my reseach question is: How does achieving a bachelor’s degree (higher Education) assist with job fulfillment? Your paper should have an introduction paragraph that Includes your thesis sentence, and
Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 86 Full -Range Leadership as a Predictor of Extra Effort in Online Higher Education : T he Mediating Effect of Job Satisfaction Donald E. Barnett, Ed.D. Grand Canyon University Abstract Online higher education has rapidly expanded in the United States and displays a great opportunity for growth. Coupled with the growth of e-learning is the need for adjunct faculty to satisfy the need for additional online classes . Despite the importance of online adjunct faculty, little research has been performed to determin e their work experiences . This quantitative, correlational study investigated the predictive relationship between the perceived use of transformational, transactional, and laissez -faire leadership behaviors on the extra effort of adjunct faculty who facili tate online classes at a for -profit university in the United States . In a further investigation, the researcher investigated the variable of j ob satisfaction to determine if it mediated the relationship between leadership style and extra effort. The resear cher used the Multifactor Leadership Questionnaire and Spector’s Job Satisfaction survey to collect data used in inferential analysis. The researcher performed a stepwise multiple regression and a Baron and Kenny mediation analysis to answer the research q uestions. The results showed perceived transformational leadership behaviors displayed a statistically significant positive predictive relationship with extra effort, and job satisfaction was a partial mediator between the relationship of transformational leadership and extra effort. The results suggest transformational leadership is beneficial to the extra effort put forth by the sample of adjunct faculty who teach online classes. Introduction The workforce in higher education has shifted over the past few decades. At one time , the faculty of institutions of higher education were primarily tenured or tenure -track. Presently, faculty in United States post -secondary education are primarily adjunct, non -tenure -track, instructors (Eagan, Jaeger, & Grantham, 2 015). Kezar (2012) observed that 75% of all new hires at universities in the United States were part -time, adjunct faculty, and this number is steadily increasing (Gilpin, Saunders, & Stoddard, 2015) . The increased u se of adjunct faculty coincides with an increase of online class offerings. In the United States, e nrollment in online classes exceeded 5.8 million students in 2014, with 2.85 million students enrolled exclusively in online courses (Allen & Seaman, 2016). The increased demand for online educatio n has exceeded the capabilities of full time, tenured faculty (Caruth & Caruth, 2013) , and increased the demand for adjunct faculty to facilitate online offerings. Despite the increased employment of adjunct faculty to facilitate online courses , there is a lack of r esearch investigating online adjunct effectiveness (Datray, Saxon, & Martirosyan, 2014) . Moreover, there is a specific lack of research on the job satisfaction of adjunct, and particularly adjunct faculty who teach online courses (Rich, 2015). Cu rrently, there is a dearth of research investigating the outcomes of perceived administrative leadership on online adjunct faculty extra effort. This lack of research is notable because online adjuncts are relatively new to higher Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 87 education. Understandin g their work experiences may provide information that can be used to design leadership development programs for university administrators. The purpose of this paper is to address this gap in knowledge and investigate the predictive relationship between the administrative use of Full -Range Leadership, as percei ved by adjunct faculty who facilitate online courses , and the perceived extra effort offered by the same online adjunct faculty. Additionally, the researcher investigated the mediating relationship of job satisfaction on any perceived overall leadership style that displayed a predictive relationship with online adjunct faculty extra effort. Adjunct faculty members , despite their importance, typically do not receive adequate support from university admi nis trators (Kezar, 2013a) . A typical adjunct has inadequate opportunities for advancement, and seldom receives an increase in salary . Universities generally do not offer health insurance to adjunct faculty, and r etirement benefits are extremely limited. Ad dit ionally, adjuncts seldom have influence in university policy . Universities employ adjuncts at a considerable cost savings because they are remunerated at roughly one -third the salary of tenure d, or tenure -track, faculty (Halcrow & Olson, 2008 ; Kezar, 20 13b ; Morton, 2012). Irrespective of the increasing importance of adjunct faculty, universities typically do not nurture adjuncts in the same manner as tenure -track faculty. Generally, adjuncts are detached from their full -time counterparts (Webb, Wong, & H ubb al, 2013; Dailey -Hebert, Mandernach, Donnelli – Sallee, & Norris, 2014; Ott & Cisneros, 2015), their university , and department (Benton & Li, 2015). Adjuncts who teach online classes especially experience this disconnect, (Benton & Li, 2015), and adjunct fac ulty typically depend on other adjunct members of faculty for encouragement (Rich, 2015). Given these circumstances, it is important to discover what perceived leadership behaviors encourage online adjunct faculty members to go beyond expectations and give extra effort in the performance of their job duties. Literature Review The theoretic al foundation for this research wa s the Full -Range Leadership Model (FRLM). The FRLM is comprised of three distinct styles of leadership: transformational leadership, transactional leadership, and laissez -faire leadership. Each of these styles of leadership is divided into individual dimensions, which allows for a thorough investigation of most behaviors demonstrated by leaders (Avolio & Bass , 2004) . Researchers have u sed the FRLM extensively in the exp loration of perceived leadership behaviors in organizations , and it is one of the best -conceived and most validated leadership models . Transfor mational L eadership . Transf ormational leadership encourages “performance bey ond expectations” from subordinates (Bass, 1985) . Bass (1985), who expanded on the work of Burns (1978), stated transformational leadership increases subordinate motivation and willingness to exceed expectations by addressing follower needs and fostering t he values and ideals of the leader and organization. Consequently, followers strive to exceed expectations and give extra effort in the performance of their duties. Transformational leaders go beyond satisfying the basic needs of their followers by awakeni ng and fulfilling their subordinates ’ higher order needs , which encourages and arouses individuals to achieve their highest potential (Burns, 1978). Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 88 Perceived t ransformational leadership behaviors have demonst rated a positive relationship with employee p erfo rmance (Tham rin, 2012), and enhancing the job satisfaction of university faculty in online for -profit and traditional public universities in the United States (Barnett, 2017; Bateh & Heyliger, 2014) . Avolio and Bass (2004), in their modification of the FLR M , divided transformational leadership into five dimensions. Idealized influence . A leader’s demonstration of high ethical and moral standards exemplifies idealized influence . Leaders who are perceived as using idealized influence do not seek persona l gai n (Northouse, 2013), and are a focus of imitation and respect from their subordinates (Bass & Riggio, 2006). Bass and Avolio (1994) suggested followers might desire to emulate their leaders and identify with them because of a leader’s perceived dedica tion to ethical and moral conduct. Stadelmann (2010) found idealized influence was a significant predictor of follower extra effort. Avolio and Bass (2004) separated idealized influence into two distinct behaviors: behavioral and attributed, with behaviora l den oting how followers perceive the leader ’s ethical and moral behaviors , and attributed denoting the overall perceptions of the leader ’s ability to lead . Inspirational motivation. Leaders use inspirational motivation by effectively communicating high expect ations. They motivate and inspire subordinates by demonstrating enthusiasm and optimism about the organization’s future (Northouse, 2013). Leaders convey a promising vision of the future and motivate their followers to be dedicated to the vision of t he org anization (Avolio & Bass, 2004). Inspirational communication is a primary aspect of inspirational motivation (Avolio, Bass, & Jung , 1999). Intellectual stimulation. Intellectual stimulation consists of encouraging subordinates to exhibit innovative behavio rs, express creativity, and do their utmost to exhibit performance that exceeds expectations (Northouse, 2013). Leaders provide challenging assignments and encourage problem solving to formulate new ways of thinking. Leaders never criticize their s ubordina te’s ideas. Rather, they encourage independent thought and creative approaches that facilitate the innovation in the completion of job tasks (Avolio & Bass, 2004). Individualized consideration. A leader acts as a mentor and coach to develop their follower s to their fullest ability . Leaders who exhibit individualized consideration actively and effectively listen to their followers, express encouragement, frequently interact with their subordinates, and offer emotional and social support when needed (Northou se, 2013). Balyer (2012) observed individualized consideration is a behavior that makes a follower feel unique and appreciated. Transactional Leadership. Burns (1978), inspire d by the 1947 work of Max Weber, initially formed the Transactional L eadership Theory. Transactional leaders use praises, rewards, and promises that promote self -interest to motivate their followers to achieve organizational goals (Burns, 1978). Leadership strictly defines a ll job dutie s, benefits are clearly stated, and dis ciplinary codes are strictly enforced (Bass & Avolio, 1994). Transactional leadership is Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 89 composed of three dimensions: contingent rewards, management -by -exception (active), and management -by -exception (passive). Avolio and Bass (2004) later moved managemen t-by – exce ption (passive) to laissez -faire leadership for measuring leadership perceptions with the Multifactor Leadership Questionnaire. Contingent r eward. As the name implies, contingent reward is based on exchanges, or agreements, between leader and fo llower tha t denote rewards for accomplishing the agreed upon work, and punishments for substandard performance (Bass & Riggio, 2006). Contingent reward is derived from an agreement between two individuals, or parties, that sets forth a contract that design ates an ex change of currency, or other item of value, for a specific action (Burns, 1978). Contingent reward largely uses self -inter est as a method of motivation, and leadership clearly communicates all individual goals and organizational expectations to t he employe e (Bass, 1997). Bass (1985) observed contingent rewards foster follower confidence and reinforce performance expectations. Management -by -exception (active) . Bass (1997) maintained l eaders who practice management -by -exception (active) inform thei r followers of all organizational policies and goals, and communicate clear individual expectations. Leaders actively monitor their employees work, and take appropriate action before there is a v iolation of company policy or deterioration in the quality of the work. Managers pay close attention to employee performance and are quick to take corrective action when needed. Management -by -exception (passive). Bass (1997) observed management -by -exception (passive) differs from the active form because the leader only makes a curative action after a problem occurs or an employee’s work becomes substandard. Managers typically use n egative reinforcements , such as negative feedback, criticism, punishment, or some other form of correction in this dimension of leadersh ip (Northous e, 2013). As noted earlier, Avolio and Bass (2004) changed management -by -exception (passive) to a dimension of laissez -faire leadership for measuring leadership perceptions. Laissez -faire Leadership. Bass and Riggio (2006) stated laissez -faire leadership, in the managerial context, involves the absence and avoidance of any form of leadership. Laissez -faire leadership differs from manag ement -by -exception (passive) in several ways. A laissez -faire leader does not act when a correction is required . They do n ot provide necessary feedback, offer aid , or develop their followers in any way (Northouse, 2013). Laissez -faire leaders avoid acting and shirk responsibility. They are inactive, indifferent, uninfluential, inattentive, and absent when their pr esence is re quired by their followers (Bass, 1990). Laissez -faire leadership behaviors are still perceived in some managers (Bateh & Heyliger, 2014), but seldom observed in entire organizations (Bass, 1990) . Extra Effort. Selt zer and Bass (1990) observ ed extra eff ort entails employee behaviors that benefit the organization, which go beyond one’ s normal job expectations . Locke, Shaw, Saari, and Latham (1981) asserted extra effort represented an individual’s inner willingness to devote extra energy and ti me to achiev ing the goals of the organization. Similarly, Morris (2 009) defined extra effort to be when an employee voluntary gives effort , intensity, and time that goes beyond expectations. Avolio and Bass (2004) stated extra effort involved the leader’s capability Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 90 to inspire their follow ers to try harder, surpass management expectations , and foster their aspiration to succeed. Bass (1990) stated individuals would give extra effort for leaders who exhibit transformational leadership behaviors. Transactiona l leadership and passive management -by -exception, according to Bass (1990) , are less effective in encouraging extra effort on the part of subordinates . In agreement with Bass , Stadelmann (2010) found transformational leadership was a significant predictor of follower extra effort. Extra Effort and Job Satisfaction. Several theories have been set forth to explain extra effort. The expectancy theory (Vroom, 1964) stated individuals expend effort in proportion to the rewards they expect to receive. Moreover, the expectan cy theory states leaders must attempt to understand their employees’ “valence of possible outcomes and his expectancies regarding the consequences of different levels of effort for attaining them” (p. 192). Herzberg’s Motivator/H ygie ne Theory recognized ex trinsic motivators are inclined to promote greater job satisfaction, which in turns leads to an individual exerting extra effort. Likewise, the Reciprocity Theo ry (Batemen & Orga n, 1983) and Social Exchange T heory (Konovsky & Pugh, 1994 ) sugges ted individu als who exhibit high levels of job satisfaction will perform better than employees with lower levels of job satisfaction . Philbin (1997) discovered evidence suggesting job satisfaction is an important reason why individuals put forth extra ef fort in their jobs. Trofino (2003) found increases in job satisfaction led to increases in extra eff ort. In the educational context. Nguni, Sleegers, and Denessen (2006) discovered high levels of job satisfaction in teachers resulted in extra effort in hel ping their st udents. Given the theoretical and empirical evidence, it is prudent to conclude job satisfaction plays a significant role in extra effort. Research Questions Previous research has shown positive relationships between the perceived use of tran sformational leadership behaviors and employee extra effort (Stadelmann, 2010). Bass (1990) determined transformational leaders were effective in fostering employee extra effort. Avolio and Bass (2004) noted contingent reward, a dimension of transactional leadership, w as associated with the exchange of rewards for extra effort. Simila rly, Vroom (1964 ) observed individuals tend to expend effort in relation to the expected reward for their effort , which suggests transactional leadership might have a positive relationship to employee extra effort. Laissez -faire leadership, particularly passive management -by -exception, is generally ineffective in promoting extra effort (Bass, 1990). The reciprocity and social exchange theori es observed that job satisfaction is a n important v ariable in increased job satisfaction. Based on these observations , and the previous discussions regarding the dimensions of full -range leadership and employee extra effort, the study proposes the research question s and null hypotheses listed below : RQ1: T o what extent does the administrators’ transformational, transactional, and laissez – faire leadership style, as perceived by the online adjunct faculty who report to them, predict the e xtra effort of the same faculty? H1 0: There is no statisti cally signifi cant predictive relationship between the administrator’s transforma tional leadership style and extra effort. