A Critical Look at Ourselves: Do Male and FemaleProfessors Respond the Same to EnvironmentCharacteristics?

Stacey R. Kessler • Paul E. Spector • Mark B. Gavin

Received: 25 February 2012 / Published online: 25 September 2013� Springer Science+Business Media New York 2013

Abstract We examined the relationship between gender and both job satisfaction and

research productivity using data from 1,135 psychology faculty working in 229 academic

departments. We found that gender differences in job satisfaction and research productivity

were related to elements of the department (i.e., teaching orientation and structure).

Overall, women reported lower levels of productivity than their male counterparts. Women

also reported higher levels of job satisfaction in more teaching-oriented departments

whereas men reported higher levels job satisfaction in more research-oriented departments.

We suggest that these findings might be the result of gender differences in preferences with

women preferring more socially-oriented positions and men prefer more ‘‘things/data’’-

oriented positions.

Keywords Job satisfaction � Research productivity � Research/teaching

orientation � Structure � Gender

Introduction

Over the past 40 years, women have made substantial gains in academia, specifically, and

in the workplace, more generally. For example, an increased number of women hold top

administrative positions within academia and women have increased their representation as

S. R. Kessler (&)Department of Management, School of Business, Montclair State University, Partridge Hall 322B,1 Normal Avenue, Upper Montclair, NJ 07043, USAe-mail: kesslers@mail.montclair.edu

P. E. SpectorUniversity of South Florida, Tampa, FL, USA

M. B. GavinWest Virginia University, Morgantown, WV, USA

123

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assistant, associate, and full professors at research-oriented universities (Hyde et al. 2002).

However, some researchers suggest that these substantial gains have not completely erased

gender differences. Specifically, women hold only 36 % of all tenure-line faculty positions

and only 20 % of full professor positions (Sax et al. 2002; National Center for Education

Statistics 2005; Sallee 2012). Additionally, on average, women still have lower levels of

research productivity than their male counterparts (Stack 2004), yet the exact reasons for

this difference are still not established.

Furthermore, trends within the math and science disciplines indicate that pay and

advancement for women within academia are still lagging (Van Anders 2004), that women

tend to be underrepresented on faculties in many disciplines, and that women tend to be

clustered in lower ranks than men (Sax et al. 2002; Benschop and Brouns 2003; August and

Waltman 2004). Women are also less likely than men to receive raises and promotions

(Etzkowitz et al. 2000; August and Waltman 2004). Finally, some evidence suggests that

women are less likely to receive tenure than men, are promoted to associate and full

professor more slowly, earn lower salaries on average, and are more likely to leave aca-

demia altogether (August and Waltman 2004; Barbezat and Hughes 2005; Stewart and

LaVaque-Manty 2008).

While the majority of this research has been conducted within science, math, and

engineering departments (e.g., Van Anders 2004; Todd et al. 2008), it is possible that the

findings apply to other related disciplines. We focus on psychology departments because

they have about an equal distribution of men and women (Wicherski et al. 2003) and

because psychology, as a discipline, has displayed sensitivity to gender issues. For

example, major professional societies, including the American Psychology Association

(APA) and the Association for the Psychological Sciences (APS), have specific teaching

resources (e.g., textbooks, peer-reviewed journal articles, annual conference symposia) for

incorporating gender and diversity issues in undergraduate and graduate study. Addi-

tionally, numerous divisions within the APA note women’s studies in their mission

statements. Between the educational background and apparent interest in gender studies, it

seems that psychology departments would be resistant to the phenomena that drive gender

underrepresentation. However, even within psychology, one sees the same pattern of

women being clustered at lower ranks. Approximately 25 % of full professors, 40 % of

associate professors, 50 % of assistant professors, and 65 % of lecturers are women

(Wicherski et al. 2003). Furthermore, whereas approximately half of faculty members are

women, only 30 % of tenure-track faculty members are women (Wicherski et al. 2003). In

the current study, we examine environmental factors (structure and teaching focus of the

department) that might interact with gender to relate to job satisfaction and research

productivity.

Theoretical Framework

As a theoretical background, we incorporate two distinct classes of theories: vocational

interests and organizational structure. Among the most widely used framework for

assessing vocational interests is Holland’s (1973) model. He describes a six point hexagon

structure consisting of the following vocational interests: realistic (prefer to work with

things, often outdoors), investigative (enjoy working in scientific disciplines including

mathematics, biology, and physical as well as social sciences), artistic (enjoy creatively

expressing themselves through mediums such as writing, art, and dance), social (enjoy

working with and helping other people), enterprising (enjoy leadership roles that lead to

achieving economic outcomes), and conventional (enjoy working in a well structured

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environment; Holland 1973; Su et al. 2009). Prediger (1982) built upon Holland’s (1973)

framework by providing two dimensions across which these vocational interests can be

measured. These include the ‘‘things—people’’ continuum and the ‘‘data—ideas’’ con-

tinuum. Subsequent researchers have built upon this hexagon by adding job dimensions as

well as specific jobs to the model (Prediger and Vansickle 1992).

Using Holland’s (1973) model of vocational interests as well as Prediger (1982)

‘‘things—people’’ continuum, Su et al. (2009) conducted a meta-analysis on gender dif-

ferences among the STEM (science, technology, engineering, and mathematics) positions.

One of the most striking findings of this meta-analysis was that men preferred to work with

things while women preferred to work with people. This gender difference was one of the

largest found in their study (d = .93). Although these findings address choices at the

occupation level, they can be applied to choices within occupations where there can be

variability in the demands for working with things versus people.

We argue that research/teaching-oriented faculty positions can be categorized along

Prediger (1982) ‘‘things—people’’ and ‘‘data—ideas’’ continuum. More specifically, we

argue that research activities, for the most part involve working with things, with a great

deal of time spent working on a computer, writing and conducting data analysis.

Depending on the nature of the research, there can be laboratory tasks involving the use of

equipment. Teaching (and mentoring) on the other hand, involves a great deal of direct

contact with students. Although certainly some research tasks involve interacting with

others, and teaching involves things other than student contact, the balance of time spent is

quite different. Thus we might expect that, on average, men would display a higher

preference than women for research and women would display a higher preference than

men for teaching.

Moving from vocational interests, we now turn to Burns and Stalker’s (1961) theory on

the distinction between organic and mechanistic structures. This theory provides a well-

established and comprehensive perspective on the work environment (Dickson et al. 2006).

