Gender disparity in pay, work schedule autonomy and job satisfaction at higher education levels.
Despite these historical gains in annual salary and educational attainment, reductions in gender wage disparity found in the 80's and 90's have begun to slow, if not stop (Blau & Kahn, 2007). According to previous research, women made 80 percent of men's annual salary, even when controlling for major and occupation choice in the years after graduation (Dey & Hill, 2007) and when examining comparable work across many different countries (OECD, 2011). This slowing momentum not only illustrates the ongoing need to address the gender pay gap as a modern concern, but also the role that factors of human capital, such as education level, may play in the gender pay gap. To further investigate this trend, we examined whether educational attainment predicts various job dimensions (i.e., attitudes, characteristics, and outcomes) differently for men and women. The study is a temporal comparison of 2002 and 2008 national samples of employees in the United States used to examine trends in job pay, job satisfaction, and work schedule autonomy. This research addresses the mixed findings on gender differences in job satisfaction, as well as work-life balance.
Explanations for the Gender Pay Gap
The gender pay gap has been examined from economic, sociological, and psychological frameworks (Stockdale & Nadler, 2013). Human capital theory suggests that supply-side variables, such as education level, enhance employees' professional experiences and abilities (Becker, 1964; Olson, 2013). In a meta-analysis of predictors of career success, human capital indicators (including education level) positively predicted pay and promotions across the career span (Ng et al., 2005). The human capital approach suggests that as women build their human capital, the gender pay gap will decline. As evidence, from 1970-1995, increases in women's labor force participation and job experience showed substantial decreases in the gender wage gap (Blau, 1998).
In response to human capital theories, social psychologists have offered competing explanations for gender disparities, creating a more complex and integrative approach to understanding gendered work outcomes in the United States (Tharenou, 2013). Human capital indicators do not explain the gender wage gap in its entirety (Blau, 1998). Moreover, theories based solely on human capital overlook the pervasive nature of factors, such as discrimination, that affect human capital variables (Lips, 2013). In response, human capital theorists have acknowledged the model's limitations, but point out the model's theoretical contributions, especially when combined with other psychological models (Olson, 2013; Stockdale & Nadler, 2013).
Despite these gains, the gender wage gap did not decrease in recent decades as much as it did from the 1970's to the 1990's (Blau & Kahn, 2006). Rather, the gender wage gap increased between 1995 and 2000 in multiple industries (U.S. General Accountability Office, 2001). Among highly paid, advanced positions, men have and still make substantially higher salaries, and receive more promotions and salary increases than women (Bertrand & Hallock, 2001; Blau & Khan, 2016; Lyness & Judiesch, 1999; Wood, Corcoran, & Courant, 1993). In 2012, women were earning 74.7 percent of men's salaries in business and financial operations occupations and 77.4 percent of men's salaries in education and health services occupations (Bureau of Labor Statistics, 2014). Although these studies involve women in higher paying jobs with higher education levels, the majority of these studies do not directly examine the relationship between human capital variables and pay. In utilizing education as a human capital variable, we examine these emerging trends in annual income, job satisfaction, and work schedule autonomy.
Gender Differences in Work Schedule Autonomy
In the current study, work schedule autonomy refers to the employee's perceptions of flexibility and control over when they work. For example, a working parent who can leave the workplace early for a parent-teacher conference to fulfill family obligations, and then return to work later in the evening to complete work obligations, likely has high work schedule autonomy. Commitments that compete for employees' time (i.e., work and family) and an inflexible work schedule can strain employees' resources and lead to work-family conflict (Greenhaus & Beutell, 1985). Work hours are positively related to work-family conflict among both men and women (Maume & Houston, 2001), suggesting that time at work detracts from time available for other commitments (Greenhaus & Beutell, 1985; O'Driscoll, Brough, & Kalliath, 2006). Work schedule autonomy, often provided by flexible scheduling policies, is considered an advantageous job facet because it allows employees time for fulfilling multiple roles (Gerkovich, 2006). Work environments that offer flexible scheduling produce benefits that include reduced workfamily conflict, higher job satisfaction, and lower turnover among both men and women (McNall, Masuda, & Nicklin, 2010). Flexible work hour policies are positively related to organizational commitment and job satisfaction among women, especially for those with family responsibilities (Scandura & Lankau, 1997).
