AUTHOR: Kenneth J. Meier Sharon H. Mastracci Kristin Wilson
TITLE: Gender and Emotional Labor in Public Organizations: An Empirical
Examination of the Link to Performance
SOURCE: Public Administration Review (Washington, D.C.) 66 no6 899-909 N/D
2006
COPYRIGHT: The magazine publisher is the copyright holder of this article and it is
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ABSTRACT
Scholars of public organizations have begun to emphasize emotional labor in studies of
gender in the workplace, finding that the skills women bring to organizations are often
overlooked and under compensated even though they play a vital role in the organization.
Emotional labor is an individuals effort to present emotions in a way that is desired by the
organization. The authors hypothesize that employers with greater emotional labor
expectations of their employees will have more effective interactions with clients, better
internal relationships, and superior program performance. This article tests the effects of
emotional labor in a bureaucratic workforce over time. Multiple regression results show
that organizations with more women at the street level have higher overall organizational
performance. Additionally, emotional labor contributes to organizational productivity
over and above its role in employee turnover and client satisfaction.
Essays on Equity, Gender, and Diversity
In a 2004 Public Administration Review article, Mary Ellen Guy and Meredith A.
Newman introduced the concept of "emotional labor" to public organizations. Emotional
labor consists of personal interactions--separate from actual job descriptions-- among
employees and between employees and clientele that facilitate the effective and smooth
operation of the organization. As Morris and Feldman define it, emotional labor is "the
effort, planning, and control needed to express organizationally desired emotion during
interpersonal transactions" (1996, 987). Guy and Newman demonstrate that the
employees who are most likely to be required to provide emotional labor in an
organization are women and that organizations generally undervalue emotional labor,
resulting in lower salaries paid to women compared to men. Similarly, Webb (2001) and
Bellas (1999) have found that female public servants are expected and required to engage
in emotion work to a greater degree than men, and the typical employee responds to
occupational expectations in the same manner that she aspires to meet explicit
requirements articulated in a job description. Finally, Hochschild (1979) identifies both
gender- and class-based associations with on-the-job emotional labor expectations.
This paper starts by accepting the idea that women employees are more likely to
contribute emotional labor to the organization and asks whether we can empirically
demonstrate results that are consistent with this idea. Though such an assumption is not
without debate, we discuss theoretical foundations that allow for it, particularly in an
undertheorized area of inquiry. This approach is designed to supplement more qualitative
approaches to the same question. First, a brief review of the emotional labor literature
will provide some theoretical specification of the concept and how it might affect
organizational performance. Second, we design an empirical test of this theory using a
large sample of school districts to examine measures of client satisfaction, employee
satisfaction, and overall organizational performance. Third, we present empirical
findings that are consistent with the idea that emotional labor is an important part of
organizations and their performance. Finally, we conclude by addressing a set of
normative and empirical issues raised by the literature and the results of this paper.
Emotional Labor as a Concept
Weber's (1946) ideal typical bureaucracy eliminated the personal, informal aspects of
the organization to create a rational, impersonal bureaucracy. Scholars have long known
that the formal and impersonal side of bureaucracy is supplemented by a human side that
encompasses values, norms, mores, and personal attributes (Barnard 1938; Follett 1940;
McGregor 1960; Simon 1947). Starting with Hochschild (1979, 1983) a group of scholars
distinguished emotional labor from these informal aspects of organization. Emotional
labor is the projection of feelings and emotions needed to gain the cooperation of clients
or coworkers, the ability to see another's side of the issue and integrate that perspective
into what the organization does. Akin to other work-related skills, employee emotions are
subject to management in order to realize an employer's objectives. According to Guy
and Newman, these are the emotions that are "a mainstay of health and human service
professions, public education, paraprofessional jobs, and most support positions such as
administrative assistants, receptionists, clerical staff and secretaries" (2004, 289). These
processes, with rare exception (Steinberg 1999), are not part of the formal job
description, with its focus on measurable skills, achievement levels, or attributes.
Therefore, according to Guy and Newman, emotional labor is generally undervalued in
organizations, resulting in lower pay for persons in positions that call for emotional labor.
Although this can explain an aspect of the gender pay gap, as Guy and Newman point
out, it "begs the question: What is it about women's jobs that causes them to pay less?"
(2004, 289).