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 91 H2 0: There is no statistically significant predictive relationship between the administrator’s transac tional leadership style and ext ra effort. H30: There is no statistically significant predictive relationship between the administrator’s laissez -faire leadership style and extra effort. RQ2: Does overall job satisfaction mediate the relationship between any overall leadership style th at displayed a predictive relationship with extra effort in this study and extra effort? H4 0: Overall job satisfaction does not mediate the relationship between any overall style of leadership that displayed a positive relationship with extra effort in th is study and extra effort. Method Design. To determine if administrative leadership behaviors were related to the extra effort of adjunct faculty who teach online classes, the researcher used a Pearson’s correlation to determine if there was a correlation between perc eived overall transformational, transactional, and laissez -faire leadership behaviors and online adjunct faculty extra effort . N ext, the researcher performed stepwise multiple linear regression s with overall transformational, transactional, an d laissez -fai re leadership as the predictor variables and extra effort as the criterion variable to determine if there was any significant predictive relationship between variables. Finally, the researcher conducted a Baron and Kenny mediation analys is to assess if ov erall job satisfaction mediated the relationship between any predictive overall leadership style and extra effort. The researcher performed t hree regressions t o determine whether the data supported mediating relationship. Four criteria must b e met for medi ation to be established, : 1) the independent variable must display a relationship to the dependent variable, 2) the independent variable must be related to the mediator variable, 3) the mediator variable must show a relationship to the depend ent variable w hile in the presence of the independent variable, and 4) the independent variable must cease to be a significant predictor of the dependent variable in the presence of the mediator variable (Baron & Kenny, 1986). Population. The sample for this study was taken from a population of approximately 8 00 adjunct faculty members at a large for -profit university in the Midwest U nited States. After Institutional Review Board ( IRB ) approval from the research site, t he population was sent an email that invited partic ipation in the study provided they had taught an online class within the past six months. The invitation gave directions to access the survey, which was hosted on an online survey site. Of the 8 00 adjuncts, 85 individuals responded to the su rvey invitation . Out of the 85 respondents , 77 completed the survey in its entirety . Given the large size of the university, anonymity concerns, and the fact that this research did not target a specific department within the university, it is impossible to know how many leaders were rated , or if more than one respondent rated an individual supervisor. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 92 Instrument s. The Multifactor Leadership Ques tionnaire 5x short (MLQ) (Avolio & Bass, 2004) was used to collect data on perceived leadership behaviors and ext ra effort. The M LQ measured the nine dimensions of the FRLM and extra effort using 39 questions measured on a 5 -point Likert -type scale. The MLQ used four questions each to measure perceptions of the nine dimensions of the FRLM: inspirational motivation, i ntellectual stim ulation, idealized influence (attributed), idealized influence (behavioral), individual consideration, contingent reward, management -by -exception (active), management -by -exception (passive), and laissez – faire. The MLQ also measured extra ef fo rt using three questions. To measure overall perceptions of transformational, transactional, and laissez -faire leadership, the individual dimensions of each leadership style were combined to create a higher order construct, as suggested by Bass, Avolio, Ju ng, and Berson (2003). Spector’s Job Satisfaction Survey (JSS) (Spector, 1997 ) was used to collect data on overall job satisfaction. The JSS used 36 questions to measure nine dimensions of job satisfaction on a 6 -point Likert -type scale. The job factors me asured include d perceptions of the nature of work, communication, operating procedures, coworker relationships, fringe benefits, contingent rewards, supervisio n, pay, and promotion potential . Per Spector (1997), the researcher summed the totals of all the individual dim ensions to create a higher order construct to measure overall job satisfaction . Validity . Per George and Mallery (2012 ), a Cronbach’s alpha value of 0.90 or more is considered excellent, 0.80 -0.89 is deemed good, 0.70 -0.79 is regard as satisfactory , 0.60 -0.69 is considered questionable, 0.50 -0.59 is poor, and below 0.50 is unacceptable. For this study, all constructs were d eemed acceptable (Table 1 ). Data Analysis Demographic questions were not used in this study. Instead, the researcher produced the foll owing table that displays the means, standard deviations, and Cronbach’s alpha for the populations perceptions of their direct superior’s use of transformational leadership, transactional leadership , and laissez -faire leadership, and their own extra effort , and overall job satisfaction (Table 1) . Significant findings fr om an analysis of the data showed the sample perceived transactional leadership as the most used style of leadership ( M = 2.87), followed by transformational leadership ( M = 2.85) , and laisse z-faire leadership ( M = 2.79). Avolio and Bass (2004) observed that for a variable to be viewed as used extensively, the mean should surpass M = 3, which none of the variables measured by the MLQ achieved. Per Spector (1997) a mean value o f 116.34 indicate d ambivalence towards job satisfaction; neither satisfied nor dissatisfied. Table 1. Measures of Central Tendency and Cronbach’s Coefficient Alpha (N = 77) Leadership Style M SD α Transformational leadership 2.85 0.84 0.95 Transactional leadership 2.87 0.65 0.69 Laissez -faire leadership 2.79 0.77 0.79 Overall job satisfaction 116.34 19.92 0.90 Extra e ffort 2.90 1.00 0.78 Note. M = Mean; SD = Standard Deviation Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 93 The research er performed a Pearson’s correlation to discover if there was a correlation between extra effort and perceived overall transformational, transactional, and laissez -fai re leadership (Table 2 ). Based on the results of the study, transformational leadership i s related to extra effort ( r = .59, p < .01). Transactional leadership is related to extra effort ( r = 0.37, p < 0.01). Laissez -faire leadership is related to extra effort ( r = -0.45, p < .01). Table 2 . Pearson’s Correlation with Four Variables Variabl e 1 2 3 Extra e ffort — — — Transformational leadership 0. 59** — — Transactional leadership 0. 37** 0.44** — Laissez -faire leadership -0.45** -0.65** -0.23* * p < .01 ** p < .05 In an examination of the predictive relationship betw een perceived overall leadership behaviors and extra effort, a stepwise multiple linear regression was calculated to predict extra effort based on the independent variables transformational leadership, transactional leadership, and l aissez -faire leadership (Table 3 ). A significant regression was found (F (1,75) = 39.74, p < .001), with an r2 of 0.35. The adjusted r-square value of 0.34 in dicated approximately 34% of the variability in the dependent variable of extra effort was predicted by the three indepen dent variables in the model. Partic ipants’ predicted extra effort was equal to 0.90 – 0.14 (Transformational Leadership). The squared semi -partial correlation for the predictor of transactional leadership, 0.35, indicated approximately 35% of unique varian ce on the outcome of extra effort could be attributed to the transformational leadership variable. Extra effort increased 0.14 points for every 1 -point increase in transformational leadership. Transformational leadership was the only significant predictor of extra effort (β = 0.59 , p < 0.01) . This suggests increases in transformational leadership are associated with increases in extra effort. Table 3 . Stepwise Multiple Regression Results for Extra Effort with Three Variables Variable B SE B β t Sig. Transformatio nal leadership 0.14 0.02 0.59 6.30 < 0.01 Transactional leadership 0.13 0.08 0.16 1.59 0.12 Laissez -faire leadership -0.08 0.08 -0.12 -0.92 0.36 Constant 0.90 0.33 — — — Model Summary: F = 39.744, p <.01 N = 77 R2 = .346 Adjusted R2 = .338 Note. Sig.= Significance ( p-value). Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 94 Lastly , since transformational leadership was the only variable to display a significant predictive relationship with extra effort, the researcher performed a Baron a nd Kenny mediation analysis to assess if overall job satisfaction mediated the relationship between perceived transformational leadership and extra effort (Table 4). The researcher conducted a regression with transformational leadership predicting extra ef fort. The regression of extra effort on transformational leadership was significant, (F(2, 75) = 39.74, p < .0 1). The results showed transformational leadership was a significant predictor of extra effort, (B = 0.14 ), indicating the first criterio n for med iation was met . The researcher then conducted a regression with transformational leadership predicting overall job satisfaction . The regression of overall job satisfaction on transformational leadership was significant, (F(2, 75) = 30.26, p < .01), showing transformational leadership was a significant predictor of overall job satisfaction, (B = 2.54 ). This indicated the second criterion for mediation was met. Next, the researcher performed a regression with transformational leadership and overall job sat isfaction predicting extra effort . The regression of extra effort on transformational leadership and overall job satisfaction was significant, (F(3, 74) = 43.03, p < .0 1), which suggested transformational leadership and overall job satisfaction accounted f or a significant amount of variance in extra effort. The individual predictors were examined one last time . The results found overall job satisfaction was a significant predictor of extra effort when transformational leadership was included in the model, (B = -0.03 ), indicating the third criterion for mediation was sati sfied. The results showed transformational leadership was a significant predictor of extra effort when overall job satisfaction was included in the model, (B = 0.21 ), indic ating the fourth c riterion f or mediation was not satisfied. Since criterion 1, 2, and 3 were met, while criteria 4 was not, partial mediation is therefore supported. Table 4. Regression Results with Overall Job Satisfaction Mediating the Relationship between Extra Effo rt an d Transformational Leadership Dependent Independent B SE t p Regression 1: Extra effort Transformational 0.14 0.02 6.30 < 0 . 01 Regression 2: Job s atisfaction Transforma tiona l 2.54 0.46 5.50 < 0. 01 Regression 3: Extra effort Transformational 0.21 0.02 9.25 < 0. 01 Job s atisfaction 0.03 0.00 5.53 < 0. 01 Results Null Hypothesis 1 H1 0: There is no statistically significant pred ict ive relationship between the administrator’s transforma tional leadership style and extra effort. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 95 The predictor of transformational leadership was statistically significant for the outcome of extra effort (β = 0.59, p < 0.01). Null Hypothesis 1 was rej ect ed. There is suff icient evidence to indicate there is a statistically significant predictive relationship between the perceived use of transformational leadership behaviors and extra effort in the sample. Null Hypothesis 2 H2 0: There is no statist ical ly significant predictive relationship between the administrator’s transactional leader ship style and extra effort. The predictor of transactional leadership was not statistically significant to the outcome of extra effort (p = 0.12). Null Hypotheses 2 wa s n ot rejected. There is not sufficient evidence to indicate there is a statistically significant predictive relationship between the administrators’ perceived transactional leadership behaviors and extra effort in the sample. Null Hypothesis 3 H3 0: Ther e i s no statistically significant predictive relationship between the administrator’s laissez -faire leadership style and extra effort. The predictor of overall laissez -faire leadership was not statistically significant to the outcome of extra effort ( p = 0.3 6). Null Hypotheses 3 was not rejected. There is not sufficient evidence to indicate there is a statistically significant predictive relationship between the administrators’ perceived laissez -faire leadership behaviors and extra effort in the sample . Null Hypothesis 4 H4 0: Overall job satisfaction does not mediate the relationship between any overall style of leadership that displayed a positive predictive relationship with extra effort in this study and extra effort. The results of a Baron and Ke nny med iation found job satisfaction was a partial mediator between the relationship of transformational leadership, the only overall predictor of extra effort in this study , and extra effort. Null Hypotheses 4 was rejected. There is sufficient evidence to ind ica te job satisfaction partially mediates the relationship between transformational leadership and extra effort. Discussion This study sought to determine if the use of transformational, transactional, and laissez – faire leadership , as perceived by th e sa mpl e, had a predictive relationship with the perceived extra eff ort of adjunct faculty who taught online classes. The secondary goal of this study was to determine if job satisfaction had a mediating effect between leadership style and extra effort. Th e resul ts of stepwise multiple regressions showed perceived transformational leadership behaviors were the only significant predictor of extra effort. These res ults suggested the use of Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 96 transformational leadership was beneficial to the extra effort put for th b y t he individuals in the sample, which addressed RQ1. This study confirmed the findings of Stadelmann (2010 ), who found perceived transformational leadership behaviors displayed a positive significant predictive relationship with extra effort . This st udy also confirmed the work of Bass (1990) , who found individuals put forth extra effort for leaders who are perceived to exhibit transformational leadership behaviors. Likewise, this research agreed with Bass ’s (1990) observation that perceived transforma tion al leadership behaviors were more beneficial to organizations than perceived transactional leadership behaviors. Due to the nature of this study, it is unknown how many supervisors were rated by the sample, or if more than one respondent rated an indiv idua l su pervisor. Regardless, the results suggest ed the adjunct faculty who taught online classes at the research site preferred their leader’s perceived use of transformational leadership. Not only did the perceptions of transformational leadership displa y a sign ificant positive relationship to extra effort, the results of the bivariate regression used in the mediation analysis showed perceived transformational leadership behaviors were also a positive predictor of overall job satisfaction. This is interes ting bec ause the sample rated transformational leadership as the second most used style of leadership (M = 2.85) at the research site, behind transactional leadership (M = 2.87) which the sample rated as the perceived most used leadership style . Laissez -faire lead ership displayed a mean value of 2.79 . The sample perceived all three styles of leadership used to a similar extent, even though only perceived transformational leadership behaviors displayed a positive relationship with extra effort. Moreover, the sam ple indicated ambivalence towards their job satisfaction , and displayed a marginal production of extra effort . This suggests that there may be a disconnect between leadership, or other organizational factors, and adjunct faculty who teach online course s at thi s university . Lastly, this study added to academic knowledge concerning the mediating effect of job satisfaction on the relationship between perceived transformational leadership behaviors and extra effort. This study found job satisfaction partia lly media ted the relationship between perceived transformational leadershi p behaviors and extra effort , which answered R2. The Reciprocity T heo ry (Bateman & Organ, 1983) and Social Exchange T heory (Konovsky & Pugh, 1994) suggested overall job satisfaction is a n imp ortant factor in the extra effor t of individuals. Given the finding that job satisfaction was a partial mediator between the relationship of the sample’s perceptions of their direct superior’s use transformational leadership and extra effort , this stu dy ag reed with, and adds to the knowledge on these two theories. Again, transactional leadership was perceived by the sample as the most used style of leadership by their superiors ( M = 2.87), which might help explain the apathy of the sample towards t heir job satisfaction ( M = 116), and their relatively average production of extra effort ( M = 2.90). Conclusion and Recommendations for Future Research The purpose of this study was to determine if there was a predictive relationship between the perceive d us e of transformational, transactional, and laissez -faire leadership behaviors by the sample’s direct superior and adjunct faculty extra effort, and to investigate