Although work schedule autonomy can elicit positive job attitudes, it is also related to disadvantages unique to women's career advancement. The work environment can provide cues that emphasize the necessity for being physically present at work. Women in male-dominated work groups reported higher work-family conflict, whereas the group's gender composition did not predict men's work-family conflict (Maume & Houston, 2001). Women often feel that by utilizing work schedule autonomy, they are sacrificing career advancement opportunities (Almer, Cohen, & Single, 2003). Furthermore, women managers on flextime schedules were rated significantly lower in career dedication and advancement motivation compared to women on a non-flexible work schedule (Rogier & Padgett, 2004). These outcomes suggest that women face considerable occupational backlash for indulging in the flexibility provided by work schedule autonomy.
Gender Differences in Job Satisfaction
There have been mixed findings on gender differences in job satisfaction. One ambiguous trend in gender studies of job satisfaction is the "central paradox," (Kim, 2005) where women commonly report higher levels of job satisfaction than men in the face of lower pay, autonomy, and/or promotional opportunity (p. 667). This central paradox occurs cross culturally and among various job types (Bender, Donohue, & Heywood, 2005; Clark, 1997; Okpara, Squillace, & Erondu, 2005).
Applying the range-of-affect theory to the relationship between job facets and job satisfaction could explain these counterintuitive findings. Range-of-affect (Locke, 1976; Wu & Yao, 2006) proposes that individuals evaluate their level of satisfaction based on how well their jobs meet their expectations in a given facet. For example, if an individual values work schedule autonomy and also expects their job to possess a high degree of autonomy, they would experience high disaffection if the job did not meet this expectation. Work schedule autonomy would be considered a personally relevant job facet in this scenario due to its significant impact on satisfaction (McFarlin & Rice, 1992). Based on the different levels of relevance individuals place on various job aspects, employees may experience satisfaction with different aspects of their jobs. For example, men tend to value extrinsic aspects (pay and promotion) and women intrinsic aspects (flexibility and benefits). Gender differences in job satisfaction may be a reflection of differences in valued job facets. If women tend to find certain job facets more valuable than men, then ratings of job satisfaction would differ in corresponding ways.
Despite the progress made in female professional advancement, the pay gap between men and women in the United States has persisted. Gender differences in human capital variables, such as education, have been offered as a partial explanation for gender wage disparities (Stockdale & Nadler, 2013). If this is the case, women and men with similar educations would have similar earnings and related job outcomes. Although the extant research has often examined the gender pay gap at different career levels, this does not directly examine the predictive value of education as a human capital factor. Furthermore, educational attainment can be used to examine gender differences in job satisfaction and work schedule autonomy.
The interaction of education and gender will be examined using national samples of U.S. workers across all industries collected at two times (2002 and 2008). Broad gender differences in the U.S. on wages, perceptions of work schedule autonomy, and job satisfaction will be examined. More specifically, the interaction of gender and education will be examined: do women and men benefit in similar or dissimilar ways with higher levels of education? We propose the following hypotheses:
Previous research suggests women receive less pay (Lips, 2013) and are more likely to experience backlash for utilizing work schedule flexibility (Roger & Padgett, 2004), yet generally report more job satisfaction than men (Clark, 1997; Kim, 2005). To examine these counterintuitive findings, we will compare gender and job-related outcomes as predictors of job satisfaction.
Hypothesis 1: Regarding gender differences, women will report lower annual pay (Hypothesis 1a) and lower work schedule autonomy (Hypothesis 1b) than men. However, women will report higher job satisfaction than men (Hypothesis 1c).
Hypothesis 2: Regarding differences in educational attainment levels, employees at higher education levels will report higher pay (Hypothesis 2a), higher work schedule autonomy (Hypothesis 2b), and higher job satisfaction (Hypothesis 2c).
