Women and Work:
A report of the
State Employment and Training Commission's
Council on
Gender Parity in Labor and Education
Prepared by
Dr. Mary
Gatta, Director of Research & Analysis
Center for
Women and Work
Rutgers, The
State University of New Jersey
May 2001
Donald
T. DiFrancesco, Acting Governor
Dianne
Mills McKay, Chair
Council
on Gender Parity in Labor & Education
John J. Heldrich, Chairman
State Employment & Training Commission
Introduction
The New Jersey Council on Gender Parity in
Labor and Education recognizes the underrepresentation of women in science and
technology jobs and educational programs as a workforce issue that inhibits the
full utilization of its potential workforce.
The issues surrounding the exclusion of women from these occupations and
training opportunities are explored in this report and recommendations are
suggested to remedy the situation. This
report and its recommendations were developed as an extension of the New Jersey
State Employment and Training Commission's (SETC) Unified State Plan for New Jersey's Workforce
Readiness System. The Unified
State Plan, first
introduced in 1992 and revised in 1996, is an effort to address the
complexities of creating a unified high-quality workforce investment
system. The Council strongly believes
that this report will aid the State of New Jersey in meeting one of the core
principles of the Unified State Plan: there must be full utilization of all
potential workers.[1]
This report
should be seen as an initial step in recognizing workforce issues. Simply identifying the underrepresentation
of women in science and technology fields is not enough - instead, the Council
believes that strategies must be developed to increase the proportion of women
in these fields. As early as 1985, the
U.S. Office on Technology Assessment found that New Jersey would be facing a
shortage of scientists and engineers.
That Office encouraged recruiting women and minorities into the fields
of science and technology. It was
reasoned that doing so would alleviate the shortage of workers by the
twenty-first century.[2] However, because these recommendations were
not followed, New Jersey is facing the workforce crisis that it was alerted to
over fifteen years ago.
Gender parity
in the educational and workforce training system is an economic necessity for
the U.S. to remain globally competitive.
Indeed, this issue is crucial for New Jersey to attract and maintain the
industries such as information technology, telecommunications, pharmaceuticals,
and biotechnology, which, among other science and high-technology industries,
make up an essential component of the State’s economic base. While increasing the representation of women
in these fields and educational programs is clearly good for women, it is also
good for business and good for the New Jersey economy.
New Jersey's
Economic Future: Projected Job Growth and Skill Needs
As we enter the twenty-first
century, New Jersey’s economic base is shifting from an industrial
goods-producing economy to a knowledge-based economy. Much of this recent transformation has been propelled by the
State’s rapid expansion in the sectors of science and technology. New Jersey’s growth in this area has been so
great that The New York Times has recently dubbed New Jersey
the “Silicon Parkway.” Northern New
Jersey has 3,000 more high-technology firms than Silicon Valley; 30 of the
fastest growing national high-technology companies are in New Jersey; and New
Jersey ranks 5th among states with growing high-technology companies.[3] New Jersey is quickly becoming a national
and global leader in the science and technology sector, creating an
increasingly large number of new jobs to fill each year. However, as New Jersey continues to grow in
this field, the State is facing a potentially devastating labor crisis. Simply put, the labor demand is not being
met by the current labor supply. If
this situation is not addressed, significant labor shortages that will occur
throughout the early part of the twenty-first century will hinder the State’s
economic growth.
New Jersey’s shift to a knowledge-based
economy has drastically reshaped the overall employment picture. New jobs and industries that require
higher-level skills from workers are being created, while old ones are
declining and disappearing. Indeed,
economic success is highly dependent on the talents of the workforce at all
occupational levels in the new economy.
For example, since computers and machines currently perform much of the
needed industrial labor, factory workers are now expected to possess the skills
and leadership to manage the technology as opposed to merely engaging in
physical work. This new relationship
between workers and technology requires that the workforce possess high-level
skills in computers, electronics, life sciences, mathematics, and engineering,
along with various combinations of those skills. In addition, workers need flexible analytical and communication
skills that will enable them to adapt their talents to changing labor market
conditions.
As evidenced from data collected by the
New Jersey Department of Labor, New Jersey's goods-producing industrial sectors
are projected to decline by 2008 (see Figure 1). Manufacturing industries are expected to continue to decline as
they have throughout the 1990s, falling 7.1 percent by 2008. This translates into a loss of 34,100 jobs
in this sector. Within the
manufacturing sector, the apparel and textile industries are projected to
experience the greatest decline, a loss of approximately 31.4 percent or a loss
of 7,600 jobs by 2008. Consistent with
a shift to a knowledge-based economy, employment declines are predicted to be
the greatest in industries that manufacture durable goods.

Figure
1:
Notes:
TCPU
- Transportation, Communications, and Public Utilities
FIRE -
Finance, Insurance and Real Estate
Source: Projections 2008 New Jersey Employment and Population in the 21st Century. Vol. 1 Industry and Occupational Employment Projections for New Jersey 1998-2008. Part A (State Projections, July 2000) NJ Department of Labor Market and Demographic Research.
Alternatively, New Jersey's growth throughout
the first decade of the twenty-first century is expected to occur primarily in
service-producing industries. This
sector includes New Jersey's two largest industries, business services and
health services. Business services
industries are projected to be the fastest growing state industry, creating
135,500 new jobs to fill by 2008. The
expansion of business services is primarily propelled by continued strong
growth in computer and data processing services. Most significantly, this growth reflects the creation and
expansion of information technology occupations. While there are many different ways to define information
technology, the Council chose to adapt a definition used by the Women and Minorities in Information
Technology Forum: Information
technology jobs involve the creation, storage, exchange, and/or use of
information through technological means.
