Introduction

The increased labor force participation rates of women combined with conditions of structural lag have led many individuals to struggle in fulfilling the often competing responsibilities associated with paid work and family life (Hochschild and Machung 1989; Winslow 2005). A growing literature has examined conflict between paid work and family life and the importance of structural factors, including occupation and industry, in shaping the navigation of these domains (England et al. 1994; Hochschild 1997; Lytton and Romney 1991; Moen and Roehling 2005; Peters 1994; Reskin 1993; Reskin and Roos 1990). Structural variables are particularly crucial because many occupations and industries are organized in ways that do not facilitate balance between work and family life (Maier 1999; Maume and Houston 2001; Moen and Roehling 2005).

Here we examine how the extent of occupational and industry sex segregation interact with gender to impact the dependent variables of family-to-work conflict, work-to-family conflict, coworker support, and supportive work–family culture. The analysis is guided by the theory that violating gender expectations by working in a sex atypical industry or occupation influences people’s workplace experiences and navigation of paid work and family life. Although the dataset used in the present study is from the US, the study is of broad importance as the labor forces of many countries are characterized by some degree of occupational and industrial sex segregation and people throughout the world are concerned with potential conflicts between paid work and family life (e.g. Charles and Grusky 2004; Hill et al. 2004). We examine the research questions using data from the 2002 edition of the National Study of the Changing Workforce (N = 2,810).

In addressing our research questions, we posit that within sex segregated workplaces individuals encounter gendered expectations concerning their behavior (Acker 1992; Pierce 1995; Reskin and Roos 1990). For example, previous studies have demonstrated that employees working in sex-typical occupations and industries are rewarded, whereas employees in sex-atypical jobs are frequently intensely scrutinized and left out of important social networks (Jacobs 1993; Kanter 1977; Kimmel 1993; Pierce 1995; Williams 1992). While previous studies have been beneficial in examining how the extent of occupational and industry sex segregation is a major predictor of sex-based inequalities in pay along with fairness of promotion policies, few studies have examined how sex segregation impacts inequalities experienced in seeking to balance work and family life (Glass 1990; Reskin et al. 1999).

We focus on occupations and industries because they continue to be organized in ways that impede the balance of work and family (Maume and Houston 2001). Together they jointly impact the workplace environment experienced by employees. An individual working in a sex-typical occupation in a sex-atypical industry is likely to have different experiences than an individual working in a sex-typical occupation in a sex-typical industry. For instance, a woman working as an administrative assistant in the automobile industry is likely to encounter a much different workplace environment than a woman working as an administrative assistant in the real estate industry. Hence, in order to better understand work-to-family conflict, family-to-work conflict, coworker support, and supportive work–family culture, we take into account the extent of both occupational and industry sex segregation. Our study contributes to work–family scholarship by more fully attending to gender and structural factors by examining the key role played by the extent of occupational and industry sex segregation.

Conceptualization

Work-to-Family Conflict and Family-to-Work Conflict

As scholars began to address the implications of women’s increased labor force participation rates, the potential for work and family to come into conflict was at the forefront of research concerns (Hochschild 1997; Kanter 1977). The term work–family conflict is often used to refer to when an individual experiences incompatibilities between work and family life (Voydanoff 2005). Researchers, however, soon found that conflict between work and family is bi-directional, with work and family domains both having the potential to impact each other, hence the terms work-to-family conflict and family-to-work conflict are typically used (Voydanoff 1988, 2002, 2005). Work-to-family conflict is used to refer to inter-role conflict that occurs when paid work activities make it difficult to attend to family needs (Burley 1995; Greenhaus and Beutell 1985; Voydanoff 1988, 2002). For example, when a workplace expects an employee to work overtime without much notice this can cause difficulties preparing dinner or watching children. Work-to-family conflict is of central concern because it has been linked to many negative outcomes including distress, strain, reduced family cohesion and marital satisfaction, and social withdrawal (e.g., MacDermid and Harvey 2006; Stevens et al. 2002). The term family-to-work conflict is used to refer to family demands making it difficult to attend to paid work responsibilities (Dilworth 2004; Voydanoff 2005). For instance, if a parent needs to leave work early to pick up a sick child, then this might lead to difficulty completing a project on time. Both work-to-family conflict and family-to-work conflict are viewed as reducing an individual’s ability to successfully balance paid work and family life.