Mechanically-structured organizations are governed by strict rules within a stringent

hierarchical system. In this type of organization, the upper-level management governs the

organization, makes decisions, and dictates these decisions to lower-level employees for

completion, fostering a stable and predictable environment (Cameron and Quinn 1999). In

contrast, jobs are not as rigidly defined within organic structures, and employees each have

an integral knowledge of other employees’ tasks. This type of an organization has fewer

rules and regulations (Mintzberg 1983). While some researchers (i.e., Harrison 1974;

Meadows 1980) suggest that organic structures are associated with improved organiza-

tional attitudes even in academic/research settings, Burns and Stalker (1961) caution that

one type of structure is not superior to the other.

Just as men and women differ in their social preferences in work settings, it seems that

the genders also have different structural preferences. According to Su et al.’s (2009) meta-

analysis, women tend to prefer conventional vocations where the environment is well

structured. Although Su et al. (2009) focused on vocational choice at the occupational

level, these findings can be applied to choices within occupations. More specifically, while

‘‘well structured’’ can refer to the vocational choice, it can also refer to the environmental

structure (e.g., departmental structure) within that vocation.

Gender, Job Satisfaction, and Research Productivity

Previous researchers have found that women report lower levels of job satisfaction and

research productivity than do men (Olsen et al. 1995; Hagedorn 1996; Stack 2004; Hult

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et al. 2005; Smeby and Try 2005; Gardner 2012). Researchers have examined satisfaction

using both global measures of satisfaction as well as more faceted measures (Olsen et al.

1995; Hagedorn 1996; Hult et al. 2005; Seifert and Umbach 2008; Sabharwal and Corley

2009; Yu 2008). For example, using a faceted approach, Seifert and Umbach (2008) found

that women reported lower levels of job satisfaction across more dimensions than did men.

Specifically, women were less satisfied with job autonomy and perceived less equitable

treatment. Sabharwal and Corley (2009) found similar findings. In their study of 2003

doctoral recipients, they found that women reported lower levels of overall job satisfaction

and satisfaction with job security than did men. Regarding productivity, numerous

researchers have found that women have fewer refereed publications than men (Stack

2004; Smeby and Try 2005). A recent study by Diem and Wolter (2013) used the Web of

Science and Google Scholar to examine research performance among faculty in education

sciences in Switzerland. They found that while women faculty members have fewer

publications and citation counts than men, this finding was most pronounced among older

faculty members. Based upon previous research, we expect to replicate these findings.

Hypothesis 1: Women will report lower levels of job satisfaction and lower levels of

productivity than their male counterparts.

Department Differences in Research/Teaching Orientation

Academic departments specifically, and universities more generally, differ in their orien-

tations towards teaching and research. In the current study, we are interested in the

department level’s orientation as the university and departmental context often differ from

one another (Smeby and Try 2005) and it is the department’s orientation that is more likely

to impact individuals in a more proximal manner. For example, some departments place a

strong emphasis on research productivity and require faculty members to be quite prolific,

publishing in high quality journals. In these departments, personnel actions are strongly

based upon the quality and quantity of publications in top peer-reviewed journals,

reflecting the popular phrase: ‘‘publish or perish.’’ In order to emphasize and support this

goal, research-oriented departments tend to provide faculty with smaller teaching loads

(one or two courses per semester) so that they can focus most of their time and energy on

research activities. On the other hand, departments that focus more on teaching place a

premium on faculty members’ teaching skills and the utilization of these skills around the

classroom and related activities. These departments expect faculty members to devote

much time and attention to their students both inside and outside of the formal classroom.

Therefore, teaching-oriented departments usually require faculty to teach a higher course

load (e.g., three or four courses per semester), emphasizing this focus on teaching and

mentoring students as opposed to research. Indeed, a study conducted by the National

Center for Education found that faculty working in more research-oriented universities

taught fewer course per year (1991).

Based upon the required teaching load of a department, it is possible to classify

departments as more teaching- or research-oriented. It should be noted, however, that these

foci are not mutually exclusive as a number of departments define themselves as having

some mixture of research productivity and teaching quality. Therefore, this focus is best

conceptualized as a continuum as opposed to a dichotomy.

A department’s research/teaching orientation is an aspect of the work environment

that may moderate the effect of gender on job satisfaction. Specifically, researchers

suggest that women academics report more job dissatisfaction than their male

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counterparts (Trower and Bleak 2004). These findings occur despite mixed results

found between gender and job satisfaction in the general literature (e.g., Brockner and

Adsit 1986; Witt and Nye 1992). Because women prefer the social interaction of

teaching and mentoring students (Konrad et al. 2000), they may consequently be more

satisfied when they spend more time engaged in these activities. Along these lines,

departments that place a heavy emphasis on teaching, as evidenced by increased

teaching load, may provide better person-organization fit for women, resulting in

higher levels of job satisfaction (Kristof 1996). Specifically, according to social role

theory, men and women are more comfortable with behaviors that are consistent with

their identity (Bem 1974). Because the feminine gender role encourages women to be

compassionate and nurturing, women may have greater comfort with teaching. Con-

versely, men may experience less comfort with teaching, which may decrease job

satisfaction. Olsen et al. (1995), in their study on faculty members in a more research-

oriented university, suggested that fit played a role. More specifically, some women

faculty members reported that women had to be careful in seeming too committed to

teaching because it would be interpreted by others that women faculty members would

be more dedicated to teaching than to research. This seemed to occur despite objective

indices (e.g., publication rates) suggesting the contrary. This is consistent with social

role theory in the sense that women are often expected to be nurturing and therefore

might favor teaching over research.

Hypothesis 2: Department research/teaching orientation will moderate the relationship

between gender and job satisfaction such that women will report higher job satisfaction

when working in teaching-oriented departments, whereas men will report higher job sat-

isfaction when working in research-oriented departments.

The department’s research/teaching orientation might also moderate the relationship

between gender and research productivity. Specifically, women might enjoy better person-

organization fit in teaching-oriented departments (Kristof 1996) because of the emphasis

on teaching and mentoring students. While research productivity can be evaluated in

numerous ways, publication proliferation remains the primary way of evaluating faculty

productivity in terms of tenure and promotion, and is consequently an important criterion

(Todd et al. 2008). Therefore, using publication proliferation as an index of productivity,

we propose that a woman’s research productivity will be similar to men in teaching-

oriented departments. However, in research-oriented departments that provide worse fit for

women, we propose that men will be more productive than women.

