The 2016 Policy Report on
Balanced Development of
Human Resources for the
FutureAnalysis of Global Gender Indices and Joint Survey Results from INWES APNN
Member Countries
Kong-Ju-Bock Lee (Department of Physics, Ewha Womans University)
Jung Sun Kim (Division of Health Sciences, Dongseo University)
Yanghee Kim (Director, Gender & Leadership)

Foreword
Launched in 2014, this policy study started as part of the International
Cooperation Policy Project of the Association of Korean Woman Scientists & Engineers(KWSE). While its rapid transition to an aging society and low birth rate have been
identified as factors hindering national competitiveness, Korea is still poorly ranked
among OECD member countries in terms of participation by highly educated women in
economic activity. As a more efficient approach to the balanced development of humanresources for the future, an utmost priority of Korea is to maximize the utilization ofhighly educated women. Considering how national competitiveness is proportionate tocompetitiveness in science and technology, this study focuses on fully utilizing highly
educated female scientists and engineers.
Similar to the first study, this study examined quantitative indices published annuallyby the Organization for Economic Cooperation and Development (OECD), the World
Economic Forum (WEF) and the United Nations Development Program (UNDP), andexamined changes over the past two years. The analysis of international human resources
development indices covered the 13 member countries (Nepal, New Zealand, Malaysia,
Mongolia, Bangladesh, Vietnam, Sri Lanka, India, Japan, Taiwan, Pakistan, Korea andAustralia) of the Asia and Pacific Nations Network (APNN) under the International Networkof Women Engineers and Scientists (INWES), in which KWSE is playing a leading role.
Several interpretations may exist depending on the definitions of international indices, but thisstudy is meaningful in that it allows a rough comparison of the status of human resources
development around the world. In addition, the analysis of indices from the perspective ofgender holds significance in contributing to the development of balanced human resources
policies.
A large part of this report is dedicated to the results of the 2016 joint survey on thegender barriers in the fields of science and technology involving 1,379 female scientists andengineers from 13 member countries of the APNN, in continuance to the 2014 joint survey on
gender equality in the fields of science and technology and the 2015 survey on the glass ceilingas perceived by female scientists and engineers. This gender barriers survey is comprised ofvarious questions including the perception of discriminatory, discriminatory experiences, theconcept of gender role ideology, career prospects, policy demands and the concept of genderequality. To facilitate more extensive and efficient utilization, the results are presented by eachmember country.
The greatest significance of this study is that the international joint survey of
APNN member countries is now in its third consecutive year. As mentioned in theforeword of the 2014 report, we hope that this report will lay a foundation to create an
Asian equivalent to She Figures (a collection of statistics for policies targeting genderresearch innovation published by the EU every three years since 2003), and serve as a
useful reference in policy development for the balanced utilization of highly educated andtalented female science and engineering professionals in the Asia-Pacific region,
including Korea.
November 3, 2016
Kong-Ju-Bock Lee, Ph.D.
Department of Physics, Ewha Womans University3

Acknowledgements
This report was made possible by the invaluable support of many people. We would liketo take this opportunity to extend our sincere gratitude to everyone who participated inthis policy study, provided data, analyzed statistical data from the survey and provided
financial support. Our special thanks go to the survey participants, as well as to theinternational joint survey team who carried out the survey.
Resources and Advice:
Byung-Joo Min (Member of the 19th National Assembly of the Republic of Korea)
Kong-Joo Lee (President, INWES)
Haryoung Poo (President, KWSE)
Mi-jin Bang (Former Team Leader, Seoul Creative Economy Innovation Center)
Financial Support:
National Research Foundation of Korea
Ministry of Science, ICT and Future Planning
Survey and Statistical Analysis:Hyun-kyung Oh (Researcher, Korean Women’s Development Institute)
Sunha Myung, Hyon Jung Jang (KWSE Secretariat)
International Joint Survey Team:
Affiliation
APNN Representative1)
Engineers-Australia
Marlene Kanga
IEM
Ir. Leong Wai Yie
IPENZ
Tracey Ayre
JNWES
Kayoko Sugahara
KWSE
Jung Sun Kim
TWiST
Shun-Lien Sung
VAFIW
Nguyen Thi Mai Lan
WESTIP
Durdana Habib
WISE-Bangladesh
Siddika Sultana
WISE-India
Dillip Pattanaik
WISE-Nepal
Jun Hada
WISE-Sri Lanka
Nethra Tantrigoda
WSTEM
Ariunbolor PurveeCountry
Australia
Malaysia
New Zealand
Japan
Korea
TaiwanVietnam
Pakistan
Bangladesh
India
Nepal
Sri Lanka
Mongolia

1) A representative to APNN or the person who carried out the survey.
Established in 2011, APNN is a network of countries in the Asia-Pacific region under the INWES. APNN currently
has 13 member countries, including INWES’s Asian members, and Australia and New Zealand. APNN hosts anannual meeting, which took place in Australia in 2011, in Malaysia in 2012, in Taiwan in 2013, in Korea in 2014,
in Mongolia in 2015, followed by the latest meeting in New Zealand in 2016. The first chair organization was
KWSE of Korea; JNWES was elected the second chair organization from 2014. It has been confirmed that the2017 APNN meeting will take place in Yokohama, Japan.

4Summary of International Indices for Human Resources
Development and Joint Survey Results by APNN Member
Country1)International Indices on Human Resource Development by APNN Member
Country(HDI=1: most developed, GDI=1: complete equality, GII=0: complete equality, GGI=1: complete equality)
UNDP HDIUNDP GDI

UNDP GIIWEF GGI

2014
from 188 countries

2014
from 188 countries

2014
from 155 countries

2015
from 145 countries

Rank

Value

Rank

Value

Rank

Value

Rank

Value

Nepal

145

0.548

114

0.908

108

0.489

110

0.658

New Zealand

9

0.913

68

0.961

32

0.157

10

0.782

Malaysia

62

0.779

90

0.947

42

0.209

111

0.655

Mongolia

90

0.727

49

1.028

63

0.325

56

0.709

Bangladesh*

142

0.570

109

0.917

111

0.503

64

0.704

Vietnam

116

0.666

-

-

60

0.308

83

0.687

Sri Lanka

73

0.757

85

0.948

72

0.370

84

0.686

India

130

0.609

151

0.795

130

0.563

108

0.664

Japan

20

0.891

66

0.961

26

0.133

101

0.670

Taiwan**

(25)

0.882

-

-

(5)

0.052

(79)

0.690

Pakistan

147

0.538

160

0.726

121

0.536

144

0.559

Korea

17

0.898

104

0.930

23

0.125

115

0.651

Australia

2

0.935

42

0.976

19

0.110

36

0.733

Country* Bangladesh has been an INWES APNN member country since 2015** Taiwan’s data were determined by the Taiwanese government based on the UNDP and WEF
methodology (source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(Source: UNDP, Human Development Report 2015, WEF Global Gender Gap Report 2015)52) Survey on Gender barriers Among APNN Member Countries : Overall Average(unit: points)①

Classifications
1②

2

Perception of3
discrimination
4

5
6③
Gender Experience ofbarriers discrimination 7
8

Item

AverageStandard
deviation

2.46

1.219

2.51

1.180

2.50

1.235

2.93

1.318

Boys are encouraged more than girls to go into the
STEM field.
It is more difficult for a woman to get a job in the STEM
field than for a man even with the same qualifications.
Becoming a tenured professor, being promoted or
becoming a principal investigator is more difficult for
Women in STEM generally receive less pay for equal
work, compared with their equally-qualified maleSub-scales
I have experienced disadvantages in leading or
participating in research projects because I am a woman.
I have experienced disadvantages in receiving researchfunds or scholarships because I am a woman.
I have experienced sexual harassment or unfair
treatments sometime in my career.
Balancing work and life (marriage and family) has been ahandicap for me.

Sub-scales
Primary breadwinners (who take care of financial
9
obligations) of households should be men.
Women are born to have a way of caring children that10④
men are not capable of in the same way.
Gender role
In order to maintain the order and peace of a family, the11husband should have greater power and authority than thestereotypes
In a relative sense, men are rational while women are
12
emotional and thus, they ought to complement each otherSub-scales⑤ Career outlook

13 I believe things will turn out fine in my future career.

⑥ Policy needs

14⑦ Equality concept

It is crucial to have strong policy support to solve genderinequality in the STEM field.
I believe gender equality will be fully achieved only if
15
women are given equal opportunities as men.

2.60
3.00

1.272

3.32

1.221

3.30

1.356

2.60

1.217

3.05
3.55

1.343

3.34

1.347

3.78

1.327

2.92

1.387

3.40
3.70

1.044

4.07

1.070

2.13

1.149

note: ① The responses to questions were measured with a five-point Likert scale (1.Strongly agree,
2.Somewhat agree, 3.Neutral, 4. Somewhat disagree, 5. Strongly disagree)② Perception of discrimination: Lower score means higher perception of discrimination④ Experience of discrimination: Lower score means more discrimination experienced⑤ Gender role ideologies: Higher score means more progressive⑥ Career outlook: Higher score means a more positive outlook

63) Survey on Gender barriers Among APNN Member Countries: Average by
Nation and by indicators(unit: points)

Perception of
GenderClassifications discriminatory Discriminatorolery experience
realityideology

Careerprospects

PolicydemandGenderequality

Nepal

2.51

3.26

4.14

3.83

4.55

1.56

New Zealand

2.51

2.99

4.28

3.68

4.25

1.78

Malaysia

3.20

3.43

3.15

3.62

3.69

2.25

Mongolia

2.21

2.89

2.81

3.99

4.26

2.06

Vietnam

3.19

2.44

3.07

3.37

4.77

1.85

Sri Lanka

3.37

3.61

3.47

4.11

4.09

2.37

India

1.13

2.27

4.68

3.55

4.30

1.01

Japan

2.84

2.91

3.22

2.96

3.15

3.26

Taiwan

2.65

3.19

3.87

3.78

3.87

2.24

Pakistan

2.64

3.31

2.40

4.02

4.07

1.71

Korea

2.24

2.99

3.61

3.39

4.19

3.12

Pakistan

2.29

3.18

3.06

4.37

4.23

1.41

Other

2.92

3.15

3.65

3.63

3.91

1.88

Average

2.60

3.05

3.40

3.70

4.07

2.13

F

57.32122.78455.032

16.58819.73449.809P***(p<.001)

***

***

***

***

***

***

7

Contents
Foreword ............................................................................................................................3
Acknowledgements ...........................................................................................................4
Summary of International Indices for Human Resources Development and Joint Survey
Results by APNN Member Country ................................................................................5
1. Introduction .................................................................................................................23
2. Current Status of Human Resources Development by Nation ....................................27
2.1 Cross-country comparison based on HDI by UNDP ............................................27
2.1.1 HDI composition and cross-country comparison .......................................27
2.1.2 Cross-country comparison based on the GDI and the HDI by gender ......30
2.2 Cross-country comparison based on GII of UNDP ..............................................32
2.2.1 Composition of the GII ...............................................................................32
2.2.2 Comparison of GII among OECD member countries ................................33
2.2.3 Comparison of the GII among APNN member countries .........................34
2.2.4 Recent changes in Korea’s GII ...................................................................35
2.3 Cross-country comparison of the GGI of the WEF ..............................................38
2.3.1 Composition of the GGI and data source....................................................38
2.3.2 Recent changes in sub-indices of the GGI ..................................................39
2.3.3 Comparison of the GGI among OECD member countries .........................40
2.3.4 Comparison of the GGI among APNN member countries .........................422.3.5 Recent changes in Korea’s GGI..................................................................43
2.4 Cross-country comparison of labor force participation rates of the OECD .........46
2.4.1 Male and female labor force participation rates among OECD member countries........46
2.4.2 Korea’s labor force participation rate by highly educated women .............49
2.5 Cross-country comparison based on the overview of female scientists by UNESCO................................................................................................................................52
3. Survey of APNN Member Countries on Gender Barrier ............................................57
3.1 Discussions of gender barriers ..............................................................................57
3.1.1 Gender role ideology ..................................................................................57
3.1.2 Unfairness in employment, wages and promotion (glass ceiling) ..............58
3.1.3 Work-life balance and career break ............................................................598

3.1.4 Other unfair treatment .................................................................................61
3.2 Survey method ......................................................................................................62
3.2.1 Survey respondents, method and period .....................................................62
3.2.2 Survey tool: Questionnaire composition.....................................................62
3.2.3 Analysis of survey data ...............................................................................63
4. Results of the Survey on Gender barriers Among APNN Member Countries ..........67
4.1 General respondent profiles ..................................................................................67
4.2 Cross-country comparison of the gender barriers in 12 APNN member countries............................................................................................................................70
4.2.1 Descriptive statistical analysis ....................................................................70
4.2.2 Cross-country comparison ..........................................................................73
4.2.3 Analysis by item .........................................................................................81
4.3 Results of comprehensive analysis ...................................................................114
4.3.1 Correlational analysis .............................................................................114
4.3.2 Multiple regression analysis .....................................................................116
4.4 Analysis of survey results by participating nation ............................................118
4.4.1 Nepal .........................................................................................................118
4.4.2 New Zealand .............................................................................................130
4.4.3 Malaysia ....................................................................................................143
4.4.4 Mongolia ...................................................................................................157
4.4.5 Vietnam .....................................................................................................169
4.4.6 Sri Lanka ...................................................................................................183
4.4.7 India ..........................................................................................................198
4.4.8 Japan .........................................................................................................211
4.4.9 Taiwan ......................................................................................................224
4.4.10 Pakistan ...................................................................................................237
4.4.11 Republic of Korea ...................................................................................250
4.4.12 Bangladesh ..............................................................................................264
5. Conclusion and Suggestions ......................................................................................281
References .....................................................................................................................285

9

Table of Contents
Table 2-1 The components of HDI ..................................................................................27
Table 2-2 HDI and its components by country (2014) ....................................................28
Table 2-3 GDI ranks and female/male HDI scores by country (2014) ............................29
Table 2-4 The HDI and GDI of APNN member countries in 2013 and 2014 .................30
Table 2-5 The components of GII ....................................................................................32
Table 2-6 GII status of OECD member countries (2014) ................................................33
Table 2-7 GII values of APNN member countries in (2014) ...........................................34
Table 2-8 the GII of APNN member countries in 2013 and 2014 ...................................35
Table 2-9 GII values of Korea from 2008 to 2014 ..........................................................36
Table 2-10 International indices on Human Resource Development by APNN Member
Countries (2014)............................................................................................36
Table 2-11 Structure of the GGI ......................................................................................38
Table 2-12 GGI ranks and values of OECD member countries (2015)...........................41
Table 2-13 GGI ranks and values of APNN member countries (2015) ...........................42
Table 2-14 The GGI of APNN member countries in 2014 and 2015 ..............................43
Table 2-15 GGI evolution of Korea by indicators for past decade (2006~2015) ............43
Table 2-16 GGI status of Korea (2011~2015) .................................................................45
Table 2-17 OECD Female & male labor force participation rate of OECD members(2013~2015) .................................................................................................47
Table 2-18 Labor force participation rate of highly educated* female and male of OECDmembers (2011~2013) ..................................................................................48
Table 2-19 Labor force participation rate of Korean by sex, field of specialty, and marital
status (2014)...................................................................................................49
Table 2-20 Labor force participation rate of the science and engineering population of
Korea by age group (2014) ...........................................................................50
Table 2-21 UIS ratio of female researcher by region (2013) ...........................................53
Table 2-22 Female researcher ratio of APNN member countries ....................................53
10

Table 3-1 Survey questions..............................................................................................64
Table 4-1 Participants of the survey ................................................................................68
Table 4-2 Average on each item.......................................................................................70
Table 4-3 Respondents profile by nation .........................................................................74
Table 4-4 Comparison of average scores of participating nations by scales ...................77
Table 4-5 Boys are encouraged more than girls to go into the STEM field: Total ..........82
Table 4-6 It is more difficult for a woman to get a job in the STEM field than for a maneven with the same qualifications: Total .........................................................84
Table 4-7 Becoming a tenured professor, being promoted or becoming a principal
investigator is more difficult for female scientists than for male scientists:
Total ...............................................................................................................86
Table 4-8 Women in STEM generally receive less pay for equal work, compared with
their equally-qualified male colleagues: Total ................................................88
Table 4-9 I have experienced disadvantages in leading or participating in research projects
because I am a woman: Total...........................................................................90
Table 4-10 I have experienced disadvantages in receiving research funds or scholarships
because I am a woman: Total.........................................................................92
Table 4-11 I have experienced sexual harassment or unfair treatments sometime in mycareer: Total ...................................................................................................95
Table 4-12 Balancing work and life has been a handicap for me: Total ..........................97
Table 4-13 Primary breadwinners of households should be men: Total ..........................99
Table 4-14 Women are born to have a way of caring children that men are not capable ofin the same way: Total .................................................................................101
Table 4-15 In order to maintain the order and peace of a family, the husband should havegreater power and authority than the wife: Total .........................................103
Table 4-16 Men are rational while women are emotional and they ought to complement
each other: Total ..........................................................................................105
Table 4-17 I believe things will turn out fine in my future career: Total .......................107
Table 4-18 It is crucial to have strong policy support to solve gender inequality in the
STEM field: Total ........................................................................................109
Table 4-19 I believe gender equality will be fully achieved only if women are given equal
11opportunities as men: Total ......................................................................... 112
Table 4-20 Correlations Matrix ..................................................................................... 114
Table 4-21 Stepwise multiple regression analysis in Career outlook ............................ 116
Table 4-22 Stepwise multiple regression analysis in Policy needs................................ 117
Table 4-23 Profile of participants from Nepal ............................................................... 118
Table 4-24 Gap between Nepal & others on gender barriers ........................................ 119
Table 4-25 Perception of discrimination of Nepal: Demographic differences ..............122
Table 4-26 Experience of discrimination of Nepal: Demographic differences .............124
Table 4-27 Gender role stereotypes of Nepal: Demographic differences ......................125
Table 4-28 Career outlook of Nepal: Demographic differences ....................................127
Table 4-29 Policy needs of Nepal: Demographic differences .......................................128
Table 4-30 Equality concept of Nepal: Demographic differences.................................130
Table 4-31 Profile of participants from New Zealand ...................................................131
Table 4-32 Gap between New Zealand & others on gender barriers .............................133
Table 4-33 Perception of discrimination of New Zealand: Demographic differences ..135
Table 4-34 Experience of discrimination of New Zealand: Demographic differences .137
Table 4-35 Gender role stereotypes of New Zealand: Demographic differences ..........138
Table 4-36 Career outlook of New Zealand: Demographic differences ........................140
Table 4-37 Policy needs of New Zealand: Demographic differences ...........................141
Table 4-38 Equality concept of New Zealand: Demographic differences .....................143
Table 4-39 Profile of participants from Malaysia ..........................................................144
Table 4-40 Gap between Malaysia & others on gender barriers ...................................147
Table 4-41 Perception of discrimination of Malaysia: Demographic differences .........148
Table 4-42 Experience of discrimination of Malaysia: Demographic differences ........150
Table 4-43 Gender role stereotypes of Malaysia: Demographic differences.................152
Table 4-44 Career outlook of Malaysia: Demographic differences...............................153
Table 4-45 Policy needs of Malaysia: Demographic differences ..................................155

12

Table 4-46 Equality concept of Malaysia: Demographic differences ...........................156
Table 4-47 Profile of participants from Mongolia .........................................................158
Table 4-48 Gap between Mongolia & others on gender barriers...................................160
Table 4-49 Perception of discrimination of Mongolia: Demographic differences ........162
Table 4-50 Experience of discrimination of Mongolia: Demographic differences .......163
Table 4-51 Gender role stereotypes of Mongolia: Demographic differences ................165
Table 4-52 Career outlook of Mongolia: Demographic differences ..............................166
Table 4-53 Policy needs of Mongolia: Demographic differences .................................167
Table 4-54 Equality concept of Mongolia: Demographic differences...........................169
Table 4-55 Profile of participants from Vietnam ...........................................................170
Table 4-56 Gap between Vietnam & others on gender barriers .....................................173
Table 4-57 Perception of discrimination of Vietnam: Demographic differences ..........175
Table 4-58 Experience of discrimination of Vietnam: Demographic differences .........176
Table 4-59 Gender role stereotypes of Vietnam : Demographic differences .................178
Table 4-60 Career outlook of Vietnam: Demographic differences ................................180
Table 4-61 Policy needs of Vietnam: Demographic differences ...................................181
Table 4-62 Equality concept of Vietnam: Demographic differences .............................182
Table 4-63 Profile of participants from Sri Lanka .........................................................184
Table 4-64 Gap between Sri Lanka & others on gender barriers ..................................186
Table 4-65 Perception of discrimination of Sri Lanka: Demographic differences ........189
Table 4-66 Experience of discrimination of Sri Lanka: Demographic differences .......190
Table 4-67 Gender role stereotypes of Sri Lanka: Demographic differences ...............192
Table 4-68 Career outlook of Sri Lanka: Demographic differences..............................193
Table 4-69 Policy needs of Sri Lanka: Demographic differences .................................195
Table 4-70 Equality concept of Sri Lanka: Demographic differences ..........................197
Table 4-71 Profile of participants from India ................................................................198
Table 4-72 Gap between India & others on gender barriers ..........................................201

13

Table 4-73 Perception of discrimination of India: Demographic differences I .............203
Table 4-74 Experience of discrimination of India: Demographic differences ..............205
Table 4-75 Gender role stereotypes of India: Demographic differences .......................206
Table 4-76 Career outlook of India: Demographic differences .....................................207
Table 4-77 Policy needs of India: Demographic differences.........................................209
Table 4-78 Equality concept of India: Demographic differences .................................. 211
Table 4-79 Profile of participants from Japan ...............................................................212
Table 4-80 Gap between Japan & others on gender barriers .........................................213
Table 4-81 Perception of discrimination of Japan: Demographic differences ..............216
Table 4-82 Experience of discrimination of Japan: Demographic differences..............217
Table 4-83 Gender role stereotypes of Japan: Demographic differences ......................219
Table 4-84 Career outlook of Japan: Demographic differences ....................................220
Table 4-85 Policy needs of Japan: Demographic differences ........................................222
Table 4-86 Equality concept of Japan: Demographic differences .................................223
Table 4-87 Profile of participants from Taiwan .............................................................225
Table 4-88 Gap between Taiwan & others on gender barriers ......................................227
Table 4-89 Perception of discrimination of Taiwan: Demographic differences ............229
Table 4-90 Experience of discrimination of Taiwan: Demographic differences ...........230
Table 4-91 Gender role stereotypes of Taiwan: Demographic differences....................232
Table 4-92 Career outlook of Taiwan: Demographic differences ..................................233
Table 4-93 Policy needs of Taiwan: Demographic differences .....................................235
Table 4-94 Equality concept of Taiwan: Demographic differences ..............................236
Table 4-95 Profile of participants from Pakistan ...........................................................238
Table 4-96 Gap between Pakistan & others on gender barriers.....................................240
Table 4-97 Perception of discrimination of Pakistan: Demographic differences ..........242
Table 4-98 Experience of discrimination of Pakistan: Demographic differences .......243
Table 4-99 Gender role stereotypes of Pakistan: Demographic differences ..................245

14

Table 4-100 Career outlook of Pakistan: Demographic differences ..............................246
Table 4-101 Policy needs of Pakistan: Demographic differences .................................248
Table 4-102 Equality concept of Pakistan: Demographic differences ...........................249
Table 4-103 Profile of participants from Republic of Korea .........................................251
Table 4-104 Gap between Republic of Korea & others on gender barriers...................253
Table 4-105 Perception of discrimination of Republic of Korea: Demographic differences...................................................................................................................255
Table 4-106 Experience of discrimination of Republic of Korea: Demographic differences...................................................................................................................257
Table 4-107 Gender role stereotypes of Republic of Korea: Demographic differences 259
Table 4-108 Career outlook of Republic of Korea: Demographic differences ..............260
Table 4-109 Policy needs of Republic of Korea: Demographic differences .................262
Table 4-110 Equality concept of Republic of Korea: Demographic differences ...........263
Table 4-111 Profile of participants from Bangladesh ....................................................265
Table 4-112 Gap between Bangladesh & others on gender barriers..............................266
Table 4-113 Perception of discrimination of Bangladesh: Demographic differences ...269
Table 4-114 Experience of discrimination of Bangladesh: Demographic differences ..270
Table 4-115 Gender role stereotypes of Bangladesh: Demographic differences ...........272
Table 4-116 Career outlook of Bangladesh: Demographic differences .........................273
Table 4-117 Policy needs of Bangladesh: Demographic differences ............................275
Table 4-118 Equality concept of Bangladesh: Demographic differences ......................276

List of Figures
Figure 2-1 The World Average of GGI by Indicators (2015) ..........................................39
Figure 2-2 GGI evolution 2006~2015 .............................................................................40
Figure 2-3 Ratio of women researchers by region (2013) ...............................................52
Figure 4-1 Average on each item .....................................................................................72
15

Figure 4-2 Perception of discrimination by nation ..........................................................78
Figure 4-3 Experience of discrimination by nation .........................................................78
Figure 4-4 Gender role stereotype s by nation ................................................................79
Figure 4-5 Career outlook by nation................................................................................79
Figure 4-6 Policy needs by nation ...................................................................................80
Figure 4-7 Equality concept by nation ..........................................................................80
Figure 4-8 Boys are encouraged more than girls to go into the STEM field: Average by
nation ...........................................................................................................83
Figure 4-9 It is more difficult for a woman to get a job in the STEM field than for a maneven with the same qualifications: Average by nation...................................85
Figure 4-10 Becoming a tenured professor, being promoted or becoming a principal
investigator is more difficult for female scientists than for male scientists:
Average by nation .......................................................................................87
Figure 4-11 Women in STEM generally receive less pay for equal work, compared with
their equally-qualified male colleagues: Average by nation ........................89
Figure 4-12 I have experienced disadvantages in leading or participating in research
projects because I am a woman: Average by nation ...................................91
Figure 4-13 I have experienced disadvantages in receiving research funds or scholarships
because I am a woman: Average by nation ..................................................93
Figure 4-14 I have experienced sexual harassment or unfair treatments sometime in mycareer: Average by nation ............................................................................95
Figure 4-15 Balancing work and life has been a handicap for me: Average by nation ...98
Figure 4-16 Primary breadwinners of households should be men: Average by nation .100
Figure 4-17 Women are born to have a way of caring children that men are not capable ofin the same way: Average by nation ..........................................................102
Figure 4-18 In order to maintain the order and peace of a family, the husband should havegreater power and authority than the wife: Average by nation ..................104
Figure 4-19 Men are rational while women are emotional and they ought to complement
each other: Average by nation....................................................................106
Figure 4-20 I believe things will turn out fine in my future career: Average by nation...................................................................................................................108

16

Figure 4-21 It is crucial to have strong policy support to solve gender inequality in the
STEM field: Average by nation ................................................................. 110
Figure 4-22 I believe gender equality will be fully achieved only if women are given equal
opportunities as men: Average by nation.................................................... 113
Figure 4-23 Gap between Nepal & others on gender barriers .......................................121
Figure 4-24 Average of Nepal & others on Perception of discrimination .....................123
Figure 4-25 Average of Nepal & others on Experiences of discrimination ...................124
Figure 4-26 Average of Nepal & others on Gender role stereotypes .............................126
Figure 4-27 Average of Nepal & others on Career outlook ...........................................126
Figure 4-28 Average of Nepal & others on Policy needs ..............................................129
Figure 4-29 Average of Nepal & others on Equality concept ........................................129
Figure 4-30 Gap between New Zealand & others on gender barriers ...........................134
Figure 4-31 Average of New Zealand & others on Perception of discrimination .........135
Figure 4-32 Average of New Zealand & others on Exp. of discrimination ...................136
Figure 4-33 Average of New Zealand & others on Gender role stereotypes .................139
Figure 4-34 Average of New Zealand & others on Career outlook ...............................139
Figure 4-35 Average of New Zealand & others on Policy needs ..................................142
Figure 4-36 Average of New Zealand & others on Equality concept ............................142
Figure 4-37 Gap between Malaysia & others on gender barriers ..................................146
Figure 4-38 Average of Malaysia & others on Perception of discrimination ................149
Figure 4-39 Average of Malaysia & others on Exp. of discrimination..........................151
Figure 4-40 Average of Malaysia & others on Gender role stereotypes........................151
Figure 4-41 Average of Malaysia & others on Career outlook ......................................154
Figure 4-42 Average of Malaysia & others on Policy needs .........................................154
Figure 4-43 Average of Malaysia & others on Equality concept...................................156
Figure 4-44 Gap between Mongolia & others on gender barriers .................................159
Figure 4-45 Average of Mongolia & others on Perception of discrimination ...............161
Figure 4-46 Average of Mongolia & others on Exp. of discrimination .........................164
17

Figure 4-47 Average of Mongolia & others on Gender role stereotypes .......................164
Figure 4-48 Average of Mongolia & others on Career outlook .....................................166
Figure 4-49 Average of Mongolia & others on Policy needs ........................................168
Figure 4-50 Average of Mongolia & others on Equality concept ..................................168
Figure 4-51 Gap between Vietnam & others on gender barriers ...................................172
Figure 4-52 Average of Vietnam & others on Perception of discrimination .................174
Figure 4-53 Average of Vietnam & others on Exp. of discrimination ...........................177
Figure 4-54 Average of Vietnam & others on Gender role stereotypes .........................178
Figure 4-55 Average of Vietnam & others on Career outlook .......................................179
Figure 4-56 Average of Vietnam & others on Policy needs ..........................................180
Figure 4-57 Average of Vietnam & others on Equality concept ....................................183
Figure 4-58 Gap between Sri Lanka & others on gender barriers .................................187
Figure 4-59 Average of Sri Lanka & others on Perception of discrimination ...............188
Figure 4-60 Average of Sri Lanka & others on Exp. of discrimination.........................191
Figure 4-61 Average of Sri Lanka & others on Gender role stereotypes.......................191
Figure 4-62 Average of Sri Lanka & others on Career outlook .....................................194
Figure 4-63 Average of Sri Lanka & others on Policy needs ........................................196
Figure 4-64 Average of Sri Lanka & others on Equality concept..................................197
Figure 4-65 Gap between India & others on .................................................................202
Figure 4-66 Average of India & others on Perception of discrimination ......................203
Figure 4-67 Average of India & others on Exp. of discrimination ................................204
Figure 4-68 Average of India & others on Gender role stereotypes ..............................205
Figure 4-69 Average of India & others on Career outlook ............................................208
Figure 4-70 Average of India & others on Policy needs ................................................209
Figure 4-71 Average of India & others on Equality concept .........................................210
Figure 4-72 Gap between Japan & others on gender barriers .......................................215
Figure 4-73 Average of Japan & others on Perception of discrimination......................216

18

Figure 4-74 Average of Japan & others on Exp. of discrimination ...............................218
Figure 4-75 Average of Japan & others on Gender role stereotypes .............................219
Figure 4-76 Average of Japan & others on Career outlook ...........................................221
Figure 4-77 Average of Japan & others on Policy needs ...............................................221
Figure 4-78 Average of Japan & others on Equality concept ........................................223
Figure 4-79 Gap between Taiwan & others on gender barriers .....................................226
Figure 4-80 Average of Taiwan & others on Perception of discrimination ...................228
Figure 4-81 Average of Taiwan & others on Exp. of discrimination .............................231
Figure 4-82 Average of Taiwan & others on Gender role stereotypes...........................231
Figure 4-83 Average of Taiwan & others on Career outlook .........................................234
Figure 4-84 Average of Taiwan & others on Policy needs ............................................234
Figure 4-85 Average of Taiwan & others on Equality concept......................................237
Figure 4-86 Gap between Pakistan & others on gender barriers ...................................241
Figure 4-87 Average of Pakistan & others on Perception of discrimination .................241
Figure 4-88 Average of Pakistan & others on Exp. of discrimination ...........................244
Figure 4-89 Average of Pakistan & others on Gender role stereotypes .........................245
Figure 4-90 Average of Pakistan & others on Career outlook .......................................247
Figure 4-91 Average of Pakistan & others on Policy needs ..........................................247
Figure 4-92 Average of Pakistan & others on Equality concept ....................................250
Figure 4-93 Gap between Republic of Korea & others on gender barriers ...................254
Figure 4-94 Average of Republic of Korea & others on Perception of discrimination .256
Figure 4-95 Average of Republic of Korea & others on Exp. of discrimination ...........257
Figure 4-96 Average of Republic of Korea & others on Gender role stereotypes .........258
Figure 4-97 Average of Republic of Korea & others on Career outlook .......................260
Figure 4-98 Average of Republic of Korea & others on Policy needs ..........................261
Figure 4-99 Average of Republic of Korea & others on Equality concept ....................263
Figure 4-100 Gap between Bangladesh & others on gender barriers ............................265

19

Figure 4-101 Average of Bangladesh & others on Perception of discrimination ..........268
Figure 4-102 Average of Bangladesh & others on Exp. of discrimination....................271
Figure 4-103 Average of Bangladesh & others on Gender role stereotypes..................272
Figure 4-104 Average of Bangladesh & others on Career outlook ................................274
Figure 4-105 Average of Bangladesh & others on Policy needs ...................................274
Figure 4-106 Average of Bangladesh & others on Equality concept.............................277

20

1. Introduction

1. Introduction
According to Statistics Korea, Korea will become a super-aged society in the next
10 years; that is, more than 20% of its population will be aged 65 or older. Given that
Korea’s birth rate is already the lowest in the world, its rapid pace of aging indicates a
rapid decline of the economically active population. Even with computers replacing
humans in the age of artificial intelligence, a country’s workforce remains a highly
influential factor in determining national competitiveness. This is because the size of thecompetent workforce decreases when the overall workforce falls below a critical point,
which also causes a deterioration in the nation’s capacity to develop novel technology.
One silver lining to Korea’s workforce prospects is that women are notparticipating actively in economic activities. Korea’s female participation in economic
activities was a mere 57.9% in 2015, lower than the OECD average of 63.0%. Worse, its
rate of labor participation by women with tertiary education stood at 64.1% in 2013,
falling short of the OECD average of 83.3% and making it the lowest among OECDmember countries. Even Turkey, which recorded the lowest female labor force
participation (35.0% in 2015) among OECD member countries, had a higher value of
73.7% when it came to labor force participation by highly educated women. With highly
educated men in Korea recording 92.4% in labor force participation, slightly higher thanthe OECD average of 92.1%, the very low rate of labor force participation by female
counterparts leaves room for various sociocultural interpretations. By utilizing highly
educated women who are currently not participating in or who are unable to participate
in economic activities, we can expect a slowing of the decline in the workforce, causedby rapid aging and low birth rate.
It is a highly challenging task to encourage highly educated women to participate
more actively in economic activities. The difficulty of work-life balance and the collective
ignorance of Korean society are main reasons for the low rate of female labor force
participation. Some mistakenly believe that gender equality has been achieved, whileothers claim that reverse discrimination has made possible the rapid progress of womenin teaching and state examinations. There are illusions such as: “There is no gender
discrimination among professionals,” and “All practices in the fields of science andtechnology are rational.” Women who have gained reputations in their professions after
beating off stiff competition from men are often told to rely on their individual capacity,
demonstrating the society’s lack of interest in resolving structural gender discrimination.
This study approached these structural issues using the two methods described below.
First, this study examined international statistics concerning the aforementioned
structural issues by country. To perform a comparative analysis of female human resources
development, it analyzed quantitative indices published annually by the OECD, WEF and
23

UNDP. Each international organization has different definitions and objectives, but this study
is meaningful in that it allows a rough comparison of the status of human resources
development around the world. In addition, the analysis of indices from the perspective ofgender holds significance in contributing to the development of balanced human resources
policies. The analysis of international human resources development indices covered the 13
member countries (Nepal, New Zealand, Malaysia, Mongolia, Bangladesh, Vietnam, Sri
Lanka, India, Japan, Taiwan, Pakistan, Korea and Australia) of the Asia and Pacific Nations
Network (APNN) under the International Network of Women Engineers and Scientists(INWES), in which KWSE is playing a leading role.
Second, utilizing the existing KWSE network a joint survey of INWES APNN
member countries has been conducted for three consecutive years. The 2014 survey focusedon gender equality in the fields of science and technology1, the 2015 survey on the glass ceilingas perceived by female scientists and engineers 2 and the 2016 survey on gender barriers in thefields of science and technology. The gender barriers refers to the existence and experiences ofgender discrimination that function as hindrances to gender equality. This includes
institutional/customary barriers and conscious/unconscious barriers. Specific examples
are traditional gender role stereotypes, unfairness in employment and promotion, worklife balance and responsibility for family and other unfair treatment. To assess genderbarriers experienced by female scientists and engineers in all stages, from talent nurturing,job-seeking and re-entry after a career break, the survey was broadly divided into
perception of discriminatory reality, discriminatory experiences and gender role ideology,
which covered career prospects, policy demands and the concept of gender equality. A
total of 1,379 female scientists and engineers from 12 APNN member countries,
excluding Australia, participated in this year‘s survey. This demonstrates that the joint
international survey is gaining support among member countries, and that it is opening
up more opportunities for countries in the Asia-Pacific region to share methods ofnurturing and utilizing female scientists and engineers. The results were presented bymember country in order to facilitate more extensive and efficient utilization.
Chapter 2 examines the current status of human resources development by
country based on the aforementioned international indices, while Chapter 3 gives asummary of the gender barriers survey completed by APNN member countries. Chapter
4 provides survey results by indicator, question and country. The report ends in Chapter
5 with a conclusion and recommendations.

1 2014 Policy Report on Balanced Development of Human Resources for the Future; Analysis of Global Gender
Indices & Joint Survey Results from APNN Countries, Kong-Ju-Bock Lee, Jung Sun Kim (2014).
2 The Glass Ceiling for Asian Women in STEM: The 2015 INWES APNN Joint Survey Report. International
Cooperation Policy Research Team of the Association of Korean Women Scientists & Engineers (2015).