Supportive Work-Family Culture and Coworker Support

Scholars have also been interested in the extent to which organizations are characterized by a culture that is supportive of workers balancing work and family and the role played by coworker support. As workers negotiate paid work and family life they often encounter workplaces that are not sympathetic to non-work issues that they may face. Hence, of central concern to many employees is how supportive their workplace organization’s culture is of their family needs (Thompson et al. 1999). Here we use the term supportive work-family culture to refer to the extent that the organization and supervisor value and assist their employees’ integration of work and family (Allen 2001; Thompson et al. 1999). Studies have found that supportive organizational cultures are related to reduced work-to-family conflict and family-to-work conflict (Hill 2005; Thompson et al. 1999). Clearly, the level of supportive work–family culture of an organization is likely to have a crucial impact on the ease of workers negotiating these spheres, hence it is essential to explore factors that impact this key variable.

Coworkers also play a central role in how people negotiate their work and family lives. Here we focus on coworker support, which refers to the extent that individuals view their fellow workers as being helpful and supportive of them (Liao et al. 2004). Individuals seeking to balance work and family life may have their efforts thwarted by unsupportive coworkers or enhanced by supportive coworkers. For example, leaving work early to attend a child’s sporting event may be unsuccessful if coworkers refuse to cooperate with the worker seeking to rearrange their schedule. On the other hand, supportive coworkers can serve to make balancing work and family easier by helping to pick up the slack if an employee needs to leave early for a family reason.

Occupational and Industry Classification

In this study we use the extent of occupational and industry sex segregation (as measured by the percent of women in each) as our primary predictor variables. Using percentage of women per occupation and industry is one way to measure the extent to which an occupation or industry is characterized by sex segregation. We propose that as the percentage of women in an occupation or industry increases that this reflects the occupation or industry being more sex-typical for women and sex-atypical for men. It has been suggested within social and economic research (IPUMS 2007) that the examination of both occupational category and industry classification is necessary to offer the greatest insight into workplace dynamics. Hence, in order to enhance understanding of the impact of segregated workplaces on work–family outcomes, it is important to examine the composition within both the industry classification and the occupational category. An industry refers to business activity that occurs within a particular sector of the economy with industry classifications consisting of 12 industry sectors (Bureau of Labor Statistics. Retrieved September 25, 2007, from http://bls.gov.). The sectors primarily focus on private-sector employment within areas such as construction, leisure and hospitality, manufacturing, natural resources and mining, and wholesale and retail trade. However, the government sector also includes many publicly-owned establishments such as public hospitals. An occupation refers to “collections of jobs that involve similar activities across establishments” (Padavic and Reskin 2002, p. 64). Occupational categories consist of nine groupings and representative occupations include service workers, sales workers, laborers, and technicians.

Theoretical Background

Normative gender expectations of the larger society influence whether or not the responsibilities of paid work and family life are viewed as being in conflict with one another. For instance, the roles of father and worker are generally thought to be congruent, whereas the roles of mother and worker are viewed as conflicting and women are often expected to prioritize family over work (Chafetz 1988, 1999; Duxbury and Higgins 1991, 1994). Hence, women working in the paid labor force confront different evaluations of their behavior by society than men. Also playing a central role is the fact that the American workplace is still characterized by a high degree of occupational and industry sex segregation (Maume and Houston 2001; Reskin 1993). All workplace environments are interwoven with gendered expectations (Acker 1992) that have important implications for negotiating work and family domains, but these expectations are influenced by the extent of occupational and industry sex segregation (Jacobs 1993). Indicative of this is the fact that an individual in an occupation or industry dominated by the other sex is usually spoken of with qualifiers and treated in stereotypical ways (Miller-Loessi 1992; Reskin et al. 1999). Indeed research continues to suggest that the dominant group tends to ignore information that contradicts their stereotyped view of the minority group (Reskin et al. 1999). Customers have also been shown to have negative reactions to employees in sex-atypical jobs. For example, research has demonstrated that customers were uncomfortable with and had decreased satisfaction when dealing with employees that did not match the gender-type of the job (Mohr and Henson 1996; Williams 1989).

The central theoretical underpinnings of our perspective lie in Kanter’s path-breaking book Men and Women of the Corporation, which argued that those who work in sex-atypical occupations are “tokens” that often encounter negative experiences. While her study focused on the consequences of female tokens working in sex-atypical fields, she proposed that males working in sex-atypical fields would encounter similar challenges. In particular, Kanter’s (1977) work showed that female tokens were likely to be left out of important informal networks, to be constantly watched, and to be subjected to “boundary-heightening” exaggerated displays of masculinity from men meant to demonstrate to women that they did not fit in.