Specific information technology jobs include designing and developing
software and hardware systems, providing technical support for computer
systems, and creating and supporting network systems and databases.[4] As evident from the definition, information
technology jobs are represented in all New Jersey industries, not just
technical specialties. This requires
workers in all industries to possess a general set of technical skills
regardless of occupation.[5]
These
projected industrial shifts, along with the proliferation of technology in all
labor sectors, correspond to changes within New Jersey's occupational
structure. By the year 2008,
professional and technical specialty occupations are projected to experience
the largest employment growth, at least double that of all other occupational
categories. Specifically, from 1998 to
2008, two out of every five new jobs in New Jersey will be in the professional
and technical occupational category (see Figure 2). This will create 193,000 new jobs in New Jersey including
computer scientists, systems analysts, and engineers. Most of the occupations included within this category are high-skilled
jobs in the service producing industries.
In contrast, the occupational categories expected to experience
relatively slow growth are: operators, fabricators, and laborers; and precision
production, crafts, and repairers.
These areas will create only 33,600 and 16,000 new jobs respectively.

Figure
2:
Source: Projections 2008: New Jersey
Employment and Population in the 21st Century, June 2000, NJ
Department of Labor Market and Demographic Research.
Almost half a million new jobs are
projected to be created by 2008, however, the total number of job openings in
New Jersey is expected to be even greater.
This results from the movement of workers out of the labor force (as a
result of retirement, death, permanent disability and/or career change). In New Jersey, on average, 146,660 jobs will
need to be filled each year, with approximately two-thirds of those jobs
resulting from individuals leaving the workforce. In replacement jobs, as in new jobs, the most openings are projected
to occur in the professional and technical occupations, approximately 38,000
jobs each year (see Figure 3).

Figure
3:
Source: Projections 2008: New Jersey
Employment and Population in the 21st Century, June 2000, NJ Department
of Labor Market and Demographic Research.
These occupational categories include
many sets of occupations that represent specific employee skills needs. For example, the top five occupations that
will experience the greatest percentage growth between 1998 and 2008 are in
science, engineering, and technology fields.
In contrast, the occupations that are expected to decline are
concentrated in industrial sectors (see Table 1).
Table 1:
State of New
Jersey Occupations With The Greatest Percentage Change*,
1998-2008
|
|
1998 |
2008 |
Change:
1998-2008 Annual Average Job
Openings |
||||
|
Occupation |
Number |
Number |
Number |
Percent |
Total |
Growth |
Replacements |
|
Computer Support
Specialists |
18,600 |
35,500 |
16,800 |
90.4 |
1,800 |
1,680 |
120 |
|
Systems Analysts |
28,800 |
52,500 |
23,700 |
82.0 |
2,540 |
2,370 |
180 |
|
Computer Engineers |
13,400 |
24,400 |
10,900 |
81.2 |
1,180 |
1,090 |
80 |
|
Medical Assistants |
8,400 |
13,800 |
5,400 |
63.9 |
750 |
540 |
210 |
|
Home Health Aides |
22,000 |
35,900 |
13,700 |
61.8 |
1,680 |
1,370 |
310 |
|
Social/Human
Service Assistants |
7,500 |
11,600 |
4,100 |
54.0 |
600 |
410 |
190 |
|
Teachers &
Instructors, NEC |
5,600 |
8,600 |
3,000 |
53.3 |
360 |
300 |
60 |
|
Dental Assistants |
8,000 |
11,900 |
3,900 |
48.0 |
510 |
390 |
120 |
|
Telmktrs/Door
Sales/Related Wkrs |
24,500 |
34,500 |
9,900 |
40.4 |
1,620 |
990 |
630 |
|
Teachers, Preschool |
9,600 |
13,400 |
3,800 |
39.5 |
590 |
380 |
210 |
|
|
|
|
|
|
|
|
|
|
Sewing Machine
Opers, Garment |
9,700 |
5,700 |
-4,000 |
-41.7 |
130 |
0 |
130 |
|
Word Processors
& Typists |
18,500 |
13,100 |
-5,400 |
-29.4 |
360 |
0 |
360 |
|
Computer Oprs, Ex Peripheral Eq |
7,300 |
5,300 |
-1,900 |
-26.7 |
100 |
0 |
100 |
|
Bank Tellers |
16,200 |
13,000 |
-3,200 |
-19.8 |
690 |
0 |
690 |
|
Switchboard
Operators |
6,800 |
5,500 |
-1,300 |
-18.8 |
150 |
0 |
150 |
|
Electrical/Electronic
Assemblers |
6,100 |
5,300 |
-700 |
-12.4 |
110 |
0 |
110 |
|
Crossing Guards |
5,800 |
5,100 |
-600 |
-10.7 |
170 |
0 |
170 |
|
Insptrs/Tstrs/Grdrs/Smplrs/Wghrs |
12,500 |
11,100 |
-1,300 |
-10.7 |
340 |
0 |
340 |
|
Payroll &
Timekeeping Clerks |
5,800 |
5,300 |
-600 |
-9.5 |
120 |
0 |
120 |
|
Parts Salespersons |
6,100 |
5,600 |
-500 |
-8.2 |
170 |
0 |
170 |
|
|
|
|
|
|
|
|
|
|
Notes: *1998 Employment of
5,000+ |
|
|
|
|
|
|
|
|
Totals may not add
across due to rounding. Employment is
rounded to nearest hundred. Percent
changes based on unrounded data. |
|||||||
|
Job openings are rounded
to the nearest ten. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Source: Projections 2008 New Jersey Employment and
Population in the 21st Century. Vol.
1 Industry and Occupational Employment Projections for New Jersey 1998-2008. Part A (State Projections, July 2000) NJ
Department of Labor Market and Demographic Research. |
|||||||
The occupations with the greatest
percentage increase demand workers with advanced skill levels. As such, this shift in growing jobs
corresponds to a shift in training requirements. Occupations that demand higher levels of education and more
specialized higher-level training requirements are expected to grow at more
than twice the rate of occupations that require lower educational training
needs (see Table 2). In addition, the
industrial factory jobs that will remain in the twenty-first century will
demand more skills and education than previously required. As stated earlier, this reflects the need for
workers to manage technology systems.