Both Fletcher (1999) and Guy and Newman (2004) contend that scientific management
and similar approaches squeezed out the consideration of emotional labor because it is
difficult to measure and does not fit in with standards of how organizations should
operate. Workers in an organization are defined by positions, and the logic of position
classification is that two similar positions (or the workers who fill those positions) are
equal substitutes for each other. Although Tilly and Tilly (1994) examine skill sets in
general, but not emotional labor specifically, differences between women's and men's
capacities to engage in emotion work indicate that they may not be ideal substitutes for
each other.(FN1) One attempt to reconcile emotional labor with scientific management
approaches is Goleman's (1998) concept of "emotional intelligence." Emotion in an
organization can clearly have negative as well as positive consequences for the
organization (see also Sass 2000; Shuler and Sypher 2000; Wharton 1993). Employees
might "go native" and help clients subvert the system, or interpersonal ties might result in
cliques rather than informal methods of getting work done. Emotional intelligence, in
Goleman's view, is the management of emotional labor so that it benefits the
organization.
The few studies of emotional labor in the private sector have generally involved
qualitative examinations of specific sectors, such as air travel, retail sales, emergency
response, or health care delivery. Some case study evidence indicates that emotional
labor can affect organizational performance. Pugh (2001), examining the retail banking
industry, found that greater emotional labor had a positive impact on customers, resulting
in customer loyalty, repeat business, and financial gains for the bank. Sass (2000) and
Shuler and Sypher (2000) show positive results for nursing home workers and 911
dispatchers, respectively. Nursing in particular has been the subject of several studies
(James 1989; O'Brien 1994; Smith 1998; Steinberg 1999; Steinberg and Figart 1999).
Sometimes the targets of emotional labor are not clients but other members of the
organization. Pierce (1999) shows how paralegals were able to support and maintain the
emotional stability of the lawyers for whom they worked through deferential treatment
and caretaking. Emotional labor can also be part of an organization's values and norms.
Sutton's (1991) study of bill-collection agencies argues that managers who understand
emotional labor can provide a better work environment for employees. In part, this work
environment might be more congenial because workers can express their emotions, thus
allowing for greater commitment to the organization and its objectives.
Although emotional labor is not necessarily gender specific (Goleman 1998), the
overwhelming majority of studies show that women both provide more emotional labor
and are subject to expectations that they will do so (Bellas 1999; Hochschild 1979, 1983;
James 1989; Martin 1999; Pierce 1999; Webb 2001). This is akin to gendered differences
in family care responsibilities: Although no physiological justification exists for one sex
or the other to assume such duties, particularly elder care, women provide and are
expected to provide the bulk of family care. Hochschild has revealed and articulated the
gendered dimensions of both emotional labor (1979, 1983) and family care (1997),
finding that women not only provide the bulk of both but also are expected to do so. To
proceed with analyses of family care responsibilities or emotional labor provision as if
such highly institutionalized behaviors and expectations did not exist is not useful, in our
view. Thus, Martin's (1999) study of police officers is especially relevant because women
police officers were expected to provide emotional labor within the organization through
"informal interaction with other officers," in contrast to interactions with citizens, where
both male and female officers were expected to provide emotional labor. Much of the
gender segregation by occupation has links to emotional labor because many femaledominated occupations are expected to employ emotional skills to bring about
organizational ends, whereas male-dominated occupations are not.
Much of the gender segregation by occupation has links to emotional labor because many femaledominated occupation are expected to employ emotional skills to bring about organizational ends,
whereas male-dominated occupations are not.
The gendered nature of emotional labor is perhaps best revealed by feminist theories of
bureaucracy. In the work of Ferguson (1984), Stivers (1995, 2002), and others, the traits
associated with emotional labor--capacity for employing emotions as a skill to achieve
organizational mission, willingness to listen, ability to see other sides of an issue, a
concern with personal relationships, the nurturing others--are the traits bureaucracies seek
to eliminate, reduce, or at least undervalue. Stivers, in particular, seeks an explicit
recognition of these feminine roles and a restructuring of bureaucracy to accommodate
them.(FN2)
From a somewhat different perspective, one can seek elements of emotional labor or
the importance of emotional labor in some management theories. The stress on informal
aspects of organizations in the human relations approach is fairly self-evident (Argyris
1964; McGregor 1960). Less self-evident but equally supportive is the emphasis on
values as central to organizations and building loyalty within the organization (Barnard
1938; Simon 1947). More recently, even the New Public Management, an approach that
ostensibly takes efficiency as its preeminent value, has a "citizens as customers"
orientation (Dilulio, Garvey, and Kettl 1993; Osborne and Gaebler 1992). If agencies see
themselves as providing services to customers, then emotional labor becomes an integral
part of the process of gaining consumer support and loyalty.
The literature on emotional labor provides a challenging set of ideas concerning
organizations and research on organizations. This study seeks to add a new dimension to
studies of emotional labor. We ask the question, if emotional labor exists and if it is
primarily associated with women employees, how do organizations differ? How would
this generate evidence of better relationships with clients or better relationships among
employees? How might either of these differences be tied to what organizations can
accomplish?