Scholarship following Kanter has indeed illustrated numerous examples of the negative treatment women receive for violating gender norms by participating in sex-atypical occupations and industries. Studies have found that females in sex-atypical occupations are left out of important social networks, viewed as less competent than their male counterparts, receive less pay, and are treated in stereotypical ways (English 2003; Pierce 1995; Tallichet 1995). Other findings suggest that women in sex-atypical occupations have to work harder to be taken as seriously as men and experience more work-to-family conflict than their male counterparts (Hult 2005; Rosser 2004). While some research suggests that men working in sex-atypical occupations are actually rewarded for this (Pierce 1995; Williams 1989, 1992, 1993), we propose that men will encounter difficulties for violating gender norms by working in sex-atypical occupations and industries. Indeed some research does indicate that men do feel isolated and vulnerable in sex atypical occupations (e.g., Allan 1993). Hence, in general, as the percent women in an occupation and industry increase, we expect that men and women will be impacted in different ways—men will generally have more negative experiences and women will have more positive experiences. In other words, both men and women will be exposed to negative outcomes for working in sex-atypical industries or occupations.

According to Kanter’s research, women must be 15% or less of an occupation in order to truly be considered tokens (Kanter 1977). While this numerically-precise definition can be insightful (especially for qualitative research seeking to explore particular occupations and industries), we take the key ideas of Kanter to argue that the extent of occupational and industry segregation will play a central role in shaping outcomes regardless of whether or not the sex imbalance is skewed enough for the individual to truly be considered a token. Some research, in fact, has shown that as women become non-tokens in occupations, negative behavior by men often increases in response to this perceived threat (Yoder 1991).

Having established the key role played by sex segregation in shaping individuals experiences, we propose that the extent of occupational and industry sex segregation is central in shaping work-to-family conflict, family-to-work conflict, supportive work-family culture, and coworker support. The primary reason for this is that many workplace organizations remain organized according to the assumption that family responsibilities should be kept completely separate from paid work (Acker 1992). Such assumptions are likely to be heightened in occupations and industries that are typically male (Acker 1992; Pierce 1995). For instance, in occupations with a higher percentage of male employees, power has historically been held by men who may not have been concerned with alleviating the conflict workers may experience between work and family domains. Further, researchers have suggested that work-family programs aiming to ease work-to-family conflict are often underutilized because workers fear they will be viewed as less committed or dedicated to their jobs if they take advantage of them (Glass 2000). This is of critical importance as research has indicated that it is the use of policies, rather than their mere availability that reduces work-to-family interference (O’Driscoll et al. 2003; Thompson et al. 1999). We argue that fear of using policies and programs is likely influenced by the extent of occupational and industry sex segregation present. Workers, especially women, working in sex-atypical occupations and industries, may be reluctant to take advantage of available programs because they view the workplace environment as being unsupportive of taking such an action.

We suggest that as the percent of women in an occupation and industry decreases that women will be more likely to encounter family-to-work conflict and work-to-family conflict than other women (working in occupations/industries with higher percentages of women) and men. This stems both from the higher likelihood that such women will have family-related needs to attend to compared to men (Coltrane 2000; Shelton and John 1996) and from the fact that they will encounter additional pressure to keep their work and family lives separate as they are viewed as violating gendered expectations. For instance, Maume and Houston’s (2001) study of white-collar workers indicated that women in male-dominated groups experienced increased perceptions of work-to-family conflict. We propose that, for men, as the percent of women in an occupation and industry increases, men’s work-to-family conflict and family-to-work conflict will increase. This is because such men are likely to encounter a workplace organization that frowns on them engaging in further behavior that is not normative for their gender.

We are also interested in how the extent of occupational and industry sex segregation shapes coworker support. Relational demography research suggests a similarity-attraction framework with respect to this variable (Tsui et al. 1992). As such, gender similarity, as a shared demographic characteristic, will likely lead to increased social integration (Mueller et al. 1999). Demographic similarity has also been linked to cooperative relationships, greater commitment to the group, and effective communication (Liao et al. 2004). Hence, we expect that for both men and women working in a sex-atypical industry will result in lower levels of coworker support, as they are viewed as being different from and less connected to their workers. Therefore, as percent women per occupation and industry increase, we expect that men’s coworker support will decrease and women’s will increase. Indeed, previous research has found that women in sex-atypical occupations are often excluded from social networking and receive less support from their coworkers (Kanter 1977; Pierce 1995; Schneer and Reitman 1994; South et al. 1987).