24

2. Current Status of Human Resources
Development by Nation

2. Current Status of Human Resources Development by Nation
This chapter examines the definition of the Human Development Index (HDI)
and the Gender Inequality Index (GII) as released by the UN, the definition of the Gender
Gap Index (GGI) as released by the WEF, and the current status of human resources
development in member countries of the OECD and APNN under INWES. It also reviews
the status of female scientists based on a recent report by UNESCO. The definitions of
the various indices are the same as those provided in the 2013 Policy Report on Balanced
Development of Human Resources for the Future.
2.1 Cross-country comparison based on HDI by UNDP
2.1.1 HDI composition and cross-country comparison
The Human Development Index (hereinafter referred to as “HDI”) of the UNDP
is a summary measure of average achievement in three key dimensions of humandevelopment: a long and healthy life, being knowledgeable and having a decent standardof living. For the purpose of this measurement, specific indices such as life expectancy,
mean years of schooling, expected years of schooling and gross national income percapita are assessed (see Table 2-1). The HDI is designed to have a value between 0 and
1; a higher HDI translates to greater achievement in human development.
< Table 2-1 The components of HDI>
Components of HDI

Basis of calculationLife
expectancy
atbirth assuming that the death rate will
Life expectancy at birth
be maintained as when one was born
Mean years of schoolingYears that a 25-year-old person or older has spent in schools
Years that a 5-year-old child will spend with his
Expected years of schoolingeducation in his whole life
Gross national income per capita
Measured based on Purchasing Power Parity (PPP)

Table 2-2 lists some countries’ performance in HDI and in specific indices basedon the Human Development Report 2015 by UNDP. The number of countries surveyed
increased from 187 in 2013 to 188 in 2014. The countries are divided into several groups
based on the HDI indices: countries of very high human development (rankings 1 to 49
with an average HDI of 0.896), of high human development (rankings 50 to 105 with anaverage HDI of 0.744), of medium human development (rankings 106 to 144 with anaverage HDI of 0.630) and of low human development (rankings 145-188 with an average
HDI of 0.505). Norway ranked the highest in terms of human development achievement
at 0.994, topping the list of countries for the 12th consecutive year. Korea attained aslightly higher HDI of 0.898 compared to 0.891 in 2013, but fell from the 15th to the 17thplace. Japan dropped from the 17 th position in 2013 to the 20 th position in 2014, recording
an HDI of only 0.891. Similar to the results for 2013, Niger had the lowest achievementin human development at 0.348.
27

< Table 2-2 HDI and its components by country (2014)>(HDI=1: Highest human development index)

HDI
rank

Country

HDI

Very high human development
1
Norway0.944
2Australia
0.935
3
Switzerland
0.930
4
Denmark
0.923
5Netherland
0.922
6Germany
0.916
6
Ireland
0.916
8
U.S.A
0.915
9
Canada0.913
9
New Zealand 0.913
11Singapore
0.912
12Hong Kong
0.910
13Liechtenstein 0.908
14
Sweden0.907
14
England0.907
16
Iceland
0.899
17
Korea
0.898
18
Israel0.894
19Luxembourg
0.892
20
Japan
0.891
49
Montenegro
0.802High human development
62
Malaysia
0.779
73
Sri Lanka
0.757
90
China
0.727
90
Mongolia
0.727
Medium human development
116
Vietnam
0.666
130
India
0.609
142
Bangladesh
0.570
Low human development
145
Nepal
0.548
147
Pakistan
0.538
188
Niger
0.348
Taiwan
0.882
(25)

Life
expectancy(years)Mean yearsofschooling(years)Expected
yearsofschooling(years)Purchasing
power
parity perperson(2011 PPP $)

81.6
82.4
83.0
80.2
81.6
80.9
80.9
79.1
82.0
81.8
83.0
84.0
80.0
82.2
80.7
82.6
81.9
82.4
81.7
83.5
76.2

12.6
13.0
12.8
12.7
11.9
13.1
12.2
12.9
13.0
12.5
10.6
11.2
11.8
12.1
13.1
10.6
11.9
12.5
11.7
11.5
11.2

17.5
20.2
15.8
18.7
17.9
16.5
18.6
16.5
15.9
19.2
15.4
15.6
15.0
15.8
16.2
19.0
16.9
16.0
13.9
15.3
15.2

64,99242,261
56,431
44,02545,43543,91939,56852,94742,15532,68976,62853,95979,851
45,63639,26735,18233,89030,67658,711
36,927
14,558

74.7
74.9
75.8
69.4

10.0
10.8
7.5
9.3

12.7
13.7
13.1
14.6

22,762
9,779
12,547
10,729

75.8
68.0
71.6

7.5
5.4
5.1

11.9
11.7
10.0

5,092
5,497
3,191

69.6
66.2
61.4
79.8

3.3
4.7
1.5
16.2

12.4
7.8
5.4
10.7(2010)

2,311
4,866
908
45,148APNN countries (Taiwan’s data from: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(Source: UNDP Human Development Report 2015)28

Table 2-2 distinguishes the HDI of APNN member countries from nonmember countries. In the Asia-Pacific region, New Zealand, Korea and Japan were in thegroup of very high human development, despite slight drops in the ranking. Malaysia, Sri
Lanka and Mongolia were in the high human development group. In particular, Mongolia
showed a significant improvement in ranking, jumping from the 103 rd position in 2013
to the 90 th position in 2014.
<Table 2-3 GDI ranks and female/male HDI scores by country (2014)>
HDI rank Country GDI = Female HDI/Male HDI GDI rank
Female HDI
Male HDI
Very high human development
1
Norway
0.996
12
0.940
0.944
2
Australia 0.976
42
0.922
0.945
3
Switzerla 0.950
80
0.898
0.945
4
Denmark 0.977
39
0.912
0.934
5
Netherla 0.947
89
0.893
0.943
6
Germany 0.963
64
0.901
0.936
6
Ireland
0.973
48
0.901
0.926
8
U.S.A
0.995
14
0.911
0.916
9
Canada
0.982
31
0.904
0.921
9
New
0.961
68
0.894
0.930
11
Singapor 0.985
24
0.898
0.912
12
Hong
0.958
71
0.892
0.931
14
Sweden
0.999
3
0.906
0.906
14
England 0.965
62
0.888
0.920
16
Iceland
0.975
44
0.886
0.909
17
Korea
0.930
104
0.861
0.926
18
Israel
0.971
52
0.879
0.905
19
Luxemb 0.971
53
0.877
0.903
20
Japan
0.961
66
0.870
0.905
49
Montene 0.954
77
0.782
0.819
High human development
62
Malaysia 0.947
90
0.753
0.795
73
Sri
0.948
85
0.730
0.769
90
China
0.943
94
0.705
0.747
90
Mongoli 1.028
49
0.737
0.716
Medium human delopment
116
Vietnam 130
India
0.795
151
0.525
0.660
142
Banglade 0.917
109
0.541
0.590
Low human development
145
Nepal
0.908
114
0.521
0.574
147
Pakistan 0.726
160
0.436
0.601
188
Niger
0.729
159
0.287
0.394
APNN countries (except Taiwan. No HDI data found on Taiwan)(Source: UNDP Human Development Report 2015)29

Vietnam and India remained in the medium human development group despite
moving up in ranking from the 121st and 135th in 2013 to the 116th and 130th place in2014, respectively. Bangladesh, which became an APNN member state last year, was also
in the group of medium human development. Nepal and Pakistan again belonged to thelow human development group, with their mean schooling years failing to surpass five
years.
2.1.2 Cross-country comparison based on the GDI and the HDI by gender
The UNDP also publishes an index that shows male HDI against female HDI;
this is known as the gender-related development index (hereinafter referred to as GDI).
GDI is defined as the female HDI divided by the male HDI. The country with the lowest
gender gap ranks the highest; this is the country for which the absolute value of [(female
HDI)/male HDI]-1] is closest to 0. Because the UNDP did not provide GDI rankings in
2015, this study calculated the values using the same standards as were used in theprevious year. The GDI values for the countries listed in Table 2-2 are listed in Table 23. The HDI and GDI of APNN member countries in 2013 and 2014 are given in Table 24.
<Table 2-4 The HDI and GDI of APNN member countries in 2013 and 2014>(unit: points, %, GII=0: complete equality)

UNDP HDICountry

2013
from 187 countries

Rank
Nepal
145
New Zealand
7
Malaysia
62
Mongolia
103
Bangladesh * 142
Vietnam
121
Sri Lanka
73
India
135
Japan
17
Taiwan **(21)
Pakistan
146
Korea
15
Australia
2

Value
0.912
0.971
0.935
0.698
0.558
0.638
0.750
0.586
0.890
0.882
0.537
0.891
0.933

UNDP GDI

2014
from 188 countries

2013
from 187 countries

2014
from 188 countries

Rank
145
9
62
90
142
116
73
130
20
(25)
147
17
2

Rank
102
47
91
32
107
66
132
79
145
85
40

Rank
114
68
90
49
109
85
151
66
160
104
42

Value
0.548
0.913
0.779
0.727
0.570
0.666
0.757
0.609
0.891
0.882
0.538
0.898
0.935

Value
0.912
0.971
0.935
1.021
0.908
0.961
0.828
0.951
0.750
0.940
0.975

Value
0.908
0.961
0.947
1.028
0.917
0.948
0.795
0.961
0.726
0.930
0.976

* Bangladesh has been an INWES APNN member country since 2015** Taiwan’s data were determined by the Taiwanese government based on the UNDP and WEF
methodology (source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(Source: UNDP, Human Development Report 2014, 2015)30

Despite its 17th position in the HDI, Korea has a much lower ranking of 104th
in terms of GDI, indicating that the country’s female HDI (0.861) is much lower than its
male HDI (0.926). The fact that Korea ranked 85th in GDI in 2013 means that the gender
gap broadened in 2014. In Mongolia, male HDI was lower than female HDI, leading to a
GDI higher than 1.

31

2.2 Cross-country comparison based on GII of UNDP
As mentioned above, Korea’s HDI is relatively good but the gender gap of the
HDI is strikingly large. This gap has worsened in recent years compared to other countries.
To ensure balanced cultivation of future talent, bridging this gender gap should be
addressed as the country’s urgent priority. Therefore, we would like to further examine a
few indices regarding gender gaps that were analyzed in the 2014 report. In the global
sense, representative gender equality indices include the Gender Inequality Index (GII)of the UNDP and the Gender Gap Index (GGI) of the WEF. Here, we will have a lookat the GII of the UNDP first. The GII is a new index developed by the UNDP in 2010 inorder to improve the shortcomings of the GDI, which was briefly touched upon above,and the Gender Empowerment Measure (GEM) 1, which was not mentioned specifically.
GII can be used to confirm the loss arising from inequality in male and female
development.
Korea ranked 27th in GII among 148 countries in 2012, 17th among 152 countries
in 2013 and 23rd among 155 countries in 2014. The following section examines thecomposition of indices and the current status of member countries of the OECD and
APNN.
2.2.1 Composition of the GII<Table 2-5 The components of GII >Area

Dimensions

Mortality of women due to pregnancy, delivery
and complications (per 100,000 live births)
Adolescent fertility rate Births per 1000 women aged 15-19 years old
Female share of
Female ratio in parliamentparliamentary seats
Empowerment
Ratio of secondary
Ratio of secondary education
education
Female/male ratio of labor force participation ofLabor force
Economic status
Participate on rate population over 15 years of age (or ages 15 to 64)
Reproductive
healthMaternal mortality ratio

As shown in Table 2-5, the GII consists of to a total of five indices for three
specific areas: reproductive health measured by maternal mortality ratio and adolescentbirth rates, which are special indices dealing only with females to measure female healthand inequality in job opportunities; empowerment, measured by proportion ofparliamentary seats occupied by females and proportion of adult females and males withat least some secondary education; and economic status, expressed as labor market
participation and measured by labor force participation rate.
1

The GEM measures female participation in political activities and political decision-making, female
participation in economic activities and economic decision-making and female share of income.

32

As shown in the specific indices, the GII does not include income as one of its
indices, considering that statistics on income levels in different countries are not sufficient,and also because GII was designed to allow indices with higher correlation to genderequality to have greater values, which is sometimes pointed out as a weakness.
2.2.2 Comparison of GII among OECD member countries<Table 2-6 GII status of OECD member countries (2014)>- MMR=Maternal mortality ratio- FSPS=Female share of parliamentary seats- LFPR=Labor force participation rate

- AFR=Adolescent fertility rate
- RSE=Ratio of secondary education(unit: points, %, GII=0: complete equality)

GII
Country
Slovenia
Switzerland
Germany
Denmark
Austria
SwedenNetherlands
Belgium
NorwayItaly
Finland
IcelandFranceRep. Czech
Spain
Luxembourg
IsraelAustralia
Portugal
Ireland
Korea
CanadaJapan
PolandGreeceNew ZealandEstonia
Slovakia
England
Hungary
U.S.A
Chile
TurkeyMexicoRSE

Value

OECD/UN rank

0.016
0.028
0.041
0.048
0.053
0.055
0.062
0.063
0.067
0.068
0.075
0.087
0.088
0.091
0.095
0.100
0.101
0.110
0.111
0.113
0.125
0.129
0.133
0.138
0.146
0.157
0.164
0.164
0.177
0.209
0.280
0.338
0.359
0.373

1/1
2/2
3/3
4/4
5/5
6/6
7/7
8/8
9/9
10/10
11/11
12/12
13/13
14/15
15/16
16/17
17/18
18/19
19/20
20/21
21/23
22/25
23/26
24/28
25/29
26/32
27/33
28/33
29/39
30/42
31/55
32/65
33/71
34/74

MMR

AFF

FSPS

7
6
7
5
4
4
6
6
4
4
4
4
12
5
4
11
2
6
8
9
27
11
6
3
5
8
11
7
8
14
28
22
20
49

0.6
1.9
3.8
5.1
4.1
6.5
6.2
6.7
7.8
4.0
9.2
11.5
5.7
4.9
10.6
8.3
7.8
12.1
12.6
8.2
2.2
14.5
5.4
12.2
11.9
25.3
16.8
15.9
25.8
12.1
31.0
55.3
30.9
63.4

27.7
28.5
36.9
38.0
30.3
43.6
36.9
42.4
39.6
30.1
42.5
41.3
25.7
18.9
38.0
28.3
22.5
30.5
31.3
19.9
16.3
28.2
11.6
22.1
21.0
31.4
19.8
18.7
23.5
10.1
19.4
15.8
14.4
37.1

LFPR

FemaleMale

Female

Male

95.8
95.0
96.3
95.5
100.0
86.5
87.7
77.5
97.4
71.2
100.0
91.0
78.0
99.9
66.8
100.0
84.4
94.3
47.7
80.5
77.0
100.0
87.0
79.4
59.5
95.0
100.0
99.1
99.8
97.9
95.1
73.3
39.0
55.7

98.0
96.6
97.0
96.6
100.0
87.3
90.5
82.9
96.7
80.5
100.0
91.6
83.2
99.7
73.1
100.0
87.3
94.6
48.2
78.6
89.1
100.0
85.8
85.5
67.0
95.3
100.0
99.5
99.9
98.7
94.8
76.4
60.0
60.6

52.3
61.8
53.6
58.7
54.6
60.3
58.5
47.5
61.2
39.6
55.7
70.5
50.7
51.1
52.5
50.7
57.9
58.8
54.9
53.1
50.1
61.6
48.8
48.9
44.2
62.0
56.2
51.1
55.7
44.8
56.3
49.2
29.4
45.1

63.2
74.9
66.4
66.4
67.7
67.9
70.6
59.3
68.7
59.5
64.0
77.4
61.6
68.3
65.8
64.6
69.1
71.8
66.2
68.1
72.1
71.0
70.4
64.9
62.5
73.8
68.9
68.6
68.7
60.0
68.9
74.8
70.8
79.9

* Latvia is not included because it became a member of OECD in May, 2016
(Source: UNDP, Human Development Report 2015)33

Table 2-6 shows the GII of OECD member countries in 2014. The GII takes avalue between 0 and 1, with 0 denoting complete equality and with 1 representing
complete inequality. Most countries showed minimal differences compared to 2013, but
Luxembourg jumped from the 25th (GII=0.154) to the 16th place (GII=0.100) among
OECD countries, while Korea fell from the 16th (GII=0.101) to the 21st place (GII=125)
2.2.3 Comparison of the GII among APNN member countries
Table 2-7 shows the GII of APNN member countries, in increasing order of genderinequality, in 2014. Because Taiwan was not covered by the UN survey, the GII value
provided by the Taiwanese government was used instead to calculate its ranking.
<Table 2-7 GII values of APNN member countries in (2014)>- The same abbreviations as in Table 2-6(unit: points, %)GIICountryUN
Rank
Taiwan*(5)Australia
19
Korea
23
Japan
26
New Zealand 32
Malaysia42
Vietnam
60
Mongolia
63
Sri Lanka
72
Nepal
108
Bangladesh** 111
Pakistan
121
India
130

RSE
MMR

AFR

FSPS

Value
0.052
0.110
0.125
0.133
0.157
0.209
0.308
0.325
0.370
0.489
0.503
0.536
0.563

Female
7
6
27
6
8
29
49
68
29
190
170
170
190

4.0
12.1
2.2
5.4
25.3
5.7
29.0
18.7
16.9
73.7
80.6
27.3
32.8

RSE LFPR

35.5
30.5
16.3
11.6
31.4
14.2
24.3
14.9
5.8
29.5
20.0
19.7
12.2

94.3
77.0
87.0
95.0
65.1
59.4
85.3
72.7
17.7
34.1
19.3
27.0

Male
94.6
89.1
85.8
95.3
71.3
71.2
84.1
76.4
38.2
41.3
46.1
56.6

Female

Male

58.8
50.1
48.8
62.0
44.4
73.0
56.6
35.1
79.9
57.4
24.6
27.0

71.8
72.1
70.4
73.8
75.5
82.2
69.3
76.3
87.1
84.1
82.9
79.9

* Taiwan’s data were determined by the Taiwanese government based on the UNDP and WEF
methodology (source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)* * Bangladesh has been an INWES APNN member country since 2015
(Source: UNDP, Human Development Report 2015)

The countries with severe gender inequality were Bangladesh, which became an APNN
member country in 2015, Nepal, Pakistan and India. Korea’s GII at the 23rd position wasslightly higher than Japan’s 26th, but Korea had a much higher maternal mortality ratioof 27 per 100,000 than Japan’s 6 per 100,000. Given that maternal mortality ratio isdefined as “the annual number of female deaths per 100,000 live births from any cause
related to or aggravated by pregnancy or its management,” we can see that this ratio falls
far behind Korea’s level of economic development. This can be considered a consequenceof a loophole in social welfare policies for the alienated female population, and should betaken into account in the development and implementation of policies for female welfare.
Table 2-8 compares the GII values and rankings of APNN member countries
34

over the past two years. Excluding Taiwan, for which the GII was provided by its
government, APNN member countries had fairly low GII rankings. Moreover, the GII
rankings of countries, except New Zealand, Bangladesh and Sri Lanka were lower thanthat of 2013. Nepal and Mongolia showed a significant drop in ranking, while Bangladesh
improved compared to 2013 despite its level of gender inequality still remaining severe.
<Table 2-8 the GII of APNN member countries in 2013 and 2014>(GII=0: complete equality)

UNDP GIICountry
Nepal
New Zealand
Malaysia
Mongolia
Bangladesh*
Vietnam
Sri Lanka
India
Japan
Taiwan**Pakistan
Korea
Australia

2013
from 152 countries

2014
from 155 countries

Rank
98
34
39
54
142
58
75
127
25
(5)
127
17
19

Rank
108
32
42
63
111
60
72
130
26
(5)
121
23
19

Value
0.479
0.185
0.210
0.320
0.529
0.322
0.383
0.563
0.138
0.055
0.563
0.101
0.113

Value
0.489
0.157
0.209
0.325
0.503
0.308
0.370
0.563
0.133
0.052
0.536
0.125
0.110

* Bangladesh has been an INWES APNN member country since 2015
* * Taiwan’s data were determined by the Taiwanese government based on the UNDP and
WEF methodology(source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(Source: UNDP, Human Development Report 2015)

2.2.4 Recent changes in Korea’s GII
Korea’s GII has fluctuated recently, as shown in Table 2-9, but, overall, it has ahigher level of gender equality when considering the mean GII of the participating
countries under the UN; Korea has a generally lower level of gender equality, except foradolescent birth rates, compared to the mean GII among OECD member countries.
Some results deserving more attention are the ratio of women with secondaryor higher education and the female labor force participation. In the 2014 survey by theUN, the average ratio of women with secondary or higher education was 54.5%, and theaverage rate of female labor force participation was 50.3%. Although Korean women withsecondary or higher education accounted for a high 77.0%, the female labor force
participation rate was only 50.1%, indicating that highly educated women are not actively
involved in economic activities. This trend can be observed in other OECD member
countries. Among OECD member countries, the average ratio of women with secondary35

or higher education was 85.4%, but the average rate of female labor force participation
was 53.2%. More details on labor force participation are given in Section 2-4. It should
be noted, however, that Korea’s labor force participation by women with secondary or
higher education was similar to the OECD average, but its labor force participation by
women with tertiary education was lower at 62.3% than the OECD average of 78.6%.
<Table 2-9 GII values of Korea from 2008 to 2014>- The same abbreviations as in Table 2-6

GII
Year
2008a
2011 b2012 c2013 d2014 e2014(UN)
2014(OECD)(unit: points, %)Reproductive
healthRank Value MMR

AFR

20/138 0.310
11/146 0.111
27/148 0.153
17/152 0.101
23/155 0.125
0.449
0.128

5.5
2.3
5.8
2.2
2.2
47.4
13.5

14
18
16
16
27
210
9.9

Economic
activity
RSE
LFPR
FSPS
Female Male Female Male
13.7
79.4
91.7
54.4
75.6
14.7
79.4
91.7
50.1
72.0
15.7
79.4
91.7
49.2
71.4
15.7
77.0
89.1
49.9
72.0
16.3
77.0
89.1
50.1
72.1
21.8
54.5
65.4
50.3
76.7
27.7
85.4
88.1
53.2
68.1
Empowerment* Latvia is not included because it became a member of OECD in May, 2016
(Source: UNDP, Human Development Report a2010, b2011, c2013, d2014, e2015),<Table 2-10 International indices on Human Resource Development by APNN Member
Countries(2014)>(HDI=1: most developed, GDI=1: complete equality, GII=0: complete equality)

Country
Nepal
New Zealand
Malaysia
Mongolia
Bangladesh*
Vietnam
Sri Lanka
India
Japan
Taiwan**Pakistan
Korea
Australia

UNDP HDI
2014
from 188 countries
Rank
Value
145
0.548
9
0.913
62
0.779
90
0.727
142
0.570
116
0.666
73
0.757
130
0.609
20
0.891
(25)
0.882
147
0.538
17
0.898
2
0.935

UNDP GDI
2014
from 188 countries
Rank
Value
114
0.908
68
0.961
90
0.947
49
1.028
109
0.917
85
0.948
151
0.795
66
0.961
160
0.726
104
0.930
42
0.976

UNDP GII
2014
from 15 countries
Rank
Value
108
0.489
32
0.157
42
0.209
63
0.325
111
0.503
60
0.308
72
0.370
130
0.563
26
0.133
(5)
0.052
121
0.536
23
0.125
19
0.110

* Bangladesh has been an INWES APNN member country since 2015
* * Taiwan’s data were determined by the Taiwanese government based on the UNDP and WEF
methodology (source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(source: UNDP, Human Development Report 2015)36

Section 2-1 and 2-2 examined the various indices of human resources development, suchas HDI, GDI and GII, released by the UNDP. Table 2-10 gives the 2014 statistics for
APNN member countries. Most countries have similar rankings in the three indices, but
Korea shows a wide gap across the indices. Korea ranked 17th and 23rd in HDI and GII,but performed very poorly in GDI at the 104th position. Although Korea has an individual
human development index higher than those of many other countries, its female HDI ismuch lower than its male HDI. This wide gap in HDI and GDI rankings was observed in
New Zealand and Australia as well.

37

2.3 Cross-country comparison of the GGI of the WEF
The GGI, reported by the WEF, measures gender gaps in the economy, education,
health and politics; it focuses on closing the gender gap in a country, rather than on female
empowerment. Korea has a shockingly low GGI ranking (115 th out of 145 countries in2015). Some have criticized this result as unreliable, but the index composition andsupporting evidence provided below indicate that the GGI ranking cannot be overlooked.
2.3.1 Composition of the GGI and data source<Table 2-11 Structure of the GGI>
(Ratio=Female/Male)

Subindex

Economic
participation
andopportunity

Educational
attainment

Health andsurvival

Political
empowerment

Variable
Weights
SourceLabor force participation
0.199 International Labour Organization
rate ratio
Wage equality between
0.310 World Economic Forumwomen and men for similar
work
Female estimated earned
0.221 World Economic Forum
income over male value
Female legislators, senior
officials and managers over
0.149 International Labour Organization
male value
Female professional andtechnical workers over male 0.121 International Labour Organization
value
Total
1
Female literacy rate over
0.191 UNESCO Institute for Statistics
male value
Female net primaryenrolment rate over male
0.459 UNESCO Institute for Statistics
value
Female net secondary
enrolment rate over male
0.230 UNESCO Institute for Statistics
value
Female gross tertiaryenrolment ratio over male
0.121 UNESCO Institute for Statistics
value
Total
1
Sex ratio at birth (converted
0.693 Central Intelligence Agency
to female-over-male ratio)
Female healthy life
0.307 World Health Organization
expectancy over male value
Total
1
Females with seats in
0.310 Inter-Parliamentary Union
parliament over male value
Females at ministerial level
0.247 Inter-Parliamentary Union
over male value
Number of years of a female
head of state (last 50 years)
0.443 World Economic Forumover male value
Total
1(source: WEF, Global Gender Gap Report)

38

The GGI consists of a total of 14 specific indicators in four fundamental
categories: economic participation and opportunity, educational attainment, health andsurvival and political empowerment. Specific indicators for each area, and data sources
for each index, are listed in Table 2-11. All indicators are calculated as a male indicatorvalue against a female indicator value; a value closer to 1 denotes a narrower gender gap,
while a value smaller than 1 indicates that females have lower standings than males, anda value greater than 1 means that females have higher standings than male. Each indicatoris given a weighting, with wage equality between women and men for similar work,
female net primary enrollment rate over male value, sex ratio at birth and years withfemale head of state (female-over-male ratio) over the past 50 years getting greater
weights.
2.3.2 Recent changes in sub-indices of the GGIPrior to comparing GGI values among OECD member countries or among
APNN member countries, let’s examine the average values and yearly changes ofindicators for each area of the countries included in the WEF study. Fig. 2-1 shows theworld average of indicators for each area in 2015. We can see that gender gaps in healthand survival and in educational attainment have been substantially closed, with each area
recording values of 0.96 and 0.95, respectively. However, gender gaps are still wide ineconomic participation and contribution at 0.59, and in political empowerment at 0.23.
<Figure 2-1 The World Average of GGI by Indicators (2015)>(source: WEF Global Gender Gap Index 2015)

Figure 2-2 shows the yearly changes in GGI indicators for each area over the past
decade. The yearly changes are very gradual across all areas, except politicalempowerment. The slow pace of improvement in economic participation and contribution,
despite the large gender gap, has many implications. More details can be found in thefollowing section.
39

<Figure 2-2 GGI evolution 2006~2015>(source: WEF Global Gender Gap Index 2015)

2.3.3 Comparison of the GGI among OECD member countries
Table 2-12 shows the GGI of 34 OECD member countries in 2015 (35 member
countries including Latvia in 2016) and individual scores and rankings for each category.
The rankings are based on 145 countries, and the GII rankings in the first column are
based on the 155 countries surveyed by the UNDP.
The GII rankings by the UNDP and the GGI rankings by the WEF are provided
together to highlight the importance of using different indices for a more comprehensive
assessment of gender equality. The latest data on GII involved 155 countries in 2014,
while GGI involved 145 countries in 2015. While there are some differences in thenumber of participating countries and in the reference years, the two rankings can becompared because the overall trends remain largely the same. For instance, as shown in
Table 2-12, the top-ranking GII country Slovenia ranked 9th out of 145 countries in GGI(23rd out of 142 countries in 2014). Iceland, which took the 12th place in GII, was the top
country in the GGI rankings (1st in 2014). Such differences are attributable to the fact that
the GII focuses on female survival and minimum dignity by considering maternalmortality ratio and adolescent births, among other factors, whereas the GGI takes into
consideration gender ratios of decision makers and wages.
Korea is one of the countries with the largest gaps, with its GII ranking of 23rdout of 155 countries and GGI ranking of 115th out of 145 countries (117th out of 142
countries in 2014). This is not very different from Japan’s situation: it ranked 26th in the
GII but 101st in the GGI. Among OECD countries, Turkey was found to have the widest
gender gap, with its GII ranking of 71st and GGI ranking of 130th. Interestingly, thecountries with poor GGI rankings among the 34 OECD member countries are either in
Asia (Japan and Korea) or bordering Asia and Europe (Turkey). This implies that
geocultural conditions are closely related to gender issues.

40

<Table 2-12 GGI ranks and values of OECD member countries (2015)>

GII
rank*
1
2
3
4
5
6
7
8
9
10
11
12
13
15
16
17
18
19
20
21
23
25
26
28
29
32
33
33
39
42
55
65
71
74

Economic
Education
Health andPolitical
participation &attainment
survival
empowerment
Country&opportunity
Rank Value Rank Value Rank Value Rank Value Rank Value
Slovenia
9 0.784
24 0.778
29 1.000
79 0.973
16 0.385
Switzerland
8 0.785
17 0.798
69 0.993
74 0.974
18 0.376
Germany
11 0.779
38 0.737
88 0.987
56 0.979
11 0.413
Denmark
14 0.767
20 0.788
1 1.000 107 0.970
29 0.309
Austria
37 0.733
52 0.705
1 1.000
1 0.980
39 0.246
Sweden
4 0.823
4 0.836
54 0.996
71 0.974
5 0.486
Netherland
13 0.776
39 0.732
1 1.000 104 0.970
13 0.401
Belgium
19 0.753
34 0.762
1 1.000
66 0.974
35 0.275
Norway2 0.850
1 0.868
32 1.000
70 0.974
3 0.559
Italy
41 0.726 111 0.603
58 0.995
74 0.974
24 0.331
Finland
3 0.850
8 0.815
1 1.000
1 0.980
2 0.607
Iceland
1 0.881
5 0.836
1 1.000 105 0.970
1 0.719
France15 0.761
56 0.699
1 1.000
1 0.980
19 0.365
Rep. Czech
81 0.687
94 0.636
1 1.000
42 0.979
83 0.134
Spain
25 0.742
67 0.674
47 0.998
93 0.972
26 0.326
Luxembourg
32 0.738
31 0.766
1 1.000
71 0.974
53 0.212
Israel53 0.712
71 0.671
51 0.996
69 0.974
54 0.205
Australia
36 0.733
32 0.766
1 1.000
74 0.974
61 0.193
Portugal
39 0.731
46 0.712
60 0.995
79 0.973
41 0.244
Ireland
5 0.807
26 0.777
44 0.998
56 0.979
6 0.474
Korea
115 0.651 125 0.557 102 0.965
79 0.973 101 0.107
Canada30 0.740
28 0.773
1 1.000 109 0.969
46 0.218Japan
101 0.670 106 0.611
84 0.988
42 0.979 104 0.103
Poland51 0.715
75 0.667
38 1.000
42 0.979
52 0.213
Greece87 0.685
87 0.644
56 0.996
56 0.979
91 0.120
New Zealand 10 0.782
30 0.768
1 1.000 105 0.970
15 0.390
Estonia
21 0.749
47 0.711
39 0.999
1 0.980
30 0.308
Slovakia
97 0.675
93 0.638
1 1.000
79 0.973 115 0.087
England
18 0.758
43 0.724
37 1.000
66 0.974
23 0.335
Hungary
99 0.672
62 0.685
76 0.991
42 0.979 139 0.035
U.S.A.
28 0.740
6 0.826
40 0.999
64 0.975
72 0.162
Chile
73 0.698 123 0.570
36 1.000
41 0.979
42 0.243
Turkey130 0.624 131 0.459 105 0.957
1 0.980 105 0.103
Mexico71 0.699 126 0.545
75 0.991
1 0.980
34 0.281
GGI* Note that the rankings of UNDP GII in 2014 are the latest.
* Latvia is not included because it became a member of OECD in May, 2016

(Source: UNDP, Human Development Report 2014,
WEF, Global Gender Gap Report 2015)41

2.3.4 Comparison of the GGI among APNN member countries
Table 2-13 gives the GGI, released by the WEF in 2015, for APNN member
countries. Among APNN member countries, New Zealand and Australia showed no
gender gaps in educational attainment, ranking first for two consecutive years since 2014.
In terms of political empowerment, the gender gap was closer at 39% for New Zealand,but only 19.3% for Australia. As a result, New Zealand took the 10th position in the GGIrankings, and Australia ranked a much lower 36 th.
In Asia, most countries have relatively low GGI rankings, except for Mongoliain the 56th place. While Mongolia and Sri Lanka topped the list of countries in health andsurvival, this merely indicates that gender gaps do not exist in this area, and should not
be misinterpreted as showing that people in the two countries lead longer and healthierlives. Japan, India, Nepal, Malaysia, Korea and Pakistan did not make it into the top 100
of GGI rankings. Malaysia, Mongolia, Japan and Korea showed wide gender gaps in thearea of political empowerment. Among APNN member countries, India had the smallest
gender gap in political empowerment at 0.433. The GGI scores and rankings of APNN
member countries in 2014 and 2015 are given in Table 2-14.
<Table 2-13 GGI ranks and values of APNN member countries (2015)>
Economic
Health andPolitical
participation & Education
Country
attainment
survival
empowerment
opportunity
Rank Value Rank Value Rank Value Rank Value Rank Value
30 0.768
1 1.000
105 0.970
15 0.390
New Zealand 10 0.782
36 0.733
32 0.766
1 1.000
74 0.974
61 0.193
Australia
GGI(79) 0.690
Taiwan*56 0.709
Mongolia
64 0.704
Bangladesh **83 0.687
Vietnam
84 0.686
Sri Lanka
101
0.670
Japan
108 0.664
India
110 0.658
Nepal
111 0.655
Malaysia
115 0.651
Korea
144 0.559
Pakistan

(43)
22
130
41
120
106
139
121
95
125
143

0.727
0.783
0.462
0.731
0.577
0.611
0.383
0.575
0.634
0.557
0.330

(1)
73
109
114
57
84
125
122
100
102
135

1.000
0.992
0.948
0.941
0.995
0.988
0.896
0.917
0.967
0.965
0.813

(115)
1
95
139
1
42
143
94
110
79
125

0.968
0.980
0.971
0.950
0.980
0.979
0.942
0.972
0.969
0.973
0.967

(35)
117
8
88
59
104
9
70
134
101
87

0.275
0.084
0.433
0.124
0.193
0.103
0.433
0.169
0.051
0.107
0.127

* Taiwan’s data from: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)** Bangladesh has been an INWES APNN member country since 2015
(Source: WEF, Global Gender Gap Report 2015)42

<Table 2-14 The GGI of APNN member countries in 2014 and 2015>(GDI=1: complete equality)

WEF GGI
2014
from 142 countries
Rank
Value
112
0.6458130.7772107
0.6520420.721268
0.697376
0.6915790.6903114
0.6455104
0.6584(50)
0.7144141
0.5522117
0.6403240.7409Country
Nepal
New Zealand
Malaysia
Mongolia
Vietnam *Vietnam
Sri Lanka
India
Japan
Taiwan**Pakistan
Korea
Australia

2015
from 145 countries
Rank
Value
110
0.658
10
0.782
111
0.655
56
0.709
64
0.704
83
0.687
84
0.686
108
0.664
101
0.670
(79)
0.690
144
0.559
115
0.651
36
0.733

* Bangladesh has been an INWES APNN member country since 2015** Taiwan’s data were determined by the Taiwanese government based on the UNDP and WEF
methodology (Source: http://eng.stat.gov.tw/ct.asp?xItem=25280&ctNode=6032&mp=5)(Source: WEF, Global Gender Gap Report 2015)

2.3.5 Recent changes in Korea’s GGI<Table 2-15 GGI evolution of Korea by indicators for past decade (2006~2015)>
Economic
Health andPolitical
participation Education
Year
GGI
&
survival
empowerment
attainment(Number ofopportunity
Participating
Countries) Rank Value Rank Value Rank Value Rank Value Rank Value
2006 (115)2007 (128)2008 (130)2009 (134)2010 (134)2011 (135)2012 (135)2013 (136)2014 (142)2015 (145)changes

92
97
108
115
104
107
108
111
117
115

0.616
96 0.481
0.641
90 0.580
0.615 110 0.487
0.615 113 0.520
0.634 111 0.520
0.628 117 0.493
0.636 116 0.509
0,635 118 0.504
0,640 124 0.512
0.651 125 0.557▲0.035▲0.07782 0.948
94 0.967
94 0.949 106 0.967
99 0.937 107 0.967
109 0.894
80 0.973
100 0.947
79 0.973
97 0.948
78 0.974
99 0.959
78 0.973
100 0.959
75 0.973
103 0.965
74 0.973
102 0.965
79 0.973▲0.017▲0.00684 0.067
95 0.067
102 0.071
104 0.071
86 0.097
90 0.097
86 0.101
86 0.105
93 0.112
101 0.107▲0.040(Source: WEF, Global Gender Gap Report 2015)

43

The WEF began releasing GGI rankings in 2006. Korea’s GGI indicators by area
for the past decade are shown in Table 2-15. Similar to Fig. 2-2, the gender gaps ineducational attainment and health and survival did not grow any narrower. Unlike theaverage changes exhibited by other countries, Korea over the past decade showed agreater bridging of gender gaps in economic participation and opportunity than in politicalempowerment. Specifically, Korea’s gender gap in economic participation andopportunity was reduced by 7.7%, and in political empowerment by 4%. Despite having
the greatest improvement of gender gap in economic participation and opportunity,
compared to other countries Korea still shows the largest gender gap in this area.
Table 2-16 displays changes in Korea’s GGI ranking and scores over the past
five years (2011-2015). By indicator, Korea continues to rank at the top in female literacy
and in female healthy life expectancy. The latter recorded a score of 1.06, indicating that
Korean women have relatively longer life expectancy than men. The ratio of women
holding ministerial positions, which was maintained at around 10% of male counterparts,
fell to 6% in 2015. This was the indicator having the lowest rank at the 130th position. It
is surprising that such a rapid decline occurred under the leadership of the country’s firstfemale president. This is significantly related to Korea’s gender gap in politicalempowerment being reduced by only 4% over the past decade.
Korea’s education fever and high reliance on private education have long beensocial problems. In 2015, Korea took the 116th position in terms of the gender gap in net
secondary enrollment rate, with a number of female students equivalent to only 75% of
the number of male students. The favorable treatment given to boys appears to continue
until the teenage years, such that they have more opportunities for secondary education.
The preference for sons over daughters is decreasing these days, but Korea’s sex ratio atbirth stood at 0.93, giving it a low rank of 128th. The country ranked 116th in wage equality
between women and men for similar work in 2015, with women earning only about 55%
compared to men. For the same year, Korea fell to the 113th place for gender gap inmanagerial and executive positions, with the ratio of women holding managerial andexecutive positions remaining at 10% of their male counterparts.
The recent increase in the number of female candidates passing various state
examinations has induced claims of reverse discrimination against men. However,statistical data provided by the WEF in various areas shows that gender gaps clearly exist,
even though accurate measurements may not be possible. The statistical figures also
indicate that changes do not occur in the short term. Recently, the issue of low birth rate
has come under the spotlight in discussions of welfare policies. Concerns over a decreasein population are connected to a deterioration of national competitiveness caused by thesmaller economically active population. Over the past five years, the female labor force
participation in Korea has remained unchanged at 72-73% of male labor force
44

participation. In other words, the low female labor force participation deserves more
attention than do policies to fight low birth rate.
<Table 2-16 GGI status of Korea (2011~2015)>
Year
2011
2012
2013
2014
2015
0.628
0.635
0.635
0.640
0.651
GGI
Rank/Number of countries
107/135 108/135 111/136 117/142 115/145
0.509
0.504
0.512
0.557
Economic participation value 0.493(Rank)
(117)
(116)
(118)
(124)
(125)
0.73
0.73
0.72
0.72
0.73
Labor force participation
rate ratio (Rank)
(84)
(83)
(87)
(86)
(90)
0.51
0.54
0.52
0.51
0.55
Wage equality between
Economic women and men (Rank)
(126)
(117)
(120)
(125)
(116)
participation Female estimated earned
0.41
0.44
0.44
0.48
0.56
income over male value
&
(113)
(109)
(108)
(109)
(101)
opportunity (Rank)
Female legislators, senior
0.11
0.11
0.11
0.12
0.12
officials and managers over
(111)
(104)
(105)
(113)
(113)
male value (Rank)
0.69
0.69
0.69
0.69
0.83
Female professional and
(87)
(87)
(90)
(98)
(86)
technical (Rank)
(97)
(99)
(100)
(103)
(102)
0.948 0.959
0.959 0.9648 0.965
Education attainment value(rank)
(97)
(99)
(100)
(103)
(102)
1
1
1
1
1
Female literacy rate overmale value (Rank)
(1)
(1)
(1)
(1)
(1)
0.99
0.99
0.99
0.99
0.99
Educational Female net primary
(96)
(94)
(86)
(83)
(83)
attainment enrolment rate (Rank)
0.96
0.99
0.99
0.99
0.99
Female net secondary
enrolment rate (Rank)
(97)
(91)
(82)
(85)
(89)
Female gross tertiary
0.7
0.72
0.72
0.75
0.75
enrolment ratio over male
(110)
(112)
(108)
(114)
(116)
value (Rank)

Subindex

0.974
(78)
0.94
Health andSex ratio at birth (Rank)
survival(124)
1.06
Female healthy life
expectancy over male (Rank)(1)
Political Empowerment value 0.097(Rank)(90)
0.17
Females with seats inparliament over male (Rank) (79)
Political
0.14
empowerment Females at ministerial level
over male (Rank)(75)
Number of years of a female
0.02
head of state (last 50
years)over male value (Rank) (40)
Health and survival value(Rank)

0.973
(78)
0.93
(121)
1.06
(1)
0.101
(86)
0.19
(81)
0.14
(80)
0.02

0.973
(75)
0.93
(119)
1.06
(1)
0.105
(86)
0.19
(85)
0.14
(79)
0.03

0.9730
(74)
0.93
(122)
1.06
(1)
0.1117
(93)
0.19
(91)
0.13
(94)
0.05

0.973
(79)
0.93
(128)
1.06
(1)
0.107
(101)
0.20
(94)
0.06
(130)
0.07

(41)

(42)

(39)

(31)