Hypothesis 3: Department research/teaching orientation will moderate the relationship

between gender and research productivity such that women will report lower levels of

research productivity in research-oriented departments than will men in research-oriented

departments, but there will be no gender differences in research productivity in teaching-

oriented departments.

Department Differences in Structure

While some researchers (e.g., Harrison 1974; Meadows 1980) suggest that organic

structures are associated with improved organizational attitudes even in academic/research

settings, little, if any, research has been conducted on gender differences and organicity.

Given that uncertainty and ambiguity are commonplace in organic structures (Cameron

and Quinn 1999) and that women tend to prefer conventional vocations where the

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environment is well structured (Su et al. 2009), it is conceivable that women would report

higher levels of job satisfaction and productivity in more mechanistically structured work

environments. Another factor that may contribute to women preferring structure is Ragins’

(1999) finding that early career women have fewer advanced role models to assist them in

understanding the structure than do early career men. Because organically-structured

organizations provide less explicit communication regarding rules than mechanistically-

structured organizations, faculty are more likely to need role models in more organically

structured departments in order to understand the ambiguity inherent to this structure.

Therefore, we hypothesize that women will be more satisfied and productive in mecha-

nistically structured departments than in organically structured departments because the

rules, regulations, and expectations are explicit.

Hypothesis 4: Structure will moderate the relationship between gender and job satis-

faction such that women will be more satisfied than men in mechanistically structured

departments and men will be more satisfied than women in organically structured

departments.

Hypothesis 5: Structure will moderate the relationship between gender and productivity

such that women will be more productive in mechanistically structured departments.

In the current study, we tested these hypotheses using a sample of faculty members

nested in psychology departments. We surveyed faculty members in both the U.S. and

Canada. We build on previous work by examining the role of particular environmental

variables. Our study differs by focusing on preference/fit based upon expected norms as

well as the role of structure.

Method

Participants and Data Collection

A comprehensive online listing of psychology programs located in the United States and

Canada was reviewed to compile faculty contact information for each department (Han-

over College n.d.). Universities with multiple listings, 2-year colleges, and exclusively

French-speaking schools were removed from the original database of 657 psychology

departments, resulting in 585 departments. Two methods were used to survey faculty. First,

a cover letter describing the study and link to the survey was sent to the department chairs.

Each chair was invited to forward the link to all full-time department members and

encourage their participation. Second, a follow-up letter and the survey link was sent

directly to each individual faculty member via e-mail. Additional information about each

department, including location, size, and setting of the university (e.g., rural, urban, or

suburban), was collected via a college directory publication (Barron’s 2005).

In total, surveys were completed by 1,306 faculty members across 373 departments.

Sixty-seven departments had no respondents. Approximately 160 participants were

excluded because they were not full-time psychology faculty members or did not provide

useable responses. Additionally, 114 (77 of which provided usable data) of the solicited

departments were excluded because too few (i.e., less than two) faculty members

responded, making the calculation of department-level variables impossible. We ran t tests

to detect whether there was a significant difference between those departments where two

for more faculty members responded and where only one faculty member responded. For

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job satisfaction, the t test was non-significant and Cohen’s d was .11. The t test for

productivity indicated a significant difference and Cohen’s d was .42. Therefore, it seems

as though faculty in more teaching-oriented departments were less likely to provide

publication data. This could indicate a restriction of range, possibly attenuating our effect

sizes, and making our tests conservative.

The final sample consisted of 1,135 full time, tenured or tenure-track psychology faculty

members working in 229 academic departments. The response rate for individual faculty

was 15.9 % based on the number of completed surveys versus the number of e-mails sent.

This should be considered a lower bound estimate as it is impossible to know how many

e-mails were not received or opened. It should be noted that 56.7 % of departments had at

least one faculty member respond to the survey and 34.9 % of departments had two or

more faculty members responding.

All departments were part of 4-year colleges and universities. One hundred forty-five of

these universities had graduate programs (master’s and/or doctoral). Approximately 30 %

of departments were located in urban areas, another 30 % were located in suburban areas,

25 % were located in rural areas, and 10 % of the departments’ locations were unclassified.

About 67 % of the schools had fewer than 20,000 students enrolled and 63 % of the

schools were public.

The sample of 1,135 faculty members included 550 men and 560 women (the remaining

participants did not report gender). The mean age of faculty members was 46.8 years

(SD = 14.2 years). The sample consisted of 435 full professors, 300 associate professors,

and 342 assistant professors. Additionally, 452 participants reported holding leadership

positions between 2003 and 2005. This variable refers to any leadership position within the

department or school. Examples include but are not limited to area director, program

director, or department chair.

Measures

Department’s Research/Teaching Orientation

In order to determine whether a department is more teaching-oriented or more research-

oriented, faculty members were asked to report their course load. In general, faculty

members within each department reported the same teaching load. In under 2 % of cases,

faculty members reported different teaching loads. In these cases, the modal response was

used. In cases where the mode could not be established, the mean was used. We assume

that a lighter course load occurs in departments where faculty have higher research pro-

ductivity expectations placed on them. This is supported by a study conducted by the

National Center for Education that found that faculty working in more research-oriented

universities taught fewer course per year (1991).

Department Structure

The organizational structure scale used in Khandwalla (1976/1977) was adapted for use in

academic organizations. Participants were asked to rate seven items describing their cur-

rent academic department’s management style using a 1–7 response scale. Low scale

anchors reflected mechanistically structured departments and high scale anchors repre-

sented organically structured departments. Therefore, higher scores indicated more organic

structures. Two sample items include ‘‘strong emphasis on always getting department

members to follow the formally laid down procedures’’ (mechanistic) and ‘‘strong

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emphasis on getting things done even if this means disregarding formal procedures’’

(organic) as well as ‘‘tight formal control of most decisions through formal channels of

authority’’ (mechanistic) and loose, informal control; heavy dependence on informal

relationships and norm of cooperation for getting work done (organic). The observed

Cronbach alpha was .83. Since the structure of the department is conceptualized as a shared

phenomenon, the aggregate ratings of faculty members in each department was calculated

using the mean response. In order for a department to be included in the analyses, at least

two faculty members needed to provide ratings of the structure.

Job Satisfaction

A three-item global measure was used to assess job satisfaction (Cammann et al. 1979). A

sample item is ‘‘in general, I like working here.’’ One item, ‘‘in general, I don’t like my

job,’’ was reverse coded such that higher scores indicate a higher level of satisfaction. The

Cronbach alpha was .85.