The Empirical Study
Virtually all studies of emotional labor are either theoretical or qualitative case studies
(an exception is Guy and Newman, who use the concept as a basis for explaining gender
differences in salaries; see also Mastracci, Newman, and Guy 2004). One of the reasons
for this methodological choice is that emotional labor can be documented only by
observing interactions between one person and another (either another employee or an
organization's client). Documenting emotional labor in large-scale studies, as a result, is
difficult, if not impossible. This study takes a different approach: It assumes that women
are the preponderant suppliers of emotional labor and then looks at whether the other
implications of emotional labor appear in organizations that employ a larger proportion of
women. Again, one might charge that the assumption that emotional labor is gauged by
the proportion of women in an organization is essentialist. However, this initial attempt to
estimate emotional labor and to link it to organizational performance not only calls
attention to the importance of emotional labor as a factor in performance but also the
need for better measures. Although it is an imperfect and perhaps unfair proxy for
emotional labor, our operating assumption is supported by the literature. Guy and
Newman list several examples of "the conflation of gender and emotional labor" (2004,
293-94), and Glomb, Kammeyer-Mueller, and Rotundo (2002) have found a statistically
significant link between emotional labor demands in an occupation and lower wages.
Notably, low-wage occupations are consistently female dominated (Mastracci 2003). In
short, if the assumption that women supply most of the emotional labor to an
organization is true, how else might these organizations be different in predictable ways?
Theoretical Hypothesis 1: Organizations with more emotional labor will have more
positive interactions with clients (Guy and Newman 2004, 295). This hypothesis is the
central theoretical argument concerning emotional labor. As employees bring more
emotional labor to their interactions with clients, clients will be more satisfied with these
interactions and engage in behavior that facilitates organizational performance. This
behavior might be as simple as showing up at the organization for treatment, or it might
consist of relatively elaborate behaviors, such as those called for in the coproduction of
mental health or education services.
Theoretical Hypothesis 2: In organizations with more emotional labor, relationships
within the organization should be better. Emotional labor provides the glue that holds
organizations together. Theoretically, it makes the organization a more pleasant place to
work; it might even provide significant job satisfaction to individuals who provide that
labor. One implication of this greater satisfaction, then, is that these organizations will
experience fewer personnel problems (Guy and Newman 2004, 292). We are not
assuming, however, that only one type of emotion--niceness, politeness, or caring-necessarily brings about positive organizational outcomes. Assertiveness and the creation
of an environment in which individuals feel free to state their needs plainly and confront
even sensitive issues openly can also bring about positive organizational outcomes. We
hypothesize that a greater proportion of women--who have been found not only to
provide emotional labor but also are expected to do so (Bellas 1999; Guy and Newman
2004; Hochschild 1983)--will engender such an environment and will enable the capacity
for emotional work necessary to bring that about. All else being equal (labor pool
characteristics, agency missions, etc.), such organizations might have lower turnover
rates than similar organizations. Testing this hypothesis and others requires a set of
organizations that perform the same function.
Theoretical Hypothesis 3: Organizations with more emotional labor will be more
effective than other organizations, all else being equal The bottom-line argument for
emotional labor is that it improves organizational performance. One argument flows
directly from hypotheses 1 and 2. High levels of organizational turnover require
organizations to invest more funds in the recruitment and training of workers. New
workers face a learning curve whereby they get better at their jobs as they become more
familiar with organizational expectations. Lower turnover, therefore, should lead to more
organizational effectiveness. Similarly, more cooperative clients who are willing to assist
rather than resist the organization should make the attainment of organizational goals
easier. Whether these are the only two ways that emotional labor facilitates
organizational effectiveness is open to question, however, simply because emotional
labor might also influence other organizational processes (e.g., team building, more open
accountability processes). Any empirical test should determine whether emotional labor
has an impact on performance over and above its impact on turnover and client behavior.
The Empirical Setting: School Districts
Schools are ideal settings in which to examine the influence of emotional labor.
Several scholars specifically mention teaching as a job that has an emotional labor
component (Bellas 1999; Guy and Newman 2004; Hargreaves 1995; James 1989; Nias
1996). Education requires teachers to interact on several levels with students in order to
motivate them to learn. The educational literature is in unanimous agreement that
although classroom instruction is important, what students do at home is also critical.
Education, in short, is a classic coproduced good that requires the cooperation of the
student and the student's family. The study of schools as organizations is facilitated by
the existence of large data sets documenting everything from student performance down
to the minute details of educational finance. These extensive databases mean that studies
of schools or school districts as organizations do not have to start from square one but
have both a good database and an extensive literature that suggests how processes work.