(Source: WEF, Global Gender Gap Report 2011 ~ 2015)45

2.4 Cross-country comparison of labor force participation rates of the OECD
As mentioned earlier, Korea’s gender gap in educational attainment is only 4%.
That is, the ratio of female educational attainment to male educational attainment is 0.96.
However, the female-to-male ratio in economic participation and opportunity is 0.5,translating to a wide gender gap of 50%. Though women and men have similar
educational levels, women face tougher conditions for economic activity than men do. As
such, we will take a closer look at the labor force participation rate in this section.
The OECD’s labor force participation rates are based on the population of people aged
15 to 64, which is somewhat different from the International Labour Organization (ILO)
criteria, which involve a population of people aged 15 or older. The OECD criteria are
more in use nowadays, and thus this study, too, used OECD statistics. For clarification,
labor force population is an indicator that is calculated based on the employed populationand the unemployed population seeking employment during the survey period; labor
force population does not necessarily mean employed population.
2.4.1 Male and female labor force participation rates among OECD member countries
Table 2-17 shows male and female labor force participation from 2013 to 2015
based on OECD statistics. Latvia was excluded as it joined the OECD only in May 2016.
Over the past three years, the OECD average in labor force participation rose slightly
from 71.0% to 71.3%. What is encouraging is that the female labor force participation
increased from 62.6% to 63.0%.
Iceland, the top ranking country, continued to show a steady increase in labor
force participation, recording a value of 86.6% in 2013 and a higher value of 87.9% in
2015. It showed the smallest gender gap among the countries surveyed, with both men
and women recording values of 80-89% in labor participation. Other countries in northern
Europe with small gender gaps in labor participation have a flexible attitude toward
gender roles, such that both men and women participate in childrearing. Fathers are
required to apply for childcare leave, and wages are likely to remain the same during thisperiod. In Iceland, the mother and father are each assigned five months in the 12-monthchildcare leave, and the remaining period is left to choice. Iceland’s high labor force
participation rates and low gender gaps can be attributed to its effective welfare policies.
Meanwhile, the lowest-ranking Turkey showed a drastic gender gap in labor
force participation in 2015, with men at 77% and women at a mere 35%. Although not as
severe as Turkey, other countries such as Mexico, Chile, Italy, Greece, Japan and Korea
showed large gender gaps in labor force participation.
Korea’s female labor force participation increased from 55.6% in 2013 to 57.9%
46

in 2015, falling short of the OECD average by 5%p and putting Korea at a rank of 30th
among 34 countries. Compared to the top ranking country, Iceland, the difference isalmost 30%p. Meanwhile, female labor participation in Korea’s neighboring country
Japan rose from 65.0% in 2013 to 66.7% in 2015, or 8%p higher than that of Korea,
indicating that women in Japan have more active labor participation than their Koreancounterparts. As pointed out in the gender gap section above, female labor participationin Korea is very low compared to male labor participation. In particular, the fact thatfemale labor participation falls below 60% when equality in educational opportunity has
been achieved goes to show that labor participation by highly educated women is also
low.
<Table 2-17 OECD Female & male labor force participation rate of OECD members (2013~2015)>(unit: %)Country
Australia
Austria
Belgium
CanadaChile
Rep. Czech
Denmark
Estonia
FinlandFranceGermany
GreeceHungary
Iceland
IrelandIsrael
Italy
Japan
Korea
Luxembourg
MexicoNetherland
New Zealand
NorwayPolandPortugal
Slovakia
Slovenia
Spain
SwedenSwitzerland
TurkeyEngland
U.S.A
OECD average

Total
76.4
75.5
67.5
78.0
66.4
72.9
78.1
75.1
74.8
71.1
77.6
67.5
64.7
86.6
70.1
71.6
64.3
74.9
66.6
69.9
64.3
79.7
77.9
78.3
67.0
73.0
69.8
70.5
75.3
81.1
83.3
55.0
77.2
72.8
71.0

2013
Male Female Total
82.4
70.5
76.3
80.4
70.7
75.4
72.7
62.3
67.7
81.4
74.7
77.8
78.1
54.9
66.6
80.5
65.1
73.5
80.6
75.6
78.1
78.6
71.7
75.2
76.0
73.5
75.5
75.5
67.0
71.1
82.6
72.6
77.7
76.9
58.3
67.4
71.0
58.6
67.0
88.8
84.3
86.7
77.2
63.2
69.7
76.0
67.3
72.2
74.4
54.3
64.9
84.6
65.0
75.5
77.6
55.6
67.8
76.3
63.2
70.8
82.5
47.8
63.7
84.7
74.6
79.3
83.1
73.0
79.0
80.4
76.1
78.1
73.9
60.1
67.9
76.5
69.8
73.2
77.2
62.4
70.3
74.2
66.6
70.9
80.9
69.7
75.3
83.3
78.8
81.5
88.6
78.0
83.8
76.3
33.7
55.1
82.9
71.6
77.6
78.7
67.2
72.7
79.6
62.6
71.2

2014
Male Female Total
82.1
70.5
77.0
80.0
70.8
75.5
72.4
63.0
67.6
81.3
74.7
78.0
77.6
55.7
66.8
81.2
65.6
74.0
81.1
75.0
78.5
79.3
71.2
76.6
77.1
73.8
75.9
75.3
67.2
71.2
82.5
72.9
77.6
76.0
59.0
67.8
73.4
60.7
68.6
89.1
84.2
87.9
77.1
62.5
70.1
76.1
68.4
72.2
74.7
55.2
65.0
84.9
66.0
75.9
78.6
57.0
68.3
77.2
64.2
70.9
82.1
46.8
63.4
84.6
74.0
79.6
84.1
74.1
79.0
80.2
75.9
78.4
74.6
61.1
68.1
76.7
70.0
73.4
77.6
62.8
70.9
74.3
67.2
71.8
80.7
69.8
75.5
83.6
79.3
81.7
88.5
79.0
84.1
76.6
33.6
56.1
83.1
72.1
77.6
78.5
67.1
72.6
79.7
62.8
71.3

2015
Male Female
82.7
71.2
80.1
70.9
72.2
63.0
81.8
74.2
77.7
55.8
81.4
66.5
81.6
75.3
80.4
72.9
77.4
74.4
75.3
67.3
82.1
73.1
75.9
59.9
75.3
62.2
90.3
85.5
77.6
62.8
76.1
68.3
75.2
54.9
85.0
66.7
78.6
57.9
76.0
65.6
81.8
46.6
84.6
74.7
84.2
74.1
80.5
76.2
74.8
61.4
76.7
70.3
77.5
64.3
75.4
67.9
80.9
70.0
83.5
79.9
88.5
79.8
77.0
35.0
82.8
72.5
78.5
66.9
79.7
63.0

* Latvia is not included because it became a member of OECD in May, 2016
(Source: OECD.Stat, Labour force participation rate (indicator).
doi: 10.1787/8a801325-en (Accessed on 15 July 2016)47

Labor force participation rates by highly educated men and women among
OECD countries for the year 2011 to 2013 are listed in Table 2-18. As defined by theOECD, persons who have received tertiary education are considered highly educated. In
the Korean context, this is equivalent to a two-year college education or higher. Labor
force participation by highly educated persons is, as expected, higher than the overall rate.
In particular, the OECD average for labor force participation by highly educated womenis 83%, which is 20%p higher than the overall rate for women.
<Table 2-18 Labor force participation rate of highly educated* female and male of OECDmembers (2011~2013)>(unit: %)Country
Australia
Austria
Belgium
CanadaChile
Rep. Czech
Denmark
Estonia
FinlandFranceGermany
GreeceHungary
Iceland
IrelandIsrael
Italy
Japan
Korea
Luxembourg
MexicoNetherland
New Zealand
NorwayPolandPortugal
Slovakia
Slovenia
Spain
SwedenSwitzerland
TurkeyEngland
U.S.A
OECD average

Total
86.7
88.6
87.1
85.9
83.9
85.3
90.4
86.9
87.8
88.1
90.1
85.9
82.5
93.0
87.0
86.2
83.3
82.4
79.2
88.1
83.3
89.9
87.5
91.8
88.7
90.6
86.1
90.7
89.2
92.2
91.1
82.4
86.5
84.1
87.1

2011
Male Female Total
92.7
81.9
86.9
91.7
84.7
89.2
90.1
84.5
87.6
89.4
83.0
85.9
91.9
76.0
88.1
93.7
76.6
85.8
92.6
88.6
90.6
90.9
84.6
87.5
91.1
85.4
87.8
91.4
85.3
88.9
93.1
86.3
90.0
88.7
82.9
85.8
88.2
78.2
83.1
95.2
91.5
93.4
92.1
82.8
86.1
89.2
83.6
88.6
88.4
79.3
84.1
95.2
69.3
82.4
92.4
62.4
79.4
92.4
83.1
87.8
91.6
74.2
84.3
92.3
87.2
90.4
93.2
83.3
87.6
93.2
90.6
91.7
92.7
86.0
89.0
91.8
89.8
91.5
91.4
81.8
85.2
91.9
89.9
90.3
91.9
86.7
89.7
93.8
91.1
92.5
95.5
84.8
91.8
89.3
72.0
82.3
91.3
82.0
87.2
89.2
79.6
84.0
91.7
82.6
87.5

2012
Male Female Total
92.9
82.0
86.0
92.1
85.7
89.4
90.4
85.1
87.9
89.6
83.0
86.0
95.9
81.2
93.3
78.4
87.0
93.1
88.7
90.6
91.6
85.2
87.8
91.0
85.4
87.8
92.2
86.1
89.1
93.3
86.1
89.9
88.5
83.1
83.3
90.0
78.0
83.2
93.5
91.4
81.7
85.9
92.6
85.4
88.8
88.7
80.4
83.8
95.0
69.6
83.6
92.5
63.0
79.7
92.8
81.7
88.1
92.5
75.4
84.0
92.8
87.7
91.4
92.9
83.6
89.1
93.6
90.2
91.2
93.2
86.1
89.3
92.2
91.0
90.9
90.6
81.0
84.9
91.4
89.5
89.0
92.4
87.2
89.8
94.0
91.3
92.9
95.9
85.9
91.9
89.2
72.5
83.4
92.3
82.3
87.4
89.3
79.5
83.8
92.1
82.8
87.6

2013
Male Female
91.9
81.3
91.7
86.7
90.9
85.3
89.7
83.0
94.7
79.6
92.6
89.1
92.6
85.0
90.8
85.5
92.3
86.3
93.2
86.1
84.8
81.8
90.0
78.2
91.1
91.4
81.5
93.0
85.5
88.2
80.4
95.6
71.3
92.4
64.1
92.5
83.3
92.5
75.2
93.5
89.1
93.9
85.2
93.0
89.7
93.5
86.3
91.7
90.4
90.8
80.1
90.7
87.7
92.2
87.5
94.5
91.6
95.5
86.7
90.3
73.7
92.6
82.6
89.4
79.0
92.1
83.3

* Latvia is not included because it became a member of OECD in May, 2016
(Source: OECD Employment Outlook 2013, 2014, 2015)48

Some data for Iceland are not available, but it can be inferred that labor force
participation rates of highly educated men and women fall in the 90-99% range. In
Norway, Portugal, Slovenia and Sweden, labor force participation rates by highly
educated women are approximately 90% or higher. Regardless of gender, a vast majorityof highly educated persons participate in economic activities. Turkey, where the female
labor force participation rate was only 33.7% in 2013, recorded a value of 73.7% for labor
force participation by highly educated women.
In Japan and Korea, the gender gap in labor force participation grows more
prominent among highly educated persons. In 2013, the labor force participation byhighly educated men surged to 95.6% in Japan, and 92.4% in Korea. Smaller increases inlabor force participation by highly educated women, with values of 71.3% in Japan and64.1% in Korea, contributed to a broader gender gap. Among OECD member countries,
Korea has had the lowest labor participation rate by highly educated women for the past
several years, indicating that the country is extremely inefficient at utilizing humanresources.
2.4.2 Korea’s labor force participation rate by highly educated womenThis section takes a closer look at labor force participation rates in Korea, which
has the lowest labor force participation rate by highly educated women among OECDmember countries. It must be noted first that the labor force participation rates in thissection are based on the ILO criteria (population aged 15 or older), and are different fromthe labor force participation rates based on the OECD criteria (population aged 15 to 64)
that have been used until now. However, this difference is negligible in understanding
general correlations.
<Table 2-19 Labor force participation rate of Korean by sex, field of specialty, andmarital status (2014)>(unit: %)Natural science

Engineering

Medical science

Othersaverage 72.7

average 88.4

average 80.0

average 74.7

Male

FemaleMale

FemaleMale

FemaleMale

Female

88.9

59.5

92.8

66.1

92.8

74.6

86.4

65.7

S

M

S

M

S

M

S

M

S

M

S

M

S

M

S

M

84.9 90.3 84.6 50.7 88.0 94.7 86.1 55.1 87.5 94.8 91.0 65.1 82.9 87.7 84.8 56.1
* S: Single (not married), M: Married* Note that values are from ILO (of 15 years or older population) which is different from theOECD values where the population of ages 15 to 64.
(Source: 2014 Re-evaluation Report of Statistics for nurturing and utilizing women in science and technology)

49

Korea’s labor force participation rates by academic major, gender and marital
status for the year 2014 are listed in Table 2-19. By major, engineering majors have thehighest labor force participation at 88.4%, and natural science majors the lowest at 72.7%.
The higher labor force participation by engineering majors compared to medical andpharmaceutical majors can be attributed to the larger economically active population in
the former (3,124,913 in 2014) than the latter (248,014 in 2014). Gender gaps in labor
force participation across all majors were severe, but the gap was extremely wide at
29.4%p for natural science majors. This was higher than the gap of 26.7%p forengineering majors, 18.2%p for medical and pharmaceutical majors, and 20.7%p forother majors.
In Korea, the gender gap in labor force participation differs significantly
according to marital status. Married men have higher labor force participation than single
men across all majors. For women, however, the labor force participation rate drops by
about 30%p across all majors after marriage. By major, the gender gap in labor force
participation is relatively small before marriage, but grows to about 40%p after marriage.
While single women in medical and pharmaceutical majors recorded a higher labor force
participation rate than their male counterparts, the same rate by married women falls
below that of married men by as much as 30%p. This prevalent gender gap even among
medical and pharmaceutical majors, who are able to take specialized jobs, shows that
Korean society holds many stereotypes about the role of a married woman. Rather thanseeking solutions to the problem of low birth rate, it will be more efficient to develop
measures that encourage the economically active population, especially highly educatedwomen, to play a more active role in the workforce.
<Table 2-20 Labor force participation rate of the science and engineering population of
Korea by age group (2014)>(unit: %)

Age

20~29

30~39

40~49

50~59

Male

82.5

94.8

96.9

92.6

Female

77.4

58.2

59.4

53.4

Male

85.5

96.4

97.5

92.9

Female

81.7

60.2

62.0

63.7

Specialty/Gender

Natural science

Engineering* Note that values are from ILO (of 15 years or older population) which is different from theOECD values where the population of ages 15 to 64.
(Source: 2014 Re-evaluation Report of Statistics for nurturing and utilizing women in scienceand technology)

50

The gender gaps in labor force participation by marital status are shown in labor
force participation rates by age as well. Table 2-20 shows the labor force participation
rates by men and women with majors in natural science and in engineering by age.
Considering that the average age of first marriage is 32.6 for men and 30.0 for women,
men and women in their 20s have a small gender gap, as both show values of around 70 to
80% for labor force participation; however, for men over 30, this rate exceeds 90%, while
for women in the same age group, the rate drops below 60% for natural science majors andto the 60% range for engineering majors, representing a huge gender gap. This is attributable
to increased burdens of housework, childbirth and childrearing after marriage, which makewomen’s participation in the labor force difficult. Moreover, they lead to a chain of social
problems such as an increase in the average age of first marriage among women and a greater
avoidance of childbirth.

51

2.5 Cross-country comparison based on the overview of female scientists by
UNESCOThe UNESCO Institute for Statistics (hereinafter referred to as UIS) has been
conducting a biannual statistical survey since 2004. This section examines the status offemale scientists reported in 2015 by the UIS (statistics provided for 2013); unfortunately,
the report contains insufficient data on female scientists in Asian countries. Moreover, it
should be noted that science fields in this survey are defined to include not only naturalsciences and engineering fields but also social sciences and humanities. Therefore, theratios regarding women in science suggested by the UIS are generally higher than thoseby our study.
According to the UIS analysis, as can be seen in Table 2-21, the average ratio of
female scientists globally is 28.4%. By region, this measure was highest in Central Asia
at 47.1%, as was the case in 2011. The ratio of female scientists in Latin America and the
Caribbean increased by 0.5%p to 44.3%, and decreased in Central Asia and Eastern by
0.5%p to 39.9%. In East Asia and the Pacific region, to which Korea belongs, the ratio of
female scientists was the lowest in 2011. This region showed an increase from 19.7% to22.6%, while Southwest Asia had the lowest ratio following a decrease from 20.0% to
18.9%.
<Figure 2-3 Ratio of women researchers by region (2013)>(Source: UNESCO Institute for Statistics, October 2015)

Figure. 2-3 shows the representation of women as a share of total researchers
around the world by region using different colors. Vivid colors represent a higher ratio of
female researchers, while grey denotes no statistical data available.

52

<Table 2-21 UIS ratio of female researcher by region (2013)>(unit: %)UIS Region
World average
Central Asia
Latin America / Caribbean
Central and Eastern Europe
United Arab Republic
North America / Western Europe
Africa of Southern Sahara
Southern and Western Asia
Eastern Asia and Pacific

Ratio of female researcher
2011
2013
30.0
28.4
45.5
47.1
43.8
44.3
40.4
39.9
37.9
36.8
32.1
32.0
29.2
30.0
20.0
18.9
19.7
22.6

(Source: UNESCO Institute for Statistics, October 2015)

Table 2-22 gives the ratios of female researchers as provided by UIS for APNN
member countries; data for recent years, however, are irregular. Compared to 2011,
Mongolia and Pakistan had a slight decrease, while Japan and Korea increased by 0.8%p
and 1.5%p, respectively. In particular, as mentioned above, the ratios of female
researchers as determined by the UIS include researchers in the fields of humanities,
social sciences and medical science, and thus it should be stressed once again that theactual ratios of female researchers in pure natural sciences and engineering would besignificantly lower than the UIS figures.
<Table 2-22 Female researcher ratio of APNN member countries>(unit: %)Country (year)
New Zealand (2001)
Mongolia (2013)
Bangladesh (1997)*
Vietnam (2011)
Sri Lanka (2010)
Japan (2013)
Malaysia (2012)
Nepal (2010)
India (2010)
Korea (2013)
Pakistan (2013)

Ratio of female researcher
52.0
48.9
14.0
41.7
36.9
14.6
49.9
7.8
14.3
18.2
29.8

* Bangladesh has been an INWES APNN member country since 2015
(Data do not exist for Australia and Taiwan)(Source: UNESCO Institute for Statistics, October 2015)

53

54

3. Survey of APNN Member Countries on
Gender Barrier3. Survey of APNN Member Countries on Gender Barrier
3.1 Discussions of gender barriersThis section examines various gender-related challenges experienced by female
scientists and engineers of APNN member countries. Emerging industries such as ICT
convergence, new energy, new materials and biohealth have an increasing demand forfemale human resources. However, these industrial needs remain unmet because thesupply falls short of the demand. This shortage is due to the gender barriers prevalent inall stages, from talent nurturing and job-seeking to re-entry after a career break.
Gender barriers refers to the experiences of gender discriminations, which function
as hindrances to gender equality. These include institutional/customary barriers andconscious/unconscious barriers. Specific examples are gender role stereotypes, unfairness
in employment and promotion, work-life balance and responsibility for family, and otherunfair treatment.
3.1.1 Gender role ideology
Despite the increase in the number of female scientists around the world, thestereotypical notion is that men are more suited for jobs in science and engineering.
Gender role ideology is a set of beliefs about the proper roles of men and women. It is
exhibited as an assertion on the roles that men and women should assume, and involves
gender stereotypes regarding characteristics, interests and behavior of men and women.
An individual’s gender role ideology reflects his or her tendency to uphold genderequality or gender discrimination. As such, those with a more traditional gender roleideology are often regarded as sexists (Campbell, Schellenberg, & Senn, 1997) 1.
Overt sexism has mostly disappeared thanks to the recent implementation ofgender equality policies and expanded discourse on gender issues. This, on the other hand,
has led to more widespread occurrences of covert sexism and subtle sexism. For instance,
women are employed only in certain professions and kept below a certain rank, orassigned less important tasks so that they have lower chances of promotion. Benevolent
sexism is a chivalrous attitude toward women that appears favorable but is in fact
discriminatory (Glick & Fiske, 1997) 2. We can see that attitudes toward gender are multidimensional and varying over time (Kim & Chung, 1999) 3.

1 Campbell, B., Schellenberg, E.G., & Senn, C.Y. (1997). Evaluating measures of contemporary sexism. Psychologyof Women Quarterly, 21, 89-102.
2 Glick, P., & Fiske, S.T. (1997). Hostile and benevolent sexism: Measuring Ambivalent sexist toward women.
Psychology of Women Quarterly, 21, 119-135.
3 Yang-hee Kim, Kyung-ah Chung. (1999). Development of the Korean Gender Egalitarianism Scale. Korean
Women’s Development Institute573.1.2 Unfairness in employment, wages and promotion (glass ceiling)
According to the Ministry of Science, ICT and Future Planning, 1 the number ofwomen, at 43,662, accounts for only 18.9% of the total human resources in the fields ofscience and technology research in Korea. The ratio of female R&D human resources indomestic companies is a mere 17.5%. Developed countries such as the United Kingdom,
Germany and France have higher ratios of 37.7%, 26.7% and 25.6%, respectively. A
possible cause is that Korea has fewer female students majoring in science andengineering. The number of female students, at 228,473, is only 28.4% of the total numberof students in science and engineering. The ratio of female students in natural sciences is
51.1%, higher than the male ratio, but is extremely low in engineering majors at 18.2%.
This ratio drops even further in graduate programs. In the natural sciences, this ratio is51.2% in master’s programs and 36.7% in doctoral programs. In engineering, it is 18.6%
in master’s programs and 10.4% in doctoral programs. In most Asian countries, boys
rather than girls are encouraged to pursue majors in STEM.
In science and engineering, the manufacturing-based industrial structure has
centered on men for a long time, making it difficult for women to survive amidst stiffcompetition. The preference of companies for male candidates is exhibited in theemployment gender gap. In 2014, the gender gap in the employment of graduates of fouryear universities was 4.8% in engineering, 2.1% in natural science, 0.9% in thehumanities, 0.5% in social sciences and –0.6% in medical and pharmaceutical fields. In
all fields except medical and pharmaceutical, more men were employed than women. The
gender gap in engineering fields was wider by as much as 4.3%p compared to gender
gaps in the humanities and social sciences.
According to data on the employment of science and technology researchpersonnel by gender given in the 2014 Report on the Utilization of Female Scientists andEngineers (Ministry of Science, ICT and Future Planning, 2015), the percentages of men
and women were 81.3% and 18.7%, respectively. By employment contract, 55.0% of
women were hired as regular/permanent employees, and 45.0% as non-regular/temporary
employees. As for men, 78.7% were hired as regular/permanent employees, and 21.3%
as non-regular/temporary employees. These figures indicate that women have less job
stability. The wages received by female employees reflect their shorter years ofexperience and lower status. In the aforementioned survey, new female employees onregular contracts earning at least 35 million won a year accounted for 53.2%, which islower than the ratio of their male counterparts at 61.4%. In the case of new nonregular/temporary employees, 41.1% of men and 44.0% of women earn less than 20
million won a year. In the 2014 survey, the ratio of women holding managerial positions

1 Ministry of Science, ICT and Future Planning (2015). 2014 Survey on the Utilization of Female Scientists andEngineers. Korea Center for Women in Science, Engineering and Technology (WISET).

58

was only 7.3%, and the ratio of women who advanced to higher positions was 12.9%,
demonstrating the presence of a glass ceiling in the fields of science and technology.
“Glass ceiling” 1 is a term used to refer to an invisible barrier that prevents
women from assuming high-ranking positions regardless of their levels of achievement
or strengths. 2 “Glass” means that the barrier is not visible but clearly present, while“ceiling” implies that women cannot easily advance to higher positions. 3 In 1989, theterm came under the spotlight when Secretary Elizabeth Dole of the US Department ofLabor created the Glass Ceiling Commission 4. This commission found in 1991 that theglass ceiling persisted in companies with federal government contracts even thoughgender equality principles were supposed to be followed in employment. The report
defines glass ceiling as “those artificial barriers based on attitudinal or organizational biasthat prevent qualified individuals from advancing upward in their organization into
management-level positions." The federal government introduced the Office of Federal
Contract Compliance Programs (OFCCP) in 1992, so as to remove obstacles that prevent
women and minority groups from rising to management-level positions in government
agencies and companies with federal government contracts 5.
In the United States, where women hold 50% of mid-level managerial positions,the glass ceiling mostly applies to high-ranking executive positions. However, in Korea,
it is present from middle-level management. Among OECD member countries, Korea has
the highest glass ceiling. Women remain at low ranks in organizations, while men
dominate higher ranks, resulting in vertical segregation. Due to the glass ceiling, womenare discouraged to make efforts to climb the ladder and can adopt a pessimistic attitude
toward their careers as they do not feel valued.
3.1.3 Work-life balance and career break
Most APNN member countries stick to traditional gender role ideology, underwhich women have responsibility for taking care of children and family. Women face agreater burden of maintaining work-life balance since they end up playing a more activerole in childbirth, childrearing and housework. In Korea, many women voluntarily quit
their jobs to concentrate on family. In Korea, the female employment rate is 68% for

1 Morrison, A.M (1992). The New Leaders. San Francisco: Jossey-Bass. Morrison, A.M., White, R.P., Van Velsor, E.
(1987). Breaking the Glass Ceiling. Reading, MA: Addison Wesley.
2 Lampe, A, (2001). Review of the book Gender in the Workplace: A Case Study Approach. Gender, Work andOrganization. 8(3), pp.346-351.
3 Davies-Netzley, S. A. (1998). Women above the Glass Ceiling: Perceptions on Corporate Mobility and Strategies
for Success. Gender and Society, Vol. 12, No. 3, p. 340
4 Federal Glass Ceiling Commission. Solid Investments: Making Full Use of the Nation's Human Capital. Washington,
D.C.: U.S. Department of Labor, November 1995.
5 Korea’s employment policies implemented in 2006 were based on the US OFCCP, but have been extremely
ineffective in comparison.

59

women in their late 20s (25-29) but it drops to 54% among women in their 30s. This is instark contrast to the increase in male employment, to as high as 92.1%, in their 30s. One
out of every five married women in Korea gives up her career due to marriage, childbirthor childrearing. The number of women resuming their careers after childbirth andchildrearing is significantly low in the fields of science and engineering. A graph of
economic participation rate of women belonging to the productive population follows an
M-shape, indicating a return to the workplace in their 40s. However, a graph of womenin science and engineering follows an L-shape. That is, they fail to return once they giveup their careers.
Social costs incurred due to career breaks by the female workforce amount to15.5 trillion won, which is similar to the annual government budget for research anddevelopment. Worse still, women with career breaks find it extremely difficult to become
re-employed in a decent job. Even if they manage to become re-employed, most receive
lower wages or assume lower ranks. Only 47.3% of women managed to return as
regular/permanent employees, and 22.2% were hired as temporary employees. Among
women who used to earn a monthly average of two million won, 50.3% were employedin positions paying 1-2 million won a month, and 34.0% received less than 1 million (Yun,2015) 1.
A career break is a period of time out from one’s career. In Korea, women withcareer breaks are defined as “women unable to continuously gain years of career
experience due to marriage, pregnancy, childbirth and childrearing” 2. This definition has
been criticized for neglecting resignation arising from dissatisfaction with working
conditions or gender discrimination, and for assigning women the role of primary
caregiver in the family (E.g.: Oh, 2015) 3 . In fact, many women leave their jobs toconcentrate on their children or family because they do not see a future in thediscriminatory structure. Against this backdrop, it is essential to examine the causes ofcareer breaks, so as to prevent such occurrences among women. If we consider careerwith a continuous growth without breaks as normal, the typical female career in Korea
can be seen as deviating from the normal career path. Recently, some men are also
experiencing career breaks caused by frequent job changes and increasing cases of
early/honorary retirement. Instead of perceiving female career breaks as abnormal, we

1 Jong-tae Yun (2015). The Need to Establish the Busan Wemenomics Center. Wemenomics Center Forum to Support
the Nurturing of Busan’s Female Talents in Science and Engineering. Organized by the Federation of Busan Scienceand Technology. 2015.12.
2 Minister of Gender Equality and Family (2009). The First Basic Plan to Promote Economic Activities of Women
with Career Breaks.
3 Eun-jin Oh (2015). The Re-employment of Women with Career Breaks and Related Policies: Exploration of New
Strategies, Organized by the Korean Women’s Development Institute, presentation material for Issues in
Supporting Policies for the Re-employment of Women with Career Breaks at the 96th Gender Equality Policy Forum.
2015.8.28.

60

should implement policies that support their re-entry into the labor market under morefavorable conditions.
3.1.4 Other unfair treatment
Female scientists and engineers face unfair treatment such as exclusion fromvarious decision-making processes, disadvantages in research funding or project
management, and sexual harassment. In the aforementioned survey by the Ministry of
Science, ICT and Future Planning (2015), the ratio of women participating in humanresources committees in public research institutions was only 5.7%. That is, mostdecisions on hiring and promoting human resources are left to men. In addition, the ratioof women overseeing R&D projects was a mere 7.8%. This ratio dropped even further for
R&D projects with larger budgets.
There are illusions such as: “There is no gender discrimination amongprofessional vocations,” and “All practices in the fields of science and technology are
rational.” Women who have gained reputations in their professions after beating off stiffcompetition from men are often told to rely on their individual capacity, demonstrating
the society’s lack of interest in resolving structural gender discrimination. However, a
study by MIT 1 showed that the most important reason for discrimination against womenin terms of wages/rewards/external funding and exclusion from leadership positions is
the collective ignorance of discriminatory practices. The low ratio of female employees
despite the increase in female students majoring in mathematics or science can be
attributed to the poor working conditions for women and to various forms of sexual
discrimination in the workplace. Many female scientists and engineers, working inlaboratories that are not woman-friendly, face the dilemma of whether to give up theirresearch or to pay less attention to family.

1 MIT (1999). A Study on the Status of Women Faculty in Science at MIT.

61

3.2 Survey method
3.2.1 Survey respondents, method and period
The survey was conducted in 13 member countries (Nepal, New Zealand, Malaysia,
Mongolia, Bangladesh, Vietnam, Sri Lanka, India, Japan, Taiwan, Pakistan, Korea, andAustralia) of the APNN, asking female science and engineering professionals about theirperception of the gender barriers. Of the 13 countries in which the survey was performed,
12 countries except Australia agreed to participate in the survey via e-mail. The respective
networks (WISE-Nepal, IPENZ, IEM, WSTEM, WISE-Bangladesh, VAFIW, WISE-Sri
Lanka, WISE-India, JNWES, TWiST, WISTEP, KWSE) were utilized to ask respondents
to take either online or offline surveys. In most countries, respondents were able to choose
either Korean or English as the primary language, while Japan and Mongolia distributed
offline surveys in their mother tongues.
The survey period, during which the instructional e-mail was sent, was from May
15 to June 30, 2016. An instructional e-mail was first sent to member countries on April 18,
about one month prior to the survey period. Countries that participated in offline surveys
compiled and submitted their results by e-mail, while the results of online surveys were
downloaded via Google Forms. Statistical analysis was performed on both online andoffline results for Korea and Japan. Malaysia and New Zealand only responded online.
While India, Bangladesh, Sri Lanka, Pakistan and Vietnam only responded offline, online
results were combined if such nationalities were also present among offline respondents.
3.2.2 Survey tool: Questionnaire composition
The survey consisted of questions on general characteristics of respondents andtheir perception of the gender barriers. The nine questions on general characteristics weresimilar to those of the previous survey, covering year of birth, year of college admission,
major, career, position/rank, duration of career break, marital status, number of children
and nationality (see Table 3-1).
The 12 questions on the gender barriers were comprised of three sub-scales. First,
there were four questions on the perception of the discriminatory reality in the relevantsociety. For instance, respondents were asked whether boys are more actively encouraged
than girls to pursue majors in STEM, and whether it is more difficult for women to findjobs in STEM than men. Second, there were four questions on the discriminatory
experiences of respondents. The respondents were asked whether they have experienced
discriminations or disadvantages because of their gender in participating or supervisingresearch projects, and whether the struggle to maintain a healthy work-life balance
functioned as a career handicap. Third, there were four questions on the gender roleideology of respondents. The questions covered the role of breadwinner in the family, thecapacity to take care of children, and the balance of power between husband and wife.
62

Finally, there were three questions on career prospects, policy demands, and the conceptof gender equality.
3.2.3 Analysis of survey data
Responses were coded excluding invalid or insufficient answers. For open-ended
questions, similar or common answers were combined together and pre-coded. To
ensure that the responses were properly coded, 20 questionnaires were randomly selected
and checked. Any errors, if detected, were corrected. Next, SPSS Statistics version 23.0
was used to perform the following analyses.
① Basic analysis: Frequency and descriptive statistical analysis- Frequency and descriptive statistical analysis were performed to examine the generalcharacteristics of respondents.
- Frequency and descriptive statistical analysis were again performed for each question
on the gender barriers, career prospects, policy demands, and the concept of genderequality.
② Differential and correlational analysis- An independent t-test and one-way ANOVA were employed to analyze the generalcharacteristics of respondents and differences in perceptions of the gender barriers.
The analyses were performed on the individual items as well as sub-scales such as
the perception of discriminatory reality, discriminatory experiences and gender roleideology. Duncan test was performed to allow multiple comparisons between groups
if required.
- An independent t-test and one-way ANOVA were employed to analyze the generalcharacteristics of respondents, career prospects by country, policy demands and theconcept of gender equality. Duncan’s test was performed to allow comparison
between groups if required.
- Pearson’s correlation was used to examine the relationships between continuous
variables, including the perception of discriminatory reality, discriminatory
experiences, gender role ideology, career prospects and policy demands.
③ Comprehensive analysis- Variables influencing major dependent variables were examined and multiple
regression analyses were performed to determine their relative contributions.

63

<Table 3-1. Survey questions>Classifications

Question① Year of birth② Year entering college③ Major field④ Occupation

Personal Information⑤ Position/status⑥ Duration of career break⑦ Marital status⑧ Number of children⑨ Nationality① Boys are encouraged more than girls to go into the STEM field.

Perception of
discrimination

Experiencesof
Genderdiscrimination
barriers② It is more difficult for a woman to get a job in the STEM field than for aman even with the same qualifications.
③ Becoming a tenured professor, being promoted or becoming a principal
investigator is more difficult for female scientists than for male scientists.
④ Women in STEM generally receive less pay for equal work, comparedwith their equally-qualified male colleagues.
① I have experienced disadvantages in leading or participating in research
projects because I am a woman.
② I have experienced disadvantages in receiving research funds or
scholarships because I am a woman.
③ I have experienced sexual harassment or unfair treatments sometime in mycareer.
④ Balancing work and life (marriage and family) has been a handicap for me.

Gender role
stereotype

Career outlook
Policy needs
Equality concept

64① Primary breadwinners (who take care of financial obligations) of
households should be men.
② Women are born to have a way of caring children that men are not capableof in the same way.
③ In order to maintain the order and peace of a family, the husband shouldhave greater power and authority than the wife.
④ In a relative sense, men are rational while women are emotional and thus,
they ought to complement each other by doing what is appropriate forthemselves.
I believe things will turn out fine in my future career.
It is crucial to have strong policy support to solve gender inequality in the
STEM field.
I believe gender equality will be fully achieved only if women are given
equal opportunities as men.

4. Results of the Survey on Genderbarriers
Countries

Among

APNN

Member4. Results of the Survey on Gender barriers Among APNN
Member Countries
4.1 General respondent profiles
In total, 1,379 valid responses were collected from 12 member countries up toJune 30, 2016. With the exception of New Zealand and Taiwan, each country recorded
about 100 female respondents belonging to science and engineering professions. Table 41 gives the profile of respondents by nationality, age, marital status, number of children,
profession, major, and duration of career break. Details are provided below.
① Nationality
Out of the 1,379 respondents, Malaysia had the highest number of participants at 175,
followed by Mongolia at 161, Japan at 138, and Korea at 135. Vietnam, Sri Lanka,
Pakistan, Bangladesh, Nepal and India had about 100 participants each. The numberof respondents from New Zealand and Taiwan were 68 and 79, respectively. Thosewith unspecified nationalities was 32 (2.3%).
② Age
By age, a large proportion of respondents was in their 20s, amounting to 541 (39.3%).
This was followed by 414 in their 30s (30.1%), 211 in their 40s (15.3%), and 211 intheir 50s (15.3%). The average age of respondents was 35.36.
③ Marital status
The number of married respondents at 714 (51.8%) was greater than that of single
respondents at 577 (41.8%). The number of divorced or separated respondents was 52(3.8%), while 36 were in the ‘other’ status (2.6%). Those who selecteddivorced/separated/other under marital status were combined into the ‘single’ groupin the analysis.
④ Number of children
A large proportion of respondents, or 723 persons (53.1%), did not have any children.
This was followed by 306 with two children (22.5%), 233 with one child (17.1%), and100 with three or more children (7.3%). The average number of children was 0.84.
⑤ Occupation
The available options provided were student, teacher/professor, researcher, healthcare
professional, engineer (company or research institute), and other. The top answer wasteacher/professor at 358 (26.0%), followed by engineer at 337 (24.5%), researcher at
227 (16.5), healthcare professional at 87 (6.3%), and other at 149 (10.8%).
67

⑥ Major field of study
The question on major was given in open-ended form, and assigned codes based on acollege major classifications provided by the Ministry of Education. As a result,engineering majors accounted for 47.9% at 647. This was followed by natural sciences
at 319 (23.6%), medical and pharmaceutical at 190 (14.1%), social sciences at 130(9.6%), teaching at 39 (2.9%), and humanities at 15 (1.1%).
⑦ Duration of career break
The respondents were asked if they had a career break due to pregnancy, childbirth or
any other reason. There were 665 respondents (49.5%) without any career break. 271(20.2%) had rested for 3 years or more, 156 (11.6%) for 1~2 years, 138 for 2~3 years(10.3%), and 113 (8.4%) for less than a year. The average duration of a career break
was 18.07 months.
<Table 4-1. Participants of the survey>(unit: Person, %)Classifications
Nationality
Nepal
New Zealand
Malaysia
Mongolia
Vietnam
Sri Lanka
India
Japan
TaiwanPakistan
Republic of Korea
Bangladesh
OthersAge
29 or below
30～39
40～49
50 or above
Average
Marital status
SingleMarriedDivorced
Other

68

Number of Respondents

%

1,379
94
68
175
161
100
101
93
138
79
102
135
101
32

6.8
4.9
12.7
11.7
7.3
7.3
6.7
10.0
5.7
7.4
9.8
7.3
2.3

541
414
211
211

39.3
30.1
15.3
15.3
35.36 years

577
714
52
36

41.8
51.8
3.8
2.6

No. of childrenNone12
3 or more
AverageOccupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Major field of study
Humanities
Social Science
Natural Science
Medicine & Pharmacology
Arts & Physical Ed.
Teaching Profession
Engineering Science
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
Average

69

723
233
306
100

53.1
17.1
22.5
7.3
0.84 person

219
358
227
87
337
149

15.9
26.0
16.5
6.3
24.5
10.8

15
130
319
190
11
39
647

1.1
9.6
23.6
14.1
.8
2.9
47.9

665
113
156
138
271

49.5
8.4
11.6
10.3
20.2
18.07 months

4.2 Cross-country comparison of the gender barriers in 12 APNN member countries
4.2.1 Descriptive statistical analysis<Table 4-2. Average on each item>(unit: Points)

Classifications① Question

Boys are encouraged more than girls to go into the STEM
1 field.
It is more difficult for a woman to get a job in the STEM field②
2 than for a man even with the same qualifications.
PercepBecoming a tenured professor, being promoted or becomingtion of 3 a principal investigator is more difficult for female scientists
than for male scientists.
discrimination 4 Women in STEM generally receive less pay for equal work,
compared with their equally-qualified male colleagues.
AverageI have experienced disadvantages in leading or participating
5 in research projects because I am a woman.
③
I have experienced disadvantages in receiving research funds
6 or scholarships because I am a woman.
ExperiGender ences of 7 I have experienced sexual harassment or unfair treatments
sometime in my career.
barriers discrimiBalancing work and life (marriage and family) has been anation8 handicap for me.
AveragePrimary breadwinners (who take care of financial
9 obligations) of households should be men.
Women are born to have a way of caring children that men
10 are not capable of in the same way.
④
In order to maintain the order and peace of a family, theGender 11 husband should have greater power and authority than the
role
wife.
ideologie
In a relative sense, men are rational while women are
12 emotional and thus, they ought to complement each other by
doing what is appropriate for themselves.
Average⑤Career outlook 13 I believe things will turn out fine in my future career.