Research Productivity

The most commonly used indicator to assess faculty job performance is the number of

peer-reviewed publications (Knights and Richards 2003). In the current study, faculty

members were asked to report the number of peer-reviewed journal publications they

authored between the years of 2003–2005. A higher number of publications indicated a

higher level of research productivity.

Demographic Variables

Participants were asked to report their age, gender, tenure status, and rank.

Analytical Approach

Hierarchical Linear Modeling, and specifically the HLM 7.0 program, was used to conduct

the analyses because individuals are nested within groups (academic departments). In order

to conduct the HLM analyses, we followed a model-building sequence consistent with

Raudenbush and Bryk’s (2002) recommendations.

A number of comments regarding terminology and modeling decisions are warranted at

this point. First, HLM associates variables with levels. Level 1 refers to the individual

level, or in this case, the variables associated with individual faculty members: job sat-

isfaction, research productivity, and gender. Level 2 in this study refers to academic

departments, and variables at this level included the department structure and research/

teaching orientation. Second, all models were run using restricted maximum likelihood

estimation and robust standard errors were used for assessing the significance of the

hypothesized effects. Third, while our hypotheses were tested using fixed effects coeffi-

cients, we specified our models to allow for random effects as well. This means that

variance across departments was allowed in both average levels of the individual-level

outcomes and in the relationships between gender and the individual-level outcomes.

Each model sequence was run twice, once focusing on job satisfaction as the outcome

and once focusing on research productivity as the outcome. The first model run in each

sequence was the fully unconditional model. It specifies an outcome and no predictors at

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either level 1 or level 2. The resulting model is equivalent to a one-way random effects

ANOVA model in which the outcome is modeled as a function of department membership.

This model is used to partition variance in the outcome into its within- and between-

department components. This allows for the calculation of the ICC(1), which indexes the

amount of between-department variance in the outcome. Between-department variance is

necessary to warrant the use of HLM (e.g., Bliese 2000).

The second model run in each sequence added in gender as a level-1 predictor of the

outcome. This allowed us to test Hypothesis 1. It is important to note that in order to

facilitate an understanding of the results, the level-1 independent variable, gender, was

group-mean centered because it was subsequently involved in cross-level interactions, as

specified in Hypotheses 2, 3, 4 and 5. When investigating cross-level interactions, group-

mean centering of level-1 variables is recommended (e.g., Enders and Tofighi 2007;

Hofmann and Gavin 1998).

The third model run in each sequence added in each of department research/teaching

orientation (R/T orientation) and department structure as level-2 predictors. Specifically,

we added the cross-level main effects of each of the two department variables predicting

the outcomes as well as the cross-level interaction effects involving the two department

variables as moderators of the relationship between gender and the outcomes. The cross-

level main effects capture differences in average levels the outcome across departments as

a function of the department variables, while the cross-level interactions capture differ-

ences in the relationship between gender and each of the outcomes across departments as a

function of the departmental variables. Though the cross-level interactions are the effects

of interest as per the hypotheses (i.e., Hypotheses 2–5), it is necessary to control for the

cross-level main effects when estimating and interpreting the cross-level interactions. The

fully specified model takes the following form in equations:

Level 1 : Yij ¼ b0j þ b1j Genderð Þ þ rij ð1Þ

Level 2 : b0j ¼ c00 þ c01 Structureð Þ þ c02 R/T orientationð Þ þ U0j ð2Þ

b1j ¼ c10 þ c11 Structureð Þ þ c12 R/T orientationð Þ þ U1j ð3Þ

Equation 1 is run for each department, relating the outcome of interest to gender. In Eq. 1,

Yij is the outcome of interest (either job satisfaction or research productivity) for individual

i in department j. b0j represents the intercept for department j and captures the average

level of the outcome within department j after accounting for gender. b1j represents the

slope for department j and captures the relationship between gender and the outcome

within department j. rij represents a residual variance term, specifically capturing the

remaining within-department variance in the outcome after accounting for gender.

Equations 2 and 3 comprise the level-2 portion of the model. Equation 2 uses the

intercepts from the within-department regression equations as outcomes. c00 captures the

grand mean of the outcome after accounting for the effects of structure and R/T orientation.

c01 and c02 capture the cross-level main effects of structure and R/T orientation, respec-

tively, on the between-department differences in average levels of the outcome. These ccoefficients represent fixed effects. U0j is a residual variance term that captures remaining

between-department variance in average levels of the outcome after accounting for the

effects of the included predictors. This residual variance term represents a random effect.

Equation 3 uses the slopes from the within-department regression equations as outcomes.

c10 captures the pooled slope relating gender and the outcome within department after

accounting for the effects of structure and R/T orientation. c11 and c12 capture the cross-

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level interactions of structure and R/T orientation, respectively, on the within-department

relationship between gender and the outcome. U1j is a residual variance term that captures

remaining between-department variance in the within-department relationship between

gender and the outcome after accounting for the effects of the included predictors. As

before, the c coefficients represent fixed effects and U1j represents a random effect. When

modeling job satisfaction and productivity as an outcome, c10 is used to test Hypothesis 1,

c11 is used to test Hypothesis 2, and c12 is used to test Hypothesis 4. When using research

productivity as the outcome, c10 is used to test Hypothesis 1, c11 is used to test Hypothesis

3, c12 and is used to test Hypothesis 5.

Results

Tables 1 and 2 show the descriptive statistics and correlations among level-1 and level-2

study variables, respectively. In Table 1, it should be noted that correlations between

gender and other study variables are quite small. However, there are statistically significant

differences to note. In particular, men reported being more satisfied in their jobs and more

productive in their research. Men also reported holding higher ranks (i.e., full professor)

than did women.