This study examines the universe of Texas school districts during three academic years
(2000-02). In addition to having an excellent database that has been used to study other
important questions about public organizations (Bohte 2001; Smith and GranbergRademacker 2003; Smith and Larimer 2004; Weiher 2000), Texas has the advantage of
being home to more than 1,000 of the 14,000 school districts in the United States. These
districts range from rural to urban, rich to poor, small to large, and homogeneous to
heterogeneous. In short, as educational organizations go, they are highly diverse. The
findings from this study, therefore, can likely be generalized to other public school
systems. Whether they can be generalized to other public organizations is an open
question. Although public schools are the most common public organizations in the
United States and employ far more public servants than any other type of governmental
organization, schools are highly professionalized organizations that vest a great deal of
discretion at the street level (i.e., the classroom). The findings here most likely apply to
similar types of organizations, but only additional empirical studies can verify that
contention.
Key Variables and Research Hypotheses
The four key theoretical variables in this study are emotional labor, client satisfaction,
employee satisfaction, and organizational performance. As noted previously, we assume
that emotional labor can be measured by the percentage of female employees and that
organizations with more female employees will generate more emotional labor, all else
being equal. In this study, we use the percentage of teachers who are female. Education is
a policy area that is characterized by glass ceilings: Although teachers are overwhelming
female, as one moves up the hierarchy, only 8 percent of superintendents are women
(Meier and Wilkins 2002). The average district in this study had 75.4 percent female
teachers, but the range is substantial, from 38.9 percent to 100 percent.
Though client satisfaction might be measured in a variety of ways (and we could
debate whether schoolchildren, their parents, or others in the community are the clients),
this study uses student attendance. We assume that emotional labor makes the
educational experience more pleasant for students. Although much of absenteeism is
unavoidable because of illness or other factors, a portion of it is linked to student
motivation. Particularly among older students, positive experiences in school are
associated with higher attendance (Phillips 1997). The measure is the average daily
attendance percentage, which ranges from 91.4 percent to 99.2 percent.
H[sub1]: The percentage of female teachers will be positively associated with average
daily attendance.
As noted earlier, employee satisfaction will be measured by employee turnover--in this
case, teacher turnover. Compared to most other public employees, teacher turnover is
high. The average district had 16.9 percent of its teachers leave in a year; again, the range
is substantial, from 0 percent to 100 percent (in the latter case, a school district with three
teachers had all leave in the same year).
H[sub2]: School districts with higher percentages of female teachers will have lower
teacher turnover rates.
Four measures of organizational outcomes are used to assess the effectiveness of these
school districts. Clearly, the most salient outcome measure for Texas schools is their
overall pass rate on the state standardized test (known during 2000-02 as the Texas
Assessment of Academic Skills, or TAAS). The TAAS is a high-stakes test that students
must pass in order to graduate from high school; schools and school districts are
evaluated based on the TAAS, and those evaluations are front-page news when released.
The mean pass rate for the TAAS was 84.5 percent, with a range of 32 percent to 100
percent. The TAAS is a mid-level achievement indicator, picking up basic skills. A full
assessment of performance would also look at indicators that are more sensitive to at-risk
students and those that reflect the performance of the district's best students. For at-risk
students, we will use the dropout rate, measured as the total percentage of students who
drop out of school in grades 9-12 (mean = 5.2 percent, range = 0 percent to 37.5 percent).
Although they are widely criticized as underestimating the true dropout rate, the official
figures provide a rough gauge of performance failure for at-risk students. For collegebound students, we use the average ACT score (Texas institutions of higher education
require the ACT; mean= 19.9, range = 12.2 to 26.7) and the percentage of students who
scored above 1110 on the SAT or its ACT equivalent (a state-defined measure of college
readiness; mean = 20.9 percent, range = 0 percent to 75 percent).
H[sub3]: The percentage of female teachers will be positively associated with TAAS
scores, ACT scores, and the percentage of students scoring above 1110 on the SAT and
negatively associated with dropouts.
Control Variables
A variety of other factors affect attendance, turnover, and organizational performance,
so a series of control variables must be included in each regression. Because class
attendance can be considered similar to an organizational performance indicator
(although it is an output rather than an outcome), it can be estimated with the same set of
controls as the other outcome measures. In the field of education, a well-developed set of
educational production functions exist that specify the types of variables that should be
used as controls (Hanushek 1996; Hedges and Greenwald 1996). Essentially, these
control variables can be grouped into two sets: resources and constraints. As indicators of
resources, we include per-student spending on instruction, average teacher salary, class
size, average years of teacher experience, and the percentage of noncertified teachers. As
constraints on performance, we include the percentages of black, Latino, and poor
students, the latter being defined as students who are eligible for free or reduced-price
school lunches.