It is crucial to have strong policy support to solve gender
14 inequality in the STEM field.
I believe gender equality will be fully achieved only if
Equality concept 15 women are given equal opportunities as men.
⑥Policy needs

AverageStandard
deviation

2.46

1.219

2.51

1.180

2.50

1.235

2.93

1.318

2.60
3.00

1.272

3.32

1.221

3.30

1.356

2.60

1.217

3.05
3.55

1.343

3.34

1.347

3.78

1.327

2.92

1.387

3.40
3.70

1.044

4.07

1.070

2.13

1.149

note : ① The responses to questions were measured with a five-point Likert scale (1.Strongly agree, 2.Somewhat
agree, 3.Neutral, 4. Somewhat disagree, 5. Strongly disagree)② Perception of discrimination : Lower score means higher perception of discrimination③ Experience of discrimination : Lower score means more discrimination experienced④ Gender role ideologies : Higher score means more progressive⑤ Career outlook : Higher score means a more positive outlook⑥ Policy needs : Higher score means higher needs for policy support

70

All of the 15 questions excluding those on the general characteristics of
respondents, were evaluated on a five-point Likert scale (see Table 4-2). Among those,
12 questions on the gender barriers were comprised of three sub-scales: perception of thediscriminatory reality, discriminatory experiences, and gender role ideology. A lower
score on perception of discriminatory reality and discriminatory experiences indicates ahigher level of discrimination. A higher score on gender role ideology indicates a moreprogressive attitude. The survey included one question each on career prospects, policy
demands, and the concept of gender equality. The responses to career prospects werereverse coded such that a higher score implies a more positive attitude. Similarly, a higherscore for policy demands indicates greater demands. Figure. 4-1 presents the averagevalue by question.
The average score of 2.60 for the perception of discriminatory reality indicatesthat respondents do not feel severe discrimination existed. Out of the four questions, themost severe discrimination was felt for “Boys are more actively encouraged than girls to
pursue majors in STEM” (2.46). This was closely followed by “Female scientists face
more difficulties than male scientists in becoming full-time faculty or principal
investigators” (2.50) and “Women face more difficulties than men in finding jobs in
STEM despite having the same competence as their male counterparts” (2.51). Less
discrimination was felt for “Women receive lower wages than male colleagues having thesame qualifications in the fields of science and technology” (average of 2.93).
The average response to the four questions on discriminatory experiences was
3.05, which can be interpreted as a medium-level of discrimination. Here, a lower scoreindicates a higher level of discrimination. More severe discrimination was experienced in“Maintaining work-life balance (marriage, family) has been a handicap in my career”(2.60). This was followed by “I have faced disadvantages in participating in a research
project or becoming a principal investigator because I am female” (3.00), “I have beensexually harassed or received unfair treatment at work” (3.30), and “I have experienced
disadvantages in receiving research funds or scholarships because I am female” (3.32).
The average response to the four questions on gender role ideology sub-scale wason the progressive side at 3.40. The most progressive attitude was found in “Husbands
must have more power and authority than wives for peace and order in the household”(average of 3.78), representing that most respondents opposed patriarchal power relations
within the family. The second most progressive attitude was shown toward “Men must
be the breadwinner of households” (3.55). That is, the respondents were somewhat
negative when it came to the belief that ‘breadwinner = men’. In response to “Women
have an innate ability to take care of children, but men do not” (3.34), the respondents
were somewhat opposed to the idea regarding the fundamental differences in the ability
to take care of children based on biological sex. Lastly, in response to “Men and women71

must assume adequate roles because the former tend to be more rational and the latter
more emotional” (2.92), the average response fell in the middle of the scale but was
relatively more conservative than other items in the same sub-scale.
Career prospects were examined through the question stated “I believe my career
will go well.” The responses were reverse coded such that a higher score indicates a morepositive outlook. The average response at 3.70 was optimistic. The responses to “Strong
policies are necessary to overcome gender inequality in STEM fields” were also reverse
coded, and the average of 4.07 reflected a high demand.
Questions on the concept of gender equality were used to determine whether the
respondents would be satisfied with having just equal opportunities. The average response
was 2.13 on a 5-point scale (the lower the score, the greater the affirmation), and mostagreed with the statement. Throughout the modern history, the concept of equality had
developed from ‘equality in opportunities’ to ‘equality in conditions’ and to ‘equality inresults’. The belief that it suffices to have just equal opportunities is a liberalist stance,
and it overlooks the fact that equal opportunities cannot be enjoyed by persons who areunder different conditions. For instance, the Act on Equal Employment guarantees
equality in employment, but women have to engage in economic activities whileassuming the primary responsibility for childrearing. This condition is different from thatof men, making it difficult for women to enjoy equal opportunities. That’s why theequality in conditions is needed. However, it is an idealistic notion to have equality inconditions. Thus, it is now considered that discrimination to be present if there is noequality in outcome. Most respondents are likely to have answered this question without
fully comprehending this conceptual differences regarding equality.
<Figure 4-1. Average on each item>72

4.2.2 Cross-country comparison
4.2.2.1 Respondent profiles by country
Table 4-3 compares the respondent profiles by country. The different perception
toward the gender barriers may be related to differences in general characteristics such asage, marital status, duration of career break, major field of study and occupation. The
average age of respondents was 35.36, but the average age by country varied from the
20s to 50s. Malaysian respondents were the youngest (25.59) among the three countries
whose respondents were of an average age falling in the 20s. This was followed by
Bangladesh (25.65) and India (26.82). The six countries whose respondents showed anaverage age falling in the 30s included Nepal, Pakistan and New Zealand. The
respondents from Taiwan and Korea were of an average age of 40s while Japan, of 50.89,
the oldest average age.
The marital status of respondents is presumed to be related to average age. As
expected, the country with the highest proportion of single respondents was Malaysia at
76.6%. This was followed by Bangladesh at 74.3% and India at 52.7%. The country withthe highest proportion of married respondents was Vietnam at 87%. This was followed
by Mongolia (72.0%), Japan (70.3%) and Korea (61.5%).
The average number of children for all respondents was 0.84. Only Vietnam(1.66), Mongolia (1.65) and Japan (1.01) had an average exceeding 1. The country withthe lowest number of children was Bangladesh (0.15) followed by Malaysia (0.36) andIndia (0.48).
By major field of study, 47.9% of the respondents were in engineering. This wasfollowed by natural sciences (23.6%), medical and pharmaceutical (14.1%) and social
sciences (9.6%). The distribution of respondents by major differed by country. In New
Zealand, a large majority, or 89.7%, were in engineering. Other countries with a highproportion of engineering majors were Malaysia (75.4%) and Pakistan (76%). On theother hand, most Japanese were in the natural sciences (54%), while those in engineeringand medical/pharmaceutical accounted for 19.7% each. Countries with a high proportionof natural science majors were Taiwan (45.6%), Sri Lanka (43%) and Korea (38.8%). In
Bangladesh, the most common major was medical and pharmaceutical at 46.9%, followedby natural sciences (35.7%). Among Vietnamese respondents, the most common major
was engineering (39%) followed by social sciences (35%).
By occupation, 26% were professors/teachers, 24.5% were engineers, 16.5%
were researchers, 15.9% were students, and healthcare professionals were 6.3%. This
distribution again varied by country. New Zealand had the highest proportion of engineers
at 85.3%. This was followed by Nepal (44.1%) and Mongolia (42.9%). The country withthe highest proportion of professors/teachers was Vietnam (82%), followed by Pakistan73

(43.1%). Researchers were the most common in Korea (50%), and healthcare
professionals (35.6%) in Bangladesh.
The average duration of career break was 18.07 months. By country, Vietnam
had the longest average career break of 52.04 months (average age of 37.28 and 1.66
children). Mongolia had the second longest average of 36.71 months (average age of
37.37 and 1.65 children). In other words, Vietnam had a much longer average career breakthan Mongolia despite their respondents having a similar average age and number ofchildren. Japan had the third longest average of 27.03 months (average age of 50.89 and1.01 children). The country with the shortest average, at 4.56 months, was Malaysia. Thiswas because Malaysian respondents had an average age of 25.59 and 0.36 children, and61.1% of those were students. The country with the second shortest average was
Bangladesh (5.99 months), which is related to its respondents having an average age of
25.65 and 0.15 children. Korean respondents, with an average age of 42.59 and 0.96
children, had a career break of 9.12 months. Compared to the average career break of
27.03 months among Japanese respondents with 1.01 children on average, Koreanscientists and engineers had shorter career breaks.
<Table 4-3 Respondents profile by nation>(unit: Person, %)Nationality Average
age

Nepal

New
Zealand

32.14

33.72

Marital status
Single46.8

Married

52.1

Others1.1

Single32.4

Married

42.6

Others74

25.0

No. ofchildren

0.61

0.63

Major field of
Occupation
study
Humanities
0.0 student
Social Science
5.4 teacher/professor
Natural Science
18.5 researcher
Medicine&
14.1 Medical professional
Pharmacology
Arts &Physical Ed.
0.0
engineer
Teaching Profession
5.4
Engineering Science 56.5 Others
Humanities
0.0 student
Social Sciences
1.5 teacher/professor
Natural Science
8.8 researcher
Medicine&
0.0 medical professional
Pharmacology
Arts &Physical Ed.
0.0 engineer
Teaching Profession
0.0
OthersEngineering Science 89.7

Averageduration
6.5
11.8
12.9
9.7

13.10

44.1
15.1
1.5
1.5
1.5
0.0
85.3
10.3

17.18

Nationality Average
age

Malaysia

Mongolia

Vietnam

Sri Lanka

India

25.59

37.37

37.28

37.71

26.82

Marital status
Single76.6

Married

19.4

Others4.0

Single19.3

Married

72.0

Others8.7

Single1.0

Married

87.0

Others12.0

Single42.6

Married

45.5

Others11.9

Single52.7

Married

47.3

Others75

0.0

No. ofchildren

0.36

1.65

1.66

0.70

0.48

Major field of
Occupation
study
Humanities
0.6 student
Social Science
10.3 teacher/profession
Natural Science
6.9 researcher
Medicine&
5.1 medical professional
Pharmacology
Arts &Physical Ed.
1.7 engineer
Teaching Profession
0.0
OthersEngineering Science 75.4
Humanities
2.5 student
Social Science
19.5 teacher/professor
Natural Science17.0 researcher
Medicine&
3.1 medical professional
Arts &Physical Ed.
0.0 engineer
Teaching Profession
9.4
OthersEngineering Science 48.4
Humanities
7.0 student
Social Science
35.0 teacher/professor
Natural Science
7.0 researcher
Medicine&
8.0 medical professional
Arts &Physical Ed.
1.0 engineer
Teaching Profession
3.0
OthersEngineering Science 39.0
Humanities
0.0 student
Social Science
3.0 teacher/professor
Natural Science
43.0 researcher
Medicine&
28.0 medical professional
Arts &Physical Ed.
0.0 engineer
Teaching Profession
2.0
OthersEngineering Science 24.0
Humanities
0.0 student
Social Science
9.0 teacher/professor
Natural Science
0.0 researcher
Medicine&
11.5 medical professional

Averageduration
61.1
11.4
1.1
0.6

4.56

21.7
4.0
6.8
34.8
15.5
0.0
42.9

36.71

0.0
0.0
72.0
17.0
0.0
11.0

52.04

0.0
8.9
19.8
18.8
14.9
14.9

16.39

22.8
6.5
11.8
1.1
9.7

Arts &Physical Ed.

3.8 engineer

32.3

Teaching Profession
Engineering Science

16.7
Others
59.0

38.7

8.39

Nationality Averageage

Marital status
SingleJapan

TaiwanPakistan

Republicof Korea

BanglaDesh

Total

76

50.89

41.52

32.40

42.59

25.65

35.36

No. ofchildren

23.9

Married70.3

Others5.8

Single44.3

Married

48.1

Others7.6

Single40.2

Married

56.9

Others2.9Single37.0

Married

61.5

Others1.5Single74.3

Married

25.7

Others0.0Single41.8

Married

51.8

Others

6.4

1.01

0.78

0.79

0.96

0.15

0.84

Major field of
Occupation
study
Humanities
0.7 student
Social Science
5.1 teacher/professor
Natural Science
54.0
researcher
Medicine&
19.7
Arts &Physical Ed.
0.7 medical professional
Teaching Profession
0.0 engineer
Engineering Science 19.7 Others
Humanities
1.3 student
Social Science
8.9 teacher/professor
Natural Science
45.6 researcher
Medicine&
20.3 medical professional
Arts &Physical Ed.
2.5 engineer
Teaching Profession
1.3
OthersEngineering Science 20.3
Humanities
1.0 student
Social Science
7.0 teacher/professor
Natural Science
9.0 researcher
Medicine&
16.0 medical professional
Arts &Physical Ed.
0.0 engineer
Teaching Profession
0.0
OthersEngineering Science 67.0
Humanities
0.0 student
Social Science
0.7 teacher/professor
Natural Science
38.8 researcher
Medicine&
9.7 medical professional
Arts &Physical Ed.
0.7 engineer
Teaching Profession
0.0
OthersEngineering Science 50.0
Humanities
0.0 student
Social Science
2.0 teacher/professor
Natural Science
35.7 researcher
Medicine&
46.9 medical professional
Arts &Physical Ed.
0.0 engineer
Teaching Profession
0.0
OthersEngineering Science 15.3
Humanities
1.1 student
Social Science
9.6 teacher/professor
Natural Science
23.6 researcher
Medicine&
14.1 medical professional
Arts &Physical Ed.
0.8 engineer
Teaching Profession
2.9
OthersEngineering Science 47.9

Averageduration
1.4
34.8
28.3
3.6
18.8
13.0
26.6
30.4
16.5
5.1
7.6

27.03

11.12

13.9
6.9
43.1
16.7
6.9
15.7

9.83

10.8
6.0
32.1
50.0
0.7
4.5

9.12

6.7
29.7
6.9
13.9
35.6
5.9

5.99

7.9
15.9
26.0
16.5
6.3
24.5
10.8

18.07

4.2.2.2 Cross-country comparison of the gender barriers by sub-scales
The following is a cross-country comparison of the perception of the genderbarriers by sub-scales (see Table 4-4). First, for the perception of discriminatory reality,
the overall average of 2.60 is slightly below the median (a lower score indicates greater
discrimination). Indian respondents showed the highest awareness of gender
discrimination at 1.13, setting it far apart from respondents from the other countries. Thiswas followed by Mongolia (2.21), Korea (2.24), Bangladesh (2.29), Nepal and New
Zealand (both 2.51), Pakistan (2.64) and Taiwan (2.65). The country which showed theleast awareness of discrimination was Sri Lanka, with a score of 3.37 out of 5. This wasfollowed by Malaysia (3.20), Vietnam (3.19) and Japan (2.84). The only three countries
with a level of perception falling below the median score (3) were Sri Lanka, Malaysia
and Vietnam (see Figure. 4-2).
<Table 4-4. Comparison of average scores of participating nations by scales>(unit: Points)

Classifications Perception of Experience of Gender role
discrimination discrimination stereotype

Careeroutlook

Policy needs

Equality
concept

Nepal

2.51

3.26

4.14

3.83

4.55

1.56

New Zealand

2.51

2.99

4.28

3.68

4.25

1.78

Malaysia

3.20

3.43

3.15

3.62

3.69

2.25

Mongolia

2.21

2.89

2.81

3.99

4.26

2.06

Vietnam

3.19

2.44

3.07

3.37

4.77

1.85

Sri Lanka

3.37

3.61

3.47

4.11

4.09

2.37

India

1.13

2.27

4.68

3.55

4.30

1.01

Japan

2.84

2.91

3.22

2.96

3.15

3.26

Taiwan

2.65

3.19

3.87

3.78

3.87

2.24

Pakistan

2.64

3.31

2.40

4.02

4.07

1.71

Republic ofK
Bangladesh

2.24

2.99

3.61

3.39

4.19

3.12

2.29

3.18

3.06

4.37

4.23

1.41

Others

2.92

3.15

3.65

3.63

3.91

1.88

Total

2.60

3.05

3.40

3.70

4.07

2.13

F

57.32122.78455.032

16.58819.73449.809P***(p<.001)

***

***

***

***

***

***

77

<Figure 4-2. Perception of discrimination by nation>

The results for discriminatory experiences (see Fig. 4-3) showed that the averageof 3.05 is slightly higher than the median score. Similarly, a lower score indicates greater
experiences of gender discriminations. The country that showed the most discriminatory
experiences was India (2.27). This was followed by Vietnam (2.44), Mongolia (2.89) andJapan (2.91). Korea, having the same score as New Zealand at 2.99, ranked the fifth
highest among the 12 countries. Sri Lanka had the lowest scores for both the perceptionof discriminatory reality and the actual discriminatory experiences. Malaysia had thesecond lowest scores for both the perception of discriminatory reality and discriminatory
experiences.
<Figure 4-3. Experience of discrimination by nation>

As shown in Fig. 4-4, female scientists and engineers showed a progressive
attitude toward gender roles with an average of 3.40. The country with the mostprogressive attitude toward gender roles was India, with an average of 4.68 on a 5-point78

scale. This was followed by New Zealand (4.28), Nepal (4.14), Taiwan (3.87), Korea(3.61), Sri Lanka (3.47) and Japan (3.22). Similar scores were obtained for Malaysia(3.15), Vietnam (3.07) and Bangladesh (3.06). Mongolia (2.81) and Pakistan (2.40), withscores slightly below the average, were relatively conservative toward gender roles.
<Figure 4-4. Gender role stereotype s by nation>

The average score of 3.70 for career prospects, after reverse coding, wassomewhat positive (see Fig. 4-5). Female scientists and engineers in Bangladesh were themost optimistic (4.37), while those in Japan were the least optimistic (2.96). Bangladesh
was followed by Sri Lanka (4.11), Pakistan (4.02) and Mongolia (3.99). In increasingorder of optimism, Japan (2.96) was followed by Vietnam (3.37), Korea (3.39) and India(3.55). Japan had a score close to the median, and Vietnam and Korea had scores higher
than the median, but were relatively less positive compared to the other countries.
<Figure 4-5. Career outlook by nation>79

As shown in Fig. 4-6, the average for policy demands was relatively high at 4.07
(after reverse coding). The scores for all countries in this area were higher than the median.
Vietnam had the highest average (4.77), and Japan the lowest (3.15). Vietnam wasfollowed by Nepal (4.55), India (4.30), Mongolia (4.26) and New Zealand (4.24). In
increasing order, Japan was followed by Malaysia (3.69), Taiwan (3.87), Pakistan (4.07)
and Sri Lanka (4.09). Korea (4.19) was the seventh highest among the 12 countries.
<Figure 4-6. Policy needs by nation><Figure 4-7. Equality concept by nation>

Fig. 4-7 shows the equality concept by country. The overall average of 2.13
showed that the respondents generally adopted a liberalist stance. A lower score for thestatement “I believe that gender equality will be fully achieved if only women are given
the same opportunities as men” indicates greater affirmation. The country with the highest
average was Japan (3.26) followed by Korea (3.12). That is, female scientists andengineers in Japan and Korea feel that it is insufficient simply to have equal opportunities.
80

On the other hand, those in India (1.01) strongly agreed that equal opportunities were
sufficient. India was followed by Bangladesh (1.41), Nepal (1.56), Pakistan (1.71), New
Zealand (1.81), Vietnam (1.85), Mongolia (2.06), Taiwan (2.24) and Malaysia (2.25). The
respondents were likely to have provided answers without fully comprehending thedifference between equality in opportunities, equality in conditions and equality inoutcome. As such, greater caution must be exercised in interpreting these results.
4.2.3 Analysis by item
This section provides an analysis of how the respondents’ general characteristics
such as age, marital status, number of children, occupation, and duration of career breakinfluence the perception of gender barriers, career prospects, policy demands and genderrole ideology. ANOVA was employed for the analysis, and Duncan’s post hoc test wasused to pinpoint where the differences lied when differences were statistically significant.
1. Boys rather than girls are encouraged to pursue majors in STEM.
The first question on the perception of discriminatory reality was “Boys rather
than girls are encouraged to pursue majors in STEM.” The responses to this question aresummarized in Table 4-5. The overall average of 2.46 indicated slight agreement (thelower the score, the greater the affirmation). An analysis of responses by age showed thatthe differences were statistically significant. The lowest score of 2.32 was given by theage group younger than 29, who were more inclined to believe that gender discrimination
exists since childhood in pursuing science and technology majors. This was followed byrespondents in the 40-49 age group (2.43), followed by 50 or older, and 30-39 (F=5.659,
p≤.001). Duncan’s post hoc test found significant differences between the age group
younger than 29 and the 30-39 group. By marital status, the scores were similarly low
between married (2.44) and single (2.46) respondents, but higher at 2.69 for thoseclassified as other (divorced, separated, etc.). These differences, however, were notstatistically significant. Differences arising from the number of children and period ofcareer break were also not significant.
On the other hand, the differences were found to be significant by occupation. The
group having the lowest average was healthcare professionals (2.18), followed byengineers (2.22). These two groups are likely to have been aware, from an early age, ofgender discrimination in pursuing majors in STEM. The other groups (except “other,”) in
increasing order, were researchers (2.56), professors/teachers (2.64) and students (2.72)(F=8.457, p≤.000). Post hoc analysis showed that the differences were significant
between students and healthcare professionals, between students and engineers, andbetween students and jobs classified as other.

81

<Table 4-5. Boys are encouraged more than girls to go into the STEM field: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
2.46

SD
1.219

541
414
210
206

2.32
2.64
2.43
2.54

1.199
1.221
1.189
1.255

576
709
88

2.46
2.44
2.69

1.234
1.201
1.254

720
231
305
100

2.43
2.44
2.61
2.34

1.235
1.188
1.196
1.208

219
357
224
87
336
148

2.72
2.64
2.56
2.18
2.22
2.24

1.189
1.230
1.177
1.317
1.167
1.199

665
112
155
138
270

2.45
2.59
2.40
2.38
2.49

1.214
1.234
1.236
1.109
1.281

F

p

5.659

***(.001)

1.714(.180)

1.993(.113)

8.457***(.000)

0.620(.648)As shown in Fig. 4-8, India had the lowest average among countries, showingthat female scientists and engineers in India strongly agreed with “Boys rather than girls
are encouraged to pursue majors in STEM.” This was followed by Mongolia (1.93),
Bangladesh (2.03), Pakistan (2.11) and Nepal (2.31). The country that disagreed mostwith the existence of gender discrimination in pursuing majors in STEM since childhood
was Sri Lanka (3.39), followed by Vietnam (3.30). Korea, with an average of 2.42, fell inthe middle of the 12 countries.

82

<Figure 4-8. Boys are encouraged more than girls to go into the STEM field: Average by nation>(Lower scores mean more agreed unit: points)

2. Women face more difficulties than men in finding jobs in STEM despite
having the same competence as their male counterparts.
The second question on the perception of discriminatory reality was “Women
face more difficulties than men in finding jobs in STEM despite having the same
competence as their male counterparts.” The overall average of respondents was 2.51,
indicating that they acknowledged the presence of discrimination (see Table 4-6). An
analysis of the results by age showed that the 40-49 age group had the lowest score. The
30-39 group and the group older than 50 had scores of 2.59 and 2.57, respectively, but
the differences across age groups were not statistically significant. By marital status,
married respondents had the lowest score (2.45), followed by single respondents (2.45)
and respondents classified as other (divorced, separated, etc.) at 2.72. The differences
arising from marital status and duration of career break were not significant.
On the other hand, differences arising from the number of children andoccupation were significant. The group with three or more children had the lowest
average of 2.35 (most aware of discrimination), and the group with no children had thehighest average of 2.60 (least aware of discrimination). The group with one child had an
average of 2.40, similar to that of the group with two children at 2.44 (F=3.188, p≤.023).
The post-hoc analysis showed statistically significant differences between the group withthree or more children and the group with no children.
By occupation, healthcare professionals were the most aware of discrimination
with the lowest average of 2.36. This was followed by researchers (2.41), engineers (2.50)
and professors/teachers (2.51). Students had the highest average of 2.80. While this islower than the median, they were relatively less aware of the discriminatory reality thanother groups due to their lack of experience. The post-hoc analysis found significant
differences between students and those in other occupation groups.
83

<Table 4-6. It is more difficult for a woman to get a job in the STEM field than for a maneven with the same qualifications: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
2.51

SD
1.180

541
414
209
210

2.48
2.59
2.36
2.57

1.207
1.152
1.144
1.197

577
712
87

2.55
2.45
2.72

1.200
1.150
1.273

721
232
306
100

2.60
2.40
2.44
2.35

1.221
1.080
1.161
1.104

219
358
226
87
335
149

2.80
2.51
2.41
2.36
2.50
2.37

1.162
1.087
1.101
1.312
1.264
1.210

664
113
156
138
270

2.51
2.61
2.59
2.59
2.34

1.188
1.242
1.223
1.118
1.132

F

p

2.049

(.105)

2.583(.076)

3.188*(.023)3.822**(.002)

1.878(.112)

By country (see Fig. 4-9), India had the lowest average (1.16), which is similar
to the results for the first question. In other words, female scientists and engineers in India
strongly agreed that women face difficulties in finding jobs in STEM. This was followed
by Mongolia (1.93) and Korea (2.03). That is, Korea was the third highest among the 12
countries to acknowledge that women face more difficulties than men in finding jobs in
STEM despite having the same competence as their male counterparts. Sri Lanka, withthe highest average of 2.30, was the least aware of discrimination. This was followed by
New Zealand (3.10), Malaysia (3.09) and Japan (2.97).

84

<Figure 4-9. It is more difficult for a woman to get a job in the STEM field than for a maneven with the same qualifications: Average by nation>(Lower scores mean more agreed unit: points)

3. Female scientists face more difficulties than male scientists in becoming full-time
faculty or principal investigators.
The third question on the perception of discriminatory reality was “Female
scientists face more difficulties than male scientists in becoming full-time faculty or
principal investigators.” The overall average of 2.50 (a lower score indicates greaterawareness of discrimination) indicates that the presence of discrimination is somewhat
acknowledged (see Table 4-7). The analysis looked at whether the respondents showed
any difference in perception according to individual variables. By age, the 40-49 group
had the lowest average (2.44), while the age group younger than 29 had the highest (2.54).
However, this difference was not significant. The difference arising from the duration ofcareer break was also not significant.
On the other hand, differences arising from marital status, number of children
and occupation were significant. By marital status, similar high scores were obtained for
married respondents (2.42) and those classified as other (2.47). Single respondents had
the highest average (2.61) (F=4.062, p≤.017). That is, single women were the least awarethat female scientists face more difficulties than male scientists in becoming full-time
faculty or principal investigators. This can be attributed to the fact that single respondents,
who are mostly students, have the least experience of gender discrimination. By the
number of children, the group with three or more children had the lowest score (2.32),
followed by the group with one child (2.34) and the group with two children (2.37). The
group with no children had the highest average (2.63) (F=5.735, p≤.001). This coincides
with the results for differences arising from marital status. The post-hoc analysis foundstatistically significant differences between the group with no children and each of theother groups.
85

Differences arising from occupation were also statistically significant. Engineers(2.42) and healthcare professionals (2.43) had similarly low scores (indicating a highawareness of discrimination). This was followed by professors/teachers and researchers,
which groups had the same score of 2.47. Similar to the results for the first two questions,students had the highest average (2.92) (F=6.615, p≤.000). That is, students were the least
aware of discrimination because of their lack of experience. The post-hoc analysis foundsignificant differences between students and each of the other occupation groups.
<Table 4-7. Becoming a tenured professor, being promoted or becoming a principal investigatoris more difficult for female scientists than for male scientists: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
2.50

SD
1.235

541
414
209
209

2.54
2.51
2.44
2.46

1.274
1.174
1.192
1.297

576
712
87

2.61
2.42
2.47

1.242
1.240
1.098

721
231
306
100

2.63
2.34
2.37
2.32

1.262
1.212
1.172
1.145

219
357
226
87
335
149

2.92
2.47
2.47
2.43
2.42
2.28

1.211
1.200
1.215
1.491
1.208
1.163

663
113
155
138
270

2.52
2.55
2.47
2.30
2.44

1.238
1.302
1.316
1.175
1.145

F

p

0.499

(.683)

4.062*(.017)5.735**(.001)6.615***(.000)

1.099(.355)

By country (see Fig. 4-10), female scientists and engineers in India had the lowest
average (1.17), meaning they strongly agreed that female scientists face more difficulties
than male scientists in becoming full-time faculty or principal investigators. Korea (1.94)
86was the second highest, indicating that its female scientists and engineers were highly
aware of gender discrimination. This was followed by Mongolia (2.16), New Zealand(2.29) and Bangladesh (2.32). On the other hand, Malaysia had the highest average of
3.25, followed by Sri Lanka (3.21). These two countries slightly disagreed that female
scientists face more difficulties than male scientists in becoming full-time faculty or
principal investigators.
<Figure 4-10. Becoming a tenured professor, being promoted or becoming a principal
investigator is more difficult for female scientists than for male scientists:
Average by nation>(Lower scores mean more agreed unit: points)

4. Women receive less wages than male colleagues having the same qualificationsin the fields of science and technology.
The fourth question in the perception of discriminatory reality was “Women
receive less wages than male colleagues having the same qualifications in the fields ofscience and technology.” The amount of wages received for the same work by gender is
an important indicator showing the perception of discriminatory reality faced by women.
For this reason, the gender wage gap is included in international indices related to genderequality (e.g. WEF’s GGI).
This question was used to determine the perception of respondents of gender
discrimination in the amount of wages. The overall average of 2.93 was close to themedian (see Table 4-8). The age group most aware of gender discrimination was aged 29
or younger (2.90), and the group least aware was in the range of 40-49 (3.07). Thisdifference was not statistically significant. Differences arising from marital status,
number of children and period of career break were also not significant.
On the other hand, the difference arising from occupation was statisticallysignificant. Engineers were the most aware of the discriminatory reality faced by womenin the amount of wages (2.54), followed by healthcare professionals (2.78), researchers87(3.08), students (3.15) and teachers/professors (3.30) (F=18.647, p≤.000). The post hoc
analysis found no statistically significant differences between students,
teachers/professors and researchers, but these groups showed significant differences withhealthcare professionals, engineers and those classified as other.
<Table 4-8. Women in STEM generally receive less pay for equal work, compared with theirequally-qualified male colleagues: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
2.93

SD
1.318

541
414
209
210

2.82
3.01
3.07
2.90

1.316
1.332
1.354
1.247

577
712
87

2.85
2.99
2.95

1.292
1.318
1.470

721
232
306
100

2.88
2.95
3.08
2.82

1.299
1.347
1.337
1.282

219
358
226
87
335
149

3.15
3.30
3.08
2.78
2.54
2.44

1.189
1.278
1.236
1.376
1.294
1.367

664
113
156
138
270

2.85
2.94
2.90
3.02
3.07

1.301
1.325
1.314
1.375
1.349

F

p

2.569

(.053)

1.805(.165)

1.902(.127)

18.647***(.000)

1.600(.172)

By country (see Fig. 4-11), female scientists and engineers in India (average of1.12) were extremely aware of the gender wage gap, indicating that women in scienceand technology face a high level of discrimination in terms of wages. However, it should
be noted that the average age of Indian respondents was 26.83, much lower than theoverall average of 35.36. New Zealand ranked second (2.34), followed by Korea and
Nepal in the third place (both 2.57). This shows that Korean scientists and engineers havea relatively high awareness of the gender wage gap. Vietnam (4.32) was the least aware88

of this discriminatory reality, followed by Sri Lanka (3.70), Pakistan and Malaysia (3.32)
and Japan (3.07). These five countries had scores lower than the median of 3.
<Figure 4-11. Women in STEM generally receive less pay for equal work, compared with theirequally-qualified male colleagues: Average by nation>(Lower scores mean more agreed unit: points)

5. I have experienced disadvantages in participating in a research project or
becoming a principal investigator because I am female.
The next four questions centered on the respondents’ discriminatory experiences.
The first was “I have experienced disadvantages in participating in a research project or
becoming a principal investigator because I am female.” The overall average was 3.00,
which falls in the middle of the scale (see Table 4-9). There were no significant
differences by age, marital status and number of children.
On the other hand, the differences arising from occupation and duration of career
break were found to be significant. By occupation, healthcare professionals had
experienced the most disadvantages (2.78), followed by engineers (2.83),
teachers/professors (3.01), researchers (3.20) and students (3.35). Female healthcare
professionals and engineers had faced more disadvantages in research projects, whilestudents lacked such experiences (F=8.601, p≤.000). This can be attributed to students
having less project experience and their ineligibility as principal investigators comparedto female scientists and engineers. The post hoc analysis found statistically significant
differences between students and each of the other occupation groups, and between
researchers and the other groups.
By duration of career break, a majority of respondents had taken a career breakof 3 years or longer (2.77). This was followed by no career break (2.97), a break of 1-2
89years and a break of 2-3 years (F=3.864, p≤.004). The post hoc analysis showed that thedifferences were significant between the group with a career break of 2-3 years, those
without and those with a career break of 3 years or longer.
<Table 4-9. I have experienced disadvantages in leading or participating in research projects
because I am a woman: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.00

SD
1.272

541
412
210
210

2.99
3.00
3.03
2.96

1.337
1.253
1.163
1.252

577
710
88

3.01
2.96
3.16

1.338
1.219
1.240

722
230
306
100

3.03
2.82
3.00
3.07

1.326
1.291
1.158
1.112

219
356
226
87
336
149

3.35
3.01
3.20
2.78
2.83
2.66

1.196
1.222
1.222
1.298
1.281
1.369

665
111
156
138
270

2.97
3.18
3.07
3.22
2.77

1.307
1.259
1.340
1.145
1.203

F

p

0.122

(.947)

1.056(.348)

1.728(.159)

8.601***(.000)

3.864**(.004)

By country (see Fig. 4-12), the average of Indian respondents (1.03) was much
lower than that of other countries. In other words, female scientists and engineers in India
strongly agreed with this question, indicating a high level of gender inequality. This wasfollowed by Vietnam (2.65), Japan (2.98), New Zealand (2.99), Bangladesh (3.03) andKorea (3.07). The level of discrimination experienced by female scientists and engineersin Korea was slightly below the median, but Korea was ranked 6th out of 12 countries. Sri
Lanka had the least experience (3.50), followed by Malaysia (3.34), Taiwan (3.27) andPakistan (3.23).
90

<Figure 4-12. I have experienced disadvantages in leading or participating in research projects
because I am a woman: Average by nation>(Lower scores mean more agreed unit: points)

6. I have experienced disadvantages in receiving research funds or scholarships
because I am female.
The second question on discriminatory experiences was “I have experienced
disadvantages in receiving research funds or scholarships because I am female.” Theoverall average for this question was 3.32 (the lower the score, the moreacknowledgement of disadvantages), which was lower than the median (see Table 4-10).
The difference arising from age was not significant. On the other hand, the difference
arising from marital status was significant. Married respondents (3.21) had experienced
the most disadvantages in receiving research funds or scholarships, followed by separated
or divorced (3.39) and, finally, single respondents (3.43) (F=5.245, p≤.005). The resultsof the post hoc analysis were not significant.
The difference arising from the number of children was also significant.
Respondents with only one child faced the most disadvantages (3.06), followed by thosewith two children (3.14), those with three or more children (3.35) and those with nochildren (3.45) (F=8.563, p≤.000). The post hoc analysis showed significant differences
between the group with no children and the group with one child, and between the groupwith no children and the group with two children.
The respondents’ occupations were related to experiences of disadvantages inreceiving research funds or scholarships. The group that faced the most disadvantages
was healthcare professionals (3.08). This was followed by engineers (3.20),
teachers/professors (3.22), researchers (3.63) and students (3.68) (F=11.672, p≤.000).
The post hoc analysis showed that students and researchers experienced fewer
disadvantages compared to other occupation groups.

91

<Table 4-10. I have experienced disadvantages in receiving research funds or scholarships
because I am a woman: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.32

SD
1.221

541
414
209
209

3.40
3.24
3.33
3.25

1.326
1.199
1.084
1.107

576
712
87

3.43
3.21
3.39

1.259
1.192
1.145

721
231
306
100

3.45
3.06
3.14
3.35

1.261
1.248
1.107
1.038

219
358
226
87
334
149

3.68
3.22
3.63
3.08
3.20
2.96

1.176
1.165
1.145
1.241
1.182
1.394

663
113
156
138
270

3.36
3.58
3.46
3.43
2.92

1.271
1.209
1.188
1.107
1.130

F

p

1.539

(.203)

5.245**(.005)8.563***(.000)

11.672***(.000)

9.468***(.000)

The duration of career break was also related to experiences of disadvantages inreceiving research funds or scholarships. The group with a career break of 3 years or
longer had an average (2.92) falling below the median, while the other groups had a scoreof at least 3. Those without career breaks experienced the most disadvantages (3.36),
while those with a career break of less than a year faced the fewest disadvantages (3.58)(F=9.468, p≤.000). The post hoc analysis showed that the group with a career break of
three years or longer experienced significantly greater disadvantages than the othergroups.

92

<Figure 4-13. I have experienced disadvantages in receiving research funds or scholarships
because I am a woman: Average by nation>(Lower scores mean more agreed unit: points)

Next, the experiences of discriminations or disadvantages in receiving researchfunds or scholarships were examined by country (see Fig. 4-13). The country wherefemale scientists and engineers faced significantly greater disadvantages was India (1.20).
This is consistent with the results for experiences of disadvantages in participating inresearch projects or becoming principal investigators. Vietnam was the second highest interms of disadvantages experienced by female scientists and engineers in receiving
research funds or scholarships (2.42). This was followed by Japan (3.18), Mongolia (3.22)
and Korea (3.46). Female scientists and engineers in Sri Lanka faced the fewest
disadvantages (3.97), followed by Nepal and Malaysia. All countries except India andVietnam had scores higher than the median of 3, indicating that disadvantages inreceiving research funds or scholarships were not that extensive.
7. I have been sexually harassed or received unfair treatment at work.
The third question on discriminatory experiences was “I have been sexuallyharassed or received unfair treatment at work.” The overall average for this question was
3.30 (a lower score indicating more experience of discrimination), which was lower thanthe median (see Table 4-11). By age, the average was higher for lower age groups (3.64
for respondents younger than 20, 3.26 for 30-39, 2.96 for 40-49 and 2.88 for 50 or older).
The increase in experiences of sexual harassment or other unfair treatment with age canbe interpreted as the result of having greater exposure to such incidents (F=23.715,p≤.000). The post hoc analysis found significant differences between the age group
younger than 29 and other groups, and between the 30-39 group and the 50 or older group.
The difference arising from marital status was also significant. Single respondents had
the highest average (3.45, least discriminatory experiences), followed by married (3.22)
and those classified as other (3.01) (F=6.876, p≤.001). The post hoc analysis found93

significant differences between the single group and other groups. The difference arisingfrom the number of children was found to be significant. The group with no children had
the highest average (3.45), followed by the group with one child (3.33), the group withtwo children (3.17) and the group with three or more children (2.78). This is because older
groups, who have had more exposure to unfair treatment with age, are likely to be parents
to more children (F=8.070, p≤000). The post hoc analysis found significant differences
between the group with three or more children and each of the other groups.
The difference arising from occupation was significant. Engineers were the mostexperienced in terms of sexual harassment or other unfair treatment (3.15), followed byresearchers (3.17) and healthcare professionals (3.18). Groups with relatively fewer
experiences of sexual harassment and unfair treatment were teachers/professors (3.29)
and students (3.55) (F=4.518, p≤.000). The post hoc analysis found that students had
experienced significantly fewer disadvantages compared to each of the other occupationgroups: researchers, engineers and healthcare professionals. Lastly, the difference arisingfrom the period of career break was also significant. The group with a career break of 3
or more years (3.04) had experienced the most sexual harassment or unfair treatment,
followed by the group with a career break of 2-3 years (3.03), the group with a career
break of 1-2 years (3.35), the group with a career break of less than 1 year (3.35) and thegroup with no career break (3.46) (F=6.308, p≤.000). In the post hoc analysis, the groupwith no career break, the group with a career break of less than 1 year and the group witha career break of 1-2 years showed significant differences compared to each of theremaining two groups (2-3 years, 3 or more years).
The experiences of sexual harassment and other unfair treatment among female
scientists and engineers were examined by country (see Fig. 4-14). The country with themost experience of gender discrimination was New Zealand (2.57), followed by
Mongolia (22.61), Korea (2.86) and Japan (2.91). On the other hand, the country with thehighest score, indicating the least experience of sexual harassment or other unfair
treatment, was India (4.91). This is in contrast to the results for perception of
discriminatory reality and discriminatory experiences, for which India obtained thelowest scores (indicating high levels of discrimination). Female scientists and engineers
in India experienced more discrimination than their counterparts in other countries, butless discrimination in terms of sexual harassment or other unfair treatment. This wasfollowed by Sri Lanka (3.74), Vietnam (3.61), Pakistan (3.60), Bangladesh (3.50) and
Malaysia (3.45). Korea, with an average of 2.86, was the third highest among countries.
The two countries with more sexual harassment and unfair treatment than Korea were
Mongolia (2.61) and New Zealand (2.57).

