DOE Weapons Laboratories
Actions Needed to Strengthen EEO Oversight
Gao ID: GAO-02-391 April 22, 2002
Allegations of racial profiling at the Department of Energy's (DOE) weapons laboratories raised questions about the equitable treatment of minorities and women in personnel actions at these laboratories. The former secretary of energy reiterated a policy of zero tolerance of discrimination of any kind and said that he expected and required full compliance with both the spirit and letter of all civil rights laws, regulations, and policies. The current secretary has reaffirmed this commitment. In 2000, the percentage of minority employees at each of the laboratories ranged from 19 percent at Lawrence Livermore to 34 percent at Los Alamos. The minority population at the laboratories increased from 1995 to 2000 but not for each minority group at each laboratory. For fiscal years 1998 through 2000, GAO found statistically significant differences in some personnel actions, but not in others, when minority men and women and white women in managerial and professional job categories were compared with white men in these categories. Comparing men and women of same race or ethnicity, GAO found that white, Asian, and Hispanic women earned less than did their male counterparts. GAO found that management promotions for minority men and women and white women generally met 80 percent of the promotion rate for white men. Because of data limitations, GAO could not determine whether minority men and women and white women were as likely as white men to be hired by the laboratories. Minority and female laboratory staff raised concerns in four areas--recruiting, pay, promotion, and laboratory work environment. These data are from recent laboratory surveys and studies, a DOE 2000 Task Force Against Racial Profiling, and formal complaints investigated by OFCCP from 1990 through 2001. DOE and OFCCP must work together to ensure that the laboratories meet EEOC requirements.
Recommendations
Our recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
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GAO-02-391, DOE Weapons Laboratories: Actions Needed to Strengthen EEO Oversight
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United States General Accounting Office:
GAO:
Report to Congressional Requesters:
April 2002:
DOE Weapons Laboratories:
Actions Needed to Strengthen EEO Oversight:
GAO-02-391:
Contents:
Letter:
Results in Brief:
Background:
The Composition of Staff Varies by Laboratory, and Each Laboratory Has
Seen Some Change in Job Category Groups by Race/Ethnicity and Gender in
1995 Compared with 2000:
Certain Personnel Actions for Managers and Professionals Show
Statistically Significant Differences for Minority Men and Women and
White Women Compared with White Men, While Others Do Not:
Staffs‘ EEO Concerns Focus Primarily on Four Issues:
Improved Collaboration between DOE and OFCCP Could Help to Ensure
Laboratories‘ EEO Compliance:
Conclusions:
Recommendations for Executive Action:
Agency Comments:
Appendix I: Objectives, Scope, and Methodology:
First Objective: Describe the Composition of Weapons Laboratory Staff
by Race/Ethnicity, Gender, and Job Category in 1995 and 2000:
Second Objective: Determine Whether There are Statistically Significant
Differences in Selected Personnel Actions for Managers and
Professionals When Comparing Minority Men and Women and White Women
with White Men in Fiscal Years 1998 through 2000:
Third Objective: Describe EEO Concerns Raised by Laboratory Staff:
Fourth Objective: Identify, if Appropriate, Opportunities for Improving
DOE‘s and OFCCP‘s Oversight of the Laboratories‘ Compliance with EEO
Requirements:
Appendix II: Composition of Staff by Job Category Group as a Percentage
of Their Race/Ethnicity and Gender Group:
Appendix III: Additional Information on Personnel Actions at the Three
Laboratories:
Descriptive Statistics for Variables Used in Our Analysis of Salary,
Merit Pay, Cash Awards, and Separations for Managerial and Professional
Laboratory Staff:
Number and Type of Disciplinary Actions Taken, by Race/Ethnicity and
Gender for Managerial and Professional Laboratory Staff:
Results of Tests for Men Versus Women and Minority Versus Nonminority
for Managerial and Professional Laboratory Staff:
Appendix IV: Comments from the Department of Energy:
Appendix V: Comments from the Department of Labor:
Appendix VI: GAO Contacts and Staff Acknowledgments:
Tables:
Table 1: Percent Difference in Salaries for Managerial and Professional
Minority Men and Women and White Women in Comparison with White Men,
Fiscal Years 1998 through 2000:
Table 2: Percent Differences in Merit Pay Increases for Managerial and
Professional Minority Men and Women and White Women in Comparison with
White Men, Fiscal Years 1998 through 2000:
Table 3: Differences in the Likelihood of Receiving a Cash Award for
Managerial and Professional Minority Men and Women and White Women in
Comparison with White Men, Fiscal Years 1998 through 2000:
Table 4: Differences in the Likelihood of Separating from the
Laboratory for Managerial and Professional Minority Men and Women and
White Women in Comparison with White Men, Fiscal Years 1998 through
2000:
Table 5: Number of Promotions for Each Race/Ethnicity and Gender Group,
Percentage of the Group Promoted, and Number of Additional Promotions
Needed to Reach 80 Percent of the Promotion Rate of White Men, Fiscal
Years 1998 through 2000:
Table 6: DOE‘s EEO Ratings for Los Alamos and Lawrence Livermore,
Fiscal Years 1998 through 2000:
Table 7: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff, Fiscal Years 1998 through 2000:
Table 8: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff”Variables Used in the Salary, Merit Pay,
Cash Award, and Separation Analyses, Fiscal Years 1998 through 2000:
Table 9: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff”Average Base Salary for Job Subcategories
Used in the Analysis, Fiscal Years 1998 through 2000:
Table 10: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff, Fiscal Years 1998 through 2000:
Table 11: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff”Variables Used in the Salary, Merit Pay, Cash Award,
and Separation Analyses, Fiscal Years 1998 through 2000:
Table 12: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff”Average Base Salary for Job Subcategories Used in the
Analysis, Fiscal Years 1998 through 2000:
Table 13: Descriptive Statistics for Lawrence Livermore Managerial and
Professional Laboratory Staff, Fiscal Years 1998 through 2000:
Table 14: Descriptive Statistics for Lawrence Livermore Managerial and
Professional Laboratory Staff”Variables Used in the Salary, Merit Pay,
Cash Award, and Separation Analyses, Fiscal Years 1998 through 2000:
Table 15: Descriptive Statistics of Lawrence Livermore Managerial and
Professional Laboratory Staff”Average Base Salary for Job Subcategories
Used in the Analysis, Fiscal Years 1998 through 2000:
Table 16: Disciplinary Actions at Los Alamos for Managerial and
Professional Laboratory Staff, 1995 through June 2001:
Table 17: Disciplinary Actions at Sandia for Managerial and
Professional Laboratory Staff, 1995 through June 2001:
Table 18: Disciplinary Actions at Lawrence Livermore for Managerial and
Professional Laboratory Staff, 1995 through 2000:
Table 19: Results for Managerial and Professional Laboratory Staff of
Salary, Merit Pay, Cash Awards, and Separations Analyses Comparing All
Women with All Men, Fiscal Years 1998 through 2000:
Table 20: Results for Managerial and Professional Laboratory Staff of
Salary, Merit Pay, Cash Awards, and Separations Analyses Comparing All
Minorities with Nonminorities, Fiscal Years 1998 through 2000:
Figures:
Figure 1: Percentage of Positions in Each Job Category Group at the
Three Weapons Laboratories, 2000:
Figure 2: Composition of Laboratory Staff at Los Alamos, by
Race/Ethnicity, 1995 and 2000:
Figure 3: Composition of Laboratory Staff at Sandia, by Race/Ethnicity,
1995 and 2000:
Figure 4: Composition of Laboratory Staff at Lawrence Livermore, by
Race/Ethnicity, 1995 and 2000:
Figure 5: Composition of Each Laboratory‘s Staff, by Gender, 1995 and
2000:
Figure 6: Composition of Job Category Group at Los Alamos by White Men,
White Women, and Minorities, 1995 and 2000:
Figure 7: Composition of Job Category Group at Los Alamos by Each
Minority Group, 1995 and 2000:
Figure 8: Composition of Job Category Group at Sandia by White Men,
White Women, and Minorities, 1995 and 2000:
Figure 9: Composition of Job Category Group at Sandia by Each Minority
Group, 1995 and 2000:
Figure 10: Composition of Job Category Group at Lawrence Livermore by
White Men, White Women, and Minorities, 1995 and 2000:
Figure 11: Composition of Job Category Group at Lawrence Livermore by
Each Minority Group, 1995 and 2000:
Figure 12: Composition of Staff at Los Alamos, by Job Category Group,
as a Percentage of Their Gender or Minority Group, 1995 and 2000:
Figure 13: Composition of Staff at Sandia, by Job Category Group, as a
Percentage of Their Gender or Minority Group, 1995 and 2000:
Figure 14: Composition of Staff at Lawrence Livermore, by Job Category
Group, as a Percentage of Their Gender or Minority Group, 1995 and
2000:
Figure 15: Minority Group by Job Category Group at Los Alamos, 1995 and
2000:
Figure 16: Minority Group by Job Category Group at Sandia, 1995 and
2000:
Figure 17: Minority Group by Job Category Group at Lawrence Livermore,
1995 and 2000:
Abbreviations:
DOE: Department of Energy:
EEO: equal employment opportunity:
EEO-1: Employer Information Report:
EEOC: Equal Employment Opportunity Commission:
GAO: General Accounting Office:
GPRA: Government Performance and Results Act of 1993:
OFCCP: Office of Federal Contract Compliance Programs:
WFIS: Work Force Information System:
[End of section]
United States General Accounting Office:
Washington, DC 20548:
April 22, 2002:
The Honorable Eddie Bernice Johnson:
Ranking Minority Member:
Subcommittee on Research:
Committee on Science:
House of Representatives:
The Honorable David Wu:
House of Representatives:
Allegations of racial profiling[Footnote 1] at the Department of
Energy‘s (DOE) weapons laboratories, raised most notably in the 1999
case of Dr. Wen Ho Lee, an Asian American accused of espionage, have
called into question the equitable treatment of minorities and women in
personnel actions at these laboratories in areas such as hiring, pay,
and promotion. Responding to these concerns, the former secretary of
energy reiterated the department‘s position of zero tolerance for
discrimination of any kind and stated that he expected and required
full compliance with both the spirit and letter of all civil rights
laws, regulations, and policies. The current secretary has reaffirmed
this commitment for DOE and its contractor employees.
About 22,000 employees work at the nation‘s three weapons
laboratories”Los Alamos, Sandia, and Lawrence Livermore. These
employees, who, among other things, design nuclear weapons and conduct
nuclear and nonnuclear research and development, operate the
laboratories under contract with DOE. Most of these employees” 65
percent”work as managers and professionals.
Under title VII of the Civil Rights Act of 1964, as amended, employers
cannot discriminate against their employees or job applicants on the
basis of race, color, religion, sex, or national origin. The Equal
Employment Opportunity Commission (EEOC) has primary responsibility for
enforcing compliance with the act for the U.S. workforce. Executive
Order 11246, as amended, prohibits the same type of discrimination as
prohibited by title VII and applies to federal contractors, such as
those that operate the weapons laboratories.
The Department of Labor enforces the order and has assigned this
responsibility to its Office of Federal Contract Compliance Programs
(OFCCP). OFCCP investigates complaints of employment discrimination,
conducts compliance evaluations, and takes administrative and
enforcement actions when necessary. Under an agreement between EEOC
and OFCCP, when a charge of employment discrimination is filed with
OFCCP, it generally refers individual complaints against federal
contractors to EEOC for investigation, while OFCCP generally retains and
investigates discrimination complaints involving groups of people or
patterns of discrimination filed against federal contractors.
Under the executive order, DOE is responsible for ensuring that its
contracts contain the equal employment opportunity (EEO) provisions
required by OFCCP and for cooperating with OFCCP and providing
information and assistance as required. DOE is also responsible for
overseeing the laboratories‘ implementation of the EEO provisions in the
contracts. The primary responsibility for complying with EEO
requirements rests with the laboratories.
Concerned about equitable treatment for minorities and women in
personnel actions at the weapons laboratories, you asked us to
(1) describe the composition of weapons laboratory staff by
race/ethnicity, gender, and job category in 1995 and 2000 to determine
how the composition of laboratory staff has changed in the 5-year
period; (2) determine whether there are statistically significant
differences in selected personnel actions for managers and
professionals when comparing minority men and women and White women
with White men in fiscal years 1998 through 2000, the most current
reliable data available at the time of our data request; (3) describe
EEO concerns raised by laboratory staff; and (4) identify, if
appropriate, opportunities for improving DOE‘s and OFCCP‘s oversight of
the laboratories‘ compliance with EEO requirements. In responding to
these issues, as agreed with your offices, we did not draw conclusions
on the appropriateness of the race/ethnicity and gender composition of
laboratory staff nor on whether the weapons laboratories have
discriminated against any employee or group of employees. Also at your
request, we agreed to perform our analysis for each minority and gender
group if the data were sufficient for such analysis. Minorities include
Asian or Pacific Islander (Asian); Black, not of Hispanic origin
(Black); Hispanic; and American Indian or Alaskan Native (American
Indian), as specified jointly by EEOC and OFCCP.
For our analysis of the composition of laboratory staff, we used the
data on race/ethnicity, gender, and the eight job categories[Footnote
2] that the laboratories are required to provide to EEOC,[Footnote 3]
for 1995 and 2000, and combined those data into three job category
groups: managers and professionals; technicians, clerks, and craft
workers; and operatives, laborers, and service workers.[Footnote 4] We
compared data from 1995 and 2000 to determine how the composition of
laboratory staff had changed in the 5-year period.
For our analysis of whether statistically significant differences by
race/ethnicity and gender in selected personnel actions affecting
managers and professionals occurred,[Footnote 5] we used data from the
laboratories‘ personnel and other databases primarily for fiscal years
1998 through 2000, the most current reliable data available at the time
of our data request. The personnel actions we examined were salary
levels, merit pay increases, cash awards, separations, promotions,
disciplinary actions, and hires. In conducting the statistical tests
for salary, merit pay, cash awards, and separations, we ensured that we
were comparing similar staff by holding constant age; tenure at the
laboratory; education level; job subcategory as defined by the
laboratory; citizenship status; security clearance level; and for
Sandia‘s staff, whether they were located in California or New Mexico.
Although the laboratories have somewhat different personnel systems and
practices, our analyses of personnel actions included only those
variables common to all three. Consequently, our analyses of personnel
actions are neither exhaustive nor specifically tailored for each
laboratory. Our analyses are not designed to prove or disprove
discrimination; rather they are designed to provide information at a
common and aggregate level about race/ethnicity and gender differences
in personnel actions at the laboratories. The presence of a
statistically significant difference does not prove discrimination, nor
does the absence of a statistically significant difference prove that
staff have not been discriminated against. The presence of
statistically significant differences means that we are 95 percent
confident that differences could happen by chance in less than 5
percent of the cases. To determine whether promotions of minority men
and women and White women into management positions reflected the
diversity of the potential applicant pools, we used the 80 percent rule
set out in the federal government‘s Uniform Guidelines on Employment
Selection Procedures.[Footnote 6] Our detailed scope and methodology
are discussed
in appendix I.
Results in Brief:
Weapons laboratories‘ data for 1995 and 2000 show that the composition
of staff varies by laboratory and that each laboratory has seen some
change in job category groups by race/ethnicity and gender. In terms of
staff composition, in 2000, the percentage of minority employees at each
of the laboratories ranged from 19 percent at Lawrence Livermore, to
27 percent at Sandia, to 34 percent at Los Alamos. The three
laboratories experienced some increase in their overall minority
population from 1995 to 2000 but not for each minority group at each
laboratory. Each of the laboratories has similar proportions of men and
women, about 70 percent and 30 percent, respectively, for both years.
In terms of job category group composition by race/ethnicity and
gender, for the 2 years, White men held a greater percentage of the
managerial and professional jobs than their representation in the
laboratory workforce overall”averaging 64 percent compared with 54
percent. Conversely, White women held a lower proportion of managerial
and professional positions than their representation in the laboratory
workforce”averaging 18 percent and 20 percent, respectively. Minorities
held a lower proportion of managerial and professional positions than
their representation in the laboratory workforce”averaging 18 and 26
percent, respectively. From 1995 to 2000, the laboratories experienced
some increase in minority representation in the managers and
professionals job category group but not for each minority group at
each laboratory. White women increased their representation in this job
category group at Los Alamos and Sandia but experienced a decrease at
Lawrence Livermore.
For fiscal years 1998 through 2000, we found statistically significant
differences in certain personnel actions and not in others for minority
men and women and White women in managerial and professional job
categories compared with White men in these categories at the three
laboratories. Most notably, with the exception of Asian men at Los
Alamos and Sandia, and Hispanic men at Lawrence Livermore, the salaries
for minority men and women and White women were lower than for White
men. Comparing men and women of the same race/ethnicity, we found
that White, Asian, and Hispanic women earned less than their male
counterparts. Conversely, merit pay increases for minority men and
women and White women tended to be equal to or greater than merit pay
increases for White men, except for Hispanic men at Lawrence Livermore.
For cash awards, only at Sandia were some minority men and women
more likely to receive cash awards than White men. Only Los Alamos had
statistically significant differences in the likelihood of minority men
and women and White women leaving their jobs compared with White men.
Specifically, Hispanic men and women, White women, and Black and
American Indian men and women were less likely than White men to leave
in the 3-year period. We found that management promotions for minority
men and women and White women generally met 80 percent of the
promotion rate for White men, with a few exceptions. We did not find
statistically significant differences, with some exceptions, for
disciplinary actions. Because of data limitations, we could not
determine whether minority men and women and White women were as likely
as White men to be hired by the laboratories. To understand the
implications of these statistical differences and to evaluate their
practical significance, we are recommending that the secretary of
energy, in consultation with the director of OFCCP, determine their
causes and take appropriate actions.
We identified minority and female laboratory staff‘s EEO concerns in
four areas”recruiting, pay, promotion, and laboratory work environment”
primarily from recent laboratory surveys and studies, a DOE 2000 Task
Force Against Racial Profiling, and formal complaints investigated by
OFCCP from 1990 through 2001. These same EEO concerns also surfaced
during some of our interviews with representatives of racial/ethnic
groups and women at the laboratories. In particular, some minority
staff attribute their low representation in certain job categories to
recruiting strategies that do not extensively target colleges and
universities with large minority populations. In terms of pay, some
minorities and women believe that they are paid less than their White
male peers. They also have concerns about promotion opportunities into
top management positions. Finally, some minorities and women expressed
concerns about the laboratories‘ lack of sensitivity to cultural and
gender differences.
Opportunities exist for DOE and OFCCP to work together toward their
common goal of ensuring that the laboratories meet EEO requirements.
Currently, DOE and OFCCP take different approaches to evaluating the
laboratories‘ EEO performance. In its contract oversight role, DOE
focuses on the laboratories‘ EEO performance in meeting their EEO
objectives by working with laboratory managers throughout the year on
EEO issues and then formally rating the laboratories‘ own assessment of
their EEO performance, annually. In contrast, OFCCP focuses on
enforcing EEO compliance with applicable laws and regulations by
evaluating virtually all aspects of a contractor‘s employment
practices; however, OFCCP conducts its evaluations intermittently.
