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4
Professional Activities, Institutional Resources,
Climate, and Outcomes
Once Ph.D.s have been hired into an academic position, it is natural to ask. what
happens next? The milestones of an academic career are hiring, tenure, and promotion.
In the context of these decisions, a primary question must be whether male and female
faculty are treated similarly while they are employed. Is the day-to-day experience of
being a faculty member similar for men and women?
Equitable treatment and opportunity are important for several reasons. First, how
a faculty member is treated affects the ability of that faculty member to do the best
research and teaching of which he or she is capable. This in turn affects subsequent
decisions on the part of the university about salary, tenure, and promotion. It also affects
subsequent decisions on the part of the faculty member about whether to entertain outside
offers and whether to leave that university for a position elsewhere. Furthermore, the
equitability with which a faculty member is treated can contribute powerfully to whether
a faculty member feels he or she is a central part of the enterprise, as well as to the
faculty member’s sense of well-being and satisfaction with his or her professional life.
As noted in Chapter 1, there was anecdotal evidence that women do not fare as
well as men professionally, but such differences can be subtle and hard to detect. The
survey data presented in this report will provide information that is relevant to this
perception and help clarify the current status for women in the six disciplines surveyed at
Research Intensive (RI) institutions. According to one commentator:
The study initiated at the Massachusetts Institute of Technology (MIT)
several years ago by Nancy Hopkins has now been replicated at several
other institutions, including Cal Tech. The reports have shown that women
in science and engineering faculty are more likely to report that they feel
marginalized and isolated at their institution, have less job satisfaction,
have unequal lab space, unequal salary, unequal recognition through
awards and prizes, unequal access to university resources, and unequal
invitations to take on important administrative responsibilities, especially
those that deal with the future of the department or the research unit. The
fact that this study has been replicated at other institutions says that this is
not an MIT specific problem. This is a generalized problem about the way
women faculty at research-intensive universities experience their career
environment (Tilghman, 2004:9).1
1
Shirley Tilghman, “Ensuring the Future Participation of Women in Science, Mathematics, and
Engineering,” in National Research Council, The Markey Scholars Conference: Proceedings. Washington,
DC: National Academies Press, 2004, pp. 7-12.
65
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66 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
This chapter examines variables that could contribute to a faculty member’s
ability to excel at teaching and research. It asks about factors related to equitable
treatment of male and female faculty at Research Intensive universities in the six
disciplines surveyed, whether there are gender differences in salary, publications, or the
inclination to remain at that university, and whether differential treatment accounts for
any gender differences in salary, publications, or the inclination to move on. The
variables of primary interest to us fall into three categories: professional life, institutional
resources, and climate. Under professional life, we include how much of each of the
following a faculty member does: the amount of research; the amount of teaching,
advising, supervising, and mentoring; and the amount of service to the university or
broader community. Under institutional resources sometimes provided to support a
faculty member’s teaching and research, we include start-up funds, summer salary, travel
funds, reduced teaching loads, laboratory space and equipment, and staff (postdocs,
research assistants, clerical support). Under climate, we include variables that can
contribute to a faculty member’s sense of engagement or marginalization within the
department and the institution, such as whether the faculty member is mentored by more
experienced colleagues, whether the faculty member is asked to contribute to important
decisions in the department and the university, and whether a faculty member regularly
engages in conversation about research and teaching with his or her colleagues.
Three initial comments are necessary prior to proceeding with the assessment.
First, there are dozens of factors that together comprise a faculty member’s job, from the
number of students she teaches, to whether she has the newest equipment in her lab, to
whether she thinks her peers are collegial. One major benefit that studies of hiring,
tenure, and promotion have is that there is a dichotomous end point that helps to focus
attention. The study of professional activities, institutional resources, climate, and
outcomes lacks this. Therefore, anchoring the analysis is somewhat more challenging.
Second, the following analysis is descriptive. Essentially, what is reported here about
professional life, institutional resources, and climate is the average response of male and
female faculty to a series of questions about their work habits and environment. In the
final section of this chapter, we look at how professional life, institutional resources, and
climate contribute to important outcomes, such as research productivity and salary. In
these analyses, we attempt to control for as many factors as we can that might contribute
to the outcome, but it is likely that there are additional relevant variables about which we
have no data. Without all relevant controls accounted for in the analysis, the results need
to be taken as preliminary and as an impetus for further, more sophisticated research,
rather than a definitive statement on the existence of disparities between male and female
faculty. Finally, it should be noted that the analyses presented here provide an
aggregated, often average, view. That view is not inconsistent with some women having
very few resources and some women having quite a lot, nor does it negate the possibility
that individual women (or men) are discriminated against in their access to resources.
The deviation around average individual accounts of satisfaction or dissatisfaction can
reflect a difficult reality, even when the averages among male and female faculty are the
same.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 67
The next three sections focus on professional activities, institutional resources,
and climate issues. Professional activities include teaching, research, and service.
Institutional resources cover a gamut of variables, including lab space, start-up packages,
and research assistants. Climate focuses on such issues as mentoring and collegiality.
Several of the above factors are further disaggregated into a variety of component
elements. To study whether male and female faculty members reported different
experiences on these dimensions and variables, we examine four types of information.
First and foremost is our survey of faculty in six disciplines in RI universities.2 A second
valuable resource is the U.S. Department of Education’s National Survey of
Postsecondary Faculty (NSOPF), undertaken in 2004 (“NSOPF:04”).3 That survey
queried respondents regarding the Fall 2003 term and thus occurred in a similar
timeframe as the faculty survey. The other two information sources used throughout the
chapter are individual research studies undertaken by scholars and gender equity reports
completed by RI universities.
After reviewing the three elements of day-to-day careers, we turn our attention to
faculty outcomes. In the fourth section, we ask whether there are differences between
male and female faculty in publication rates, grant funding, laboratory space (which is
both an institutional resource and an outcome), nominations for honors and prizes, salary,
outside offers, or the inclination to remain at the current institution, and which
professional life qualities, institutional resources, or climate variables contribute to
differences in these outcome variables. This section draws on research done by
individuals or as part of institutional studies to examine the issues of retention and job
satisfaction, as our survey did not gather data on these variables.
PROFESSIONAL ACTIVITIES
In this section, we examine the three key areas of professional activities that
characterize the day-to-day job of a faculty member: teaching, service, and research.
Different departments weigh the value of these three activities differently, but in the RI
institutions, research is likely to be a primary concern. It is commonly believed that
women spend more time teaching or performing service-related activities and less time
on research than male faculty.