94

<Table 4-11. I have experienced sexual harassment or unfair treatments sometime in my career: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30 ~ 3940 ~ 49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.30

SD
1.356

541
414
211
210

3.64
3.26
2.96
2.88

1.331
1.315
1.303
1.338

577
713
88

3.45
3.22
3.01

1.377
1.331
1.326

723
232
306
100

3.42
3.33
3.17
2.78

1.398
1.350
1.253
1.160

219
358
226
87
337
149

3.55
3.29
3.17
3.18
3.15
3.62

1.208
1.275
1.295
1.559
1.424
1.469

665
113
156
138
270

3.46
3.35
3.28
3.03
3.04

1.391
1.374
1.444
1.226
1.235

F

p

23.715***(.000)

6.876**(.001)8.070***(.000)

4.518***(.000)

6.308***(.000)<Figure 4-14. I have experienced sexual harassment or unfair treatments sometime in mycareer: Average by nation>(Lower scores mean more agreed unit: points)

95

8. Maintaining work-life balance (marriage, family) has been a handicap in mycareer.
The last question on discriminatory experiences was “Maintaining work-lifebalance (marriage, family) has been a handicap in my career.” Similar to the otherquestions on the gender barriers, a lower score indicates more discriminatory experiences.
The overall average was 2.60, which means the respondents struggled to maintain worklife balance (see Table 4-12). By age, the 39-39 group had the lowest average (2.30). Thiscan be attributed to this group having children of an age demanding more attention andcaretaking. This was followed by the 40-49 group (2.45), the 40 or older group (2.54) andthe 29 or younger group (2.91). That is, maintaining work-life balance was most difficult
for the 30-39 group and the least difficult for the 29 or younger group (F=22.334, p≤.000).
The post hoc analysis found significant differences between the 29 or younger group andeach of the remaining age groups.
The struggle to maintain work-life balance varied significantly with marital status.
Married respondents (2.31) and divorced/separated respondents (2.32) faced moredifficulties than respondents who were single (3.01) (F=60.113, p≤.000). The post hoc
analysis obtained consistent results. In addition, the difference arising from the numberof children was significant. That is, the group with two children faced the most difficulties(2.11), followed by the group with one child (2.26), the group with three or more children(2.40) and the group without children (2.94) The post hoc analysis showed significant
differences between the group without children and each of the remaining groups(F=46.465, p≤.000).
The difference arising from occupation was significant as well.
Teachers/professors struggled the hardest to maintain work-life balance (2.24). This wasfollowed by healthcare professionals (2.48), researchers (2.56), engineers (2.70) andstudents (3.07) (F=14.258, p≤.000). It is expected that students, who are younger andsingle, face the fewest challenges in maintaining work-life balance. The post hoc analysis
found significant differences between students and each of the other groups.
Finally, the difference arising from the duration of career break was significant.
The group with a career break of more than 3 years expressed the strongest agreement to
the given statement (1.99). This was followed by the group with a career break of 2-3
years (2.38), a career break of less than 1 year (2.53), a career break of 1-2 years (2.74)
and no career break (2.86) (F=28.237, p≤.000). The post hoc analysis found significant
differences between the group with a career break of 3 or more years and each of theremaining groups.

96

<Table 4-12. Balancing work and life has been a handicap for me: Total>
Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

(Lower scores mean more agreed unit: person, points)
Average
SD
F
p
2.60
1.217

541
414
210
210

2.91
2.30
2.45
2.54

1.146
1.250
1.210
1.154

577
712
88

3.01
2.31
2.32

1.143
1.188
1.170

722
232
306
100

2.94
2.26
2.11
2.40

1.136
1.210
1.169
1.155

219
358
226
87
336
149

3.07
2.24
2.56
2.48
2.70
2.70

1.121
1.213
1.154
1.363
1.149
1.256

665
113
156
138
270

2.86
2.53
2.74
2.38
1.99

1.131
1.150
1.358
1.167
1.174

22.334***(.000)

60.113***(.000)

46.465***(.000)

14.258***(.000)

28.237***(.000)

The career handicap caused by maintaining work-life balance among female
scientists and engineers was examined by country (see Fig. 4-15). Among the 12 countries,
Vietnam had the lowest score (1.10), indicating the most struggle to maintain work-lifebalance. This was followed by India (1.92), Mongolia (2.54), Korea (2.56), Bangladesh(2.58), Japan (2.60) and Taiwan (2.65). The country with the highest average was Sri
Lanka (3.23), followed by Malaysia (3.20). Female scientists and engineers in Sri Lanka
and Malaysia gave scores lower than the median. The two countries were followed by
New Zealand (2.90), Pakistan (2.81) and Nepal (2.72). Among the 12 countries, Korea
was the fourth highest in terms of difficulties associated with maintaining work-lifebalance.

97

<Figure 4-15. Balancing work and life has been a handicap for me: Average by nation>(Lower scores mean more agreed unit: points)

9. Men must be the breadwinner of households
The next four questions were used to examine the gender role ideology of
respondents. The overall average for the first statement “Men must be the breadwinner ofhouseholds” was 3.55 (see Table 4-13). A higher score indicates a more progressive
attitude. As such, we can see that the respondents generally adopted a progressive stancetoward the role of men as breadwinners. By age, the 29 or younger group (2.62) and the30-39 group (2.63) had similarly high scores, followed by the 49-49 group (3.43) and the
50 or older group (3.33) (F=3.409, p≤.017). Younger respondents were more progressive
when it came to the role of breadwinner. The post hoc analysis found no significant
differences between the 29 or younger group and the 30-39 group, and between the 4049 group and the 50 or older group.
The difference arising from marital status was significant. Single respondents
had a higher average (3.68) than married (3.46) or divorced/separated respondents (3.46),
indicating that respondents who were single had a more progressive attitude toward therole of breadwinner (F=4.306, p≤.014). The difference arising from the number ofchildren was also significant. That is, the group with no children had the highest average(3.65), followed by the group with one child (3.57), the group with two children (3.553)
and the group with three or more children (2.94). Those with more children had a moreconservative gender role ideology toward the role of breadwinner (F=8.410, p≤.000). The
post hoc analysis found significant differences between the group with three or morechildren and each of the other groups.
The difference arising from occupation was significant. The group with thehighest score was researchers (3.78), and the group with the lowest was healthcare
professionals (3.28) (F=5.113, p≤.000). The post hoc analysis found significant
differences between students/teachers/professors/healthcare professionals and98researchers/engineers/others. Lastly, the difference arising from the period of career break
was not significant.
<Table 4-13. Primary breadwinners of households should be men: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.55

SD
1.343

541
413
211
210

3.62
3.63
3.43
3.33

1.357
1.303
1.348
1.353

577
712
88

3.68
3.46
3.45

1.315
1.358
1.347

723
232
305
100

3.65
3.57
3.53
2.94

1.357
1.314
1.251
1.391

219
358
226
87
336
149

3.43
3.36
3.78
3.28
3.66
3.77

1.215
1.255
1.187
1.654
1.414
1.485

665
113
155
138
270

3.59
3.62
3.68
3.50
3.40

1.383
1.429
1.352
1.245
1.253

F

p

3.409

*(.017)4.306*(.014)8.410***(.000)

5.113***(.000)

1.558(.183)The responses to “Men must be the breadwinner of households” were examinedby country (see Fig. 4-16). India, at 5 out of 5, had the highest average. This means that
all Indian respondents disagreed with the given statement. Again, this is related to Indian
respondents having a younger average age of 26.82 than the overall average of 35.36. The
countries that followed were Nepal (4.71), New Zealand (4.43), Korea (4.09), Sri Lanka(3.93) and Taiwan (3.80). The country with the lowest average was Pakistan (2.32),
followed by Mongolia (2.78) and Bangladesh (2.97). Female scientists and engineers inthese countries had a relatively conservative outlook on the role of the breadwinner.
Korea had an average of 4.09, and Japan was lower at 3.21. This means that Korean
respondents adhered less strongly than Japanese respondents to the belief that men must
be the breadwinner of households.
99

<Figure 4-16. Primary breadwinners of households should be men: Average by nation>(Lower scores mean more agreed unit: points)

10. Women have an innate ability to take care of children, but men do not.
The second question used to examine gender role ideology was “Women have an
innate ability to take care of children, but men do not.” The purpose of this question was
to determine whether respondents associated the role of caretaking to an innate genderbased ability. The overall average was 3.34, which indicates a slightly progressive attitude(see Table 4-14). The female scientists and engineers who participated in this study had
a level of gender sensibility that enabled them to distinguish between the biological
function of childbirth (sex) and the social role of childcare (gender).
By age, the 30-39 group had the highest average (3.44), followed by the 29 oryounger group (3.39), the 40-49 group (3.26) and the 50 or older group (3.07) (F=4.148,p≤.006). The post hoc analysis found significant differences between the 50 or older
group, the 29 or younger group and the 30-39 group. The differences arising from marital
status or period of career break were not significant. The group with one child had thehighest average (3.42), followed by the group with two children (3.38), no children (3.36)
and three or more children (2.89) (F=4.204, p≤.006). The post hoc analysis foundsignificant differences between the group with three or more children and each of theremaining groups.
The difference arising from occupation was also significant. Excluding the
respondents having jobs classified as other, engineers had the highest average (3.49). Thiswas followed by students and teachers/professors (both 3.29), healthcare professionals(3.22) and researchers (3.11) (F=3.721, p≤.002). The post hoc analysis found significant
differences between researchers and engineers, and between researchers and other groups.

100

<Table 4-14. Women are born to have a way of caring children that men are not capable of in thesame way: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30 ~3940 ~ 49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.34

SD
1.347

540
413
211
210

3.39
3.44
3.26
3.07

1.415
1.322
1.273
1.259

576
712
88

3.37
3.32
3.28

1.383
1.324
1.304

722
232
305
100

3.36
3.42
3.38
2.89

1.390
1.330
1.225
1.270

219
358
226
87
335
149

3.29
3.29
3.11
3.22
3.49
3.61

1.287
1.239
1.385
1.536
1.329
1.464

664
113
155
138
270

3.33
3.13
3.28
3.34
3.48

1.418
1.424
1.390
1.310
1.123

F

p

4.148

**(.006).296(.744)

4.204**(.006)

3.721**(.002)

1.484(.205)The responses to “Women have an innate ability to take care of children, but men
do not” were analyzed by country (see Fig. 4-17). Female scientists and engineers in India
had the highest average, meaning that they were the most progressive (4.74). This wasfollowed by Nepal (3.99), Taiwan (3.80), New Zealand (3.74) and Vietnam (3.70). The
country with the lowest average was Pakistan (1.93). Female scientists and engineers inPakistan were highly conservative, believing that women have an innate ability to takecare of children.
Korea, with a score slightly lower than the median, was a distant second to Sri
Lanka (2.79). Compared to other APNN member countries, Korea has a conservative
attitude toward the role of childcare. Korean mothers are increasingly burdened with the
responsibility for childcare and private education. Women’s career breaks have grown
more severe in spite of improved policies for work-life balance. In the process of101

expanding work-life balance policies, the government has associated work-life balance
mostly with women. This social atmosphere may have influenced Korean respondents tobe more conservative.
<Figure 4-17. Women are born to have a way of caring children that men are not capable of in
the same way: Average by nation>(Lower scores mean more agreed unit: points)

11. Husbands must have more power and authority than wives for peace and orderin the household.
The third question to determine gender role ideology was “Husbands must havemore power and authority than wives for peace and order in the household.” This question
was used to assess the respondents’ perception regarding patriarchal gender relations,which is a factor driving inequality between genders. The overall average was 3.78,
meaning that the respondents generally disagreed (see Table 4-15). That is, therespondents had a fairly progressive attitude.
The difference arising from age was significant. The 29 or younger group had thehighest average (3.94), followed by the 30-39 group (3.77), the 40-49 group (3.72) andthe 50 or older group (3.43). That is, younger respondents were more inclined to be
progressive (F=7.845, p≤.000). The post hoc analysis found no significant difference
between the 30-39 group and the 40-49 group, but the differences between other groups
were significant.
The difference arising from marital status was significant. Single respondents(3.92) had a higher average than married respondents (3.68), indicating that the formergroup was more progressive (F=5.333, p≤.005). Similar trends were observed for thedifference arising from the number of children. That is, the respondents with no children
had the highest average (3.92), followed by those with one child (3.81), those with twochildren (3.62) and those with three or more children (3.62). The more the number of102children, the more conservative (F=9.305, p≤.000). The post hoc analysis foundsignificant differences between the group with three or more children and each of theother groups.
<Table 4-15. In order to maintain the order and peace of a family, the husband should have greater
power and authority than the wife: Total>(Lower scores mean more agreed unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.78

SD
1.327

541
413
211
210

3.94
3.77
3.72
3.43

1.275
1.346
1.259
1.420

577
712
88

3.92
3.68
3.72

1.274
1.354
1.373

723
232
305
100

3.92
3.81
3.62
3.27

1.294
1.308
1.333
1.325

219
358
226
87
336
149

3.80
3.47
3.97
3.63
3.92
3.97

1.183
1.263
1.254
1.549
1.367
1.430

665
113
155
138
270

3.87
4.02
3.99
3.83
3.38

1.328
1.295
1.294
1.194
1.319

F

p

7.845

***(.000)

5.333**(.005)

9.305***(.000)

6.399***(.000)

9.011***(.000)

The difference arising from occupation was also significant. Researchers had thehighest average (3.97), followed by engineers (3.92), students (3.80), healthcare
professionals (3.63) and teachers/professors (3.47) (F=6.399, p≤.000). That is,researchers were the most progressive and teachers/professors the most conservative
when it came to power relations between husband and wife. Similarly, the difference
arising from the period of career break was found to be significant. The group with acareer break of less than 1 year had the highest average (4.02), followed by the groupwith a career break of 1-2 years (3.99), the group without any career break (3.87), the103

group with a career break of 2-3 years (3.83) and the group with a career break of 3 ormore years (3.38) (F=9.011, p≤.000). The post hoc analysis found significant differences
between the group with a career break of 3 or more years and each of the other groups.
The statement “Husbands must have more power and authority than wives forpeace and order in the household” was used to examine how the respondents’ perceptionof patriarchy and gender relations varied by country (see Fig. 4-18). India, with an averageof 5, expressed the strongest disagreement. This was consistent with the results for therole of breadwinner. India was followed by New Zealand (4.68), Nepal (4.55), Taiwan(4.33) and Korea (4.18). The country with the lowest score was Vietnam (2.72), followed
by Pakistan (2.95) and Japan (3.27). Compared to their counterparts in Japan and Koreanscientists and engineers were more progressive regarding the power relationship between
husbands and wives.
<Figure 4-18. In order to maintain the order and peace of a family, the husband should havegreater power and authority than the wife: Average by nation>(Lower scores mean more agreed unit: points)

12. Men and women must assume adequate roles because the former tend to be
more rational and the latter more emotional.
The last question to determine gender role ideology was “Men and women must
assume adequate roles because the former tend to be more rational and the latter more
emotional.” This question was used to examine the stereotype that men are more rational
and women more emotional. The overall average was 2.92, slightly lower than the median(see Table 4-16). The respondents gave the most conservative responses to this questionout of the four questions on gender role ideology.
By age, the 40-49 group had the lowest average (2.67), and the 29 or younger
group the highest (2.99) (F=2.848, p≤.036). Both groups had an average below 3, but wecan see that the 49-49 group was more conservative than the 29 or younger group. The
104

post hoc analysis found significant differences between the 40-49 group and the othergroups. The difference arising from marital status was also significant. That is, single
respondents (3.03) were more progressive than married (2.83) and divorced/separated
respondents (2.93) (F=3.460, p≤.036). By the number of children, the group with nochildren had the highest average (3.10), followed by the group with one child (2.86), thegroup with two children (2.73) and the group with three or more children (2.48). That is,
the higher the number of children, the more conservative the attitude (F=9.338, p≤.000).
The post hoc analysis found significant differences between the group with three or morechildren and the group without, between the group with three or more children and thegroup with one child, and between the group with two children and the group without.
<Table 4-16. Men are rational while women are emotional and they ought to complement eachother: Total>(Lower scores mean more agreed, unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

105

Cases
1,379

Average
2.92

SD
1.387

541
413
211
210

2.99
2.95
2.67
2.95

1.387
1.362
1.371
1.434

577
712
88

3.03
2.83
2.93

1.382
1.371
1.515

723
232
305
100

3.10
2.86
2.73
2.48

1.394
1.421
1.266
1.439

219
358
226
87
336
149

2.95
2.76
3.02
2.53
3.02
3.11

1.298
1.263
1.405
1.539
1.436
1.509

665
113
155
138
270

3.09
2.96
3.03
2.73
2.54

1.400
1.426
1.468
1.412
1.215

F

p

2.848

*(.036)

3.460*(.032)

9.338***(.000)

3.559**(.003)8.699***(.000)

The difference arising from occupation was significant as well. Researchers andengineers (both 3.02) had the highest average, followed by students (2.95),
teachers/professors (2.76) and healthcare professionals (2.53) (F=3.559, p≤.003). That is,healthcare professionals were most inclined to associate rational and emotional
characteristics with specific genders. Finally, the difference arising from the period ofcareer break was also significant. The group without any career break had the highest
average (3.09), followed by the group with a career break of 1-2 years (3.03), the groupwith a career break less than 1 year (2.96), the group with a career break of 2-3 years(2.73) and the group with a career break of 3 or more years (2.54) (F=8.699, p≤.000). The
post hoc analysis found no significant difference between those without any career break,those with a career break less than 1 year and those with a career break of 1-2 years.
However, significant differences were found between the group with a career break of 3
or more years, the group with a career break of 1-2 years and the group without any career
break.
The responses to “Men and women must assume adequate roles because theformer tend to be more rational and the latter more emotional” were examined by country(see Fig. 4-19). New Zealand had the highest average (4.29), meaning that it was the mostprogressive. This was followed by India (3.97), Taiwan (3.56), Korea (3.38), Nepal (3.27)
and Japan (3.20). The country with the lowest average was Mongolia (1.74), followed by
Bangladesh (2.21), Pakistan (2.41) and Vietnam (2.44). That is, Mongolian scientists andengineers were the most conservative when it came to stereotypes of men being morerational and women being more rational, followed by their peers in Bangladesh, Pakistan
and Vietnam.
<Figure 4-19. Men are rational while women are emotional and they ought to complement
each other: Average by nation>(Lower scores mean more agreed, unit: points)

10613. I believe my career will go well.
This question examines how female scientists and engineers of APNN member
countries regard their career prospects. The overall average for the statement “I believe
my career will go well” was 3.70 (see Table 4-17), indicating a fairly positive outlook.
The difference was significant by age. The 29 or younger group had the highest score(3.88), followed by the 30-39 group (3.64), the 40-49 group (3.62) and the 50 or younger
group (3.43). That is, younger respondents envisioned more gloomy career prospects(F=11.241, p≤.000). The post hoc analysis found significant differences between the 50
or older group and each of the remaining groups and between the 29 or younger groupand each of the remaining groups.
<Table 4-17. I believe things will turn out fine in my future career: Total>(Higher scores mean more agreed, unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
3.70

SD
1.044

541
412
211
210

3.88
3.64
3.62
3.43

1.047
1.027
.971
1.066

577
711
88

3.80
3.64
3.50

1.104
.985
1.050

723
231
305
100

3.76
3.69
3.54
3.72

1.090
1.042
.928
.944

219
356
226
87
337
149

3.78
3.63
3.53
4.17
3.73
3.65

1.125
.951
1.038
.979
1.033
1.121

665
113
156
136

3.76
3.61
3.69
3.83
3.53

1.077
1.114
1.139
.865
.919

270

F

p

11.241***(.000)

5.126**(.006)

2.982*(.030)5.547***(.000)

3.250*(.012)

By marital status, single respondents had the brightest career prospects (3.80),
followed by married respondents (3.64) and respondents classified as other (3.50)
107

(F=5.126, p≤.006). The post hoc analysis found no significant difference between married
respondents and those classified as other. However, the difference between single
respondents and each of the other two groups was significant. Career prospects were also
related to the number of children. That is, the group without children and the group withthree or more children (3.72) had brighter prospects than the group with one child (3.69)
and the group with two children (3.54) (F=2.982, p≤.030). The post hoc analysis foundno significant difference between groups.
Career prospects differed according to the respondents’ occupations. Healthcare
professionals had the brightest career prospects (4.17), followed by students (3.78),
engineers (3.73), teachers/professors (3.63) and engineers (3.53) (F=5.547, p≤.000). The
post hoc analysis found significant differences between healthcare professionals and eachof the remaining groups. The difference arising from the period of career break was alsosignificant. The group with a career break of 2-3 years had the brightest career prospects(3.83), followed by students (3.76), the group with a career break of 1-2 years (3.69) andthe group with a career break less than 1 year (3.61) (F=3.250, p≤.012). The post hoc
analysis found significant differences between the group with a career break of 3 or more
years and the group with a career break of 2-3 years and between the group with a career
break of 3 or more years and the group without any career break.
The career prospects of female scientists and engineers were examined bycountry (see Fig. 4-20). Among the 12 countries, Bangladesh had the highest score (4.37),
indicating that its female scientists and engineers were the most positive. This wasfollowed by Sri Lanka (4.11), Pakistan (4.02) and Mongolia (3.99). Meanwhile, female
scientists and engineers in Japan had the gloomiest outlook (2.96). This can be attributed
to Japanese respondents having a higher-than-average age of 50.89, which was also theoldest among the 12 APNN member countries. The countries that followed were Vietnam(3.37) and Korea (3.39). Female scientists and engineers in Korea cannot be seen as being
highly positive toward their career prospects.
<Figure 4-20. I believe things will turn out fine in my future career: Average by nation>(Higher scores mean more agreed, unit: points)

10814. Strong policies are necessary to overcome gender inequality in STEM fields.
This question examined the policy demands of female scientists and engineers.
The overall average for the statement “Strong policies are necessary to overcome genderinequality in STEM fields” was 4.07 (see Table 4-18). Since the scores were reverse
coded, we can consider the respondents as having high policy demands. The difference
arising from age was significant. That is, the 30-39 age group had the highest policy
demands (4.20), followed by the 29 or younger group (4.10), the 40-49 group (4.03) andthe 50 or older group (3.80) (F=6.981, p≤.000). The post hoc analysis found that the 50
or older group had significantly lower policy demands than other age groups. The
differences arising from marital status or the number of children were not significant.
<Table 4-18. It is crucial to have strong policy support to solve gender inequality in the STEM
field: Total>(Higher scores mean more agreed, unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
109

Cases
1,379

Average
4.07

SD
1.070

541
414
210
210

4.10
4.20
4.03
3.80

1.015
.955
1.124
1.302

577
712
88

4.02
4.09
4.18

1.080
1.044
1.209

722
232
306
100

4.02
4.11
4.18
4.05

1.098
1.071
1.022
.957

219
358
226
87
336
149

3.85
4.12
4.09
4.18
4.17
3.95

1.156
1.000
1.110
.947
1.083
1.045

665
113
156
138
270

4.04
3.90
3.91
4.21
4.27

1.070
1.217
1.183
.916
.963

F

p

6.981

***(.000)

1.188(.305)

1.782(.149)

3.112**(.008)

4.820**(.001)

On the other hand, the differences arising from occupation and the duration ofcareer break were significant. By occupation, healthcare professionals (4.18) andengineers (4.17) had the highest policy demands, followed by teachers/professors (4.12),
researchers (4.09), other (3.95) and students (3.85). The post hoc analysis found thatstudents, after excluding respondents classified as other, had significantly lower policy
demands than the other career groups.
By the duration of career break, the group with a career break of 3 years or more
had the highest policy demands (4.27), followed by the group with 2-3 years (4.21) thegroup without any career break (4.04), the group with a career break of 1-2 years (3.91)
and the group with a career break less than 1 year (3.90). The post hoc analysis foundsignificant differences between the group without any career break, the group with acareer break less than 1 year, the group with a career break of 1-2 years, the group with acareer break of 2-3 years and the group with a career break of 3 or more years.
The policy demands of female scientists and engineers were examined by country(see Fig. 4-21). The overall average was 4.07 out of 5. Among the 12 countries surveyed,
9 countries had an average higher than 4. Vietnam had the highest average (4.77),
indicating that its female scientists and engineers felt a strong need for government
policies. Single respondents among Vietnamese respondents accounted only for 1%, andmost were married or divorced. As seen in the analysis of discriminatory experiences bycountry, Vietnam was the most highly ranked in terms of the struggle to maintain worklife balance. Such circumstances are likely to have contributed to the high demand forpolicies among Vietnamese respondents. The countries that followed were Nepal (4.55),
India (4.30) and Mongolia (4.26).
<Figure 4-21. It is crucial to have strong policy support to solve gender inequality in the STEM
field: Average by nation>(Higher scores mean more agreed, unit: points)

110

On the other hand, Japan had the lowest policy demands (3.15), followed by
Malaysia (3.69) and Taiwan (3.87). Korea, with an average of 4.19, was the seventh
highest among the 12 countries. Female scientists and engineers in certain countries may
have lower policy demands either because they are already satisfied with existing policies
or they do not find policies to be reliable.

15. I believe that gender equality will be fully achieved once women are given thesame opportunities as men.
The statement “I believe that gender equality will be fully achieved once women
are given the same opportunities as men” was used to examine the concept of equality as
perceived by female scientists and engineers. As explained earlier, this statement fails toreflect the concept of equality at present which stresses the equality in results as it
concentrates only on the equality of opportunity. The overall average for this statement
was 2.13, meaning that the respondents were generally satisfied with having the equalityof opportunity (see Table 4-19).
The difference arising from age was significant. The 29 or younger group had thelowest score (1.84), followed by the 30-39 group (2.04), the 40-49 group (2.47) and the
50 or older group (2.72). Younger respondents agreed more with the liberal concept ofequality (F=40.422, p≤.000). Duncan’s test found significant differences between all
possible pairs.
The difference arising from marital status was also significant. Single
respondents had the lowest average (2.03), while married respondents (2.20) and thoseclassified as other (2.22) had similar scores (F=3.795, p≤.023). The post hoc analysis
found no significant differences. The difference arising from the number of children was
significant. Female scientists and engineers with two or more children had the highest
score (2.26) and those without children the lowest (2.05) (F=2.954, p≤.032). The post hoc
analysis found no significant difference.
The difference arising from occupation was significant. Healthcare professionals(1.64) had the lowest average, followed by engineers (1.94), students (2.05) and others(2.05), teachers/professors (2.20) and researchers (2.60) (F=13.667, p≤.000). The post
hoc analysis found significant differences between researchers and the remaining
occupational groups. The difference arising from the duration of career break was not
significant.

111

<Table 4-19. I believe gender equality will be fully achieved only if women are given equal
opportunities as men: Total>(Lower scores mean more agreed, unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
1,379

Average
2.13

SD
1.149

541
413
211
210

1.84
2.04
2.47
2.72

1.044
1.048
1.148
1.291

577
712
88

2.03
2.20
2.22

1.162
1.131
1.169

723
232
305
100

2.05
2.21
2.26
2.22

1.179
1.200
1.068
1.011

219
358
226
87
336
149

2.05
2.20
2.60
1.64
1.94
2.05

1.122
1.045
1.215
1.000
1.099
1.272

665
113
155
138
270

2.06
2.25
2.24
2.22
2.11

1.177
1.278
1.223
1.038
.984

F

p

40.422***(.000)

3.795*(.023)

2.954*(.032)

13.6671.483***(.000)(.205)The perceptions of female scientists and engineers of the concept of equality were
examined by country (see Fig. 4-22). India had the lowest average (1.01), followed by
Bangladesh (1.41), Nepal (1.56) and Pakistan (1.71). Meanwhile, Japan (3.26) had thehighest average followed by Korea (3.12). That is, female scientists and engineers in India,
Bangladesh and Nepal were inclined to believe that gender equality was fully achieved
simply with equality in opportunity. This may imply the lack of laws and policies ensuring
the equality of opportunity for female scientists and engineers in these countries.
On the other hand, female scientists and engineers in Japan and Korea were more
inclined to believe that gender equality could not be achieved simply with equality inopportunity. This can be attributed to the harsh reality faced by female scientists andengineers despite improvements to related laws and policies in the two countries. It should
be noted that de jure equality does not necessarily result in de facto equality.
112

<Figure 4-22. I believe gender equality will be fully achieved only if women are given equal
opportunities as men: Average by nation>(Lower scores mean more agreed, unit: points)

113

4.3 Results of comprehensive analysis
The earlier section examined whether the responses were influenced by theindividual variables of respondents. In this section, we perform Pearson’s correlational
analysis to determine how the sub-scales of the perception of discriminatory reality,
experiences of discriminations, gender role ideology, career prospects and policy
demands are related to the other variables.
4.3.1 Correlational analysis
Table 4-20 gives the results of correlational analysis with a focus on continuous
variables. Age was directly proportionate to the number of children (r=.528, p≤.000).
Similarly, the duration of career break was longer for older respondents (r=.288, p≤.000).
There was no significant relationship between age and the awareness of discriminatory
reality. On the other hand, older respondents were more likely to have experienced greater
discrimination (r=-.079, p≤.004). Older respondents also adopted a more conservative
ideology toward gender roles (r=-.099, p≤.000). The older the age, the gloomier the careerprospects (r=-.159, p≤.000).
<Table 4-20. Correlations Matrix>

Classifications

1.
Age

2.
3.
4.
5.
6.
No. of Duration Perception Experience Genderchildren of career
of
role
of
break discrimin discrimination stereoty
ation
pes

Pearson Correlation
Sig. (2-tailed)N
Pearson Correlation .528**
2.No. ofSig. (2-tailed).000childrenN
1360
Pearson Correlation .288** .369**
3.Duration ofSig. (2-tailed)
.000
.000
career break
N
1342
1329
Pearson Correlation
.000
-.035
.054*
4.Perception ofSig. (2-tailed)
.991
.204
.048
discrimination
N
1368
1353
1337
Pearson Correlation -.079** -.147** -.097** .527**
5.Experience ofSig. (2-tailed)
.004
.000
.000
.000
discrimination
N
1371
1356
1338
1367
Pearson Correlation -.099** -.143** -.116** -.199**
6.Gender role
Sig. (2-tailed)
.000
.000
.000
.000
stereotypes
N
1374
1359
1340
1368
Pearson Correlation -.159** -.059* -.079** -.019
7.CareerSig. (2-tailed)
.000
.029
.004
.490
outlook
N
1374
1359
1340
1368
1. Agenote: Correlation is significant at the 0.05 level (2-tailed).

114

-.042
.117
1371
.152**
.000
1371

.019
.473
1374

An analysis of the relationship between the number of children and othervariables showed that respondents with more children had longer career breaks (r=.369,
p≤.000). While the number of children was not related to the perception of discriminatory
reality, it had a significant relationship to discriminatory experiences. That is, respondents
with more children had more discriminatory experiences (r=-.147, p≤.000). Those withmore children had a more conservative gender role ideology, and this is presumed to becaused by the correlation between the number of children and age (-.143, p≤.000). The
number of children and career prospects showed a weak negative correlation (r=-.059,
p≤.029). That is, those with more children had a tendency to have less positive careerprospects.
As for the relationship between career break and the awareness of discriminatory
reality, those with longer career breaks were less aware of the discriminatory reality(r=.054, p≤.048). The duration of career break was more strongly correlated todiscriminatory experiences than the awareness of the discriminatory reality. That is, thosewith longer career breaks had more discriminatory experiences (r=-.097, p≤.000). In
addition, the longer the career break, the more conservative the gender role ideology(r=-.116, p=.000); this is presumed to be related to the relationship between age and theperiod of career break. Career prospects were also gloomier among respondents withlonger career breaks (r=-.079, p≤.004).
An extremely high correlation was found between the awareness of
discriminatory reality and discriminatory experiences (r=.527, p≤.000). That is, the higher
the level of awareness, the more experiences of discrimination. Meanwhile, the awarenessof the discriminatory reality (a lower score indicates higher awareness) had a negative
correlation to gender role ideology (a higher score indicates a more progressive attitude)(r-.199, p≤.000). This shows that individuals with a more conservative gender roleideology do not perceive acts of gender discrimination as discrimination.
The awareness of the discriminatory reality was not correlated to career prospects.
The relationship between gender role ideology and the awareness of the discriminatory
reality was not significant, unlike the significant negative relationship between genderrole ideology and the perception of discriminatory reality. On the other hand, there was anegative correlation between discriminatory experiences and career prospects. That is,
the greater the discriminatory experiences, the gloomier the career prospects (r=.152,p≤.000). Lastly, there was no significant relationship between gender role ideology andcareer prospects.

115

4.3.2 Multiple regression analysis
4.3.2.1 Predictor variables of career prospects
Multiple regression analysis was performed to examine the variables influencing
the career prospects of female scientists and engineers in STEM fields. The eight
independent variables were age, number of children, duration of career break, theperception of discriminatory reality, discriminatory experiences, gender role ideology,
concept of equality and policy demands. The dependent variable was career prospects.
The analysis found that the variable having the greatest influence on career prospects was
the concept of equality. That is, the higher the adherence to the concept of equality, thebrighter the career prospects (β=-.258, p≤.000). The next most influential variable wasdiscriminatory experiences (β=.254, p≤.000). Female scientists and engineers with fewer
discriminatory experiences were more positive about their careers (β=.250, p≤.000).
Gender role ideology also had an influence on career prospects. The more conservative
the gender role ideology, the brighter the career prospects (β=-.063, p≤.013). As
explained above, the four significant variables in predicting career prospects were theconcept of equality, discriminatory experiences, policy demands and gender role ideology.
Their total variance was 18.9%, indicating a high explanatory power (R²=.189, F=76.283,
p≤.000). Other variables such as age, number of children, period of career break andawareness of the discriminatory reality were not significant.
<Table 4-21. Stepwise multiple regression analysis in Career outlook>
Independence
variable(Constant)
Equality concept
Experience of discrimination
Policy needs
Gender role stereotypes
R2
Fp

The dependent variable : Career outlook
B
B
t
p
2.495
12.673***(.000)
-.235
-.258
-9.591***(.000)
.303
.254
9.862
***(.000)
.246
.250
9.010
***(.000)
-.063
-.063
-2.477*(.013).189
76.283***(.000)

4.3.2.2 Predictor variables of policy demands
Multiple regression analysis was performed to examine the variables influencing
respondents’ policy demands, with the aim of eliminating gender discrimination in STEM
fields. The eight independent variables were age, number of children, duration of career
break, the perception of discriminatory reality, discriminatory experiences, gender roleideology, concept of equality and career prospects. The dependent variable was policy
demands. The analysis found that the variable having the greatest influence on policy
demands was the concept of equality. That is, the higher the awareness of the concept ofequality, the greater the demands (β=-.238, p≤.000). The next most influential variable116was career prospects. The better the career prospects, the greater the demands (β=.226,p≤.000). The third was discriminatory experiences. That is, female scientists andengineers with more discriminatory experiences felt a greater need for policies (β=-.172,p≤.000). Next, a greater awareness of the discriminatory reality led to more policy
demands (β=-.146, p≤.000). The fifth most influential variable was gender role ideology.
The more progressive the ideology, the greater the demands (β=.097, p≤.000). Finally,
policy demands were also related to the number of children. The higher the number ofchildren, the greater the demands (β=.061, p≤.013). As explained, the six significant
variables in predicting policy demands were the concept of equality, career prospects,
discriminatory experiences, the awareness of the discriminatory reality, gender roleideology and the number of children. With a total variance of 25.8%, these variables had
a high explanatory power (R²=.258, F=75.721, p≤.000). Other variables such as age andthe duration of career break were not significant.
<Table 4-22. Stepwise multiple regression analysis in Policy needs>
Independence
variable(Constant)
Equality concept
Perception of discrimination
Career outlook
Experience of discrimination
Gender role stereotypes
No. of children
R2
F
p

117

The dependent variable :Policy needs
B
B
t
p
4.361
24.512***(.000)
-.220
-.238
-9.118***(.000)
-.159
-.146
-4.995***(.000)
.230
.226
8.782
***(.000)
-.209
-.172
-5.886***(.000)
.100
.097
3.910
***(.000)
.063
.061
2.485
*(.013).258
75.721***(.000)4.4 Analysis of survey results by participating nation
4.4.1 Nepal
4.4.1.1 Respondent profile
A total of 94 respondents participated in Nepal. Those in their 20s accounted for
47.8%, followed by those in their 30s at 39.1%, those in their 40s at 10.9%, and those in
their 50s at 2.2%. By marital status, those married took up 52.1%, while single
respondents and others took up 46.8% and 1.1%, respectively. Among the respondents,
62% had no children; 22.8% of them had two children; 15.2% had one child; and no
respondent had three or more children. By occupation, 44.1% of the respondents werereported to be engineers, followed by researchers (12.9%) and teachers/professors(11.8%). The respondents who had not experienced career interruption accounted for
48.3%, and those who had experienced career interruption of less than one year and three
years or more accounted for 16.9% and 15.7%, respectively (see Table 4-23).
<Table 4-23. Profile of participants from Nepal>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more
118

N

%

44
36
10
2

47.8
39.1
10.9
2.2

44
49
1

46.8
52.1
1.1

57
14
21
92

62.0
15.2
22.8
0.0

6
11
12
9
41
14

6.5
11.8
12.9
9.7
44.1
15.1

43
15
7
10
14

48.3
16.9
7.9
11.2
15.7

4.4.1.2 Difference of gender barriers in Nepal and other countries: Overview<Table 4-24. Gap between Nepal & others on gender barriers>(unit: points)

Item
1. Boys are encouraged more than girls
to go into the STEM field.
2. It is more difficult for a woman to geta job in the STEM field than for aman even with the same
qualifications.
Perception
3. Becoming a tenured professor, being
promoted or becoming a principalofinvestigator is more difficult for
female scientists than for male
discrimination
scientists.
4. Women in STEM generally receive
less pay for equal work, comparedwith their equally-qualified malecolleagues.
Sub-scales
5. I have experienced disadvantages inleading or participating in research
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds orExperiencescholarships because I am a woman.
7. I have experienced sexual harassmentofor unfair treatments sometime in mydiscrimination
career.
8. Balancing work and life (marriage
and family) has been a handicap forme.
Sub-scales
9. Primary breadwinners (who take careof financial obligations) of households
should be men.
10. Women are born to have a way ofcaring children that men are notcapable of in the same way.
11. In order to maintain the order andpeace of a family, the husband should
Gender role
have greater power and authority thanstereotypes
the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each otherby doing what is appropriate forthemselves.
Sub-scales
I believe things will turn out fine in
Career outlook 13.myfuture career.
14. It is crucial to have strong policy
Policy needs
support to solve gender inequality in
the STEM field.
15.
I believe gender equality will be
Equality
fully achieved only if women areconcept
given equal opportunities as men.