the mediating effect of job satisfaction on the relationship between perceived transformat iona l lea dership behaviors and extra effort . The results showed perceived transformational leadership behaviors were a Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 97 significant predictor of extra effort. Additionally , the results showed job satisfaction was a partial mediator of the relationship betwe en percei ved transformational leadership behaviors and extra effort. These results are significant because they add to the limited amount of research on adjunct faculty who teach in an online environment. The study sample displayed ambivalence about thei r jo b sati sfaction and produced only a marginal amount of extra effort. In addition, the sample perceived transactional leadership, which did not display a significant relationship with extra effort, as the leadership style most used by their direct superi or. Percei ved t ransformational leadership behaviors were the sole signifi cant predictor of extra effort and displayed a positive relationship with job satisfaction. The high perceived use of transactional leadership might indicate leadership training in transf ormati onal leadership is warranted at the research site. Increases in the administration’s use of transformational leadership behaviors might increase extra effort and job satisfaction in the sample. The results of this research provided information th at may be beneficial in designing leadership development programs intended specifically for leaders who supervise online adjunct faculty. This st udy does have limitations. T his research study only investigated one school, which limits the conclusions to j ust one uni versity. While a quantitative study produced data that allowed for inferential statistics, the study is limited by not investigating the motives and insight a qualitative study may have provided ; therefore, future research could focus on a quali tati ve exam ination of this topic . Demographic questions were not used in this study, which would have allowed for a more thorough investigation of the sample. Future research could investigate if there are differences in leadership perceptions based on age , le ngth of employment, sex, or another demographic factor. The sample for this study was taken from a population of online adjunct faculty from a for -profit university. Similar research on the relationship between leadership and extra effort should also b e co nducted in the public and private sectors of higher education because the experiences of online adjuncts in these sectors might be different than their counterparts in the for -profit sector . Another recommendation for further research is that additiona l studies regarding online adjunct experiences be conducted in the for -profit sector of higher education , which have recently been the subject of controversy . Lastly, similar research in different countries is recommended. This research might provide insig ht i nto any cultural differences between samples . Future research investigating the perceptions of online adjuncts work experiences is warranted because of the limited amount of research on this population and their importance to the educational system . Onli ne adjun cts, while a relatively new phenomenon, play an important role in higher education. Understanding their work experiences and perceptions may help universit ies provide effective support for these often -overlooked employees. Moreover, providing p rope r suppor t for online adjuncts may, in turn, foster a better educational experience for students. The results of this research should be considered when designing leadership development programs for individuals who supervise online faculty. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 98 Acknowledge m ent I would like to acknowledge the excellent proof reading skills of my wife, Heather Barnett , without whose support this study would not have been possible. References Allen, I. E., & Seaman, J. (2016). Online report card – Tracking online education i n the United States . Retrieved from Online Learning Consortium: http://onlinelearningsurvey.com/reports/onlinereportcard.pdf Avolio, B. J., & Bass, B. M. (2004). Multifactor Leadership Questionnaire: Third Edition Manual and Sampler Set . Menlo Park, PA: M ind Garden I nc. Avolio, B. J., Bass, B. M., & Jung, D. I. (1999). Re -examining the components of transformational and transactional leadership using the Multifactor Leadership Questionnaire. Journal of Occupational and Organizational Psychology , 72 , 441 -462. Balyer, A. (2012). Transformational leadership behaviors of school principals: A qualitative research based on teachers’ perceptions. International Online Journal of Educational Sciences , 4(3), 581 -591. Barnett, D. (2017). Leadership and Job Satisfa ction: Adjun ct Faculty at a For -Profit University. International Journal of Psychology and Educational Studies , 4(3), 53 -63. http://dx.doi.org/10.17220/ijpes.2017.03.006 Baron, R. M., & Kenny, D. A. (1986). The moderator -mediator variable distinction in s ocial psycho logical research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology , 51 (), 1173 -1182. Bass, B. M. (1985). Leadership and performance beyond expectations . New York, NY: The Free Press. Bass, B. M. (1990). From transactional to transformational leadership: Learning to share the vision. Organizational dynamics , 18 (3), 19 -31. Bass, B. M. (1997). Does the transactional -transformational leadership paradigm transcend organizational and national bound aries. Ameri can Psychologist , 52 (2), 130 -139. Bass, B. M., Avolio, B. J., Jung, D. I., & Berson, Y. (2003). Predicting unit performance by assessing transformational and transactional leadership. Journal of Applied Psychology , 88 (2), 207 -218. http://dx.do i.org/10.103 7.0027 -9010.88.2.207 Bass, B. M., & Avolio, B. J. (1994). Improving organizational effectiveness through transformational leadership . Thousand Oaks, CA: Sage Publications. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 99 Bass, B. M., & Riggio, R. E. (2006). Transformational leadership . Mahw ah, NJ: Erlb aum. Bateh, J., & Heyliger, W. (2014). Academic administrator leadership styles and the impact on faculty job satisfaction. Journal of Leadership Education , 13 (3), 34 -49. http://dx.doi.org/10.12806/v13/i3/rf3 Batema n, T. S., & Organ, D. W. (1 983). Job sa tisfaction and the good soldier: The relationship between affect and employee “citizenship”. Academy of Management Journal , 4, 587 – 595. Benton, S., & Li, D. (2015). Professional development for online adjunct faculty: The Chair’s role. The Dep artment Chai r, 26 (1), 1 -3. http://dx.doi.org/10.1002/dch.30027 Burns, J. M. (1978). Leadership . New York, NY: Harper and Row. Caruth, G. D., & Caruth, D. L. (2013). Adjunct faculty: Who are these unsung heroes of academe? Current Issues in Education , 16 (3), 1 -10. Dailey -Hebert, A., Mandernach, B., Donnelli -Sallee, E., & Norris, V. (2014). Expectations, motivations, and barriers to professional development: Perspectives from adjunct instructors teaching online. Journal of Faculty Development , 28 (1), 67 -82. Datray, J. L., Saxon, D. P., & Martirosyan, N. M. (2014). Adjunct faculty in developmental education: Best practices, challenges and recommendations. Community College Enterprise , 20(1), 36 -49. Eagan, M. K., Jaeger, A. J., & Grantham, A. (2015). Sup porting the academic majority: Policies and practices related to part -time faculty’s job satisfaction. The Journal of Higher Education , 86 (3), 448 -481. http://dx.doi.org/10.1353/jhe.2015.0012 George, D., & Mallery, P. (2012). IBM SPSS Statistics 23 step b y step: A si mple guide and reference (12th ed.). Boston, MA: Pearson. Gilpin, G. A., Saunders, J., & Stoddard, C. (2015). Why has for -profit colleges’ share of higher education expanded so rapidly? Estimating the responsiveness to labor market changes. Ec onomics of E ducation Review , 45 , 53 -63. http://dx.doi.org/10.1016/j.econedurev.2014.11.004 Halcrow, C., & Olson, M. R. (2008). Adjunct faculty: Valued resource or cheap labor? Focus on Colleges, Universities, and Schools , 6(1), 1 -8. Kezar, A. (2012). Ex amining nont enure track faculty perceptions of how departmental policies and practices shape their performance and ability to create student learning at four -year institutions. Research in Higher Education , 54 (5), 571 -598. http://dx.doi.org/10.1007/s11162 -013 -9288 -5 Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 100 Kezar, A. (2013a). Departmental cultures and non -tenure track faculty: Willingness, capacity, and opportunity to perform at four -year institutions. The Journal of Higher Education , 84 (2), 153 -188. http://dx.doi.org/10.1353/jhe.2013.0011 Kezar, A. (2013b). Examining non -tenure track faculty perceptions of how departmental policies and practices shape their performance and ability to create student learning at four -year institutions. Research in Higher Education , 54 (5), 571 -598. http://dx.doi.org /10.1007/s11 162 -013 -9288 -5 Konovsky, M. A., & Pugh, S. D. (1994). Citizenship behavior and social exchange. Academy of Management Journal , 37 (3), 656 -669. Locke, E. A., Shaw, K. N., Saari, L. M., & Latham, G. P. (1981). Goal setting and task performance 1969 -1980. Psychological bulletin , 90 (1), 125 -152. https://doi.org/10.1037/0033 -2909.90.1.125 Morris, R. J. (2009). Employee work motivation and discretionary work effort. Unpublished doctoral dissertation. Brisbane Graduate School of Business, Brisbane. Morton, D. R. (2012). Adjunct faculty embraced: The institution’s responsibility. Christian Education Journal , 9(2), 398 -407. Nguni, S., Sleegers, P., & Denessen, E. (2006). Transformational and transactional leadership on teachers’ job satisfaction, o rganizationa l commitment, and organizational citizenship behavior in primary schools: The Tanzanian case. School Effectiveness and School Improvement , 17 (2), 145 -177. Northouse, P. (2013). Leadership: Theory and practice (6th ed.). Los Angeles, CA: Sage Publications. Ott, M., & Cisneros, J. (2015, September 21). Understanding the changing faculty workforce in higher education: A comparison of full -time non -tenure track and tenure line experiences. Education Policy Analysis Archives , 23 (90), 1 -28. http://d x.doi.org/10 .14507/epaa.v23.1934 Philbin, L. P. (1997). Transformational leadership and the secondary school principal. Unpublished doctoral dissertation, Purdue University, West Lafayette, IN. Rich, T. (2015). A worthy asset: The adjunct faculty and th e influences on their job satisfaction. To Improve the Academy , 34 (1/2), 156 -170. http://dx.doi.org/10.1002/tia2.20010 Spector, P. E. (1997). Job satisfaction survey, JSS page. Stadelmann, C. (2010). Swiss armed forces militia system: Effect of transfor mational lea dership on subordinates’ extra effort and the moderating role of command structure. Swiss Journal of Psychology , 92 (2), 83 -93. Journal of Leadership Education DOI:10.12806/V1 8/I1/R 6 January 201 9 RESEARCH 101 Thamrin, H. M. (2012). The influence of transformational leadership and organizational commitment on job satisfaction and employ ee performance. International Journal of Innovation, Management and Technology , 3(5), 566 -572. http://dx.doi.org/10.7763/ijimt.2 012.v3.299 Trofino, J. (2003). Power sharing: A transformational strategy for nurse retention, effectiveness, and ext ra effort. Nursing Leadership Forum , 8(2), 64 -71. Vroom, V. H. (1964). Work and motivation . New York, NY: Wiley. Webb, A. S., Wong, T. J ., & Hubbal, H. T. (2013). Professional development for adjunct teaching faculty in a research -intensive university: Engagement in scholarly approaches to teaching and learning. International Journal of Teaching & Learning in Higher Education , 25 (2), 231 -238. Author Biography Donald E. Barnett, Ed.D. , a past Presidential Management Fellow, is a manager for the Social Security Administration. He also serves on several dissertation committees at Grand Canyon University as a Content Expert on leadership , job satisfaction, and motivation. [email protected]
my reseach question is: How does achieving a bachelor’s degree (higher Education) assist with job fulfillment? Your paper should have an introduction paragraph that Includes your thesis sentence, and
Jo u rn al o f A pplie d P sy ch olo g y Does E d uca tio n al A tta in m en t P ro m ote J o b S atis fa ctio n ? T h e B it te rs w eet Tra d e-o ffs B etw een J o b R eso u rc e s, D em an d s, a n d S tr e ss Brit ta n y C . S olo m on , B oris N . N ik o la e v, a n d D ean A . S hep herd Onlin e F ir s t P u b lic a tio n , A pril 2 2, 2 021. h ttp ://d x.d oi. o rg /1 0.1 037/a p l0 000904 CIT A TIO N Solo m on , B . C ., N ik o la e v, B . N ., & S hep herd , D . A . ( 2 021, A pril 2 2). D oe s E d uca tio n al A tta in m en t P ro m ote Jo b S atis fa ctio n ? Th e B it te rs w eet T ra d e-o ffs B etw een Jo b R eso u rc e s, D em an d s, a n d S tr e ss. Jo u rn al o f A pplie d P sy ch olo g y . A dva n ce o n lin e pub lic a tio n . h ttp ://d x.d oi. o rg /1 0.1 037/a p l0 000904 RESEARCH REPORT Does Educational Attainment Promote Job Satisfaction? The Bittersweet Trade-offs Between Job Resources, Demands, and Stress Brittany C. Solomon 1, Boris N. Nikolaev 2, and Dean A. Shepherd 1 1Department of Management & Organization, Mendoza College of Business, University of Notre Dame 2Department of Entrepreneurship, Hankamer School of Business, Baylor University Education is considered one of the most critical human capital investments. But does formal educational attainment “pay off ”in terms of job satisfaction? To answer this question, in Study 1 we use a meta- analytic technique to examine the correlation between educational attainment and job satisfaction ( k=74, N=134,924) and find an effect size close to zero. We then build on the job demands-resources (JD-R) model and research that distinguishes between working conditions and perceived stress to theorizethat educational attainment involves notable trade-offs. In Study 2 we develop and test a multipath, two-stage mediation model using a nationally representative sample to explore this idea. We find that, while better-educated individuals enjoy greater job resources (income, job autonomy, and job variety),they also tend to incur greater job demands (work hours, task pressure, job intensity, and time urgency). On average, these demands are associated with increased job stress and decreased job satisfaction, largely offsetting the positive gains associated with greater resources. Given that the net relationship between education and job satisfaction emerges as weakly negative, we highlight that important trade-offs underlie the education –job satisfaction link. In supplemental analyses, we identify boundary conditions based on gender and self-employment status (such that being female exacerbates, and being self-employed attenuates, the negative association between education and job satisfaction). Finally, we discuss the practical implications for individuals and organizations, as well as alternative explanations for the education –jobsatisfactionlink. Keywords: education, job satisfaction, job demands-resources (JD-R) model, stress Supplemental materials: https://doi.org/10.1037/apl0000904.supp According to Aristotle, “the roots of education are bitter, but the fruit is sweet. ”Indeed, education is considered one of the most critical investments in human capital. Higher educational attainment can lead to more attractive job opportunities, greater labor force fl exibility, and more rewarding jobs ( Becker, 1964 ;Dickson & Harmon, 2011 ;Ng et al., 2005 ;Oreopoulos & Salvanes, 2011 ). Despite the potential for education to yield many bene fits, some studies point in the opposite direction. For example, educational attainment has been negatively associated with organizational com- mitment ( Angle & Perry, 1981 ;Morris & Sherman, 1981 ), job involvement ( Lounsbury & Hoopes, 1986 ), and organizational identi fication ( Gould & Werbel, 1983 ). Furthermore, higher levels of education and overquali fication (which is often based on educa- tion; McKee-Ryan & Harvey, 2011 ) can lead to burnout, turnover intentions, job search behavior, and voluntary turnover ( Erdogan & Bauer, 2009 ;Maslach et al., 2001 ;Maynard & Parfyonova, 2013 ). Of course, there are many indicators of what constitutes a “better ” (or “worse ”) job. We focus on job satisfaction because it is arguably the most studied construct related to “how people think about and relate to their work and jobs ”(Judge et al., 2017 , p. 357). Currently, it is not clear that more formally educated employees are more satis fied at work. To determine what we could glean about the relationship between the attainment of institutional education (hereafter, simply “educa- tion ”) and job satisfaction, we performed a meta-analytic technique on 74 independent samples since the year 2000 (Study 1). The link between education and job satisfaction had an effect size close to zero, but we reasoned there is likely more to the story than could be detected by a simple (albeit powerful) test of this correlation. Following Kluger and Tikochinsky ( 2001 , p. 419), we conducted a second study to highlight how “additional factors must be taken into account to understand the (commonsense) phenomenon-under study. ”Speci fically, we drew on the job demands-resources (JD-R) model ( Demerouti et al., 2001 ) to theorize that education is associ- ated with trade-offs that may help explain our meta-analytic finding (Study 2). We then tested a multipath, two-stage mediation model using a nationally representative, publicly available data set (see Appendix A), which improved the study ’s generalizability, trans- parency, and reproducibility (see Barnes et al., 2018 ). We found that better-educated individuals enjoy greater job resources (income, job Brittany C. Solomon https://orcid.org/0000-0002-0462-7535 Correspondence concerning this ar ticle should be addre ssed to Brittany C. Solomon, Department of Management & Organization, Mendoza College of Business, University of No tre Dame, Notre Dame, IN, United States. Email: [email protected] Journal of Applied Psychology © 2021 American Psychological Association ISSN: 0021-9010 https://doi.org/10.1037/apl0000904 1 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. autonomy, and job variety) and incur greater job demands (work hours, task pressure, job intensity, and time urgency), which explain job stress and job satisfaction in the hypothesized directions. The scripts we used for all analyses and data for Study 1 can be found on the Open Science Framework. 