Hypothesis 3: There will be a significant interaction between gender and education level; the gap between men's and women's pay is expected to be greater at higher education levels than at lower education levels (Hypothesis 3a) and a larger gap between men's and women's work schedule autonomy favoring men will be found at higher education levels (Hypothesis 3b). However, the gap favoring women compared to men on job satisfaction will be greater at higher education levels (Hypothesis 3c).
Hypothesis 4: The trends found in 2002 and 2008 will be similar indicating stable gender based disparity.
2002 Sample. Data were drawn from the 2002 National Study of the Changing Workforce (NSCW), a representative sample (N =3500) of the U.S. workforce drawn once every five to seven years by Family and Work Institute, a non-profit research organization. Data were collected using a computer-assisted telephone interviewing (CATI) program. The sample for this study focused on full time salary earning workers in the private sector (N = 2322). The sample was 46% male and 54% female, average age 42 (SD = 11.6) working an average of 39.9 hours a week (SD = 5.4). In terms of working hours, 80% of the sample worked regular daytime shifts, with 11% working some form of flexible work schedule. A very strong majority of the sample, 97%, reported neutral to positive feelings towards their work schedule and 92% of the sample felt respected to some degree at work. In the sample, 81% were European Americans, 10% African American, 6% Hispanic, 2% Asian, and 1% other. Gender differences in the demographic variables are presented in Table 1.
2008 Sample. Our data in the 2008 sample were drawn according to the same methods as the 2002 sample. The sample was 49% male and 51% female, the average age was 46 (SD = 11.3) working an average of 44.1 hours a week (SD = 8.7). In terms of working hours, 81% of the sample worked regular daytime shifts, with 7% working some form of flexible work schedule (see Table 1). In the sample, 81% were European American, 9% African American, 6% Hispanic, 3% Asian, and 1% other, See Table 1.
2002 and 2008 Sample. For the purposes of this study, existing questions taken from the NSCW survey of the changing workforce (2002; 2008) were utilized as predictors including gender (i.e., male or female) and education level (i.e., High School, Some College, Bachelor's, or Graduate Degree). The primary outcome was pretax yearly earnings in dollars. Research using annual pay sometimes utilizes a logarithmic transformation due to extreme scores in the overall population. The NSCW sample data had already been adjusted for sampling bias and the subset of full time salary employed workers that were examined did not need their pay transformed for analysis. Additional outcomes included job satisfaction ("All in all, how satisfied are you with your job?" on a 1 not satisfied at all, to 4, very satisfied) scale, with higher numbers representing more satisfaction) and work schedule autonomy ("Overall, how much control would you say you have in scheduling your work hours?" on a 1 none, to 6, complete control, with higher numbers representing more autonomy).
2002 and 2008 Sample. The NSCW survey consists of approximately 600 items. Data were drawn from a national sample selected through stratified sampling and adjusted to be representative of national demographic averages based on recent U.S. Bureau of Labor Census statistics. Participants were contacted multiple times via telephone and were compensated from $20 to $75 for completing the survey. The response rate was above 50% and the adjusted sampling error was calculated by the Family and Work Institute at +/- 1%.
2002 A series of correlations were conducted to examine the relationships between the variables of interest: gender, annual pay, job satisfaction and work schedule autonomy. Additionally, the demographic variables of weekly work hours and age were also examined as potential control/covariates. Gender was significantly related to all the variables with the exception of age (see Table 2).
A MANOVA was conducted to examine significant mean differences between men and women by education level on the outcomes, Wilk's A = .91, F(5, 1382) = 27.16, p < .001, significant mean differences can be found in Table 2. Based on the MANOVA and the results of the correlations, a series of univariate ANCOVA's were conducted to add weekly work hours as a covariate to the hypothesized relationships; however, weekly work hours was not a significant covariate in any of the three analyses and its inclusion did not alter the results. Thus the hypotheses were tested using three 2 (Gender) X 4 (i.e., Education Level: High School, Some College, Bachelors Degree, or Graduate Degree) ANOVAs to examine the specific relationships indicated by the MANOVA on the 2002 sample. Assumptions were checked and met for each analysis. The ANOVAs supported the correlation findings (Table 2) regarding the main effect of gender. It was found that women (M = $34,986) had lower pay compared to men (M = $51.425; supporting H1a), and women (M = 3.28) had higher work schedule flexibility than men (M = 3.17; not supporting H1b) and women (M = 3.46) had higher levels of job satisfaction (M = 3.37; supporting H1c).