For example, nationally, in 1959, only about eight percent of factory
workers had attended college. By 1997,
that figure has grown to 34 percent.
Advanced skills training in technology, science, and process management
is then essential for the New Jersey workforce.[6]
Table
2:
New Jersey Estimated and Projected Employment by Education and Training Requirements, 1998-2008
|
|
1998 |
|
2008 |
|
Change 1998-2008 |
Annual Average New Jobs |
|||
|
Educational and Training Requirements |
Number |
Pct. |
Number |
Pct. |
Number |
Pct. |
Total |
Growth |
Replacements |
|
|
|
|
|
|
|
|
|
|
|
|
Total, All Occupations |
4,004,400 |
100.0 |
4,471,000 |
100.0 |
466,600 |
11.7 |
146,660 |
52,290 |
94,370 |
|
Total High Requirements |
1,029,900 |
25.7 |
1,231,200 |
27.6 |
201,200 |
19.5 |
40,490 |
20,390 |
20,100 |
|
First Professional
Degree |
62,900 |
1.6 |
72,900 |
1.6 |
10,000 |
15.9 |
2,020 |
1,000 |
1,020 |
|
Doctoral Degree |
28,200 |
0.7 |
33,400 |
0.8 |
5,300 |
18.7 |
1,280 |
540 |
750 |
|
Master's Degree |
41,700 |
1.1 |
48,600 |
1.1 |
7,000 |
16.7 |
1,590 |
720 |
870 |
|
Work experience
plus Bachelor's or |
191,000 |
4.8 |
216,100 |
4.9 |
25,000 |
13.1 |
5,900 |
2,550 |
3,350 |
|
Bachelor's Degree |
549,900 |
13.7 |
661,900 |
14.8 |
112,000 |
20.4 |
22,840 |
11,350 |
11,490 |
|
Associate’s Degree |
156,300 |
3.9 |
198,200 |
4.4 |
41,900 |
26.8 |
6,870 |
4,250 |
2,620 |
|
Total Moderate Requirements |
780,900 |
19.4 |
845,800 |
18.9 |
64,900 |
8.3 |
24,460 |
7,380 |
17,070 |
|
Postsecondary
vocational training |
140,400 |
3.5 |
154,100 |
3.5 |
13,800 |
9.8 |
4,660 |
1,490 |
3,160 |
|
Work experience in
a related occupation |
356,800 |
8.9 |
385,700 |
8.6 |
29,000 |
8.1 |
10,620 |
3,280 |
7,350 |
|
Long-term
on-the-job training |
283,700 |
7.0 |
305,900 |
6.8 |
22,200 |
7.8 |
9,180 |
2,610 |
6,570 |
|
Total Low Requirements |
2,193,600 |
54.8 |
2,394,000 |
53.5 |
200,400 |
9.1 |
81,710 |
24,510 |
57,200 |
|
Moderate-term on-the-job
training |
650,300 |
16.2 |
675,800 |
15.1 |
25,600 |
3.9 |
19,100 |
5,550 |
13,550 |
|
Short-term
on-the-job training |
1,543,300 |
38.6 |
1,718,200 |
38.4 |
174,800 |
11.3 |
62,610 |
18,960 |
43,650 |
|
|
|||||||||
|
Notes: |
|||||||||
|
For "Total All
Occupations" the “Average Annual New Jobs” will not equal annualized
"Employment Change" since, for declining occupations, new jobs are
tabulated as zero since no net job growth is projected, while the employment
change is based solely on the difference between 1998 and 2008 employment
totals. Note that occupational data
include estimates of self-employed and unpaid family workers and are not
directly comparable to the industry employment total |
|||||||||
|
Totals may not add
due to rounding. Employment data are
rounded to nearest hundred.
Percentages and percent changes are based on unrounded data. |
|||||||||
|
Source: Projections 2008 New Jersey Employment and
Population in the 21st Century. Vol.
1 Industry and Occupational
Employment Projections for New Jersey
1998-2008. Part A (State Projections,
July 2000) NJ Department of Labor Market and Demographic Research |
|||||||||
As a result of the economic changes,
many experts agree that the labor force shortages that New Jersey employers
faced throughout the 1990s will continue to persist during the first decade of
the new century. These labor force shortages
are inextricably related to the demographic makeup of the New Jersey
workforce. The occupational shift from
an industrial to an information-based economy has not been matched with a
corresponding shift in skills training of the workforce. While this skills-job disparity is most
drastically felt in professional and technical specialty occupations, it is
also characteristic of workers at lower levels of the occupational
structure. As such, employers are finding
it quite difficult to fill their job demands.
A 1998 study conducted by the Council on Competitiveness found that 70
percent of American CEOs state that skill shortages among workers is the
greatest barrier to the growth of their companies. Indeed, this Council identified an "acute skills shortage in
every part of the country that threatens the foundation of American
competitiveness."[7] The workforce does not possess the skills
necessary to keep pace with New Jersey's science and technology growth in all
industrials sectors. Clearly, New
Jersey will continue to experience the transformation from an industrial to an
information economy. However, the
success of this new economy will be predicated on the skills of its workforce. New Jersey's ability to hold on to its
status as a leader in science and technology will be dependent on the ability
to supply and retain educated skilled workers in science and technology.
The Status of
Women in New Jersey's Economy
The changing base of New Jersey's
economy has an impact on labor force participation by women. While New Jersey does not collect data that
allows us to detail the occupational participation of women within the State,
national data sources indicate that women are severely underrepresented in both
science and technology jobs and educational programs. It is widely recognized by labor researchers that the inclusion
of women in this field would have a drastic labor market effect. Peter Freeman and William Asprey, in The Supply of Information Technology Workers
in the United States, state that if the number of women in the information
technology workforce increased to equal the number of men, the huge demand for
labor in these jobs could be met.[8] It is then essential that policymakers
address the status of women in the economy and, specifically, in nontraditional
sectors and training programs, such as science and technology.