1 Study 1 To analyze the relationship between education and job satisfac- tion based on the extant literature, we first conducted a review to identify published articles related to job satisfaction since the year 2000. Speci fically, we used a Boolean search of the keywords “job satisfaction ”OR “work satisfaction ”OR “employee satisfaction ”in the following journals: Journal of Applied Psychology, Academy of Management Journal, Organizational Behavior and Human Deci- sion Processes, Personnel Psychology, Journal of Management, Journal of Organizational Behavior, Journal of Occupational and Organizational Psychology, Journal of Vocational Behavior, Jour- nal of Business and Psychology, Journal of Business Venturing, and Entrepreneurship Theory and Practice .2This review yielded 381 articles. Of those, 295 did not include education. Another 22 did not provide codeable information. Thus, our review covered 64 articles and 72 independent samples. We also included samples from two nationally representative data sets. 3Thus, our analysis is based on 65 manuscripts ( k=74 and N=134,924). Appendix B lists each study and provides coding, reliability, sample size, and effect size information. We note that none of the reviewed articles examined the direct (or indirect) relationship between education and job satisfaction; education was exclusively a control. According to Bernerth and Aguinis (2016) , education is the fourth most common covariate (at 23%) in job satisfaction studies. Because the effect of education varies across different groups (e.g., based on gender, race, etc.), and is thus likely to vary across studies, we used a random-effects model ( Hunter & Schmidt, 2004 ) and also corrected for observed correlations of the sampling error and measurement unreliability. We used the metafor software package in R ( Viechtbauer, 2010 ). As reported in Table 1 , the sample-size-weighted mean observed correlation corrected for unre- liability ( ˆ ¯ ρ ) spanned around zero ( ˆ ¯ ρ = .010, p=.58, 95% con fi- dence interval (CI) =[ .046, .026]). The Q test-statistic for homogeneity ( Q=283.32) had a p-value of .00, suggesting signi fi- cant heterogeneity between studies. The presence of heterogeneity can also be inferred from the I2, implying that close to 71% of the variability in the effect-size estimates is due to differences between studies. To explore this heterogeneity, we performed group analyses by examining whether there was a signi ficant difference between studies that used a single-item (global) versus multi-item (facet) job satisfaction measure and between studies that used a multi-item (global) versus multi-item (facet) job satisfaction measure. These tests ( Qb=.01, p=.92 and Qb=.75, p=.39, respectively) indi- cated that differences between these groups were statistically nonsigni ficant. Overall, the effect size for the relationship between education and job satisfaction neared zero. 4Because education was a covariate (vs. primary variable of interest) in the reviewed studies, we do not expect publication bias due to the “file drawer problem ”to be of concern. Study 2 In Study 2, we also expect to find an effect size close to zero. But, importantly, our aim is to further investigate the nature of the education –job satisfaction link by illuminating potential trade- offs associated with investments in education. Drawing on the JD-R model, we theorize that, relative to less-educated employees, the highly educated are more apt to attain jobs that provide them with greater resources but also involve greater demands. These working conditions tend to be associated with job stress and satisfaction (i.e., primary and secondary appraisals, respectively; Lazarus & Folkman, 1984 ,1987 ). As such, we expect that resources decrease stress and increase job satisfaction, while demands increase stress and decrease job satisfaction (see Figure 1 ). While the educated may bene fit in many ways, we test this trade-off story to provide one explanation for the near-zero effect that emerged in Study 1. In supplemental analyses, we explore gender and self-employment status as boundary conditions. Table 1 Education and Job Satisfaction: Meta-Analytic Findings Variable kN ¯r SDr ˆ ¯ ρ SDp 80% CV 90% CI % % ARTV Education 74 134,924 0.009 0.016 0.010 0.018 [ .034, 0.013] [ 0.046, 0.026] 39% Note .k=number of correlations meta-analyzed; N=total sample size; ¯ r =sample-size-weighted mean observed correlation; SDr =sample-size-weighted standard deviation of the observed correlations; ˆ ¯ ρ =sample-size-weighted mean observed correlation corrected for unreliability; SDp=standard deviation ˆ ¯ ρ ; 80% CV =80% credibility interval around ˆ ¯ ρ ; 90% CI =90% con fidence interval around ˆ ¯ ρ ; % ARTV =percent variance due to corrected artifacts. All analyses were conducted using random-effects meta-analyses based on the Hunter-Schmidt method (2004) to correct for observed correlations for sampling error and measurement unreliability. For single-item job satisfaction measures, we followed Wanous and Reichers (1996) and used α=.7. Because education was a demographic variable, and no reliability information was reported, we followed Ng et al. (2005) and used α=1. 1osf.io/ucyz2 . 2We initially searched for words in the title, abstract, and subject. This search often returned several thousand articles, most of which were irrelevantfor our purposes. Therefore, we narrowed the search to the title and abstract.For comparison with Study 2, and to keep the search manageable, we searched for articles published since 2000.3We also included the sample used in Study 2 and a sample from the British Household Panel Survey (from a prior version of this manuscript; fordetails, see Appendix B). The results did not change when excluded.4While Ng et al. (2005) found a weak, but positive relationship between education and job satisfaction, their meta-analysis consisted of studiespublished prior to 2004. Differences between their findings and ours (including the gender analysis in Study 2) may be due to changes in the economy (and a better educated female workforce), suggesting the impor- tance of considering the time period studied in future work on the education-job satisfaction link. 2 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Education and Job Satisfaction via Job Resources and Stress We first theorize that job resources help explain the education –job satisfaction link. Resources involve the rewards derived from one ’s work and the nature of the work itself ( Demerouti et al., 2001 ). Here, we focus on income, job autonomy, and job variety. All three resources are prominent in the JD-R model ( Bakker & Demerouti, 2007 ,2017 ;Demerouti et al., 2001 ) and its precur- sors (e.g., Hackman & Oldham, 1975 ;Karasek, 1979 ). Most notably, the potential to earn more money continues to be one of the top reasons people attend college ( Eagan et al., 2017 ). And higher education requires self-direction and involves acquiring a range of knowledge and critical thinking skills ( Arnold & King, 1997 ;Bowen, 1997 ). Thus, it should not be surprising that education is positively associated with income (e.g., Ng & Feldman, 2009 ;Ng et al., 2005 ), as well as job autonomy (i.e., discretion and control) and variety ( Oreopoulos & Salvanes, 2011 ;Ross & Reskin, 1992 ;Seybolt, 1976 ). Whether valued in their own right or because they enable the acquisition or protection of other resources ( Bakker & Demerouti, 2007 ;Hobfoll, 1989 ), income, autonomy, and variety likely operate as first-stage mediators between education and job satisfaction (with reduced job stress linking these resources with satisfaction). Indeed, while extrinsic rewards can diminish intrinsic motivation ( Deci et al., 1999 ), the job satisfaction of the highly educated may still be “bought ”via higher income. Pay satisfaction is a core component of job satisfaction ( Smith et al., 1969 ), and those with hi gher pay report being more satis fied ( Judge, Piccolo, et al., 2010 ). Earning more also enhances opportunities for work recovery ( Leana & Meuris, 2015 ;Saxbe et al., 2011 ), including more “pleasant ” off-job activities ( Bennett et al., 2018 ;Demerouti et al., 2009 ) that may improve work engagement ( Demerouti et al., 2012 ;ten Brummelhuis & Bakker, 2012 ) and help manage stressors and strain ( Geurts & Sonnentag, 2006 ; Sonnentag & Fritz, 2007 ). Job autonomy and variety may also yield higher job satisfaction due to having freedom [when to work, how to work, and what to do at work ( Karasek, 1979 ;Morgeson & Humphrey, 2006 )] and using a range of capabilities ( Fried & Ferris, 1987 ), respectively. Such resources create a sense of accomplishment and meaningfulness ( Hackman & Oldham, 1980 ). Autonomy and variety are also associ- ated with increased work engagement ( Christian et al., 2011 ;Mauno et al., 2007 ) and decreased burnout ( Demerouti et al., 2001 ;Hakanen et al., 2011 ). These insights are relevant because engaged employees are less likely to experience work stress ( Bakker et al., 2014 ,p.391) and tend to report higher job satisfaction (e.g., Rich et al., 2010 ). In contrast, burnout is inextricably linked to stress ( Pines & Keinan, 2005 ) and undermines job satisfaction ( Schaufeli & Buunk, 2002 ). Thus, it follows that autonomy and variety tend to lower stress and improve job satisfaction ( Fried & Ferris, 1987 ;Humphrey et al., 2007 ). Altogether, we expect: Hypothesis 1 :(H1a ) Education is positively associated with job resources (i.e., income, job autonomy, and job variety), ( H1b ) job resources are negatively associated with job stress, and ( H1c ) education is indirectly and positively associated with job satisfaction, as mediated by job resources and job stress. Education and Job (Dis)Satisfaction via Job Demands and Stress So far, our logic is consistent with the dominant narrative regarding educational investment —attaining higher education should yield a more satisfying job. But, from a JD-R perspective, it is also important to consider the role of job demands. These working conditions generally require sustained physical and/or psychological effort and may be costly ( Demerouti et al., 2001 ). Thus, as the second step in our theorizing, we argue that job demands operate as a countervailing mechanism to the resources pathway between education and job satisfaction. We focus on hours worked and qualitative demands that re flect task pressure, job intensity, and time urgency, all of which are prominent in the literature (e.g., Crawford et al., 2010 ;Kristensen et al., 2004 ). Valuable insights have been gained from distinguishing between challenge and hindrance demands (e.g., Podsakoff et al., 2007 ). However, the same working conditions do not have similar meanings for all employees ( Mazzola & Disselhorst, 2019 ;Webster et al., 2011 ). Thus, we do not make the challenge –hindrance distinc- tion here, but we do differentiate between demands and perceived job stress. Thus, consistent with Bliese et al. (2017) , we separate aspects of the job from the subjective reactions to those working conditions. Importantly, the highly educated tend to attain jobs in which they incur high-pressure, intense, and time-sensitive work ( Hakanen et al., Figure 1 Conceptual Model Linking Education, Job Stress, and Job Satisfaction Through Job Demands and Job Resources + Education Job Resources Job Stress + + + Job Demands Job Satisfaction + THE EDUCATION –JOB SATISFACTION LINK 3 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 2011 ;Judge, Klinger, et al., 2010 ;Wilk & Cappelli, 2003 ). Such job demands can become stressful ( Cavanaugh et al., 2000 ) and costly if employees cannot adequately recover from their work ( Bakker & Demerouti, 2007 ;Bennett et al., 2018 ;Sonnentag & Fritz, 2015 ). Relative to the less-educated, highly educated employees report more work-related rumination, anxiety, and stress ( Moen et al., 2013 ; Perko et al., 2017 ;Smith, 2001 ). When stress is too high, it threatens the attainment of personal goals and, thus, can reduce job satisfaction ( Begley & Czajka, 1993 ; Hendrix et al., 1985 ;Sullivan & Bhagat, 1992 ). As such, greater job demands incurred by the highly educated may also help explain the education –job satisfaction link. For example, hours worked can lead to increased stress ( Parker & DeCotiis, 1983 ;Perlow, 1999 )and decreased job satisfaction ( Clark & Oswald, 1996 ). Other demands may operate similarly: Negative experiences can result from having too much to accomplish with too little time [i.e., time pressure/work intensity ( Schaubroeck et al., 1989 )]. Some research indicates that similar demands inherently imply greater stress ( Motowidlo et al., 1986 ;Parker & DeCotiis, 1983 ) and predict lower job satisfaction ( Verhofstadt et al., 2007 ;cf. Judge et al., 2000 ;Judge, Klinger, et al., 2010 ;Ng & Feldman, 2009 ;Ng et al., 2005 ). In sum, education may undermine job satisfaction via increased job demands and perceived stress. We do not imply that the highly educated are generally worse off, but, concurrent with H1a –c, we expect: Hypothesis 2 :(H2a ) Education is positively associated with job demands (i.e., hours worked and qualitative demands), ( H2b ) job demands are positively associated with job stress, and ( H2c ) education is indirectly and negatively associated with job satis- faction, as mediated by job demands and job stress. Sample We tested our model using data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey —a nationally representative panel study of Australian households. The Australian Government funds the HILDA survey through the Department of Social Services. The survey collects information on many aspects of life, such as economic and personal wellbeing, labor markets, and family life. Like other major household panels, the coverage is broad and includes a core set of topics that appear in every wave and others that appear less frequently (see https://melbourneinstitute.unimelb .edu.au/hilda/for-data-users ). Based on people residing in private dwellings in Australia, the initial sample was selected in 2001 by identifying a sample of 488 Census Collection Districts and select- ing a representative number of households within each district. New respondents received a “New Entrant Brochure ”5explaining the survey. Data were collected through self-report surveys and in- person interviews, usually at the home of the respondent. Phone interviews were a last resort. Interviews varied in length from wave to wave but rarely exceeded 83 min per household. Because there is little within-person variation in education and 2005 was the first year in which most variables used to create our indices were available, we used only 2005 data for our analyses (which are cross-sectional). 6 Our sample included 16,958 full- and part-time (wage- and self-) employed individuals, ages 18 –65 ( M =35, SD =13; 50% male). Respondents were compensated with a $25 (Australian dollar; AUD) check at this wave. For more information, see Watson and Wooden (2012) . Measures Education reflects the number of years of education completed. We imputed these values from variables that measure respondents ’ highest educational level, age left school, and the highest year of school completed ( Summer field et al., 2016 ). For example, we assigned 12 years of education to a respondent who completed secondary education and 16 years to someone with a college degree. We did not measure the actual time spent obtaining a degree because it can vary with the number of degrees or time spent studying that did not lead to a degree. This approach is common in the economics of education literature ( Card, 1999 ) and among studies that use the HILDA survey (e.g., Nikolaev, 2016 ;Shields et al., 2009 ). We use several measures that use Likert scales. Job satisfaction was assessed with “All things considered, how satis fied are you with your job, ”which is a reliable and valid proxy for global job satisfaction (e.g., Wanous et al., 1997 ), from 0 ( totally dissatis fied) to 10 ( totally satis fied). This item was strongly correlated ( r=.85) with a facet-level index of job satisfaction based on “the work itself, ”“total pay, ”“hours worked, ”“job security, ”and “flexibility. ” Job stress, job autonomy, job variety, and qualitative demands were latent measures based on multiple items assessed using Likert- type scales from 1 ( strongly disagree )to7( strongly agree ). See Appendix C for evidence of content, convergent, discriminant, and nomological validities. We conceptualized job stress as a reaction to various working conditions with “My job is more stressful than I had ever imagined ”and “I fear that the amount of stress in my job will make me physically ill ”(α=.80). These items have been used in prior work (e.g., Hessels et al., 2017 ;Wu, 2016 ), are similar to the scale developed by Motowidlo et al. (1986) , and capture experi- ences of stress (rather than any categorical demand/stressor). Within the JD-R literature, job resources may help achieve work goals, reduce physiological and psychological costs that stem from job demands, or stimulate personal growth ( Demerouti et al., 2001 ). Thus, we captured job autonomy with “I have a lot of freedom to decide when I do my work, ”“I have a lot to say about what happens at my job, ”and “I have a lot of freedom to decide how I do my own work ”(α=.82). We captured job variety with “My job requires me to learn new things, ”“ I use many of my skills and abilities in my current job, ”and “My job provides me with a variety of interesting things to do ”(α=.74). These items are prominent in prior studies (e.g., Crawford et al., 2010 ) and consistent with our theorizing as it relates to education. Measures of qualitative demands often include pressure to complete tasks, job intensity, and time urgency (e.g., Crawford et al., 2010 ). We used the following items to capture job 5https://melbourneinstitute.uni melb.edu.au/__data/assets/pdf_ file/ 0008/3115484/BrochureW19M.pdf” >https://melbourneinstitute.unimelb .edu.au/__data/assets/pdf_ file/0008/3115484/BrochureW19M.pdf . 