lowers risks of spousal abuse when their male partners are employed but increases risks when their male partners are unemployed. Further research might also examine sexual harassment dyads and the positions and perspectives of harassers (Quinn 2002). Harassers appear to view targets as a threat to their own power – in the workplace and in the broader society.

Theory and research on gender stratification often makes the implicit assumption that problems such as sexual harassment, sex discrimination, and workplace bullying will recede if and when women attain greater power at work. Yet power in the form of supervisory authority also provokes backlash from clients, subordinates, and fellow supervisors. This paradox of power represents both a challenge and an opportunity for existing frameworks. Beyond gender, characteristics such as race or class may similarly trump formal organizational authority in determining workplace power. While firms are increasingly adopting policies to increase diversity in management (Kalev, Dobbin, and Kelly 2006), this study points to a new obstacle for women and, perhaps, racial minorities in leadership positions (but see Hirsh and Lyons 2010). To test the latter idea, an extension of this analysis might examine whether racial minorities who supervise others are subject to greater racial harassment.

While legal and organizational responses to sexual harassment have evolved rapidly in the past three decades, the cultural image of harassers and targets has not kept pace with changing workplace realities. Many still view the typical harassment scenario as one involving a sleazy male boss and a powerless female secretary. As this article shows, the reality is far more varied. Moving away from such stereotypes is a critical step for improving organizational policies and training procedures on sexual harassment. Effective training must go beyond male boss/female subordinate role-playing exercises and better reflect the diversity of harassment experiences. Effective grievance procedures must also enable targeted workers to come forward without undermining their own authority. For women who become bosses themselves, their positions create a paradox of power in a gender system that continues to subordinate women. In taking on positions of authority, they also take on a greater risk of sexual harassment.

Biographies

Heather McLaughlin is a sociology Ph.D. student at the University of Minnesota. She received her bachelor’s degree in psychology and sociology from the University of Maine. Her research interests include gender and sexuality, law, work and occupations, life course, and the family, and her dissertation work focuses on gender, youth sport, and work. Her work has appeared in journals such as Law & Society Review and The Sociological Quarterly.

Christopher Uggen is Distinguished McKnight Professor of Sociology at the University of Minnesota and editor of thesocietypages.org (with Doug Hartmann). He studies crime, law, and inequality, believing that good social science can light the way to a more just and safer world.

Amy Blackstone is Associate Professor and chair of sociology at the University of Maine. Her current projects include studies of workplace satisfaction among faculty, older workers’ harassment experiences, and the lives of voluntarily childless adults. Blackstone’s prior research on activism in the breast cancer and anti-rape movements has appeared in journals such as Gender & Society and Journal of Contemporary Ethnography.