Table 1 Descriptive statistics and correlations among level 1 variables

Mean SD N 1 2 3 4 5 6

1. Jobsatisfaction

15.33 3.22 925 –

2. Productivity 5.16 5.09 806 .01 –

3. Gender .50 .50 1,110 -.07* -.14** –

4. Age 46.83 14.15 1,107 -.05 .05 -.16** –

5. Rank 1.98 .92 1,132 -.01 -.20** .17** -.29** –

6. Leadership .59 .49 1,115 .00 -.05 .06* -.21** .17** –

* p \ .05; ** p \ .01; N’s range from 714 to 1,132 and indicate number of faculty members responding;Gender: 0 = men, 1 = women; Rank: 1 = full professor, 2 = associate professor, 3 = assistant professor,4 = other; Leadership: 0 = held leadership position, 1 = did not hold a leadership position

Table 2 Descriptive statistics and correlations among level 2 Variables

Mean SD N 1 2 3 4 5 6

1. Location – – – –

2. Sector – – – .16* –

3. R/T orient. 2.50 .83 220 .14* -.02 –

4. Structure 29.72 4.76 217 .02 .24* -.06 –

5. Job satisfaction 15.24 1.86 209 .11 .20* -.03 .35** –

6. Productivity 5.08 3.65 189 .00 -.07 -.59 -.07 -.04 -

* p \ .05; ** p \ .01; N’s range from 186 to 221 and refer to the number of departments included;Location: 1 = urban, 2 = suburban; Sector: 1 = public, 2 = private; Orientation refers to research vteaching orientation. R/T Orient. = Research/Teaching Orientation of Department; Productivity refers toresearch productivity

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The results of the HLM models specifying job satisfaction as an outcome are reported in

Table 3. The coefficients, their specific meaning, and their relationship to the hypotheses

are as described above in the section on the analytical approach. From Model 1, the ICC(1)

was calculated as .01, indicating that only 1 % of the variance in job satisfaction resides

between departments. While this value is certainly below what would typically be needed

to justify the use of HLM (e.g., Bliese 2000), this indicates that there is little between-

department variance in average levels of job satisfaction. However, it does not indicate the

absence of between-department variance in the within-department relationship between

gender and job satisfaction. Thus, we examined the other two models for purposes of

testing Hypotheses 1, 3 and 5. Model 2 results do not provide support for Hypothesis 1 as

gender was unrelated to job satisfaction (c10 = -0.06, n.s.). Moving to Model 3 results,

Hypothesis 2 was fully supported as women reported being more satisfied working in more

teaching-oriented departments than did men (c12 = 0.92, p \ .05). That is, women faculty

members had higher levels of job satisfaction in more teaching-oriented departments,

whereas men had higher job satisfaction in more research-oriented departments (Fig. 1).

However, Hypothesis 4 was not supported, as department structure had no impact on the

relationship between gender and job satisfaction (c11 = 0.0, n.s.). While not related to any

hypothesis, it might be worth noting that there is a significant effect of structure on job

satisfaction (c01 = 0.14, p \ .05), suggesting that that average levels of job satisfaction are

higher in departments with more organic structures.

The results of the HLM models specifying research productivity as an outcome are

reported in Table 4. The coefficients, their specific meaning, and their relationship to the

hypotheses are as described above in the section on analytical approach. From Model 1, the

ICC(1) was calculated as .21, indicating that 21 % of the variance in research productivity

resides between departments. This value exceeds typical cutoffs justifying the use of HLM

(e.g., Bliese 2000), though, as before, it does not address the between-department variance

Table 3 Job satisfaction as outcome variable

Model 1 Model 2 Model 3

Fixed effects

For intercept (b0j)

Intercept (c00) 15.35 (0.12)** 15. 34 (0.12)** 11.03 (0.91)**

Structure (c01) 0.14 (0.12)**

R/T orientation (c02) 0.04 (0.03)

For gender slope (b1j)

Gender (c10) -0.06 (0.31) -2.13 (2.23)

Structure (c11) 0.00 (0.07)

R/T orientation (c12) 0.92 (0.39)*

Random effects

Intercept (l0j) 0.15 (0.39) 0.34 (0.58) 0.10 (0.32)

Gender slope (l1j) 3.25 (1.80)** 2.98 (1.73)**

Level-1 (rij) 9.92 (3.15) 9.23 (3.04) 9.10 (3.02)

R/T Orientation = Research/Teaching Orientation. Entries show parameter estimates with robust standarderrors in parentheses

Gender was group-mean centered

** p \ .01; * p \ .05

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in the within-department relationship between gender and research productivity. We

examined the other two models for the purposes of testing Hypotheses 1, 3 and 5. Model 2

results do not provide support for Hypothesis 1 as gender was not significantly related to

research productivity (c10 = -0.66, p \ .05). Specifically, this result shows that men did

not report higher levels of research productivity than did women. With respect to the other

results from Model 3, Hypothesis 3 approached significance (c12 = 0.86, p \ .10; Fig. 2)

as men working in more research-oriented departments reported higher levels of research

productivity than did women working in more research-oriented departments. Finally, from

Model 3, results do not support Hypothesis 5 as there was no moderating effect of

1.50 2.00 2.50 3.00 3.5014.88

15.12

15.37

15.62

15.86

Research/Teaching Orientation

Job

Sat

isfa

ctio

n

Men

WomenFig. 1 Moderation results forgender, research/teachingorientation, and job satisfaction

Table 4 Research productivity as outcome variable

Model 1 Model 2 Model 3

Fixed effects

For intercept (b0j)

Intercept (c00) 5.15 (0.25)** 5.15 (0.25)** 13.02 (1.14)**

Structure (c01) -0.03 (0.03)

R/T orientation (c02) -2.82 (0.22)**

For gender slope (b1j)

Gender (c10) -0.66 (0.45) 0.00 (2.70)

Structure (c11) -0.10 (0.08)

R/T orientation (c12) 0.86 (0.50)^

Random Effects

Intercept (l0j) 5.85 (2.42)** 5.94 (2.44)** 1.54 (1.24)^

Gender slope (l1j) 2.84 (1.69) 3.52 (1.88)

Level-1 (rij) 21.66 (4.65) 21.00 (4.58) 20.44 (4.52)

R/T Orientation = Research/Teaching Orientation. Entries show parameter estimates with robust standarderrors in parentheses. Gender was group-mean centered

** p \ .01; * p \ .05; ^ p \ .10

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department structure on the within-department relationship between gender and research

productivity (c11 = -0.10, n.s.).

Discussion

Although women have certainly made progress over the past 40 years, researchers suggest

that discrepancies still exist. Within academia, researchers have indicated that women hold

only 36 % of all tenure-line faculty positions and 20 % of full professor positions (Sax

et al. 2002; National Center for Education Statistics 2005; Sallee 2012). Additionally,

women tend to have lower levels of research productivity than their male counterparts

(Stack 2004). In the current study, we chose to focus on a single department, psychology,

because they have roughly equal distributions of men and women (Wicherski et al. 2003)

and because psychology, as a discipline, has displayed a sensitivity to gender issues.