These two different approaches produce different assessments that at
times appear to yield contradictory results. For example, in 1999, DOE
rated Sandia as ’outstanding“ in human resources, which includes EEO
performance; while a 1999 OFCCP compliance evaluation at Sandia
resulted in two affirmative action program violations for not
addressing ways to increase the hiring and representation of Blacks and
Hispanics at the laboratory; Sandia agreed to correct these problems.
While both DOE‘s and OFCCP‘s approaches yield different information
about the laboratories‘ EEO performance, the agencies work
independently and do not routinely coordinate their efforts. Both
agencies have EEO information and expertise that would be beneficial to
share. Effective coordination among agencies with common goals has been
a long-standing problem in the federal government and difficult to
resolve. The Government Performance and Results Act of 1993 establishes
a framework for coordination among federal agencies”agencies sharing
common goals are to work together to develop program strategies that
support each other‘s efforts. Closer collaboration between DOE and
OFCCP could help ensure that the laboratories comply with EEO
requirements. We are therefore recommending that the secretaries of
energy and of labor explore the costs and benefits of establishing a
formal, ongoing collaborative relationship in order to work more
effectively toward their common goal.
In commenting on a draft of this report, DOE stated that it would work
with the Department of Labor‘s OFCCP to achieve the desired effect of
the recommendations as well as to establish better communication between
the two agencies. DOE further states that it has initiated its own
statistical review, which is consistent with our recommendation. The
Department of Labor also agreed with our recommendations. Specifically,
the Department of Labor‘s OFCCP offers its services and expertise to
DOE so it may perform the necessary and appropriate analysis of the
statistical differences we reported, and if problems exist, OFCCP can
work in partnership with DOE to assist in the design and implementation
of corrective action, as appropriate. Furthermore, the Department of
Labor states that it looks forward to working more closely with DOE in
order to effect stronger EEO workplaces at the nation‘s weapons
laboratories. EEOC did not have any comments on the report‘s findings,
conclusions, or recommendations but did provide minor technical
comments, which we incorporated, as appropriate.
Background:
Contractors operate DOE‘s three major weapons laboratories.[Footnote 7]
The laboratories have a total workforce of about 22,000”Los Alamos, with
about 8,000 employees in New Mexico, and Lawrence Livermore, with
about 6,500 employees in California, are both operated by the
University of California, which has had the contracts, with periodic
revisions, since 1943 and 1952, respectively. The Los Alamos contract
amounted to $1.6 billion in fiscal year 2001. The Lawrence Livermore
contract amounted to $1.4 billion for the same period. Sandia,
employing about 7,500 and located in New Mexico and California, is
operated by the Sandia Corporation, a wholly owned subsidiary of
Lockheed Martin, which has had the contract since 1993.[Footnote 8] The
total Sandia contract amount for fiscal year 2001 was $1.6 billion. In
terms of contract amounts, the University of California and Lockheed
Martin are among DOE‘s top three largest contractors and the top six
federal contractors in the United States.
Executive Order 11246, as amended, provides, generally, the same
prohibitions against discrimination for federal government contractors
as title VII of the Civil Rights Act of 1964, as amended.[Footnote 9]
The order states that federal contractors will not discriminate against
any employee or applicant for employment on the basis of race, color,
religion, sex, or national origin. In addition to the requirements of
title VII, the order further states that federal contractors will take
affirmative action to ensure that applicants and employees are treated
without regard to their race, color, religion, sex, or national origin
in personnel actions, including recruitment and hiring, pay, benefits,
promotion, selection for training, demotions and transfers, lay-offs,
and termination.[Footnote 10] The contractors must spell out in their
written affirmative action programs the steps they will take to ensure
equal employment opportunity.
OFCCP‘s regulations implementing the executive order require
contractors, including the laboratories, to submit data annually to
EEOC[Footnote 11] on specified job categories, by race/ethnicity and
gender.[Footnote 12] These data are submitted on the Employer
Information Report (EEO-1)[Footnote 13] to EEOC. EEOC uses these data
to help determine whether employers have potentially engaged in, or are
engaging in, discriminatory employment practices. For this report,
private-sector employers provide annual employment statistics by gender
for each of the nine major job categories and for each of five
population groups: Whites, Blacks, Hispanics, Asians or Pacific
Islanders, and American Indians or Alaskan Natives. The nine major job
categories are officials and managers, professionals, technicians,
sales workers, office and clerical, craft workers, operatives,
laborers, and service workers.
Figure 1 displays the percentage of all positions across the three
weapons laboratories falling into each of the three job category
groups, according to the EEO-1 information for 2000 provided by the
laboratories. As the figure shows, managers and professionals account
for the majority of laboratory staff.
Figure 1: Percentage of Positions in Each Job Category Group at the
Three Weapons Laboratories, 2000:
[Se PDF for image]
This figure is a pie-chart depicting the following data:
Percentage of Positions in Each Job Category Group at the Three Weapons
Laboratories, 2000:
Managers and professionals: 65%;
Technicians, clerks, and craft workers: 32%;
Operatives, laborers, and service workers: 3%.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos, Sandia, and
Lawrence Livermore.
[End of figure]
EEOC forwards the EEO-1 data to OFCCP. With these data, OFCCP
identifies facilities that may warrant further examination”known as
compliance evaluations”because their employment of minorities and
women appears to differ from industry averages. According to OFCCP
officials, OFCCP annually conducts compliance evaluations for a limited
number of those identified facilities. While the EEO-1 information is
the primary selection source for the majority of the compliance
evaluations conducted by OFCCP, OFCCP can schedule a compliance
evaluation, when warranted by special circumstances, such as three or
more complaints with a common issue filed with EEOC. According to OFCCP
officials, in selecting facilities, OFCCP does not consider the value
of the contract or the facilities‘ history of compliance.
As part of a compliance evaluation, OFCCP analyzes the contractor‘s
personnel actions and compensation systems to determine if the
contractor complied with the obligation not to discriminate. For
evaluations where OFCCP identifies major EEO violations, it tries to
resolve them through conciliation agreements with the contractors.
Conciliation agreements generally require the contractor to make the
victim of discrimination ’whole.“ Thus a contractor may be required to
award a victim of discrimination monetary relief. OFCCP monitors the
contractor‘s progress to ensure that corrective actions have been taken
as detailed in the conciliation agreement.
While OFCCP emphasizes bringing contractors into compliance with the
employment laws, rather than penalizing them for not complying, OFCCP
may recommend legal actions if a contractor fails to resolve
discrimination or affirmative action violations. As a last resort, the
secretary of labor may order that a contract be suspended or canceled
and the contractor may be debarred from doing business with the federal
government.
OFCCP also investigates specific complaints of employment
discrimination involving groups of people or patterns of discrimination
filed against federal contractors. OFCCP usually refers any individual
complaints of discrimination involving race, color, religion, sex, or
national origin to EEOC for investigation, as agreed under a memorandum
of understanding between the two agencies. EEOC will also investigate
any complaints filed directly by contractor staff with it, according to
EEOC officials.
DOE‘s workforce consists of more than 100,000 employees: about
13 percent of these are federal employees, and about 87 percent are
contractors in its 15 national laboratories. While DOE‘s civil rights
office in headquarters is responsible for ensuring that the
department‘s federal employees are treated fairly, DOE primarily relies
on its operations offices, which are located near the laboratories, for
overseeing the laboratories‘ implementation of EEO contract provisions,
according to DOE officials. Albuquerque and Oakland”the two operations
offices responsible for overseeing the three weapons laboratories”are
responsible for (1) ensuring that the laboratory contracts include the
required EEO contract clauses; (2) negotiating additional EEO clauses
where needed; (3) assessing the laboratories‘ EEO performance; and (4)
working with the contractors at the laboratories to review their EEO
systems, evaluate their performance against EEO performance measures,
and develop solutions for identified problems.
The laboratories take a number of actions to fulfill their EEO
responsibilities. These include, among other things:
* submitting EEO-1s to EEOC[Footnote 14] and similar information to DOE
to be included in its Work Force Information System (WFIS);
* developing affirmative action programs that are designed not only to
improve the number of minorities and women for specific jobs in which
they are underrepresented but to ensure that the laboratory has
fulfilled its EEO responsibilities;
* preparing diversity plans, which detail the laboratories‘ efforts to
promote workforce diversity by training employees on the importance of
diversity at the laboratories and the prevention of racial profiling;
* providing mechanisms through which staff can raise EEO concerns or
complaints; and;
* developing annual self-assessments on their EEO performance for DOE‘s
review.
The Composition of Staff Varies by Laboratory, and Each Laboratory Has
Seen Some Change in Job Category Groups by Race/Ethnicity and Gender in
1995 Compared with 2000:
According to their data for 1995 and 2000, the three laboratories vary
somewhat in the composition of their staff and have experienced some
changes by race/ethnicity and gender over the period. In 1995 and 2000,
minorities accounted for 18 and 19 percent of the staff at Lawrence
Livermore, 26 and 27 percent at Sandia, and 32 and 34 percent at Los
Alamos, respectively. From 1995 through 2000, each of the three
laboratories experienced some increase in its overall percentage of
minority population but not for every minority group at each laboratory.
All the laboratories have similar proportions of men and women”
approximately 70 and 30 percent, respectively. The percentage of women
increased slightly at two laboratories while slightly decreasing at the
third. In terms of each job category group‘s composition by
race/ethnicity and gender, White men generally held a greater
percentage of the managerial and professional jobs than their
representation in the laboratories, averaged for 1995 and 2000.
However, from 1995 through 2000, the representation of White men in the
managerial and professional job category group decreased at each of the
three laboratories. White women and minorities had a lower percentage
of managers and professionals than their representation in the total
laboratory staff, averaged for 1995 and 2000. The laboratories
experienced some increase in minority representation in the managers
and professionals job category group but not for each minority group at
each laboratory. White women increased their representation in this job
category group at two laboratories but experienced a decrease at the
third. Data on the composition of laboratory staff may be presented in
two ways, according to EEOC: (1) as presented in figures 6 to 11, by
the number of a racial/ethnic or gender group in a specific job
category group at the laboratory divided by the total number of staff
in that job category group at the laboratory and (2) by the number of a
racial/ethnic or gender group in a specific job category group at the
laboratory divided by the total number of that racial/ethnic or gender
group at the laboratory. (For this latter presentation, see app. II.)
Composition of Laboratory Staff by Race/Ethnicity and Gender:
For 1995 and 2000, figures 2 through 4 show the composition of each
laboratory‘s staff by race/ethnicity. Figure 5 shows the composition of
the three laboratories‘ staff by gender.
Figure 2: Composition of Laboratory Staff at Los Alamos, by
Race/Ethnicity, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Race/ethnicity: White;
Percent, 1995: 68%;
Percent, 2000: 66%.
Race/ethnicity: Hispanic;
Percent, 1995: 26%;
Percent, 2000: 28%.
Race/ethnicity: Asian;
Percent, 1995: 2%;
Percent, 2000: 4%.
Race/ethnicity: Black;
Percent, 1995: 0.4%;
Percent, 2000: 0.5%.
Race/ethnicity: American Indian;
Percent, 1995: 1.8%;
Percent, 2000: 1.9%.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos.
[End of figure]
Figure 3: Composition of Laboratory Staff at Sandia, by Race/Ethnicity,
1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Race/ethnicity: White;
Percent, 1995: 74%;
Percent, 2000: 72%.
Race/ethnicity: Hispanic;
Percent, 1995: 16%;
Percent, 2000: 18%.
Race/ethnicity: Asian;
Percent, 1995: 3%;
Percent, 2000: 3.2%.
Race/ethnicity: Black;
Percent, 1995: 3%;
Percent, 2000: 2.7%.
Race/ethnicity: American Indian;
Percent, 1995: 2.7%;
Percent, 2000: 3%.
Source: GAO‘s analysis of EEO-1s obtained from Sandia.
[End of figure]
Figure 4: Composition of Laboratory Staff at Lawrence Livermore, by
Race/Ethnicity, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Race/ethnicity: White;
Percent, 1995: 82%;
Percent, 2000: 80%.
Race/ethnicity: Hispanic;
Percent, 1995: 6.3%;
Percent, 2000: 6.6%.
Race/ethnicity: Asian;
Percent, 1995: 6%;
Percent, 2000: 6.8%.
Race/ethnicity: Black;
Percent, 1995: 4%;
Percent, 2000: 3.7%.
Race/ethnicity: American Indian;
Percent, 1995: 1.5%;
Percent, 2000: 1.4%.
Source: GAO‘s analysis of WFIS‘s data (1995); EEO-1 obtained from
Lawrence Livermore (2000).
[End of figure]
Figure 5: Composition of Each Laboratory‘s Staff, by Gender, 1995 and
2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Los Alamos National Laboratory:
Men, 1995: 70%;
Men, 2000: 67%;
Women, 1995: 30%;
Women, 2000: 33%.
Sandia National Laboratory:
Men, 1995: 70%;
Men, 2000: 69%;
Women, 1995: 30%;
Women, 2000: 31%.
Lawrence Livermore National Laboratory:
Men, 1995: 69%;
Men, 2000: 70%;
Women, 1995: 31%;
Women, 2000: 30%.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos and Sandia
(1995 and 2000); WFIS data for Lawrence Livermore (1995); EEO-1
obtained from Lawrence Livermore (2000).
[End of figure]
Composition of Each Job Category Group by Race/Ethnicity and Gender:
In 1995 and 2000, for all laboratories, White men held an average of
54 percent of all laboratory jobs and an average of 64 percent of the
managerial and professional jobs. For the same years, White women, who
constitute an average of 20 percent of all laboratory staff, held about
18 percent of the managerial and professional jobs. In contrast,
minorities, who held an average of 26 percent of all laboratory jobs,
held 18 percent of the managerial and professional jobs. For each of
the laboratories, we examined the composition of the staff by job
category group and within each job category group, the composition by
White men, White women, and minorities. From 1995 through 2000, the
laboratories experienced some increase in minority representation in
the managers and professionals job category group but not for each
minority group at each laboratory. White women increased their
representation in this job category group at Los Alamos and Sandia but
experienced a decrease at Lawrence Livermore. Figures 6 through 11 show
the composition of each job category group by race/ethnicity and
gender.
Los Alamos:
Figure 6: Composition of Job Category Group at Los Alamos by White Men,
White Women, and Minorities, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (67% of staff):
White men, 1995: 66%;
White men, 2000: 60%;
White women, 1995; 17%;
White women, 2000: 19%;
Minorities, 1995: 17%;
Minorities, 2000: 21%.
Technicians, clerks and craft workers (33% of staff):
White men, 1995: 25%;
White men, 2000: 23%;
White women, 1995; 18%;
White women, 2000: 16%;
Minorities, 1995: 57%;
Minorities, 2000: 61%.
Operatives, laborers and service workers (0.5% of staff):
White men, 1995: 7%;
White men, 2000: 6%;
White women, 1995; 0;
White women, 2000: 5%;
Minorities, 1995: 90%;
Minorities, 2000: 88%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000 and does
not add to 100 percent because of rounding.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos.
[End of figure]
Figure 7: Composition of Job Category Group at Los Alamos by Each
Minority Group, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (67% of staff):
Hispanic, 1995: 12.5%;
Hispanic, 2000: 15%;
Asian, 1995: 2%;
Asian, 2000: 4%;
Black, 1995: 0.5%;
Black, 2000: 0.5%;
American Indian, 1995: 1%;
American Indian, 2000: 1.5%.
Technicians, clerks and craft workers (33% of staff):
Hispanic, 1995: 50%;
Hispanic, 2000: 55%;
Asian, 1995: 0.5%;
Asian, 2000: 1%;
Black, 1995: 0.3%;
Black, 2000: 0.4%;
American Indian, 1995: 2.8%;
American Indian, 2000: 3%.
Operatives, laborers and service workers (0.5% of staff):
Hispanic, 1995: 90%;
Hispanic, 2000: 80%;
Asian, 1995: 0;
Asian, 2000: 0;
Black, 1995: 0;
Black, 2000: 0;
American Indian, 1995: 2.7%;
American Indian, 2000: 4%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000 and does
not add to 100 percent because of rounding.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos.
[End of figure]
Sandia:
Figure 8: Composition of Job Category Group at Sandia by White Men,
White Women, and Minorities, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (63% of staff):
White men, 1995: 68%;
White men, 2000: 66%;
White women, 1995; 13%;
White women, 2000: 15%;
Minorities, 1995: 15%;
Minorities, 2000: 17%.
Technicians, clerks and craft workers (33% of staff):
White men, 1995: 34%;
White men, 2000: 32%;
White women, 1995; 28%;
White women, 2000: 26%;
Minorities, 1995: 35%;
Minorities, 2000: 40%.
Operatives, laborers and service workers (4% of staff):
White men, 1995: 20%;
White men, 2000: 21%;
White women, 1995; 3%;
White women, 2000: 5%;
Minorities, 1995: 75%;
Minorities, 2000: 70%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of EEO-1s obtained from Sandia.
[End of figure]
Figure 9: Composition of Job Category Group at Sandia by Each Minority
Group, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (63% of staff):
Hispanic, 1995: 10%;
Hispanic, 2000: 11.5%;
Asian, 1995: 3.6%;
Asian, 2000: 3.8%;
Black, 1995: 2%;
Black, 2000: 1.8%;
American Indian, 1995: 1%;
American Indian, 2000: 1.1%.
Technicians, clerks and craft workers (33% of staff):
Hispanic, 1995: 30%;
Hispanic, 2000: 33%;
Asian, 1995: 2%;
Asian, 2000: 2.5%;
Black, 1995: 3.5%;
Black, 2000: 3.3%;
American Indian, 1995: 3.8%;
American Indian, 2000: 5.3%.
Operatives, laborers and service workers (4% of staff):
Hispanic, 1995: 61%;
Hispanic, 2000: 58%;
Asian, 1995: 2%;
Asian, 2000: 0.5%;
Black, 1995: 10%;
Black, 2000: 9.5%;
American Indian, 1995: 9.5%;
American Indian, 2000: 8%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of EEO-1s obtained from Sandia.
[End of figure]
Lawrence Livermore:
Figure 10: Composition of Job Category Group at Lawrence Livermore by
White Men, White Women, and Minorities, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (57% of staff):
White men, 1995: 62%;
White men, 2000: 60%;
White women, 1995; 22%;
White women, 2000: 20%;
Minorities, 1995: 16%;
Minorities, 2000: 18%.
Technicians, clerks and craft workers (38% of staff):
White men, 1995: 50%;
White men, 2000: 50%;
White women, 1995; 28%;
White women, 2000: 28%;
Minorities, 1995: 20%;
Minorities, 2000: 20%.
Operatives, laborers and service workers (5% of staff):
White men, 1995: 54%;
White men, 2000: 52%;
White women, 1995; 15%;
White women, 2000: 13%;
Minorities, 1995: 30%;
Minorities, 2000: 35%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of WFIS‘s data (1995); EEO-1 obtained from
Lawrence Livermore (2000).
[End of figure]
Figure 11: Composition of Job Category Group at Lawrence Livermore by
Each Minority Group, 1995 and 2000:
This figure is a multiple vertical bar graph depicting the following
approximated data:
Managers and professionals (57% of staff):
Hispanic, 1995: 4%;
Hispanic, 2000: 4.2%;
Asian, 1995: 7.5%;
Asian, 2000: 8.2%;
Black, 1995: 3%;
Black, 2000: 2.8%;
American Indian, 1995: 1%;
American Indian, 2000: 1%.