While women have made notable inroads
in the workforce and educational training programs, significant barriers for
women continue to persist. Although
women comprise approximately 46 percent of the total American workforce, women
fill only 19 percent of the science, engineering, and technology jobs,[9]
and women hold only 10 percent of the highest level information technology
jobs.[10] However, attracting women to jobs in science
and technology is only part of the problem.
Studies find that women leave these careers twice as frequently as men.[11] As such, addressing issues of retaining
women once they choose science and technology jobs is also needed.
While women have made advances into
nontraditional fields, these advances have not been in the growing fields of
science and technology and, instead, tend to be concentrated in declining
industrial fields. Nationally, women
continue to make up less than 25 percent of the labor force in many detailed
occupations in science and technology (Appendix A). As the table indicates, the nontraditional jobs in which women
have currently made the greatest inroads are in industrial goods production. These jobs are the ones that are projected
to decline in the upcoming decade. For
example, in 1999, women made up at least 20 percent of the workforce in:
precision production occupations; printing machine operators; operators,
fabricators, and laborers; precision inspectors, testers and related workers;
metal and plastic processing machine operators; and non-construction
laborers. However, women made up less
than 20 percent in: drafting occupations; architects; data processing equipment
repairers; electrical and electronic technicians; and surveying mapping
technicians. Furthermore, women made up
ten percent or less in: engineers; electronic, communication and industrial
equipment repairers; and stationary engineers.
These data illustrate that, and there is some irony here, women have
advanced in nontraditional fields precisely at the points when the occupations
are declining.
In addition, while women make up a
growing percentage of college students, they are severely underrepresented in
the academic majors that typically prepare workers with science and technology
skills. For example, in 1999, women
earned only 20 percent of the degrees in engineering and earned less than
one-third of all degrees in computer science and physical sciences in New Jersey. Alternatively, women earned over 75 percent
of all degrees in marketing, education, and library science.
The issue of women's participation in
science and technology jobs and educational training programs is critical for
New Jersey's economic success. Women
are projected to account for two-thirds (or 63 percent) of the State's labor
force growth by 2008 (see Figure 4). It
is further predicted that this trend will continue through 2015.

Source:
Projections 2008: New Jersey Employment and Population in the 21st
Century, Vol. 2, Industry and Occupational Employment Projections for New
Jersey, 1998-2008. Part A (State Projections, July 2000). NJ Department of
Labor Market and Demographic Research.
In addition to increasing their labor
force growth, women are making up a large portion of the State’s college
student population. Trends indicate
that the number of white males entering college will decrease throughout the
early part of this century. As such,
women will continue to make up a significant portion of New Jersey's college
population.[12] It is essential to tap this potential labor
source while still in an educational setting if the State is to succeed in the
science and technology area.
New Jersey Council on
Gender Parity in Labor and Education’s Mini-Conference “Gender Equity and
Technology in the New Jersey Workplace: Setting the Agenda”
Based on the preliminary findings and
discussions among Council members, the New Jersey Council on Gender Parity in
Labor and Education set forth to define the problem of gender inequities in
science, math, and technology. The Council attempted to integrate both the
educational and business aspects of this problem. The Council views these aspects as interrelated to the definition
of the overall problem and proposed recommendations to address it. In doing so, the Council defined eight areas
of inquiry:
1. Gender
Gap: Strategies to motivate girls to take science, math, and technology courses on K-12 level.
2. Bridging the
Gap: Educational policy to ensure gender equity in science, math, and technology programs.
3. Closing the
Gap: College programs to attract and retain women in science, math, and
technology.
4. Gender
Parity Partnerships: Enhancing school-business collaboration
5. Business
Successes: Corporate programs to develop a technologically-trained workforce
6. Business
Strategies: Attracting and retaining women in science, math, and technology
jobs
7. Business
Models: Technological training of certified and non-college educated workforce
8. On Their
Own: Women entrepreneurs
To help
collect information about these areas of inquiry, the Council held a
mini-conference, Gender Equity and
Technology in the New Jersey Workplace: Setting the Agenda, to which it
invited experts in science and technology fields from academia, business, and
government. During intense roundtable
discussions, conference participants brainstormed on issues of gender equity in
relation to each of the topics. Each
roundtable was charged with two main objectives: first, to define the issues
and/or problems in reaching gender equity for its topic; and second, to present
strategies, models, and resources to minimize, remove, or identify gender
barriers for its topic. The first
charge of the roundtable discussion helped the Council outline the issue of
gender equity in science, math, and technology in New Jersey, while the second
charge helped to inform the recommendations that the Council sets forth in this
report. Thus, each roundtable
discussion contributed to the overall framework that the Council used in this
report to define and address gender equity in science, math, and technology.
The following
represents a synopsis of the main problems and/or issues in reaching gender
equity that emerged from each roundtable discussion.
Pre-College Education
Ninety percent of the jobs in which
kindergartners will be working when they reach adulthood do not yet exist.[13] These jobs will require flexible analytical
skills that have a strong foundation in science, math, and technological
studies. It is imperative that all
children receive such skills in order to be adequately prepared to enter into
our workforce. However, girls are being
turned away from science, math, and technology courses at a very early age.
The 1998 report by the American
Association of University Women (AAUW), Gender
Gaps: Where Our Schools Fail Our Children, highlights alarming disparities
between boys’ and girls’ educational attainment in technology, technology
related fields, engineering, and science.
Specifically, girls are less likely to take high level computing classes
in high school and currently comprise only 11 percent of those taking Advanced
Placement computer science exams. Girls
outnumbered boys only in their enrollment in word processing classes, what the
AAUW termed the 1990s version of typing classes.[14]
These gender differences in
educational training are detrimental to girls' preparedness for our
technologically driven labor market.