We also argue that the extent of occupational and industry sex segregation will likely impact supportive work–family culture. Institutional constituency research suggests that organizations may strategically respond to accommodate the needs of their given constituency (Goodstein 1994). For female-dominated industries and occupations, this suggests that organizations and supervisors, understanding the importance of the family domain for their primary employees, will act in ways that help their employees balance paid work and family life. Given these organizations’ reliance on females for their human capital, more supportive work cultures are a logical approach in order to secure the needed talent. Goodstein’s (1994) findings, though complex, suggest that firms will respond strategically if they are dependent on a particular constituency. Although his results did not clearly show that firms adopt more work–family policies as the proportion of women working for them increased, his findings supported the notion that firms are indeed aware of their constituencies and act accordingly. Hence, women working in sex-typical industries and occupations may report greater supportive work–family culture than men and women working in sex-atypical industries and occupations. We argue that for men a slightly more complicated relationship is likely to exist. Given that society continues to hold women more responsible for family and that women continue to do the bulk of domestic labor (Brines 1994; Coltrane 2000; Shelton and John 1996), we argue that men will be perceived as not needing assistance in balancing work and family. Even when men work in occupations and industries with higher percentages of females, we argue that men will perceive less supportive work–family culture. This perception may stem from two factors. First, men themselves may be less cognizant of how supportive an organization is of family needs given that they generally do not perform as much domestic labor as women. Second, organizations and supervisors may not perceive men to be as in need of family support and hence may inadvertently withhold it from them.

The Present Research and Hypotheses

To summarize, our argument suggests that the percentage of women in an occupation and industry will differentially shape the experiences of men and women. Specifically we argue that, for women, as the percent women in an occupation and industry increases, so will perceptions of coworker support and supportive work–family culture, but family-to-work conflict and work-to-family conflict will decrease. In contrast, for men, as the percentage of women in an occupation and industry increase, so will family-to-work conflict and work-to-family conflict, but perceptions of coworker support and supportive work–family culture will decrease. This is in line with a perspective that suggests individuals working in sex-atypical industries and occupations will experience difficulties for doing so, while individuals working in sex-typical industries and occupations will be rewarded.

The research questions are examined using data from the 2002 edition of the National Study of the Changing Workforce (N = 2,810). The analysis is performed using separate OLS regressions for each dependent variable. In predicting each dependent variable we include the interaction terms of gender with percentage of women in an occupation and gender with the percentage of women in an industry along with the other predictor variables. These interaction terms allow us to determine if men and women are impacted differently by the percentage of women in an occupation or industry. In addressing these research questions we also take into account several important control variables pertaining to individual characteristics along with paid work and family life that might impact the proposed relationships. Specifically, we control for the individual characteristics of age and education level; the key workplace variables of job tenure, job autonomy, number of hours worked per week, and gender of the supervisor; and for the family life variables of whether the respondent is a single parent and if the respondent has children in the home. While these are not the only workplace and family variables that likely shape the experiences of workers, we argue that they can stand in for other additional variables pertaining to paid work and family life (Rothausen 1999; Smith et al. 1989). Based on our conceptualization and theoretical perspective, we put forth the following hypotheses concerning the moderating role of gender on the four dependent variables:

  • Hypothesis 1: As the percentage of women in an occupation and industry increase women will report higher levels and men lower levels of coworker support.

  • Hypothesis 2: As the percentage of women in an occupation and industry increase women will report higher levels and men lower levels of supportive work–family culture.

  • Hypothesis 3: As the percentage of women in an occupation and industry increase women will report lower levels and men higher levels of work-to-family conflict.

  • Hypothesis 4: As the percentage of women in an occupation and industry increase women will report lower levels and men higher levels of family-to-work conflict.