Nepal Except Nepalt(p)(n=94)(n=1,285)
2.31
2.48-1.282 (.200)
2.47

2.51

-.352

(.725)

2.68

2.49

1.320

(.190)

2.57

2.95-2.700**(.007)

2.51

2.60

-0.94

(0.35)

3.16

2.98

1.189

(.237)

3.95

3.27

6.417

***
(.000)

3.20

3.31

-.760

(.447)

2.72

2.59

1.014

(.311)

3.26

3.04

2.36

4.71

3.47

3.99

3.29

4.879

***
(.000)

4.55

3.72

7.801

***
(.000)

3.27

2.89

2.882

**
(.005)

4.14

3.34

9.14

***
(.000)

3.83

3.69

1.247

(.213)

4.55

4.04

5.664

***
(.000)

1.56

2.17-6.242***(.000)* Perception of discrimination: Lower score means higher perception of discrimination* Experience of discrimination: Lower score means more discrimination experienced* Gender role stereotypes: Higher score means more progressive* Career outlook: Higher score means a more positive outlook* Policy needs: Higher score means higher needs for policy support

119*(.018)***15.117(.000)

Table 4-24 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Nepal with that perceived by their counterparts inthe other 11 countries. First, the scale of the perception of a discriminatory reality was
2.51 on the average, indicating no significant difference from the average of 2.60 fromthe other 11 nations. Examining each of the four questions contained in this scale, we
observed that the respondents in Nepal reported a significantly higher score in perceptionof a discriminatory reality (t=-2.700, p≤.007) only for the question about equal pay for
equal work. Although slight differences were found for the remaining three questions,they did reach a statistically significant level
The t-test to identify whether the Nepali respondents had a different
discriminatory experience compared with the respondents from the other countries
resulted in an average score of 3.26, which is significantly higher than the average scoreof 3.04 of the other countries (t=2.36, p≤.018). Since lower scores refer to greater
discriminatory experience, the result suggests that the respondents in Nepal had lessdiscriminatory experience than their counterparts in the other 11 countries surveyed. We
analyzed the four questions for this sub-scale and observed a significant difference onlyin the question about disadvantage in winning research grants or scholarships. In otherwords, the score of the Nepali respondents with respect to experiencing disadvantage inwinning research grants and scholarships (3.95) was lower than the average score (3.27)of the other countries (t=6.417, p≤.007). No statistically significant difference was foundin the other three questions.
The sub-scale for gender roles ideology produced a significant difference interms of both the sub-scale average and individual item average scores. The average for
Nepal had a value of 4.14, significantly higher than the average of 3.34 of the othercountries (t=9.14, p≤.000). A higher score refers to a stronger tendency of progressiveness.
For each question under in this sub-scale, the average score in Nepal was higher than the
average of the other 11 countries, suggesting a more progressive attitude toward genderroles.
The result for career prospects among the Nepali respondents did not show any
significant difference from the average score of the other 11 countries. On the other hand,a statistically significant difference was observed for policy demand. The score for policy
demand in Nepal (4.55) was significantly higher than the score (4.04) of the othercountries (t=5.664, p≤.000). In the case of gender equality, women in Nepal (1.56)
demonstrated a greater tendency, compared with women in the other countries (2.17), tobelieve that full gender equality would be realized once women were granted equal
opportunity (t=-6.242, p≤.000). Figure 4-23 illustrates the overall difference in perceptionof gender barriers between the respondents in Nepal and those in the other countries.

120

<Figure 4-23. Gap between Nepal & others on gender barriers>(unit: Points)

4.4.1.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Nepal according to the personal variables of the respondents and compare
the results with those obtained in the other countries.
Perception of Discriminatory reality
For this scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-25 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the Nepali respondents. Whereas
a significant difference was observed by age and occupation, variables such as marital
status, number of children and duration of career interruption did not show a significant
difference. By age group, those in their 30s most strongly agreed with the statement thatgender inequality existed in Nepali society, followed by those in their 50s and 20s; therespondents in their 40s agreed least with the statement (F=4.399, p≤.006).
By marital status, the perception of discriminatory reality was most strongly
perceived by the single respondents, but no statistically significant difference wasobserved, as with the cases of the number of children and period of career interruption.
On the other hand, the difference by occupation was statistically significant. The strongest
perception of gender inequality was reported by healthcare/medical professionals andleast by teachers/professors (F=2.985, p≤.016).

121

<Table 4-25. Perception of discrimination of Nepal: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more

Cases
94

Average
2.51

SD

F

p

44
36
10
2

2.52
2.28
3.40
2.38

0.70
0.80
1.48
1.59

4.399

.006

44
49
1

2.47
2.54
2.75

0.78
1.02
-

.092

.912

57
14
21
-

2.48
2.80
2.39
-

0.68
1.01
1.34
-

.923

.401

6
11
12
9
41
14

2.63
3.39
2.65
2.22
2.38
2.25

0.63
1.34
0.86
1.03
0.64
0.97

2.985

.016

43
15
7
10
14

2.47
3.02
2.46
2.48
2.14

0.76
0.83
1.06
1.10
1.19

1.761

.144

* Lower score means higher perception of discrimination

Figure 4-24 compares the perception of a discriminatory reality by the
respondents in Nepal and by those from the other countries. The level of perception ofgender inequality in society ranked fifth, following that in India, Mongolia, Korea and
Bangladesh (average score of 2.51 on the five-point scale).

122

<Figure 4-24. Average of Nepal & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-26 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of the
Nepali respondents. By age, those in their 30s reported the strongest discriminatory
experience, as in the case of the perception of discriminatory reality, and the score waslowest among those in their 40s, but without statistical significance. No significant
difference was found for the variables of marital status, the number of children, and careerinterruption. On the other hand, similar to the case of perception of a discriminatory
reality, respondents of different occupational groups produced a statistically significant
difference. The strongest experience was reported among healthcare/medical
professionals (2.31); the lowest was found among teachers/professors (3.70) (F=2.500,
p≤.036). The scores of researchers and engineers were found in between.
Figure 4-25 compares the discriminatory experience among the Nepali
respondents and among respondents from the other countries. Unlike the fifth-ranking
level of the perception of discriminatory reality perceived by the respondents in Nepal,
the actual experience of discrimination was the fourth lowest, following Sri Lanka,
Malaysia, and Pakistan (average score of 3.26 on the five-point scale).

123

<Table 4-26. Experience of discrimination of Nepal : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more

Cases
94

Average
3.26

SD

F

p

44
36
10
2

3.44
2.94
3.65
3.25

.817
.968
1.281
1.061

2.554

.061

44
49
1

3.45
3.08
3.25

.841
1.048

1.766

.177

57
14
21

3.41
3.13
2.94

.850
1.176
1.101

1.963

.147

6
11
12
9
41
14

3.50
3.70
3.31
2.31
3.30
3.25

.837
1.024
.724
.917
.890
1.152

2.500

.036

43
15
7
10
14

3.52
3.27
3.04
2.88
2.93

.856
.571
1.220
1.022
1.378

1.664

.166

* Lower score means more discrimination experienced<Figure 4-25. Average of Nepal & others on Experiences. of discrimination>(unit: points)* Lower score means more discrimination experienced

124Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Table 4-27 provides the results of ANOVA ofwhether gender role ideology varies depending on the personal variables of the Nepali
respondents. By age group, the highest score was observed among the respondents in their
50s and the score was lowest among those in their 40s; however, the difference was notstatistically significant. The differences according to the marital status, the number ofchildren, occupation, and duration of career interruption were not significant either.
<Table 4-27. Gender role stereotypes of Nepal : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more
* Higher score means more progressive

125

Cases
94

Average
4.14

SD

F

p

43
36
10
2

4.10
4.18
4.23
3.88

0.744
0.935
0.595
0.177

.165

.920

43
49
1

4.19
4.09
4.50

0.766
0.824

.282

.755

56
14
21

4.08
4.00
4.35

.827
1.074
.407

1.060

.351

6
11
12
9
40
14

3.83
4.11
4.48
4.22
4.06
4.34

.753
.479
.695
.605
.894
.585

.983

.433

42
15
7
10
14

4.08
4.13
4.21
4.30
4.25

.800
.767
.585
.815
.803

.238

.916

Figure 4-26 compares the gender role in Nepal and other countries. The averagescore for gender role attitudes among Nepali scientists and engineers recorded a highscore of 4.14 out of 5 points, which shows that the country is the third most progressive
after India and New Zealand.
<Figure 4-26. Average of Nepal & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

Career prospects
As can be seen in Figure 4-27, the respondents in Nepal demonstrated relative
optimism about their career prospects, with an average score of 3.83. This puts the country
in fifth place, following Bangladesh, Sri Lanka, Pakistan, and Mongolia.
<Figure 4-27. Average of Nepal & others on Career outlook>(unit: points)* Higher score means a more positive outlook

126

Table 4-28 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Nepali respondents. Although the score among
those in their 30s was the lowest, the age differences were not statistically significant. In
addition, the differences due to marital status were not big enough to be statisticallysignificant either. On the other hand, significant differences were found according to thenumber of children. Those with one child marked the highest score for career prospects(4.38), followed by the group without children (3.89); the lowest score (3.48) was
observed among those with two or more children (F=3.627, p≤.031). The differences by
occupation and the duration of career interruption were not significant.
<Table 4-28. Career outlook of Nepal : Demographic differences>(unit: person, points)

Classifications
Cases
Average
94
3.83
Total
Age
29 or below
44
3.98
30~39
35
3.63
40~49
10
4.00
50 or above2
4.00
Marital status
Single44
4.00
Married
48
3.71
Other
1
2.00
No. of children
None
57
3.89
1
13
4.38
2
21
3.48
3 or above
Occupation
Student
6
4.33
Teacher/professor
10
3.70
Researcher
12
3.75
Medical personnel
9
4.00
Engineer
41
3.76
Other
14
3.79
Duration of career break
None
43
3.95
Less than 1 year
15
3.40
1~2 years
7
3.86
2-3 years
94.00
3 years or more
14
3.93
* Higher score means a more positive outlook

127

SD

F

p

0.88
1.11
1.33
0.00

.858

.466

2.668

.075

3.627

.031

0.82
1.16
0.75
0.71
1.04
1.31

.424

.831

0.97
1.18
0.69
0.87
1.00

.967

.430

0.94
1.05

.939
.870
1.078

Policy demand
Table 4-29 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Nepali respondents. The variables most
relevant to policy demand were age and occupation. By age group, policy demand was
the highest score among those in their 30s (4.75) and lowest among those in their 40s(3.60) (F=6.624, p≤.000). By occupation, healthcare/medical professionals presented thestrongest policy demand (an average of 5.0, which represents a complete level ofagreement), followed by students and engineers with similar scores. The score for policy
demand was the lowest (3.45) among teachers/professors (F=6.403, p≤.000). However,policy demand showed no relation with the other variables such as the marital status, thenumber of children, and duration of career interruption.
<Table 4-29. Policy needs of Nepal : Demographic differences>Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more

Cases
94

Average
4.55

SD

44
36
10
2

4.68
4.75
3.60
4.50

.740
.439
1.430
.707

44
49
1

4.64
4.49
4.00

.838
.845

57
14
21

4.68
4.57
4.24

.711
.852
1.091

6
11
12
9
41
14

4.83
3.45
4.42
5.00
4.76
4.50

43
15
7
10
14

4.63
4.47
4.43
4.70
4.50

* Higher score means higher needs for policy support

128(unit: person, points)
F
p

6.624

.000

.570

.567

2.208

.116

.408
1.293
.793
0.000
.538
.941

6.403

.000

.817
.743
.787
.675
1.160

.234

.918

The average score for policy demand among the Nepali respondents amounted to4.55 out of 5 points, which places Nepal second only to Vietnam, as illustrated in Figure
4-28.

<Figure 4-28. Average of Nepal & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Gender equality
ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency to believe that equal opportunity was a sufficient factor ofgender equality. Table 4-30 suggests that such a belief was not affected by personalvariables.
As can be seen in Figure 4-29, the respondents in Nepal revealed a strong belief
that equal opportunity would result in perfect equality (the average score was 1.56; lower
scores represent stronger agreement). Nepal ranked third after India and Bangladesh.
<Figure 4-29. Average of Nepal & others on Equality concept>(unit: points)

129

<Table 4-30. Equality concept of Nepal : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2-3 years
3 years or more

Cases
94

Average
1.56

SD

F

p

44
36
10
2

1.59
1.58
1.30
2.50

1.019
.732
.483
2.121

1.040

.379

44
49
1

1.61
1.53
1.00

1.017
.767

.301

.741

57
14
21

1.56
1.50
1.67

.926
.855
.856

.164

.849

6
11
12
9
41
14

1.17
1.36
2.17
1.44
1.51
1.64

.408
.505
1.115
.726
.870
1.082

1.583

.173

43
15
7
10
14

1.53
1.67
1.43
1.40
1.93

.855
1.113
.787
.516
1.072

.719

.581

4.4.2 New Zealand4.4.2.1 Respondent profile
A total of 68 respondents participated in the survey in New Zealand, representing
the smallest number among the surveyed nations. By age, those in their 30s accounted forthe largest portion at 44.1%, followed by those in their 20s (36.8%), and those in their
40s and 50s.
By marital status, married respondents accounted for 42.6%, single respondents
for 32.4%, and the others took up the rest. Among the respondents, 66.2% had no children;
20.6% had two children; 8.8% had one child; and 4.4% had three or more children. Most
respondents in New Zealand belong to the group of healthcare/medical professionals,
taking up 85.3%. Seven respondents (10.3%) were engineers, and each of the remaining
three was categorized as teacher/professor, researcher, and student. It is therefore of no
significance to analyze the difference in the perception of gender barriers by using the130

occupation of respondents as a variable.
With respect to the duration of career interruption, 45.6% of the respondents had
no experience, while 19% had an interruption between one and two years. Those with twoto three years accounted for 16.2%, those with three or more years for 13.2%, and thosewith less than one year for 2.9%.
<Table 4-31. Profile of participants from New Zealand>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

25
30
10
3

36.8
44.1
14.7
4.4

22
29
17

32.4
42.6
25.0

45
6
14
3

66.2
8.8
20.6
4.4

1
1
1
58
7

1.5
1.5
1.5
85.3
10.3

31
2
13
11
9

45.6
2.9
19.1
16.2
13.2

4.4. 2.2 Difference of gender barriers in New Zealand and other countries: Overview
Table 4-32 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in New Zealand with that perceived by theircounterparts in the other 11 countries. For the sub-scale on the perception of the realityof discrimination against women, the average score of women scientists and engineers in
New Zealand was 2.52, showing no significant difference from the average of 2.60 in theother 11 countries. Analyzing each of the four questions under this sub-scale, we observed
a significant difference in the questions about whether women have more difficultyfinding a job in the STEM fields and whether women earn equal pay for equal work. For
131

the former question, the average score in New Zealand had a value of 3.10, much higher
than the average score of 2.48 in the other 11 countries. In other words, the respondents
in New Zealand agreed to a lesser degree with the statement that women scientists andengineers have greater difficulty finding a job than their male counterparts (t=4.279,
p≤.000).
In the meantime, the respondents in New Zealand had an average score of 2.52,
compared with 2.96 for the other 11 countries, with regard to the statement that womenearn less pay for equal work conducted by their male counterparts. This shows that theparticipants in New Zealand agreed more with the wage discrimination by gender than
did the respondents in the other 11 countries surveyed (t=-3.802, p≤.000). Although slightdifferences were found for the remaining two questions, they did reach a statisticallysignificant level.
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in New Zealand with that experienced by respondents inthe other countries, the average score for New Zealand was 2.99, which is slightly higher
than the average of 3.06 of the 11 countries (lower scores represent more discriminatory
experience); however, the difference was not statistically significant. Examining thedifferences for each of the four questions constituting this sub-scale, we found moreexperience of sexual harassment and unfair treatment among the respondents in New
Zealand than among those in the other 11 countries (t=-4.594, p≤.007). On the other hand,the experience of having work-life balance as a handicap was reported less in New
Zealand compared with the other nations (t=2.063, p≤.039). This is perhaps because New
Zealand has established more sound systems and culture for work-life balance than mostmember states of APNN.

With respect to the scale of the gender role ideology (higher scores refer to moreprogressive attitudes), significant differences were observed in the average scores of boththe sub-scale and individual questions, as was the case with Nepal. The average score of
4.28 for this sub-scale in New Zealand proved significantly higher than 3.35 in theremaining 11 countries (t=9.065, p≤.000). For each question under this criterion, theaverage score in New Zealand was higher than the average of the other 11 countries,
suggesting a more progressive attitude toward gender roles.

132

<Table 4-32. Gap between New Zealand & others on gender barriers>(unit: points)

Perceptionofdiscrimina
tion

Experienceofdiscrimina
tion

Genderrole
stereotypes

Careeroutlook
Policyneeds
Equality
concept

Item
1. Boys are encouraged morethan girls to go into the STEM
field.
2. It is more difficult for a woman
to get a job in the STEM field
than for a man even with thesame qualifications.
3. Becoming a tenured professor,
being promoted or becoming a
principal investigator is moredifficult for female scientists
than for male scientists.
4. Women in STEM generally
receive less pay for equal
work, compared with theirequally-qualified malecolleagues.
Sub-scales
5. I have experienced
disadvantages in leading or
participating in research
projects because I am awoman.
6. I have experienced
disadvantages in receiving
research funds or scholarships
because I am a woman.
7. I have experienced sexual
harassment or unfair treatments
sometime in my career.
8. Balancing work and life
(marriage and family) has beena handicap for me.
Sub-scales
9. Primary breadwinners (whotake care of financial
obligations) of households
should be men.
10. Women are born to have a
way of caring children that
men are not capable of in thesame way.
11. In order to maintain the orderand peace of a family, thehusband should have greater
power and authority than thewife.
12. In a relative sense, men are
rational while women are
emotional and thus, they ought
to complement each other by
doing what is appropriate forthemselves.
Sub-scales
13. I believe things will turn out
fine in my future career.
14. It is crucial to have strong
policy support to solve genderinequality in the STEM field.
15. I believe gender equality will
be fully achieved only if
women are given equal
opportunities as men.

New Zealand
Except New(n=94)
Zealand (n=1,285)

(p)

2.34

2.47

-.995

.323

3.10

2.48

4.279

.000

2.29

2.51

-1.900 .061

2.34

2.96

-3.802 .000

2.52

2.60

-.700

.484

2.99

3.00

-.069

.945

3.49

3.31

1.651

.102

2.57

3.34

-4.594 .000

2.90

2.59

2.063

.039

2.99

3.06

-.676

.499

4.43

3.51

7.486

.000

3.74

3.32

2.509

.012

4.68

3.73

8.442

.000

4.29

2.85

10.145 .000

4.28
3.68

3.35
3.70

9.065
-.172

.000
.864

4.25

4.06

1.419

.156

1.78

2.15

-2.571 .010

* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

133tFor career prospects, the respondents in New Zealand showed results similar to
those in the other 11 countries. Policy demand in the country was slightly higher than in
the other participating nations, but no significant difference was found. In the case ofequality, the tendency to believe that full gender equality would be realized once women
were granted equal opportunity was significantly higher in New Zealand (1.78) than in
the other countries (2.15) (t=-2.571, p≤.010). Figure 4-30 illustrates the overall differencein perception of gender barriers between the respondents in New Zealand and those in theother countries<Figure 4-30. Gap between New Zealand & others on gender barriers>(Unit: Points)

4.4.2.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in New Zealand according to the personal variables of the respondents andcompare the results with those obtained in the other countries.
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-33 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the respondents in New Zealand.
By age, the perception of a discriminatory reality was highest among those in their 40s
and lowest among those in their 50s; however, the difference did reach statisticalsignificance. Marital status and the number of children did not result in a significant
difference, either. By occupation, the perception of a discriminatory reality was highest
among teachers/professors and lowest among engineers; however, the difference was notof statistical significance. The difference depending on the duration of career interruption
was not significant, either.
134

<Table 4-33. Perception of discrimination of New Zealand: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
68

Average
2.52

SD

F

p

25
30
10
3

2.72
2.48
1.93
3.17

0.79
0.87
0.74
1.42

2.739

.051

22
29
17

2.42
2.46
2.75

0.75
1.01
0.77

.800

.454

45
6
14
3

2.51
2.67
2.46
2.67

0.81
0.86
1.10
1.13

.103

.958

1
1
1

2.25
2.00
2.50

.485

.747

58
7

2.58
2.14

0.91
0.67

31
2
13
11
9

2.53
3.13
2.21
2.89
2.42

0.86
0.18
0.71
1.22
0.71

1.145

.344

* Lower score means higher perception of discrimination<Figure 4-31. Average of New Zealand & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

135

Figure 4-31 compares the perception of a discriminatory reality by the
respondents in New Zealand and by those from the other countries. The level ofperception of gender discrimination in society ranked sixth, following that in India,
Mongolia, Korea, Bangladesh, and Nepal (average score of 2.52 on the five-point scale).
Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-32 compares the discriminatory experienceamong the respondents in New Zealand and among respondents from the other countries.
As mentioned above, the level of perception of a discriminatory reality among the
respondents in New Zealand was sixth highest, and the actual experience of
discrimination was fifth highest, following India, Vietnam, Mongolia, and Japan (averagescore of 2.99 on the five-point scale).
<Figure 4-32. Average of New Zealand & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Table 4-34 provides the results of ANOVA of whether discriminatory experiencevaries depending on the personal variables of the respondents in New Zealand. By age,the score for discriminatory experience was highest among those in their 30s (2.73) andlowest among those in their 50s (3.58) (F=4.463, p≤.007). The difference according tomarital status was of statistical significance: the discriminatory experience resulted in thehighest score (2.66) among the married respondents and lowest (3.37) among the othergroup (F=4.446, p≤.015).

136

<Table 4-34. Experience of discrimination of New Zealand : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
68

Average
2.99

SD

F

p

25
30
10
3

3.39
2.68
2.73
3.58

0.69
0.82
1.07
0.38

4.463

.007

22
29
17

3.13
2.66
3.37

0.77
0.92
0.71

4.446

.015

45
6
14
3

3.11
2.92
2.64
2.92

0.81
0.77
0.92
1.61

1.034

.383

1
1
1

3.25
1.75
3.25

.597

.666

58
7

2.98
3.14

0.88
0.91

31
2
13
11
9

3.05
3.50
2.63
3.16
2.89

0.85
0.00
0.79
1.08
0.94

.854

.497

* Lower score means more discrimination experienced

Conversely, no significant differences were observed in terms of the numberof children, occupation, and career interruption. As mentioned above with respect to the
respondent profile of New Zealand, most of the respondents in the country wereengineers and therefore it is not practical to consider occupation as a meaningfulvariable for analysis.
Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Table 4-35 provides the results of ANOVA ofwhether gender role ideology varies depending on the personal variables of the
respondents in New Zealand. By age group, the highest score (conservative) was observed137

among the respondents in their 50s, and the score was lowest among those in their 40s;
however, the difference was not statistically significant. Although married respondents
revealed a more conservative tendency compared with the other group, the difference interms of the marital status did not prove statistically significant. Next, the number ofchildren resulted in a significant difference: the respondents with three or more children
were found to be notably more conservative than other respondents. The difference
between the other groups was not significant (F=3.007, p≤.037), and the differences interms of occupation and duration of career interruption were not significant, either.
<Table 4-35. Gender role stereotypes of New Zealand : Demographic differences>Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
* Higher score means more progressive

138(unit: person, points)
F
p

Cases
68

Average
4.28

SD

25
30
10
3

4.29
4.30
4.35
3.83

0.79
0.84
0.65
1.59

.321

.810

22
29
17

4.33
4.11
4.51

0.67
0.92
0.77

1.372

.261

45
6
14
3

4.29
4.42
4.46
3.00

0.80
0.52
0.83
0.66

3.007

.037

1
1
1

5.00
5.00
4.50

.530

.714

58
7

4.23
4.46

0.84
0.67

31
2
13
11
9

4.31
4.63
4.33
4.18
4.17

0.75
0.53
0.69
1.15
0.98

.177

.950

Figure 4-33 compares attitudes toward gender roles among the respondents in
New Zealand and among respondents from the other countries. The average score forgender role attitudes had a value of 4.28 out of 5, making the country second mostprogressive following India.
<Figure 4-33. Average of New Zealand & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

Career prospects
As can be seen in Figure 4-34, the respondents in New Zealand demonstrated
relative optimism about their career prospects, with an average score of 3.68. This puts
the country in seventh place, following Bangladesh, Sri Lanka, Pakistan, Mongolia, Nepal,
and Taiwan.
<Figure 4-34. Average of New Zealand & others on Career outlook>(unit: points)* Higher score means a more positive outlook

139

Table 4-36 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the respondents in New Zealand. By age, thecareer prospects were most optimistic among those in their 50s and least optimistic among
those in their 30s, but no significant difference was observed. Marital status did not resultin a statistically significant difference, either, although the score among the single
respondents was higher than that among the married and the other group. In addition, no
significant difference was found in terms of the number of children, the occupation ofcareer interruption, or occupation.
<Table 4-36. Career outlook of New Zealand : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
68

Average
3.68

SD

F

p

25
30
10
3

3.88
3.47
3.70
4.00

1.13
1.07
1.25
1.00

.712

.549

22
29
17

3.91
3.48
3.71

1.06
1.12
1.16

.925

.402

45
6
14
3

3.73
4.00
3.43
3.33

1.07
0.89
1.28
1.53

.524

.667

1
1
1

4.00
2.00
4.00

.932

.451

58
7

3.64
4.14

1.13
0.90

31
2
13
11
9

3.74
4.00
3.38
3.64
3.67

1.00
1.41
1.12
1.57
1.00

.274

.894

* Higher score means a more positive outlook

Policy demand
The respondents in New Zealand had a relatively higher average of 4.25 out of 5
for policy demand. Table 4-37 provides the results of ANOVA of whether policy demand140

varies depending on the personal variables of the respondents in New Zealand. The
correlations between policy demand and personal variables all proved statisticallyinsignificant. By age, the score for policy demand was lowest among those in their 50s.
However, the difference was not significant because the number of the respondents older
than 50 was only three.
<Table 4-37. Policy needs of New Zealand : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
68

Average
4.25

SD

F

p

25
30
10
3

4.28
4.33
4.30
3.00

0.98
0.88
1.06
2.00

1.653

.186

22
29
17

4.36
4.07
4.41

0.85
1.19
0.87

.814

.448

45
6
14
3

4.44
3.83
4.00
3.33

0.81
0.75
1.47
1.15

2.092

.110

1
1
1

4.00
5.00
5.00

.382

.820

58
7

4.26
4.00

1.07
0.58

31
2
13
11
9

4.61
4.00
4.15
3.73
3.89

0.80
0.00
0.80
1.56
0.93

2.231

.076

* Higher score means higher needs for policy support

As can be seen in Figure 4-35, these results place the country in the fifth rank,following Vietnam, Nepal, India, and Mongolia.

141

<Figure 4-35. Average of New Zealand & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Gender equality
Table 4-38 shows the ANOVA conducted to identify whether personal variables
resulted in a different level of tendency among the respondents in New Zealand to believethat equal opportunity was a sufficient factor of gender equality.
The result indicates that a significant difference was observed only for the numberof children, and no statistical significance was found for the other variables. The averageamong the respondents with three or more children was highest, followed by that among
the women with one child. The difference between the remaining two groups was notnotable (F=4.193, p≤.009).
As can be seen in Figure 4-36, the respondents in New Zealand showed a tendency
to believe that full gender equality would be realized once women were granted equal
opportunity (average of 1.78; lower scores represent stronger agreement). This ranks thecountry in fourth place, following India, Bangladesh, and Nepal.
<Figure 4-36. Average of New Zealand & others on Equality concept>(unit: points)

142

<Table 4-38. Equality concept of New Zealand : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
68

Average
1.78

SD

F

p

25
30
10
3

1.84
1.63
2.10
1.67

1.07
0.96
1.45
1.15

.505

.680

22
29
17

1.77
1.86
1.65

0.97
1.19
1.06

.209

.812

45
6
14
3

1.67
2.17
1.57
3.67

0.98
0.75
1.16
1.15

4.193

.009

1
1
1

1.00
1.00
3.00

.577

.680

58
7

1.78
1.86

1.11
0.90

31
2
13
11
9

1.71
2.00
1.38
2.00
2.33

0.94
0.00
0.65
1.61
1.32

1.188

.325

4.4.3 Malaysia

4.4.3.1 Respondent profile
A total of 175 respondents participated in Malaysia, recording the highest numberin this survey. Table 4-39 is the respondent profile, by age, marital status, number ofchildren, occupation, and the duration of career interruption.
Those in their 20s accounted for 72.6%, followed by those in their 30s at 22.9%,
those in their 40s at 3.4%, and those in their 50s at 1.1%. This indicates that the age
distribution among Malaysian respondents was highly biased, with their average age
being the youngest among the 12 countries at 25.59 years of age. Therefore, thischaracteristic must be considered in analyzing the differences by age. By marital status,
single respondents accounted for 76.6%; those married for 19.4%; and others for 4.0%,
reflecting the biased distribution of age groups. Likewise, those without children
143accounted for 83.4%, followed by those with three or more children (7.4%), those withtwo children (5.1%), and those with one child (2.9%).
By occupation, 61.1% of the respondents reported themselves to be students,
followed by engineers (21.7%), teachers/professors (11.4%), researchers (1.1%), andhealthcare/medical professionals (0.6%). The respondents who had not experienced
career interruption accounted for as much as 72%, whereas 7.4% of them reported having
had an interruption of less than one year and 6.3% an interruption between 1-2 years. For
analysis of Malaysian surveys, it is important to factor in that the respondents were fairly
young and most of them were students.
<Table 4-39. Profile of participants from Malaysia>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

127
40
6
2

72.6
22.9
3.4
1.1

134
34
7

76.6
19.4
4.0

146
5
9
13

83.4
2.9
5.1
7.4

107
20
2
1
38
7

61.1
11.4
1.1
.6
21.7
4.0

126
13
11
5
5

72.0
7.4
6.3
2.9
2.9

4.4.3.2 Difference of gender barriers in Malaysia and other countries: Overview
Table 4-40 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Malaysia with that perceived by their counterpartsin the other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 3.20 in Malaysia, showing a significant
144difference from the score of 2.51 among the other 11 countries (t=2.36, p≤.018). For thissub-scale, a lower score translates into a higher agreement with the idea of the perceptionof discriminatory reality. It is therefore concluded that Malaysian women tend to perceivea discriminatory reality less strongly than do their counterparts in other countries.
Analyzing each of the four questions under this sub-scale, we observed weaker
perception of a discriminatory reality by Malaysian women in all four questions. A
significant difference in the questions was about whether women have more difficultyfinding a job in the STEM fields and whether women earn equal pay for equal work. For
the former question, the average score in Malaysia had a value of 3.10, much higher than
the average score of 2.48 in the other 11 countries. In other words, the respondents in
Malaysia agreed to a lesser degree with the statement that women scientists and engineers
have greater difficulty finding a job than their male counterparts (t=4.279, p≤.000). With
regard to the statement “Boys are more encouraged than girls to choose the STEM fields,”
the respondents in Malaysia demonstrated less agreement, with an average of 3.13,
compared with the average (2.37) of the other countries (t=8.301, p≤.000). In addition,
Malaysian women agreed less strongly (3.09), compared with their counterparts in theother countries (2.42), with the statement “Compared with men, women with the sameabilities face greater difficulty finding a job in the STEM fields” (t=7.106, p≤.000). On
the other hand, for the statement “Women scientists have more difficulty than their malecounterparts in becoming full-time professors or managers,” the Malaysian respondents(3.25) revealed a weaker perception than in other countries (2.40) (t=8.734, p≤.000).
Lastly, regarding the statement “Women receive less wages for the same work in the
STEM fields than men with the same qualifications,” women in Malaysia agreed lessstrongly (3.32) compared with the respondents in the other countries (2.87) (t=4.776,p≤.000).
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Malaysia with that experienced by respondents in theother countries, the average score in Malaysia was 3.43, significantly higher than the
average of 3.00 in the other countries (t=6.288, p≤.000). Since lower scores refer togreater discriminatory experience, the result suggests that the respondents in Malaysia
had less discriminatory experience than their counterparts in the other 11 countries
surveyed. Examining the differences for each of the four questions constituting this subscale, we found a significant difference in all questions other than that about theexperience of sexual harassment and other unfair treatment. With respect to the difficultyin participating in research projects or becoming research managers, the respondents in
Malaysia (3.34) had a lower average score than those in the other countries (2.95)(t=4.430, p≤.000). The likelihood of experiencing disadvantage in winning research
grants or scholarships was significantly lower among Malaysian women (3.75) than it
was for the others (3.25) (t=5.769, p≤.000). The respondents in Malaysia also showed a145

significantly lower average (3.20) than the others (2.51) regarding whether work-lifebalance worked as a handicap (t=7.449, p≤.000).
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Malaysia had an average score of 3.15,
significantly lower than the average score of 3.43 among the other countries (t=-3.944,p≤.000). This suggests that Malaysian women tend to be more conservative. For
individual questions, the Malaysian women proved more conservative (t=-3.944, p≤.000)
compared with the respondents in the other countries, regarding the ideas that men are
bread-winners of a household (t=-5.559, p≤.000), that women have an inherent ability totake care of babies (t=-2.553, p≤.011), and that husbands should have more power thantheir wives to maintain order within the family (t=-3.805, p≤.000). They did not, however,show a difference with respect to the idea that men and women should have respectively
suitable jobs since men are rational and women emotional.
With respect to career prospects, the respondents in Malaysia showed nodifference from those in the other 11 countries surveyed. However, Malaysian women
had a significantly lower average (3.69) for policy demand, compared with theircounterparts in the other countries (4.13) (t=-4.672, p≤.000). Lastly, the tendency tobelieve that full gender equality would be realized once women were granted equal
opportunity proved similar in Malaysia and other countries.
Figure 4-37 illustrates the overall difference in perception of gender barriers
between the respondents in Malaysia and those in the other countries. ><Figure 4-37. Gap between Malaysia & others on gender barriers>(Unit: Points)

146

<Table 4-40. Gap between Malaysia & others on gender barriers>(unit: points)

ExceptMalaysia
Item
Malaysia(n=175)(n=1,024)
1. Boys are encouraged more than girls
3.13
2.37
to go into the STEM field.
2. It is more difficult for a woman toget a job in the STEM field than for a
3.09
2.42
man even with the same qualifications.
3. Becoming a tenured professor, being
Perception of promoted or becoming a principal
2.40
discrimination investigator is more difficult for female 3.25
scientists than for male scientists.
4. Women in STEM generally receive
less pay for equal work, compared with 3.32
2.87
their equally-qualified male colleagues.
Sub-scales
3.20
2.51
5. I have experienced disadvantages inleading or participating in research
3.34
2.95
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds or scholarships 3.75
3.25
Experience of because I am a woman.
discrimination 7. I have experienced sexual
harassment or unfair treatments
3.45
3.28
sometime in my career.
8. Balancing work and life (marriage
2.51
and family) has been a handicap for me. 3.20
Sub-scales
3.43
3.00
9. Primary breadwinners (who take careof financial obligations) of households
3.07
3.62
should be men.
10. Women are born to have a way ofcaring children that men are not capable 3.11
3.37
of in the same way.
11. In order to maintain the order andGender role peace of a family, the husband should
3.46
3.83
have greater power and authority thanstereotypes
the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each other
2.94
2.92
by doing what is appropriate forthemselves.
Sub-scales
3.15
3.43
13. I believe things will turn out fine in
3.62
3.71
Career outlook my future career.
14. It is crucial to have strong policy
3.69
4.13
Policy needs support to solve gender inequality in
the STEM field.
15. I believe gender equality will be
Equality
fully achieved only if women are given
2.25
2.11
concept
equal opportunities as men.
* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

147

t

(p)

8.301

.000

7.106

.000

8.734

.000

4.776

.000

9.134

.000

4.430

.000

5.769

.000

1.608

.109

7.449

.000

6.288

1371

-5.559.000-2.553.011-3.805

.000

.198

.843

-3.944.000-.925-4.672
1.524

4.4.3.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Malaysia according to the personal variables of the respondents and compare
the results with those obtained in the other countries.
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-41 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the Malaysian respondents.
<Table 4-41. Perception of discrimination of Malaysia: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
175

Average
3.20

SD

F

p

127
40
6
2

3.27
3.00
2.88
3.25

0.86
1.10
0.52
0.71

1.165

.325

134
34
7

3.22
3.07
3.32

0.92
0.89
1.09

.420

.657

146
5
9
13

3.22
3.30
3.28
2.75

0.91
0.82
1.28
0.65

1.109

.347

107
20
2
1
38
7

3.27
3.29
3.75
4.00
3.00
2.68

0.87
0.74
0.35

1.270

.279

126
13
11
5
5

3.11
3.33
3.64
3.30
3.45

0.92
1.06
1.17
0.69
0.51

1.038

.389

1.11
0.89

* Lower score means higher perception of discrimination

Since only eight respondents in their 40s and 50s participated in the survey, with mostof the respondents being single or without children, no significant implication can be
drawn from the analysis of differences by age, marital status, and the number of148

children. ANOVA found no significant difference according to personal variables. Byage, the respondents in their 20s, representing the largest share of the survey
participants, had an average score of 3.27, which suggests that young women in
Malaysia tend to have weak awareness of discrimination. Albeit statisticallyinsignificant, awareness of discrimination was found to be higher among those in their
30s and 40s, rather than those in their 20s. Unlike in the past, women of today seem toexperience stronger discrimination when they have a job and get married after
graduating from school. No significant difference was found for the variables of marital
status, number of children, occupation, and duration of career interruption.
Figure 4-38 compares the perception of a discriminatory reality by the
respondents in Malaysia and by those from the other countries. The level of perceptionof gender discrimination in society was below the median level, only higher than Sri
Lanka (average score of 3.20 on the five-point scale).
<Figure 4-38. Average of Malaysia & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-42 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of the
Malaysian respondents. By age, most discriminatory experience was reported by those in
their 40s (2.71), and least by those in their 50s (4.13). Between those two extremes, thosein their 30s (3.26) reported slightly more experience of discrimination than those in their
20s (3.51) (F=3.241, p≤.024). By marital status, discriminatory experience was lessamong single respondents than among the married or the other group, but this difference
was not statistically significant. In addition, no significant difference was found for thenumber of children, duration of career interruption, or occupation.
149

<Table 4-42. Experience of discrimination of Malaysia : Demographic differences>(unit: person, points)

Classifications

SD

F

3.51
3.26
2.71
4.13

0.81
0.77
0.70
0.88

3.241

134
34
7

3.50
3.23
3.18

0.81
0.77
0.90

1.899

.153

None
1
2
3 or above
Occupation

146
5
9
13

3.47
3.15
3.31
3.19

0.80
0.80
1.01
0.81

.737

.531

Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career break

107
20
2
1
38
7

3.50
3.41
4.13
2.00
3.29
3.21

0.82
0.72
1.24

1.436

.214

126
13
11
5
5

3.43
3.17
3.77
3.30
3.45

0.77
0.81
1.25
0.86
0.87

.830

.508

Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of children

None
Less than 1 year
1~2 years
2~3 years
3 years or more

Cases

Average

175

3.43

127
40
6
2

p

.024

0.81
0.71

* Lower score means more discrimination experienced

Figure 4-39 compares the discriminatory experience among the respondents in
Malaysia and among respondents from the other countries. Just as the awareness of adiscriminatory reality was second lowest among women in science and engineering in
Malaysia, the actual experience of discrimination in this country was also second lowest
after Sri Lanka (average score of 3.43 on the five-point scale). In other words, scientists
and engineers in Malaysia tend to report less perception and experience of discrimination
against women than do their counterparts in other APNN member nations. This isprobably because the respondents had a low level of sensitization to perceiving
discrimination as discrimination, or because no notable discrimination exists in reality.

150

<Figure 4-39. Average of Malaysia & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-40 compares attitudes toward genderroles among the respondents in Malaysia and among respondents from the other countries.
The Malaysian respondents scored 3.15 out of 5 in the scale of gender role ideology,
representing a slightly higher level than the median. Compared with other countries, thisaverage score in Malaysia was higher only than that in Pakistan, Mongolia, Bangladesh,and Vietnam.
<Figure 4-40. Average of Malaysia & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

Table 4-43 provides the results of ANOVA of whether gender role ideology
varies depending on the personal variables of the Malaysian respondents. By age group,
the highest score was observed among the respondents in their 20s, and the score was151lowest among those in their 50s; however, the difference was not statistically significant.
Marital status produced a statistically significant difference, suggesting a moreprogressive attitude toward gender roles among the single respondents (3.25), comparedwith the married (2.88) and the other group (2.39) (F=5.350, p≤.006). According to thenumber of children, the attitude toward gender roles was more progressive among thewomen with two children (3.31) than among the women without children (3.22), with one
child (3.05), or with three or more children (2.46). In particular, the average scoreobtained for the respondents with three or more children produced a significant difference
from the other groups (F=3.252, p≤.023). No significant difference was observed for
occupation or duration of career interruption.
<Table 4-43. Gender role stereotypes of Malaysia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
175

Average
3.15

SD

F

p

127
40
6
2

3.19
3.09
3.04
2.00

0.84
0.98
0.80
1.06

1.305

.274

134
34
7

3.25
2.88
2.39

0.84
0.93
0.76

5.350

146
5
9
13

3.22
3.05
3.31
2.46

0.83
0.89
1.01
0.93

3.252

107
20
2
1
38
7

3.21
3.01
4.00
2.00
3.07
2.86

0.84
0.97
1.41

126
13
11
5
5

3.22
2.88
2.89
3.20
3.20

0.88
0.78
1.24
1.24
0.62

* Higher score means more progressive

152

.006

.023

1.139

.342

.701

.593

0.89
0.93

Career prospects
Table 4-44 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Malaysian respondents. No significant
difference was found for age, marital status, number of children, or duration of careerinterruption. By occupation, students reported less optimistic career prospects thanteachers/professors or engineers; however, the difference was not significant.
<Table 4-44. Career outlook of Malaysia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
175

Average
3.62

SD

F

p

127
40
6
2

3.61
3.70
3.33
4.00

1.15
1.22
1.21
1.41

.258

.855

134
34
7

3.61
3.79
3.00

1.15
1.09
1.63

1.386

.253

146
5
9
13

3.60
4.00
4.00
3.54

1.14
1.41
1.00
1.27

.536

.658

107
20
2
1
38
7

3.61
3.85
2.50
5.00
3.55
3.71

1.14
0.99
2.12

.843

.521

126
13
11
5
5

3.58
3.92
3.18
4.40
3.80

1.15
1.19
1.60
0.89
1.30

1.186

.319

1.29
1.11

* Higher score means a more positive outlook

As can be seen in Figure 4-41, the respondents in Malaysia demonstrated relative
optimism about their career prospects, with an average score of 3.62. However, thisindicates that the country had the fifth lowest average, following Japan, Vietnam, Korea,
and India.