Technicians, clerks and craft workers (38% of staff):
Hispanic, 1995: 9%;
Hispanic, 2000: 9.5%;
Asian, 1995: 5%;
Asian, 2000: 4.7%;
Black, 1995: 4.7%;
Black, 2000: 4.2%;
American Indian, 1995: 2%;
American Indian, 2000: 2%.
Operatives, laborers and service workers (5% of staff):
Hispanic, 1995: 12%;
Hispanic, 2000: 15%;
Asian, 1995: 5%;
Asian, 2000: 8%;
Black, 1995: 10%;
Black, 2000: 10.4%;
American Indian, 1995: 1.8%;
American Indian, 2000: 1%.
Note: The percentage that each job category group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of WFIS‘s data (1995); EEO-1 obtained from
Lawrence Livermore (2000).
[End of figure]
Certain Personnel Actions for Managers and Professionals Show
Statistically Significant Differences for Minority Men and Women and
White Women Compared with White Men, While Others Do Not:
For fiscal years 1998 through 2000, we found statistically significant
differences in certain personnel actions but not in others for minority
men and women and White women in managerial and professional job
categories compared with White men in these categories at the three
laboratories. Most notably, with the exception of Asian men at Los
Alamos and Sandia, and Hispanic men at Lawrence Livermore, salaries for
minority men and women and White women were lower than for White
men. Comparing men and women of the same race/ethnicity, we found
that White, Asian, and Hispanic women earned less than their male
counterparts in comparison with White men. For example, Hispanic men
at Los Alamos earned 2 percent less than White men, while Hispanic
women earned 10 percent less. Conversely, merit pay increases for
minority men and women and White women tended to be equal to or
greater than merit pay increases for White men, except for Hispanic men
at Lawrence Livermore. For cash awards, some minority men and women
at Sandia were more likely to receive an award than White men, while at
Lawrence Livermore and Los Alamos, some were less likely to receive an
award. Only Los Alamos had statistically significant differences in the
likelihood of minority men and women and White women leaving the
laboratories compared with White men. These differences existed after
factoring in the following variables”age; tenure at the laboratory;
education level; job subcategory (including postdoctoral and temporary
status); citizenship status; security clearance level; and for Sandia‘s
staff, whether they were located in California or New Mexico. (See app.
III for information on these variables for each laboratory.) Although
the laboratories have somewhat different personnel systems and
practices, our analyses of personnel actions included only those
variables common to all three. For example, we did not include
individual performance ratings and rankings, laboratories‘
organizational structure, and market-based salary analysis and
adjustments. We found that management promotions for minority men and
women and White women generally met 80 percent of the promotion rate
for White men, with a few exceptions. We did not find statistically
significant differences, with some exceptions, for disciplinary
actions. Because of data limitations, we could not determine whether
minority men and women and White women were as likely as White men to
be hired by the laboratories. (See app. I for details on our
methodology.)
Salaries for Managerial and Professional Staff:
We found statistically significant differences in the salaries for
minority men and women and White women in managerial and professional
job categories compared with White men in these categories, holding
constant age; tenure at the laboratory; education level; job
subcategory; citizenship status; security clearance level; and for
Sandia‘s staff, whether they were located in California or New Mexico.
Minority men and women and White women earned from 2 to 10 percent less
than White men, except for Asian men at Los Alamos and Sandia, and
Hispanic men at Lawrence Livermore, for whom there were no statistical
differences from White men. Table 1 presents the results of our
analysis. In this table, negative numbers indicate that the group
earned a lower salary than White men, and blank spaces indicate that
there were no significant differences for that group.
Table 1: Percent Difference in Salaries for Managerial and Professional
Minority Men and Women and White Women in Comparison with White Men,
Fiscal Years 1998 through 2000:
Race/ethnicity and gender: Asian men;
Percent less than White men, Los Alamos: [Blank];
Percent less than White men, Sandia: [Blank];
Percent less than White men, Lawrence Livermore: -5%.
Race/ethnicity and gender: Hispanic men
Percent less than White men, Los Alamos: -2%;
Percent less than White men, Sandia: -4%;
Percent less than White men, Lawrence Livermore: [Blank].
Race/ethnicity and gender: Black and American Indian men and women[A];
Percent less than White men, Los Alamos: -5%;
Percent less than White men, Sandia: -4%;
Percent less than White men, Lawrence Livermore: -7%.
Race/ethnicity and gender: Asian women;
Percent less than White men, Los Alamos: -3%;
Percent less than White men, Sandia: -3%;
Percent less than White men, Lawrence Livermore: -8%.
Race/ethnicity and gender: Hispanic women;
Percent less than White men, Los Alamos: -10%;
Percent less than White men, Sandia: -7%;
Percent less than White men, Lawrence Livermore: -10%.
Race/ethnicity and gender: White women;
Percent less than White men, Los Alamos: -5%;
Percent less than White men, Sandia: -4%;
Percent less than White men, Lawrence Livermore: -8%.
Note: Blank spaces indicate that results for these groups compared with
White men were not statistically significant. Our analysis explains 88,
85, and 77 percent of the variance in salary differences in the 3-year
period at Los Alamos, Sandia, and Lawrence Livermore, respectively.
[A] The laboratories did not have sufficient numbers of Blacks and
American Indians for us to separately analyze their salaries by
race/ethnicity and gender.
Source: GAO‘s analysis of laboratories‘ data.
[End of table]
As the table shows, overall, the greatest salary differences were found
for Hispanic women, who earned from 7 to 10 percent less than White men.
Conversely, with earnings ranging from zero to 5 percent less than
those of White men, Asian men‘s salaries show the least difference with
White men‘s salaries. In comparing men and women of the same
race/ethnicity, we also found that White, Asian, and Hispanic women
earned statistically significantly less than their male counterparts in
comparison to White men. For example, Hispanic men at Los Alamos earned
2 percent less than White men, while Hispanic women earned 10 percent
less.
Merit Pay Increases for Managerial and Professional Staff:
The amount of merit pay increases for minority men and women and
White women in managerial and professional job categories tended to be
equal to or greater than the merit pay increases for White men in these
categories, holding constant age; tenure at the laboratory; education
level; job subcategory; citizenship status; security clearance level;
and for Sandia‘s staff, whether they were located in California or New
Mexico.
Where there are statistically significant differences in merit pay
increases, they favor minority men and women and White women, except for
Hispanic men at Lawrence Livermore. Table 2 presents the results of our
analysis. In this table, the negative number indicates that the group
earned a lower merit pay increase than White men, positive numbers
indicate that they earned more, and blank spaces indicate that there
were no statistically significant differences for that group. For
example, we found that White women and Asian men at Los Alamos, and
White and Hispanic women at Sandia earned higher merit pay increases
than White men.
Table 2: Percent Differences in Merit Pay Increases for Managerial and
Professional Minority Men and Women and White Women in Comparison with
White Men, Fiscal Years 1998 through 2000:
Race/ethnicity and gender: Asian men;
Percent difference compared with White men, Los Alamos: 33%;
Percent difference compared with White men, Sandia: [Blank];
Percent difference compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Hispanic men;
Percent difference compared with White men, Los Alamos: [Blank];
Percent difference compared with White men, Sandia: [Blank];
Percent difference compared with White men, Lawrence Livermore: -51%.
Race/ethnicity and gender: Black and American Indian men and women[A];
Percent difference compared with White men, Los Alamos: [Blank];
Percent difference compared with White men, Sandia: [Blank];
Percent difference compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Asian women;
Percent difference compared with White men, Los Alamos: [Blank];
Percent difference compared with White men, Sandia: [Blank];
Percent difference compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Hispanic women;
Percent difference compared with White men, Los Alamos: [Blank];
Percent difference compared with White men, Sandia: 31%;
Percent difference compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: White women;
Percent difference compared with White men, Los Alamos: 15%;
Percent difference compared with White men, Sandia: 36%;
Percent difference compared with White men, Lawrence Livermore:
[Blank].
Note: Blank spaces indicate that results for these groups compared with
White men were not statistically significant. Our analysis explains 78,
58, and 67 percent of the variance in merit pay increases for the 3-
year period at Los Alamos, Sandia, and Lawrence Livermore,
respectively.
[A] The laboratories did not have sufficient numbers of Blacks and
American Indians for us to separately analyze their merit pay by
race/ethnicity and gender.
Source: GAO‘s analysis of laboratories‘ data.
[End of figure]
Cash Awards for Managerial and Professional Staff:
For cash awards, some minority men and women in managerial and
professional job categories at Sandia were significantly more likely to
receive an award than White men in these categories, while at Lawrence
Livermore and Los Alamos, some minority men and women were less
likely to receive an award, holding constant age; tenure at the
laboratory; education level; job subcategory; citizenship status;
security clearance level; and for Sandia‘s staff, whether they were
located in California or New Mexico. Table 3 presents the results of
our analysis. In this table, numbers less than 1 indicate that the
group has a lower likelihood of receiving a cash award than White men,
numbers greater than 1 indicate that the group is more likely than
White men to receive a cash award, and blank spaces indicate that there
were no significant differences for that group. For example, at Sandia,
Asian women were a little more than three and a half times as likely as
White men to receive a cash award.
Table 3: Differences in the Likelihood of Receiving a Cash Award for
Managerial and Professional Minority Men and Women and White Women in
Comparison with White Men, Fiscal Years 1998 through 2000:
Race/ethnicity and gender: Asian men;
Likelihood of receiving a cash award compared with White men, Los
Alamos: [Blank];
Likelihood of receiving a cash award compared with White men, Sandia:
2.69%;
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: 0.68%.
Race/ethnicity and gender: Hispanic men;
Likelihood of receiving a cash award compared with White men, Los
Alamos: [Blank];
Likelihood of receiving a cash award compared with White men, Sandia:
1.82%;
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: 0.56%.
Race/ethnicity and gender: Black and American Indian men and women[A];
Likelihood of receiving a cash award compared with White men, Los
Alamos: 0.53%;
Likelihood of receiving a cash award compared with White men, Sandia:
[Blank];
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: [Blank].
Race/ethnicity and gender: Asian women;
Likelihood of receiving a cash award compared with White men, Los
Alamos: [Blank];
Likelihood of receiving a cash award compared with White men, Sandia:
3.66%;
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: [Blank].
Race/ethnicity and gender: Hispanic women;
Likelihood of receiving a cash award compared with White men, Los
Alamos: [Blank];
Likelihood of receiving a cash award compared with White men, Sandia:
[Blank];
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: 0.36%.
Race/ethnicity and gender: White women;
Likelihood of receiving a cash award compared with White men, Los
Alamos: [Blank];
Likelihood of receiving a cash award compared with White men, Sandia:
[Blank];
Likelihood of receiving a cash award compared with White men, Lawrence
Livermore: [Blank].
Note: Numbers less than 1 indicate that the group has a lower
likelihood of receiving a cash award than White men, numbers greater
than 1 indicate that the group is more likely than White men to receive
a cash award, and blank spaces indicate that results for these groups
compared with White men were not statistically significant. Our
analysis explains 36, 80, and 25 percent of the differences in the
likelihood of receiving a cash award in the 3-year period at Los
Alamos, Sandia, and Lawrence Livermore, respectively.
[A] The laboratories did not have sufficient numbers of Blacks and
American Indians for us to analyze their cash awards by race/ethnicity
and gender separately.
Source: GAO‘s analysis of laboratories‘ data.
[End of table]
Separations for Managerial and Professional Staff:
At Sandia and Lawrence Livermore, minority men and women and White
women in managerial and professional job categories were no more likely
to leave the laboratory than White men in these categories, holding
constant age; tenure at the laboratory; education level; job
subcategory; citizenship status; security clearance level; and for
Sandia‘s staff, whether they were located in California or New Mexico.
However, at Los Alamos, minority men and women and White women, except
for Asian men and women, were less likely to leave the laboratory than
White men. Table 4 presents the results of our analysis. In this table,
numbers less than 1 indicate that the group has a lower likelihood of
separation from the laboratories than White men, numbers greater than 1
indicate that the group is more likely than White men to separate, and
blank spaces indicate that there were no significant differences for
that group. For example, White women at Los Alamos were about two-
thirds as likely as White men to separate in the 3-year period.
Separations include both voluntary actions, such as retirement, and
involuntary actions, such as terminations for cause.
Table 4: Differences in the Likelihood of Separating from the
Laboratory for Managerial and Professional Minority Men and Women and
White Women in Comparison with White Men, Fiscal Years 1998 through
2000:
Race/ethnicity and gender: Asian men;
Likelihood of separation compared with White men, Los Alamos: [Blank];
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Hispanic men;
Likelihood of separation compared with White men, Los Alamos: 0.63%;
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Black and American Indian men and women[A];
Likelihood of separation compared with White men, Los Alamos: 0.40%;
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Asian women;
Likelihood of separation compared with White men, Los Alamos: [Blank];
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: Hispanic women;
Likelihood of separation compared with White men, Los Alamos: 0.56%;
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Race/ethnicity and gender: White women;
Likelihood of separation compared with White men, Los Alamos: 0.69%;
Likelihood of separation compared with White men, Sandia: [Blank];
Likelihood of separation compared with White men, Lawrence Livermore:
[Blank].
Note: Numbers less than 1 indicate that the group has a lower
likelihood of separating than White men, numbers greater than 1
indicate that the group is more likely than White men to separate, and
blank spaces indicate that results for these groups compared with White
men were not statistically significant. Our analysis explains 66, 79,
and 81 percent of the variation in the likelihood of separating in the
3-year period at Los Alamos, Sandia, and Lawrence Livermore,
respectively.
[A] The laboratories did not have sufficient numbers of Blacks and
American Indians for us to separately analyze their separations by
race/ethnicity and gender.
Source: GAO‘s analysis of laboratories‘ data.
[End of table]
Promotions for Managerial and Professional Staff:
We used the 80 percent rule[Footnote 15] set out in the federal
government‘s Uniform Guidelines on Employment Selection Procedures as a
criterion for determining whether the promotions of minority men and
women and White women into management positions reflect the diversity
of the potential applicant pools.[Footnote 16]
We found that management promotions for minority men and women and
White women in managerial and professional job categories over fiscal
years 1998 through 2000 generally met 80 percent of the promotion rate
of White men in these categories at the three laboratories, with a few
exceptions:
* At Los Alamos, while four Asian women were promoted, three additional
promotions would have been needed to reach the 80 percent criterion.
Similarly, two more Black men, two more American Indian men, and two
more Hispanic women would need to have been promoted to reach 80
percent of the promotion rate for White men.
* At Sandia, while nine Hispanic women were promoted, three more would
have been needed to reach the 80 percent criterion.
* At Lawrence Livermore, no Asian men and one Asian woman were
promoted, but five promotions and one additional one, respectively,
would have been needed to reach 80 percent of the promotion rate for
White men.
In some cases, the promotion rate for some minority men and women was
greater than the promotion rate for White men. For example, at Lawrence
Livermore, 10.8 percent of Black men received promotions compared with
2.2 percent of White men.
Table 5 shows, for each laboratory, the number of promotions by
race/ethnicity and gender, the percentage promoted by race/ethnicity and
gender, and the additional number of promotions needed to reach 80
percent of the White male promotion rate.
Table 5: Number of Promotions for Each Race/Ethnicity and Gender Group,
Percentage of the Group Promoted, and Number of Additional Promotions
Needed to Reach 80 Percent of the Promotion Rate of White Men, Fiscal
Years 1998 through 2000:
Race/ethnicity and gender: White men;
Los Alamos, Number: 662;
Los Alamos, Percent: 19.6;
Los Alamos, Needed: [Blank];
Sandia, Number: 243;
Sandia, Percent: 6.5;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 66;
Lawrence Livermore, Percent: 2.2;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: Asian men;
Los Alamos, Number: 24;
Los Alamos, Percent: 16.3;
Los Alamos, Needed: [Blank];
Sandia, Number: 8;
Sandia, Percent: 5.2;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 0;
Lawrence Livermore, Percent: 0.0;
Lawrence Livermore, Needed: 5.
Race/ethnicity and gender: Hispanic men;
Los Alamos, Number: 118;
Los Alamos, Percent: 21.3;
Los Alamos, Needed: [Blank];
Sandia, Number: 30;
Sandia, Percent: 7.0;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 2;
Lawrence Livermore, Percent: 1.7;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: Black men;
Los Alamos, Number: 1;
Los Alamos, Percent: 4.5;
Los Alamos, Needed: 2;
Sandia, Number: 4;
Sandia, Percent: 4.9;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 8;
Lawrence Livermore, Percent: 10.8;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: American Indian men;
Los Alamos, Number: 5;
Los Alamos, Percent: 10.4;
Los Alamos, Needed: 2;
Sandia, Number: 2;
Sandia, Percent: 3.8;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 2;
Lawrence Livermore, Percent: 6.5;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: White women;
Los Alamos, Number: 187;
Los Alamos, Percent: 17.7;
Los Alamos, Needed: [Blank];
Sandia, Number: 52;
Sandia, Percent: 5.2;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 23;
Lawrence Livermore, Percent: 2.1;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: Asian women;
Los Alamos, Number: 4;
Los Alamos, Percent: 8.2;
Los Alamos, Needed: 3;
Sandia, Number: 4;
Sandia, Percent: 5.4;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 1;
Lawrence Livermore, Percent: 0.7;
Lawrence Livermore, Needed: 1.
Race/ethnicity and gender: Hispanic women;
Los Alamos, Number: 62;
Los Alamos, Percent: 15.0;
Los Alamos, Needed: 2;
Sandia, Number: 9;
Sandia, Percent: 3.8;
Sandia, Needed: 3;
Lawrence Livermore, Number: 1;
Lawrence Livermore, Percent: 1.1;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: Black women;
Los Alamos, Number: 4;
Los Alamos, Percent: 80.0;
Los Alamos, Needed: [Blank];
Sandia, Number: 2;
Sandia, Percent: 5.4;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 0;
Lawrence Livermore, Percent: 0.0;
Lawrence Livermore, Needed: [Blank].
Race/ethnicity and gender: American Indian women;
Los Alamos, Number: 3;
Los Alamos, Percent: 12.5;
Los Alamos, Needed: [Blank];
Sandia, Number: 1;
Sandia, Percent: 3.8;
Sandia, Needed: [Blank];
Lawrence Livermore, Number: 0;
Lawrence Livermore, Percent: 0.0;
Lawrence Livermore, Needed: [Blank].
Note: Numbers are rounded down. Blank spaces indicate that the 80
percent rule was met (no additional staff needed to meet 80 percent of
the White male promotion rate).
Source: GAO‘s analysis of laboratories‘ data.
[End of table]
Disciplinary Actions for Managerial and Professional Staff:
From 1995 through June 2001, Los Alamos took 127 disciplinary actions
against managers and professionals and Sandia took 112; for fiscal years
1995 through 2000, Lawrence Livermore took 139. The small number of
actions limited the types of statistical tests we could use.[Footnote
17] For those analyses we conducted, we did not find statistically
significant differences in the rate at which minority men and women and
White women were disciplined compared with White men, with the
following exceptions:
* At Los Alamos, the rate at which men were disciplined was higher than
for women.
* At Sandia, the rate at which Hispanics were disciplined was higher
than for Whites.
* At Lawrence Livermore, Blacks were disciplined at a higher rate than
Whites, and men at a higher rate than women.