6As Kennedy (2008) describes, when at all possible, it is best to approach data analyses with ordinary least squares regression applied to cross- sectional data. Moreover, the intraclass correlation coef ficient strongly indicates that the data can be reliably aggregated to the person level withoutlosing important variation (ICC(1) =.96; p<.00; Bliese, 1998 , p. 359). With this in mind, we analyzed data at the person level in a single year so as to simplify the analysis and not induce contamination (i.e., bias) in ourempirical estimates. 4 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. demands that match this conceptualization, originate from earlier related research (e.g., Karasek, 1979 ;Karasek et al., 1998 ), and are similar to items used in recent research (e.g., Xie et al., 2008 ): “ I don ’t have enough time to do everything at work, ”“ My job requires me to work intensely, ”and “My job requires me to work fast ”(α=.72). 7 To measure income , we used the logarithmic transformation of respondents ’labor earnings (wages and salaries from all employ- ment) for the fiscal year. Hours worked reflects total time spent on work each week (including paid or unpaid overtime). Finally, following prior research on job satisfaction, we controlled for gender (Bernerth & Aguinis, 2016 ;0 =male, 1 =female), age and age squared (Clark et al., 1996 ),marital status (Ng et al., 2005 ; 0 =not married, 1 =married), and self-employment status [Benz & Frey, 2008 ;0 =wage-employed, 1 =self-employed (i.e., “employee of one ’s own business ”or“employer/self-employed ”was selected)]. Consistent with other national surveys [ Global Entrepreneurship Monitor (GEM), 2016 ;Organisation for Economic Co-operation and Development [OECD], 2016 ], eight percent of participants were self-employed, about one-third of whom were women. The results are robust to the exclusion of these covariates and to the inclusion of the Big Five traits (which we include in an alternative analysis, as they are associated with job satisfaction [ Judge et al., 2002 ]; see Appendix D). We report the descriptive statistics and bivariate correlations in Table 2 . The correlation between education and job satisfaction is negative but trivial in magnitude. Yet, as we theorized, the relation- ship is more nuanced. Below, we demonstrate that the highly educated tend to enjoy greater resources but also incur demands and the associated stress that accompany their jobs. Analytical Approach We estimated a series of structural equation models in Stata 16 using the sem command, which relies on a maximum likelihood estimator ( Baron & Kenny, 1986 ;Preacher & Hayes, 2008 ). We used Satorra – Bentler standard errors to correct for potential nonnormality, and we used a bootstrapping technique to calculate bias-corrected con fidence intervals using 10,000 bootstrapped samples for the indirect, direct, and total mediation effects. These models indicated that our proposed mediators separately mediated the education –job satisfaction relationship (see Table 3 ). As expected, income, job autonomy, and job variety each mediated the positive indirect effect of education on job satisfaction. Also as expected, hours worked, qualitative demands, and job stress each mediated the negative indirect effect of education on job satisfaction. Given the support for these effects, we then proceeded to estimate a single omnibus model, including the covariates described. 8We necessarily included the direct effects from education to job stress and from education to all the resources and demands (i.e., first-stage mediators) to job satisfaction. Primary Results Prior to hypothesis testing, we conducted a con firmatory factor analysis to examine the factor structure of our multi-item variables. We fit the data to a four-factor model in which items loaded onto their respective latent variables, which provided a reasonably acceptable fit:χ2(38) =5681.7, comparative fit index (CFI) =.92, standardized root-mean-square residual (SRMR) =.07, root mean square error of approximation (RMSEA) =.09. Our full model explains 28% and 25% of the variation in job stress and job satisfaction, respectively. Figure 2 reports direct effects for each pathway. 9Table 4 reports indirect, direct, and total effects of education on stress and satisfaction. We report unstandardized effects below ( p<.01 unless noted otherwise), and we include both unstandardized and standardized effects in Figure 2 . First, we found that education is positively associated with resources (H1a), which are negatively associated with stress Table 2 Descriptive Statistics and Correlations Variable Mean SD 123456789101112 1. Education 12.66 2.17 1.00 2. Job satisfaction 7.60 1.74 .06 1.00 3. Job stress 2.78 1.47 .09 .30 1.00 4. Qualitative demands 4.59 1.34 .15 .10 .42 1.00 5. Hours worked 35.33 14.74 .10 .03 .26 .25 1.00 6. Job autonomy 4.04 1.57 .13 .27 .05 .05 .16 1.00 7. Job variety 4.79 1.38 .20 .27 .12 .34 .29 .34 1.00 8. Income 10.18 1.11 .23 .00 .19 .19 .57 .20 .24 1.00 9. Gender .50 .50 .05 .02 .02 .02 .33 .09 .06 .23 1.00 10. Age 34.35 13.03 .06 .07 .10 .02 .16 .21 .09 .31 .01 1.00 11. Self-employed .08 .27 .03 .04 .01 .03 .13 .31 .07 .06 .09 .20 1.00 12. Married .61 .49 .12 .02 .09 .08 .19 .16 .11 .30 .03 .35 .13 1.00 Note .N=16,958. All correlations greater than .02 are signi ficant at p<.01 (two-tailed test). 7We dropped “My job is complex and dif ficult ”due to its low factor loading in our con firmatory factor analysis. 8In Appendix D, we present models (1) with no controls, (2) controlling for the Big Five personality traits, and (3) controlling for time sinceeducational attainment. Moreover, in a series of robustness tests (available upon request), we controlled for job tenure, occupation tenure, and occupa- tion type, used an alternative five-item (facet-like) measure of job satisfac- tion, examined future job satisfaction and different timing in our variables(using an expanded version of the HILDA data set across multiple waves), and replicated our indirect effects using Mplus 8.5. All results were similar or identical to those reported in the main text.9The χ2statistic was highly signi ficant ( p>χ2=0.00). However, the χ2 exact- fit test is extremely sensitive to discrepancies from expected values at increasing sample sizes (e.g., see Barrett, 2007 ). With a sample size greater than 10,000 observations (such as ours), the χ2test is almost always signi ficant ( Burnham & Anderson, 2002 ). THE EDUCATION –JOB SATISFACTION LINK 5 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. (H1b). Speci fically, education is positively associated with income ( B=.12), autonomy ( B=.09), and variety ( B=.12). Also as expected, autonomy ( B= .12) and variety ( B= .03) are nega- tively associated with job stress. However, income is positively associated with stress ( B=.06). Thus, the indirect effect of educa- tion on job stress (via resources only) is negative but quite small (indirect effect = .008, 95% CI [ .012, .004]). Next, our results indicated that education is indirectly and posi- tively associated with job satisfaction, as mediated by job resources and job stress. Speci fically, autonomy ( B=.27) and variety ( B=.48) are positively associated with job satisfaction, and stress is negatively associated with job satisfaction ( B= .47). Though, the magnitude of income ’s effect on job satisfaction nears zero ( B=.02, p=.21). Ultimately, the indirect net effect of education Table 3 Mediation Models for Separate Indirect and Total Effects of Education on Job Satisfaction Resources and Demands Education →Mediator Mediator →Job satisfaction Indirect effect [95% CI] Total effect [95% CI] Income .117 (.004) .029 (.013) .003 [.000, .006] .046 [ .058, .033] Job autonomy .085 (.005) .440 (.013) .037 [.033, .042] .046 [ .058, .033] Job variety .119 (.005) .525 (.016) .063 [.057, .069] .046 [ .058, .033] Hours worked .688 (.050) .003 (.001) .002 [ .003, .000] .046 [ .058, .033] Qualitative demands .071 (.004) .068 (.016) .005 [ .007, .002] .046 [ .058, .033] Job stress .061 (.005) .446 (.014) .027 [ .032, .023] .046 [ .058, .033] Note . The table reports the results of structural equation models linking education to job satisfaction through separate mediators, indirect mediation effects, and total mediation effects. Satorra-Bentler standard errors are reported in parentheses, and bias-corrected con fidence intervals based on bootstrapped standard errors with 10,000 replications are reported in brackets. Figure 2 Effects of Education on Job Satisfaction via Job Demands, Job Resources, and Job Stress .02 [.01, .03] (.04) Education Qualitative Demands Job Autonomy -.47[-.50, -.44] (-.32) Job Stress Job Variety .12[.11, .13] (.22) .07 [.07, .08](.16) .46[.44, .48] (.41) -.12[-.14, -.11](-.13) Hours Worked JOB DEMANDS JOB RESOURCES Job Satisfaction .48[.45, .50] (.33) .69 [.59, .78] (.10) .09[.08, .09] (.15) .02[.01, .02] (.19) -.03[-.05, -.02] (-.03) .27[.25, .29] (.19) -.003[-.004, -.001] (-.02) -.0303[-.0606, -.0001] (-.02) Income .12[.11, .12] (.23) .01[-.01, .04] (.01) .06 [.04, .07](.05) -.10[-.11, -.08](-.12) Sex Age Age Squared .15 [.10, .19](.04) -.03 [-.04, -.01](-.19) .41[.25, .56](.23) Married Self- Employed .01 [-.04, .07](.00) -.20 [-.29, -.12](-.03) Note .N=16,958. Unstandardized coef ficients are reported with 95% con fidence intervals in brackets and standardized coef ficients in parentheses. R2(job stress) =.28, R2(job satisfaction) =.25. All effects are statistically signi ficant at p<.01 unless the con fidence interval overlaps with zero. Consistent with our modeling approach, ellipses and rectangles indicate latent and observed variables, respectively. 6 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. on job satisfaction (via resources alone and via resources and job stress) is positive (indirect effect =.086, 95% CI [.079, .095]), providing support for H1c. These results indicate that the more highly educated experience higher job satisfaction. Our results suggest that this is, in part, because they have more intrinsically rewarding jobs (i.e., autonomy and variety) and thus less stressful working conditions. So far, our results support the narrative that higher education is associated with an array of job resources that can help improve employees ’job satisfaction. However, our second set of hypotheses highlights how higher education can also be associated with undesirable (perhaps unex- pected) outcomes. First, we found that education is positively associated with job demands (H2a), and job demands are positively associated with job stress (H2b). Speci fically, education is associ- ated with longer hours worked ( B=.69) and greater qualitative demands ( B=.07). In turn, hours worked ( B=.02) and qualitative demands ( B=.46) are positively associated with job stress. We also found that the indirect effect of education on job stress (via hours worked and qualitative demands) is positive overall (indirect effect =.045, 95% CI [.040, .050]). Next, our results indicate that education is indirectly and nega- tively associated with job satisfaction through job demands and job stress. Speci fically, hours worked ( B= .003) and qualitative demands ( B= .03) are negatively associated with job satisfaction. And, as we reported above, stress and job satisfaction are inversely related ( B= .47). Ultimately, the indirect net effect of education on job satisfaction (via demands alone and via demands and stress) is negative (indirect effect = .025, 95% CI [ .029, .022]; H2c). Thus, these findings suggest that those with higher education experience somewhat lower job satisfaction, in part, because of the greater job demands they encounter and thus more stressful working conditions. Importantly, as suggested by the JD-R model, we interpret both sets of results in combination. Given that job stress is an important aspect of our model, we first note that education ’s total effect on stress, via both job resources and demands, is positive (total indirect effect =.056, 95% CI [.047, .066]). Thus, overall, highly educated employees experience greater job stress. Regarding job satisfaction, our results indicate that education ’s positive indirect effect via job resources and job stress (.086) is partially offset by education ’s negative indirect effect via job demands and job stress ( .025). Yet, even after accounting for all of these paths, we still found a negative direct association between education and job satisfaction ( B= .096, 95% CI [ .108, .084]). Ultimately, education ’s negative association with job satisfaction (i.e., the direct effect, the indirect effect via demands, and the indirect effect via demands and stress) offsets its positive association with job satisfaction (i.e., the indirect effects via resources and via both resources and stress), such that the total (net) effect of education on job satisfaction is negative, albeit quite small (total effect = .043, 95% CI [ .056, .031]). Although our analyses cannot provide evidence of causal effects, a positive total (net) relationship between education and job satis- faction did not emerge. Thus, while the highly educated may receive an array of positive returns on their educational investment, our fi ndings suggest that studying the direct relationship between education and job satisfaction on its own may be unfruitful or misleading in light of countervailing mechanisms. Supplemental Analyses Next, we explored whether gender and self-employment status operate as moderators, altering var ious pathways between education and job resources, demands, and st ress. First, women still face work- place adversity ( Weyer, 2007 ) that can undermine the positive returns on their educational investment ( Heilman & Chen, 2003 ;Stevenson & Wolfers, 2009 ). This dynamic is particularly important given the reversal of the gender gap in education, with more women completing higher education than men ( Organisation for Economic Co-operation and Development [OECD], 2017 ). As such, we explored the notion that the education –job satisfaction link is negative and stronger for women. Using our HILDA survey sample, we conducted a group comparison analysis. We allowed the path coef ficients (structural paths) and the error variances to differ across the two groups (males and females). We also tested (using the postestimation command estat ginvariant in Stata 16) whether each path in our model is signi ficantly different between the two groups (or should be treated as equal). As reported in Figure 3 , we found a signi ficantly stronger nega- tive direct association between education and job satisfaction for women than men. Our results also indicate that highly educated women are more likely to earn higher income and experience greater job variety than their male counterparts. But they report signi ficantly less autonomy, greater qualitative demands —which is associated with greater job stress —and more hours worked. Overall, the total effect of education on job stress (via resources and demands) is considerably stronger for women (total effect =.073, 95% Table 4 Indirect Effects, Direct Effects, and Total Effects of Education on Job Stress and Job Satisfaction Outcome Job stress Job satisfaction Pathway B 95% CI β B 95% CI β Indirect effect via job resources .008 .012, .004 .014 .086 .079, .095 .108 Indirect effect via job demands .045 .040, .050 .083 .025 .029, .022 .031 Direct effect .020 .011, .029 .036 .096 .108, .084 .119 Total effect .056 .047, .066 .105 .043 .056, .031 .054 Note . The table reports indirect effects, direct effects, and total effects of education on job stress and job satisfaction based on our primary structura l equation model. Indirect effects on job satisfaction include indirect effects via both job resources/job demands alone and via job resources/job demands and job stress. B =unstandardized coef ficient, 95% CI =bias-corrected 95% con fidence interval based on bootstrapped standard errors with 10,000 replications, β =standardized coef ficient. THE EDUCATION –JOB SATISFACTION LINK 7 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Figure 3 Effects of Education on Job Satisfaction by Gender. N (males) =8,398, N (females) =8,560 .02 [.01, .03] (.04) Education Qualitative Demands Job Autonomy -.43[-.47, -.39] (.28) Job Stress Job Variety .09[.08, .11] (.18) .05[.04, .07](.11) .40[.37, .43] (.37) -.10[-.12, -.08](-.11) Hours Worked JOB DEMANDS JOB RESOURCES Job Satisfaction .46 [.42, .50] (.31) .37[.25, .50] (.06) .10[.08, .11] (.17) .01[.01, .02] (.18) -.06[-.09, -.04] (-.06) .28 [.25, .31] (.20) -.002[-.004, .001] (-.01) -.06[-.10, -.02](-.04) Income .11[.10, .12] (.22) .02 [-.01, -.06] (.01) .07[.05, .08](.06) -.07[-.09, -.05] (-.09) .01 [-.01, .02] (.01) Education Qualitative Demands Job Autonomy -.51[-.55, -.47] (-.35) Job Stress Job Variety .15[.14, .17] (.27) .09[.08, .10](.20) .52[.48, .55](.44) -.13[-.15, -.11] (-.13) Hours Worked JOB DEMANDS JOB RESOURCES Job Satisfaction .50[.46, .53] (.35) 1.22[1.09, 1.34] (.19) .08[.07, .09] (.15) .02[.02, .02] (.22) -.02[-.04, .01](-.02) .25[.22, .29](.18) -.002 [-.005, .001] (-.02) .00[-.05, -.04](.00) Income .14[.13, .15] (.27) .06[.03, .08] (.05) -.12[-.14, -.10](-.15) PANEL B: FEMALES PANEL A: MALES .02[-.02, .05] (.01) Age Age Squared Married Self- Employed -.06[-.07, -.04] (-.43) .77[.55, .99](.44) .01[-.07, .09] (.00) -.22[-.32, -.12](-.04) Age Age Squared Married Self- Employed .00[-.02, .02] (-.01) .14[-.08, .36](.08) .02[-.06, .09](.00) -.15[-.29, -.01](-.02) Note . Solid lines represent signi ficantly different paths between groups ( p<.01). Unstandardized coef ficients are reported with 95% con fidence intervals in brackets and standardized coef ficients in parentheses. Males: R2 (job stress) =.26, R2(job satisfaction) =.23. Females: R2(job stress) =.30, R2(job satisfaction) =.26. All effects are signi ficant at p<.01 unless the con fidence interval overlaps with zero. Consistent with our modeling approach, ellipses and rectangles indicate latent and observed variables, respectively. 