153

<Figure 4-41. Average of Malaysia & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Policy demandWith respect to policy demand, women scientists and engineers in Malaysia had
an average score of 3.69 out of 5, suggesting a level higher than the median. However,this score is lower than that in the other countries. As can be seen in Figure 4-42, policy
demand by Malaysian women was second lowest after Japan.
<Figure 4-42. Average of Malaysia & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Table 4-45 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Malaysian respondents. No personal variables
suggested a statistical relevance to policy demand. This result is partially because thepersonal variables were not evenly distributed among the respondents. By marital status,
the single respondents reported more policy demand than the married respondents;
however, the difference was not significant.
154

<Table 4-45. Policy needs of Malaysia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
175

Average
3.69

SD

F

p

127
40
6
2

3.69
3.70
3.33
4.50

1.18
1.16
1.03
0.71

.508

.677

134
34
7

3.75
3.53
3.29

1.15
1.08
1.80

.948

.390

146
5
9
13

3.74
3.00
3.67
3.54

1.16
1.41
1.32
0.78

.764

.516

107
20
2
1
38
7

3.70
3.80
1.50
5.00
3.68
3.71

1.15
1.11
0.71

1.747

.126

126
13
11
5
5

3.79
3.62
2.82
3.60
3.00

1.12
1.45
1.60
0.89
0.00

2.197

.072

1.19
1.11

* Higher score means higher needs for policy support

Gender equality
Table 4-46 shows the ANOVA conducted to identify whether personal variables
resulted in a different level of tendency among the respondents in Malaysia to believe that
equal opportunity was a sufficient factor of gender equality. As a result, age proved not
to be a meaningful variable. By marital status, although the single respondents had astronger belief that equal opportunity was sufficient than the married or the other group,
the difference was not statistically significant. The results according to the number ofchildren were not consistent, either. By occupation (excluding the only respondent
categorized as healthcare/medical professional), engineers (1.97) tend to most strongly
accept the concept of equal opportunity, followed by students (2.26) andteachers/professors (2.40) (F=3.249, p≤.008). No significant difference was found for thelength of career interruption.
155

<Table 4-46. Equality concept of Malaysia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
175

Average
2.25

SD

F

p

127
40
6
2

2.23
2.23
2.83
2.50

1.17
1.17
0.98
2.12

.547

.651

134
34
7

2.17
2.53
2.43

1.15
1.13
1.51

1.364

.258

146
5
9
13

2.22
2.60
2.22
2.54

1.18
1.14
1.09
1.20

.444

.722

107
20
2
1
38
7

2.26
2.40
5.00
1.00
1.97
2.57

1.12
1.10
0.00

3.249

.008

126
13
11
5
5

2.18
2.31
1.82
3.00
3.40

1.20
1.32
0.75
0.71
0.55

2.217

.070

1.22
0.98

<Figure 4-43. Average of Malaysia & others on Equality concept>(unit: points)

As can be seen in Figure 4-43, the tendency to believe that full gender equality
would be realized once women were granted equal opportunity proved slightly higher
156

than the median level in Malaysia (average of 2.25; a lower score represents stronger
agreement). This score is fourth highest following the averages in Japan, Korea, and Sri
Lanka.
4.4.4 Mongolia
4.4.4.1 Respondent profile
A total of 161 respondents participated in the survey in Mongolia (see Table 447), the second largest number after Malaysia. The age distribution was relatively even,with 32.3% in 40s, 28% in 30s, 26.7% in 20s, and 13% in 50s. By marital status, married
respondents represented 72%, single 19.3%, and the other group 8.7%. The largest groupof respondents had two children (37.9%), followed by those with three or more children(23%), those with one child (20.5%), and those without children (18.6%). By occupation,engineers were largest in number (42.9%), followed by teachers/professors (34.8%),
researchers (15.5%), and students (6.8%). Most of the respondents (46%) had at least
three years of career interruption, 24.8% had two to three years of interruption, and 18%
had experienced no career interruption.
4.4.4.2 Difference of gender barriers in Mongolia and other countries: Overview
Table 4-48 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Mongolia with that perceived by their counterpartsin the other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 2.21 in Mongolia, showing a significant
difference from the value of 2.65 among the other 11 countries (t=-6.832, p≤.000). Thisimplies that women in Mongolia tend to more strongly perceive discrimination against
women in their society, compared with their counterparts in the other countries. As aresult of analyzing each of the four questions included in this sub-scale, we observed asignificant difference in all three questions, except for the question about the same wages
for the same work. With regard to the statement “Boys are more encouraged than girls tochoose the STEM fields,” the respondents in Mongolia demonstrated more agreement,with an average of 1.93, compared with the average (2.53) of the other countries (t=-7.408,
p≤.000).
In addition, Mongolian women more strongly agreed (1.93), compared with theircounterparts in the other countries (2.59), with the statement “Compared with men,
women with the same abilities face greater difficulty finding a job in the STEM fields”(t=-7.408, p≤.000). Furthermore, for the statement “Women scientists have moredifficulty than their male counterparts in becoming full-time professors or managers,” theMongolian respondents (2.16) revealed a stronger perception than in other countries (2.55)(t=-4.499, p≤.007).

157

<Table 4-47. Profile of participants from Mongolia>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

43
45
52
21

26.7
28.0
32.3
13.0

31
116
14

19.3
72.0
8.7

30
33
61
37

18.6
20.5
37.9
23.0

11
56
25
69

6.8
34.8
15.5
42.9

29
4
13
40
74

18.0
2.5
8.1
24.8
46.0

As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Mongolia with that experienced by respondents in theother countries, the average score in Mongolia was 2.89, significantly different from theaverage of 3.08 in the other countries (t=-3.236, p≤.001). Since lower scores refer togreater discriminatory experience, the result suggests that the respondents in Mongolia
had more discriminatory experiences than their counterparts in the other 11 countries
surveyed. Examining the differences for each of the four questions constituting this subscale, we found a significant difference with respect to participating in research projects
or becoming a project manager, and the experience of sexual harassment and other unfair
treatment. In other words, compared with their counterparts in the other countries (2.97),
women scientists and engineers in Mongolia experienced less difficulty (average of 3.16)
in participating in research projects or becoming research managers (t=2.113, p≤.036).
This indicates that the difference for this question headed in a direction opposite to thoseof the remaining questions. On the other hand, the experience of sexual harassment orother disadvantage was reported as more prevalent among Mongolian women (2.61)
158

compared with their counterparts in the other countries (3.40) (t=-8.782, p≤.000). For theremaining two questions, Mongolian women reported slightly more experience of
discrimination; however, the difference was not statistically significant.
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Mongolia had an average score of 2.81,
significantly lower than the average score of 3.47 among the other countries (t=-10.678,
p≤.000). This suggests that women in Mongolia tend to be more conservative. By
individual questions, except for the one that women have an inherent ability to take careof babies, the remaining three questions produced significant differences. Mongolian
women tend to be more conservative with regard to the ideas that men are bread-winners
of a household that husbands should have more power than their wives to maintain order
within the family, and that men and women should have respectively suitable jobs since
men are rational and women emotional.
For career prospects, the respondents in Mongolia (3.99) reported themselves as
more optimistic than those in the other 11 countries (3.66) (t=5.307, p≤.000). In addition,
the women scientists and engineers in Mongolia expressed a significantly higher policy
demand, compared with the respondents in the other countries (t=3.075, p≤.002). Lastly,
the tendency to believe that full gender equality would be realized once women were
granted equal opportunity proved similar in Mongolia and other countries.
Figure 4-44 illustrates the overall difference in perception of gender barriers
between the respondents in Mongolia and those in the other countries.

<Figure 4-44. Gap between Mongolia & others on gender barriers>(Unit: Points)

159

<Table 4-48. Gap between Mongolia & others on gender barriers>(unit: points)

ExceptMongolia
Item
Mongoliat(n=161)(n=1,218)
1. Boys are encouraged more than girls to
1.93
2.53
-7.408go into the STEM field.
2. It is more difficult for a woman to get a
job in the STEM field than for a man
1.93
2.59
-7.959even with the same qualifications.
Perception of 3. Becoming a tenured professor, being
promoted or becoming a principal
2.16
2.55
-4.499discrimination
investigator is more difficult for female
scientists than for male scientists.
4. Women in STEM generally receive lesspay for equal work, compared with
2.81
2.94
-1.368their equally-qualified male colleagues.
Sub-scales
2.21
2.65
-6.832
5. I have experienced disadvantages inleading or participating in research
3.16
2.97
2.113
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds or scholarships 3.22
3.33
-1.298Experience of
because I am a woman.
discrimination 7. I have experienced sexual harassment
or unfair treatments sometime in my
2.61
3.40
-8.782career.
8. Balancing work and life (marriage and
2.54
2.61
-.780
family) has been a handicap for me.
Sub-scales
2.89
3.08
-3.236
9. Primary breadwinners (who take careof financial obligations) of households
2.78
3.65
-8.922should be men.
10. Women are born to have a way ofcaring children that men are not capable 3.22
3.35
-1.408of in the same way.
11. In order to maintain the order andGender role
peace of a family, the husband should
3.49
3.82
-3.400have greater power and authority thanstereotypes
the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each other
1.74
3.08
-16.151
by doing what is appropriate forthemselves.
Sub-scales
2.81
3.47
-10.678
13.
I
believethings
will
turn
out
fine
in
Career outlook
3.99
3.66
5.307
my future career.
14. It is crucial to have strong policy
Policy needs
support to solve gender inequality in
4.26
4.05
3.075
the STEM field.
15. I believe gender equality will be fully
Equality
achieved only if women are given equal 2.06
2.14
-1.140concept
opportunities as men.
* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

160

(p)
.000
.000
.000
.173
.000
.036
.195
.000
.436
.001
.000
.161
.001

.000
.000
.000
.002
.255

4.4.4.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Mongolia according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Figure 4-45 compares the perception of a discriminatory reality by
the respondents in Mongolia and by those from the other countries. The level ofperception of gender discrimination in society was second highest only to India (averagescore of 2.21 on the five-point scale).
<Figure 4-45. Average of Mongolia & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Table 4-49 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Mongolian respondents. By marital status,
married respondents reported stronger perception of a discriminatory reality than did theirsingle counterparts (F=3.253, p≤.041). Although no significant difference was found forthe number of children, occupation resulted in a significant difference: researchers (2.05)
and engineers (2.07) more strongly perceived a discriminatory reality than did students(2.73) and teachers/professors (2.35) (a lower score represents more discriminatory
reality) (F=3.881, p≤.010). Lastly, career interruption suggested a significant difference
as well. Specifically, the respondents experiencing at least three years of careerinterruption perceived a discriminatory reality most strongly (2.03), followed by thosewith a career interruption period of two to three years, those with one to two years, andthose experiencing no interruption (2.59). This suggests a consistent correlation between
longer interruption period and a stronger perception of a discriminatory reality (F=3.448,p≤.010).
161

<Table 4-49. Perception of discrimination of Mongolia: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation

Cases
161

Average
2.21

SD

F

p

43
45
52
21

2.31
2.37
2.00
2.15

0.83
0.73
0.67
0.67

2.554

.057

31
116
14

2.42
2.20
1.82

0.81
0.73
0.57

3.253

.041

30
33
61
37

2.38
2.27
2.17
2.07

0.85
0.75
0.68
0.74

1.112

.346

11
56
25

2.73
2.35
2.05

0.68
0.57
0.77

3.881

.010

69

2.07

0.82

29
4
13
40
74

2.59
2.44
2.40
2.16
2.03

0.74
1.16
0.77
0.64
0.72

3.448

.010

Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-50 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of theMongolian respondents. No significant correlation with the perception of discriminatory
reality was observed for variables such as age, number of children, occupation, and careerinterruption. Still, the average score was highest among those in their 20s (2.97), followedby those in their 30s and 40s (2.88 each), and those in their 50s (2.73), implying atendency that younger generations have less discriminatory experience. By occupation, a
discriminatory reality was reported at the lowest level among students (3.20) and highest162

among researchers (2.78); however, the difference was not significant.
<Table 4-50. Experience of discrimination of Mongolia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
161

Average
2.89

SD

F

p

43
45
52
21

2.97
2.88
2.88
2.73

0.81
0.68
0.57
0.66

.608

.611

31
116
14

2.83
2.92
2.68

0.72
0.66
0.73

.940

.393

30
33
61
37

2.90
2.79
2.96
2.83

0.61
0.82
0.64
0.68

.570

.635

11
56
25

3.20
2.87
2.78

0.60
0.74
0.72

1.023

.384

69

2.89

0.63

29
4
13
40
74

2.94
2.69
2.92
2.96
2.83

0.57
1.20
1.10
0.68
0.61

.374

.827

* Lower score means more discrimination experienced

For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-46 compares the discriminatory experienceamong the respondents in Mongolia and among respondents from the other countries. The
average score for this sub-scale was slightly higher than the median (average score of
2.89 on the five-point scale). Just as the awareness of discriminatory reality was second
highest among women in science and engineering in Mongolia, the actual experience of
discrimination in this country was also third highest after India and Vietnam.

163

<Figure 4-46. Average of Mongolia & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-47 compares attitudes toward genderroles among the respondents in Mongolia and among respondents from the other countries.
The average score for this sub-scale of gender role attitudes was 2.81 out of 5, below themedian level. This implies that Mongolian women have the second most conservative
attitude toward gender roles, after only women in Pakistan.
<Figure 4-47. Average of Mongolia & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

Table 4-51 provides the results of ANOVA of whether gender role ideology
varies depending on the personal variables of the Mongolian respondents. Whereas no
significant results were found for variables such as age, marital status, number of children,
occupation, and duration of career interruption, married respondents tend to be moreprogressive toward gender roles than the single respondents. By occupation,teachers/professors reported themselves to be more progressive than students.
164

<Table 4-51. Gender role stereotypes of Mongolia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
161

Average
2.81

SD

F

p

43
45
52
21

2.74
2.96
2.70
2.88

0.66
0.72
0.72
0.58

1.344

.262

31
116
14

2.69
2.85
2.70

0.70
0.67
0.86

.851

.429

30
33
61
37

2.70
3.03
2.82
2.68

0.77
0.51
0.72
0.70

1.862

.138

11
56
25

2.64
2.87
2.76

0.39
0.72
0.88

.391

.760

69

2.81

0.64

29
4
13
40
74

2.74
3.19
2.88
2.88
2.76

0.74
0.31
0.70
0.65
0.72

.610

.656

* Higher score means more progressive

Career prospects
Table 4-52 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Mongolian respondents. By age, younger
respondents tended to have more optimistic career prospects; however, the difference byage did reach a significant level. Although married respondents reported career prospects
more optimistic than those of the other group, with the single being more optimistic thanthe married, the difference by marital status was of no statistical significance. The numberof children did not result in a significant difference, either. Although students held themost optimistic and engineers the least optimistic attitudes toward career prospects, thedifference was not significant. In addition, the variable of career interruption did not
produce a significant difference.

165

<Table 4-52. Career outlook of Mongolia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
161

Average
3.99

SD

F

p

43
45
52
21

4.14
4.02
3.90
3.81

0.71
0.62
0.69
0.68

1.512

.214

31
116
14

4.16
3.97
3.79

0.64
0.70
0.58

1.705

.185

30
33
61
37

4.23
3.88
3.98
3.89

0.57
0.74
0.72
0.61

1.862

.138

11
56
25

4.36
3.96
4.04

0.50
0.66
0.73

1.382

.250

69

3.93

0.69

29
4
13
40
74

4.24
4.00
4.15
4.05
3.84

0.58
0.82
0.80
0.55
0.72

2.269

.064

* Higher score means a more positive outlook<Figure 4-48. Average of Mongolia & others on Career outlook>(unit: points)* Higher score means a more positive outlook166

As can be seen in Figure 4-48, the respondents in Mongolia demonstrated
relative optimism about their career prospects, with an average score of 3.99. This puts
the country in fourth place, following Bangladesh, Sri Lanka, and Pakistan.
Policy demand
Table 4-53 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Mongolian respondents. No personal variables
suggested a statistical relevance to policy demand. This result is partially because therespondents in Mongolia mostly reported strong policy demand. By occupation, policy
demand was strongest among researchers (4.48) and least strong among
teachers/professors (4.18).
<Table 4-53. Policy needs of Mongolia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
161

Average
4.26

SD

F

p

43
45
52
21

4.40
4.04
4.31
4.33

0.73
0.80
0.83
0.80

1.662

.178

31
116
14

4.23
4.24
4.50

0.80
0.81
0.65

.696

.500

30
33
61
37

4.23
4.27
4.28
4.24

0.82
0.76
0.80
0.83

.030

.993

11
56
25

4.36
4.18
4.48

0.50
0.74
0.87

.924

.430

69

4.23

0.84

29
4
13
40
74

4.21
3.75
4.38
4.53
4.15

0.77
0.96
0.77
0.68
0.84

2.040

.091

* Higher score means higher needs for policy support167

As can be seen in Figure 4-49, the respondents in Mongolia had a relatively highaverage of 4.26 in policy demand, ranking fourth after Vietnam, New Zealand, and India.
<Figure 4-49. Average of Mongolia & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Gender equality
As can be seen in Figure 4-50, the tendency of Mongolian women to believe thatfull gender equality would be realized once women were granted equal opportunity wasslightly stronger than the median level (average of 2.06; a lower score represents stronger
agreement). This ranks Mongolia in seventh place, following India, Bangladesh, New
Zealand, Pakistan, Nepal, and Vietnam.
<Figure 4-50. Average of Mongolia & others on Equality concept>(unit: points)

168

ANOVA analysis was conducted to identify whether personal variables resulted
in a different level of tendency among the respondents in Mongolia to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-54). The results showthat such belief was not correlated to personal variables. Still, the single respondents
tended to agree more with this statement, compared with the married and the other group.
By occupation, students agreed most with the idea, followed by researchers,
teachers/professors, and engineers; however, the difference was not sufficiently
significant. Career interruption did not produced a statistically significant result, either.
<Table 4-54. Equality concept of Mongolia : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
161

Average
2.06

SD

F

p

43
45
52
21

2.05
2.07
2.10
2.00

0.84
0.65
0.66
0.63

.101

.959

31
116
14

1.87
2.11
2.07

0.72
0.73
0.27

1.442

.239

30
33
61
37

1.83
2.18
2.15
2.00

0.70
0.68
0.73
0.67

1.794

.151

11
56
25

1.73
2.07
1.96

0.65
0.50
0.89

1.333

.266

69

2.14

0.77

29
4
13
40
74

1.90
2.75
1.85
2.15
2.08

0.67
0.50
0.69
0.58
0.77

1.857

.121

4.4.5 Vietnam
4.4.5.1 Respondent profile
In Vietnam, a total of 100 respondents participated in the survey (see Table 455). A large majority of them were in their 30s (71%) and 40s (23%), leaving those in
their 50s (5%) and 20s (1%) in extremely small numbers. By marital status, most169

respondents were married (87%), followed by the other group (12%), and only one
respondent was single. It is therefore of no significance to analyze the survey results by
the respondents’ marital status. Most of the Vietnamese respondents had two children(61%), followed by those with one child (35%) and with three or more children (3%). By
occupation, teachers/professors constituted the majority (72%), followed by researchers(17%) and engineers (11%). All of the respondents in Vietnam were in employment at
the time of the survey, and no students or healthcare/medical professionals were included
among the respondents. By length of career interruption, most respondents had at least
three years of interruption (79%), followed by those with two to three years (15%); theother respondents represented only a slight share. Compared with other countries, thosein Vietnam experienced relatively longer career interruption.
<Table 4-55. Profile of participants from Vietnam>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

1
71
23
5

1.0
71.0
23.0
5.0

1
87
12

1.0
87.0
12.0

1
35
61
3

1.0
35.0
61.0
3.0

72
17

72.0
17.0

11

11.0

1
2
3
15
79

1.0
2.0
3.0
15.0
79.0

4.4.5.2 Difference of gender barriers in Vietnam and other countries: Overview
The table below shows the results of a t-test comparing the gender barriers
perceived by women scientists and engineers in Vietnam with that perceived by their170

counterparts in the other 11 countries. To begin with, the sub-scale of the perception of
discriminatory reality against women had an average score of 3.19 in Vietnam, showing
a significant difference from the score of 2.55 among the other 11 countries (t=15.602,
p≤.000; a lower score is translated as stronger agreement with the perception of
discriminatory reality). In other words, compared with women in the other countries,
Vietnamese women tend to less strongly perceive discrimination against women in theirsociety. As a result of analyzing each of the four questions included in this sub-scale, asignificant difference was observed in three questions, except for the statement “Women
scientists have more difficulty than their male counterparts in becoming full-time
professors or managers.” With regard to the statement “Boys are more encouraged than
girls to choose the STEM fields,” the respondents in Vietnam demonstrated lessagreement, with an average of 3.30, compared with the average (2.40) of the othercountries (t=10.969, p≤.000). This may be because Vietnamese women are less aware of
discriminatory reality or because discrimination is actually less prevalent in Vietnam.
In addition, Vietnamese women agreed less strongly (2.63), compared with theircounterparts in the other countries (2.50), with the statement “Compared with men,
women with the same abilities face greater difficulty finding a job in the STEM fields”(t=-7.408, p≤.000.) This indicates that women in Vietnam tend to less strongly perceivea discriminatory reality. Lastly, regarding the statement “Women receive less wages forthe same work than men,” women in Vietnam significantly agreed less strongly (4.32)
compared with the respondents in the other countries (2.82). This implies that the
respondents in Vietnam strongly denied the presumption that such discrimination existed
in their society (t=23.364, p≤.000).
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Vietnam with that experienced by respondents in theother countries, the average score in Vietnam was 2.44, significantly higher than the
average of 3.10 in the other countries (t=-14.695, p≤.000). Since lower scores refer togreater discriminatory experience, the result suggests that the respondents in Vietnam had
more discriminatory experience than their counterparts in the other 11 countries surveyed.
Examining the differences for each of the four questions constituting this sub-scale, we
found a significantly higher score in the discriminatory experience of Vietnamese womenin all questions than was the case for the respondents in the other countries. First,
Vietnamese women (2.65) reported more difficulty in participating in research projects
or becoming research managers, compared with the respondents in the other countries(3.02) (t=-3.551, p≤.001). They (2.42) also experienced more disadvantage in winningresearch grants or scholarships than their counterparts in the other countries (3.39) (t=11.849, p≤.000).
Likewise, a significant result was observed for sexual harassment and other171disadvantages. The women scientists and engineers in Vietnam (3.61) had moreexperience of sexual harassment and other disadvantages than those in the other countries(3.28) (t=4.343, p≤.000). Lastly, the Vietnamese respondents (1.10) also reported moretendency of experiencing work-life balance as a handicap, compared with women in theother countries (2.72) (t=-34.449, p≤.000). This result seems relevant to theabovementioned fact that 79% of the Vietnamese respondents had career interruption forthree years or longer, which is notably long compared with other countries.
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Vietnam had an average score of 3.07,
significantly lower than the average score of 3.42 among the other countries (t=-8.141,p≤.000). This implies that women in Vietnam tend to be more conservative about genderroles. All four individual questions for this sub-scale resulted in significant differences.
First, the participants in Vietnam proved to be more conservative regarding the ideas that
men are bread-winners of a household that husbands should have more power than theirwives to maintain order within the family, and that men and women should haverespectively suitable jobs since men are rational and women emotional. On the other hand,with respect to the idea that women have an inherent ability to take care of babies,
Vietnamese women (3.70) reported a more progressive tendency than did the respondents
in the other countries (3.31) (t=5,522, p≤.000).
<Figure 4-51. Gap between Vietnam & others on gender barriers>(Unit: Points)

172

<Table 4-56. Gap between Vietnam & others on gender barriers>(unit: points)

Item

ExceptVietnam Vietnam(n=100) (n=1,279)t(p)

1. Boys are encouraged more than girls to go
into the STEM field.
2. It is more difficult for a woman to get a
job in the STEM field than for a man evenwith the same qualifications.
Perception of 3. Becoming a tenured professor, being
promoted or becoming a principal
discrimination
investigator is more difficult for female
scientists than for male scientists.
4. Women in STEM generally receive lesspay for equal work, compared with theirequally-qualified male colleagues.
Sub-scales
5. I have experienced disadvantages inleading or participating in research
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds or scholarships
Experience of
because I am a woman.
discrimination 7. I have experienced sexual harassment or
unfair treatments sometime in my career.

3.30

2.40

10.989

.000

2.63

2.50

1.978

.049

2.50

2.50

-.046

.963

4.32

2.82

23.364

.000

3.19

2.55

15.602

.000

2.65

3.02

-3.551

.001

2.42

3.39

-11.849 .000

3.61

3.28

4.343

8. Balancing work and life (marriage andfamily) has been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care offinancial obligations) of households
should be men.
10. Women are born to have a way of caring
children that men are not capable of in thesame way.
Gender role 11. In order to maintain the order and peaceof a family, the husband should havestereotypes
greater power and authority than the wife.
12. In a relative sense, men are rational
while women are emotional and thus, theyought to complement each other by doing
what is appropriate for themselves.
Sub-scales
13. I believe things will turn out fine in my
Career outlook
future career.
14. It is crucial to have strong policy support
Policy needs
to solve gender inequality in the STEM
field.
15.
I believe gender equality will be fully
Equality
achieved only if women are given equal
concept
opportunities as men.

1.10

2.72

-34.449 .000

2.44

3.10

-14.695 .000

3.42

3.56

-2.007

.046

3.70

3.31

5.522

.000

2.72

3.86

-11.613 .000

2.44

2.96

-7.897

.000

3.07

3.42

-8.141

.000

3.37

3.72

-4.871

.000

4.77

4.02

14.483

.000

1.85

2.15

-5.671.000* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

173

.000

For career prospects, the average score obtained by women in Vietnam (3.37)
was above the median level, but lower than the average in the other countries (3.72)(t=4.871, p≤.000). As discussed earlier, whereas Vietnamese women less strongly
perceived a discriminatory reality relatively, they reported more personal experience of
discrimination. This suggests that the discriminatory experience affected the careerprospects of Vietnamese women. As a result of analyzing the difference of policy demand,
the respondents in Vietnam (4.77) expressed stronger policy demand than did theircounterparts in the other surveyed countries (4.02) (t=14.483, p≤.000). Lastly,
Vietnamese women (1.85) also more strongly agreed with the idea that equal opportunity
was a sufficient factor of gender equality, compared with the respondents in the othercountries (2.15) (t=-5.671, p≤.000).
Figure 4-51 illustrates the overall difference in perception of gender barriers
between the respondents in Vietnam and those in the other countries.
4.4.5.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Vietnam according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality.
<Figure 4-52. Average of Vietnam & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Figure 4-52 compares the perception of a discriminatory reality by the
respondents in Vietnam and by those from the other countries. The level of perception ofgender discrimination in society had a score of 3.19, lower than the median level andhigher only than Sri Lanka and Malaysia.
174

<Table 4-57. Perception of discrimination of Vietnam: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30～39
40～49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
100

Average
3.19

SD

1
71
23
5

3.00
3.21
3.15
3.00

0.34
0.15
0.00

1
87
12

3.00
3.19
3.21

0.32
0.10

1
35
61
3

3.00
3.09
3.25
3.17

0.36
0.26
0.14

72
17

3.19
3.15

0.32
0.27

11

3.25

0.19

1
2
3
15
79

3.00
2.00
3.25
2.97
3.26

0.00
0.43
0.16
0.23

F

p

1.069

.366

.218

.805

2.425

.070

.382

.683

18.892.000* Lower score means higher perception of discrimination

Table 4-57 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Vietnamese respondents. No significant
difference was found for different age groups. By marital status, no statistical significancewas observed, although married respondents more strongly perceived a discriminatory
reality than did the single participants. According to the number of children, therespondents with more children tended to perceive a discriminatory reality less strongly;
however, the difference was not significant. Although occupation did not result in asignificant difference, the duration of career interruption produced a statisticallysignificant difference. The awareness of a discriminatory reality was highest among thosewith less than one year of career interruption (2.00), followed by those with one to two
years, those with two to three years, and those without experience of career interruption(3.00) (F=18.892, p≤.010).

175

Discriminatory experience
Table 4-58 provides the results of ANOVA of whether discriminatory experiencevaries depending on the personal variables of the Vietnamese respondents. By age, nosignificant difference, statistical or not, was found, except for the difference between
those in their 20s and the other age groups. By marital status, the single respondents (2.75)
reported less discriminatory experience than the married (2.48) or the other group (2.13)(F=5.679, p≤.005). The number of children and occupation did reach a significant
difference. However, women with at least one child reported more discriminatory
experience than did those without children. Lastly, career interruption produced asignificant difference: discriminatory experience was reported most among thoseexperiencing at least three years of interruption (2.35), and least among thoseexperiencing one to two years of interruption (F=13.619, p≤.000).
<Table 4-58. Experience of discrimination of Vietnam : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
100

Average
2.44

1
69
23
5

2.75
2.44
2.41
2.55

0.43
0.19
0.11

1
85
12

2.75
2.48
2.13

0.35
0.38

1
33
61
3

2.75
2.43
2.45
2.33

0.53
0.25
0.63

70
17

2.46
2.43

0.38
0.33

11

2.34

0.39

1

2.75

3
15
79

3.33
2.70
2.35

* Lower score means more discrimination experienced

176

SD

1.01
0.19
0.30

F

p

.408

.747

5.679

.005

.317

.813

.502

.607

13.619.000

For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-53 compares discriminatory experienceamong the respondents in Vietnam and among respondents from the other countries. The
average score (2.44) of the Vietnamese respondents was below the median level,
representing higher discriminatory experience than the overall average. Whereas the
respondents in Vietnam reported the third lowest perception of discriminatory reality, theactual experience of discrimination was second highest after India. This suggests that
Vietnam has a gap between the perception of a discriminatory reality and experience of
discrimination.
<Figure 4-53. Average of Vietnam & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-54 compares attitudes toward genderroles among the respondents in Vietnam and among respondents from the other countries.
The average score for gender role ideology was 3.01 out of 5, reaching the median level.
Relatively speaking, Vietnamese women’s attitude toward gender roles was the third mostconservative after the respondents in Pakistan and Mongolia.
Table 4-59 provides the results of ANOVA of whether gender role ideology
varies depending on the personal variables of the Vietnamese respondents. Except forcareer interruption, variables such as age, marital status, number of children, andoccupation did not produce a significant difference. Certainly, the average scores by age
suggest that those in their 20s had the most progressive attitude toward gender roles. By
marital status, the single respondents tended to be more progressive than the married andthe other group. In terms of the duration of career interruption, those who experienced atleast three years of interruption were more conservative than the other respondents(F=10.375, p≤.000).
177

<Figure 4-54. Average of Vietnam & others on Gender role stereotypes>(unit: points)* Higher score means more progressive<Table 4-59. Gender role stereotypes of Vietnam : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
* Higher score means more progressive

178

Cases
100

Average
3.07

SD

1
71
23
5

3.50
3.03
3.12
3.30

0.32
0.29
0.11

1
87
12

3.50
3.08
2.98

0.32
0.27

1
35
61
3

3.50
3.05
3.08
2.92

0.31
0.32
0.14

72
17

3.08
3.04

0.31
0.32

11

3.02

0.33

1
2
3
15
79

3.50
3.50
3.17
3.42
2.98

0.00
0.58
0.22
0.26

F

p

2.134

.101

1.479

.233

.939

.425

.244

.784

10.375.000

Career prospects
Table 4-60 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Vietnamese respondents. The difference by
age was not significant. By marital status, the single respondents had more optimistic
career prospects than the married and the other group, but this difference was notstatistically significant. Likewise, no significant relevance was found for the number ofchildren, although the respondents with more children tended to be more conservative.
Occupation was not a statistically significant variable, either. Lastly, the length of careerinterruption resulted in a significant difference. As discussed earlier, because most
respondents disproportionately experienced at least two years of career interruption, asignificant difference was observed between those experiencing two to three years ofinterruption (3.93) and those experiencing at least three years of interruption (3.25). Thisimplies that the respondents with at least three years of interruption were mostconservative (F=9.934, p≤.000).
As can be seen in Figure 4-55, the respondents in Vietnam demonstrated relative
optimism about their career prospects, with an average score of 3.37. However, thisindicates that the country had the second lowest average, following Japan. This result
seems related to Vietnamese women’s strong experience of discrimination andconservative attitude toward gender roles.
<Figure 4-55. Average of Vietnam & others on Career outlook>(unit: points)

179

<Table 4-60. Career outlook of Vietnam : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/profe
ssor
Researcher
Medicalpersonnel
Engineer
Other
Duration ofcareer breakNoneLess than 1year
1~2 years
2~3 years
3 years or
more

Cases
100

Average
3.37

SD

1
71
23
5

4.00
3.32
3.35
4.00

0.71
0.49
0.00

1
87
12

4.00
3.39
3.17

0.69
0.39

1
35
61
3

4.00
3.46
3.33
3.00

0.85
0.54
0.00

72

3.40

0.69

17

3.35

0.70

11

3.18

0.40

1
2

4.00
2.00

0.00

3
15

4.33
3.93

0.58
0.46

79

3.25

0.59

F

p

1.996

.120

1.065

.349

.898

.445

.534

.588

9.934

.000

* Higher score means a more positive outlook

Policy demand<Figure 4-56. Average of Vietnam & others on Policy needs>(unit: points)* Higher score means higher needs for policy support180

As can be seen in Figure 4-56, the Vietnamese respondents had an average scoreof 4.77 out of 5 for policy demand, the highest score among all 12 countries surveyed.
This reflects the increasing interest in policy of women in Vietnamese society amidst thevigorous economic development.
The table below provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Vietnamese respondents. The only personalvariable statistically relevant to policy demand was the duration of career interruption.
According to the number of children, the respondents with three or more children had ahigher average than those without children or those with one or two children; however,the difference was not significant. Career interruption produced a significant difference.
It is necessary to analyze this result with a focus on those with two to three years ofinterruption and those experiencing at least three years of interruption, the two groups
taking up the most share of the respondents. As a result, those with at least three years ofinterruption had an average score of 4.91 for policy demand, higher than those with twoto three years of interruption (4.20) (F=24.157, p≤.000).
<Table 4-61. Policy needs of Vietnam : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
100

Average
4.77

1
71
23
5

4.00
4.76
4.83
4.80

0.43
0.39
0.45

1
87
12

4.00
4.77
4.83

0.42
0.39

1
35
61
3

4.00
4.77
4.77
5.00

0.43
0.42
0.00

72
17

4.76
4.82

0.43
0.39

11

4.73

0.47

1
2
3
15
79

4.00
5.00
4.00
4.20
4.91

0.00
0.00
0.41
0.29

* Higher score means higher needs for policy support

181

SD

F

p

1.270

.289

1.821

.167

1.418

.242

.197

.822

24.157.000

Gender equality
ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Vietnam to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-62).
<Table 4-62. Equality concept of Vietnam : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
100

Average
1.85

SD

1
71
23
5

2.00
1.87
1.91
1.20

0.41
0.29
0.45

1
87
12

2.00
1.83
2.00

0.44
0.00

1
35
61
3

2.00
1.71
1.92
2.00

0.52
0.33
0.00

72
17

1.82
1.88

0.42
0.49

11

2.00

0.00

1
2
3
15
79

2.00
1.00
1.67
2.00
1.85

0.00
0.58
0.38
0.40

F

p

5.003

.003

.993

.374

2.068

.109

.982

.378

3.050

.021

The results suggest that such a belief is related to the respondents’ age. The
tendency to agree with the belief that equal opportunity was a sufficient factor of genderequality was lowest among those in their 20s (2.00; but not significant because therespondent was only one), followed by those in their 40s (1.91) and 30s (1.87) with thesimilar scores, and highest among those in their 50s (1.20). The difference arising fromthe number of children and occupation was not significant. However, the length of careerinterruption produced a significant difference. Those with less than one year ofinterruption (1.00) agreed most with the statement that equal opportunity was a sufficient
factor of gender equality, followed by those with one to two years of interruption (1.67)
182

and with at least three years (1.85). The scores reported by those with at least three years
of interruption and by those without any interruption (take into account that this
respondent was only one) were the lowest (2.00) (F=3.050, p≤.021).
<Figure 4-57. Average of Vietnam & others on Equality concept>(unit: points)

As can be seen in Figure 4-57, the Vietnamese respondents showed a strong
tendency to believe that full gender equality would be realized once women were granted
equal opportunity (average of 1.81; a lower score represents stronger agreement). This
places Vietnam in the sixth rank, following India, Bangladesh, New Zealand, Pakistan,and Nepal.
4.4.6 Sri Lanka
4.4.6.1 Respondent profile
A total of 101 respondents in Sri Lanka participated in this survey (see Table 463). Most of them were in their 30s (37.6%), followed by those in their 20s (26.7%), andthose in their 40s and 50s (17.8% each). The largest group by marital status was married
respondents (45.5%), followed by the single participants (42.5%) and the other group(11.9%). According to the number of children, those without any child accounted for
59.4%; those with one child for 17.8%; those with two children for 15.8%; and those withat least three children for 6.9%.
By occupation, teachers/professors accounted for 19.8%; researchers for 18.8%;
healthcare/medical professionals and engineers for 14.9% each; and students for 8.9%.
The other group accounted for 22.8%, higher than that of any other country. The majorityof the respondents had no career interruption (47.5%), followed by those with one to two
years of interruption (20.8%), those with at least three years of interruption (15.8%), andthose experiencing interruption of less than one year (4%).

183

<Table 4-63. Profile of participants from Sri Lanka>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

27
38
18
18

26.7
37.6
17.8
17.8

43
46
12

42.6
45.5
11.9

60
18
16
7

59.4
17.8
15.8
6.9

9
20
19
15
15
23

8.9
19.8
18.8
14.9
14.9
22.8

48
4
21
12
16

47.5
4.0
20.8
11.9
15.8

4.4.6.2 Difference of gender barriers in Sri Lanka and other countries: Overview
occupation
Table 4-64 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Sri Lanka with that perceived by their counterpartsin the other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 3.37 in Sri Lanka, showing a significant
difference from the score of 2.54 among the other 11 countries (t=8.694, p≤.000; a lower
score is translated as stronger agreement with the perception of discriminatory reality). In
other words, compared with women in the other countries, Sri Lankan women tend to lessstrongly perceive discrimination against women in their society. As a result of analyzingeach of the four questions included in this sub-scale, the awareness of discrimination
among Sri Lankan women was consistently low in all questions. With regard to thestatement “Boys are more encouraged than girls to choose the STEM fields,” therespondents in Sri Lanka demonstrated less agreement, with an average of 3.39, comparedwith the average (2.39) of the other countries (t=7.202, p≤.000). The reason is either that184

Sri Lankan women are relatively less aware of this discriminatory reality, or that actual
discrimination is not prevalent in Sri Lanka.
In addition, Sri Lankan women agreed less strongly (3.20), compared with theircounterparts in the other countries (2.45), with the statement “Compared with men,
women with the same abilities face greater difficulty finding a job in the STEM fields”(t=6.172, p≤.000) This implies that women in Sri Lanka tend to less strongly perceive a
discriminatory reality. Furthermore, for the statement “Women scientists have moredifficulty than their male counterparts in becoming full-time professors or managers,” theSri Lankan respondents (3.21) revealed a weaker perception than in other countries (2.45)(t=6.027, p≤.000). Lastly, regarding the statement “Women receive less wages for thesame work than men,” women in Sri Lanka agreed less strongly (3.70) compared with the
respondents in the other countries (2.87), indicating that they relatively strongly denied
the existence of such discrimination (t=23.364, p≤.000).
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Sri Lanka with that experienced by respondents in theother countries, The average score in Sri Lanka was 3.61, significantly higher than the
average of 3.10 in the other countries (t=9.034, p≤.000). Since lower scores refer togreater discriminatory experience, the result suggests that the respondents in Sri Lanka
had less discriminatory experience than their counterparts in the other 11 countries
surveyed. Examining the differences for each of the four questions constituting this subscale, we found a significantly lower score in the discriminatory experience of Sri Lankan
women in all questions than was the case for the respondents in the other countries. First,
the respondents in Sri Lanka (3.50) experienced less difficulty in participating in research
projects or becoming research managers than their counterparts in the other countries(2.96) (t=4.124, p≤.001). They (3.97) also reported less experience of disadvantage inwinning research grants or scholarships than the respondents in the other countries (3.27)(t=6.449, p≤.000).
Likewise, a significant result was observed for sexual harassment and otherdisadvantages: the respondents in Sri Lanka (3.74) experienced less sexual harassment orother disadvantage than their counterparts in the other countries (3.27) (t=3.383, p≤.001).
Lastly, the experience of having work-life balance as a handicap was significantly lessprevalent among the respondents in Sri Lanka (3.23), compared with their counterpartsin the other countries (2.55) (t=5.435, p≤.000).