Despite this, our findings reveal a few key gender differences within psychology depart-

ments. Specifically, zero-ordered correlations indicated that men reported being more

satisfied in their jobs and more productive in their research. Men also reported holding

higher ranks (i.e., full professor) than did women. Subsequent analyses also indicated that

women were more likely to report working in teaching-oriented departments than were

men.

In an attempt to understand the underlying mechanisms affecting these relationships, we

focused on environmental factors (structure and teaching focus of the department) within

the departments. Su et al. (2009) proposed and found support for the idea of differences in

gender vocational preferences. Specifically, they found that men preferred working with

things while women preferred working with people. We applied this line of reasoning to

departments, arguing that research/teaching-oriented departments can be categorized along

Prediger (1982) ‘‘things—people’’ and ‘‘data—ideas’’ continua. Specifically, we suggest

that, for the most part, research activities, involve working with things and data with a

great deal of time spent working on a computer, writing and conducting data analysis.

However, teaching (and mentoring) involves a great deal of direct contact with students.

1.50 2.00 2.50 3.00 3.502.04

3.66

5.28

6.90

8.53

Research/Teaching Orientation

Pro

du

ctiv

ity

Men

Women

Fig. 2 Moderation results forgender, research/teachingorientation, and productivity

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Based upon Su et al. (2009), we expected that women would be more satisfied working in

teaching-oriented departments while men would be more satisfied working in research-

oriented departments. We found some support for this notion as women had significantly

higher levels of job satisfaction in teaching-oriented departments whereas men reported

higher levels of job satisfaction in more research-oriented departments. Regarding pro-

ductivity, within research-oriented departments, men and women reported different levels

of productivity with men averaging 1.5 more publications than women within the 3 year

period.

Underlying these gender differences and the reasons behind them are important salary

implications. Specifically, positions within research-oriented universities (i.e., lower

teaching loads) often pay higher salaries than positions in teaching-oriented universities. If

women prefer working in (and are more successful in) teaching-oriented departments/

universities, they will most likely earn lower salaries than colleagues in research-oriented

departments/universities.

Note though that we still do not have an underlying explanation for these observed

gender differences. This underlying explanation is quite important for numerous reasons. If

these preferences are biologically based, then the discrepancy in salaries is unrelated to the

‘‘glass-ceiling.’’ However, if women are encouraged throughout their lives to assume more

‘‘people’’ oriented positions where they might earn lower salaries, this is an issue that

needs to be rectified by reconsidering gender norms and roles. Given that it is widely

accepted that both biological and environment factors explain behavior, it make sense to

conclude that some aspect of these vocational choices have been encouraged by society (Su

et al. 2009).

It is important to note that our hypotheses regarding department structure were

unsupported. One significant finding of note though is that there was a significant rela-

tionship between structure and job satisfaction. That is faculty members reported higher

levels of job satisfaction in more organically structured departments. This finding is in line

with previous researchers (i.e., Meadows 1980). Perhaps different moderators such as

mentoring, motivation, and self-confidence could have affected the observed relationships.

For example, it is possible that mentoring is more important in organically structured

departments where rules and regulations are less clear. In such cases, mentors would be

helpful to acclimate new faculty members and might even have an effect on productivity.

Theoretical Implications

Meadows (1980) suggested that employees in more organically structured organizations

reported higher levels of job satisfaction. Although the current study found support for

these findings, the findings should be viewed cautiously. Specifically, both faculty mem-

bers and employees in non-academic settings choose to remain in their current department

and organization. This suggests that the fit between the employee and the department/

organization is an important consideration.

Contrary to a previous study, organic structures did not facilitate productivity (Harrison

1974). One potential explanation for the discrepancy is the use of subjective indices of

performance in previous research (Harrison 1974). Another explanation is that some

researchers have overlooked the component of Burns and Stalker’s (1961) theory that

indicates that one structure is not necessarily preferable over the other and that the type of

structure to be implemented is dependent upon a number of factors. This is an important

point since many researchers seem to show an almost universal preference for organically

structured organizations.

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A more general theoretical implication of the current study concerns the gender-job

satisfaction relationship. Researchers have studied gender differences in job satisfaction

and have found mixed results (e.g., Brockner and Adsit 1986; Witt and Nye 1992). One

limitation of many of these studies is that gender was confounded with job type. Often,

women were overrepresented at lower levels of organizations or in different job types than

men. An advantage of the current study is that all participants worked in the same job, that

of a professor in a psychology department, in the same discipline. While gender was

confounded with age and rank, controlling for those variables in additional analyses did not

explain our gender differences. Our results suggested that women were somewhat less

satisfied with their faculty jobs than were men. An additional finding was that men and

women appear to have somewhat different work preferences and the impact of the job

environment varied to some extent between men and women.

Limitations and Opportunities for Future Research

One limitation of the current study is the potential for coverage error (Groves et al.

2009). Although we surveyed faculty in two different ways (via their department chair

and directly by email), it is possible that faculty did not have the chance to participate in

the current study. For example, new faculty and new department chairs might not have

been listed on the department website. Additionally, since faculty members could have

been contacted twice, it is possible that some faculty members completed the survey

twice without realizing it. Along these lines, it is also possible that faculty with fewer

publications were less likely to participate because they were uncomfortable sharing this

information. Indeed, among faculty who responded, many declined to include their

number of publications. This could have affected the results as small sample sizes could

affect the power and at least partially explain nonsignificance in some of the HLM

analyses.

Another related limitation concerns nonresponse bias at the department level. Specifi-

cally, we only included departments with multiple members responding to the survey. In

larger departments, there was a better chance of multiple faculty members replying to the

survey than in smaller departments. Therefore, it is possible that our sample is skewed in

favor of including larger departments over smaller departments. This could affect the

results as it is likely that larger departments have more resources that could result in higher

levels of job satisfaction and/or productivity (Gardner 2012).

An additional limitation was the narrow focus on psychology departments. Although the

data supported that women faculty tended to cluster at lower academic ranks and report

lower research productivity, these differences might not generalize to other disciplines.

Additional data are needed from a variety of departments with greater gender imbalance

than psychology to determine the extent to which gender representation is associated with

differences in outcome variables. It would also be informative to investigate the impact of

organizational structure in nonacademic organizations, particularly those where women

continue to have difficulties progressing in their careers. Along these lines, as women

become more represented in academia, it is certainly possible that these findings could

change.