There was a significant interaction between gender and education level on pretax yearly salary, F(3, 1241) = 4.29, p = .005, Partial [[eta].sup.2] = .01. Overall, men reported higher earnings in general (M = $53,507) compared to women (M = $38,296), and this difference increased at most levels of education (partially supporting H2a). Men were paid more than women at all levels of education and the pay gap significantly increased from high school, to some college, to bachelor's degree. The difference in pay was less at the graduate degree level, but still substantial. The difference in pretax annual salary between men and women with a high school degree was $9,304, with some college education was $12,668, at the bachelor's degree level it was $23,921, and at the graduate degree level it was $19,393. These differences represent women making 66% to 73% of the salary of men with the same level of education. Simple main effects found that gender differences were significant at each level of education (p's < .01) and that each level of education was significantly different (p's < .01; see Table 3; supporting H3a).
It was also hypothesized that men would report higher work schedule autonomy than women, higher levels of education would be related to higher work schedule autonomy, and that the gender gap favoring men in work schedule autonomy would increase with educational attainment. There were not significant main effects of education (not supporting H2b). However, there was a significant interaction between gender and education level on work schedule autonomy, F(3, 2312) = 11.37, p< .001, Partial [[eta].sup.2] = .02. Simple main effect tests indicated that men with higher education attainment reported significantly greater work schedule autonomy than women with higher education (supporting H3b). Men with a high school education (M = 3.24, SD = 1.79) had significantly less work schedule autonomy than those with some college (M= 3.64, SD = 1.57) and those with a bachelor's degree (M= 4.02, SD = 1.42) or graduate degree (M = 4.22, SD = 1.42) had more control than either high school or some college (p's < 01). Women reported significantly more control than men at the high school education level (M = 3.58, SD = 1.81); however, women reported less control than men at the bachelor's degree level (M = 3.46, SD = 1.60), and graduate degree level (M = 3.48, SD = 1.78), p's <.01. Women did not differ from men at the some college level (M= 3.65, SD = 1.70) and women did not significantly increase their levels of control as they obtained more education (see Table 3).
It was also hypothesized that women would report higher job satisfaction than men and higher levels of education would be related to higher job satisfaction, and that the gender gap favoring men in job satisfaction would increase with educational attainment. There was no significant interaction between gender and education level on job satisfaction, F(3, 2312) = 1.74, p = .16 (not supporting H3c). However, there was a main effect of gender on job satisfaction, F(1, 2312) = 10.63, p = .001, Partial [[eta].sup.2] = .01. Unexpectedly, men reported lower levels of job satisfaction in general (M = 3.37, SD = .70) compared to women (M = 3.46, SD = .66). There was also a significant main effect of education on job satisfaction, F(3, 2312) = 5.79, p = .001, Partial [[eta].sup.2] = .01. Tukey post hoc tests determined a significant difference between graduate degree and all other levels of education (p's < .03). High school (M= 3.38, SD = .72) (supporting H2c), some college (M= 3.38, SD = .71), and bachelor's degree earners (M= 3.43, SD = .64) were all lower on job satisfaction than graduate degree earners (M = 3.55, SD = .57). Education did not interact with gender on job satisfaction; however, women were more satisfied than men, and those holding a graduate degree were more satisfied than those with less education.
2008 A series of correlations were conducted to examine the relationships between the variables of interest; gender, annual pay, and work schedule autonomy. Additionally, the demographic variables of weekly work hours and age were also examined as potential control/covariates. Gender was significantly related to all the variables with the exception of work schedule autonomy (see Table 4). Overall, correlational analyses found that women had lower weekly work hours and pay compared to men, and higher job satisfaction and were older than men. A MANOVA was conducted to examine significant mean differences, Wilk's [lambda] = .96, F(5, 877) = 6.97, p< .001, significant mean differences can also be found in Table 5.