The AAUW defines being technologically literate as possessing a set of
critical skills, concepts, and problem-solving abilities to apply information
technology in sophisticated and innovative ways. This allows for problem solving across disciplines and subject
areas, and an understanding of the basic principles of computer programming and
science. Using this definition, the
study found that girls usually are not in educational programs where they can acquire
these skills. Further, when they are in
technology classes, they tend to be concentrated in computer “tools” courses -
such as databases, page layout programs, online publishing, and productivity
software. As a result, many girls do
not qualify for the ranks of the technologically literate.
Exclusion from computer literacy
courses is not the only challenge that girls face in the technology area. The report Tech-Savvy: Educating Girls in
the New Computer Age finds that girls face additional barriers to
technology such as masculine cultural stereotypes of the isolated male computer
geek; computer games that are geared toward boys; and teaching methods that
discourage interest in applied computer work.
Perhaps one of the most important findings is the link between
educational socialization and future occupational choices. Tech-Savvy
researchers found that often when "gender equity" in computer
technology appears in school curriculums, many times it translates in practice
into programs in which girls mastered the computer "tools" of
PowerPoint, Email, Internet Search Engines, Word Processing, and
Databases. This has not worked in
girls' favor. These skills are demanded
in many of the low paying, traditionally female jobs in the Sales, Clerical, and
Retail sectors. In contrast, women are
significantly underrepresented in Information Technology jobs, Systems Analyst,
Programming, and Software Design positions-- all of which demand technological
literacy, not simply tool mastery.
Main Reasons for the
Underrepresentation of Girls that were Identified by Mini-Conference
Participants and Current Research
1.
There is a lack of attention to teacher training and
certification in science and technology.
Many teachers have some anxiety about technology and little knowledge
about how to use it. In addition, many
teachers do not possess the technical skills necessary to fully integrate
technology into the classroom, and those that do have difficulty keeping their
knowledge current.[15] Although a great deal of money is allotted
to technology education, a very small percentage of that money addresses
teachers' needs. For instance, during
the 1999-2000 school year, approximately 5.67 billion dollars was spent on
technology nationwide. Of that money,
only 17 percent was spent on teacher training.[16] If teachers do not possess the skills in
technology and science, they cannot encourage them in their students or act as
role models in that respect.
2.
Gender biases, defined as differential treatment based on
gender, occur in many classrooms. Most
commonly studies have found that boys may monopolize computer and science
equipment without intervention by the teacher. For instance, the Scholarly Communication Project found
growing evidence of biases in the classroom.
In this study, researchers observed classroom interactions, and then
interviewed teachers and students on their interpretations of the events. Researchers found that “…during classroom
observations, the boys monopolized the computer tools. In focus groups conducted after the class,
girls complained that boys often rushed to get supplies and made fun of girls
trying to use the equipment. Further,
the teachers allowed the boys to get away with it. Boys would criticize girls, resorting to stereotypes about girls’
lack of skills."[17]
3.
Parents, teachers, and guidance counselors may subtly
discourage girls from science, math, and technology. For instance, each time a teacher defers to a boy in the
classroom to help with the computers or audio-visual materials, a negative
message is sent to the girls in the room.
In addition, socialization patterns continue to direct boys and girls
onto gender appropriate career paths.
4.
Instances of sexual harassment occur in elementary and high
school classrooms. The New Jersey Gender Equity Task Force, a forerunner of the
Council, recognized sexual harassment as a gender barrier in education. In its report, Balancing the Equation: A Report on Gender Equity in Education, the
Task Force found that sexual harassment significantly affects girls’
experiences in all educational programs, but is particularly destructive in the
nontraditional programs, such as science, math, and technology. Sexual harassment contributes to an
environment of intimidation in these classrooms. After incidences of sexual harassment, girls often report that
they will choose not to participate in science, math, and technology classes,
clubs, after school activities, and eventually careers.[18]
5.
Gender harassment, although less publicly recognized, is
quickly becoming a problem in many science, math, and technology classrooms.
This refers to acts of verbal or physical aggression, intimations, and
hostility, based on sex, but not involving sexual activity or language. The most prevalent forms of the harassment
include teasing and bullying.[19] For instance, boys may make fun of girls or
belittle girls’ abilities in nontraditional classrooms. For example, the AAUW found that boys often
refer to girls’ femininity and appearance in computer science classrooms. This has the effect of making girls
uncomfortable in these classrooms and distracts them from their work.[20]
6.
Educational software and video games are geared toward boys.
Most computer games and software packages are designed for men by men. They are geared toward traditionally male
behaviors and activities. Specifically,
these games and software packages are action packed, violent, sports oriented,
and aggressive. The AAUW, in reviewing
popular mathematics educational software used in kindergarten through sixth grade
classrooms, found that only twelve percent of the characters were female or had
female gender identifiable characteristics.[21]
Not only do
women rarely appear in computer games and software, but when they do appear,
they often are portrayed in very stereotypical and unhealthy ways. For instance, female characters tend to play
passive traditional roles, such as the princess who must be saved by the male
hero, as opposed to leadership roles.
In addition, many female characters are physically portrayed in an
unhealthy manner. A recent study of 24
of the top selling video games found that 85 percent of female characters were
portrayed as having large breasts and unusually small waists and/or very thin
bodies. In addition, 38 percent of
female characters appeared in video games with a significant portion of their
body exposed. Most commonly,
researchers found that female video game characters tended to expose their
thighs, stomachs, breasts and/or cleavage.[22] This negative and unhealthy portrayal of women
in video games may contribute to girls’ overall rejection of video games.
7.
Girls face social isolation in science, math, and technology
classrooms. Since many technology and science pursuits are directed to boys, girls
find that when they choose to go against the “norm” and pursue nontraditional
classes, they may feel like an uninvited guest. The AAUW reports that since girls are usually outnumbered in
classes, they are unable to form peer support groups. These groups are essential to success in technology as they often
encourage participation in advanced computer classes. Without a core group of girls in classes, female students are at
risk for feelings of social isolation within the classroom.[23]
8.
There are no core curriculum standards for technology
education in New Jersey.