Teacher turnover is a different phenomenon from organizational performance, and
therefore, it is likely affected by different factors. We generally expect that incentives, the
difficulty of the job, and organizational support factors play a role in personnel turnover
(Griffeth, Hom, and Gaertner 2000). To tap incentives, we include both the average
teacher salary and the median income of all persons living in the school district (in
combination, these contrast non-teaching opportunities with teaching remuneration). Task
difficulty is measured in the same way as constraints in the production function--the
percentages of black, Latino, and poor students. Organizational support factors include
class size, the ratio of teacher aides to students, and the number of administrative staff per
100 students. Because new teachers are more likely to leave the profession, the
percentage of teachers with five or fewer years of experience is included. Finally,
because student performance might make the job more attractive to teachers, we include
the TAAS pass rate from the previous year in the equation.
In both cases, the objective is not to provide a complete explanation of the dependent
variables--that is a question of concern for education policy, not public administration.
Rather, the objective is to include sufficient controls so that we can be confident the
results are not spurious. Because we have several indicators of a given concept, such as
resources, the equations are characterized by a fair amount of collinearity in these
variables. As a result, the individual resource coefficients sometimes become negative in
the presence of controls for other resources. Finally, each of the equations includes
dummy variables for the years 2001 and 2002 to control for any serial correlation in the
data.
Findings
If our theoretical assumption is correct and emotional labor is provided primarily by
female employees, we should see a positive correlation between female teachers and
student attendance. Although many attendance patterns are not systematic, simply
because illnesses cannot be predicted in advance (see table 1), the regression results show
a positive relationship between the percentage of female teachers and student attendance.
A 1 percentage point increase in female teachers is associated with a 0.0102 percentage
point increase in class attendance, all else being equal. The relationship is not large, but
over the full range of the data, female teachers make a 0.63 percentage point difference-about 8.1 percent of the current range-- in attendance. Relatively small differences such
as this, when spread out over the 4.2 million students in Texas, could have a substantial
impact.(FN3) Our first hypothesis is supported by the data. The remaining significant
relationships in the table are consistent with our expectations: Lower attendance is
associated with black students, poor students, larger classes, and uncertified teachers.
Table 1 Emotional Labor and Client Satisfaction: The Relationship between Female
Employment and Attendance
Dependent Variable = Daily Class Attendance (Percent)
Independent Variable
Slope
T-score
Female teachers (percent)
.0102
5.24
Teachers salaries (thousands)
-.0046
0.56
Instructional funding (thousands)
-.0186
0.93
Black students (percent)
-.0065
4.71
Latino students (percent)
.0009
1.02
Low-income students (percent)
-.0103
8.34
Class size
-.1275
12.28
Teacher experience
.0087
1.17
Noncertified teachers
-.0131
4.83
R[sup2]
.20
Standard error
.74
F
70.63
N
3,118
Note: Coefficients for individual years are not reported.
Do the positive benefits of emotional labor also accrue to employees of the
organization? We hypothesized that because greater emotional labor would generate
more satisfaction with the job, it would reduce turnover. Because turnover varies a great
deal by type of organization and by profession, having a large number of organizations
that perform the same function-- education--is useful. Table 2 shows that a 1 percentage
point increase in female teachers is associated with a 0.12 percentage point decline in
teacher turnover, all else being equal. Over the full range of the data, this translates into a
maximum reduction in teacher turnover of about 7.5 percentage points, almost a full
standard deviation in turnover rates (or approximately 21,000 teachers per year). With a
few exceptions, turnover is negatively related to low-income students and positively
associated with more teacher aides; the remaining relationships in table 2 are consistent
with the expectations in the literature.
Increased student attendance and lower teacher turnover are intermediate processes in
the education system. What is more important is the knowledge learned by the student.
Do greater attendance and lower teacher turnover translate into higher achievement
levels? Table 3 presents three different views of the relationship of emotional labor to
student performance on the TAAS. The first column uses the percentage of female
teachers as the sole indicator of emotional labor. A 1 percentage point increase in female
teachers is associated with a 0.0746 percentage point increase in the number of students
passing the TAAS, all else being equal. Over the full range of the data, this translates to a
maximum impact of about 4.5 points on the TAAS, a little over one-half of a standard
deviation in test results. All other relationships in the first column are consistent with the
findings in the literature, except for instructional funding. Instructional funding is fairly
collinear with the other variables in the model, sharing 70 percent of its variance with
other independent variables, notably, teacher salaries and class size (which, in
combination, make up most of instructional funding). The high level of collinearity
changes this sign from positive to negative.