Method

Sample

The proposed hypotheses are examined using data collected from the 2002 National Study of the Changing Workforce and the 2002 edition of Job Patterns for Minorities and Women in Private Industry. The 2002 National Study of the Changing Workforce was instigated by the Families and Work Institute (Bond et al. 2003). The total dataset is comprised of 2,810 wage and salaried employees, including 1,640 women and 1,170 men. The percent women per industry and occupation were collected from the Equal Employment Opportunity Commission (EEOC) reports published in the 2002 edition of Job Patterns for Minorities and Women in Private Industry. We used the gender composition within industry classifications and occupational categories as determined by the EEOC to gauge sex-typical occupations and industries. Given the influx of women into the labor force, using actual percentages rather than classifying industries and occupations based on past research provides a more accurate representation.

Procedure

The 2002 data were collected by Harris Interactive using a questionnaire developed by the Families and Work Institute. A nationwide cross-section of employed adults was interviewed over an 8-month time period. All regions within the continental US were represented. Interviews lasted approximately 45 min and were conducted using a computer-assisted telephone interviewing system. The sample was generated by random-digit-dial methods. Eligibility of participants was limited to paid employees, 18 years and older. The response rate of estimated eligible households was approximately 52% (Bond et al. 2003). Industry and occupation categories were assigned according to the three-digit classification used by the US Census.

Measures

Refer to the “Appendix” for all items comprising each measure.

Supportive Work-Family Culture

Supportive work–family culture was measured with nine items that encompass support provided by both the organization and supervisor. Eight of these items comprise an established scale that has been used in previous research (e.g., Sahibzada et al. 2005) and one additional item was included for increased reliability. Representative items include “If you have a problem managing your work and family responsibilities, the attitude at my place of employment is: ‘You made your bed, now lie in it!’” and “I feel comfortable bringing up personal issues with my supervisor.” (1 = strongly agree; 4 = strongly disagree). Scales were aligned so higher scores represent greater perceived levels of supportive work–family culture. The items were summed and then divided by four to remain on a one to four scale. The usable sample is 2,294 with a Cronbach’s alpha of .85.

Coworker Support

Coworker support was measured with four items. Three of the items comprise an established scale that has been used in previous research (e.g., Maume and Sebastian 2007). For increased reliability, we have included one additional item. Representative items include “I have the coworker support I need to manage my work and family life” and “I’m treated with respect at work.” (1 = strongly agree; 4 = strongly disagree). The scores were reverse coded so that higher scores reflect higher levels of coworker support. The usable sample is 2,804 with a Cronbach’s alpha of .78.

Work-to-Family Conflict

Work-to-family conflict was measured with an established five-item scale that has been used in previous research (e.g., Hill 2005; Maume and Houston 2001; Voydanoff 2005). Representative questions include “How often has your job kept you from concentrating on important things in your family or personal life?” and “How often have you not had enough time for your family or other important people in your life because of your job?” (1 = very often; 5 = never). The scores were reverse coded so that higher scores represent higher levels of work-to-family conflict. The usable sample is 2,789 with a Cronbach’s alpha of .87.

Family-to-Work Conflict

Family-to-work conflict was measured by a five-item scale that has been used in previous research (e.g., Hill 2005; Voydanoff 2005). Representative questions include “How often has your family or personal life kept you from doing as good a job at work as you could?” and “How often has your family or personal life kept you from concentrating on your job?“ (1 = very often; 5 = never). Scores were reverse coded such that high scores represent higher levels of family-to-work conflict. The usable sample is 2,783 with a Cronbach’s alpha of .81.

Percent Women per Industry

We used the percentage of women in an industry to measure the extent of industry sex segregation. The percentage of women per industry was collected from the EEOC 2002 publication of Job Patterns for Minorities and Women in Private Industry. Industry percentages were determined within each Standard Industrial Classification code. Examples of industry classifications include mining, construction, manufacturing of non-durable goods, wholesale trade, and retail trade. Percentages of women ranged from 12.5% in construction to 61.9% in finance, insurance, and real estate. The usable sample is 2,791.

Percent Women per Occupation

To measure the extent of occupational sex segregation we used the percentage of women in each occupation, which was collected from the EEOC (2002) publication of Job Patterns for Minorities and Women in Private Industry. The categories were consistent with those identified by the US Bureau of the Census. Occupation percentages were determined within each of the nine groupings provided. Examples of occupational categories include technicians, sales workers, craft workers, laborers, and service workers. Percentages ranged from 13% for craft workers to 79.8% for office and clerical workers. The usable sample is 2,797.