College
Education
Background
Despite the need for workers with
high-level technological skills, women make up only 15 to 20 percent of
undergraduate computer science majors.[24] These percentages have actually decreased
from the 1980s when women made up approximately 37 percent of computer science
majors.[25] Many experts attribute this decline to a
change in the content of the computer science curriculum during the
decade. Simply put, there was a
movement away from word processing in the 1980s to computer programming and
systems analysis in the 1990s. This
movement shifted women out of the academic major, and men into it. Similarly, there has been a corresponding
decrease in advanced degrees awarded to women from 1980s through the
1990s. In addition, women continue to
earn an even smaller number of science and engineering degrees. The upshot is that women are not majoring
in the academic fields in which there is a large future projected job growth
and increased salary opportunities.
The New Jersey Commission on Higher
Education recently recognized the gender disparity in technology and science
workforce training in their Fifth Annual
Systemwide Accountability Report.
In this report, the Commission found that New Jersey colleges and
universities have not been graduating a sufficient number of students trained
in science and technology to fill the growing job demand. They found that entwined within this
workforce issue was that, while both the labor force and the college population
consist of a growing percentage of women, women are vastly underrepresented
among science and technology degree recipients. As evident from Appendix B,
there were differences in the educational attainment of New Jersey male and
female college students in both degree level and academic major in 1999. In many cases these differences seem to
reflect traditional gender socialization patterns. For example, the major with the highest percentage of women was
Vocational Home Economics (95.2 percent female). In this major, the majority of the degrees were conferred at the
Subbaccalaureate and Associate levels.
Conversely, women received the lowest percentage of degrees in
Engineering Technology (7.7 percent female) and Engineering (19.5 percent
female). In these degree areas,
students earned Bachelors, Masters, and Doctorate degrees, in addition to
Subbaccalaureate and Associate degrees.
These findings demonstrate that,
although there are some exceptions, generally women continue to graduate from
gender-traditional educational programs.
For instance, women earned over 75 percent of the degrees in Marketing,
Education, and Library Sciences, all of which are traditionally associated with
women. In contrast, only about one-third
of all degrees in traditionally male fields (such as Computer Science, Physical
Sciences, and Engineering) were earned by women. These are precisely the majors that are currently being heavily
recruited for in New Jersey workplaces.
In academic fields where there is a
more equitable overall distribution of men and women, there tend to be a
considerably smaller percentage of women who graduate with the highest degree
levels. For example, while women earned
over half the degrees in the Life Sciences, overall they received less than 40
percent of the Doctorate degrees. An
even more noteworthy example is the field of mathematics. In this traditionally male field, women earned
51.9 percent of all the degrees conferred, yet they received only 9.1 percent
of all Doctorate degrees. These very
recent data demonstrate there are persistent gender differences in degrees
awarded both within and between educational majors in New Jersey that continue
to funnel women away from science, math, and technology fields of study.
As indicated in Appendix C, while there
has been some improvement over the past decade, women have typically been
underrepresented in computer science, engineering, engineering technology,
mathematics, physical sciences, and science technologies from 1990 to
1999. In fact, over the ten-year
period, the health sciences was the only science program in which women had
earned an overwhelming majority of the degrees. However, the majority of these degrees were awarded in nursing
and nursing specialties at the Associate, Baccalaureate, and Masters
levels. In contrast, women earned less
than 45 percent of the First Professional degrees in health sciences. These degrees are awarded in Medicine,
Dentistry, and Pharmacy.
Main Reasons for the Underrepresentation
of Women that were Identified by Mini-Conference Participants and Current
Research
1.
The academic environment in some science and technology
programs is not friendly toward women.
Women experience subtle forms of discrimination throughout their
undergraduate and graduate careers such as: programming projects are designed
for male students; a general devaluing of women's contributions by professors,
especially attributing them to male students; hostile attitudes from a few male
students; and classes that overwhelmingly use male language (for instance,
"the user...he", or "suppose your wife"), and gender
stereotyped examples. These cumulative behaviors can have negative effects on
women's academic and career development by influencing their decisions to
switch out of science, math, and technology majors or subspecialties within
majors; minimizing the development of students' relationships with faculty
members; lowering career aspirations and/or undermining women’s confidence.[26]
2.
There is a lack of female mentors in colleges. Since women are underrepresented on science,
math, and technology university faculties, it is difficult for female students
to locate positive mentors. Many female
students leave nontraditional majors because they were not able to form a
mentoring relationship with a faculty member.
This relationship is especially critical at the graduate level, where
faculty mentors share with students information on research funding, avenues
for publication, conferences, networking with other professionals, and
potential opportunities for research collaborations. Such information is essential for success in graduate school and
in helping to secure a professional job.
3.
As a result of the lack of many female role models, many
female college students are unaware of potential career options for women in
nontraditional fields. Role models
serve as evidence that a successful career in science and technology is not
only a possibility but also a viable option for women. For instance, female faculty members prove
by their very existence that obtaining a doctorate degree and a faculty
position are possible. Similarly,
gaining exposure to successful women in science and technology careers outside
of academia increases female students’ knowledge of the opportunities available
to them in science, math, and technology fields.[27] Of course, the largest barrier to female
role models is that women are simply missing from science, math, and technology
faculties and jobs. Women make up a
small proportion of faculty in technical disciplines throughout the country, as
well as in New Jersey. Thus, the
potential pool of role models is quite small.
4.
Women who choose to major in science, math, and technology are
more likely than their male counterparts to switch to a nonscience major.[28] This “leak” in the pipeline is attributed to
such factors as poor quality of teaching; inflexible curriculums; lack of role
models and faculty advice; the competitive nature of science, math, and
technology classrooms; and feelings of isolation.
Business
Women continue to hold a small
proportion of science and technology jobs.
We found that the underrepresentation of women in these fields is
detrimental to both women and employers.