A note about time spent in professional activities is necessary. There are two
ideas here: how many hours male and female faculty work and how they divide up the
time they spend. Several studies have looked at the number of hours male and female
faculty work and have found they tend to work long hours and similar numbers of hours.
For example, a self-assessment conducted by the University of Pennsylvania found both
men and women work nearly 60 hours per week. The NSOPF:04 found that full-time,
2
Because we performed a large number of t-tests on our faculty survey data, we will only report as
significant those results with p<.05 in order to protect ourselves from false positives. Results near p<.05
will be reported as approaching significance. For the regression analyses on our survey data, reported in
the final outcomes section of this chapter, we will report any results with p<.05 as significant. The reader
will want to note that there are some instances in which the differences are statistically significant, but the
absolute differences are quite small.
3
We also performed a large number of t-tests on the NSOPF:04 data, so we followed the rule for reporting
significance in these data that is described in the previous footnote.
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68 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
professoriate faculty at RI institutions in S&E worked about 58 hours per week on
average (58.5 for women and 58.1 for men).4 Rather than ask faculty members how
many hours they work, our survey asked respondents how they divide their time among
research, teaching, and service. That is what we report here.
Research
It is often assumed men spend a greater percentage of their time doing research
than women. The percentage of time spent on research or scholarship was combined with
percentage of time spent seeking funding in our survey data. Overall, men reported
spending a slightly greater percentage of their time on research activities than women:
42.1 compared to 40.0 percent. This difference, while approaching significance, is quite
small in absolute terms. Drawing on similar faculty from the NSOPF:04, there was no
significant difference between men and women in the time spent on research activities:
43.2 to 39.7 percent.5 It is worth noting the overall percentage of time faculty report
spending on research activities is remarkably similar in the two surveys.6
Figure 4-1 shows the reported percentage time spent by faculty in research
activities (including preparation of grant and contract proposals) disaggregated by gender
and by discipline. Averages were computed over faculty who provided this information
on the survey. To investigate whether there are differences in the percentage of time
spent in research across disciplines or across genders, we fitted a simple linear model
with percent time as the response variable and with discipline, gender, and the interaction
between discipline and gender as the effects. We found no significant differences in
percentage time spent in research, either across disciplines or between genders within
discipline. Because comparing genders within discipline involved carrying out six
comparisons, we used the Tukey-Kramer approach7 to adjust the individual p-values. The
smallest of the six p-values was obtained when comparing men and women faculty in
chemistry (p-value = 0.217). All other p-values were above 0.35. Please note that
discipline and gender accounted for a very small (about 2 percent) proportion of the
variability observed in self-reported time spent in research activities. Thus, these p-
values are to be interpreted cautiously. A model in which other potential confounders are
also included is presented later in this chapter.
4
Data was created using the Department of Education’s Data Analysis System (DAS) available online at:
http://www.nces.ed.gov/dasol/. Gender was used as the row variable. The column variable was average
total hours per week worked. Filters were: only Research I institutions; full-time employed; with faculty
status; assistant, associate, or full professors; with instructional duties for credit; and with principal fields of
teaching as engineering, biological sciences, physical sciences, mathematics, and computer sciences.
5
See previous footnote on how the DAS analysis was conducted.
6
The committee acknowledges that the p-values for all of the data presented for its faculty and
departmental surveys are unadjusted and the fact that many of the data presented are interconnected.
7
Kramer, C.Y. 1956. Extension of Multiple Range Tests to Group Means with Unequal Numbers of
Replication. Biometrics. 12, 307-310.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 69
In the NSOPF: 04 data, there were no significant gender differences in any of the
aggregated disciplinary groups reported (biology, physical sciences, mathematics, and
computer science).
50
45
40
35
Percent
30
Men
25
Women
20
15
10
5
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FIGURE 4-1 Mean percent of time faculty spent on research (self-reported), by gender.
NOTE: In the final publication the following numbers will be inserted into the chart
at the top of columns.: Biology Men 43.8% (110), Women 40.2% (117); Chemistry
Men 46.8% (108), Women 40.0% (96); Civil Engineering Men 38.9% (85), W
Women 39.1% (116); Electrical Engineering Men 43.3% (101), Women 42.8%
(102); Mathematics Men 44.9% (81), Women 38.1% (82); Physics Men 38.2% (108),
Women 41.2% (119). Sample size is in parentheses. The column values are the
averages (over the respondents) of the self-reported percent times.
SOURCE: Faculty survey carried out by the Committee on Gender Differences in the
Careers of Science, Engineering, and Mathematics Faculty.
Teaching
In this section, the percentage of time spent on teaching, the number of classes
taught, and the number of students advised are examined for gender differences. It is
often assumed that female faculty spend a greater percentage of their time on
instructional duties than male faculty.
Using the data from our faculty survey, the percentages of time men and women
spent teaching and advising undergraduate and graduate students were combined and the
average percentages were compared for men and women. Overall, female and male
respondents reported spending approximately the same percentage of time on teaching
and advising (males, 41.4 percent; females, 42.6 percent.). The NSOPF: 04 provided
similar data: 44.2 percent for men and 42.0 percent for women. Here again, the
percentages in the two surveys are remarkably similar.
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70 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
Disaggregated by field, the difference between men and women faculty is approaching
significance in chemistry and civil engineering, with women reporting more time spent
on teaching and advising than men. In the NSOPF: 04 data, there were no significant
differences between men and women in the aggregated fields reported (biology, physical
sciences, mathematics, and computer science).
Amount of teaching
Our faculty survey also asked respondents how many undergraduate courses they
were teaching in the current term/semester. In general, answers ranged from zero to two.
There were no significant differences in the average number of undergraduate courses
men and women were teaching (men, 0.83 courses; women, 0.82 courses; see Appendix
4-1). The NSOPF: 04 data presented a similar picture, with a lower average number of
undergraduate courses for women (men, 0.7 courses; women, 0.6 courses).
Looking at each of the six disciplines we surveyed, men were teaching marginally
more undergraduate courses than women in electrical engineering; none of the other
fields had significant differences between men and women. In the NSOPF:04 data, there
were no significant gender differences in the teaching of undergraduate courses in the
biological sciences, physical sciences, or mathematics and computer science. (There
were too few cases to do this analysis for engineering faculty.)