Based on the MANOVA and correlations, ANCOVA's were conducted adding weekly work hours and age as covariates to the hypothesized relationships; however, weekly work hours and age were not significant covariates in any of the three analyses and their inclusion did not alter the results. Thus, the hypotheses were tested using three 2 (Gender) X 4 (Education Level) ANOVAs on the 2008 sample. Assumptions were checked for each analysis.
Hypothesis 1a stated that women would report lower salaries than men, higher levels of education would be related to higher pay (H2a), and that the gender gap favoring men in pay would increase with educational attainment (H3a). There was no significant interaction between gender and education level on pretax yearly salary, F(3, 887) = 0.68, p = .56 (H3a). However, there was a main effect of gender, F(3, 887) = 12.06, p = .001, partial [[eta].sup.2] = .01; women (M = $50,071) made less than men (M = $86,546) and this gender pay gap was strong and found at each level of education (H1a). The pay gap between men and women indicated that women made 52% to 70% of the salary of men with the same education level. There was also a main effect of education level, F(3, 887) = 5.08, p = .002, Partial [[eta].sup.2] = .02. Tukey post hoc tests (p's < .05) indicated that high school (M = $43,693) and some college (M = $49,476) were significantly lower than bachelor's (M = $78,701) and graduate degrees (M = $88,967), see Table 5 (H2a). Men were paid more than women at all levels of education, and the pay gap was statistically stable across education levels.
Hypothesis 2 (a, b, and c) stated that men would report higher work schedule autonomy than women, higher levels of education would be related to higher work schedule autonomy, and that the gender gap favoring men in work schedule autonomy would increase with educational attainment. There was not a significant difference between men and women on work schedule autonomy (H2a), but work schedule autonomy did increase with educational attainment (p < .001, H2b). However, there was a significant interaction between gender and education level on work schedule autonomy, F(3, 2284) = 4.58, p< .003, Partial [[eta].sup.2]= .01. Simple main effect tests indicated that men significantly gained in work schedule autonomy with education attainment. Men with a high school education (M = 3.24, SD = 1.83) did not differ from men with some college (M = 3.43, SD = 1.67), but both groups were significantly lower than men with bachelor's degrees (M = 3.96,SD = 1.58) and graduate degrees (M = 4.03, SD = 1.55) on work schedule autonomy (p's < 01). Women reported significantly more work schedule autonomy at the bachelor's level (M = 3.77, SD = 1.71), p's <.01, compared to any of the levels that did not significantly vary: high school (M = 3.32, SD = 1.83), some college (M = 3.48, SD = 1.72), and graduate degree level (M = 3.40, SD = 1.74). Men generally gained work schedule autonomy with greater education and women benefited from a bachelor's level education but not from a graduate degree (H2c). Men also reported a significantly higher level of job control at the graduate level of education (Table 5).
Hypothesis 3 (a, b, and c) stated that women would report higher job satisfaction than men, higher levels of education would be related to higher job satisfaction, and that the gender gap favoring men in job satisfaction would increase with educational attainment. There was a significant gender difference favoring men (p < .01, refuting H1c) and education did have a significant main effect on job satisfaction (p < .001, H2c). However, there was a significant interaction between gender and education level on job satisfaction, F(3, 2288) = 3.47, p = .01. Partial [[eta].sup.2] = .01 (H3c). Simple main effect tests indicated that women significantly gained in job satisfaction with educational attainment. Women with a high school education (M = 3.43, SD = .70) or a bachelor's degree (M= 3.39, SD = .68) had higher job satisfaction than those with some college (M = 3.28, SD = .75). Women's job satisfaction at the graduate degree level (M = 3.58, SD = .60) was significantly higher than the other levels of education (p's < 05). However, women had significantly lower job satisfaction than men, and men's job satisfaction was generally stable with greater education ( Table 5).