In examining the severity of the disciplinary action (such as reprimand,
suspension, and termination) for all offenses combined, we found that
minorities and women were not disciplined significantly more severely
than White men.[Footnote 18] Tables 16 to18 in appendix III show the
number and type of disciplinary actions against managers and
professionals by race/ethnicity and gender.
Although we tested for statistical differences, we did not attempt to
determine the cause of the differences we found. However, we did observe
that disciplinary actions for certain offenses occurred only for
specific groups. For example, only males were disciplined for Internet
misuse. We also observed that certain offenses usually resulted in more
or less severe punishments than others. For example, conducting
commercial business on laboratory property typically resulted in
harsher penalties than attendance behavior.
Hires for Managerial and Professional Staff:
We were unable to determine whether minorities and women were
significantly less likely to be hired than White men at the three
laboratories during the 3-year period we reviewed. The laboratories
provided data from their applicant tracking systems that were missing a
large percentage of information on race/ethnicity, gender, education,
and hiring decisions.
Problems with applicant data are not new. For example, in a 1989
conciliation agreement between OFCCP and Lawrence Livermore laboratory,
the laboratory agreed to, among other things, upgrade its applicant
tracking system to ensure that the system could be used for the
complete and accurate analysis of hiring in the future. Nonetheless, in
2001, when OFCCP surveyed contractors on EEO information, Lawrence
Livermore continued to report missing race/ethnicity and gender data on
applicants. All three laboratories attribute the missing data to
nonreporting by applicants, which is voluntary.
Although OFCCP requires the laboratories to collect data on the
race/ethnicity and gender of applicants, if possible, the submission of
this information by the applicant is voluntary. Officials at the three
laboratories told us that they have difficulty obtaining these data
because applicants are not required to provide information on
race/ethnicity and gender on their applications and often do not.
Officials at Sandia told us they identify applicants‘ race/ethnicity
and gender at the time of an interview, if that information was not
provided previously. Los Alamos and Lawrence Livermore officials told
us they are prohibited by the University of California‘s policy from
making visual identifications. OFCCP and EEOC officials reiterated the
importance of collecting race/ethnicity and gender information on
applicants, including the use of visual inspections, which is not
prohibited by law. Furthermore, Lawrence Livermore officials told us
that more than 90 percent of the applicants submit a resume using the
Web form, which since mid-2001 has asked applicants to voluntarily
identify their race/ethnicity and gender. However, the laboratory has
not yet assessed if this method is an effective tool to collect
information on race/ethnicity and gender for applicants.
Staffs‘ EEO Concerns Focus Primarily on Four Issues:
Minority and female laboratory staffs‘ EEO concerns focus primarily on
recruiting, pay, promotion, and the laboratories‘ work environment. We
identified these concerns through laboratory surveys and studies; a DOE
Task Force Against Racial Profiling; EEOC commissioners‘ charges
obtained from the laboratories; and formal complaints filed by
laboratory staff with OFCCP, which are described in the next section of
this report. These concerns also surfaced during some of our interviews
with representatives of racial/ethnic groups and women at the
laboratories. Our analysis did not include individual complaints filed
by laboratory staff with EEOC because this is confidential
information.[Footnote 19] In addition, we did not attempt to prove or
disprove the validity of these concerns, nor did we assess the
laboratories‘ efforts to address these concerns.
Recruiting:
Some minority staff attribute their low representation in certain job
categories to recruiting strategies that do not extensively target
colleges and universities with large minority populations. For example:
* According to the December 2000 Los Alamos Asian and Pacific Islander
Career Enhancement Task Force report, the task force found that Asian
and Pacific Islanders are underrepresented in management and
supervisory positions and the laboratory needs to increase its efforts
to aggressively recruit Asians.[Footnote 20] They believe the
laboratory has not participated in professional meetings of Asian-
specific organizations or targeted universities with significant Asian
populations as much as it could.
* Similarly, representatives of minority groups at the three
laboratories expressed concerns about recruitment efforts. For example,
representatives at each laboratory told us that some minorities are not
well represented at the laboratory because the laboratory does not
recruit extensively at colleges and universities with high proportions
of minority students.
Pay:
Some minorities and women perceive that they are not paid equitably and
that performance appraisals and ranking systems do not treat minorities
and women fairly and therefore contribute to pay inequities at the three
laboratories. For example:
* According to results of the March 2000 Los Alamos Work Environment
Survey, some minority groups and female employees were significantly
more likely to disagree with the belief that they are fairly
compensated in relation to their contribution.[Footnote 21]
* At Sandia, salaries for some women technical staff (Principal Member
of Technical Staff and Distinguished Member of Technical Staff) are
slightly below their male counterparts‘ according to the Women in
Technical Management Project Team‘s presentation in February 2000.
Also, at Sandia, fewer women than men agree or strongly agree that
Sandia is doing an excellent job of matching pay with performance
according to the 1999 Sandia Employee Attitude Survey.[Footnote 22]
*While 45 percent of Lawrence Livermore staff responded favorably
regarding their pay, benefits, and recognition, Asians responded
significantly less favorably, according to the laboratory‘s 2001
Assessing the Workplace Survey.[Footnote 23] Also, only 44 percent of
Lawrence Livermore‘s staff believe that the performance and evaluation
system is fair and consistently applied, according to the laboratory‘s
2001 survey.
Promotion:
Some minority and female staff at the three laboratories have concerns
about promotion opportunities into top management positions. For
example:
* Generally, some Asians at Los Alamos believed that they were
underrepresented in laboratory management and felt that they had a
minimal chance to be promoted into these management positions,
according to the December 2000 Asian and Pacific Islander Career
Enhancement Task Force.[Footnote 24]
* At Sandia, women were less likely to receive special appointments,
such as deputy director or senior manager, according to a 2000 study on
women in technical management.
* While 55 percent of Lawrence Livermore‘s staff were satisfied with
career development opportunities, Asians were significantly less likely
to be satisfied, according to the laboratory‘s 2001 survey.
Laboratory Work Environment:
Some minority and female staff raised concerns about the laboratories‘
lack of sensitivity to cultural and gender differences: For example:
* According to DOE‘s 2000 Task Force Against Racial Profiling, an
atmosphere of distrust and suspicion existed at the laboratories and
other DOE facilities the task force visited;[Footnote 25] some
employees felt that their loyalty and patriotism was questioned because
of racial factors. In particular, Asians cited a hostile work
environment and speculated that their opportunities for promotions,
choice job assignments, and developmental training had been greatly
reduced as a result of this atmosphere of distrust and suspicion.
* At Los Alamos, according to its 2000 survey, 13 percent of women,
25 percent of Asians, 14 percent of Hispanics, and 11 percent of
American Indian staff did not feel accepted because of their
race/ethnicity.
* At Lawrence Livermore, 59 percent of the staff believed that
differences in the unique qualities of individuals and groups are
recognized and respected within the laboratory, but Blacks and women
were significantly less likely to share this view, according to the
laboratory‘s 2001 survey. Furthermore, while 57 percent of the staff
generally agreed that the laboratory‘s work environment and culture
supports staff in speaking freely and in challenging traditional ways,
Asians were significantly less likely to hold this view.
Commissioner Charges:
EEOC has brought commissioner charges against two of the laboratories”
Los Alamos and Lawrence Livermore”charging unlawful employment
practices against Asians because of their race and national origin,
according to documents we obtained from the laboratories.[Footnote 26]
The charges cited, among other things, harassment, a hostile work
environment, and limited opportunities for promotion. Pursuant to the
commissioner charges received from the laboratories, the charges are
based on information received from current and former laboratory staff,
information in the media, and government reports. The charge against Los
Alamos was brought in February 2000, and the charge against Lawrence
Livermore was brought in October 1999. According to laboratory
officials, these cases were ongoing as of February 2002.
Improved Collaboration between DOE and OFCCP Could Help to Ensure
Laboratories‘ EEO Compliance:
Although DOE and OFCCP share the common goal of ensuring that the
laboratories meet EEO requirements, they have different roles and take
different approaches to evaluating the laboratories‘ EEO efforts. DOE‘s
primary role is contract oversight, which focuses on the laboratories‘
EEO performance in meeting their EEO contractual performance objectives,
such as the laboratories‘ efforts to improve the representation of
minorities and women at the laboratories. OFCCP‘s role is EEO
enforcement, which focuses on EEO compliance with applicable laws and
regulations. Although each agency‘s assessment yields different
information, the agencies do not routinely coordinate their efforts.
Both agencies have EEO information and expertise that would be
beneficial to share. Closer collaboration could leverage resources to
more comprehensively assess the laboratories‘ EEO compliance.
As part of its approach to fulfilling its contract oversight role, DOE
operations staff conduct performance-based assessments of the
laboratories‘ efforts to fulfill contract obligations, including those
for EEO. In doing so, DOE works with the laboratories throughout the
year to set annual performance objectives and measures. According to
DOE officials in the operations offices, they work with laboratory
managers during the year on EEO issues and review the EEO systems the
laboratories have in place. At the end of the year, the laboratories
assess their performance, including their performance on EEO
activities, and report their assessments to DOE. DOE reviews these self-
assessments and rates the laboratories‘ performance on a five-point
scale”’unsatisfactory,“ ’marginal,“ ’good,“ ’excellent,“ and
’outstanding.“ For example, Los Alamos has EEO performance objectives
in its contract to promote workforce diversity and to improve the
representation of minorities and women in the workforce through the
planning and implementation of good faith efforts designed to improve
the recruitment, selection, and retention of women and minorities in
high-priority underutilized job groups.[Footnote 27] The laboratory can
receive a ’good“ rating if it develops and implements a plan to achieve
these objectives. The higher ratings of ’excellent“ and ’outstanding“
are achieved if, among other things, the laboratory‘s high-priority
underutilized job groups show improvement toward full utilization
(’excellent“) or if full utilization is achieved for each designated
high-priority job group (’outstanding“).
Table 6 shows DOE‘s ratings for fiscal years 1998 through 2000 for Los
Alamos and Lawrence Livermore‘s EEO performance. Unlike these
laboratories, at Sandia, EEO performance is included under its human
resources performance measure. For the 3 fiscal years, DOE rated Sandia
as ’outstanding“ in human resources.
Table 6: DOE‘s EEO Ratings for Los Alamos and Lawrence Livermore, Fiscal
Years 1998 through 2000:
Year: 1998;
Los Alamos: Excellent;
Lawrence Livermore: Excellent.
Year: 1999;
Los Alamos: Excellent;
Lawrence Livermore: Good.
Year: 2000;
Los Alamos: Excellent;
Lawrence Livermore: Good.
Source: DOE‘s assessments of Los Alamos‘ and Lawrence Livermore‘s
performance for fiscal years 1998, 1999, 2000.
[End of table]
In addition, the fiscal year 2000 contracts for Los Alamos and Lawrence
Livermore each included a new EEO-related performance measure for
diversity activities. Diversity activities include, for instance,
actions to improve the effectiveness and performance of all groups and
individual members of the workforce. Such efforts are designed to be
respectful of employee and group differences, such as race, ethnicity,
gender, disability status, sexual orientation, job classification,
thinking styles, and other factors of difference. DOE rated Los Alamos‘
diversity performance as ’good“ and Lawrence Livermore‘s as ’marginal,“
primarily because Lawrence Livermore did not meet the requirement to
document a plan of initiatives by the end of the assessment year.
OFCCP”the agency responsible for EEO enforcement at the laboratories”
conducts compliance evaluations that investigate virtually
all aspects of the contractor‘s employment practices to determine
whether the laboratories have complied with applicable laws and
regulations. During these evaluations, OFCCP examines personnel,
payroll, and other employment records and affirmative action programs;
conducts statistical analyses; and interviews employees and company
officials. While OFCCP conducts comprehensive evaluations, these
evaluations are intermittent. Under OFCCP‘s selection system,
contractors are randomly selected for evaluation from a pool of
contractors who have not been evaluated in the previous 2 years and
whose labor force composition shows underutilization and/or
concentration of women or specific minority groups. According to OFCCP
officials, the agency has limited resources and capacity for conducting
compliance evaluations; only 800 staff oversee 100,000 facilities,
government-wide. In 2000, it evaluated 4.2 percent of the facilities,
or 4,162 facilities.
From 1989 through 2001, OFCCP completed eight compliance evaluations
at the three laboratories and reported the following:
* Los Alamos had four compliance evaluations. In 1993, OFCCP reported
three EEO violations regarding technical problems with the laboratory‘s
record keeping and supporting data for its affirmative action program.
For example, Los Alamos‘ workforce analysis did not include all the
required elements. In addition, OFCCP reported that Los Alamos failed
to properly monitor and keep data to determine if minorities and women
were given full and equal opportunity to participate in the informal
succession plan that could enhance their promotional opportunities.
OFCCP closed its other three evaluations in 1994, 1998, and 1999 with
no findings of violations.
* Sandia had three compliance evaluations. In a 1992 conciliation
agreement with OFCCP, Sandia agreed to correct 15 identified violations
of, among other things, EEO policies, promotions, and record keeping.
In addition, in a 1995 conciliation agreement, the laboratory agreed to
correct five EEO violations, and DOE reimbursed the laboratory for the
settlement amount of about $38,000 paid to 12 minority and women staff
for salary and promotion violations. A 1999 compliance evaluation
resulted in two affirmative action program violations for not
addressing ways to increase the hiring and representation of Blacks and
Hispanics at the laboratory, which Sandia agreed to correct.
* Lawrence Livermore last had a compliance evaluation that began in
1987. In the resulting 1989 conciliation agreement, the laboratory
agreed to correct 16 EEO problems that OFCCP had identified, including
disparate treatment of some minority groups in hiring, inadequate
recruiting efforts at historically Black colleges and universities and
those with high Hispanic enrollment, and the failure to properly
implement commitments made in its affirmative action program.
In addition to its compliance evaluations, OFCCP investigates complaints
of employment discrimination involving groups of people or patterns of
discrimination filed with OFCCP by federal contractor employees. OFCCP
conducted six EEO complaint investigations at the laboratories from 1990
through 2001”one at Los Alamos, five at Sandia, and none at Lawrence
Livermore. These complaints alleged unfair practices in promotion,
hiring, and termination, as well as sexual harassment, and retaliation
for filing complaints. OFCCP found no violation in one case at Sandia
and no determination for two complaints at Sandia [Footnote 28] For the
other three complaints, OFCCP found serious problems”two at Sandia and
one at Los Alamos”and closed them with conciliation agreements. For
example, in May 1998 Los Alamos settled a complaint of discrimination
filed by Hispanic employees who lost their job during a reduction-in-
force in November 1995. Under the settlement, the laboratory reinstated
the employees, and Los Alamos paid $625,000 in settlement costs, which
was reimbursed by DOE under the contract.[Footnote 29]
While DOE and OFCCP‘s evaluations yield different information on the
laboratories‘ EEO performance, the agencies work independently and do
not routinely coordinate their efforts. Further, at times, the agencies‘
differing approaches yield what appear to be contradictory results. For
example, in 1999, DOE rated Sandia as ’outstanding“ in human resources,
which includes EEO performance; while a 1999 OFCCP compliance
evaluation at Sandia resulted in two affirmative action program
violations for not addressing ways to increase hiring and
representation of Blacks and Hispanics at the laboratory; Sandia agreed
to correct these problems. Although the agencies agree that they are
working toward the common goal of ensuring the laboratories‘ compliance
with EEO requirements, they have not established an ongoing formal
working relationship. Both agencies have EEO information and expertise
that would be beneficial to share. For example, DOE could provide OFFCP
with information on the current EEO issues at the laboratories as they
arise, status of the laboratories‘ progress in hiring minorities and
women, and trends in EEO complaints raised by laboratory staff.
Conversely, OFCCP could provide DOE with technical assistance and
guidance on EEO compliance.
Effective coordination among agencies with common goals has been a
long-standing problem in the federal government and has proven to be
difficult to resolve. The Government Performance and Results Act of 1993
(GPRA) establishes a framework to address these long-standing
coordination challenges. The intent of GPRA is to shift the focus of
the federal government from a preoccupation with activities to results,
so that agencies sharing common goals work together to develop program
strategies that support each other‘s efforts. As we have reported,
agencies with common goals that do not effectively coordinate their
activities waste scarce resources and undercut the overall
effectiveness of federal efforts.[Footnote 30] Furthermore, Executive
Order 11246 requires DOE to cooperate with OFCCP by providing
information and assistance as requested by OFCCP. According to DOE
officials, they do not regularly coordinate because they believe that
OFCCP has the lead enforcement responsibility and should therefore
initiate coordination activities. While OFCCP generally perceives its
role as conducting independent compliance evaluations, it agreed that
developing an ongoing formal relationship with DOE officials responsible
for contractor oversight might be beneficial.
Conclusions:
The secretary of energy has indicated his commitment to ensuring that
the department maintains a respectful and productive work environment
for both federal and laboratory employees”one that is free of racial
profiling, discrimination, and fear. Our findings of statistically
significant differences in some personnel actions for managerial and
professional staff at the three weapons laboratories do not prove or
disprove discrimination; they do, however, raise questions about the
reasons for these statistical differences. It is therefore important
that DOE, in consultation with OFCCP, explore the reasons for these
differences with the laboratories to assure itself that discrimination
is not occurring. This effort would also give OFFCP and DOE an
opportunity to work together on any potential EEO issues at the
laboratories.
OFCCP‘s in-depth compliance evaluations at the laboratories provide
specific information on the laboratories‘ EEO compliance. However, these
evaluations”in contrast with DOE‘s annual assessments and regular
interactions with laboratory staff”are conducted only intermittently.
Taken together, DOE‘s and OFCCP‘s evaluations and knowledge about the
laboratories could provide a more comprehensive assessment of the
laboratories‘ EEO performance. However, the agencies do not regularly
work with each other toward their common objective of EEO compliance
at the laboratories. As result, they are not leveraging their limited
resources to achieve maximum results, as intended by the Government
Performance and Results Act of 1993.
Recommendations for Executive Action:
To understand the implications of the statistical differences we found
and to evaluate their practical significance, we recommend that the
secretary of energy, in consultation with the director of OFCCP,
determine their causes and take the necessary corrective steps, if
appropriate, to address any EEO problems identified.
To help ensure that DOE and OFCCP work more collaboratively toward
their common goal of EEO compliance at the laboratories, we recommend
that the secretary of energy and the secretary of labor explore the
costs and benefits of various options for developing and implementing
(1) a more formal collaborative relationship to facilitate the sharing
of information and expertise and (2) an effective means for monitoring
and assessing this collaborative relationship.
Agency Comments:
We provided DOE, the Department of Labor, and EEOC with a draft of this
report for their review and comment. DOE and the Department of Labor
provided written comments, which are presented in appendixes IV and V,
respectively. On April 8, 2002, the Director of Communications and
Legislative Affairs, EEOC, provided oral comments on the draft report.