The above analyses were repeated for graduate courses. Faculty teach fewer
graduate courses, so here the distinction is between faculty who were doing no graduate
teaching in the current term or semester and faculty who were doing some graduate
teaching in the current term or semester. There was no significant difference found
between men and women in terms of whether they were teaching graduate courses in our
data (percent doing no graduate teaching: men, 50.8; women, 54.9, see Appendix 4-2.) or
in the NSOPF:04 data (percent doing no graduate teaching: men, 46.8; women, 47.3).
There was no significant difference in any of the six fields we surveyed between
men and women faculty in terms of whether they are teaching graduate courses. The data
approaches significance in physics, where men are less likely to be teaching graduate
courses than women. We conducted a similar analysis of the NSOPF:04 data and found
that men were significantly more likely to be teaching graduate courses in the biological
sciences (men, 65.8 percent; women, 59.7 percent) and in the physical sciences (men,
37.3 percent; women, 29.6 percent). In mathematics and computer science, there was no
significant different between men and women in terms of whether they taught graduate
courses (men:,52.9 percent; women, 55.4 percent). (There were too few cases to conduct
this analysis for engineering faculty.)
Finally, we explored whether gender is associated with the number of graduate
thesis or honor thesis committees on which a faculty member serves. These data are
shown in Appendix 4-6, and from the table, we see that the number of thesis committees
on which faculty report serving is quite variable, ranging from zero all the way to 30.
There appear to be some differences between men and women in terms of the numbers of
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 71
committees on which they serve, but these differences appear to vary by discipline. 8 The
NSOPF:04 asked faculty how many hours they spent on thesis and dissertation
committees, and men spent marginally more time than women (men, 1.8 hours; women,
1.3 hours).
Service
There is a general awareness that female faculty spend a greater proportion of
their time serving on departmental, school, or university-wide committees than men. In
looking at the percentage of time faculty spend on service work, we combined the
percentage of time spent on administration or committee work within the university with
service outside the university. Overall, there was no difference between men and women
in the percentage of time spent on service (men, 14.4 percent; women:,15.4 percent; see
Appendix 4-7.). The NSOPF:04 found similar percentages of time spent on service, with
no difference between men and women faculty (men, 16.1 percent; women, 14.8
percent).9
Disaggregated by field, there appears to be no gender differences in the
percentage of time spent on service in any of the six fields we surveyed (See Appendix 4-
7). The NSOPF:04 found similar results (biology – men,15.8 percent, women, 15.3
percent; physical sciences – men,16.2 percent, women, 12.0 percent; and mathematics
and computer science - men, 14.4 percent, women, 14.1 percent).
Committee service
In addition to asking about the percentage of time spent on service, our faculty
survey asked respondents how many committees they have served on. The view is that,
in order to make committees more diverse, women are more frequently asked to serve on
them, with the result that they serve on more committees than men do. The faculty
survey asked respondents if they had participated in 10 types of departmental
committees: undergraduate curriculum, graduate curriculum, executive, promotion and
tenure, faculty search, fellowship, graduate admissions, facilities or space, program
review, and “other.” An initial variable was created that summed participation on the
nine identified committees. While the actual range was between zero and nine, few
faculty served on more than six committees, and disaggregated by field, there were many
cells which contained no faculty members. Therefore, faculty members who served on
six or more committees were aggregated into one category of those serving on six or
more committees, so that at least one faculty member fit into each cell when the
respondents were disaggregated by gender and field. Overall, the average number of
committees served on was similar for men (1.61 committees) and women (1.76
committees) (see Appendix 4-8.).
8
The comparisons between men and women overall, and by discipline, in terms of the number of thesis
committees a faculty member served on are not reliable, due both to small sample sizes and to the long-
tailed distribution of this response; a few large values in response can strongly affect the comparison.
9
See footnote 72 that details how the DAS analysis was conducted. Note that the definition NSOPF uses is
different than the definition used in the faculty survey.
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72 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
INSTITUTIONAL RESOURCES
This section focuses on a single, general question: do male and female faculty
receive similar institutional resources? To explore this question, we examine a number of
different resources. In order, they are: start-up packages faculty receive on joining a
department, summer salary, travel funds, reduced teaching loads, lab space, equipment,
and support staff, including access to graduate research assistants (RAs) and postdocs.
Start-up Funds
Start-up packages are given to new faculty hires. A number of elements
can be found in start-up packages, which makes it important to define clearly
what is being quantified. Systematic surveys of start-up funds began in earnest
around 2000. Examples include surveys conducted by the University of Colorado
at Boulder in 1999 and surveys conducted by the Council of Colleges of Arts &
Sciences--the New Hires Survey and the 2000 Big 10+ Chemical Engineering
Chairs Survey. Summarizing their data, Ehrenberg and Rizzo (2004) write, “at
research universities, these [start-up packages needed to attract new faculty
members in the sciences] cost an average of $300,000 to $500,000 for assistant
professors and often well over $1 million for senior faculty.” A survey of start-up
funds conducted by the Cornell Higher Education Research Institute (CHERI) in
2002 found:
“At the new assistant professor level, with few exceptions, Carnegie
Research I universities provide larger start-up packages than other
universities in the sample, and private research universities provide larger
start-up packages than public universities. When the departments are
broken down into four broad fields, physics/astronomy, biology,
chemistry, and engineering, the average reported start-up package for new
assistant professors at private Research I universities varied across fields
between $337,000 and $475,000. Estimates of the average high-end (most
expensive) assistant professor start-up package costs at these institutions
varied across fields from $587,000 to $725,000.”10
The data on start-up funds that is disaggregated by gender has been collected by
individual institutions. A 2003 task force report at Princeton University, which collected
data from five S&E departments, concluded “in the five departments examined, we found
no statistical support for gender differences in start-up space, current space, or start-up
10
“The 2002 Cornell Higher Education Research Institute (CHERI) Survey on Start-up Costs and
Laboratory Allocation Rules: Summary of the Findings.” Available at
http://www.ilr.cornell.edu/cheri/surveys/2002surveyResults.html. (Accessed October 7, 2008). See also the
presentation by Ronald G. Ehrenberg, Michael J. Rizzo and George H. Jakubson, “Who Bears the Growing
Cost of Science at Universities?” presented at the 2003 Conference. See also Ronald G. Ehrenberg,
Michael J. Rizzo and Scott S. Condie, “Start-up Costs in American Research Universities” CHERI working
paper, WP-33, March 2003, Cornell University.