Another limitation is the generalizability of research productivity as a career outcome.

Although commonly used as a measure of performance, research productivity is only one

of several measures used to evaluate performance. For example, teaching effectiveness is

an important part of faculty performance, especially in more teaching-oriented depart-

ments. It is important to note that Hattie and Marsh’s (1996) meta-analysis indicated that

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no relationship existed between teaching and research. Therefore, the results could have

been different using measures of teaching effectiveness as outcome indicators. Addition-

ally, regarding research productivity, there is evidence that men and women place different

levels of importance on this criterion (Todd et al. 2008). Accordingly, the mechanism by

which women produce fewer scholarly journal articles remains unclear. For example,

women may be thwarted from attempts to increase their productivity by organizational

boundaries, may choose to or are encouraged to focus their efforts on other professional

tasks, or may be more likely to seek/retain employment at a university that requires fewer

publications. On the other hand, women may put in the same amount of effort, but might

use strategies that focus more on quality than quantity, for example, by conducting long-

term longitudinal studies. Another possibility is that women are disproportionally in

subdisciplines where publication is less frequent. Future research examining career choice

through the life span and career strategies may help address some of these questions.

Another limitation of the current study is that we do not address the interacting role of

self-confidence and gender preferences. Multiple researchers have suggested that women

have lower levels of self-confidence than do men (Gibson and Lawrence 2010; Ahlgren

1983; Heatherington et al. 1993; Lenney 1977). Within academia, women may be guided

towards teaching by their advisors (Trix and Psenka 2003). Couple with the difficult nature

of the peer-reviewed publication process, it is possible that women believe they are

incapable of publishing in the top-tiered journals that research-oriented departments

require. Therefore, women may self-select out of research-oriented departments in favor of

more teaching-oriented ones as a teaching-oriented setting would provide women faculty

members the ability to spend more time teaching and mentoring students (consistent with

social role theory) and would provide immediate performance feedback that could help

bolster self-confidence. Future research should incorporate gender, age, tenure, self-con-

fidence, and doctoral advising/mentoring in order to better understand how these variables

interact.

Finally, we did not directly assess vocational preferences. Rather, we focused on the

more general idea that teaching-oriented departments require faculty members to spend

more time teaching and mentoring students while research-oriented departments require

faculty members to engage in research activities that are more solitary in nature. We

recognize that researchers have some social interaction when collaborating but the vast

majority of time is spent engaging in solitary activities like data analysis and writing.

Therefore, there is some gray area in this classification.

Conclusion

Almost 100 years ago, Thorndike (1911) stated that ‘‘the greatest difference between men

and women is in the relative strength of the interest in things and their mechanisms

(stronger in men) and the interest in persons and their feelings (stronger in women)’’ (Su

et al. 2009, p. 861). A century later, researchers (e.g., Su et al. 2009) are finding support in

the workplace for this observation. We too found support, albeit somewhat indirect, for

such gender differences. Our study differed from previous lines of research in that we

explored this idea in greater depth by focusing on a single vocation. Specifically, we

focused on gender differences, environmental characteristics, job satisfaction and pro-

ductivity within psychology departments. Our study updates previously reported gender

differences among faculty, showing that on average women publish less than do men,

although the differences are small and dependent on contextual variables. This is important

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because of demographic trends in career choice and attainment over time might tend to

erase such differences. Additionally, the current study showed that contextual variables

affect outcomes for women faculty members. Although research/teaching orientation and

structure do not comprehensively explain gender differences in academia, the current study

provides some evidence that subtle, perhaps inherent, aspects of the work environment do

differentially affect men and women faculty members.

References

Ahlgren, A. (1983). Sex differences in the correlates of cooperative and competitive school attitudes.Developmental Psychology, 19, 881–888.

August, L., & Waltman, J. (2004). Culture, climate, and contribution: Career satisfaction among femalefaculty. Research in Higher Education, 45, 177–192.

Barbezat, D. A., & Hughes, J. W. (2005). Salary structure effects and the gender pay gap in academia.Research in Higher Education, 46, 621–640.

Barron’s. (2005). Barron’s profiles of American colleges (26th ed.). Oxnard, CA: Barron’s EducationalSeries, Inc.

Bem, S. L. (1974). The measurement of psychological androgyny. Journal of Consulting and ClinicalPsychology, 42(2), 155–162.

Benschop, Y., & Brouns, M. (2003). Crumbling ivory towers: Academic organizing and its gender effects.Gender, Work & Organization, 10(2), 194–212.

Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for dataaggregation and Analysis. In K. J. Klein & S. W. Kozlowski (Eds.), Multilevel theory, research, andmethods in organizations (pp. 349–381). San Francisco, CA: Jossey-Bass, Inc.

Brockner, J., & Adsit, L. (1986). The moderating effect of gender on the equity-satisfaction relationship.Journal of Applied Psychology, 71, 585–590.

Burns, T., & Stalker, G. M. (1961). The management of innovation. Oxford: Oxford University Press.Cameron, K. S., & Quinn, R. E. (1999). Diagnosing and changing organizational culture: Based on the

competing values framework. Englewood Cliffs, NJ: Prentice Hall.Cammann, C., Fichman, M., Jenkins, D., & Klesh, J. (1979). The Michigan Organizational Assessment

Questionnaire. Ann Arbor: University of Michigan (Unpublished manuscript).Dickson, M. W., Resick, C. J., & Hanges, P. J. (2006). Systematic variation in organizationally-shared

cognitive prototypes of effective leadership based on organizational form. Leadership Quarterly, 17(5),487–505.

Diem, A., & Wolter, S. C. (2013). The use of bibliometrics to measure research performance in educationsciences. Research in Higher Education, 54, 86–114.

Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: Anew look at an old issue. Psychological Methods, 12, 121–138.

Etzkowitz, H., Kemelgor, C., & Uzzi, B. (2000). Athena unbound: The advancement of women in scienceand technology. London: Cambridge Press.

Gardner, S. K. (2012). ‘‘I couldn’t wait to leave the toxic environment’’: A mixed methods study of womenfaculty satisfaction and departure from one research institution. NASPA Journal About Women inHigher Education, 5, 71–95.

Gibson, D. E., & Lawrence, B. S. (2010). Women’s and men’s career referents: How gender compositionand comparison level shape career expectations. Organization Science, 21(6), 1159–1175.