In responding to the draft report, DOE agrees to work with the
Department of Labor‘s OFFCP to achieve the desired effect of our
recommendations as well as to establish better communications between
the two agencies. Regarding the methodology we used to analyze the
laboratories‘ personnel actions, DOE states that the criteria used in
our analysis is different than the criteria used by the laboratories
and could produce different statistical conclusions. Our report
acknowledges that our methodology was not designed to prove or disprove
discrimination, be specifically tailored for each laboratory, or be
exhaustive; rather our focus was to identify statistical differences
using analytical techniques widely accepted and used in human capital
studies to evaluate differences in compensation and other employment-
related subjects. Further our methodology allowed for the most
straightforward and parallel analysis of the laboratories‘ personnel
data. In addition, DOE states that it has initiated its own statistical
review, which is consistent with our recommendation, and that DOE will
use our report in the implementation of its National Nuclear Security
Administration‘s diversity program.
The Department of Labor also agreed with our recommendations.
Specifically, the department‘s OFCCP offers its services and expertise
to DOE so it may perform the necessary and appropriate analyses of the
statistical differences we reported, and if problems exist, OFCCP can
work in partnership with DOE to assist in the design and implementation
of corrective action, as appropriate. OFCCP supports entering into a
dialogue with DOE with the aim of establishing a more collaborative
effort that will leverage resources to assist DOE in better achieving
compliance with EEO statues and guidelines. Such a collaborative effort
could include the cross-training of staff, compliance assistance
regarding enhanced investigative techniques, education regarding self
audit tools that would better serve to identify potential problems
early, and where appropriate sharing with DOE the results of any
compliance evaluations and or compliant investigations of the
laboratories prior to formalizing the findings. Furthermore, the
Department of Labor states that it looks forward to working more
closely with DOE in order to effect stronger EEO workplaces at the
nation‘s weapons laboratories.
EEOC did not have any comments on the report‘s findings, conclusions, or
recommendations. However, EEOC officials did provide minor technical
comments, which we incorporated, as appropriate.
We conducted our review from February 2001 through February 2002 in
accordance with generally accepted government auditing standards.
Appendix I provides details about the scope and methodology of our
review.
As arranged with your offices, unless you publicly announce the contents
of this report earlier, we plan no further distribution of it until 30
days from the date of this letter. We will then send copies to the
secretary of energy; the secretary of labor; the chair, Equal
Employment Opportunity Commission; the director, Office of Management
and Budget; appropriate congressional committees; and other interested
parties. We will also make copies available to others on request.
If you or your staff have any questions about this report, please call
me on (202) 512-3841. Key contributors to this report are listed in
appendix VI.
Signed by:
(Ms.) Gary L. Jones:
Director, Natural Resources and Environment:
[End of section]
Appendix I: Objectives, Scope, and Methodology:
This appendix details the methods we used to (1) describe the
composition of weapons laboratory staff by race/ethnicity, gender, and
job category in 1995 and 2000 to determine how the composition of
laboratory staff has changed in the 5-year period; (2) determine
whether there are statistically significant differences in selected
personnel actions for managers and professionals when comparing
minority men and women and White women with White men in fiscal years
1998 through 2000, the most current reliable data available at the time
of our data request; (3) describe equal employment opportunity (EEO)
concerns raised by laboratory staff; and (4) identify, if appropriate,
opportunities for improving the Department of Energy‘s (DOE) and Office
of Federal Contract Compliance Programs‘ (OFCCP) oversight of the
laboratories‘ compliance with EEO requirements.
Our review focused on personnel actions and EEO concerns at DOE‘s three
major weapons laboratories”Los Alamos National Laboratory located in
New Mexico, Sandia National Laboratory located in New Mexico and
California, and Lawrence Livermore National Laboratory located in
California. We interviewed and obtained data and documentation from
relevant officials at DOE‘s, OFCCP‘s, and the Equal Employment
Opportunity Commission‘s (EEOC) headquarters offices in Washington,
D.C.; DOE officials in the Albuquerque and Oakland operations offices
located in New Mexico and California, respectively; and laboratory
officials in New Mexico and California. We used the race/ethnicity
groups specified by EEOC and OFCCP: White, not of Hispanic origin
(White); Asian or Pacific Islander (Asian); Black, not of Hispanic
origin (Black); Hispanic; and American Indian or Alaskan Native
(American Indian) for our analysis. At the request of Representatives
Eddie Bernice Johnson and David Wu, to provide the most complete
information possible, we performed our analysis for each minority and
gender group, if the data were sufficient for such analysis. We
conducted our work in accordance with generally accepted government
auditing standards from February 2001 through February 2002. In
addition, we approached each objective as discussed below.
First Objective: Describe the Composition of Weapons Laboratory Staff by
Race/Ethnicity, Gender, and Job Category in 1995 and 2000:
We obtained data from the laboratories on the number of staff by
race/ethnicity, gender, and job category group in 1995 and 2000, as
reported annually by the laboratories to EEOC on the Employer
Information Reports (EEO-1s).[Footnote 31] Because Lawrence Livermore
did not file an EEO-1 with EEOC in 1995, to complete our analysis, we
also obtained comparable data that it reported to DOE for 1995. We
compared the data from 1995 to 2000 to determine how the composition of
laboratory staff had changed in a 5-year period. Our analysis included
eight of the nine job category groups required for the EEO-1s:
officials and mangers, professionals, technicians, office and clerical,
craft workers, operatives, laborers, and service workers. The
laboratories do not have sales workers, which is the ninth job
category; therefore, sales workers were not part of our analysis. For
ease of analysis and presentation, we grouped the laboratory jobs into
three categories: managers and professionals, which comprise the
majority of staff at each of the laboratories; technicians, clerks, and
craft workers; and operatives, laborers, and service workers. We
performed this analysis to provide descriptive information about whom,
in terms of race/ethnicity and gender, works at the laboratories; we
purposely did not comment on the appropriateness of the racial/ethnic or
gender composition of staff at each laboratory.
Second Objective: Determine Whether There are Statistically Significant
Differences in Selected Personnel Actions for Managers and Professionals
When Comparing Minority Men and Women and White Women with White Men in
Fiscal Years 1998 through 2000:
Our statistical analysis of laboratory staff includes only those
categorized on the EEO-1 form as officials and managers and
professionals, and non-EEO reporting limited-term staff (such as
postdoctoral students who hold professional occupations on a temporary
basis). We elected to review only these groups because they represent
the majority of laboratory staff, and unlike certain other staff,
personnel data for these employees are maintained by the laboratories
and were available to us. We did not include the following other EEO-1
job categories used by the laboratories in our analysis: technicians,
office and clerical, craft workers, operatives, laborers, and service
workers. We also did not include sales workers because the laboratories
do not have sales workers.
We applied various statistical tests to the employee data on personnel
actions provided by the laboratories. Our analyses are not designed to
prove or disprove discrimination; rather they are designed to provide
information at an aggregate level about race/ethnicity and gender
differences in personnel actions at the laboratories. Although the
laboratories have somewhat different personnel systems and practices,
our analyses of personnel actions included only those variables common
to all three. For example, we did not include individual performance
ratings and rankings, laboratories‘ organizational structure, and
market-based salary analysis and adjustments. Consequently, our
analyses of personnel actions are neither exhaustive nor specifically
tailored for each laboratory. However, we did consult with the
laboratories regarding our analytical approach to make sure we were
receiving the appropriate data for the analysis and that the
laboratories understood how we would be using their data. Additionally,
we consulted with OFFCP about our methodology, and they agreed that our
methodology was appropriate and reasonable. Our analyses are not
designed to prove or disprove discrimination in a court of law; rather
they are designed to provide information at a common and aggregate
level about race/ethnicity and gender differences in personnel actions
at the laboratories. Therefore, our results do not indicate whether
discrimination has or has not occurred.
The federal government‘s Uniform Guidelines on Employment Selection
Procedures direct agencies to analyze personnel actions of groups
protected by title VII of the Civil Rights Act. Under the guidelines,
agencies analyze personnel actions by race/ethnicity and gender
separately; for example, to compare Whites with minorities as a group
and to compare men of all races/ethnicities with women of all
races/ethnicities. At congressional request, we performed our
statistical analyses somewhat differently to show the most information
possible about each minority and gender group at the laboratories. To
do this, we compared each minority group and gender separately if the
data were sufficient to allow this level of analysis using White men as
our benchmark. There were not enough Black men and women or American
Indian men and women to analyze separately for the salary, merit pay,
cash award, and separation analyses, and we therefore analyzed them as
one group.[Footnote 32] This approach allowed us to determine whether
each race/ethnicity and gender group, such as Hispanic women or Asian
men, had different personnel outcomes than White men. We have included
tables in appendix III detailing the results of salary, merit pay, cash
award, and separation analyses using the federal guidelines comparing
Whites with minorities as a group and men of all races/ethnicities with
women of all races/ethnicities.
Salary, Merit Pay, Cash Awards, and Separations:
To determine whether there are statistically significant race/ethnicity
and gender differences in salary, merit pay increases, cash awards, and
separations for managerial and professional staff at each laboratory, we
used multivariate regression techniques. We chose this analytic design
because (1) it is widely used in human capital literature to evaluate
differences in compensation and other employment-related subjects,
(2) it allowed for the most straightforward and parallel analysis of the
laboratories‘ personnel data, and (3) it is an appropriate statistical
method for answering objective 2.
The laboratories provided data from their personnel, payroll, and
security clearance systems for our analyses.[Footnote 33] We requested
data for exempt staff [Footnote 34] in the top two EEO-1 job categories
(officials and managers and professionals) and for selected limited-
term employees, such as postdoctoral students. We included these
limited-term employees primarily because they occupy professional
positions and because these temporary positions are often a pathway to
permanent managerial and professional positions. We requested data for
the 3-year period, fiscal years 1998 through 2000, because these were
the most current data available at the time of our data request. The
laboratories told us that because of changes in laboratory structure
and record retention, we could obtain reliable data only for the most
recent 3-year period. We analyzed the data at the individual level
using the complete population of officials and managers, professionals,
and postdoctoral laboratory staff for the 3-year period. We analyzed
the data separately for each laboratory.
Control variables allowed us to determine whether pay differences
between men and women and minorities existed despite their equality in
position and other human capital characteristics, such as tenure and
education level. For our analyses of salary, merit pay increases,
awards, and separations, we controlled for age; tenure at the
laboratory; education level; job subcategory (including postdoctoral
and temporary status); citizenship status; security clearance level;
and for Sandia‘s staff, whether they were located in California or New
Mexico. We controlled for these factors because they are widely used in
human capital models and because these items were available from all
three laboratories. Some of our models include additional, model-
specific control variables. Specifically, we included a variable in the
salary model denoting whether a promotion had been received in the 3-
year period, because less time in grade would generally be associated
with lower pay. Given that merit pay increases are proportional to
salary, we included salary as a control in the merit pay analysis.
Similarly, we included award receipt, salary, and merit pay in the
separations analysis, as they may be incentives to separate or remain at
the laboratory. Descriptive information for the laboratories based on
the control variables is provided in tables 7 to15 in appendix III.
As our measure of job subcategory, we used the EEO-1 subcategories
developed by the laboratories for use in their affirmative action
programs. These job subcategories are a breakdown of roughly 7 to 10
positions within the officials and managers EEO-1 category, and from 6
to 10 positions within the professional EEO-1 category. These
categories are based on such factors as job content, opportunities, and
compensation.[Footnote 35] While the categories are not exactly the
same across the laboratories, they should be roughly equivalent in the
way personnel are assigned to them, and they should be highly
reflective of the pay one would expect, given the level and function
associated with the job subcategory. Tables 9, 12, and 15 in appendix
III detail the titles and average base salaries associated with these
job subcategories. Compensation data reflect employees‘ most recent
base salary. Merit increases represent an average for the 3-year
period, adjusting for the length of time employees were on board during
that period. We examined only the cash distributions for our awards
analysis. Although the laboratories use a variety of noncash awards,
such as gift certificates, we did not include these in our awards
analysis because the laboratories do not record them in their personnel
or payroll systems. If an award of any amount were received at any
point in the 3-year period, the individual was coded as having received
an award. Separations from the laboratory include voluntary actions,
such as retirements and resignations, and nonvoluntary actions, such as
terminations for cause. If an employee terminated his/her employment at
the laboratory for any reason in the 3-year period, he/she was coded as
having separated.
In accordance with economic analysis literature, we used the natural log
of salary and merit pay in our models.[Footnote 36] Salary and merit
pay were modeled with Ordinary Least Squares regression, and award
receipt and separations were modeled with logistic regression.
Race/ethnicity and gender differences in salary, merit pay, cash
awards, and separations were considered statistically significant if
the probability of the t-statistic or chi square value associated with
the coefficient was 0.05 or lower. In other words, if observed
race/ethnicity and gender differences in salary, merit pay, awards, and
separations could have occurred by chance less than 5 percent of the
time, we assumed with 95-percent confidence that these differences were
statistically significant.
Promotions:
To determine whether promotions of minority men and women and White
women into the ’officials and managers“ category on the EEO-1 reflects
the diversity of the potential applicant pool (other managers and
officials and professionals), we applied the 80 percent rule set out in
the federal government‘s Uniform Guidelines on Employment Selection
Procedures. We did not analyze nonmanagerial professional promotions
because the applicant pools were either external to the laboratories or
were from job categories within the laboratories that we did not
examine. Using the 80 percent rule, we first determined the proportion
of promotions into the officials and managers category for each
race/ethnicity and gender group on the basis of the number of
promotions received in the 3-year period and the total number of
laboratory staff of each group. We then determined whether the
proportions for minority men and women and White women represented at
least 80 percent of the proportion for White men. The rule specifies
that minority promotions should reach at least 80 percent of the
promotion rate of the group with the highest promotion rate. However,
since we used White males as our reference group in all other analyses,
we used the White male promotion rate as the benchmark, regardless of
whether it was the highest.
Since there are a limited number of promotions every year, we examined
promotions for the entire 3-year period. Since postdoctoral and limited-
term employees are not eligible for promotion, they were not included
in the promotion analysis. If a personnel action denoted a
promotion[Footnote 37] into the officials and mangers category, the
race/ethnicity and gender of the employee receiving the promotion was
recorded. If an individual received more than one promotion in the 3-
year period, the action, and not the individual, would be counted as a
promotion. For example, if one Hispanic woman at the laboratory were
promoted twice in the 3-year period, it would count as two promotions
for Hispanic women. The potential applicant pool consists of permanent
laboratory staff in managerial or professional positions at any time in
the 3-year period. Because of data limitations, we could not determine
the exact number of permanent laboratory staff at the time of each
promotion. The number of individuals needed to reach 80 percent of the
White male promotion rate was rounded down. For example, where a
minority group was short of the 80 percent promotion rate by 2.8
people, that group would be reported as being 2 people short. Unlike
the analyses of salary, merit pay, awards, and separations, we did not
control for any factors that might influence the likelihood of
promotion. Additionally, we did not have data on either who was
eligible to compete for a promotion or who actually applied for a
promotion. Our approach was similar to looking at promotions of GS-14-
and GS-15-level federal employees into the Senior Executive Service, or
SES.[Footnote 38]
Disciplinary Actions:
To determine whether there were statistically significant differences in
disciplinary actions for managerial and professional staff at each
laboratory, we requested disciplinary data from the laboratories. The
requested data show disciplinary actions by type of offense (e.g.,
falsifying time records, sexual harassment, etc.), the severity of the
penalty (e.g., reprimand, suspension, termination, etc.), and the
race/ethnicity and gender of the employee disciplined. The laboratories
did not have identical types of offenses or levels of penalties. We
combined these data with laboratory population data from the EEO-1
forms. Because of differences in record keeping at the different
laboratories, the time period for disciplinary data varied slightly. In
general, the data were for fiscal years 1995 through June of 2001; Los
Alamos provided data from January 1, 1995, to June 30, 2001, Sandia
provided data from October 1, 1994, to June 8, 2001, and Lawrence
Livermore provided data from October 1, 1994, to September 30, 2000. We
analyzed these data for the entire time period because there were too
few disciplinary actions per year for reliable analyses. The total
number of staff at each laboratory was the average number over the 5 ½-
year to 6-year time period, according to the EEO-1 forms we obtained
from the laboratories or data from DOE for Lawrence Livermore in 1995.
Using appropriate statistical tests for small-group comparisons, we
tested each laboratory separately for statistically significant
differences in the rate of disciplinary actions and the severity of the
penalty. Where there were sufficient numbers of actions for both the
rate of disciplinary actions and the severity of penalties, we compared
women with men, Whites with minorities, and White men with each EEO
group (White women, Asian men and women, Black men and women, and
Hispanic men and women). There were too few disciplinary actions
involving American Indians to do any statistical tests. Although we
tested for statistical differences, we did not attempt to determine the
cause of the differences we found. However, we did observe that
disciplinary actions for certain offenses occurred only for specific
groups. For example, only men were disciplined for Internet misuse. We
also observed that certain offenses usually resulted in more or less
severe punishments than others. For example, conducting commercial
business on laboratory property typically resulted in harsher penalties
than attendance behavior.
Hiring:
To determine whether there are statistically significant race/ethnicity
and gender differences in hiring of managerial and professional staff
at each laboratory, we requested that the laboratories provide us with
information from their applicant and hiring databases in order to apply
appropriate statistical tests. To apply these tests, it is necessary to
have data files in which only a very small percentage of cases are
missing information for the variables of interest. However, the
databases from all three laboratories were missing a substantial amount
of information. At Los Alamos, 29 percent of the cases were missing
data on race/ethnicity, and 26 percent were missing information on
gender. Of the information provided by Sandia, 31 percent of the cases
were missing gender information, and about 35 percent were missing data
on race/ethnicity. Similarly, race/ethnicity data at Lawrence Livermore
were missing in 24 percent of the cases and 22 percent of the cases
lacked information on gender. Information about the disposition of
applications was available for as little as 40 percent of the
applicants at Sandia. It is not statistically, or otherwise possible,
to determine if race/ethnicity or gender affect hiring decisions
without information on the disposition of applications. The absence of
valid information for so many cases is likely to bias estimates of
whether there are statistically significant race/ethnicity and gender
differences in hiring. Since we do not know whether cases with valid
data differ from those with missing data, using the data would be
misleading and possibly even contrary to results we would see if all
cases had valid data.
Third Objective: Describe EEO Concerns Raised by Laboratory Staff:
We performed a descriptive analysis primarily on the basis of available
information contained in the laboratories‘ surveys of their staff since
1995; the report of DOE‘s Task Force on Racial Profiling, issued in
2000; information contained in EEOC commissioner charges at Los Alamos
and Lawrence Livermore, which we obtained from those laboratories; and
the results of structured interviews we conducted with representatives
of minority and women‘s groups at each laboratory. We also reviewed
available information on other types of staff complaints, such as
lawsuits, which the laboratories provided us with; however, because of
the lack of consistency and completeness of the information provided
across the laboratories, we did not include that information in our
analysis. Information contained in individual complaints filed with
EEOC is confidential, and was not included in our analysis.[Footnote
39] In this report, we included only those EEO staff concerns that we
considered most relevant. We did not attempt to describe all of the EEO
concerns raised or analyze the laboratories efforts to address these
concerns. We also did not attempt to prove or disprove the validity of
these concerns.