87
Committees on the Status of Women Faculty. “Report of the School of Science” Massachusetts Institute
of Technology, 1999.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 73
financial packages. However, we did detect certain patterns. For example, the largest
start-up packages have generally gone to men.”
Both the Committee’s faculty survey and departmental survey requested data on
start-up costs. On the faculty survey, faculty who were tenured or tenure-track and hired
after 1996 were asked, “When you were first hired at this institution, how much were you
given in start-up funds?” Respondents were asked to break down start-up costs into four
categories: equipment, renovation of lab space, staff (e.g., postdocs), and other.
Summer Salary
The faculty questionnaire asked tenure-track or tenured faculty hired after 1996
whether they received summer salary funds when they were first hired at their current
institution. Of those who responded, 71 percent of men and 68 percent of women
indicated they did. When disaggregated by discipline, interesting differences appeared,
with female faculty having a higher percentage in chemistry (81.8 percent versus 71.2
percent for male faculty) who received summer salary; while in mathematics the reverse
was true, with 42.9 percent of male faculty as contrasted with 29.1 percent of female
faculty (see Appendix 4-10).
Travel Funds
The faculty questionnaire asked tenure-track or tenured faculty hired after 1996
whether they received travel funds when they were first hired at their current institution.
Of those who responded, 56 percent of men and 59 percent of women indicated they did
(see Appendix 4-11). Again, there was no substantial gender difference at this level of
aggregation. There were some differences for men and women among the six disciplines
in terms of the percentages of people receiving travel funds initially.
The survey also asked faculty respondents, “During the last five years, have you
been given travel money by your department or institution to attend professional
conferences or to conduct research offsite?” Of those who answered, approximately 42
percent of men and 43 percent of women answered yes.
Reduced Teaching Loads
Faculty may negotiate a reduced teaching load for an initial period after they are
hired. New faculty often desire a reduced teaching load to allow them time to get settled
in a new environment and to get their labs and their research set up and underway. The
committee’s survey asked all tenure-track and tenured faculty hired after 1996 whether
they had received a reduced teaching load when hired. A large majority of new faculty
reported receiving a reduced teaching load when they were hired (see Appendix 4-3).
However, there was not a significant difference between men and women, in terms of the
percentage who received a reduced teaching load when hired in any of the six fields
surveyed.
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74 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
Lab Space
Much of the discussion on lab space stems from the 1999 MIT report, “Report of
the School of Science,” which found an “unequal distribution” of resources, including lab
space, allocated to women.11 This focused attention on the issue and a number of other
gender equity assessments at other universities have taken it up.12
Stanford’s report, for example, found no disparity in lab space: “The Provost's
Advisory Committee on the Status of Women Faculty on Thursday issued a variety of
recommendations to strengthen the recruitment and retention of women faculty and, in a
first-ever comprehensive analysis, has preliminarily found ‘insignificant’ differences
between men and women in benefits and support such as laboratory space, equipment,
start-up funds, research funds, and summer salaries.” [James Robinson, “Report: ‘No
pattern’ of disparity between men, women faculty” Stanford Report, May 20, 2003.]13
The University of Pennsylvania found mixed results: “With respect to the professional
status of women faculty, the committee determined that at the more junior ranks women
had more research space per grant dollar than men, but women full professors averaged
somewhat less space per grant dollar14 than their male colleagues; in both SAS science
departments and the School of Medicine, senior women faculty had about 85% of the
space assigned to males.”15 Case Western Reserve found women had less lab space:
“Despite these heavier workloads, participants believe that women often receive fewer
benefits and support resources. Women tend to enter the university with more limited
start-up packages. … They receive less space, have less access to graduate student
assistance, and get fewer services from support staff.”16
However, quantitative data on lab space are hard to find. It is critical that it be
measured, since, as Purdue’s report noted, it may be a perceptual or an actual
discrepancy:
“Females responded differently than males on a number of these issues.
However, most differences appear to simply reflect perceptual differences
across the schools and the varying distribution of women in the schools
(e.g., women are less satisfied than men with library resources, but this
largely reflects the fact that Education and Liberal Arts schools, where
11
Sara Rimer, “For Women in Science, Slow Progress in Academia,” New York Times, April 15, 2005
12
See for example a thorough assessment conducted by New Mexico State University in 2003, “Space
Allocation Survey.” Available at: http://www.advance.nmsu.edu/Documents/PDF/ann-rpt-03.pdf.
13
Available at: http://news-service.stanford.edu/news/2003/may21/womenfaculty-521.html
14
Note that the University of Pennsylvania’s research used an unusual metric of research space per grant
dollar.
15
University of Pennsylvania Almanac, Almanac Supplement, December 4, 2001. Vol. 48, no. 14,
http://www.upenn.edu/almanac/v48/n14/GenderEquity.html. See the full report at:
http://www.upenn.edu/almanac/v48pdf/011204/GenderEquity.pdf
16
CWRU Equity Study Committee, "Resource Equity at Case Western Reserve University: Results of
Faculty Focus Groups," March 3, 2003, pp. 46-47. Available at
http://www.case.edu/president/aaction/resourcequity2003.doc.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 75
faculty are the least satisfied with library resources, are also schools with
relatively high proportions of women faculty).
Taking into account these differences in gender representation across the
schools, females are still less likely to believe that they have adequate
laboratory space (48%) than are males (60%). In particular, women in
agriculture, health sciences, and science are substantially less likely than
their male counterparts to feel that they have adequate lab space.”17
The Committee’s survey asked faculty to identify how much lab space they have.
It should be noted that lab space may mean different things to different people and in
different disciplines. One problem, for example, is how to count shared lab space.
Overall, lab square footage ranged from 0 to 100,000 square feet. The two largest
figures—47,000 and 100,000—both occurred in civil engineering and appear to be
outliers.18 Both observations were changed to missing. Seven hundred and sixty-nine
respondents reported estimated lab space. Overall, men reported significantly more lab
space, with an average of about 1,550 square feet, than women, with an average of about
1,160 square feet. Disaggregated by field (see Figure 4-2), men had significantly more
lab space in civil engineering and physics and marginally more in biology.19
17
Purdue did a survey in 2001where they asked whether women and men faculty were satisfied with
amount of lab space. Women were less satisfied. (This is different from how much lab space each gender
has.) Available at:
http://www.cyto.purdue.edu/facsurvey/faculty/survey/
http://www.cyto.purdue.edu/facsurvey/faculty/survey/results/intro.htm
18
The medians for men and women faculty in civil engineering were quite similar, while the means were
significantly different.