Women who choose non-traditional careers can expect lifetime earnings of
150 percent more than women who choose traditional careers.[29] In addition, corporations also realize that
attracting women to nontraditional careers helps to create a competitive market
advantage. A survey of Fortune 100
human resource executives found that diversity in the workplace brings about
better utilization of talents, creativity, team problem solving, and increased
marketplace and leadership understanding.[30] This sentiment was echoed by William Wulf,
President of the National Academy of Engineering, during a talk in which he
clearly referenced the positive role of women in engineering jobs. As he states, “Every time we approach an
engineering problem with a pale, male design team, we may not find the best
solution. We may not understand the
design options or know how to evaluate the constraints…there is a real economic
cost to that. It is measured in design
options not considered, in needs unsatisfied…It is that a product that serves a
broad…customer base may not be found.”[31]
Main Reasons for the
Underrepresentation of Women that were Identified by Mini-Conference
Participants and Current Research
1.
There is a lack of role models and mentors for women in
science and technology careers. The Catalyst 1998 Census of Women Corporate Officers and Top Earners found that only
eleven percent of all corporate officers were women. Further investigation of corporate officers who held senior
research titles indicated only two women and 38 men.[32] Clearly, women are underrepresented at the
highest levels of industrial management.
The glass ceiling that still operates in corporate jobs not only
prevents women from reaching the top tiers of management but also contributes
to the absence of senior level female role models and mentors. Role models and mentors are vital to women’s
self-image as legitimate members of the profession. Furthermore, workplace mentors and role models serve as a career
link, which helps advance individuals through management careers. However, since women work in predominately
male environments, it can be very difficult for women to find supportive
mentors to help advance them through their careers.
2.
There is a lack of female friendly science and technology worksites.
The research organization, Catalyst’s study Women
Scientists in Industry: A Winning Formula for Companies, among other
studies, reports that women often leave science and technology jobs (and
similarly may not enter them at all) because of the cultural climate of their
workplaces.[33] Many of the science, math, and technology
workplaces do not provide an environment that is “female friendly.” Central to a female friendly environment are
formal and informal practices that promote a feeling among female workers that
they are respected and valued within the company.
3.
Women experience exclusion and marginalization in science
and technology firms. Many women feel that they are left out of the important
decision making meetings and opportunities. They feel that these decisions
occur in very informal and exclusionary settings, such as in hallway
conversations, on the golf course and tennis courts, and in “invitation-only”
meetings.[34] As such women may feel they are not part of
the organization and that their input is unimportant. This mentality of the “old boys club” is a long-standing
tradition in science and technology jobs that has served to minimize women’s
roles in these organizations and justify their exclusion and marginalization.
4. Gender
discrimination continues in pay and resources in science and technology jobs.
Women continue to earn less than do men in comparable jobs. For instance, in 1999, women earned on
average only 85 percent of men’s salaries in the field of information
technology.[35] The gender wage gap contributes to women’s
overall feeling that their work effort is being undervalued. Furthermore, the MIT report, A Study on the Status of Women Faculty in
Science at MIT, found that women have differential access to laboratory
equipment, space, and resources.[36] As women experience fewer labor market
rewards because of their gender, they are more likely to leave these fields in
pursuit of more equitable work environments.
5. There are
problems with integrating family and work responsibilities. Often, women feel that the greatest barriers
to their success in information technology careers are long work weeks (50-60
hours per week), expectations to work late hours, and a high stress job
environment.[37] Fifty-four percent of mothers with infants
under the age of one are in the workforce.
In addition, an estimated 85 percent of women in the workforce will
become pregnant at some point during their tenure. However, pregnancy and infant childcare are not the only family
issues facing women. Women are twice as
likely to stay home with a sick child than are men. Along with childcare responsibilities, many women provide care to
older relatives and parents. It is
estimated that it is women who will bear the burden of providing care for both
their children and aging parents/relatives.[38] Work-family integration not only requires
companies to provide flexible work arrangements, on-site childcare, and
parental leave policies, but also to move away from the cultural belief that
women should be the primary caregivers in the family.
6. Corporations
often do not focus on the employee resource of displaced homemakers and women
returning to the workplace. The report Women
and Minorities in Information Technology Forum found that some information
technology companies are tapping into many nontraditional sources of labor to
fill in the job shortage. Common
sources of workers are individuals who are pursuing second careers or are
reentering the workforce.[39] Often, these employees are enrolled in
distance education and certification courses, employer training, and
self-study. Women make up a large
portion of the workers reentering the labor force. Many times these women are displaced homemakers and possess a
general skill set that can be cultivated for a career in science, math, and
technology. This creates a potential
pool of workers that needs to be recognized. However, much of the challenge
surrounding the reentry of women into the science, math, and technology
workforce involves changing women’s perceptions of technology itself. For example, researchers find that since
women are overrepresented in clerical jobs, they do not have the opportunity to
understand the real potential of computers.
Instead, for some displaced homemakers the computer is simply the next
generation typewriter.[40]
Conclusion
The Council on
Gender Parity’s mini conference, Gender
Equity and Technology in the New Jersey Workplace: Setting the Agenda, and
this report were undertaken to identify and highlight issues relevant to gender
parity in New Jersey. The issues raised
indicate that there are specific problem areas in linking women with
educational and occupational opportunities in the growing fields of science and
technology.
To that
purpose the Council will be issuing a follow up report in the next few months
which will chronicle best practices in education and industry, and will put
forth recommendations to address the issues and barriers that women face in
science and technology. This report
will emerge from the Council’s second conference, A Women’s Place: Her Role in the New Economy.
Unless we address issues of gender inequity within our Science, Engineering and Technology labor force, we will not be able to compete globally. Women are expected to make up over half the workforce by 2020. If we do not address these issues now, when will we?
[1] New Jersey
State Employment and Training Commission. 1992. A Unified State Plan for
New Jersey’s Workforce Readiness System.
[2] Office of
Technology Assessment. 1985. Demographic Trends
and the Scientific and Engineering Workforce. Washington D.C.
[3] “Call it Silicon Parkway: Despite Problems, New Jersey’s Place in the World of High-Tech is Secure.” November 11, 2000. The New York Times.