Fourth Objective: Identify, if Appropriate, Opportunities for Improving
DOE‘s and OFCCP‘s Oversight of the Laboratories‘ Compliance with EEO
Requirements:
For each laboratory, we reviewed the laboratory‘s self-assessment of its
EEO and related performance and DOE‘s assessments of laboratories‘ self-
assessment for fiscal years 1998 through 2000. We reviewed several
recent affirmative action program documents from each of the
laboratories. We also reviewed other related documents such as pay
equity studies, diversity plans, and recruitment and outreach plans. We
also obtained a summary of OFCCP compliance evaluations and complaint
investigations and the results of those evaluations at the three
laboratories since 1989. Where possible, we obtained and reviewed
copies of the conciliation agreements resulting from OFCCP‘s
evaluations from OFCCP or the laboratories. Since OFCCP requires that
these records be kept for only 3 years, we did not have copies of all
the conciliation agreements to include in our review. We also reviewed
related laws, regulations, and DOE and OFCCP policies and procedures.
[End of section]
Appendix II: Composition of Staff by Job Category Group as a Percentage
of Their Race/Ethnicity and Gender Group:
According to EEOC, data on race/ethnicity, gender, and job category
group can be displayed by (1) participation rates or by (2) occupational
distribution. Participation rates, which are displayed in figures 6 to
11, highlight the composition of a job category group by race/ethnicity
or gender group. For example, at Los Alamos, in 2000, 61 percent of the
managers and professionals were White men. In contrast, the occupational
distribution shows the composition of race/ethnicity or gender group by
job category group. For the same example, at Los Alamos, in 2000, 86
percent of White men were managers and professionals.
Figures 12 to 14 show the occupational distribution for White men, White
women, and minorities for each laboratory.
Figure 12: Composition of Staff at Los Alamos, by Job Category Group,
as a Percentage of Their Gender or Minority Group, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
White men (50% of staff):
Managers and professionals, 1995: 84%;
Managers and professionals, 2000: 87%;
Technicians, clerks, and craft workers, 1995: 17%;
Technicians, clerks, and craft workers, 2000: 13%;
Operatives, laborers, and service workers, 1995: less than 1%;
Operatives, laborers, and service workers, 2000: less than 1%.
White women (17% of staff):
Managers and professionals, 1995: 65%;
Managers and professionals, 2000: 70%;
Technicians, clerks, and craft workers, 1995: 40%;
Technicians, clerks, and craft workers, 2000: 28%;
Operatives, laborers, and service workers, 1995: less than 1%;
Operatives, laborers, and service workers, 2000: less than 1%.
Minorities (33% of staff):
Managers and professionals, 1995: 30%;
Managers and professionals, 2000: 48%;
Technicians, clerks, and craft workers, 1995: 65%;
Technicians, clerks, and craft workers, 2000: 55%;
Operatives, laborers, and service workers, 1995: 2%;
Operatives, laborers, and service workers, 2000: 1%.
Note: The percentage that each race/ethnic and gender group represents
of the total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos.
[End of figure]
Figure 13: Composition of Staff at Sandia, by Job Category Group, as a
Percentage of Their Gender or Minority Group, 1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
White men (54% of staff):
Managers and professionals, 1995: 75%;
Managers and professionals, 2000: 80%;
Technicians, clerks, and craft workers, 1995: 25%;
Technicians, clerks, and craft workers, 2000: 18%;
Operatives, laborers, and service workers, 1995: 2%;
Operatives, laborers, and service workers, 2000: 2%.
White women (20% of staff):
Managers and professionals, 1995: 50%;
Managers and professionals, 2000: 60%;
Technicians, clerks, and craft workers, 1995: 55%;
Technicians, clerks, and craft workers, 2000: 45%;
Operatives, laborers, and service workers, 1995: 1%;
Operatives, laborers, and service workers, 2000: 2%.
Minorities (27% of staff):
Managers and professionals, 1995: 45%;
Managers and professionals, 2000: 50%;
Technicians, clerks, and craft workers, 1995: 55%;
Technicians, clerks, and craft workers, 2000: 50%;
Operatives, laborers, and service workers, 1995: 12%;
Operatives, laborers, and service workers, 2000: 10%.
Note: The percentage that each race/ethnic and gender group represents
of the total laboratory workforce is the average for 1995 and 2000 and
does not add to 100 percent because of rounding.
Source: GAO‘s analysis of EEO-1s obtained from Sandia.
[End of figure]
Figure 14: Composition of Staff at Lawrence Livermore, by Job Category
Group, as a Percentage of Their Gender or Minority Group, 1995 and
2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
White men (58% of staff):
Managers and professionals, 1995: 60%;
Managers and professionals, 2000: 62%;
Technicians, clerks, and craft workers, 1995: 32%;
Technicians, clerks, and craft workers, 2000: 30%;
Operatives, laborers, and service workers, 1995: 5%;
Operatives, laborers, and service workers, 2000: 4%.
White women (24% of staff):
Managers and professionals, 1995: 50%;
Managers and professionals, 2000: 52%;
Technicians, clerks, and craft workers, 1995: 45%;
Technicians, clerks, and craft workers, 2000: 43%;
Operatives, laborers, and service workers, 1995: 4%;
Operatives, laborers, and service workers, 2000: 3%.
Minorities (18% of staff):
Managers and professionals, 1995: 45%;
Managers and professionals, 2000: 50%;
Technicians, clerks, and craft workers, 1995: 42%;
Technicians, clerks, and craft workers, 2000: 40%;
Operatives, laborers, and service workers, 1995: 8%;
Operatives, laborers, and service workers, 2000: 10%.
Note: The percentage that each race/ethnic and gender group represents
of the total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of WFIS data (1995); EEO-1 obtained from
Lawrence Livermore (2000).
[End of figure]
Figures 15 to 17 show the occupational distribution for each of the four
minority groups at the three laboratories.
Figure 15: Minority Group by Job Category Group at Los Alamos, 1995 and
2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
Asian (3% of staff):
Managers and professionals, 1995: 90%;
Managers and professionals, 2000: 94%;
Technicians, clerks, and craft workers, 1995: 10%;
Technicians, clerks, and craft workers, 2000: 6%;
Operatives, laborers, and service workers, 1995: 0%;
Operatives, laborers, and service workers, 2000: 0%.
Black (0.4% of staff):
Managers and professionals, 1995: 70%;
Managers and professionals, 2000: 60%;
Technicians, clerks, and craft workers, 1995: 30%;
Technicians, clerks, and craft workers, 2000: 33%;
Operatives, laborers, and service workers, 1995: 0%;
Operatives, laborers, and service workers, 2000: 0%.
Hispanic (28% of staff):
Managers and professionals, 1995: 32%;
Managers and professionals, 2000: 38%;
Technicians, clerks, and craft workers, 1995: 70%;
Technicians, clerks, and craft workers, 2000: 65%;
Operatives, laborers, and service workers, 1995: 2%;
Operatives, laborers, and service workers, 2000: 1%.
American Indian (2% of staff):
Managers and professionals, 1995: 40%;
Managers and professionals, 2000: 50%;
Technicians, clerks, and craft workers, 1995: 65%;
Technicians, clerks, and craft workers, 2000: 60%;
Operatives, laborers, and service workers, 1995: 1%;
Operatives, laborers, and service workers, 2000: less than 1%.
Note: The percentage that each race/ethnic group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of EEO-1s obtained from Los Alamos.
[End of figure]
Figure 16: Minority Group by Job Category Group at Sandia, 1995 and
2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
Asian (3% of staff):
Managers and professionals, 1995: 75%;
Managers and professionals, 2000: 80%;
Technicians, clerks, and craft workers, 1995: 20%;
Technicians, clerks, and craft workers, 2000: 19%;
Operatives, laborers, and service workers, 1995: 2%;
Operatives, laborers, and service workers, 2000: 1%.
Black (3% of staff):
Managers and professionals, 1995: 40%;
Managers and professionals, 2000: 46%;
Technicians, clerks, and craft workers, 1995: 43%;
Technicians, clerks, and craft workers, 2000: 40%;
Operatives, laborers, and service workers, 1995: 13%;
Operatives, laborers, and service workers, 2000: 13%.
Hispanic (18% of staff):
Managers and professionals, 1995: 35%;
Managers and professionals, 2000: 40%;
Technicians, clerks, and craft workers, 1995: 50%;
Technicians, clerks, and craft workers, 2000: 45%;
Operatives, laborers, and service workers, 1995: 13%;
Operatives, laborers, and service workers, 2000: 12%.
American Indian (3% of staff):
Managers and professionals, 1995: 30%;
Managers and professionals, 2000: 33%;
Technicians, clerks, and craft workers, 1995: 55%;
Technicians, clerks, and craft workers, 2000: 56%;
Operatives, laborers, and service workers, 1995: 14%;
Operatives, laborers, and service workers, 2000: less than 1%.
Note: The percentage that each race/ethnic group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of EEO-1s obtained from Sandia.
[End of figure]
Figure 17: Minority Group by Job Category Group at Lawrence Livermore,
1995 and 2000:
[See PDF for image]
This figure is a multiple vertical bar graph depicting the following
data:
Asian (7% of staff):
Managers and professionals, 1995: 64%;
Managers and professionals, 2000: 72%;
Technicians, clerks, and craft workers, 1995: 30%;
Technicians, clerks, and craft workers, 2000: 25%;
Operatives, laborers, and service workers, 1995: 4%;
Operatives, laborers, and service workers, 2000: 5%.
Black (4% of staff):
Managers and professionals, 1995: 40%;
Managers and professionals, 2000: 462%;
Technicians, clerks, and craft workers, 1995: 44%;
Technicians, clerks, and craft workers, 2000: 42%;
Operatives, laborers, and service workers, 1995: 13%;
Operatives, laborers, and service workers, 2000: 13%.
Hispanic (7% of staff):
Managers and professionals, 1995: 36%;
Managers and professionals, 2000: 37%;
Technicians, clerks, and craft workers, 1995: 50%;
Technicians, clerks, and craft workers, 2000: 48%;
Operatives, laborers, and service workers, 1995: 12%;
Operatives, laborers, and service workers, 2000: 13%.
American Indian (1% of staff):
Managers and professionals, 1995: 40%;
Managers and professionals, 2000: 42%;
Technicians, clerks, and craft workers, 1995: 50%;
Technicians, clerks, and craft workers, 2000: 48%;
Operatives, laborers, and service workers, 1995: 4%;
Operatives, laborers, and service workers, 2000: 3%.
Note: The percentage that each race/ethnic group represents of the
total laboratory workforce is the average for 1995 and 2000.
Source: GAO‘s analysis of WFIS data (1995); EEO-1 obtained from
Lawrence Livermore (2000).
[End of figure]
[End of section]
Appendix III: Additional Information on Personnel Actions at the Three
Laboratories:
This appendix presents (1) descriptive statistics for managerial and
professional laboratory staff for the variables we used in our analysis
of salary, merit pay, cash awards, and separations, which is shown in
tables 7 to 15; (2) additional information on disciplinary actions for
managerial and professional laboratory staff, which is shown in tables
16 to18; and (3) the results for managerial and professional laboratory
staff of salary, merit pay, cash awards, and separations analyses
comparing all men with all women and minorities with nonminorities,
which are shown in tables 19 and 20.
Descriptive Statistics for Variables Used in Our Analysis of Salary,
Merit Pay, Cash Awards, and Separations for Managerial and Professional
Laboratory Staff:
Table 7: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff, Fiscal Years 1998 through 2000:
Total[A]:
Men, Number: 5,614;
Men, Percent: 73.0%;
Women, Number: 2,044;
Women, Percent: 27.0%.
White:
Men, Number: 4,289;
Men, Percent: 58.0%;
Women, Number: 1,353;
Women, Percent: 18.0%.
Asian:
Men, Number: 356;
Men, Percent: 5.0%;
Women, Number: 110;
Women, Percent: 1.0%.
Black:
Men, Number: 43;
Men, Percent: 0.6%;
Women, Number: 16;
Women, Percent: 0.2%.
Hispanic:
Men, Number: 637;
Men, Percent: 9.0%;
Women, Number: 475;
Women, Percent: 6.0%.
American Indian:
Men, Number: 57;
Men, Percent: 0.8%;
Women, Number: 33%;
Women, Percent: 0.5%.
[A] Number of staff by race/ethnicity does not total to the number of
men and women because of missing data for race/ethnicity.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 8: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff”Variables Used in the Salary, Merit Pay,
Cash Award, and Separation Analyses, Fiscal Years 1998 through 2000:
White men:
Average base salary: $88,849;
Average merit pay[A]: $5,267;
Average award[A]: $168;
Average years of tenure: 12;
Average age: 46;
Percentage with Ph.D., J.D., or M.D.: 50;
Percentage with Q clearance: 67;
Percentage that were U.S. citizens: 93.
Asian men:
Average base salary: $71,905;
Average merit pay[A]: $5,229;
Average award[A]: $175;
Average years of tenure: 6;
Average age: 38;
Percentage with Ph.D., J.D., or M.D.: 69;
Percentage with Q clearance: 27;
Percentage that were U.S. citizens: 46.
Hispanic men:
Average base salary: $73,298;
Average merit pay[A]: $4,192;
Average award[A]: $155;
Average years of tenure: 6;
Average age: 45;
Percentage with Ph.D., J.D., or M.D.: 15;
Percentage with Q clearance: 73;
Percentage that were U.S. citizens: 97.
Black men:
Average base salary: $64,133;
Average merit pay[A]: $4,271;
Average award[A]: $137;
Average years of tenure: 8;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 36;
Percentage with Q clearance: 38;
Percentage that were U.S. citizens: 93.
American Indian men:
Average base salary: $83,812;
Average merit pay[A]: $4,977;
Average award[A]: $132;
Average years of tenure: 15;
Average age: 46;
Percentage with Ph.D., J.D., or M.D.: 37;
Percentage with Q clearance: 79;
Percentage that were U.S. citizens: 98.
White women:
Average base salary: $69,036;
Average merit pay[A]: $4,245;
Average award[A]: $169;
Average years of tenure: 10;
Average age: 43;
Percentage with Ph.D., J.D., or M.D.: 22;
Percentage with Q clearance: 60;
Percentage that were U.S. citizens: 95.
Asian women:
Average base salary: $63,776;
Average merit pay[A]: $4,292;
Average award[A]: $176;
Average years of tenure: 6;
Average age: 38;
Percentage with Ph.D., J.D., or M.D.: 39;
Percentage with Q clearance: 27;
Percentage that were U.S. citizens: 58.
Hispanic women:
Average base salary: $55,628;
Average merit pay[A]: $3,095;
Average award[A]: $164;
Average years of tenure: 13;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 6;
Percentage with Q clearance: 65;
Percentage that were U.S. citizens: 99.
Black women:
Average base salary: $51,247;
Average merit pay[A]: $3,702;
Average award[A]: $67;
Average years of tenure: 4;
Average age: 33;
Percentage with Ph.D., J.D., or M.D.: 7;
Percentage with Q clearance: 19;
Percentage that were U.S. citizens: 100.
American Indian women:
Average base salary: $57,901;
Average merit pay[A]: $3,318;
Average award[A]: $179;
Average years of tenure: 10;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 8;
Percentage with Q clearance: 56;
Percentage that were U.S. citizens: 100.
[A] Award and merit pay averages are based on those who received them.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 9: Descriptive Statistics for Los Alamos Managerial and
Professional Laboratory Staff”Average Base Salary for Job Subcategories
Used in the Analysis, Fiscal Years 1998 through 2000:
Job Subcategory: Top Management;
Average base salary: $155,941.
Job Subcategory: Technical Staff Member Group Level Management;
Average base salary: $122,506.
Job Subcategory: Scientific Staff Member Group Level Management;
Average base salary: $93,719.
Job Subcategory: Supervisors”Technical;
Average base salary: $64,220.
Job Subcategory: Supervisors”Scientific;
Average base salary: $71,331.
Job Subcategory: Supervisors”OS/GS;
Average base salary: $44,801.
Job Subcategory: Supervisors”Technical;
Average base salary: $104,610.
Job Subcategory: Technical Staff Member;
Average base salary: $95,413.
Job Subcategory: Personnel/Health/Security;
Average base salary: $55,405.
Job Subcategory: Fiscal Specialists;
Average base salary: $55,715.
Job Subcategory: Administrative/Technical Administrative;
Average base salary: $61,944.
Job Subcategory: Communications/Programming;
Average base salary: $54,294.
Job Subcategory: Senior Designers/Techs/Ops;
Average base salary: $66,211.
Job Subcategory: Postdocs/Special Projects;
Average base salary: $43,471.
Job Subcategory: Limited-term professional staff;
Average base salary: $80,822.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 10: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff, Fiscal Years 1998 through 2000:
Total[A]:
Men, Number: 5,051;
Men, Percent: 76.0;
Women, Number: 1,607;
Women, Percent: 24.0.
White:
Men, Number: 4,210;
Men, Percent: 63.0;
Women, Number: 1,164;
Women, Percent: 17.0.
Asian:
Men, Number: 205;
Men, Percent: 3.0;
Women, Number: 93;
Women, Percent: 1.0.
Black:
Men, Number: 100;
Men, Percent: 2.0;
Women, Number: 52;
Women, Percent: 0.8.
Hispanic:
Men, Number: 478;
Men, Percent: 7.0;
Women, Number: 271;
Women, Percent: 4.0.
American Indian:
Men, Number: 56;
Men, Percent: 0.8;
Women, Number: 27;
Women, Percent: 0.4.
[A] Number of staff by race/ethnicity does not total to the number of
men and women because of missing data for race/ethnicity.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 11: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff”Variables Used in the Salary, Merit Pay, Cash Award,
and Separation Analyses, Fiscal Years 1998 through 2000:
White men:
Average base salary: $86,665;
Average merit pay[A]: $5,182;
Average award[A]: $5,839;
Average years of tenure: 16;
Average age: 45;
Percentage with Ph.D., J.D., or M.D.: 36;
Percentage with Q clearance: 70;
Percentage that were U.S. citizens: 99.
Asian men:
Average base salary: $84,670;
Average merit pay[A]: $5,101;
Average award[A]: $5,524;
Average years of tenure: 10;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 56;
Percentage with Q clearance: 55;
Percentage that were U.S. citizens: 88.
Hispanic men:
Average base salary: $75,031;
Average merit pay[A]: $4,386;
Average award[A]: $4,804;
Average years of tenure: 14;
Average age: 41;
Percentage with Ph.D., J.D., or M.D.: 11;
Percentage with Q clearance: 73;
Percentage that were U.S. citizens: 100.
Black men:
Average base salary: $70,274;
Average merit pay[A]: $3,999;
Average award[A]: $3,887;
Average years of tenure: 14;
Average age: 42;
Percentage with Ph.D., J.D., or M.D.: 11;
Percentage with Q clearance: 58;
Percentage that were U.S. citizens: 96.
American Indian men:
Average base salary: $71,943;
Average merit pay[A]: $4,064;
Average award[A]: $4,865;
Average years of tenure: 13;
Average age: 41;
Percentage with Ph.D., J.D., or M.D.: 15;
Percentage with Q clearance: 64;
Percentage that were U.S. citizens: 100.
White women:
Average base salary: $70,372;
Average merit pay[A]: $4,278;
Average award[A]: $4,443;
Average years of tenure: 11;
Average age: 43;
Percentage with Ph.D., J.D., or M.D.: 16;
Percentage with Q clearance: 60;
Percentage that were U.S. citizens: 99.
Asian women:
Average base salary: $73,811;
Average merit pay[A]: $5,601;
Average award[A]: $4,768;
Average years of tenure: 8;
Average age: 37;
Percentage with Ph.D., J.D., or M.D.: 26;
Percentage with Q clearance: 59;
Percentage that were U.S. citizens: 95.