19
Mathematics was dropped from this analysis, as only 11 respondents in mathematics reported having lab
space.
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96 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
shrinking and our data, discussed below, confirm this tendency. Furthermore, while at
first glance salary would appear to be a well-defined quantity that can be easily compared
across gender, many factors appear to affect salaries in a complex way. Therefore, it is
important to account for the potentially confounding effects of factors such as discipline,
rank, productivity and others before attributing possible salary discrepancies to the effect
of gender.
Here we examine salary information collected as part of our survey, as well as the
salary data included in the NSOPF:04.
The faculty survey asked respondents to report their base salaries. We consider
only the 1,404 full-time faculty who responded to the survey and who were assistant,
associate, and full professors. There were 1,179 faculty for whom the salary information
was not missing26. Appendix 4-21 shows the number of missing salary observations in
each discipline and by gender. As is clear from the table, the proportion of faculty who
did not respond to this question is similar across gender and across disciplines. The four
observations correspond to two men and two women, and all exceeded $600,000 for a
nine-month salary. The next-highest salaries reported were all below $250,000 for nine
months. One of the four outliers that were removed corresponded to a reported salary of
almost $1.8 million, which is clearly unrealistic. About 20 percent of all respondents
reported salaries below $100 for nine months of work. Since these are likely to be values
reported as thousands, we decided to multiply those reported salaries by 1,000 rather than
lose the information. Two other salaries were removed from consideration and
corresponded to two faculty members who, even after rescaling, ended up with nine-
month salaries below $10,000 (the next lowest salary was $45,000). The wisdom of
deleting the four highest salaries from the data set might be debatable, but from a purely
statistical viewpoint is fully justified; the next highest nine-month salary in the sample
was $212,272, so the salaries at the high end of the distribution were clear outliers.
Similarly, at the lower end, there was a clear gap between salaries below $10,000 and the
next lowest, at $45,000.Thus, for our initial salary analyses, we considered 1,173 faculty
out of 1,179 who responded.
Appendix 4-9 shows the mean salary by discipline, rank and gender. It also shows
the number of observations in each category. Statistics were computed using salaries
standardized to a nine-month basis. Nor surprisingly, salary increases with seniority in
all disciplines and both genders. Males appear to have a higher mean salary than women
in almost all disciplines, but only among full professors. The difference between men and
women seems to vanish for associate and assistant professors, and in some disciplines
(e.g., electrical engineering and physics), women associate professors appear to receive a
higher mean salary than their male colleagues. At the assistant professor level, the
differences in mean salary are negligible and favor men or women, depending on the
discipline. One interesting finding is that the highest salary among assistant professors is
paid to a female in every discipline, while the lowest salary is paid to women in only half
of the disciplines (mathematics, physics, and civil engineering).
In trying to understand the major predictors of salary, we first fitted a simple
model that did not take into account potentially important factors, such as productivity. In
this simple model, explanatory variables were gender, rank, academic age, discipline,
26
Out of the 1,179 respondents, four responses were considered to be outliers and were removed.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 97
and all the two-way interactions with gender. There were 1,169 observations with
complete covariate information and the model fitted the data well: R2 = 0.54.
There were significant gender differences in salary in this model (p = 0.009), in
which we controlled for several variables likely to differ between men and women (e.g.,
rank and discipline). However, the effect of gender cannot be interpreted in isolation of
other factors because the interaction between gender and rank was also statistically
significant (p = 0.004) .Thus, we can only investigate whether salaries for men and
women are similar within rank. We find that among full professors, men earn
significantly more than women (p < 0.05). On average, male full professors earn about 8
percent more than female full professors. There are no significant differences in salaries
for men and women among associate or assistant professors. Discipline and rank were
also significant predictors of salary. Given these results, it seems likely that some of
gender differences in faculty salaries reported in other studies, in which rank and
discipline are not controlled, are due more to the confounding factors rather than solely to
any gender difference in salary.
We also looked at the salary data in the NSOPF:04. Because income is reported
as a mean and there are small sample sizes in some disciplines, it was not possible to
break out the analysis by field. In the NSOPF:04 data for full-time faculty who had
instructional duties for credit and faculty status at an RI institution in engineering,
biological sciences, physical sciences, mathematics, and computer sciences, we found
men received marginally larger salaries than women at the full professor level. However,
there was no significant difference between the salaries of male and female faculty at the
associate professor or assistant professor level. This assessment of gender differences in
base salaries did not control for disciplinary differences or academic age, both of which
are likely to have gender differences in them.
We were also interested in whether several additional variables predicted salary.
To explore this, we again fitted a linear model to the log of base salary (nine-month
base), but now extended the list of explanatory variables in the model to include gender,
discipline, faculty rank, type of institution (public or private), prestige of the institution,
grant funding, publications (refereed journals and conference proceedings), academic age
(defined as the time elapsed between award of the Ph.D. and December 2004), and all
two-way interactions with gender. The model was fitted to the 753 observations with
complete information for all covariates and resulted in an R2 equal to 0.64. Gender,
discipline, rank, institution type, and prestige were considered classification variables; the
remaining were included as continuous variables. A random effect for institution was
included, but the institution variance component was negligibly small.
Gender was not significantly associated with salary once other potential
confounders were taken into account. Significant associations with salary were found for
discipline (p < 0.0001), rank (p < 0.0001), prestige of the institution (p < 0.0001), type of
institution (p < 0.0001), and grant funding (p = 0.002). The interaction between rank and
gender was again significant (p = 0.02). Academic age and the interaction between grant
funding and gender were approaching significance (p = 0.07 and p = 0.09, respectively).
As would be expected, full professors reported larger salaries than associate
professors, who reported larger salaries than assistant professors. The more time that had
elapsed since a faculty member received a Ph.D., the higher the salary, regardless of rank.
Highest-prestige institutions across all disciplines pay higher salaries than medium-
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98 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
prestige institutions, which in turn pay higher salaries than the lowest-prestige
institutions. Private institutions pay higher salaries than public institutions.
There was a positive association between grants and salary. Everything else
being equal, a faculty member who increases his or her funding by a factor of 2.7 in a
year would be linked with a 0.6 percent increase in salary. For a $75,000 annual salary,
this would amount to an increase of $450, and so while this relationship is statistically
significant, it has little practical significance. While the association between the number
of publications and salary was not statistically significant, it was at least positive. Once
again, please note that the discussion here somewhat overshoots the capabilities of our
surveys. Because our surveys were cross-sectional, a conclusion stating that a faculty
member who, over time, increases funding will also see an increase in her salary implies
a longitudinal effect that our data cannot capture. Thus, these results, while plausible,
must be cautiously interpreted.