2002 and 2008 Analysis
A hierarchical stepwise multiple regression, entering gender, year (2002 or 2008), pay, and work schedule autonomy predicting job satisfaction in the first block, and gender interaction terms (with pay and work schedule autonomy) in the second block was utilized to further examine the relationship between the variables. With the exception of year, all predictors were significant, [R.sup.2] = .05, F(4, 3010) = 41.13, p < .001 (see Table 6). The largest predictor of job satisfaction was a positive relationship with work schedule autonomy ([beta] = .37); more work schedule autonomy resulted in higher job satisfaction. Gender had the expected relationship with women having higher job satisfaction compared to men ([beta] = .20) and pay was weakly positively related to job satisfaction ([beta] = .07). The interaction between gender and work schedule autonomy was also a significant negative predictor of job satisfaction ([beta] = -.22). Tests of simple slopes examined the nature of this relationship. The relationship between work schedule autonomy and job satisfaction was stronger among men [beta] = .08, [beta] = .18, t(1077) = 3.37, p = .001, compared to women B = .04, [beta] = .10, t(1052) = 6.08, p < .001. Although men and women experience more job satisfaction when they have more work schedule autonomy, this effect was stronger in men and there was no effect of year on these trends.
The fourth hypothesis was tested using three 2 (Gender) X 4 (Education Level) X 2 (Year) factorial analyses of variance (ANOVA) on the combined 2002 and 2008 sample (N = 4620). Assumptions were checked and met for each analysis and a Bonferroni correction was conducted to adjust for the inflation of Type I error rate due to running multiple tests, reducing the maximum acceptable alpha to claim significance to p < .016.
Hypothesis 4 predicted that there would be more disparity between the genders with higher levels of educational attainment in both the 2002 and 2008 samples. Year (2002 or 2008) did not significantly interact with education and gender on pretax yearly salary, F(3, 2128) = 0.32, p = .81, job satisfaction, F(3,4600) = 2.79, p = .04, or control of work schedule, F(3, 4596) = 1.66, p = .17. The sample taken in 2008 did not significantly differ in the differences found between gender and education level on yearly pay, job satisfaction, and work schedule autonomy from the 2002 sample. Although practical differences may exist between the 2002 and 2008 samples, the lack of statistically significant differences between samples demonstrates the same general trends between samples. In both samples, gender wage disparity increased with educational attainment. The trends for work schedule autonomy were also very similar in both samples. It should be noted that what represented a national sample of full time salary workers was substantially different (likely due to a severe downturn in the U.S. economy in 2008; Goldman, 2009) from 2002 to 2008, and yet gender differences in pay and work schedule control were very similar. This is a noteworthy similarity, as men were losing jobs at a higher rate than women during the 2008 economic downturn (Hagenbaugh, 2009).
Although in the United States "women today have rights and opportunities that their foremothers could only dream about" (Rudman & Glick, 2008, p. 180), the current study reiterates that the gender wage gap is an ongoing challenge. The gender pay gap persisted at higher levels of education across two national samples. Although education level was related to increases in salaries, this was more advantageous for men than for women. In both samples, gender wage disparity increased with educational attainment. The trends for work schedule autonomy were also very similar in both samples. It should be noted that what represented a national sample of full time salary workers was substantially different from 2002 to 2008, and yet gender differences in pay and work schedule autonomy were very similar.
In considering human capital as an explanation for the gender wage gap, these findings demonstrate that job outcomes are shaped by educational attainment. Educational attainment's positive relationship to pay and job satisfaction demonstrates the positive impact of human capital. However, the continuing pay gap and lower work schedule autonomy indicate that unexplained disparities between men and women were present in both samples. Educational attainment was advantageous to men's work schedule autonomy, but not women's. Perhaps women at higher education levels were feeling increased job and family pressures, and did not have the necessary work schedule autonomy for these roles. Organizations should reconsider the effectiveness of resources provided to female employees, as well as how employees perceive work-life support policies (Allen, 2001; Allen, French, Dumani, & Shockley, (2015; Kossek, Barber, & Winters, 1999). Schedule flexibility has historically been viewed as a women's issue, yet this study supports the "radical potential" (Gerkovich, 2006, p. 277) that it can have for all employees. Although the current study suggests work-life support policies and resources may be effective and accessible for men, it seems that substantial improvements are still needed for improving perceptions of work schedule autonomy among women (Maume & Houston, 2001). Interventions at various job and education levels could encourage women's career advancement.