Control Variables

Job tenure, hours worked per week, job autonomy, job demand, and the gender of the supervisor were used as workplace control variables. Individual characteristics that were used as control variables are gender, age, and education level. Control variables from the family domain included whether the respondent had children at home and whether the respondent was a single parent. Supportive work–family culture was also used as a control variable in the analyses of work-to-family and family-to-work conflict. Age, job tenure, and hours worked per week were measured as age in years, years on the job, and total hours worked per week. Gender was coded 1 if the respondent was female and 0 if the respondent was male, and gender of the supervisor was coded as 1 if the supervisor was female and 0 if the supervisor was male. The variable of children at home was coded as 1 if the respondent reported at least 1 child living at home and 0 if they did not report children at home. The variable single parent was coded as 1 if the respondent was a single parent and 0 if the respondent was not. Education level was coded as 1 for high school or less, 2 for some college or technical college, 3 for a bachelor’s degree, and 4 for a graduate degree. Job autonomy was measured with three items with a Cronbach’s alpha of .68. Representative items are “I have the freedom to decide what I do on my job” and “I have a lot of say about what happens on my job.” Response categories ranged from 1 to 4 with the items reverse coded such that higher scores represent higher levels of job autonomy. Job demand was measured with five items with a Cronbach’s alpha of .78. Representative items include “I never have enough time to get everything done on the job” and “I am asked to do excessive amounts of work.” Items were rated on both 1 to 4 and 1 to 5 scales. The scales were aligned such that higher scores represent greater job demand. In order to equalize the range of responses for scale construction, the scales were standardized by setting the means to zero with a standard deviation of one.

Results

Correlations and descriptive statistics of the investigated variables are presented by gender, Table 1 for women and Table 2 for men. A MANOVA was conducted to test for differences by gender for the examined dependent variables. No significant mean differences were found for work-to-family conflict and family-to-work conflict; however, significant mean differences were found for the variables of coworker support (p < .01) and supportive work-family culture (p < .001) with women reporting higher values. All hypotheses were tested using OLS regression. The dependent variables (coworker support, supportive work-family culture, work-to-family conflict, family-to-work conflict) were regressed on the predictor variables and the interaction effects. Specifically, the control variables of age, tenure, hours worked per week, job autonomy, job demand, gender of the supervisor, education level, being a single parent, and children at home were entered as the first step in each of the regression equations. The main effects of gender, percent women per occupation, and percent women per industry were entered as the second step for each regression equation, and the interaction effects of gender and percent women per occupation and gender and percent women per industry were entered as the last step in the regression equations. In the analyses of work-to-family and family-to-work conflict, supportive work-family culture was also included in the regression equation to control for its potential effect.

Table 1 Means, standard deviations, and correlations (women).
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Table 2 Means, standard deviations, and correlations (men).
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Given the correlation values of the data, tests for multicollinearity were conducted with each regression equation. A condition index and a variance inflation factor (VIF) were determined for the independent variables. Values above 30 on the condition index and ten on the VIF represent strong collinearity and indicate a potential problem with multicollinearity. Our values were safely below that range with a condition index of 24.8 for Hypotheses 1 and 2 and a condition index of 27.4 for Hypotheses 3 and 4. All VIF values were well below ten with the individual values ranging from 1 to 1.4.

Additionally, we ran each analysis twice since our hypotheses examined the direction for each gender as it related to the percent women per occupation and industry on the dependent variables, rather than merely the simple moderating effect of gender. Initially, gender was coded as 0 for men and 1for women. In this coding, significance in the main effects of percent women shows statistical significance for the direction of the effect for men. For the second run, the reverse coding of 0 for women and 1 for men was used so that the main effects would instead test for the direction of the effect for women. Significant interaction effects in both models demonstrate moderation of gender in the relationship.

Hypothesis 1 predicts that as the percentage of women in an occupation and industry increase women will report higher levels and men lower levels of coworker support. This was tested by regressing the dependent variable of coworker support on the predictor variables and the interaction effects. The control variables specified above were entered as the first step in the regression equation, the main effect variables of gender, industry composition, and occupation composition were entered as the second step in the regression equation, and the examined interaction effects were entered as the third step in the regression equation. Results provide partial support for this hypothesis. Gender does not moderate the relationship between percent women per occupation and coworker support, but gender significantly moderates the relationship between coworker support and percent women per industry (p < .05). Findings suggest that as the percentage of women in an industry increases, women perceive greater coworker support and men perceive slightly less coworker support (refer to Table 3 and Fig. 1).