[4] Sandy, M. and Burger, C. 1999. Women and Minorities in Information Technology Forum: Causes and Solutions for Increasing the Numbers in the Information Technology Pipeline (The White Pages Report) NSF: Virginia.
[5] Carnevale, A. and Fry, R. 2000. Crossing the Great Divide: Can we Achieve Equity When Generation Y Goes to College? New Jersey: Educational Testing Service.
[6] Carnevale, A. and Fry, R. 2000. Crossing the Great Divide: Can we Achieve Equity When Generation Y Goes to College? New Jersey: Educational Testing Service.
[7] Council on Competitiveness.
1998. Winning the Skills Race.
Washington D.C.: Council on Competitiveness.
[8] Freeman, P.
and Aspray, W. 1999. The Supply of
Information Technology Workers in the United States. Computing Research
Association: Washington, DC.
[9] Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development. 2000. Land of Plenty: Diversity as America’s Competitive Edge in Science, Engineering and Technology. Washington, D.C.: National Science Foundation.
[10] Sandy, M. and
Burger, C. 1999. Women and Minorities in
Information Technology Forum: Causes and Solutions for Increasing the Numbers
in the Information Technology Pipeline (The White Pages Report) NSF:
Virginia.
[11] Advocates for Women in Science, Engineering and Math. 1997. “Gender Equity and Mentorship in Science, Engineering and Mathematics”. http://www.awsem.com.
[12] Carnevale, A. and Fry, R. 2000. Crossing the Great Divide: Can we Achieve Equity When Generation Y Goes to College? New Jersey: Educational Testing Service.
[13] “The Facts
About Women and Work”
[14] American
Association of University Women. 1998. Gender
Gaps: Where Schools Still Fail Our Children. Washington, D.C.: AAUW
Educational Foundation.
[15] Freeman, P. and Aspray, W. 1999. The Supply of Information Technology Workers in the United States. Computing Research Association: Washington, DC.
[16] “More
Technology Training for Teachers.” November 22, 2000. The New York Times.
[17] Hitchcock, Corey. 1998. “Testing 1,2, 3; Technology to Girls: Hello?” http://www.sfgate.com/.
[18] New Jersey
State Employment and Training Commission’s Gender Equity Task Force. 1997. Balancing the Equation: A Report on Gender
Equity in Education.
[19] Stein, Nancy.
1999. Classrooms and Courtrooms: Facing
Sexual Harassment in K-12 Schools. New York: Teachers College Press.
[20] American
Association of University Women. 2000.
Tech-Savvy: Educating Girls in the New Computer Age. Washington, D.C.: AAUW Educational Foundation.
[21] American Association of University Women. 2000. Tech-Savvy: Educating Girls in the New Computer Age. Washington, D.C.: AAUW Educational Foundation.
[22] Children Now.
2000. Girls and Gaming: A Console Video
Game Content Analysis. Oakland CA: Children Now.
[23] American Association of University Women. 2000. Tech-Savvy: Educating Girls in the New Computer Age. Washington, D.C.: AAUW Educational Foundation.
[24] Margolis, J.,
Fisher, A., and Miller, F. Caring About
Connections: Gender and Computing.
http://www.cs.cmu.edu.
[25] Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development. 2000. Land of Plenty: Diversity as America’s Competitive Edge in Science, Engineering and Technology. Washington, D.C.: National Science Foundation.
[26] Pearl, A. Riskin, M. Thomas, B. Wolf, E. and Wu. 1990. A. “Becoming a Computer Scientist: A report by the ACM Committee on the Status of Women in Computing.” Communications of the ACM, 33:47-58.
[27] Pearl, A. Riskin, M. Thomas, B. Wolf, E. and Wu. 1990. A. “Becoming a Computer Scientist: A report by the ACM Committee on the Status of Women in Computing.” Communications of the ACM, 33:47-58
[28] Commission on the Advancement of Women and Minorities in Science, Engineering and Technology Development. 2000. Land of Plenty: Diversity as America’s Competitive Edge in Science, Engineering and Technology. Washington, D.C.: National Science Foundation.
[29] “The Facts About Women and Work” http://www.academic.org/work.html.
[30] Commission on
the Advancement of Women and Minorities in Science, Engineering and Technology
Development. 2000. Land of Plenty:
Diversity as America’s Competitive Edge in Science, Engineering and Technology.
Washington, D.C.: National Science Foundation.
[31] Wulf, W. 1998. “Diversity in Engineering”. The Bridge. 28:1-11.
[32] Catalyst. 1998. Census of Women Corporate Officers and Top Earners. Catalyst: NY.
[33] Catalyst.
1999. Women Scientists in Industry: A
Winning Formula for Companies. Catalyst: NY.
[34] Women in Technology International. 1997. Business Impact by Women in Science and Technology. WITI.
[35]American Association of University Women. 2000. Tech-Savvy: Educating Girls in the New Computer Age. Washington, D.C.: AAUW Educational Foundation.
[36] Committees on
Women Faculty. 1999. A Study on the
Status of Women Faculty in Science at MIT. MIT: Massachusetts.
[37] Sandy, M. and Burger, C. 1999. Women and Minorities in Information Technology Forum: Causes and Solutions for Increasing the Numbers in the Information Technology Pipeline (The White Pages Report) NSF: Virginia.
[38] New York State Alliance for Girls and Women in Technology. 1995. Girls and Women in Technology: A call to action: Preparing girls and women for a technological workforce. NYS Alliance for Girls and Women in Technology: New York.
[39] Sandy, M. and Burger, C. 1999. Women and Minorities in Information Technology Forum: Causes and Solutions for Increasing the Numbers in the Information Technology Pipeline (The White Pages Report) NSF: Virginia.
[40] Corely, R. 1994.
“Women, Technology and the Internet: How Will the Three Get Along?” Working
Papers in Communication Technology and Culture.
http//www.carleton.ca/~jweston/papers.corley.94