Groves, R. M., Fowler, F. J. J., Couper, M. P., Lepkowski, J. M., Singer, E., & Tourangeau, R. (2009).Survey methodology (2nd ed.). Hoboken, NJ: Wiley-Interscience.

Hagedorn, L. S. (1996). Wage equity and female faculty job satisfaction: The role of wage differentials in ajob. Research in Higher Education, 37, 569–598.

Hanover College (n.d.). Alphabetical listing of psychological departments. Retrieved February 18, 2009.http://psych.hanover.edu/Krantz/othera-z.html.

Harrison, F. (1974). The management of scientists: Determinants of perceived role performance. Academy ofManagement Journal, 17(2), 234–241.

Hattie, J., & Marsh, H. W. (1996). The relationship between research and teaching: A meta-analysis. Reviewof Educational Research, 66, 507–542.

Res High Educ (2014) 55:351–369 367

123

Heatherington, L., Daubman, K. A., Bates, C., Ahn, A., Brown, H., & Preston, C. (1993). Two investigationsof ‘‘female modesty’’ in achievement situations. Sex Roles, 29, 739–754.

Hofmann, D. A., & Gavin, M. B. (1998). Centering decisions in hierarchical linear models: Implications forresearch in organizations. Journal of Management, 24, 623–641.

Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice-Hall.Hult, C., Callister, R. R., & Sullivan, K. (2005). Is there a global warming toward women in academia?

Liberal Education, 91, 50–57.Hyde, J. S., Hall, C. C. I., Fouad, N. A., Keita, G. P., Kite, M. E., Russo, N. F., et al. (2002). Women in

academe: Is the glass completely full? American Psychologist, 57(12), 1133–1134.Khandwalla, P. N. (1976/1977). Some top management styles, their context and performance. Organization

for Administrative Sciences, 7, 21–51.Knights, D., & Richards, W. (2003). Gender discrimination in UK academia. Gender, Work & Organization,

10(2), 213–238.Konrad, A. M., Ritchie, J. E, Jr, Lieb, P., & Corrigall, E. (2000). Gender differences and similarities in job

attribute preferences: A meta-analysis. Psychological Bulletin, 126(4), 593–641.Kristof, A. L. (1996). Person-organization fit: An integrative review of its conceptualizations, measurement,

and implications. Personnel Psychology, 49, 1–49.Lenney, E. (1977). Women’s self-confidence in achievement settings. Psychological Bulletin, 84, 1–13.Meadows, I. S. G. (1980). Organic structure and innovation in small work groups. Human Relations, 33,

369–382.Mintzberg, H. (1983). Power in and around organizations. Englewood Cliffs, NJ: Prentice Hall.National Center for Education Statistics. (2005). Profiles of Faculty in Higher Education Institutions.

(Washington, DC, August 1991), p. 70.Olsen, D., Maple, S. A., & Stage, F. K. (1995). Women and minority faculty job satisfaction: Professional

role interests, professional satisfactions, and institutional fit. The Journal of Higher Education, 66,267–293.

Prediger, D. J. (1982). Dimensions underlying Holland’s hexagon: Missing link between interests andoccupations? Journal of Vocational Behavior, 21, 259–287.

Prediger, D. J., & Vansickle, T. R. (1992). Locating occupations on Holland’s hexagon: Beyond RIASEC.Journal of Vocational Behavior, 40, 111–128.

Ragins, B. R. (1999). Gender and mentoring relationships: A review and research agenda for the nextdecade. In G. N. Powell (Ed.), Handbook of gender and work (pp. 347–370). Thousand Oaks, CA:Sage Publications, Inc.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysismethods. London: Sage Publications.

Sabharwal, M., & Corley, E. (2009). Faculty job satisfaction across gender and discipline. The SocialScience Journal, 46, 539–556.

Sallee, M. (2012). The ideal worker or the ideal father: Organizational structures and culture in thegendered university. Research in Higher Education, Online First, 1–21. Retrieved from http://www.springerlink.com/content/j854275370618222/fulltext.pdf.

Sax, L. J., Hagedorn, L. S., Arredondo, M., & Dicrisi, F. A, I. I. I. (2002). Faculty research productivity:Exploring the role of gender and family-related factors. Research in Higher Education, 43, 423–446.

Seifert, T. A., & Umbach, P. D. (2008). The effects of faculty demographic characteristics and disciplinarycontext on dimensions of job satisfaction. Research in Higher Education, 49, 357–381.

Smeby, J.-C., & Try, S. (2005). Departmental contexts and faculty research activity in Norway. Research inHigher Education, 46, 593–619.

Stack, S. (2004). Gender, children and research productivity. Research in Higher Education, 45, 891–920.Stewart, A., & LaVaque-Manty, D. (2008). Advancing women faculty in science and engineering: An effort

in institutional transformation. In H. Watt & J. Eccles (Eds.), Gender and occupational outcomes (pp.299–322). Washington, DC: APA Press.

Su, R., Rounds, J., & Armstrong, P. I. (2009). Men and things, women and people: A meta-analysis ofgender differences in interests. Psychological Bulletin, 135, 859–884.

Thorndike, E. L. (1911). Individuality. Boston: Houghton Mifflin.Todd, Z., Madill, A., Shaw, N., & Bown, N. (2008). Faculty members’ perceptions of how academic work is

evaluated: Similarities and differences by gender. Gender Roles, 59(11–12), 765–775.Trix, F., & Psenka, C. (2003). Exploring the color of glass: Letters of recommendation for female and male

medical faculty. Discourse & Society, 14(2), 191–220.Trower, C. A., & Bleak, J. L. (2004). Study of new scholars, gender: Statistical report [Universities].

Cambridge, MA: Harvard Graduate School of Education.

368 Res High Educ (2014) 55:351–369

123

Van Anders, S. M. (2004). Why the academic pipeline leaks: Fewer men than women perceive barriers tobecoming professors. Gender Roles, 51(9–10), 511–521.

Wicherski, M., Guerrero, R., & Kohout, J. (2003). 1999–2000 Faculty salaries in graduate departments ofpsychology. Washington, DC: American Psychological Association.

Witt, L. A., & Nye, L. G. (1992). Gender and the relationship between perceived fairness of pay orpromotion and job satisfaction. Journal of Applied Psychology, 77, 910–917.

Yu, Y. J. (2008). Gender disparity in stem disciplines: A study of faculty attrition and turnover intentions.Research in Higher Education, 49, 607–624.

Res High Educ (2014) 55:351–369 369

123