Table 2 Emotional Labor and Employee Satisfaction: The Relationship between
Female Employment and Turnover
Dependent Variable = Teacher Turnover (Percent)
Independent Variable
Slope
T-score
Female teachers (percent)
-.1214
6.39
Teachers salaries (thousands)
-.5007
6.27
Median income (thousands)
.0374
2.03
Black students (percent)
.0458
3.32
Latino students (percent)
.0050
0.56
Low-income students (percent)
-.0285
2.06
Class size
.0166
0.22
Less than five years experience
.2076
14.20
Teachers aides
.0718
2.49
Total bureaucracy
1.8591
6.69
TAAS pass rate (t-1)
-.1332
7.03
R[sup2]
.23
Standard error
7.24
F
72.83
N
3,111
Note: Coefficients for individual years are not reported.
The second column of table 3 adds student attendance and teacher turnover directly
into the model. The estimation is designed to tell us whether the full impact of female
teachers (the surrogate variable for emotional labor) operates through improved student
attendance and lower teacher turnover or whether female teachers have an impact over
and above the influence of these two processes. The second column shows that student
attendance and teacher turnover have strong relationships in the predicted direction with
student performance. Although the impact of female teachers is reduced by about onehalf, it remains a strong positive influence on student performance. In short, if we are
correct in our assumption about emotional labor, it influences student performance both
directly and indirectly by improving student attendance and by lowering teacher turnover.
The final column of table 3 specifies a stringent test of our emotional labor hypothesis
by including a lagged dependent variable. Such a specification requires our independent
variables to influence student performance over and above any influence the variables
might have had in past years. This specification does reduce the direct impact of female
teachers to zero, but the influence of both attendance and teacher turnover remain
significant in the predicted direction. Even with the stringent autoregressive estimation in
the last column, our third empirical hypothesis is supported.
Table 3 Emotional Labor and Organizational Performance: Female Employment and
Student Test Scores
Dependent Variable = Percent Passing the TAAS
Independent Variable
Slope
Slope
Slope
Female teachers (percent)
.0746 (4.54)
.0362(2.31)
.0088 (0.79)
Attendance rate
--2.4390(16.97)
.5216 (4.86)
Teacher turnover rate
---.1146(7.71)
-.0442 (4.17)
Lagged TASS pass rate
----.6619 (55.63)
Teachers salaries (thousands)
.7438(10.64)
.6877(10.27)
.2307 (4.80)
Instructional funding (thousands)
-1.1022(5.43)
-1.0387(5.40)
-.2481 (1.80)
Black students (percent)
-.1894(16.19)
-.1624(14.51)
-.0458 (5.60)
Latino students (percent)
-.0666(8.63)
-.0657(8.98)
-.0186 (3.55)
Low-income students (percent)
-.1193(11.43)
-.0977(9.76)
-.0296 (4.12)
Class size
-.6641(6.99)
-.3681(4.03)
-.1544 (2.38)
Teacher experience
.1673(2.65)
.0466(0.76)
-.0243 (0.56)
Noncertified teachers
-.0940(4.10)
-.0382(1.74)
-.0083 (0.53)
R[sup2]
.41
.47
.73
Standard error
6.45
6.10
4.31
F
192.24
210.36
611.26
N
3,117
3,117
3,116
Note: Coefficients for individual years are not reported.
Table 4 extends the analysis to three other educational outcomes--dropouts, ACT
scores, and high scores on the college boards. In all three cases, the percentage of female
teachers is associated with more positive outcomes for students (dropouts are a negative
factor, so the relationship should be negative). The direct impacts of female teachers are
supplemented by indirect impacts through improved student attendance in all three cases.
The teacher turnover rate, however, has no influence at all on any of these three student
outcome measures.
Conclusion
This article has investigated the concept of emotional labor in educational
organizations. Our strategy was to assume that emotional labor existed and that women
would be more likely than men to provide it. Based on that assumption, three empirical
hypotheses were tested using Texas educational data. We found that organizations with
more women at the street level--in the classroom--were also characterized by higher
student attendance, lower teacher turnover, and higher overall organizational
performance. The performance equations suggest that emotional labor contributes to
organizational productivity over and above its contribution to employee turnover and
client satisfaction.
Although we did not measure emotional labor directly (in fact, it is unclear how one
might do so in a large-scale study), the concept of emotional labor provided a plausible
causal theory as to why the relationships we found were likely (Lynn, Heinrich, and Hill
2001). By facilitating cordial relationships among teachers and by enticing students to
enjoy the education process, emotional labor should reduce turnover and improve client
relationships. As befitting the first study of its type, the analysis raises more questions
than it answers. Some of these questions are empirical, others are normative.