Hispanic women:
Average base salary: $57,947;
Average merit pay[A]: $3,605;
Average award[A]: $3,251;
Average years of tenure: 12;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 4;
Percentage with Q clearance: 58;
Percentage that were U.S. citizens: 100.
Black women:
Average base salary: $64,483;
Average merit pay[A]: $4,077;
Average award[A]: $3,754;
Average years of tenure: 9;
Average age: 36;
Percentage with Ph.D., J.D., or M.D.: 10;
Percentage with Q clearance: 42;
Percentage that were U.S. citizens: 100.
American Indian women:
Average base salary: $62,085;
Average merit pay[A]: $3,479;
Average award[A]: $3,218;
Average years of tenure: 13;
Average age: 44;
Percentage with Ph.D., J.D., or M.D.: 19;
Percentage with Q clearance: 48;
Percentage that were U.S. citizens: 100.
[A] Award and merit pay averages are based on those who received them.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 12: Descriptive Statistics for Sandia Managerial and Professional
Laboratory Staff”Average Base Salary for Job Subcategories Used in the
Analysis, Fiscal Years 1998 through 2000:
Job subcategory: President/Exec. Vice Pres./Vice Pres./Deputy Vice Pres.
Average base salary[A]: [Blank].
Job subcategory: Member of Technical Staff Director
Average base salary[A]: [Blank].
Job subcategory: Member of Laboratory Staff Director
Average base salary[A]: [Blank].
Job subcategory: Level II Technical Manager
Average base salary[A]: [Blank].
Job subcategory: Level II Administrative Manager
Average base salary[A]: [Blank].
Job subcategory: MTS Manager
Average base salary[A]: [Blank].
Job subcategory: MLS Manager
Average base salary[A]: [Blank].
Job subcategory: Team Supervisor- Professional/Operations/Security
Average base salary[A]: [Blank].
Job subcategory: Fellow/Sr. Scientist/Sr. Administrator
Average base salary[A]: [Blank].
Job subcategory: Distinguished Member of Technical Staff
Average base salary[A]: [Blank].
Job subcategory: Principal Member of Technical Staff
Average base salary[A]: [Blank].
Job subcategory: Senior Member of Technical Staff
Average base salary[A]: [Blank].
Job subcategory: Member of Technical Staff
Average base salary[A]: [Blank].
Job subcategory: Distinguished Member of Laboratory Staff
Average base salary[A]: [Blank].
Job subcategory: Principal Member of Laboratory Staff
Average base salary[A]: [Blank].
Job subcategory: Senior Member of Laboratory Staff
Average base salary[A]: [Blank].
Job subcategory: Member of Laboratory Staff
Average base salary[A]: [Blank].
Job subcategory: Postdocs
Average base salary[A]: [Blank].
Job subcategory: Temporary professional staff
Average base salary[A]: [Blank].
[A] Sandia Laboratory asked us not to publish its salary data because
according to Sandia Corporation‘s policies and practices, salary data
related to employee and job groups is for ’Official Use Only“; that is,
the information may be privileged or sensitive because of national
security, foreign policy, industrial competitiveness, or privacy
considerations.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 13: Descriptive Statistics for Lawrence Livermore Managerial and
Professional Laboratory Staff, Fiscal Years 1998 through 2000:
Total[A]:
Men, Number: 4,082;
Men, Percent: 70.0;
Women, Number: 1,708;
Women, Percent: 30.0.
White:
Men, Number: 3,366;
Men, Percent: 59.0;
Women, Number: 1,284;
Women, Percent: 22.0.
Asian:
Men, Number: 364;
Men, Percent: 6.0;
Women, Number: 200;
Women, Percent: 4.0.
Black:
Men, Number: 100;
Men, Percent: 2.0;
Women, Number: 73;
Women, Percent: 1.0.
Hispanic:
Men, Number: 158;
Men, Percent: 3.0;
Women, Number: 114;
Women, Percent: 2.0.
American Indian:
Men, Number: 37;
Men, Percent: 0.6;
Women, Number: 25;
Women, Percent: 0.4.
[A] Number of staff by race/ethnicity does not total to the number of
men and women because of missing data for race/ethnicity.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 14: Descriptive Statistics for Lawrence Livermore Managerial and
Professional Laboratory Staff”Variables Used in the Salary, Merit Pay,
Cash Award, and Separation Analyses, Fiscal Years 1998 through 2000:
White men:
Average base salary: $79,823;
Average merit pay[A]: $4,672;
Average award[A]: $254;
Average years of tenure: 14;
Average age: 44;
Percentage with Ph.D., J.D., or M.D.: 40;
Percentage with Q clearance: 66;
Percentage that were U.S. citizens: 96.
Asian men:
Average base salary: $71,225;
Average merit pay[A]: $3,844;
Average award[A]: $258;
Average years of tenure: 10;
Average age: 41;
Percentage with Ph.D., J.D., or M.D.: 49;
Percentage with Q clearance: 53;
Percentage that were U.S. citizens: 88.
Hispanic men:
Average base salary: $64,008;
Average merit pay[A]: $5,029;
Average award[A]: $231;
Average years of tenure: 11;
Average age: 39;
Percentage with Ph.D., J.D., or M.D.: 16;
Percentage with Q clearance: 52;
Percentage that were U.S. citizens: 96.
Black men:
Average base salary: $60,661;
Average merit pay[A]: $3,464;
Average award[A]: $149;
Average years of tenure: 11;
Average age: 40;
Percentage with Ph.D., J.D., or M.D.: 14;
Percentage with Q clearance: 52;
Percentage that were U.S. citizens: 98.
American Indian men:
Average base salary: $66,268;
Average merit pay[A]: $3,824;
Average award[A]: $312;
Average years of tenure: 14;
Average age: 43;
Percentage with Ph.D., J.D., or M.D.: 19;
Percentage with Q clearance: 68;
Percentage that were U.S. citizens: 100.
White women:
Average base salary: $58,213;
Average merit pay[A]: $3,570;
Average award[A]: $210;
Average years of tenure: 11;
Average age: 41;
Percentage with Ph.D., J.D., or M.D.: 13;
Percentage with Q clearance: 51;
Percentage that were U.S. citizens: 98.
Asian women:
Average base salary: $55,601;
Average merit pay[A]: $3,365;
Average award[A]: $180;
Average years of tenure: 9;
Average age: 36;
Percentage with Ph.D., J.D., or M.D.: 17;
Percentage with Q clearance: 39;
Percentage that were U.S. citizens: 94.
Hispanic women:
Average base salary: $47,394;
Average merit pay[A]: $2,736;
Average award[A]: $224;
Average years of tenure: 11;
Average age: 37;
Percentage with Ph.D., J.D., or M.D.: 4;
Percentage with Q clearance: 40;
Percentage that were U.S. citizens: 97.
Black women:
Average base salary: $49,128;
Average merit pay[A]: $2,696;
Average award[A]: $186;
Average years of tenure: 10;
Average age: 38;
Percentage with Ph.D., J.D., or M.D.: 1;
Percentage with Q clearance: 38;
Percentage that were U.S. citizens: 99.
American Indian women:
Average base salary: $45,408;
Average merit pay[A]: $2,370;
Average award[A]: $152;
Average years of tenure: 11;
Average age: 42;
Percentage with Ph.D., J.D., or M.D.: 4;
Percentage with Q clearance: 36;
Percentage that were U.S. citizens: 100.
[A] Award and merit pay averages are based on those who received them.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 15: Descriptive Statistics of Lawrence Livermore Managerial and
Professional Laboratory Staff”Average Base Salary for Job Subcategories
Used in the Analysis, Fiscal Years 1998 through 2000:
Job subcategory: Management”Scientific Internal;
Average base salary: $128,430
Job subcategory: Management”Administrative Internal;
Average base salary: $97,163.
Job subcategory: Supervisor”Technical Internal;
Average base salary: $88,872.
Job subcategory: Supervisor”Clerical Internal;
Average base salary: $55,397.
Job subcategory: Supervisor”Non Clerical Internal;
Average base salary: $63,379.
Job subcategory: Supervisor”Blue Collar Internal;
Average base salary: $59,082.
Job subcategory: Supervisor”Service Internal;
Average base salary: $43,210.
Job subcategory: Administrator National;
Average base salary: $58,199.
Job subcategory: Physicist National;
Average base salary: $82,965.
Job subcategory: Chemist/Metallurgist National;
Average base salary: $78,101.
Job subcategory: Life Scientist National;
Average base salary: $50,938.
Job subcategory: Computer Scientist National;
Average base salary: $76,248.
Job subcategory: Engineer”Mechanical National;
Average base salary: $80,988.
Job subcategory: Engineer”Electronics National;
Average base salary: $80,540.
Job subcategory: Engineer”Miscellaneous National;
Average base salary: $83,784.
Job subcategory: Tech. Info Editor/Specialist National;
Average base salary: $60,333.
Job subcategory: Environmental Scientist National;
Average base salary: $72,748.
Job subcategory: Postdocs;
Average base salary: $37,749.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Number and Type of Disciplinary Actions Taken, by Race/Ethnicity and
Gender for Managerial and Professional Laboratory Staff:
Table 16: Disciplinary Actions at Los Alamos for Managerial and
Professional Laboratory Staff, 1995 through June 2001:
Race/ethnicity: Asian;
Gender: Men;
Written reprimand: 7;
Suspension: 1;
Termination: 1;
Males: 9;
Females: [Blank];
Total actions: 9;
Average number of managerial and professional staff by racial/ethnic
group: 175.
Race/ethnicity: Asian;
Gender: Women;
Written reprimand: 0;
Suspension: 0;
Termination: 0;
Males: [Blank];
Females: 0;
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 53.
Race/ethnicity: Black;
Gender: Men;
Written reprimand: 0;
Suspension: 0;
Termination: 0;
Males: 0;
Females: [Blank];
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 21.
Race/ethnicity: Black;
Gender: Women;
Written reprimand: 0;
Suspension: 1;
Termination: 1;
Males: [Blank];
Females: 2;
Total actions: 2;
Average number of managerial and professional staff by racial/ethnic
group: 6.
Race/ethnicity: Hispanic;
Gender: Men;
Written reprimand: 7;
Suspension: 3;
Termination: 4;
Males: 14;
Females: [Blank];
Total actions: 14;
Average number of managerial and professional staff by racial/ethnic
group: 438.
Race/ethnicity: Hispanic;
Gender: Women;
Written reprimand: 2;
Suspension: 1;
Termination: 0;
Males: [Blank];
Females: 3;
Total actions: 3;
Average number of managerial and professional staff by racial/ethnic
group: 274.
Race/ethnicity: American Indian;
Gender: Men;
Written reprimand: 0;
Suspension: 0;
Termination: 0;
Males: 0;
Females: [Blank];
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 42.
Race/ethnicity: American Indian;
Gender: Women;
Written reprimand: 0;
Suspension: 0;
Termination: 0;
Males: [Blank];
Females: 0;
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 17.
Race/ethnicity: Subtotal;
Written reprimand: 16;
Suspension: 6;
Termination: 6;
Males: 23;
Females: 5;
Total actions: 28;
Average number of managerial and professional staff by racial/ethnic
group: 1,026.
Race/ethnicity: White;
Gender: Men;
Written reprimand: 48;
Suspension: 21;
Termination: 13;
Males: 82;
Females: [Blank];
Total actions: 82;
Average number of managerial and professional staff by racial/ethnic
group: 3,215.
Race/ethnicity: White;
Gender: Women;
Written reprimand: 12;
Suspension: 1;
Termination: 2;
Males: [Blank];
Females: 15;
Total actions: 15;
Average number of managerial and professional staff by racial/ethnic
group: 922.
Race/ethnicity: Subtotal;
Written reprimand: 60;
Suspension: 22;
Termination: 15;
Males: 82;
Females: 15;
Total actions: 97;
Average number of managerial and professional staff by racial/ethnic
group: 4,137.
Race/ethnicity: Unknown;
Gender: Men;
Written reprimand: 1;
Suspension: 1;
Termination: 0;
Males: 2;
Females: 0;
Total actions: 2;
Average number of managerial and professional staff by racial/ethnic
group: [Blank].
Race/ethnicity: Total;
Written reprimand: 77;
Suspension: 29;
Termination: 21;
Males: 107;
Females: 20;
Total actions: 127;
Average number of managerial and professional staff by racial/ethnic
group: 5,163.
Note: Unknown means racial/ethnic description not given.
Source: GAO‘s analysis of laboratory‘s disciplinary data and EEO-1 data
provided by Los Alamos.
[End of table]
Table 17: Disciplinary Actions at Sandia for Managerial and
Professional Laboratory Staff, 1995 through June 2001:
Race/ethnicity: Asian;
Gender: Men;
Letter of reprimand: 0;
Suspension: 2;
Termination: 1;
Demotion: 0;
Males: 3;
Females: [Blank];
Total actions: 3;
Average number of managerial and professional staff by racial/ethnic
group: 130.
Race/ethnicity: Asian;
Gender: Women;
Letter of reprimand: 1;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 1;
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 61.
Race/ethnicity: Black;
Gender: Men;
Letter of reprimand: 0;
Suspension: 0;
Termination: 0;
Demotion: 1;
Males: 1;
Females: [Blank];
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 66.
Race/ethnicity: Black;
Gender: Women;
Letter of reprimand: 1;
Suspension: 1;
Termination: 1;
Demotion: 0;
Males: [Blank];
Females: 3;
Total actions: 3;
Average number of managerial and professional staff by racial/ethnic
group: 28.
Race/ethnicity: Hispanic;
Gender: Men;
Letter of reprimand: 6;
Suspension: 6;
Termination: 2;
Demotion: 1;
Males: 15;
Females: [Blank];
Total actions: 15;
Average number of managerial and professional staff by racial/ethnic
group: 359.
Race/ethnicity: Hispanic;
Gender: Women;
Letter of reprimand: 0;
Suspension: 0;
Termination: 1;
Demotion: 0;
Males: [Blank];
Females: 1;
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 165.
Race/ethnicity: American Indian;
Gender: Men;
Letter of reprimand: 0;
Suspension: 1;
Termination: 0;
Demotion: 0;
Males: 1;
Females: [Blank];
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 40.
Race/ethnicity: American Indian;
Gender: Women;
Letter of reprimand: 0;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 0;
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 23.
Race/ethnicity: Subtotal;
Letter of reprimand: 8;
Suspension: 10;
Termination: 5;
Demotion: 2;
Males: 20;
Females: 5;
Total actions: 25;
Average number of managerial and professional staff by racial/ethnic
group: 872.
Race/ethnicity: White;
Gender: Men;
Letter of reprimand: 25;
Suspension: 26;
Termination: 11;
Demotion: 0;
Males: 62;
Females: [Blank];
Total actions: 62;
Average number of managerial and professional staff by racial/ethnic
group: 3,296.
Race/ethnicity: White;
Gender: Women;
Letter of reprimand: 8;
Suspension: 1;
Termination: 1;
Demotion: 0;
Males: [Blank];
Females: 10;
Total actions: 10;
Average number of managerial and professional staff by racial/ethnic
group: 808.
Race/ethnicity: Subtotal;
Letter of reprimand: 33;
Suspension: 27;
Termination: 12;
Demotion: 0;
Males: 62;
Females: 10;
Total actions: 72;
Average number of managerial and professional staff by racial/ethnic
group: 4,104.
Race/ethnicity: Total;
Letter of reprimand: 41;
Suspension: 37;
Termination: 17;
Demotion: 2;
Males: 82;
Females: 15;
Total actions: 97;
Average number of managerial and professional staff by racial/ethnic
group: 4,976.
Note: Sandia figures include disciplinary actions for Sandia sites in
New Mexico and California. They do not include disciplinary actions for
limited-term staff, such as postdoctoral students because Sandia does
not report these employees on its EEO-1s.
Source: GAO‘s analysis of laboratory‘s disciplinary data and EEO-1 data
provided by Sandia.
[End of table]
Table 18: Disciplinary Actions at Lawrence Livermore for Managerial and
Professional Laboratory Staff, 1995 through 2000:
Race/ethnicity: Asian;
Gender: Men;
Warning letter: 6;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: 6;
Females: [Blank];
Total actions: 6;
Average number of managerial and professional staff by racial/ethnic
group: 193.
Race/ethnicity: Asian;
Gender: Women;
Warning letter: 2;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 2;
Total actions: 2;
Average number of managerial and professional staff by racial/ethnic
group: 91.
Race/ethnicity: Black;
Gender: Men;
Warning letter: 9;
Suspension: 2;
Termination: 1;
Demotion: 0;
Males: 12;
Females: [Blank];
Total actions: 12;
Average number of managerial and professional staff by racial/ethnic
group: 64.
Race/ethnicity: Black;
Gender: Women;
Warning letter: 1;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 1;
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 45.
Race/ethnicity: Hispanic;
Gender: Men;
Warning letter: 4;
Suspension: 1;
Termination: 0;
Demotion: 0;
Males: 5;
Females: [Blank];
Total actions: 5;
Average number of managerial and professional staff by racial/ethnic
group: 93.
Race/ethnicity: Hispanic;
Gender: Women;
Warning letter: 2;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 2;
Total actions: 2;
Average number of managerial and professional staff by racial/ethnic
group: 64.
Race/ethnicity: American Indian;
Gender: Men;
Warning letter: 1;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: 1;
Females: [Blank];
Total actions: 1;
Average number of managerial and professional staff by racial/ethnic
group: 25.
Race/ethnicity: American Indian;
Gender: Women;
Warning letter: 0;
Suspension: 0;
Termination: 0;
Demotion: 0;
Males: [Blank];
Females: 0;
Total actions: 0;
Average number of managerial and professional staff by racial/ethnic
group: 15.
Race/ethnicity: Subtotal;
Warning letter: 25;
Suspension: 3;
Termination: 1;
Demotion: 0;
Males: 24;
Females: 5;
Total actions: 29;
Average number of managerial and professional staff by racial/ethnic
group: 589.
Race/ethnicity: White;
Gender: Men;
Warning letter: 61;
Suspension: 15;
Termination: 13;
Demotion: 2;
Males: 91;
Females: [Blank];
Total actions: 91;
Average number of managerial and professional staff by racial/ethnic
group: 2,362.
Race/ethnicity: White;
Gender: Women;
Warning letter: 14;
Suspension: 3;
Termination: 1;
Demotion: 1;
Males: [Blank];
Females: 19;
Total actions: 19;
Average number of managerial and professional staff by racial/ethnic
group: 823.
Race/ethnicity: Subtotal;
Warning letter: 75;
Suspension: 18;
Termination: 14;
Demotion: 3;
Males: 91;
Females: 19;
Total actions: 110;
Average number of managerial and professional staff by racial/ethnic
group: 3,185.
Race/ethnicity: Total;
Warning letter: 100;
Suspension: 21;
Termination: 15;
Demotion: 3;
Males: 115;
Females: 24;
Total actions: 139;
Average number of managerial and professional staff by racial/ethnic
group: 3,775.
Source: GAO‘s analysis of laboratory‘s disciplinary data and EEO-1
provided by Lawrence Livermore and WFIS data provided by DOE.