8 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. CI [.060, .087]) than for men (total effect =.041, 95% CI [.028, .054]). Similarly, with regard to job satisfaction, while education has a small negative effect for men (total effect = .021, 95% CI [ .040, .003]), the effect is much larger for women (total effect = .061, 95% CI [ .078, .044]). These results suggest that, compared to their male counterparts, highly educated women experience more stress at work and lower job satisfaction. These negative experiences may stem from empowerment messages that imply women are responsible for solving gender inequality at work ( Kim et al., 2018 ). Such messages may prompt highly educated women (vs. men) to shoulder greater responsibility in the household and in the labor market to adhere to gender role expectations while advancing their careers. Of course, we need future research to explore the many explanations that may underlie the differential effects of educational attainment for women vis-à-vis men. Finally, relative to traditional occupations, self-employment of- fers considerable flexibility to organize one ’s work schedule, choose the content of one ’s work, and decide how to respond to job demands ( Nikolaev et al., 2020 ;Stephan, 2018 ). As such, we explored the notion that self-employment weakens the relationship between education and job satisfaction. To do so, we conducted a group comparison analysis between the self-employed and (wage-) employed using the same data and parameters described above for our gender analysis. As reported in Figure 4 , we found that better-educated workers in self-employment (vs. wage-employment) report lower income, less autonomy, less variety, and slightly greater qualitative demands, but fewer hours worked. Quite notably, we found that the net association between education and job stress (via resources and demands) is positive and stronger for the wage-employed (total effect =.062, 95% CI [.052, .072]) while weaker with a near-zero effect for the self-employed (total effect =.007, 95% CI [ .021, .034]). Regarding job satisfaction, our results indicate that, while education has a near-zero net association with job satisfaction for the self-employed (total effect = .013, 95% CI [ .049, .023]), education has a negative net association for the wage-employed (total effect = .048, 95% CI [ .060, .034]). Altogether, com- pared to their wage-employed counterparts, those in self-employ- ment seem to be more insulated from the adverse effects of education on job stress and satisfaction. We contend that illuminat- ing this boundary condition is notable for the educated and orga- nizations that value (and want to retain) their educated employees. But again, we cannot determine causality. Discussion Neither our meta-analysis in Study 1 nor the total effect that emerged in Study 2 indicated that the highly educated tend to report higher job satisfaction. Drawing on the JD-R model and distinguish- ing between working conditions and job stress, we theorized that the story is more nuanced. In Study 2, we found that, despite being associated with greater resources (and indirectly less stress and higher job satisfaction), education is also associated with greater demands (and indirectly more stress and lower job satisfaction). Ultimately, our work suggests a trade-off story: The fruit of education may be described as sweet, but also somewhat bitter. In terms of contributions, career success studies have largely investigated education ’s effect on extrinsic outcomes, such as income. Notably, Ng et al. ’s (2005) meta-analysis included education and job satisfaction. But given changes in the economy and an increasingly educated workforce ( Fry et al., 2018 ), we believe our meta-analysis, which is based on more recent empirical work, provides additional value. Importantly, Study 1 revealed a near-zero correlation and set the groundwork for our second contri- bution. Study 2 identi fied two countervailing pathways from edu- cation to job satisfaction that indicate the nuance of the relationship missed when looking at a simple main effect. Also, building on the JD-R model, we demonstrated how resources and demands operate as explanatory mechanisms. Indeed, we have offered one explana- tion. But the positive and negative pathways that emerged in our primary and supplemental analyses provide a basis for further theorizing on the impact of education. Practical Implications We do not suggest avoiding higher education to achieve higher job satisfaction. Rather, while our indirect effects are relatively small, a realistic calculation of trade-offs between desirable working conditions and experiences of stress and job satisfaction may still help workers make decisions that suit their priorities or recalibrate their values. Leaders may also consider better ways to manage the greater demands encountered by their highly educated employees so that exploiting an organization ’s, arguably, greatest human capital does not back fire. For example, by removing incentives to adopt excessive work hours, organizations can avoid inadvertently pres- suring employees to incur stress that undermines job satisfaction. Indeed, rede fining the ideal worker away from someone “totally dedicated to their [job] and always on call ”may improve organiza- tional outcomes ( Reid & Ramarajan, 2016 , p. 86). This rede finition of the ideal worker may bene fit the highly educated as they are susceptible to incurring demands and experiencing job stress in kind. Such progress may help attract and retain top talent. Limitations and Future Directions Despite its advantages, our archival data set (Study 2) required us to rely on a single-item measure of job satisfaction and limited our use of established measures and relevant variables. For instance, perhaps a more robust measure of stress or assessing strain would better capture the negativity associated with demands and alter the net effect. Moreover, scholars have long identi fied two dimensions of job demands: challenges and hindrances ( Cavanaugh et al., 2000 ), which re flect ostensibly “good ”versus “bad ”stressors ( Lazarus, 1966 ;Selye, 1974 ). While these dimensions play distinct roles in employees ’experiences and outcomes ( Crawford et al., 2010 ;Podsakoff et al., 2007 ), we could not draw on this framework due to data availability. However, in some contexts, making a priori distinctions between challenge and hindrance demands can be arbitrary. Indeed, recent studies highlight the role of idiosyncratic appraisals and how employees can perceive so-called challenge demands as hindrances and vice versa ( Bakker & Demerouti, 2017 ;Mazzola & Disselhorst, 2019 ;Searle & Auton, 2015 ;Webster et al., 2011 ). Thus, challenges (such as high workload) may only yield positive outcomes when appraised as opportunities versus threats ( González-Morales & Neves, 2015 ). Here, we assessed job stress as a phenomenological experience and general reaction to one ’s working conditions. In the future, investigation of the subjective appraisals of each job demand THE EDUCATION –JOB SATISFACTION LINK 9 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Figure 4 Effects of Education on Job Satisfaction by Employment Status. N (Self-Employed) =1,371, N (Employed) =15,587 -.01 [-.03, .02] (-.01) Education Qualitative Demands Job Autonomy -.35[-.45, -.25] (-.25) Job Stress Job Variety .08[.06, .11] (.19) .08[.05, .10](.17) .41[.34, .48] (.40) -.14[-.20, -.07] (-.14) Hours Worked JOB DEMANDS JOB RESOURCES Job Satisfaction .48 [.38, .58] (.31) -.19[-.56, .18] (-.02) .04[.02, .07] (.09) .02[.01, .02] (.27) -.13[-.20, -.06](-.12) .14 [.06, .22] (.10) -.003 [-.009, .001] (-.04)-.08[-.17, .01] (-.06) Income .04[.01, .07] (.07) .04 [-.02, .10] (.03) -.02[-.06, .03](-.02) -.05[-.09, -.02] (-.08) .02 [.01, .03] (.04) Education Qualitative Demands Job Autonomy -.48[-.51, -.45] (-.32) Job Stress Job Variety .13[.12, .13](.22) .07[.07, .08](.15) .46[.44, .49] (.41) -.14[-.15, -.12](-.13) Hours Worked JOB DEMANDS JOB RESOURCES Job Satisfaction .47 [.45, .50] (.33) .75[.66, .85] (.11) .08[.07, .09](.15) .01[.01, .02] (.18) -.03[-.04, -.01] (-.03) .29 [.27, .32] (.19) -.003[-.004, -.001] (-.02)-.02[-.05, .01] (-.01) Income .12[.12, .13] (.24) .07[.05, .08] (.06) -.10[-.11, -.08](-.12) PANEL B: EMPLOYED PANEL A: SELF-EMPLOYED .01[-.01, .04] (.01) Age Age Squared Married Sex -.01[-.06, .04] (-.09) .14[-.42, .71](.09) .33[.11, .56] (.08) .25[.09, .42](.08) Age Age Squared Married Sex -.03[-.04, -.02] (-.22) .48[.31, .64](.26) .00[-.06, .05] (.00) .14[.09, .19](.04) Note . Solid lines represent signi ficantly different paths between groups ( p<.01). Unstandardized coef ficients are reported with 95% con fidence intervals in brackets and standardized coef ficients in parentheses. Self-employed: R2(job stress) =.26, R2(job satisfaction) =.20. Employed: R2(job stress) =.28, R2(job satisfaction) =.25. All effects are signi ficant at p<.01 unless the con fidence interval overlaps with zero. Consistent with our modeling approach, ellipses and rectangles indicate latent and observed variables, respectively. 10 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. as challenging or hindering may provide additional insights into how the highly educated experience their jobs. Also, we offered a set of indirect effects as an explanation for the null effect (or weak negative effect in Study 2) of education on job satisfaction. But there are additional potential explanations that may be illuminating based on theory [e.g., the Big-Fish-Little-Pond effect ( Huguet et al., 2009 )], empirics [e.g., Western-sample restric- tion of range ( Diener & Oishi, 2000 )], or the inclusion of moderators [e.g., worker age ( Truxillo et al., 2012 )] and alternative outcomes [e.g., life satisfaction ( Adams et al., 1996 ), job security ( Kraimer et al., 2005 ), and career mobility ( Baruch et al., 2016 )]. Nonethe- less, the current study serves to provide new insights into the relationship between education and job satisfaction and, hopefully, stimulate additional inquiry. For example, beyond job character- istics, we hope that future research explores whether an expectation- reality gap also underlies the education –job satisfaction link. Indeed, education generates higher job expectations, which appear more dif ficult to meet ( Jebb et al., 2018 ). Due to their investments, the highly educated may even have unrealistic expectations about how they fare relative to others. Thus, examining social comparison processes may be fruitful. Because childhood socioeconomic status affects educational attainment ( Bradley & Corwyn, 2002 ), account- ing for this variable would help clarify the extent to which education versus expectations is associated with job satisfaction. Also, our post hoc analyses revealed that being female exacerbates and being self-employed attenuates the negative education –job satisfaction link. These findings suggest the need for further theorizing (e.g., from a gendered [ Clark, 1997 ] and an entrepreneurship [ Carter, 2011 ] perspective, respectively) and empirical investigation of workers ’differential expectations. Furthermore, we were surprised to find a positive relationship between income and job stress (contrary to H1b). Future research may explore whether income is more likely to provide resources for nonwork life (a life resource vs. job resource) and thus reduce nonwork stress rather than work stress. In fact, exploratory findings suggest that education may increase job stress via income (indirect effect =.012, 95% CI [.010, .015]). Variation in one ’s work centrality or job involvement may also shed light on the effects of income in different (work vs. nonwork) domains. Finally, we examined a snapshot in time. Prior work indicates that effects of job rewards remain positive over time, whereas job costs increasingly undermine job satisfaction ( Rusbult & Farrell, 1983 ) and negative (vs. positive) experiences are generally stronger, compound more quickly, and prevail ( Rozin & Royzman, 2001 ). Because job demands are inevitable, future work may seek to understand how, in the long run, the highly educated may better calibrate their job expectations or leverage their resources to better manage job stress and enhance job satisfaction. References * References marked with an asterisk indicate studies included in the meta- analysis in Study 1. Adams, G. A., King, L. A., & King, D. W. (1996). Relationships of job andfamily involvement, family social support, and work –family con flict with job and life satisfaction. Journal of Applied Psychology ,81(4), 411. * Allen, T. D. (2001). Family-Supportive Work Environments: The Role of Organizational Perceptions. Journal of Vocational Behavior ,58(3), 414 –435. Angle, H. L., & Perry, J. L. (1981). An empirical assessment of organiza- tional commitment and organizational effectiveness. Administrative Sci- ence Quarterly ,26,1–14. Arnold, K. D., & King, I. C. (1997). College student development and academic life: Psychological, intellectual, social, and moral issues . Taylor & Francis. Bakker, A. B., & Demerouti, E. (2007). The job demands –resources model: State of the art. Journal of Managerial Psychology ,22, 309 –328. Bakker, A. B., & Demerouti, E. (2017). Job demands-resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology ,22, 273 –285. Bakker, A. B., Demerouti, E., & Sanz-Vergel, A. I. (2014). Burnout and work engagement: The JD-R approach. Annual Review of Organizational Psychology and Organizational Behavior ,1, 389 –411. Barnes, C. M., Dang, C. T., Leavitt, K., Guarana, C. L., & Uhlmann, E. L. (2018). Archival data in micro-organizational research: A toolkit for moving to a broader set of topics. Journal of Management ,44(4), 1453 –1478. Baron, R. M., & Kenny, D. A. (1986). The moderator –mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology , 51 , 1173 –1182. Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences ,42, 815 –824. Baruch, Y., Altman, Y., & Tung, R. L. (2016). Career mobility in a global era: Advances in managing expatriation and repatriation. The Academy of Management Annals ,10(1), 841 –889. Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education . University of Chicago Press. Begley, T. M., & Czajka, J. M. (1993). Panel analysis of the moderating effects of commitment on job satisfaction, intent to quit, and health following organizational change. Journal of Applied Psychology ,78, 552 –556. Bennett, A. A., Bakker, A. B., & Field, J. G. (2018). Recovery from work- related effort: A meta-analysis. Journal of Organizational Behavior ,39, 262 –275. Benz, M., & Frey, B. S. (2008). Being independent is a great thing: Subjective evaluations of self-employment and hierarchy. Economica , 75 , 362 –383. Bernerth, J. B., & Aguinis, H. (2016). A critical review and best-practice recommendations for control variable usage. Personnel Psychology ,69, 229 –283. Bliese, P. D. (1998). Group size, ICC values, and group-level correlations: A simulation. Organizational Research Methods ,1(4), 355 –373. Bliese, P. D., Edwards, J. R., & Sonnentag, S. (2017). Stress and wellbeing at work: A century of empirical trends re flecting theoretical and societal in fluences. Journal of Applied Psychology ,102 , 389 –402. * Booth, J. E., Park, T.-Y., Zhu, L. L., Beauregard, T. A., Gu, F., & Emery, C. (2018). Prosocial response to client-instigated victimization: The roles of forgiveness and workgroup con flict. Journal of Applied Psychology , 103 (5), 513. Bowen, H. R. (1997). Investment in learning . JHU Press. * Bowler, W. M., & Brass, D. J. (2006). Relational correlates of interpersonal citizenship behavior: A social network perspective. Journal of Applied Psychology ,91(1), 70. Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology ,53, 371 –399. * Burke, R. J., Astakhova, M. N., & Hang, H. (2015). Work passion through the lens of culture: Harmonious work passion, obsessive work passion, and work outcomes in Russia and China. Journal of Business and Psychology , 30 (3), 457 –471. Burnham,K.P.,&Anderson,D.R.