In the current study, women reported higher job satisfaction than men. Clark (1997) considered the gender differences in job satisfaction a "transitory phenomenon," (p. 365), where these differences can narrow as women's workforce participation and pay levels increase. Overall, the current study's findings of gender and education level on job satisfaction support this assertion. Work schedule autonomy predicted job satisfaction more than pay did, yet women reported lower work schedule autonomy than men.
Interestingly, the relationship between work schedule autonomy and job satisfaction was stronger for men than women. Considering range-ofaffect theory, the have-want discrepancy for work schedule autonomy appears to be especially salient for men's job satisfaction. In a predominantly female sample, perceived control was a strong determinant of job satisfaction (Thomas & Ganster, 1995). Comparatively, the current study demonstrated that work schedule autonomy predicts job satisfaction for both genders. Considering that pay did not significantly predict job satisfaction, this finding builds on the advantages of work-family support policies and is a key practical implication. Given that the measure of work schedule autonomy focused on perceptions rather than actual policies, further research is needed to determine what contributes to perceptions of work schedule autonomy.
Limitations and Future Research
Simultaneously a limitation and a point of interest are the years the samples were collected. The 2008 sample is markedly different from the 2002 sample. The yearly salary variable used in both samples was a measure of pretax yearly salary of the individual's primary job. Over half of the full-time private sector salary workers in the 2008 sample did not report this value.
This study was limited by using archival data sets collected in 2002 and 2008. Job satisfaction was measured with a single question using a 4point scale, and work schedule autonomy was measured with a single 6point item. The archival data set provided large representative samples of United States workers, but there were limitations to the questions asked and the data collected. It should also be noted that there is possible range restriction in some of the data collected. In the 2002 sample, 97% reported positive feelings towards their work schedule, which may have affected both job satisfaction and work schedule autonomy. Further research could examine these variables more extensively, perhaps in conjunction with family responsibilities and work-life balance. Additional measures of job experiences (e.g., supervisor support, job security) could also be included to compare predictors of men and women's job satisfaction. The job's context should also be considered when examining pay and job satisfaction discrepancies. The predominant gender of the occupational fields (e.g., women as nurses, men as engineers) may elucidate other mediating factors contributing to gender wage discrepancies.
In conclusion, this study demonstrates that gender disparity in pay, work schedule autonomy, and job satisfaction may not be solely explained by differences in the human capital factor of education. Although advances in women's education have helped increase women's workforce participation in the U.S., progress in narrowing the gender pay gap continues to stall. Bringing gender equality to the workplace is a multifaceted endeavor, which requires examining the similarities and differences in men and women's work experiences.
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Nadler, J. T. (1) Voyles, E. C. (2), Cocke, H. (1), & Lowery, M. R. (3)
(1) Southern Illinois University Edwardsville
(2) Northern Illinois University
(3) Eli Lilly