Although women and men at a given rank appear to be compensated at similar
levels (this does not apply for full professors), women may be at a disadvantage if they
are less likely to be promoted to higher ranks. This topic is addressed in Chapter 5,
where we found no evidence of differences among men and women in terms of
promotion to higher ranks in our sample of RI, full-time faculty.
Outside Offers
Faculty retention and attrition focus on the likelihood that faculty will remain in a
department. Some mobility is to be expected. Some faculty will move from one
academic job to another or from academia to a position outside academia (e.g., in
industry). Some faculty will leave departments to retire or because they are ill. The most
problematic kind of attrition involves faculty who leave because they feel unwelcome.
These faculty members have not failed, but they also have not fit in, and the departments
they leave have invested time, money, and other resources that can be lost. For example,
“new hires who leave their units in the first or second year end up costing programs tens
of thousands of dollars in recruitment costs, moving expenses, start-up packages, and
more” (Bugeja, 2004). The loss of a faculty member may also lead to a lost faculty line,
as the faculty member might not be replaced.
It is often thought that female faculty attrition is greater than male faculty
attrition, but the evidence is mixed (Trower and Chait, 2002; Yamagata, 2002; Carter et
al., 2003; Cohoon, et al., 2003; August and Waltman, 2004; August, 2006). One way to
examine retention issues, generally, is to ask faculty whether they have received outside
offers or whether they are considering leaving their department.27
The survey asked tenured faculty whether they had “received an offer to leave
your current institution in the last five years.” Overall, the fraction of men and women
reporting they had received one or more offers was almost identical (32.7 percent of
women and 32.5 percent of men.) (There were no differences between men and women
in biology and civil engineering (see Appendix 4-23). In chemistry and physics, a greater
proportion of men than women reported they had received at least one offer to leave their
27
Note that one reason to get an outside offer is to put pressure on a faculty member’s current department
to match a better offer. The faculty member might not actually want to leave their current department.
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 99
current institution. This was reversed in mathematics and electrical engineering, where
more women than men report receiving one or more outside offers.
We looked at what factors contribute to getting outside offers. The response
variable was considered to be dichotomous: zero, or one or more offers to leave the
institution. The results of this analysis must be very carefully interpreted, since clearly
the people who received offers and stayed were the “happy” ones. Therefore, any
statements regarding the effect of factors on offers to leave need to be qualified by noting
that the findings are conditional on the fact that faculty remained at their institutions,
whether they had offers or not.
In this analysis, we tried to investigate the effect of discipline, gender, rank, type
of institution, prestige of the institution, whether the faculty member had a mentor, and
the faculty member’s productivity in terms of grant funding and publications. However,
we found that only 526 respondents (out of a total of 1,404 full-time assistant, associate,
or full professors) had complete information for all covariates. Furthermore, only one
male assistant professor and no female assistant professors reported receiving one or
more offers to leave. Thus, we restricted attention to the 526 associate and full professors
who had complete covariate information and fitted a model that included all the
covariates of interest. The probability of receiving at least one outside offer was not
different for men and women of any rank or across disciplines. In general, the probability
of receiving one or more offers to leave was not associated with many of the covariates.
The only two associations we found were with prestige of the institution and with
research funding. As one might anticipate, faculty in institutions of medium or high
prestige were more sought after than those at institutions of lower prestige (p < 0.001).
Faculty with more research funding were also more likely to receive one or more outside
offers. For every additional $1,000 in research funding, the probability of having
received at least one outside offer increased by about 1 percent.
Job Satisfaction
Job satisfaction is heavily intertwined with climate issues. Job satisfaction may
be viewed as the expression of a faculty member’s perception of engagement, power,
treatment, and role, as well as departmental and institutional policies and procedures. It
is a large and subjective area to tap into. It can also be a causal factor, affecting such
outcomes as productivity and retention. Indeed, it seems likely that job satisfaction
mediates, at least in part, between professional activities, institutional resources, and
climate on the one hand, and the various outcome variables on the other. However,
because we did not measure job satisfaction in our survey, we cannot test this possibility
directly.
Satisfaction data
Traditionally, most information on job satisfaction comes from surveys or focus
group meetings undertaken by individual institutions or from the NSOPF. The results of
many of these surveys suggest that women’s job satisfaction falls below men’s (Holden,
2001; Trower and Chait, 2002). Two recent national surveys have examined satisfaction
with academic careers.
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100 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
The NSOPF:04 asked several questions regarding satisfaction, although it did not
probe very deeply into issues of workplace satisfaction. Four questions and responses
from this survey are shown in Table 4-3. The mean responses show that female faculty
are significantly less satisfied with their salaries and workloads than male faculty.
Women are marginally less satisfied than men with their jobs overall. Men and women
do not differ in their satisfaction with their benefits. This latter point is important,
because some have interpreted the frequent finding that women are less satisfied with
their jobs as indicating that women are generally more dissatisfied than men (or are more
willing to express their dissatisfaction). The data in Table 4-3 show women are less
satisfied than men in particular areas rather than as a more general matter.
TABLE 4-3 Satisfaction of Faculty with Employment, by Gender.
Very Somewhat Somewhat Very
Satisfied (%) Satisfied (%) Dissatisfied (%) Dissatisfied (%)
Satisfaction
Satisfaction with benefits
Male 37.8 40.6 16.9 4.7
Female 38.6 42.6 12.7 6.1
Satisfaction with salary
Male 25.4 43.4 22.1 9.1
Female 20.1 38.2 27.6 14.1
Satisfaction with workload
Male 34.7 42.6 18.5 4.3
Female 23.2 50.8 20.2 5.8
Satisfaction with job overall
Male 44.1 41.3 12.3 2.3
Female 39.1 45.3 13.4 2.2
SOURCE: National Center for Educational Statistics, 2004 National Survey of
Postsecondary Faculty (NSOPF-04). Tabulation by NRC.