[End of table]
Results of Tests for Men Versus Women and Minority Versus Nonminority
for Managerial and Professional Laboratory Staff:
Table 19: Results for Managerial and Professional Laboratory Staff of
Salary, Merit Pay, Cash Awards, and Separations Analyses Comparing All
Women with All Men, Fiscal Years 1998 through 2000:
Laboratory: Los Alamos;
Percent difference, Salary: -6;
Percent difference, Merit pay: [Blank];
Likelihood ratios, Awards: [Blank];
Likelihood ratios, Separations: 0.700.
Laboratory: Sandia;
Percent difference, Salary: -4;
Percent difference, Merit pay: 34;
Likelihood ratios, Awards: [Blank];
Likelihood ratios, Separations: [Blank].
Laboratory: Lawrence Livermore;
Percent difference, Salary: -8;
Percent difference, Merit pay: 19;
Likelihood ratios, Awards: [Blank];
Likelihood ratios, Separations: [Blank].
Note: Blank spaces indicate that results for these groups were not
statistically significant.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
Table 20: Results for Managerial and Professional Laboratory Staff of
Salary, Merit Pay, Cash Awards, and Separations Analyses Comparing All
Minorities with Nonminorities, Fiscal Years 1998 through 2000:
Laboratory: Los Alamos;
Percent difference, Salary: -2;
Percent difference, Merit pay: [Blank];
Likelihood ratios, Awards: 0.838;
Likelihood ratios, Separations: 0.812.
Laboratory: Sandia;
Percent difference, Salary: -2;
Percent difference, Merit pay: [Blank];
Likelihood ratios, Awards: 1.724;
Likelihood ratios, Separations: [Blank].
Laboratory: Lawrence Livermore;
Percent difference, Salary: -3;
Percent difference, Merit pay: [Blank];
Likelihood ratios, Awards: 0.716;
Likelihood ratios, Separations: [Blank].
Note: Blank spaces indicate that results for these groups were not
statistically significant.
Source: GAO‘s analysis of laboratory‘s data.
[End of table]
[End of section]
Appendix IV: Comments from the Department of Energy:
Department of Energy:
National Nuclear Security Administration:
Washington, DC 20585:
April 8, 2002:
Ms. Gary L. Jones:
Director, Natural Resources and Environment:
U. S. General Accounting Office:
Washington, D.C. 20548:
Dear Ms. Jones:
The General Accounting Office's draft report GAO-02-291, "DOE Weapons
Laboratories: Actions Needed to Strengthen EEO Oversight," was received
and reviewed by my office. The National Nuclear Security Administration
appreciates the opportunity to review your efforts. We understand that
the General Accounting Office (GAO) was requested to review personnel
actions taken at our weapons laboratories over the past decade to
determine if there has been differential treatment in the handling of
cases involving minorities.
As you are aware, and as the draft report states, the Secretary of
Energy has reaffirmed the Department's opposition to discrimination in
the hiring and treatment of employees. He has stated that he expects
and requires full compliance with both the spirit and letter of all
civil rights laws, regulations, and policies. This commitment applies
to both the Federal work force and the Department's contractor
employees. The National Nuclear Security Administration fully supports
the Secretary's position. The NNSA Administrator, in his report to
Congress on February 25, 2002, described the role of the Diversity
Office that he established to provide leadership, foster partnership,
and model accountability throughout the Administration in advancing the
diversity mission. While the Administration is establishing and
implementing new roles and responsibilities, the goals of a viable
diversity program are being implemented. Specifically, the
Administrator:
* presented a report to the Secretary providing an analysis of-and
recommending key actions necessary for addressing-high-profile racial
profiling issues;
* sponsored the Tri-lab diversity meeting to explore retention,
recruitment, and security policies in light of racial profiling and
career advancement concerns;
* detailed an experienced senior manager from Sandia National
Laboratories to temporarily head the Diversity Office and reassigned
additional Federal employees into the office. The same detailee and
assigned staff have initiated a number of long term actions to address
the diversity needs of the NNSA;
* brought in, and is continuing to utilize the services of a highly
recognized diversity expert to work with NNSA's senior leadership in a
wide variety of diversity related matters; and;
* established a senior executive service level position to permanently
dead the NNSA Diversity office. The incumbent, when selected from the
candidates that applied for this position, will report to the
Administrator.
The Administrator's short term goals are to:
* establish a National Nuclear Security Administration Diversity
Council and produce a diversity strategic plan;
* define and clarify interfaces with departmental headquarters,
Administration headquarters, field elements, laboratories, and
production plants;
* effectively address diversity issues in a timely manner;
* begin to make strides in improving the work environment for the
people of the Administration;
* work toward ensuring a balanced workforce; and;
* seize opportunities to promote the importance of diversity throughout
the Administration.
We appreciate the fact that your draft report acknowledges that there
may be statistically significant differences in some personnel actions
for managerial and professional staff, and that these differences do
not prove or disprove discrimination. We will utilize your report as a
data point in the implementation of the overall National Nuclear
Security Administration Diversity Program as reported to Congress.
Furthermore, the Administration and the Department will work with the
Department of Labor and specifically the Office of Federal Contract
Compliance Programs to achieve the desired effect of the
recommendations as well as to establish better communications between
the two entities.
The statistical analysis review criteria used by the General Accounting
Office is different from the criteria that the laboratories use to both
analyze and portray their diversity data. Our analysis of the draft
report also indicates a potential disagreement with your statistical
conclusions. We would appreciate receiving any information that you
have that would help us to complete our statistical review of the
program. We do have additional detailed comments we would be glad to
share with you at your convenience.
Sincerely yours,
Signed by:
Anthony R. Lane:
Associate Administrator for Management and Administration:
[End of section]
Appendix V: Comments from the Department of Labor:
U.S. Department of Labor:
Assistant Secretary for Employment Standards:
Washington. D.C. 20210:
April 16, 2002:
Ms. Gary L. Jones:
Director Natural Resources and the Environment:
U.S. General Accounting Office:
Washington DC 20548:
Dear Ms. Jones:
Thank you for the opportunity to review and provide comments on the
draft General Accounting Office (GAO) report entitled "DOE Weapons
Laboratories: Actions Needed to Strengthen EEO Oversight," " GAO-02-
391. On behalf of Secretary Chao, the Employment Standards
Administration (ESA), Office of Federal Contract Compliance Programs
(OFCCP) has reviewed the report. At the outset, let me state the
ESA/OFCCP is committed to fully carrying out its responsibilities to
ensure federal contractor compliance with our nation's equal employment
opportunity (EEO) laws. Our responses to the GAO recommendations appear
below.
GAO Recommendation: To understand the implications of the statistical
differences we found and to evaluate their practical significance, we
recommend that the secretary of energy, in consultation with OFCCP,
determine their causes and take the necessary corrective steps, if
appropriate, to address any equal employment opportunity (EEO) problems
identified.
Agency Response: OFCCP agrees that consultation and collaboration with
the Department of Energy can better address the equal employment
opportunity problems identified. As such, OFCCP offers its services and
expertise to DOE so that they may perform the necessary and appropriate
analyses in these areas to make determinations regarding the
implications of the statistical differences. If it is found that
problems exist, OFCCP can work in partnership with DOE to assist in the
design and implementation of corrective action, as appropriate.
Working to Improve the Lives of America's Workers
GAO Recommendation: To ensure that DOE and OFCCP work more
collaboratively toward their common goal of EEO compliance at the
laboratories, we recommend that the secretary of energy and the
secretary of labor explore the costs and benefits of various options
for developing and implementing (1) a more formal collaborative
relationship to facilitate sharing information and expertise and (2) an
effective means of monitoring and assessing this collaborative
relationship.
Agency Response: DOL/OFCCP supports entering into a dialogue with DOE
with the aim of establishing a more collaborative effort that will
leverage resources to assist DOE in better achieving compliance with
EEO statutes and guidelines. Such a collaborative effort could include
the cross-training of staff, compliance assistance regarding enhanced
investigative techniques, and education regarding self-audit tools that
would better serve to identify potential problems early. In addition,
where appropriate, OFCCP could share with DOE the results of compliance
evaluations and/or complaint investigations of the laboratories prior
to formalizing the findings.
In addition to our response to the recommendations, we would like to
comment on the text references and footnote 3 regarding Standard Form
100 (EEO-1). The Joint Reporting Committee (JRC) has responsibility for
collecting and reporting EEO-1 data. The JRC is composed of both the
Equal Employment Opportunity Commission (EEOC) and OFCCP. GAO should
replace "EEOC" with "the JRC" throughout the text when discussing EEO-1
data.
Finally, we appreciate the efforts of the General Accounting Office in
this regard, and we look forward to working more closely with the
Department of Energy in order to effect stronger equal employment
opportunity workplaces at the nation's weapons laboratories.
Sincerely,
Signed by:
Victoria A. Lipnic:
Assistant Secretary:
[End of section]
Appendix VI: GAO Contacts and Staff Acknowledgments:
GAO Contacts:
Andrea W. Brown (202)-512-3319:
Staff Acknowledgments:
In addition to those named above, Vondalee R. Hunt, Susan Irwin,
Rebecca Shea, Carol Herrnstadt Shulman, Karla Springer, Greg Wilmoth,
and Lisa Vojta made key contributions to this report.
[End of section]
Footnotes:
[1] According to DOE, racial profiling includes practices that
scrutinize, target, or treat employees or applicants for employment
differently or single them out or select them for unjustified
additional scrutiny, on the basis of race or national origin.
[2] The eight job categories are officials and mangers, professionals,
technicians, office and clerical, craft workers, operatives, laborers,
and service workers. The ninth job category is sales workers. The
laboratories do not have any sales workers, so they report zero in this
category.
[3] Technically, federal contractors submit EEO-1 forms, otherwise
known as Standard Form 100, to the Joint Reporting Committee, which
consists of EEOC and OFFCP. While EEOC and OFCCP jointly dictate EEO-1
requirements, the responsibility for administering this survey has
historically been held by EEOC. Thus, we will refer to EEOC in the
report rather than the Joint Reporting Committee when we discuss EEO-
1s.
[4] For ease of analysis and presentation, we grouped the EEO-1 job
categories of officials and managers and professionals into one job
category group called ’managers and professionals.“ We grouped the EEO-
1 job categories of technicians, office and clerical, and craft workers
into one job category group called ’technicians, clerks, and craft
workers.“ We grouped the EEO-1 job categories of operatives, laborers,
and service workers into one job category group called ’operatives,
laborers, and service workers.“
[5] Our statistical analysis of personnel actions is for laboratory
staff in the EEO-1 categories of officials and managers, and
professionals. We also included limited-term staff, such as
postdoctoral students in professional positions on a temporary basis.
[6] The 80 percent rule is a ’rule of thumb“ under which EEOC, OFCCP,
and other agencies will generally consider a selection rate for any
race, sex, or ethnic group that is less than 80 percent of the
selection rate for the group with the highest selection rate as a
substantially different rate of selection. This rule of thumb is a
guideline, not a regulation, and is a practical means of keeping the
agencies‘ attention on serious discrepancies in rates of hiring,
promotion and other selection decisions, and on the selection
procedures they use.
[7] The National Nuclear Security Administration, a separately
organized agency within DOE, is responsible for the nation‘s nuclear
weapons laboratories.
[8] Prior to the Sandia Corporation contract, which began in 1993,
Sandia was operated under contract, with periodic revisions, by AT&T
since 1949.
[9] Under certain circumstances, the secretary of labor may exempt a
contracting agency from including any or all of the EEO provisions of
Executive Order 11246 in a specific contract.
[10] According to OFCCP regulations, each government contractor with 50
or more employees and $50,000 or more in government contracts is
required to develop a written affirmative action program for each of
its establishments. OFCCP is responsible for reviewing the contractor‘s
affirmative action program. OFCCP generally does this as part of a
compliance evaluation.
[11] See footnote 3.
[12] This applies to all federal contractors with 50 or more employees
and a contract value of $50,000 or more.
[13] Also known as Standard Form 100.
[14] See footnote 3.
[15] The 80 percent rule is a ’rule of thumb“ under which EEOC, OFCCP,
and other agencies will generally consider a selection rate for any
race, sex, or ethnic group that is less than 80 percent of the
selection rate for the group with the highest selection rate as a
substantially different rate of selection. This rule of thumb is a
guideline, not a regulation, and is a practical means of keeping the
agencies‘ attention on serious discrepancies in the rates of hiring,
promotion, and other selection decisions, and on the selection
procedures they use. We used White men as the comparison group, rather
than the group with the highest selection rate because this method
allowed us to compare them with the same group across the laboratories.
Using the 80 percent rule, we first determined the proportion of
promotions for each race/ethnicity and gender group on the basis of
their proportions in the officials and managers and professionals
groups (the potential applicant pool). We then determined whether the
proportions for minorities and women represented at least 80 percent of
the proportion for White men. Unlike the analyses of salary, merit pay,
awards, and separations, we did not control for any factors that might
influence the likelihood of promotion. Additionally, we did not
determine whether individuals in the ’pool“ had applied for a promotion
or if they were eligible for a promotion in the 3-year period.
[16] We conducted this analysis for promotions into management
positions”the ’officials and managers“ category on the EEO-1”from a
pool consisting of any staff on board at the laboratory within the
period categorized on EEO-1s as either officials and managers or
professionals. We did not analyze nonmanagerial professional promotions
because the applicant pools were either external to the laboratories or
from job categories within the laboratories that we did not examine.
[17] A more comprehensive statistical analysis would have considered
the year of the disciplinary action, the type of offense, and the
severity of punishment when testing for statistically significant
differences by race/ethnicity and gender.
[18] There were too few disciplinary actions to statistically compare
the severity of punishment for the type of offense and to analyze any
differences by gender within each minority group. For example, we could
not analyze whether Hispanic men and White men committing the same
offense received significantly different punishments for those
offenses, nor could we determine whether men and women within a
minority group, such as Hispanics, received significantly more severe
or less punishment for the same offense.
[19] The commission is prohibited from making public any information
obtained under title VII of the Civil Rights Act of 1964, as amended,
unless that information has been made part of a legal proceeding under
the act (title VII, sec. 706(b) and 709(e); 42 U.S.C. 2000e-5(b) and
2000e-8(e)). Under EEOC‘s implementing regulations, this prohibition is
applicable to charges filed by employees and information the agency
obtains during an investigation of these charges. (29 C.F.R. 1601.22)
We could not use in our report EEOC information on complaints filed
with it by laboratory staff because we are required to maintain the same
level of confidentiality for this information as does EEOC (31 U.S.C.
716(e)(1)).
[20] The survey was distributed to 289 Asian and Pacific Islanders at
the laboratory of which 65 (22.5 percent) responded.
[21] The survey was distributed to all 7,001 full- and part-time
laboratory employees of which 2,904 (41 percent) were completed and
returned.
[22] The survey was distributed to 1,781 employees, which represented a
stratified random sample of approximately 23 percent of employees in
all divisions at Sandia. Of the 1,781 surveys distributed, 1,092 were
returned for a response rate of 61.3 percent.
[23] The survey was distributed to 7,709 laboratory employees, and had
a 70 percent return rate.
[24] The survey was distributed to 289 Asian and Pacific Islanders at
the laboratory of which 65 (22.5 percent) responded. Of the
respondents, 77 percent were aware of underrepresentation of Asian and
Pacific Islanders in management.
[25] The DOE Task Force conducted site visits during the summer and
fall of 1999 at Los Alamos National Laboratory; Sandia National
Laboratory, New Mexico and California; Lawrence Livermore National
Laboratory; Oak Ridge National Laboratory; Savannah River Site
Facility; Argonne National Laboratory; Brookhaven National Laboratory;
and Stanford Linear Accelerator Center. The task force issued its
report in January 2000.
[26] A commissioner can file a charge against an employer or other
respondent on the basis of information obtained by EEOC that indicates
discrimination may have occurred. While charges are in the
investigative stage, the confidentiality provisions of title VII
prohibit EEOC from acknowledging publicly that charges have been filed
against a specific employer. Accordingly, the information regarding the
two commissioner charges was obtained from the laboratories, not EEOC.
[27] Underutilized job groups have fewer minorities and women than
would reasonably be expected by their availability. ’Availability“ is
defined as an estimate for each job group by race/ethnicity and gender
of the population of potential employees for each job group. Los Alamos
has identified specific job groups with long-standing underutilization
as high-priority.
[28] According to an OFCCP official, OFCCP‘s system defines ’no
determination“ as one of four resolutions: (1) resolved by the
contractor prior to investigation, (2) resolved by the contractor
during the experimental Expedited Resolution Procedures, (3) resolved
by the contractor during the investigation, or (4) resolved by another
agency in favor of the complainant.
[29] The laboratories‘ litigation costs related to EEO lawsuits brought
against it by its employees are generally reimbursed by DOE as an
allowable cost under its contract.
[30] See our testimony before the Subcommittee on Government
Efficiency, Financial Management, and Intergovernmental Relations,
House Committee on Government Reform, entitled Managing for Results:
Using GPRA to Assist Oversight and Decisionmaking, GAO-01-872T
(Washington, D.C.: June 19, 2001).
[31] Technically, federal contractors submit EEO-1 forms, otherwise
known as Standard Form 100, to the Joint Reporting Committee, which
consists of EEOC and OFFCP. While EEOC and OFCCP jointly dictate EEO-1
requirements, the responsibility for administering this survey has
historically been held by EEOC. Thus, we will refer to EEOC in the
report rather than the Joint Reporting Committee when we discuss EEO-
1s.
[32] No tests of equivalence were performed for this grouping.
[33] Our data reliability assessment of the personnel, clearance, and
payroll information indicated that the data and data systems were
sufficiently reliable and complete to perform our analyses.
[34] The term ’exempt“ employee refers to exemption from the provisions
of the Fair Labor Standards Act. These employees are classified only in
the officials and managers and professionals categories on the EEO-1s.
There are no nonexempt employees classified as ’official and manager“
or ’professional.“ Although students, limited-terms, and postdocs are
not permanent employees, they are exempt employees and are in positions
that would be classified as professional level positions.
[35] For example, there are two separate tracks for laboratory and
technical staff, each with the job subcategories of director,
supervisor, managerial, distinguished, primary, senior, and general.
[36] Since we are not reporting any coefficients for the salary and
merit pay analyses that are greater than 1 (or 100 percent), the values
reported in the tables and text are appropriately interpreted as a
greater or lesser percentage earned as a result of race/ethnicity and
gender as compared with White men.
[37] For all laboratories, these were personnel actions labeled
’promotion.“
[38] See U.S. General Accounting Office, Senior Executive Service:
Diversity Increased in the Past Decade, [hyperlink,
http://www.gao.gov/cgi-bin/getrpt?GAO-01-377] (Washington, D.C.: Mar.
16, 2001).
[39] The commission is prohibited from making public any information
obtained under title VII of the Civil Rights Act of 1964, as amended,
unless that information has been made part of a legal proceeding under
the act (title VII, sec. 706(b) and 709(e); 42 U.S.C. 2000e-5(b) and
2000e-8(e)). Under EEOC‘s implementing regulations, this prohibition is
applicable to charges filed by employees and information the agency
obtains during an investigation of these charges. (29 C.F.R. 1601.22)
We could not use in our report EEOC information on complaints filed
with it by laboratory staff because we are required to maintain the same
level of confidentiality for this information as does EEOC (31 U.S.C.
716(e)(1)).
[End of section]
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