Author info: Correspondence should be sent to: Dr. Joel T. Nadler, Department of Psychology, Southern Illinois University, Edwardsville firstname.lastname@example.org
TABLE 1 Gender Demographic Differences in the 2002 & 2008 Samples 2002 2008 Men Women Men Women Age M = 42.64 M = 42.45 M = 46.53 M = 47.531 Hours (Weekly) M =39.35 M =35.431 M =43.37 M = 37.791 Work Schedule Daytime 76.5% 82.2% 79.1% 82.8% Evening/Night 7.0% 5.6% 6.6% 6.0% Rotating 7.8% 7.2% 6.2% 5.3% Flexible 8.8% 5.0% 7.9% 5.9% Education High School 29.6% 23.9% 23.1% 20.1% Some College 32.2% 33.0% 29.3% 33.9% Bachelors 23.1% 28.3% 26.9% 27.2% Graduate Degree 15.2% 14.8% 20.7% 18.8% (1) Significant difference, p < .01 TABLE 2 2002 Sample Gender Differences 1. 2. 3. 4. 1. Gender (1) -- 2. Age -.01 -- 3. Weekly Work Hours -.21 * .04 * -- 4. Yearly Salary (pay) -.26 * .16 * .26 * -- 5. Job Satisfaction (2) .05 ** .18 * .01 .11 * 6. Work Schedule autonomy (3) .04 * -.09 * .11 * -.16 * 5. Men (M) Women (M) 1. Gender (1) 2. Age 42.03 42.23 3. Weekly Work Hours 39.63 36.78 4. Yearly Salary (pay) $51,425 $34,986 5. Job Satisfaction (2) -- 3.37 3.46 6. Work Schedule autonomy (3) -.25 * 3.17 3.28 * = p<.05, (1) coded men = 1 and women = 2, (2) coded 1 to 4 with higher numbers equaling more satisfaction, (3) coded 1-6 with higher numbers equaling more work schedule autonomy. TABLE 3 2002 Interactions between Gender & Education on Pay & Work Schedule Autonomy Education High Some Bachelors Graduate School College Degree Degree (M) (M) (M) (M) Pay Men $34.197 $43.718 $67.699 $72,033 Women $24.893 $31.050 $43,778 $52,640 Women's % of Men's Salary 73% 71% 66% 73% Work Men 3.24 3.64 4.02 4.22 Schedule Autonomy (1) Women 3.58 3.65 3.46 3.48 (1) coded 1-6 with higher numbers equaling more work schedule autonomy. TABLE 4 2008 Sample Gender Differences 1. 2. 3. 4. 1. Gender (1) -- 2. Age .06 ** -- 3. Weekly Work -.18 * -.02 -- Hours 4. Yearly Salary -.13 * .07 * .11 * -- (pay) 5. Job Satisfaction (2) .06 * .10 * .01 .09 * 6. Work Schedule -.04 .02 ,07 * -.13 * autonomy (3) Women 5. Men (M) (M) 1. Gender (1) 2. Age 45.87 46.33 3. Weekly Work 45.94 43.53 Hours 4. Yearly Salary $86,87 $49,968 (pay) 6 5. Job Satisfaction (2) -- 3.44 3.46 6. Work Schedule .14 * 3.84 3.52 autonomy (3) * = p< .05, (1) coded men = 1 and women = 2, (2) coded 1 to 4 with higher numbers equaling more satisfaction, (3) coded 1-6 with higher numbers equaling more work schedule autonomy. TABLE 5 2008 Interactions between Gender & Education on Pay, Work Schedule Autonomy, & Job Satisfaction. Education High Some Bachelors Graduate School College Degree Degree (M) (M) (M) (M) Pay Men $50,316 $62,733 $104,662 $107,231 Women $35,127 $38,186 $54,422 $65,855 Women's % of Men's Salary 70% 61% 52% 61% Work Men 3.24 3.43 3.96 4.03 Schedule Women 3.32 3.48 3.77 3.40 Autonomy (1) Job Men 3.54 3.48 3.47 3.52 Satisfaction (2) Women 3.43 3.28 3.39 3.58 (1) coded 1-6 with higher numbers equaling more work schedule autonomy. (2) coded 1 to 4 with higher numbers equaling more satisfaction, TABLE 6 Multiple Regression Examining Gender, Pay, & Work Schedule Autonomy on Job Satisfaction. Predictor of Job Satisfaction B SE B [beta] Gender (1) .26 .06 .20 Pay .052 .00 .07 Work Schedule Autonomy (3) .15 .02 .37 Gender X Work Schedule Autonomy -.05 .01 -.22 Predictor of Job Satisfaction Significance Gender (1) t(3012) = 4.25, p< .001 Pay t(3012) = 3.99, p< .001 Work Schedule Autonomy (3) t(3012) = 6.43, p< .001 Gender X Work Schedule Autonomy t(3012) = -3.18, p= .001 (1) coded men = 1, women = 2, (2) adjusted to units of $100,000, (3) coded 1-6 with higher numbers equaling more work schedule autonomy.
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|Author:||Nadler, J.T.; Voyles, E.C.; Cocke, H.; Lowery, M.R.|
|Publication:||North American Journal of Psychology|
|Date:||Nov 1, 2016|
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