Table 4 Emotional Labor and Organizational Performance: Female Employment and
Other Performance Indicators
Dependent
Variables
Independent Variable
Dropouts
College percent
Female teachers (percent)
-.0256 (1.82)
(8.36)
.2938 (8.35)
Attendance rate
-1.5974 (14.86)
(3.92)
1.0716 (3.93)
Teacher turnover rate
-.0144 (1.18)
(0.39)
.0135 (0.17)
Teachers salaries (thousands)
-.0807 (1.60)
(5.06)
.7746 (6.30)
Instructional funding (thousands)
.0005 (0.00)
(1.95)
-.6891 (1.71)
Black students (percent)
.0375 (4.62)
(7.13)
.0245 (123)
Latino students (percent)
.0179 (3.27)
(4.91)
.0279 (2.06)
Low-income students (percent)
.0409 (5.31)
(13.70)
-.2889 (15.02)
Class size
.2141 (3.00)
(1.20)
-.1147 (0.64)
ACT
.0398
.1405
.0016
.0818
-.1054
-.0189
-.0088
-.0349
-.0282
Teacher experience
.0606 (1.32)
(1.20)
.0916 (0.81)
Noncertified teachers
.0148 (0.91)
(2.24)
-.1364 (3.36)
R[sup2]
.23
.31
Standard error
4.19
9.97
F
66.37
94.77
N
2,897
2,785
Note: Coefficients for individual years are not reported.
.0179
-.0175
.41
1.26
141.25
2,610
Guy and Newman (2004, 296) conclude their essay with the statement, "Making
emotional labor visible is the first step; making it compensable is the next." Although this
study did not address how emotional labor might be compensated, by linking emotional
labor to organizational outcomes, it implies one way that organizations could monetarize
the contribution of emotional labor. The link to performance provides an objective way
of placing an organizational price on emotional labor: by directly linking pay to
performance. At the same time, such a strategy is unlikely in these organizations, for
several reasons. First, though linking pay to performance has generated some
controversy in many organizations, it is particularly controversial in education, with
strong opposition from teachers' unions. Pay-for-performance proposals in education are
viewed by many as an effort to reduce all of education to a narrow set of economic values
(Smith 2003). Second, pay structures in U.S. education are set up in a gender-neutral
process by which every teacher with the same education and years of experience is paid
the same salary (with a few modest exceptions for scarce specializations, such as math or
bilingual education). Under this system, it is simply not possible to pay a woman less for
filling the same role as a man.(FN4) Given that all personnel systems with discretion
appear to create gender inequities, restoring discretion to the educational personnel
process through a pay-for-performance system may not be an advantage for women.
Third, moving to monetarize emotional labor by linking pay to performance might create
incentives for behaviors that then undercut the benefits of emotional labor. Incentive
systems are known to create self-interested behavior that maximizes one's own income at
the expense of others (Blau 1956). Such actions might dissuade employees from
providing emotional labor to their colleagues.
Second, are there aspects of emotional labor that are their own reward? All incentive
systems distinguish between monetary incentives and normative incentives, such as the
value of work, the benefits of associating with colleagues, and similar nonutilitarian
rewards (Etzioni 1964; Wilson 1989). Any set of conversations with individuals in the
helping professions (teaching, nursing, social work) will reveal that self-selection biases
operate. Individuals choose such professions precisely because they provide an
opportunity for normative rewards, one of which might be the use of emotional labor. If
emotional labor is self-fulfilling, are their risks inherent in trying to monetarize it? Webb
observed increased dissension and resistance within one state-level government office
when attempts were made to elevate emotion work to a skill in job descriptions and
performance evaluations: "change is resisted because the employers' aim is to
consolidate the bonus element into normal pay, which would result, at least in the short
term, in lower pay for many men" (2001, 831). Webb reveals one risk of monetarizing
emotion work, but further research could find others.
Third, the impact of emotional labor on organizational performance immediately
raises the question of how one manages emotional labor. As Morris and Feldman (1996)
note, organizational sanction affects how easy it is to incorporate emotional labor into
one's work. Just as organization leaders define a set of values for an organization
(Barnard 1938), they also need to define a set of emotions that are appropriate (or
inappropriate) for the organization and the conditions under which given emotions are
appropriate.
Fourth, does emotional labor by public servants who deal directly with the public-street-level personnel-- interact at all with the gender composition of management?
Pierce's (1997) paralegal example suggests that emotional labor might increase in
organizations with male managers because street-level personnel need to adjust for the
behavior of upper-level management. At the same time, one might make the opposite
arguments about the link between gender and emotional labor, suggesting that female
managers would be more encouraging of emotional labor.