The Study of New Scholars, “Tenure-Track Faculty Job Satisfaction Survey
(Trower and Bleak, 2004)”28 examined full-time tenure-track faculty at six research
universities. Important findings of the survey included “Females were significantly less
satisfied than males with the following:
• Elements of work and expectations;
• Expectations for how to spend time;
• Expectations for research output;
• Expectations for the amount of outside funding needed;
• Time available for research;
• Resources available to support work; and
28
The report, focusing on gender, is available at
http://www.gse.harvard.edu/~newscholars/downloads/SNS_report_gender.pdf
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 101
• Professional assistance for proposal writing and locating outside funds
• Relationships
• Commitment of the department chair to their success;
• Commitment of senior faculty to their success;
• Interest senior faculty take in their professional development;
• Opportunities to collaborate with senior faculty;
• Professional interactions they have with senior colleagues;
• Quality of mentoring they receive from senior faculty; and
• How well they fit in their department
• Diversity, Salary, Work–Life Balance
• The racial diversity of the faculty in their department;
• The ethnic diversity of the faculty in their department;
• Their salary; and
• The balance between their personal and professional lives (p. 2)”
Individual universities have found similar results through surveys on their
campuses. A 2002 survey of faculty at UCLA found the following: “Compared to male
faculty, women feel less influential, rate their work environment as less collegial, view
the evaluation process as less fair, feel less informed about academic advancement and
resource negotiation, and rate the distribution of resources as less equitable.”29
Dissatisfaction is an important concern. First, it is an obstacle to the success of
faculty efforts in all areas of professional activities. It can have a negative effect on the
collegiality and group decision making of a department. It may also be picked up on by
undergraduate and graduate students, who may in turn feel discouraged about academic
careers. While dissatisfaction may reflect problems in the workplace environment, it may
also reflect pressures outside the workplace that affect women more than men and make
it harder for them to get their work done.
Planning to leave or retire
Faculty who are planning to leave or retire, particularly the former, may be
indicating they are dissatisfied with their current work situation. Our survey asked
faculty whether they were planning on leaving or retiring from their current institution.30
The variable was dichotomous; Either the faculty member was not planning to leave or
retire or they were. One hundred and seventy-one faculty out of 1,404 full-time faculty
respondents did not provide an answer to this question, and the proportion of missing
observations was essentially the same among men and women (13 percent versus 11
29
Gender Equity Committee on Academic Climate. An Assessment of the Academic Climate for Faculty at
UCLA, April 2003. Los Angeles, CA: University of California at Los Angeles.
30
In future studies, these two events should be separated, since male faculty tend to be older and are more
likely to retire, while women faculty tend to be younger and are less likely to leave due to retirement.
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102 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
percent, respectively). Both in general and disaggregated by field, there were no
differences between men and women in their responses about whether they were planning
to leave or retire (overall - men 36.2 percent; women; 38.8 percent.; see p. 120 for an
explanation of the use of summary survey data.). Table 4-24 in the Appendix shows the
proportion of men and women in each discipline who have indicated that they are not
considering leaving or retiring from the institution. Since a larger percentage of men
than women should be reaching retirement age, these data may suggest that more women
than men are thinking of leaving their current institution for nonretirement reasons.
To get a clearer look at those faculty whose thoughts about leaving may more
directly reflect dissatisfaction with their professional situation, we examined the
percentage of faculty who were both planning to leave and had offers to leave in the past
five years. We reasoned that faculty who were retiring were likely to respond positively
to planning to leave, but negatively to having recent offers to leave. Faculty who wished
to change jobs were more likely to respond positively to both questions. There was no
significant gender difference in the percentage of men and women overall who fit both
conditions (men, 49 percent; women, 58 percent; see p. 120 for an explanation of the use
of summary survey data.). Disaggregated by field, the difference between men and
women was significant only in the case of electrical engineering, in which women were
more likely than men to be considering leaving and to have received an outside offer.
SUMMARY OF FINDINGS
This chapter examined the day-to-day life of a full-time academic in S&E at RI
institutions. Principal findings can be found in four areas: professional activities,
institutional resources, climate, and outcomes.
Professional Activities
Finding 4-1: There is little evidence overall that men and women spent different
proportions of their time on teaching, research, and service. There is some indication
that men spent a larger proportion of their time on research and fundraising than women
do (42.1 percent for men versus 40 percent for women). However, the difference only
approaches significance, and the actual percentages of time that male and female faculty
reported spending on research were not very different, with the exception of chemistry, in
where men spent a significantly greater percentage of their time on research and
fundraising (45.7 percent) than women do (39 percent) and mathematics (44.2 percent for
men versus 38.2 percent for women). (Figure 4-1)
Finding 4-2: Male and female faculty appeared to have taught the same amount
(41.4 percent for men versus 42.6 percent for women). There were no gender
differences in the number of undergraduate or graduate courses men and women taught:
0.83 undergraduate courses for men versus 0.82 undergraduate courses for women. The
percentage of men not teaching graduate courses was 50.8 percent versus 54.9 percent for
women. (Appendix 4-2)
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 103
Institutional Resources
Finding 4-3: Men and women seem to have been treated equally when they were
hired. The overall size of start-up packages and the specific resources of reduced
initial teaching load, travel funds and summer salary did not differ between male
and female faculty.
Finding 4-4: Male and female faculty supervised about the same number of research
assistants and postdocs. (Appendix 4-5)
Finding 4-5: There were some resources where male faculty appeared to have an
advantage. These included the amount of laboratory space (considering both
faculty overall and only those who do experimental research), access to equipment
needed for research, and access to clerical support. However, the difference in lab
space disappeared when other variables were added in a regression analysis, where
there were no differences in lab space as a function of gender or the interaction
between gender and any of the other variables. Insofar as the research a faculty
member does is dependent on these resources, and the ability to accomplish as much as
possible in turn determines his or her overall success, gender differences in these
institutional resources could lead to gender differences in success.
At the same time, it should be noted that the apparent gender differences in access
to these resources may reflect differences in access based on discipline or rank, since
some disciplines and ranks have a higher proportion of male faculty, and those disciplines
and ranks could also have more lab space and equipment. This suggestion is supported by
the finding that grant funding and research type (experimental versus nonexperimental)
were significantly associated with the allocation of lab space. Since there are
proportionately more male faculty than female faculty in some disciplines than in others,
and since there are proportionately more male faculty than female faculty among full
professors than among associate and assistant professors, it seems likely that the simple
gender difference in lab space is actually a function of discipline and rank differences, as
well as prestige of the institution. (Figure 4-2)
Climate
Finding 4-6: Female tenure-track and tenured faculty reported that they were more
likely to have mentors than male faculty. In the case of tenure-track faculty, 57 percent
of women had mentors compared to 49 percent of men. (Figure 4-6)
Finding 4-7: Female faculty reported that they were less likely to engage in
conversation with their colleagues on a wide range of professional topics. These
topics included research, salary, and benefits (and, to some extent, interaction with other
faculty members and departmental climate). This distance may prevent women from
accessing important information and may make them feel less included and more
marginalized in their professional lives. Men and women faculty surveyed did not differ
in their reports of discussions with colleagues on teaching, funding, interaction with
administration, and personal life.