Fig. 1
figure 1

Interaction effect of gender and percent women in the industry on coworker support.

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Table 3 Interaction of gender with percentage of women per occupational category and industry classification in predicting coworker support and supportive work-family culture.
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Hypothesis 2 predicts that as the percentage of women in an occupation and industry increase women will report higher levels and men lower levels of supportive work–family culture. This hypothesis was tested by regressing the dependent variable of supportive work–family culture on the predictor variables and the interaction effects. The control variables were entered as the first step in the regression equation, the main effect variables of gender, occupation composition, and industry composition were entered as the second step in the regression equation, and the examined interaction effects were entered as the third step in the regression equation. The findings are not significant for the interaction of gender and the percent women in an occupation, but the results do show that gender significantly interacts (p < .05) with the percent women per industry in predicting perceptions of supportive work–family culture (refer to Table 3). As the percentage of women working in an industry increases, women perceive higher levels of supportive work–family culture. Men’s perceptions of supportive work–family culture, on the other hand, remain constant irrespective of the percent women within the industry (refer to Fig. 2).

Fig. 2
figure 2

Interaction effect of gender and percent women in the industry on a supportive work–family culture.

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According to Hypothesis 3, as the percentage of women in an occupation and industry increase women will report lower levels and men higher levels of work-to-family conflict. This was tested by regressing the dependent variable of work-to-family conflict on the predictor variables and the interaction effects. The control variables, including family-supportive organizational climate were entered as the first step in the regression equation to control for their potential effects, the main effect variables were entered as the second step, and the examined interaction effects of gender and percent women per industry and gender and percent women per occupation were entered as the third step in the equation. Findings are not significant for this hypothesis (refer to Table 4); however, a nonsignificant trend is evident (p = .058) suggesting that as the percentage of women in an industry increases, the reported work-to-family conflict decreases for women and it increases for men (refer to Fig. 3).

Fig. 3
figure 3

Interaction effect of gender and percent women in the industry on work-to-family conflict.

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Table 4 Interaction of gender with percentage of women per occupational category and industry classification in predicting work-to-family conflict and family-to-work conflict.
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We expect based on Hypothesis 4 that as the percentage of women in an occupation and industry increase women will report lower levels and men higher levels of family-to-work conflict. This was tested by regressing the dependent variable of family-to-work conflict on the predictor variables and the interaction effects. The control variables, including family-supportive organizational climate were entered as the first step in the regression, the main effect variables of gender, industry composition, and occupation composition were entered as the second step in the regression, and the examined interaction effects were entered as the last step in the regression equation. Results support the interaction between gender and percent women per occupation as a significant predictor (p < .05) of family-to-work conflict (refer to Table 4). The interaction between gender and percent women per industry was not a significant predictor. The findings illustrate that as the percentage of women in an occupational category increases the reported family-to-work conflict decreases for women and slightly increases for men (refer to Fig. 4).

Fig. 4
figure 4

Interaction effect of gender and percent women in the occupation on family-to-work conflict.

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Discussion

The present study examines how the extent of occupational and industry sex segregation shapes the work-to-family conflict, family-to-work conflict, supportive work–family culture, and coworker support of men and women—questions that have rarely been explored in the empirical literature (Maume and Houston 2001). In doing so, we contribute to current research in four important ways. First, we bridge work–family and gender scholarship by using a gendered theoretical perspective to address these questions. Indeed by taking into account the structural variables of occupation and industry sex segregation we gain a more complete understanding of the gendered negotiation of the work–family terrain. Second, we contribute to a growing literature on the antecedents of family-to-work conflict, an often neglected facet of the work–family interface (Dilworth 2004; Stevens et al. 2007; Voydanoff 2005). Third, in predicting perceptions of supportive work–family culture and coworker support we address issues of key importance to many workers, as these variables are especially helpful for people balancing paid work and family life (Kossek et al. 2001, Thompson et al. 1999). Last, it is our hope that our analyses shed further light on the ways that the extent of occupational and industry sex segregation impact outcomes beyond pay and fairness in promotion (Glass 1990; Reskin et al. 1999).