Fifth, how do the uses of emotional labor inside and outside the organization affect
each other? Are they complementary? Or is there a limited supply of emotional labor that
an organization can produce, so that whatever is expended inside detracts from what is
available to client interactions?
Sixth, does emotional labor have other impacts on the organization and its processes?
This study only examined two--client participation and employee turnover. The
willingness to work additional hours (perhaps uncompensated), a reduction in sick leave
taken, a decline in the number of employee grievances, and a drop in adverse personnel
actions are four possibilities. The form of the impacts is also worthy of study. Rafaeli and
Sutton (1987) postulate that emotional labor can have short-term, long-term, and
contagion effects. Contagion effects are especially interesting because they imply that the
benefits to the organization will increase in a nonlinear manner as more members of the
organization contribute emotional labor. In terms of short- and long-term influences,
emotional labor might be similar to human capital, whereby in the short term,
investments in human capital decrease production (employees are engaging in emotional
labor rather than actual production), but these investments provide a stock of capital that
will generate long-term increases in performance. Again, this initial attempt to estimate
emotional labor and to link it to organizational performance calls attention to both the
importance of emotional labor as a factor in performance and the need for further
research.
Quite clearly, many questions about emotional labor and its role in public
organizations remain to be answered, especially when one considers the range of
hypotheses linked to pay equity that Guy and Newman propose. Many of these questions
are connected to the issue of measurement. This study has shown one way that emotional
labor can be examined using existing data sets, but multiple-methods research involving
primary data sources may prove to be the best approach to examining such a complex and
nuanced workplace phenomenon. Although the approach used in this study cannot tap the
interpersonal nuances of emotional labor and its many facets, it does place the concept in
a multiorganizational context and tie it into an extensive literature on organizational
performance.
Understanding how public organizations operate and how they incorporate values has
a long and honorable intellectual tradition. Emotion is a seriously understudied value that
offers great promise within that tradition. Only a wide range of methods and approaches,
including in-depth interviews, focus groups, participant observation and large-scale
quantitative studies, can provide a full understanding of the role of emotion in
organizations.
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ADDED MATERIAL
Kenneth J. Meier is the Charles H. Gregory Chair in Liberal Arts and Distinguished
Professor of Political Science at Texas A & M University and a professor of public
management at Cardiff University, Wales. He received the 2006 John Gaus Award for
exemplary scholarship in the joint tradition of political science and public administration.
His current research projects focus on building a quantitative theory of public
management and the role of race, ethnicity, and gender in public policy. E-mail:
kmeier@polisci.tamu.edu.
Sharon Mastracci is an assistant professor in the graduate program in public
administration at the University of Illinois at Chicago. She studies public personnel
policies, the changing labor force, and occupational segregation by gender--the different
ways that men and women find jobs, the different expectations of women and men at
work, and how workplace phenomena affect women and men differently. She is the
author of Breaking Out of the Pink Collar Ghetto: Policy Solutions for Non-College
Women (M.E. Sharpe, 2004). E-mail: mastracc@uic.edu.
Kristin Wilson is a former graduate student at Texas A & M University. She is
currently pursuing a career in secondary education.
Notes
1. This is also implied by economic theory along two dimensions--wages and skills--with
varying implications. With respect to skills, qualitatively different skill sets would make
women and men poor substitutes if the skills provided by one group tend not to be found
in the other. If equipment and machinery can replace technical skills but not emotional
skills, for example, then firms' investments in capital reduce the relative value of
technical skills, which may jeopardize men's employment. Offshoring and outsourcing
might have similar impacts. Hamermesh (1993) describes how policies that increase one
group's labor cost relative to another's lower the demand for the costlier group. However,
with respect to wages, because emotion work is undervalued, women may be substitutes
for men in firms that are interested in lowering their wage bill for jobs that involve such
skills. This could have the effect of jeopardizing men's employment in certain jobs, but it
also may exacerbate occupational segregation by gender, hindering women's access to
high-paying, higher-skilled jobs.
2. The argument is far more complex than is noted here. It is tied to philosophical
distinctions between the public and private spheres and the assignment of traits and
values to each of these spheres. The beneficial impact of emotional labor, in this context,
shows the illogic of organization theories that seek to explain organizational behavior
without taking concepts such as emotional labor into consideration.
3. An increase of 0.63 percent in student attendance means that approximately 26,000
more students are attending class each day of the year.
4. As an illustration, the correlation between the percentage of female teachers and
average teacher salary in this data set is -.025, a figure that is not statistically significant
even with more than 3,000 cases.