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104 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
Finding 4-8: There were no differences between male and female faculty on two
measures of inclusion: chairing committees (39 percent for men and 34 percent for
women) and being part of a research team (62 percent for men and 65 percent for
women). (Appendix 4-4 and 4-5)
Outcomes
Finding 4-9: Overall, male faculty had published marginally more refereed articles
and papers in the last three years than female faculty, except in electrical
engineering, where the reverse was true. Men had published significantly more papers
than women in chemistry (men, 15.8; women, 9.4) and mathematics (men, 12.4; women,
10.4). In electrical engineering, women had published marginally more papers than men
(7.5 for women compared with 5.8 for men). The differences in number of publications
between men and women were not significant in biology, civil engineering, and physics.
All of the other variables related to the number of published articles and papers
(discipline, rank, prestige of institution, access to mentors, and time on research) show
the same effects for male and female faculty. (Figure 4-7)
Finding 4-10: Although men were somewhat less likely to be a principal investigator
or co-principal investigator on a grant proposal than women, this difference
disappeared when other variables were added in a regression analysis, where male
and female faculty did not differ on the probability of having grant funding.
Furthermore, because the effect of gender was confounded with the effect or rank and
whether the person had a mentor, it is essentially impossible to isolate the effect of
gender. The variables that appear to be associated with the probability of having a grant
(discipline, faculty rank, being at a high- or medium-prestige university, and spending
more time on research) do so in the same way for male and female faculty. (Figure 4-8)
Finding 4-11: Male faculty had significantly more research funding than female
faculty in biology; in the other disciplines, the differences between male and female
faculty were not significant. There was no overall difference in the amount of grant
funding received by male and female faculty, but there was a significant interaction
between gender and discipline. The other variables related to the amount of grant
funding (faculty rank, whether a faculty member is at a private university, whether a
faculty member is at a university of higher prestige, having a mentor, and publishing
more) were related in the same way for male and female faculty.
Finding 4-12: Female assistant professors who had a mentor had a higher
probability of receiving grants than those who did not have a mentor. In chemistry,
female assistant professors with mentors had a 95 percent probability of having grant
funding versus 77 percent for female assistant professors in chemistry without mentors. A
similar but weaker pattern is exhibited for female associate professors. Over all six fields
surveyed, female assistant professors with no mentors had a 68 percent probability of
having grant funding versus 93 percent of women with mentors. This contrasts with the
pattern for male assistant professors; those with no mentor had an 86 percent probability
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PROFESSIONAL ACTIVITIES, INSTITUTIONAL RESOURCES & CLIMATE 105
of having grant funding versus 83 percent for those with mentors. (Appendix 4-20a and
4-20b)
Finding 4-13: Overall, male and female faculty were equally likely to be nominated
for international and national honors and awards, but the results varied
significantly by discipline, making interpretation challenging. The other variables
affecting the likelihood of being nominated for honors and awards (discipline, faculty
rank, prestige of university, number of publications) affected this likelihood in the same
way for male and female faculty. (Appendix 4-22)
Salary
Finding 4-14: Gender was a significant determinant of salary, but only among full
professors. Male full professors made, on the average, about 8 percent more than
females, once we controlled for discipline. At the associate and assistant professor
ranks, the differences in salaries of men and women disappeared. When we looked
more broadly at variables that might predict salary, we found the following predicted
salary in addition to discipline and rank: academic age (the amount of time between
receipt of a Ph.D. and December 2004); prestige of the university; type of university
(private versus public); and amount of grant funding. All of these variables predicted
salary in the same way for male and female faculty, with the exceptions of rank and grant
funding, for which the beneficial effect of a grant was more pronounced for females.
Other Job Offers
Finding 4-15: Differences in the probability of receiving an outside offer for male
and female faculty depended on discipline. In electrical engineering and in
mathematics, women were more likely to have received an outside offer, while the
trend was reversed in chemistry and physics. Men and women reported approximately
the same probability of having received at least one outside offer in biology and civil
engineering. The only two variables that predicted the likelihood of receiving an outside
offer were prestige of the institution and the amount of grant funding, which
demonstrated the same effect for male and female faculty. (Appendix 4-22)
Finding 4-16: There was no gender difference among faculty who were planning to
leave and who had received an outside offer in the last five years,31 except in
electrical engineering, where women were more likely than men to be planning to
leave and to have received a recent outside offer. The committee viewed these data as
a measure of faculty dissatisfaction. (Appendix 4-24)
In this chapter, we set out to inquire if there were gender differences in the day-to-
day academic lives of male and female faculty members. We wanted to determine if there
were differences in professional activities, institutional resources, and climate, and if
these influenced various important outcomes. Perhaps the most noteworthy finding is
how much more similar the lives of men and women faculty seem to be based on our
31
However, planning to leave or receiving outside offers are less than ideal proxies for job satisfaction. For
example, faculty may plan to leave a position to retire.
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106 GENDER DIFFERENCES AT CRITICAL TRANSITIONS IN CAREERS
surveys, compared to the striking differences found in earlier research. The survey data
indicate the importance of not simply relying on anecdotal information or past, individual
experiences and emphasize the complexity of issues such as resource allocation and
climate.
The overall data from this study send a positive signal about the institutional climates
at RI universities, and this should encourage young women as well as men to pursue
academic careers in math, science, and engineering, with the new awareness that their
abilities rather than their gender will influence their experiences and their ultimate
academic success.
Although the survey results do indicate that men and women faculty are encountering
comparable opportunities in many ways, it is important to remember that these are group
data. There may very well continue to be women who are experiencing fewer
opportunities and less positive outcomes, at least in part because of their gender. Clearly,
our survey questions, while extensive, were not exhaustive, and there were many areas
not addressed.
Finally, this chapter focused only on the academic environment. There are other
important factors not included in our survey that influence the participation and success
of women faculty, particularly aspects of their personal lives such as family obligations.
We hope that future research will be able to shed light on these critical areas.
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