We found that as the percentage of women in an industry increase women perceive more and men less coworker support, which provides compelling evidence that women are rewarded for working in industries with higher percentages of women while men are disadvantaged. This interpretation is consistent with previous work that highlights how people are sanctioned, in positive and negative ways, based on whether they comply with gender norms (Jacobs 1993; Kanter 1977; Kimmel 1993; Pierce 1995; Williams 1992). An alternative explanation is provided by relational demography, which suggests that people forge connections with those who are demographically similar to them (Tsui et al. 1992). The present study also found that as the percentage of women in an industry increases women report more supportive work–family culture, while men’s perceptions of this variable remain unchanged. This finding provides a nuanced response to Goodstein’s (1994) work which emphasized that while organizations are not more likely to adopt work–family initiatives as the percentage of women increased that organizations do try to strategically respond to the needs of their employees. One form this strategic response may take is creating a supportive work–family culture. The finding of men’s report of supportive work–family culture remaining steady is consistent with Cook’s (2008) work suggesting that women may be more cognizant than men of supportive work–family culture given the salience of family issues for women.

We found that as the percentage of women working in an occupation increases, women report less and men slightly more family-to-work conflict. We contend this is likely due to women encountering difficulties in the form of increased family-to-work conflict when they work in occupations with higher percentages of men. For example, it is possible that in such occupations, having family demands spill over into work is viewed as abnormal and hence its occurrence is likely to be visible to both the employee and their coworkers. The findings also demonstrated a nonsignificant trend (p = .058) of women experiencing less and men more work-to-family conflict as the percentage of women working in an industry increased. One explanation for this nonsignificant trend is that industries with higher percentages of women may be structured in ways that facilitate the combination of work and family roles. The fact that previous occupational research has found that predominantly female occupations are actually not characterized by lower job demands or greater flexibility (salient predictors of reduced work-to-family conflict), casts doubt on such an interpretation (e.g., Glass 1990). Further, the findings for men suggest that this interpretation may be misguided, as men report greater work-to-family conflict as the percentage of women in an industry increases. Hence this finding is likely not due to predominantly female industries being organized in ways that reduce work-to-family conflict. It is possible that men in such industries are also traversing gender norms in other arenas, such as increasing the time they devote to child-rearing and domestic labor, which might explain their higher levels of work-to-family conflict. Another explanation for men’s higher levels of work-to-family conflict in such industries is that discussions with female coworkers may serve to make the issues of work–family conflict more salient in their minds. We argue that the best explanation for the nonsignificant trend is that both men and women are rewarded for working in industries that have higher percentages of their own gender, as predicted by our theoretical perspective.

The present study is characterized by limitations that should be taken into consideration. First, although we were able to account for the gender of the supervisor and include employees’ perceptions of supervisory family support, we were unable to consider how different leadership styles may influence our outcome variables (Mills 1992). It is likely that certain leadership styles may help mitigate work-to-family or family-to-work conflict and enhance the creation of workplace cultures that are more supportive of employees’ family-related needs. Second, though we controlled for the level of education of the employees, we were not able to control for the education level required for specific jobs. It may be that women and men in sex-atypical jobs are over or under qualified and that this could influence how successful they are at balancing work and family life and how able they are to tap into coworker support networks at their place of employment. A third limitation is our lack of qualitative data which could further shed light on the actual gendered assumptions of workers and supervisors and how these shape the navigation of work and family life.

In general, our findings contradict previous research suggesting that men working in sex-atypical workplaces have few family obligations (Williams and Villemez 1993) and that men will be rewarded for working in sex-atypical occupations and industries. We argue that greater attention needs to be paid to the rich array of outcome variables for men crossing gender lines to work in female-dominated workplaces. Clearly, whether or not men are rewarded for this behavior depends on the outcome variable under consideration. Also, future research should consider measures of masculinity or femininity when examining the relationship between occupation and industry segregation and coworker support, supportive work–family culture, work-to-family conflict, and family-to-work conflict. We think this will provide a more direct test of the idea that women and men working in sex-atypical occupations and industries will be penalized for doing so because they are violating gender norms. For example, it would be interesting to determine if a man’s level of masculinity affects how likely he is to experience coworker support in a sex-atypical occupation. It would also be interesting to examine if a masculine woman working in a sex-atypical occupation would experience greater work-to-family conflict given others’ perceptions of her. This type of research would be able to delve more deeply into how the ways in which workers “do gender” shape their navigation of the work–family terrain (West and Zimmerman 1987). These types of inquiries, along with the present study, may allow for a much more nuanced understanding of the ways occupational and industry sex segregation affect the lives of men and women.