(2002). Model selection and multi- model inference: A practical information-theoretic approach (2nd ed.). Springer. THE EDUCATION –JOB SATISFACTION LINK 11 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Card, D. (1999). The causal effect of education on earnings. In O. C. Ashenfelter & D. Card (Eds.), Handbook of labor economics (Vol. 3, Part A, pp. 1801 –1863). Elsevier. * Carless, S. A., & Arnup, J. L. (2011). A longitudinal study of the determinants and outcomes of career change. Journal of Vocational Behavior ,78(1), 80 –91. Carter, S. (2011). The rewards of entrepreneurship: Exploring the incomes, wealth, and economic well –being of entrepreneurial households. Entre- preneurship Theory and Practice ,35(1), 39 –55. Cavanaugh, M. A., Boswell, W. R., Roehling, M. V., & Boudreau, J. W. (2000). An empirical examination of self-reported work stress among U.S. managers. Journal of Applied Psychology ,85,65 –74. * Chen, Z. X., & Aryee, S. (2007). Delegation and employee work outcomes: An examination of the cultural context of mediating processes in China. Academy of Management Journal ,50(1), 226 –238. Christian, M. S., Garza, A. S., & Slaughter, J. E. (2011). Work engagement: A quantitative review and test of its relations with task and contextual performance. Personnel Psychology ,64,89 –136. Clark, A., Oswald, A., & Warr, P. (1996). Is job satisfaction U-shaped in age? Journal of Occupational and Organizational Psychology ,69,57 –81. Clark, A. E. (1997). Job satisfaction and gender: Why are women so happy at work? Labour Economics ,4(4), 341 –372. Clark, A. E., & Oswald, A. J. (1996). Satisfaction and comparison income. Journal of Public Economics ,61, 359 –381. * Colbert, A. E., Bono, J. E., & Purvanova, R. K. (2016). Flourishing via workplace relationships: Moving beyond instrumental support. Academy of Management Journal ,59(4), 1199 –1223. Crawford, E. R., LePine, J. A., & Rich, B. L. (2010). Linking job demands and resources to employee engagement and burnout: A theoretical exten- sion and meta-analytic test. Journal of Applied Psychology ,95, 834 –848. * Davis, P. R., Trevor, C. O., & Feng, J. (2015). Creating a more quit-friendly national workforce? Individual layoff history and voluntary turnover. Journal of Applied Psychology ,100 (5), 1434. *Davis-Blake, A., Broschak, J. P., & George, E. (2003). Happy together? How using nonstandard workers affects exit, voice, and loyalty among standard employees. Academy of Management Journal ,46(4), 475 –485. * Debus, M. E., Probst, T. M., König, C. J., & Kleinmann, M. (2012). Catch me if I fall! Enacted uncertainty avoidance and the social safety net as country-level moderators in the job insecurity –job attitudes link. Journal of Applied Psychology ,97(3), 690. Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin ,125 , 627 –668. Demerouti, E., Bakker, A. B., Geurts, S. A. E., & Taris, T. W. (2009). Daily recovery from work-related effort during non-work time. In S. Sonnentag, P. L. Perrewé, & D. C. Ganster (Eds.), Research in occupational stress and well-being: Vol. 7. Current perspectives on job-stress recovery (pp. 85 –123). JAI Press. Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands –resources model of burnout. Journal of Applied Psychology , 86 , 499 –512. Demerouti, E., Bakker, A. B., Sonnentag, S., & Fullagar, C. J. (2012). Work related flow and energy at work and at home: A study on the role of daily recovery. Journal of Organizational Behavior ,33, 276 –295. Dickson, M., & Harmon, C. (2011). Economic returns to education: What we know, what we don ’t know, and where we are going —some brief pointers. Economics of Education Review ,30, 1118 –1122. Diener, E., & Oishi, S. (2000). Money and happiness: Income and subjective well-being across nations. Culture and subjective well-being , 185 –218. * Donohue, R. (2007). Examining career persistence and career change intent using the career attitudes and strategies inventory. Journal of Vocational Behavior ,70(2), 259 –276. Eagan, M. K., Stolzenberg, E. B., Zimmerman, H. B., Aragon, M. C., Whang Sayson, H., & Rios-Aguilar, C. (2017). The American freshman: National norms fall 2016 . Higher Education Research Institute, UCLA; www.heri .ucla.edu * Erdogan, B., & Bauer, T. N. (2005). Enhancing career bene fits of employee proactive personality: The role of fit with jobs and organizations. Person- nel Psychology ,58(4), 859 –891. * Erdogan, B., & Bauer, T. N. (2009). Perceived overquali fication and its outcomes: The moderating role of empowerment. Journal of Applied Psychology ,94, 557 –565. Fried, Y., & Ferris, G. R. (1987). The validity of the job characteristics model: A review and meta-analysis. Personnel Psychology ,40, 287 –322. Fry, R., Igielnik, R., & Patten, E. (2018). How Millennials today compare with their grandparents 50 years ago [Web log] .https://www .pewresearch.org/fact- tank/2018/03/16/how-mille nnials-compare-with- their-grandparents/ Geurts, S. A. E., & Sonnentag, S. (2006). Recovery as an explanatory mechanism in the relation between acute stress reactions and chronic health impairment. Scandinavian Journal of Work, Environment & Health ,32, 482 –492. Global Entrepreneurship Monitor (GEM). (2016). Global entrepreneurship monitor 2015/16 global report .https://www.gemconsortium.org/report González-Morales, G. M., & Neves, P. (2015). When stressors make you work: Mechanisms linking challenge stressors to performance. Work & Stress ,29, 213 –229. Gould, S., & Werbel, J. D. (1983). Work involvement: A comparison of dual wage earner and single wage earner families. Journal of Applied Psychol- ogy ,68, 313 –319. * Goulet, L. R., & Singh, P. (2002). Career commitment: A reexamination and an extension. Journal of Vocational Behavior ,61(1), 73 –91. * Guerra, G., & Patuelli, R. (2016). The role of job satisfaction in transitions into self –employment. Entrepreneurship Theory & Practice ,40(3), 543 –571. Hackman, J. R., & Oldham, G. R. (1975). Development of the job diagnostic survey. Journal of Applied Psychology ,60, 159 –170. Hackman, R. J., & Oldham, G. R. (1980). Work redesign . Addison Wesley. Hakanen, J., Bakker, A. B., & Jokisaari, M. (2011). A 35-year follow-up study on burnout among Finnish employees. Journal of Occupational Health Psychology ,16, 345 –360. Heilman, M. E., & Chen, J. J. (2003). Entrepreneurship as a solution: The allure of self- employment for women and minorities. Human Resource Management Review ,13, 347 –364. Hendrix, W., Ovalle, N. K., & Troxler, R. G. (1985). Behavioral and physiological consequences of stress and its antecedent factors. Journal of Applied Psychology ,70, 188 –201. Hessels, J., Rietveld, C. A., & van der Zwan, P. (2017). Self-employment and work-related stress: The mediating role of job control and job demand. Journal of Business Venturing ,32, 178 –196. * Higgins, M. C., & Thomas, D. A. (2001). Constellations and careers: Toward understanding the effects of multiple developmental relationships. Journal of Organizational Behavior: The International Journal of Indus- trial. Occupational and Organizational Psychology and Behavior ,22(3), 223 –247. * Hmieleski, K. M., & Sheppard, L. D. (2019). The Yin and Yang of entrepreneurship: Gender differences in the importance of communal and agentic characteristics for entrepreneurs ’subjective well-being and performance. Journal of Business Venturing ,34(4), 709 –730. Hobfoll, S. E. (1989). Conservation of resources: A new attempt at concep- tualizing stress. American Psychologist ,44, 513 –524. * Holtom, B., Goldberg, C. B., Allen, D. G., & Clark, M. A. (2017). How today ’s shocks predict tomorrow ’s leaving. Journal of Business and Psychology ,32(1), 59 –71. * Holtom, B. C., Lee, T. W., & Tidd, S. T. (2002). The relationship between work status congruence and work-related attitudes and behaviors. Journal of Applied Psychology ,87(5), 903. * Hoppe, A., Fujishiro, K., & Heaney, C. A. (2014). Workplace racial/ethnic similarity, job satisfaction, and lumbar back health among warehouse 12 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. workers: Asymmetric reactions across racial/ethnic groups. Journal of Organizational Behavior ,35(2), 172 –193. Huguet, P., Dumas, F., Marsh, H., Wheeler, L., Seaton, M., Nezlek, J., Suls, J., & Régner, I., Nezlek, J. (2009). Clarifying the role of social comparison in the big- fish–little-pond effect (BFLPE): An integrative study. Journal of Personality and Social Psychology ,97(1), 156 –170. Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A metaanalytic summary and theoretical extension of the work design literature. Journal of Applied Psychology ,92, 1332 –1356. Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings . Sage Publications. * Janssen, O. (2001). Fairness perceptions as a moderator in the curvilinear relationships between job demands, and job performance and job satis- faction. Academy of Management Journal ,44(5), 1039 –1050. Jebb, A. T., Tay, L., Diener, E., & Oishi, S. (2018). Happiness, income satiation and turning points around the world. Nature Human Behaviour , 2 ,33 –38. Judge, T. A., Bono, J. E., & Locke, E. A. (2000). Personality and job satisfaction: The mediating role of job characteristics. Journal of Applied Psychology ,85(2), 237 –249. Judge, T. A., Heller, D., & Mount, M. K. (2002). Five-factor model of personality and job satisfaction: A meta-analysis. Journal of Applied Psychology ,87(3), 530 –541. * Judge, T. A., Ilies, R., & Zhang, Z. (2012). Genetic in fluences on core self- evaluations, job satisfaction, and work stress: A behavioral genetics mediated model. Organizational Behavior and Human Decision Pro- cesses ,117 (1), 208 –220. Judge, T. A., Klinger, R. L., & Simon, L. S. (2010). Time is on my side: Time, general mental ability, human capital, and extrinsic career success. Journal of Applied Psychology ,95,92 –107. Judge, T. A., Piccolo, R. F., Podsakoff, N. P., Shaw, J. C., & Rich, B. L. (2010). The relationship between pay and job satisfaction: A meta-analysis of the literature. Journal of Vocational Behavior ,77, 157 –167. Judge, T. A., Weiss, H. M., Kammeyer-Mueller, J. D., & Hulin, C. L. (2017). Job attitudes, job satisfaction, and job affect: A century of continuity and of change. Journal of Applied Psychology ,102 (3), 356 –374. * Kammeyer-Mueller, J. D., Wanberg, C. R., Glomb, T. M., & Ahlburg, D. (2005). The role of temporal shifts in turnover processes: It ’s about time. Journal of Applied Psychology ,90(4), 644. Karasek, R. A., Jr. (1979). Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly ,24, 285 –308. Karasek, R., Brisson, C., Kawakami, N., Houtman, I., Bongers, P., & Amick, B. (1998). The job content questionnaire (JCQ): An instrument for internationally comparative assessments of psychosocial job characteris- tics. Journal of Occupational Health Psychology ,3, 322 –355. Kennedy, P. (2008). A guide to econometrics (2nd ed.). Blackwell. Kim, J. Y., Fitzsimons, G. M., & Kay, A. C. (2018). Lean in messages increase attributions of women ’s responsibility for gender inequality. Journal of Personality and Social Psychology ,115 (6), 974 –1001. * Kirkman, B. L., & Shapiro, D. L. (2001). The impact of cultural values on job satisfaction and organizational commitment in self-managing work teams: The mediating role of employee resistance. Academy of Manage- ment Journal ,44(3), 557 –569. Kluger, A. N., & Tikochinsky, J. (2001). The error of accepting the “ theoretical ”null hypothesis: The rise, fall, and resurrection of common- sense hypotheses in psychology. Psychological Bulletin ,127 (3), 408 –423. * Koch, M., Park, S., & Zahra, S. A. (2021). Career patterns in self- employment and career success. Journal of Business Venturing ,31, 105998. Kraimer, M. L., Wayne, S. J., Liden, R. C., & Sparrowe, R. T. (2005). The role of job security in understanding the relationship between employees ’ perceptions of temporary workers and employees ’performance. Journal of Applied Psychology ,90(2), 389. * Kreiner, G. E. (2006). Consequences of work-home segmentation or integration: A person-environment fit perspective. Journal of Organiza- tional Behavior: The International Journal of Industrial. Occupational and Organizational Psychology and Behavior ,27(4), 485 –507. Kristensen, T. S., Bjorner, J. B., Christensen, K. B., & Borg, V. (2004). The distinction between work pace and working hours in the measurement of quantitative demands at work. Work & Stress ,18, 305 –322. * Lankau, M. J., & Scandura, T. A. (2002). An investigation of personal learning in mentoring relationships: Content, antecedents, and conse- quences. Academy of Management Journal ,45(4), 779 –790. Lazarus, R. S. (1966). Psychological stress and the coping process . McGraw-Hill. Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping . Springer. Lazarus, R. S., & Folkman, S. (1987). Transactional theory and research on emotions and coping. European Journal of Personality ,1, 141 –169. * Leana, C., Appelbaum, E., & Shevchuk, I. (2009). Work process and quality of care in early childhood education: The role of job crafting. Academy of Management Journal ,52(6), 1169 –1192. Leana, C. R., & Meuris, J. (2015). Living to work and working to live: Income as a driver of organizational behavior. The Academy of Manage- ment Annals ,9,55 –95. * Li, N., Liang, J., & Crant, J. M. (2010). The role of proactive personality in job satisfaction and organizational citizenship behavior: A relational perspective. Journal of Applied Psychology ,95(2), 395. * Liao, H., Chuang, A., & Joshi, A. (2008). Perceived deep-level dissimilar- ity: Personality antecedents and impact on overall job attitude, helping, work withdrawal, and turnover. Organizational Behavior and Human Decision Processes ,106 (2), 106 –124. * Loi, R., Yang, J., & Diefendorff, J. M. (2009). Four-factor justice and daily job satisfaction: A multilevel investigation. Journal of Applied Psychol- ogy ,94(3), 770. Lounsbury, J. W., & Hoopes, L. L. (1986). A vacation from work: Changes in work and nonwork outcomes. Journal of Applied Psychology ,71, 392 –401. Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology ,52, 397 –422. * Masuda, A. D., McNall, L. A., Allen, T. D., & Nicklin, J. M. (2012). Examining the constructs of work-to-family enrichment and positive spillover. Journal of Vocational Behavior ,80(1), 197 –210. Mauno, S., Kinnunen, U., & Ruokolainen, M. (2007). Job demands and resources as antecedents of work engagement: A longitudinal study. Journal of Vocational Behavior ,70, 149 –171. Maynard, D. C., & Parfyonova, N. M. (2013). Perceived overquali fication and withdrawal behaviours: Examining the roles of job attitudes and work values. Journal of Occupational and Organizational Psychology ,86, 435 –455. Mazzola, J. J., & Disselhorst, R. (2019). Should we be “challenging ” employees?: A critical review and meta-analysis of the challenge-hindrance model of stress. Journal of Organizational Behavior ,40,949 –961. McKee-Ryan, F. M., & Harvey, J. (2011). “I have a job, but ::: ”A review of underemployment. Journal of Management ,37, 962 –996. Moen, P., Lam, J., Ammons, S., & Kelly, E. (2013). Time work by over- worked professionals: Strategies in response to the stress of higher status. Work and Occupations ,40,79 –114. Morgeson, F. P., & Humphrey, S. E. (2006). The Work Design Question- naire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work. Journal of Applied Psychol- ogy ,91, 1321 –1339. Morris, J. H., & Sherman, J. D. (1981). Generalizability of an organizational commitment model. Academy of Management Journal ,24, 512 –526. Motowidlo, S. J., Packard, J. S., & Manning, M. R. (1986). Occupational stress: Its causes and consequences for job performance. Journal of Applied Psychology ,71, 618 –629. THE EDUCATION –JOB SATISFACTION LINK 13 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. * Munyon, T. P., Madden, L. T., Madden, T. M., & Vigoda-Gadot, E. (2019). (Dys)functional attachments?: How community embeddedness impacts workers during and after long-term unemployment. Journal of Vocational Behavior ,112 ,35 –50. Ng, T. W. H., Eby, L. T., Sorensen, K. L., & Feldman, D. C. (2005). Predictors of objective and subjective career success: A meta-analysis. Personnel Psychology ,58, 367 –408. Ng, T. W. H., & Feldman, D. C. (2009). Age, work experience, and the psychological contract. Journal of Organizational Behavior ,30, 1053 –1075. Nikolaev, B. (2016). Does other people ’s education make us less happy? Economics of Education Review ,52, 176 –191. Nikolaev, B., Boudreaux, C. J., & Wood, M. (2020). Entrepreneurship and subjective well- being: The mediating role of psychological functioning. Entrepreneurship Theory and Practice ,44(3), 557 –586. * Nikolaev, B., Shir, N., & Wiklund, J. (2020). Dispositional positive and negative affect and self-employment transitions: The mediating role of job satisfaction. Entrepreneurship Theory and Practice ,44(3), 451 –474. * Obschonka, M., Silbereisen, R. K., & Wasilewski, J. (2012). Constellations of new demands concerning careers and jobs: Results from a two-country study on social and economic change. Journal of Vocational Behavior , 80 (1), 211 –223. Organisation for Economic Co-operation and Development. (2016). Employment —self-employment rate —OECD data .https://data.oecd.org/ emp/self-employment-rate.htm Organization for Economic Co-operation and Development. (2017). Educa- tion at a glance 2017: OECD indicators .https://doi.org/10.1787/eag- 2017-en Oreopoulos, P., & Salvanes, K. G. (2011). Priceless: The nonpecuniary bene fits of schooling. The Journal of Economic Perspectives ,25, 159 –184. * Ozer, M. (2008). Personal and task-related moderators of leader-member exchange among software developers. Journal of Applied Psychology , 93 (5), 1174. Parker, D. F., & DeCotiis, T. A. (1983). Organizational determinants of job stress. Organizational Behavior & Human Performance ,32, 160 –177. Perko, K., Kinnunen, U., & Feldt, T. (2017). Long-term pro files of work- related rumination associated with leadership, job demands, and exhaus- tion: A three-wave study. Work & Stress ,31(4), 395 –420. Perlow, L. A. (1999). The time famine: Towards a sociology of work time. Administrative Science Quarterly ,44,57 –81. Pines, A. M., & Keinan, G. (2005). Stress and burnout: The signi ficant difference. Personality and Individual Differences ,39, 625 –635. Podsakoff, N. P., LePine, J. A., & LePine, M. A. (2007). Differential challenge stressor- hindrance stressor relationships with job attitudes, turnover intentions, turnover, and withdrawal behavior: A meta-analysis. Journal of Applied Psychology ,92, 438 –454. * Porath, C., Spreitzer, G., Gibson, C., & Garnett, F. G. (2012). Thriving at work: Toward its measurement, construct validation, and theoretical re finement. Journal of Organizational Behavior ,33(2), 250 –275. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods ,40(3), 879 –891. Reid, E., & Ramarajan, L. (2016). Managing the high-intensity workplace. Harvard Business Review ,94(6), 78 –85. Rich, B. L., LePine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and effects on job performance. Academy of Management Journal ,53, 617 –635. Ross, C. E., & Reskin, B. F. (1992). Education, control at work, and job satisfaction. Social Science Research ,21, 134 –148. Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review ,5, 296 –320. Rusbult, C. E., & Farrell, D. (1983). A longitudinal test of the investment model: The impact on job satisfaction, job commitment, and turnover of variations in rewards, costs, alternatives, and investments. Journal of Applied Psychology ,68, 429 –438. Saxbe, D. E., Repetti, R. L., & Graesch, A. P. (2011). Time spent in housework and leisure: Links with parents ’physiological recovery from work. Journal of Family Psychology ,25, 271 –281. Schaubroeck, J., Cotton, J. L., & Jennings, K. R. (1989). Antecedents and consequences of role stress: A covariance structure analysis. Journal of Organizational Behavior ,10,35 –58. Schaufeli, W. B., & Buunk, B. P. (2002) Burnout: An overview of 25 years of research and theorizing. M. J. Schabracq, J. A. M. Winnubst, C. L. Cooper (Eds.), Handbook of work and health psychology (pp. 383 –425). Wiley. * Schaumberg, R. L., & Flynn, F. J. (2017). Clarifying the link between job satisfaction and absenteeism: The role of guilt proneness. Journal of Applied Psychology ,102 (6), 982. * Schjoedt, L. (2009). Entrepreneurial job characteristics: An examination of their effect on entrepreneurial satisfaction. Entrepreneurship Theory and Practice ,33(3), 619 –644. * Schlett, C., & Ziegler, R. (2014). Job emotions and job cognitions as determinants of job satisfaction: The moderating role of individual differ- ences in need for affect. Journal of Vocational Behavior ,84(1), 74 –89. Searle, B. J., & Auton, J. C. (2015). The merits of measuring challenge and hindrance appraisals. Anxiety, Stress, & Coping ,28, 121 –143. Selye, H. (1974). Stress without distress . Lippincott. Seybolt, J. W. (1976). Work satisfaction as a function of the person-environ- ment interaction. Organizational Behavior & Human Performance ,17, 66 –75. * Shaffer, M. A., Joplin, J. R. W., Bell, M. P., Lau, T., & Oguz, C. (2000). Gender discrimination and job-related outcomes: A cross-cultural com- parison of working women in the United States and China. Journal of Vocational Behavior ,57(3), 395 –427. * Shalley, C. E., Gilson, L. L., & Blum, T. C. (2000). Matching creativity requirements and the work environment: Effects on satisfaction and intentions to leave. Academy of Management Journal ,43(2), 215 –223. Shields, M. A., Price, S. W., & Wooden, M. (2009). Life satisfaction and the economic and social characteristics of neighbourhoods. Journal of Popu- lation Economics ,22, 421 –443. Smith, A. (2001). Perceptions of stress at work. Human Resource Manage- ment Journal ,11,74 –86. Smith, P. C., Kendall, L. M., & Hulin, C. L. (1969). The measurement of satisfaction in work and retirement . Rand McNally. * Son, J., & Ok, C. (2019). Hangover follows extroverts: Extraversion as a moderator in the curvilinear relationship between newcomers ’organiza- tional tenure and job satisfaction. Journal of Vocational Behavior ,110 , 72 –88. Sonnentag, S., & Fritz, C. (2007). The recovery experience questionnaire: Development and validation of a measure for assessing recuperation and unwinding from work. Journal of Occupational Health Psychology ,12, 204 –221. Sonnentag, S., & Fritz, C. (2015). Recovery from job stress: The stressor- detachment model as an integrative framework. Journal of Organizational Behavior ,36, S72 –S103. * Steel, R. P., Rentsch, J. R., & Van Scotter, J. R. (2007). Timeframes and absence frameworks: A test of Steers and Rhodes ’(1978) model of attendance. Journal of Management ,33(2), 180 –195. Stephan, U. (2018). Entrepreneurs ’mental health and well-being: A review and research agenda. The Academy of Management Perspectives ,32, 290 –322. Stevenson, B., & Wolfers, J. (2009). The paradox of declining female happiness. American Economic Journal. Economic Policy ,1, 190 –225. Sullivan, S. E., & Bhagat, R. S. (1992). Organizational stress, job satisfac- tion, and job performance: Where do we go from here? Journal of Management ,18, 353 –374. Summer field, M., Freidlin, S., Hahn, M., La, N., Li, N., Macalalad, N., O ’Shea, M., Watson, N., Wilkins, R., & Wooden, M. (2016). HILDA user 14 SOLOMON, NIKOLAEV, AND SHEPHERD This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. manual —Release 15 . https://melbourneinstitute.unimelb.edu.au/data/ assets/pdf_ file/0007/2194342/HILDA_User_Manual_Release_15.0.pdf * Sy, T., Tram, S., & O ’Hara, L. A. (2006). Relation of employee and manager emotional intelligence to job satisfaction and performance. Journal of Vocational Behavior ,68(3), 461 –473. * Takeuchi, R., Chen, G., & Lepak, D. P. (2009). Through the looking glass of a social system: Cross-level effects of high-performance work systems on employees ’attitudes. Personnel Psychology ,62(1), 1 –29. ten Brummelhuis, L. L., & Bakker, A. B. (2012). Staying engaged during the week: The effect of off-job activities on next day work engagement. Journal of Occupational Health Psychology ,17, 445 –455. * Trevor, C. O. (2001). Interactions among actual ease-of-movement deter- minants and job satisfaction in the prediction of voluntary turnover. Academy of Management Journal ,44(4), 621 –638. Truxillo, D. M., Cadiz, D. M., Rineer, J. R., Zaniboni, S., & Fraccaroli, F. (2012). A lifespan perspective on job design: Fitting the job and the worker to promote job satisfaction, engagement, and performance. Organiza- tional Psychology Review ,2(4), 340 –360. * Tschopp, C., Grote, G., & Gerber, M. (2014). How career orientation shapes the job satisfaction –turnover intention link. Journal of Organiza- tional Behavior ,35(2), 151 –171. * Van Dyne, L., & Pierce, J. L. (2004). Psychological ownership and feelings of possession: Three field studies predicting employee attitudes and organizational citizenship behavior. Journal of Organizational Behavior: The International Journal of Industrial. Occupational and Organizational Psychology and Behavior ,25(4), 439 –459. * Van Hooft, E. A. J., Born, M. Ph., Taris, T. W., Van der Flier, H., & Blonk, R. W. B. (2004). Predictors of job search behavior among employed and unemployed people. Personnel Psychology ,57(1), 25 –59. * Venkataramani, V., Labianca, G. J., & Grosser, T. (2013). Positive and negative workplace relationships, social satisfaction, and organizational attachment. Journal of Applied Psychology ,98(6), 1028. * Vergauwe, J., Wille, B., Feys, M., De Fruyt, F., & Anseel, F. (2015). Fear of being exposed: The trait-relatedness of the impostor phenomenon and its relevance in the work context. Journal of Business and Psychology ,30(3), 565 –581. Verhofstadt, E., De Witte, H., & Omey, E. (2007). Higher educated workers: Better jobs but less satis fied? International Journal of Manpower ,28(2), 135 –151. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software ,36(3), 1 –48. * Vigoda, E. (2000). Organizational Politics, Job Attitudes, and Work Out- comes: Exploration and Implications for the Public Sector. Journal of Vocational Behavior ,57(3), 326 –347. * Wanberg, C. R., & Banas, J. T. (2000). Predictors and outcomes of openness to changes in a reorganizing workplace. Journal of Applied Psychology ,85(1), 132. * Wanberg, C. R., Kanfer, R., & Banas, J. T. (2000). Predictors and outcomes of networking intensity among unemployed job seekers. Journal of Applied Psychology ,85(4), 491. * Wang, M., Zhan, Y., Mccune, E., & Truxillo, D. (2011). Understanding newcomers ’adaptability and work- related outcomes: Te sting the mediating roles of perceived P –Efit variables. Personnel Psychology ,64(1), 163 –189. * Wang, Y.-D., & Hsieh, H.-H. (2014). Employees ’reactions to psychologi- cal contract breach: A moderated mediation analysis. Journal of Voca- tional Behavior ,85(1), 57 –66. Wanous, J. P., & Reichers, A. E. (1996). Estimating the reliability of a single- item measure. Psychological Reports ,78(2), 631 –634. Wanous, J. P., Reichers, A. E., & Hudy, M. J. (1997). Overall job satisfac- tion: How good are single-item measures? Journal of Applied Psychology , 82 (2), 247. Watson, N., & Wooden, M. P. (2012). The HILDA survey: A case study in the design and development of a successful household panel survey. Longitudinal and Life Course Studies ,3, 369 –381. * Wayne, J. H., Musisca, N., & Fleeson, W. (2004). Considering the role of personality in the work –family experience: Relationships of the big five to work –family con flict and facilitation. Journal of Vocational Behavior , 64 (1), 108 –130. Webster, J. R., Beehr, T. A., & Love, K. (2011). Extending the challenge- hindrance model of occupational stress: The role of appraisal. Journal of Vocational Behavior ,79, 505 –516. * Weller, I., Holtom, B. C., Matiaske, W., & Mellewigt, T. (2009). Level and time effects of recruitment sources on early voluntary turnover. Journal of Applied Psychology ,94(5), 1146. Weyer, B. (2007). Twenty years later: Explaining the persistence of theglass ceiling for women leaders. Women in Management Review ,22, 482 –496. * Wiese, B. S., & Salmela-Aro, K. (2008). Goal con flict and facilitation as predictors of work –family satisfaction and engagement. Journal of Voca- tional Behavior ,73(3), 490 –497. Wilk, S. L., & Cappelli, P. (2003). Understanding the determinants of employer use of selection methods. Personnel Psychology ,56, 103 –124. * Wright, T. A., Cropanzano, R., Bonett, D. G., & Diamond, W. J. (2009). The role of employee psychological well-being in cardiovascular health: When the twain shall meet. Journal of Organizational Behavior: The International Journal of Industrial. Occupational and Organizational Psychology and Behavior ,30(2), 193 –208. Wu, C. H. (2016). Personality change via work: A job demand –control model of big- five personality changes. Journal of Vocational Behavior , 92 , 157 –166. Xie, J. L., Schaubroeck, J., & Lam, S. S. K. (2008). Theories of job stress and the role of traditional values: A longitudinal study in China. Journal of Applied Psychology ,93, 831 –848. *Zacher, H. (2015). Daily manifestations of career adaptability: Relation- ships with job and career outcomes. Journal of Vocational Behavior ,91, 76 –86. * Zimmerman, R. D., Swider, B. W., & Arthur, J. B. (2020). Does turnover destination matter? Differentiating antecedents of occupational changeversus organizational change. Journal of Vocational Behavior ,121 , 103470. Received May 19, 2019 Revision received January 30, 2021 Accepted February 4, 2021 ▪ THE EDUCATION –JOB SATISFACTION LINK 15 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

It is possible to do this? Write in one or two pages the following questions based on the reading of Frankfurt – On Bullshit What is the thrust of Frankfurt’s argument? That is, what is he arguing fo
Dear All –  Below I’ve posted a few sample RRP models to give you a more concrete idea of what you should be aiming for.  None are perfect, but that is not the point.  What is important is that the author is attempting to answer the prompt posed and is doing so by presenting a developed thought that supports itself with progressively consistent reasoning.   II. Williams argues that a truly amoral person is extremely rare, that it doesn’t take much for someone to become a moral person, and that morality is an integral part of the human experience. He explores this claim through a hypothetical: a man who only cares about his own self interests. This man cannot think about justice or other people’s needs. He can’t even think of his mindset as better or worse than other peoples’, because that would be considered his moral reasoning. He is severely limited in what he can think about as to not develop a sense of morality. According to Williams, this amoral person cannot even question his own mindset too much because “…it will be very difficult for him to pursue those questions very far without thinking of the general interests and needs of his fellow human beings, which would land him once more into the land of moral thought…” (p. 5). Therefore, it is almost impossible for such a man to exist because of how many thoughts would immediately compromise his status as amoral.  Williams also makes the point that social conditioning is what causes us to develop morals, and that this conditioning is unavoidable. He claims that everything that makes up a person is the result of conditioning, down to the language they speak. Society and its inevitable influence on us is what gives us morals. “For, in general, there can be no society without some moral rules, and he needs society.” Williams makes the point that morality and man are inseparable. He refutes the idea that the depraved, morally reprehensible behavior of people who are struggling to survive is the true reflection of human morality. He questions why we test the true nature of man through how they would act in extreme circumstances, when our true selves are arguably seen in how we act day to day. These true versions of ourselves are the ones with regard for morals, therefore amorality is hard to achieve.   III. In Williams’s essay, the Amoralist, we look at what he believes are challenges to moral philosophy. The Amoralist is a person who doesn’t follow societal norms of morality. Morality usually guides the actions of all of us, but the Amoralist is different. From what I can understand, if the Amoralist would choose not to lie, it wouldn’t be because of morals or because of the idea of right vs. wrong but more out of self-interest or personal wants. Some common moral considerations are caring about other people’s interests, telling the truth, or keeping promises that don’t suit them. Still, the Amoralist does not believe in these norms, thus leading Williams to compare the Amoralist to a stereotypical gangster. The amoralist acts for other people from time totime but it all depends on how he happens to feel. Williams suggests throughout the entire article that the amoralist is theoretically possible but basically practically impossible.   IV.   Williams argues that one cannot simply use regular reasoning or rationalization when confronting an amoralist. The word amorality itself is defined as an indifference or incapability for morality. Throughout his argument Williams consistently brings up the issues with how rationalization and reasoning are different to an amoralist. This is because as one uses reasoning or rationalizes to answer questions, morality plays a major role in one’s reasoning . However, in the example Williams gives the subject is an amoralist therefore, basic reasoning is already made complicated as one cannot simply rely on the morality of the subject to provide an answer. In this scenario Williams states, “We should perhaps also leave out a more formal aspect of morality,”. Williams suggests is that one should remove the concept of “right and wrong” for the argument as an amoralist as an amoralist is supposed to be indifferent to morality. This means the idea of “right and wrong” would not have an affect on any reasoning one presents. Furthermore, Williams’ states, “What he cannot consistently do is resent it or disapprove of it, for these are attitudes within a moral system.”. Williams’ writes this because it furthers the idea that to argue with an amoralist, one must remove morality from their argument. The quote suggests that since one knows what a moralist cannot consistently do is “resent” this can be used in an argument as if an amoralist were to “resent” an argument it would completely against their ideal. By getting an amoralist to break their ideals of amorality, one can begin to argue with an amoralist using morality in the argument. In addition to this idea, Williams’ writes, “the more basic moral rules and conceptions are strongly internalized in upbringings, at a level from which they do not merely evaporate,”. What Williams’ is suggesting is that one cannot simply lose all morality and become completely indifferent to morals. By knowing this Williams’ states that morality still may be used in an argument with a  moralist, as it would be difficult for a moralist to be completely indifferent to morality despite their ideals and standing on morality itself