185

<Table 4-64. Gap between Sri Lanka & others on gender barriers>(unit: points)
Sri
Item
Lanka
(n=101)
1. Boys are encouraged more than girls
3.39
to go into the STEM field.
2. It is more difficult for a woman toget a job in the STEM field than for a 3.20
man even with the same
qualifications.
3. Becoming a tenured professor, being
Perception ofpromoted or becoming a principal
3.21
investigator is more difficult fordiscrimination
female scientists than for malescientists.
4. Women in STEM generally receive
less pay for equal work, compared
3.70
with their equally-qualified malecolleagues.
Sub-scales
3.37
5. I have experienced disadvantages in
3.50
leading or participating in research
projects because I am a woman.
6. I have experienced disadvantages in
3.97
receiving research funds or
scholarships
becauseI
amawoman.
Experience of
7. I have experienced sexual
discrimination
3.74
harassment or unfair treatments
sometime in my career.
8. Balancing work and life (marriage
3.23
and family) has been a handicap forme.
Sub-scales
3.61
9. Primary breadwinners (who take care
3.92
of financial obligations) of
households should be men.
10. Women are born to have a way of
3.54
caring children that men are notcapable of in the same way.
11. In order to maintain the order andGender role
peace of a family, the husband
3.81
should have greater power andstereotypes
authority than the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each other 2.59
by doing what is appropriate forthemselves.
Sub-scales
3.47
13. I believe things will turn out fine in
4.11
Career outlook
my future career.
14. It is crucial to have strong policy
4.09
Policy needs
support to solve gender inequality in
the STEM field.
15. I believe gender equality will be
Equality
2.37
fully achieved only if women areconcept
given equal opportunities as men.
* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

186

Except
Sri Lanka(n=1,278)
2.39

t

(p)

7.202

.000

2.45

6.172

.000

2.45

6.027

.000

2.87

7.187

.000

2.54

8.694

.000

2.96

4.124

.000

3.27

6.449

.000

3.27

3.383

.001

2.55

5.435

.000

3.01

9.034

.000

3.52

3.232

.002

3.32

1.614

.107

3.78

.263

.793

2.95

-2.253

.026

3.39
3.67

.723
5.164

.470
.000

4.07

.182

.856

2.11

2.171

.030

With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Sri Lanka had an average score of 3.47,
representing a relatively more progressive attitude. This is not significantly different fromthe average of 3.39 in the other countries. Among the questions included in this sub-scale,the questions that produced a significant difference between the respondents in Sri Lanka
and those in other countries are: that men are bread-winners of a household and that men
and women should have respectively suitable jobs since men are rational and women
emotional.
With respect to the former question, the average (3.92) in Sri Lanka was higher
than that (3.52) in the other countries (t=3.232, p≤.002). On the other hand, the Sri Lankan
average (2.59) for the latter question was lower than that (2.95) in the other countries (t=2.253, p≤.026). In other words, whereas the women scientists and engineers in Sri Lanka
were relatively progressive about the idea of men being bread-winners to support thefamily, they were relatively conservative to the idea of regarding women and men as
emotional and rational, respectively, as the basis for different job selection.
With respect to career prospects, the respondents in Sri Lanka reported
themselves as more optimistic (4.11), higher than the average obtained by the others (3.67)(t=5.164, p≤.000). The analysis of any difference between Sri Lanka and the othercountries for policy demand did not find any significant difference. Lastly, therespondents in Sri Lanka (2.37) agreed more to the statement that equal opportunity wasa sufficient factor of gender equality than the respondents in the other countries (2.11)(t=2.171, p≤.000).
Figure 4-58 illustrates the overall difference in perception of gender barriers
between the respondents in Sri Lanka and those in the other countries.
<Figure 4-58. Gap between Sri Lanka & others on gender barriers>(Unit: Points)

187

4.4.6.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Sri Lanka according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of discriminatory reality
For this scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-65 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the Sri Lankan respondents. Age
did not produce statistical significance, although younger generations tended to morestrongly perceive a discriminatory reality. In addition, differences based on marital status
also did not suggest statistical significance, although the married respondents morestrongly perceived a discriminatory reality than did the single participants in the survey.
The respondents with fewer children tended to more strongly perceive a discriminatory
reality; however, the difference arising from the number of children was not significant.
The other variables such as occupation and duration of career interruption did not provesignificant, either.
<Figure 4-59. Average of Sri Lanka & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

188

<Table 4-65. Perception of discrimination of Sri Lanka: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
3.37

SD

F

p

27
38
18
18

3.18
3.41
3.47
3.49

0.74
0.85
0.85
0.77

.776

.510

43
46
12

3.25
3.48
3.40

0.75
0.85
0.84

.938

.395

60
18
16
7

3.26
3.43
3.52
3.86

0.78
0.96
0.67
0.83

1.434

.238

9
20
19
15
15
23

3.47
3.55
3.42
3.63
3.15
3.12

0.69
1.08
0.83
0.73
0.70
0.60

1.246

.294

48
4
21
12
16

3.22
3.25
3.44
3.71
3.52

0.73
0.74
0.82
0.95
0.89

1.120

.351

* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-60 compares the discriminatory experienceamong the respondents in Sri Lanka and among participants from the other countries. The
average of Sri Lanka for this sub-scale (3.61) was above the median level, suggesting thatthe country reported less discriminatory experience than average. As is the case withperception of a discriminatory reality, discriminatory experience by the respondents in
Sri Lanka was lower than that in any other country. This is probably because
discrimination does not exist in the country, or because the respondents do not sensitively
perceive discrimination.

189

Table 4-66 provides the results of ANOVA of whether discriminatory experiencevaries depending on the personal variables of the Sri Lankan respondents. Different ages
did not result in a notable difference; this was the case with differences based on marital
status and the number of children. By occupation, engineers reported more discriminatory
experience than teachers/professors; however, the difference was not significant. Lastly,
although the difference resulting from the duration of career interruption suggests thatthose who experienced interruption for less than one year or did not experience any
interruption tended to experience discrimination relatively more than the other groups,
this result also did reach statistical relevance.
<Table 4-66. Experience of discrimination of Sri Lanka : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
3.61

SD

F

p

27
38
18
18

3.59
3.74
3.53
3.44

0.61
0.59
0.73
0.57

1.077

.363

43
46
12

3.62
3.59
3.63

0.57
0.68
0.56

.030

.971

60
18
16
7

3.63
3.56
3.59
3.64

0.60
0.62
0.70
0.69

.066

.978

9
20
19
15
15
23

3.75
3.78
3.74
3.62
3.55
3.34

0.78
0.62
0.65
0.72
0.54
0.46

1.496

.198

48
4
21
12
16

3.48
3.25
3.73
4.00
3.63

0.61
0.46
0.62
0.44
0.68

2.329

.062

* Lower score means more discrimination experienced

190

<Figure 4-60. Average of Sri Lanka & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
In the sub-scale of gender role attitudes, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-61 compares attitudes toward genderroles among the respondents in Sri Lanka and among respondents from the other countries.
The average for gender role ideology sub-scale in Sri Lanka was 3.47 out of 5, above themedian level. In relative terms, Sri Lankan women were the sixth most progressive toward
gender roles, following India, Nepal, New Zealand, Taiwan, and Korea.
<Figure 4-61. Average of Sri Lanka & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

191

<Table 4-67. Gender role stereotypes of Sri Lanka : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
3.47

SD

F

p

27
38
18
18

3.41
3.77
3.07
3.32

1.15
0.88
0.83
0.91

2.472

.066

43
46
12

3.65
3.47
2.81

1.08
0.87
0.75

3.618

.030

60
18
16
7

3.53
3.61
3.20
3.14

1.05
0.90
0.80
0.94

.860

.464

9
20
19
15
15
23

3.44
3.13
3.93
3.70
3.43
3.26

1.04
0.65
0.94
1.06
0.85
1.15

1.799

.120

48
4
21
12
16

3.44
4.00
3.63
3.65
3.06

1.06
0.79
1.02
0.84
0.71

1.245

.297

* Higher score means more progressive

Table 4-67 provides the results of ANOVA whether gender role ideology varies
depending on the personal variables of the Sri Lankan respondents. Except for marital
status, the variables such as age, number of children, occupation, and career interruption
did not produce a significant difference. By marital status, the single respondents (3.65)
reported more progressive attitude toward gender roles than the married (3.47) and theother group (2.81) ((F=3.618, p≤.030). By occupation, teachers/professors tended to be
most conservative and researchers most progressive; however, the difference was notstatistically relevant.

192

Career prospects
As can be seen in Figure 4-62, the respondents in Sri Lanka demonstrated relative
optimism about their career prospects, with an average score of 4.11. This puts the country
in second place, following Bangladesh. This result seems related to Sri Lankan women’s
weaker perception of a discriminatory reality and discriminatory experience.
<Table 4-68. Career outlook of Sri Lanka : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
4.11

SD

F

p

27
38
18
18

4.15
4.24
4.11
3.78

1.06
0.71
0.58
0.73

1.350

.263

43
46
12

4.23
4.13
3.58

0.78
0.69
1.16

3.166

.047

60
18
16
7

4.13
4.17
4.19
3.57

0.85
0.71
0.66
0.98

1.127

.342

9
20
19
15
15
23

3.78
3.90
4.32
4.13
4.40
4.04

1.72
0.72
0.67
0.74
0.51
0.64

1.247

.294

48
4
21
12
16

4.08
4.50
4.24
4.00
4.00

0.77
0.58
1.00
0.74
0.82

.493

.741

* Higher score means a more positive outlook

193

<Figure 4-62. Average of Sri Lanka & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Table 4-68 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Sri Lankan respondents. The difference
resulting from age did not prove significant, although those in their 50s reported a
relatively negative career prospects than the respondents in the other age groups. By
marital status, the single respondents (4.23) had more optimistic view with respect tocareer prospects than the married (4.13) and the other group (3.58) (F=3.166, p≤.047).
The respondents with three or more children tended to have less optimistic careerprospects; however, the difference was not of statistical significance. Occupation was nota statistically relevant variable, but the average score was highest among engineers andlowest among students. Lastly, no significant difference was observed for the duration ofcareer interruption.
Policy demand
Table 4-69 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Sri Lankan respondents. Career interruption
was the only personal variable that showed statistically significant relevance to policy
demand. By marital status, the single respondents had a higher average for policy demand,followed by the married and the other group; however, the difference was not significant.
By occupation, teachers/professors had the highest average, and students the lowest;
however, the difference was not significant. Conversely, the difference from careerinterruption was statistically significant. The respondents with one year of interruption
had the highest average (5.00), followed by those with at least three years of interruption(4.63). The group with least policy demand was the respondents with one to two years ofinterruption (3.67) (F=3.139, p≤.018).

194

As can be seen in Figure 4-63, the Sri Lankan respondents had an average scoreof 4.09 for policy demand, which is relatively high. However, when compared with theother countries, this result places Sri Lanka in the fifth lowest rank, following Japan,
Malaysia, Taiwan, and Pakistan. This appears to be related to the relatively low
perception of a discriminatory reality and experience of discrimination against women in
Sri Lanka.
<Table 4-69. Policy needs of Sri Lanka : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
4.09

SD

F

p

27
38
18
18

3.89
4.39
3.72
4.11

1.19
0.86
1.02
0.96

2.351

.077

43
46
12

4.23
4.02
3.83

0.95
1.04
1.19

.900

.410

60
18
16
7

4.13
4.11
3.88
4.14

1.03
1.08
1.02
0.90

.275

.843

9
20
19
15
15
23

3.67
4.45
4.32
3.73
4.27
3.87

1.80
0.76
0.82
0.96
1.16
0.81

1.724

.137

48
4
21
12
16

4.06
5.00
3.67
3.92
4.63

1.04
0.00
1.11
0.90
0.72

3.139

.018

* Higher score means higher needs for policy support

195

<Figure 4-63. Average of Sri Lanka & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Gender equality
ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Sri Lanka to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-70). First of all, thisbelief proved to be related to the respondents’ age. With respect to the statement that
equal opportunity alone was sufficient for achieving gender equality, the respondents intheir 30s (1.96) agreed least; those in their 20s (2.44) and in 40s (2.56) followed; andthose in their 50s (2.94) agreed most (F=3.210, p≤.026). By marital status, the averagescore (2.26) of the single and married respondents showed no difference, and the othergroup had a higher average (3.17). However, the difference was not significant.
The differences according to the number of children and duration of careerinterruption were not significant. On the other hand, the difference by occupation proved
significant. Except for the other occupational groups, agreement with the statement that
equal opportunity alone was sufficient was the strongest among teachers/professors (2.85),
followed by students (2.33) and healthcare/medical professionals (2.27). The next lowest
score was reported by engineers (1.87), and researchers (1.68) reported the lowest score(F=3.689, p≤.004).
As can be seen in Figure 4-64, the respondents in Sri Lanka demonstrated a
relatively strong tendency to believe that full gender equality would be realized once
women were granted equal opportunity (average of 2.37; a lower score represents stronger
agreement). This ranks the country in third place after Japan and Korea.

196

<Table 4-70. Equality concept of Sri Lanka : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
2.37

SD

F

p

27
38
18
18

2.44
1.95
2.56
2.94

1.22
1.06
1.50
1.00

3.210

.026

43
46
12

2.26
2.26
3.17

1.22
1.14
1.34

3.037

.052

60
18
16
7

2.38
2.17
2.44
2.57

1.26
1.38
1.03
0.98

.242

.867

9
20
19
15
15
23

2.33
2.85
1.68
2.27
1.87
2.91

1.80
1.18
0.67
1.03
1.06
1.24

3.689

.004

48
4
21
12
16

2.31
1.25
2.43
2.67
2.50

1.17
0.50
1.12
1.50
1.37

1.104

.359

<Figure 4-64. Average of Sri Lanka & others on Equality concept>(unit: points)

197

4.4.7 India
4.4.7.1 Respondent profile
A total of 93 respondents participated in the survey in India (see Table 4-71). By
age, those in their 20s accounted for 75.3% and those in 30s for 24.7%; no respondents
were over the age of 40. The average age of the participants stood at 26.82, third youngest
among the 12 countries after Malaysia and Bangladesh. By marital status, 52.7% of the
respondents were single, and 47.3% were married. A majority of the respondents (64.5%)
had no child; 22.6% had one child; 12.9% had two children; and no respondents had threeor more children.
Except for the occupations classified as others, most respondents were engineers(32.3%), followed by teachers/professors (11.8%), healthcare/medical professionals(9.7%), students (6.5%), and researchers (1.1%). With respect to career interruption, most
respondents reported no experience of interruption (64.5%); 16.1% had at least three
years of interruption, followed by one to two years (9.7%), less than one year (6.5%), andtwo to three years (3.2%).
<Table 4-71. Profile of participants from India>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
198

N

%

70
23
-

75.3
24.7
-

49
44
-

52.7
47.3
-

60
21
12
-

64.5
22.6
12.9
-

6
11
1
9
30
36

6.5
11.8
1.1
9.7
32.3
38.7

60
6
9
3
15

64.5
6.5
9.7
3.2
16.1

4.4.7.2 Difference of gender barriers in India and other countries: Overview
Table 4-72 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in India with that perceived by their counterparts inthe other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 1.13 in India, showing a significant
difference from the score of 2.70 among the other 11 countries (t=-38.383, p≤.000; alower score is translated as stronger agreement with the perception of discriminatory
reality). This result implies that Indian women quite more strongly perceive gender
discrimination in their society, compared with women in the other countries, which ispresumably related to the fact that the average age of the Indian respondents was only
26.82.
As a result of analyzing each of the four questions included in this sub-scale, we
observed a consistently high awareness of discrimination among Indian women in allquestions. With regard to the statement “Boys are more encouraged than girls to choose
the STEM fields,” the respondents in India demonstrated more agreement, with anaverage of 1.08, compared with the average (2.56) of the other countries (t=-32.411,
p≤.000). In addition, Indian women significantly more strongly agreed (1.16), comparedwith their counterparts in the other countries (2.61), with the statement “Compared withmen, women with the same abilities face greater difficulty finding a job in the STEM
fields” (t=-28.818, p≤.000.) This implies that Indian women tend to perceive a
discriminatory reality more strongly. For the statement “Women scientists have moredifficulty than their male counterparts in becoming full-time professors or managers,” theIndian respondents (1.17) revealed a stronger perception than in other countries (2.60)(t=-26.342, p≤.000). Lastly, regarding the statement “Women receive less wages for thesame work than men,” women in India more strongly agreed (1.12) compared with the
respondents in the other countries (3.06) (t=-39.769, p≤.000). These results illustrate thatIndian women expressed stronger agreement with the existence of various types of gender
discrimination.
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in India with that experienced by respondents in the othercountries, the average score in India was 2.27, which was relatively high, although it was
lower than the score for the perception of a discriminatory reality. This represents asignificantly higher average than the score of 3.11 in the other countries (t=-21.476,p≤.000). Since lower scores refer to greater discriminatory experience, the result suggeststhat the respondents in India had more discriminatory experience than their counterpartsin the other 11 countries surveyed. Examining the differences for each of the fourquestions constituting this sub-scale, we found a significant difference in thediscriminatory experience of Indian women in all questions. First, the survey participantsin India (1.03) reported more experience of difficulty in participating in research projects
199

or becoming research managers than the respondents in the other countries (3.14), andthe difference was quite significant (t=-51.240, p≤.000). The Indian respondents (1.03)
also experienced more disadvantage in winning research grants or scholarships than theircounterparts in the other countries (3.47) (t=-31.148, p≤.000).
Likewise, a significant result was observed for sexual harassment and otherdisadvantages. Interestingly, however, the difference between the discriminatory
experience in India and the other countries showed an opposite trend. In other words, therespondents in India (4.91) reported significantly less experience of sexual harassmentand other disadvantages than the respondents in the other countries (3.19) (t=28.688,
p≤.000). Lastly, the Indian women (1.92) reported significantly more experience of
having work-life balance as a handicap than women in the other countries (2.65) (t=8.913, p≤..000).
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in India had an average score of 4.68, representing
a highly progressive attitude. This is significantly higher than the average of 3.30 in theother 11 countries (t=27.576, p≤.000). When examined for individual items, the Indian
respondents demonstrated a significant difference of progressiveness in all four questions
included in the sub-scale of sexual role attitudes. Indian women absolutely disagreed with
the idea that men are bread-winners of a household (average of 5.00), which represents asignificantly more progressive attitude compared with the average of the other countries(3.45) (t=41.844, p≤.000). The average score in India for the idea that women have an
inherent ability to take care of babies was 4.74, which is also more progressive than the
average of 3.23 in the other countries (t=15.856, p≤.000).
Regarding the idea that husbands should have more power and authority thantheir wives to maintain order and peace within the family, the Indian respondents
expressed an absolute disagreement (5.00), being more progressive than theircounterparts in the other countries (t=35.269, p≤.000). Lastly, compared with women in
the other 11 countries (2.84), the Indian women (3.97) proved significantly moreprogressive for the idea that men and women should have respectively suitable jobs since
men are rational and women emotional (t=9.674, p≤.000).
For career prospects, the women scientists and engineers in India produced arelatively optimistic view (3.55), offering no statistically significant difference fromwomen in the other countries (3.71). With regard to policy demand, the Indian
respondents had a significantly higher average (4.30) than the other respondents (4.05)(t=4.204, p≤.000). Lastly, in relation to the concept of equality, the Indian women (1.01)
had less tendency to believe that equal opportunity was a sufficient factor of genderequality than their counterparts (2.21) (t=-35.457, p≤.000).
200

<Table 4-72. Gap between India & others on gender barriers>(unit: points)

Item

Perception of
discrimination

Experience of
discrimination

Gender role
stereotypes

Career outlook
Policy needs
Equality
concept

1. Boys are encouraged more than girls to
go into the STEM field.
2. It is more difficult for a woman to get a
job in the STEM field than for a maneven with the same qualifications.
3. Becoming a tenured professor, being
promoted or becoming a principal
investigator is more difficult for female
scientists than for male scientists.
4. Women in STEM generally receive lesspay for equal work, compared with theirequally-qualified male colleagues.
Sub-scales
5. I have experienced disadvantages inleading or participating in research
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds or scholarships
because I am a woman.
7. I have experienced sexual harassment
or unfair treatments sometime in mycareer.
8. Balancing work and life (marriage andfamily) has been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care offinancial obligations) of households
should be men.
10. Women are born to have a way ofcaring children that men are not capableof in the same way.
11. In order to maintain the order andpeace of a family, the husband shouldhave greater power and authority than
the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each other by
doing what is appropriate forthemselves.
Sub-scales
13. I believe things will turn out fine in
my future career.
14. It is crucial to have strong policy
support to solve gender inequality in the
STEM field.
15. I believe gender equality will be fully
achieved only if women are given equal
opportunities as men.

Except
India
India
t
(n=93) (n=1,286)
1.08
2.56
-32.411

.000

1.16

2.61

-28.818

.000

1.17

2.60

-26.342

.000

1.12

3.06

-39.769

.000

1.13

2.70

-38.383

.000

1.03

3.14

-51.240

.000

1.20

3.47

-31.148

.000

4.91

3.19

28.668

.000

1.92

2.65

-8.913

.000

2.27

3.11

-21.476

.000

5.00

3.45

41.844

.000

4.74

3.23

15.846

.000

5.00

3.69

35.269

.000

3.97

2.84

9.674

.000

4.68

3.30

27.576

.000

3.55

3.71

-1.429

.153

4.30

4.05

4.204

.000

1.01

2.21

-35.457.000* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

201

(p)

Figure 4-65 illustrates the overall difference in perception of genderbarriers between the respondents in India and those in the other countries.
<Figure 4-65. Gap between India & others on gender barriers>(Unit: Points)

4.4.6.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in India according to the personal variables of the respondents and compare theresults with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Figure 4-66 compares the perception of a discriminatory reality by
the respondents in India and by those from the other countries. The level of perception ofgender discrimination in society had a score of 1.13, which represents almost a full assent
and is the highest among the 12 surveyed countries. The high sensitivity to discrimination
against women in their society appears correlated with the relatively young age of the
Indian respondents.
Table 4-73 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Indian respondents. The difference by age did
not prove significant. (It is essential to consider that the Indian respondents were all in
their 20s or 30s.) On the other hand, the difference by marital status was significant:married respondents more strongly perceived a discriminatory reality than did their single
counterparts (F=5.028, p≤.027). Whereas the number of children and duration of careerinterruption did not produce a statistically significant difference, occupation resulted in asignificant difference. The average score for the perception of discriminatory reality was202lowest (average of 1.00 each) among teachers/professors and healthcare/medical
professionals, and highest (2.00) among researchers (F=2.806, p≤.021).
<Figure 4-66. Average of India & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination<Table 4-73. Perception of discrimination of India: Demographic differences>(unit: person, points)

Classifications
Cases
Average
93
1.13
Total
Age
29 or below
70
1.16
30~39
23
1.03
40~49
50 or above
Marital status
Single49
1.20
Married
44
1.06
Other
No. of children
None
60
1.18
1
21
1.07
2
12
1.00
3 or above
Occupation
Student
6
1.25
Teacher/professor
11
1.00
Researcher
1
2.00
Medical personnel
9
1.00
Engineer
30
1.18
Other
36
1.13
Duration of career break
None
60
1.18
Less than 1 year
6
1.00
1~2 years9
1.17
2~3 years
3
1.00
3 years or more
15
1.00
* Lower score means higher perception of discrimination
203

SD
0.34
0.16

0.37
0.21
0.36
0.23
0.00

F

p

3.158

.079

5.028

.027

2.214

.115

2.806

.021

1.476

.216

0.39
0.00
0.00
0.38
0.28
0.36
0.00
0.33
0.00
0.00

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-67 compares the perception of
discriminatory reality as perceived by the respondents in India and by those from the othercountries. The average of 2.27 for this sub-scale indicates that the Indian respondents hada relatively prevalent experience of discrimination. As mentioned earlier, the perceptionof a discriminatory reality was strongest in India, and so was the actual experience of
discrimination among all 12 countries surveyed.
Table 4-74 provides the results of ANOVA of whether discriminatory experiencevaries depending on the personal variables of the Indian respondents. Different ages
resulted in a significant difference: those in their 30s experienced more discrimination
than the younger respondents (2.01 versus 2.35) (F=30.225, p≤.000). By marital status,
married respondents had more discriminatory experience than did their single
counterparts (2.40 versus 2.13) (F=24.455, p≤.000). A similar trend was found with thedifference according to the number of children: more discriminatory experience wasreported by the respondents with one child (2.05) or two children (2.02) than those
without children (2.40) (F=22.690, p≤.000).
<Figure 4-67. Average of India & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

The variable of occupation also produced a significant difference. Most
discriminatory experience was reported by teachers/professors (2.00) (excluding theoccupations classified as others), followed by healthcare/medical professionals (2.25),
students (2.42) and engineers (2.45), and researchers (3.25) (F=9.239, p≤.000). Lastly,
the respondents with at least three years of career interruption (1.93) reported more
discriminatory experience than the others, and those without career interruption reported
204the least experience (F=13.045, p≤.000).
<Table 4-74. Experience of discrimination of India : Demographic differences>(unit: person, points)

Classifications

Cases
93

Average
2.27

Total
Age
29 or below
70
2.35
30~39
23
2.01
40~49
50 or above
Marital status
Single49
2.40
Married
44
2.13
Other
No. of children
None
60
2.40
1
21
2.05
2
12
2.02
3 or above
Occupation
Student
6
2.42
Teacher/professor
11
2.00
Researcher
1
3.25
Medical personnel
9
2.25
Engineer
30
2.42
Other
36
2.18
Duration of career break
None
60
2.40
Less than 1 year
6
2.13
1~2 years9
2.11
2~3 years3
2.17
3 years or more
15
1.93
* Lower score means more discrimination experienced

SD
0.28
0.16

0.28
0.24
0.28
0.19
0.07

F

p

30.225.000

24.455.000

22.690

.000

9.239

.000

13.045

.000

0.26
0.00
0.31
0.32
0.19
0.28
0.14
0.13
0.14
0.11

Gender role ideology<Figure 4-68. Average of India & others on Gender role stereotypes>(unit: points)* Higher score means more progressive205In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-68 compares attitudes toward genderroles by the respondents in India and by those from the other countries. The average score
for the sub-scale of gender role ideology was as high as 4.68 out of 5, suggesting that the
Indian respondents had the more progressive attitude toward gender roles than those in
any other countries.
Table 4-75 provides the results of ANOVA of whether gender role attitudes varydepending on the personal variables of the Indian respondents. Except for occupation,
variables such as age, marital status, number of children, and career interruption did not
produce a significant difference. In the case of the number of children, those without child(4.71) and fewer children (4.65 for one child; 4.54 for two children) tended to be moreprogressive; however, the difference did reach statistical significance.
<Table 4-75. Gender role stereotypes of India : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
93

Average
4.68

SD

70
23

4.66
4.72

0.44
0.25

49
44

4.67
4.68

0.37
0.44

60
21
12

4.71
4.65
4.54

0.37
0.54
0.14

6
11
1
9
30
36

5.00
4.50
5.00
4.28
4.57
4.86

0.00
0.00

60
6
9
3
15

4.71
4.25
4.78
4.75
4.63

0.37
0.82
0.26
0.43
0.23

* Higher score means more progressive

206

0.70
0.40
0.23

F

p

.306

.582

.010

.920

.964

.385

6.800

.000

2.165

.079

The difference by occupation implies that students and researchers were moreprogressive (average of 5.00 each, excluding the occupations classified as others),
followed by engineers (4.57) and teachers/professors (4.50), and healthcare/medical
professionals (4.28) (F=6.800, p≤.000).
Career prospects
As can be seen in Figure 4-69, the respondents in India demonstrated relative
optimism about their career prospects, with an average score of 3.55. However, thisindicates that the country had the fourth lowest average, following Japan, Vietnam, andKorea. This result seems related to the highest perception of a discriminatory reality anddiscriminatory experience among the Indian respondents.
<Table 4-76. Career outlook of India : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
93

Average
3.55

SD

70
23

3.77
2.87

0.92
1.01

49
44

3.92
3.14

0.91
0.98

60
21
12

3.83
3.00
3.08

0.87
1.34
0.29

6
11
1
9
30
36

3.67
3.00
3.00
4.11
3.97
3.22

1.03
0.00

60
6
9
3
15

3.83
4.17
3.33
2.67
2.47

0.87
0.98
0.87
0.58
0.92

* Higher score means a more positive outlook

207

1.05
0.81
1.15

F

p

15.829.000

15.956

.000

7.633

.001

3.423

.007

8.943

.000

<Figure 4-69. Average of India & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Table 4-76 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Indian respondents. The difference by age
suggests that those in their 20s (3.77) had more optimistic views than those in their 30s(2.87) (F=15.829, p≤.047). By marital status, the single respondents (3.92) held more
optimistic career prospects than their married counterparts (3.14) (F=15.956, p≤.000).
The number of children also produced a significant difference: the average score among
those without child (3.83) was considerably higher than that of the respondents withchildren (3.00 for one child; 3.08 for two children) (F=7.633, p≤.001). Occupation also
proved a meaningful variable. The average was highest among healthcare/medical
professionals (4.11), followed by engineers (3.97) and students (3.67); the score waslowest among teachers/professors and researchers (3.00 each), except for the otheroccupations (F=3.423, p≤.007). Lastly, a significant difference was observed for theduration of career interruption. The average score was highest among the respondents
who experienced interruption of less than one year (4.17), followed by those without any
interruption (3.83), with one to two years (3.33), two to three years (2.67), and three years
or more (2.47) (F=8.943, p≤.000).
Policy demand
As can be seen in Figure 4-70, the average score for policy demand in India was
4.30, placing the country in third highest place after Vietnam and Nepal. This result seems
related with the high perception of a discriminatory reality and prevalent experience of
discrimination reported by the Indian respondents.

208

<Figure 4-70. Average of India & others on Policy needs>(unit: points)* Higher score means higher needs for policy support<Table 4-77. Policy needs of India : Demographic differences>(unit: person, points)

Classifications
Cases
Average
93
4.30
Total
Age
29 or below
70
4.34
30~39
23
4.17
40~49
50 or above
Marital status
Single49
4.41
Married
44
4.18
Other
No. of children
None
60
4.35
1
21
4.29
2
12
4.08
3 or above
Occupation
Student
6
4.33
Teacher/professor
11
4.00
Researcher
1
4.00
Medical personnel
9
4.22
Engineer
30
4.40
Other
36
4.33
Duration of career break
None
60
4.35
Less than 1 year
6
4.17
1~2 years
94.56
2~3 years
3
4.33
3 years or more
15
4.00
* Higher score means higher needs for policy support
209

SD
0.51
0.39

0.54
0.39
0.52
0.46
0.29

F

p

2.133

.148

5.303

.024

1.548

.218

1.283

.279

2.496

.048

0.52
0.00
0.44
0.56
0.48
0.52
0.41
0.53
0.58
0.00

Table 4-77 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Indian respondents. The personal variables
with statistically significant relevance to policy demand were marital status and careerinterruption. By age, those in their 20s (4.34) had stronger policy demand than those in
their 30s (4.17); however, the difference was not significant. By marital status, the single
respondents’ average (4.41) was higher than that of the married (4.18) (F=5.303, p≤.024).
According to the number of children, the highest average was reported by those withoutchildren (4.35), followed by those with one child (4.29) and those with two children (4.08);
however, the difference did reach a statistically significant level. Occupation did not
result in a significant difference, but occupation did: the average was highest (4.56)
among those experiencing one to two years of career interruption and lowest (4.00)
among those with at least three years of interruption (F=2.496, p≤.048).
Gender equality
As can be seen in Figure 4-71, the Indian respondents showed a strong tendency
to believe that full gender equality would be realized once women were granted equal
opportunity (average of 1.01; a lower score represents stronger agreement). This score
was higher than that in any other countries.
<Figure 4-71. Average of India & others on Equality concept>(unit: points)

ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in India to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-78). Such a belief was
found to be unrelated to respondent age. The differences by marital status, number ofchildren, occupation, and duration of career interruption were not significant, either.
Since the average score among the Indian women is close to 1.00, which means absoluteagreement, no distinctive results were observed.
210

<Table 4-78. Equality concept of India : Demographic differences>(unit: person, points)
Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
93

Average
1.01

SD

F

p

70
23

1.01
1.00

0.12
0.00

.326

.569

49
44

1.02
1.00

0.14
0.00

.897

.346

60
21
12

1.02
1.00
1.00

0.13
0.00
0.00

.271

.764

6
11
1
9
30
36

1.00
1.00
1.00
1.00
1.03
1.00

0.00
0.00
.406

.843

60
6
9
3
15

1.02
1.00
1.00
1.00
1.00

0.13
0.00
0.00
0.00
0.00

.132

.970

0.00
0.18
0.00

4.4.8 Japan
4.4.8.1 Respondent profile
A total of 138 respondents participated in the survey in Japan (see Table 4-79).
Those in their 50s accounted for 55.1%, followed by those in 40s (24.6%), 30s (17.4%),
and 20s (2.9%). The average age was highest at 50.89. By marital status, a majority ofthe participants were married (70.3%), followed by single (23.9%) and the other group(5.8%). Most of the respondents (41.3%) did not have any children; 23.9% had one child;
26.8% had two; and 8.0% had three or more children.
By occupation, the largest group was teachers/professors (34.8%), followed byresearchers (28.3%), engineers (18.8%), others (13.0%), healthcare/medical professionals(3.6%), and students (1.4%). Most respondents had no career interruption (37.7%); while
17.4% had less than one year of interruption; 16.7% had one to two years; 15.2% had
three years or longer; and 10.1% had two to three years.
211

<Table 4-79. Profile of participants from Japan>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

4
24
34
76

2.9
17.4
24.6
55.1

33
97
8

23.9
70.3
5.8

57
33
37
11

41.3
23.9
26.8
8.0

2
48
39
5
26
18

1.4
34.8
28.3
3.6
18.8
13.0

52
24
23
14
21

37.7
17.4
16.7
10.1
15.2

4.4.8.2 Difference of gender barriers in Japan and other countries: Overview
Table 4-80 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Japan with that perceived by their counterparts inthe other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 2.84 in Japan, showing a significant
difference from the score of 2.57 among the other 11 countries (t=2.995, p≤.003; a lower
score is translated as stronger agreement with the perception of a discriminatory reality).
This result implies that Japanese women quite weakly perceive gender discrimination in
their society, compared with women in the other countries, which is presumably related
to the fact that the average age of the Japanese respondents was quite high at 50.89.

212

<Table 4-80. Gap between Japan & others on gender barriers>(unit: points)

Item
1. Boys are encouraged more than girls to go into
the STEM field.
2. It is more difficult for a woman to get a job in the
STEM field than for a man even with the same
qualifications.

Japan Except Japan(n=138) (n=1,241)

t

(p)
.102

2.63

2.45

1.636

2.97

2.46

4.816 1374

Perception of
3. Becoming a tenured professor, being promoted or
discrimination
becoming a principal investigator is more difficult 2.79
for female scientists than for male scientists.

2.47

2.523

.013

3.07

2.91

1.465

.145

2.84

2.57

2.995

.003

2.98

3.00

-.171

.864

3.18

3.33

-1.377 .169

2.91

3.35

-3.246 .001

2.60

2.60

.024

Sub-scales
9. Primary breadwinners (who take care of financial
obligations) of households should be men.
10. Women are born to have a way of caring
children that men are not capable of in the sameway.
11. In order to maintain the order and peace of afamily, the husband should have greater power
and authority than the wife.
12. In a relative sense, men are rational while
women are emotional and thus, they ought tocomplement each other by doing what is
appropriate for themselves.

2.91
3.21

3.07
3.59

-2.029 .043
-2.792 .006

3.22

3.35

-1.057 .291

3.27

3.83

-3.822 .000

3.20

2.89

2.476

Sub-scales
13. I believe things will turn out fine in my future
career.
14. It is crucial to have strong policy support tosolve gender inequality in the STEM field.
15. I believe gender equality will be fully achieved
only if women are given equal opportunities as
men.

3.22

3.42

-1.790 .075

2.96

3.78

-9.014 .000

3.15

4.17

-8.056 .000

3.26

2.00

10.789 .000

4. Women in STEM generally receive less pay for
equal work, compared with their equallyqualified male colleagues.
Sub-scales
5. I have experienced disadvantages in leading or
participating in research projects because I am awoman.
6. I have experienced disadvantages in receiving
research funds or scholarships because I am aExperience of
woman.
discrimination 7. I have experienced sexual harassment or unfair
treatments sometime in my career.
8. Balancing work and life (marriage and family)
has been a handicap for me.

Gender role
stereotypes

Careeroutlook
Policy needs
Equality
concept* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

213

.981

.013

As a result of analyzing each of the following questions included in this sub-scale,
we found that, for the statement “Women scientists have more difficulty than their malecounterparts in becoming full-time professors or managers,” the Japanese respondents(2.79) revealed a weaker perception than in other countries (2.47) (t=2.523, p≤.013). The
average of Japanese respondents was slightly higher than the other countries’ average inthe remaining three questions as well; however, the difference was not statisticallysignificant.
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Japan with that experienced by respondents in the othercountries, the average score in Japan was 2.91, which is lower than the average of 3.07 in
the other countries (t=-2.029, p≤.043). Since lower scores refer to greater discriminatory
experience, the result suggests that the respondents in Japan had more discriminatory
experience than their counterparts in the other 11 countries surveyed. This contrasts withthe lower awareness of a discriminatory reality among Japanese women in science andtechnology, compared with the other countries. Examining the differences for each of thefour questions constituting this sub-scale, we found a significant difference only withrespect to the experience of sexual harassment and other unfair treatment. The averagescore of the Japanese respondents was 2.91, lower than 3.35 in the other countries. Thissuggests that Japanese women had significantly more experience of sexual harassmentand other disadvantages (t=-3.246, p≤.001). No significant difference was found for theother three questions.
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Japan had an average score of 3.22, representing
a relatively progressive attitude. This is slightly lower than the average of 3.42 in the other11 countries; however, the difference was not significant. By individual questions, asignificant difference was found for the three statements, except for the idea that women
have an inherent ability to take care of babies. First, the respondents in Japan (3.21) weremore conservative than the other respondents (3.59) to the idea that men are breadwinners of a household (t=-2.792, p≤.006). Compared with the others (3.83), the Japanesewomen (3.27) were also conservative in the belief that husbands should have more power
and authority than their wives to maintain order and peace within the family (t=-3.822,
p≤.000). On the other hand, with respect to the statement that men and women shouldhave respectively suitable jobs since men are rational and women emotional, the Japanese
respondents (3.20) were significantly more progressive than their counterparts in the othercountries (2.89) (t=2.476, p≤.013).

214For career prospects, Japans had an average (2.96) below the median level,significantly lower than the average in the other countries (3.78) (t=-9.014, p≤.000). Next,
we examined the difference of average score for policy demand, and found a significantly
lower average in Japan (3.15) than in the other countries (4.17) (t=-8.056, p≤.000). Lastly,with respect to the concept of equality, the Japanese women (3.20) tended to agree lesswith the idea that equal opportunity was a sufficient factor of gender equality than womenin the other countries surveyed (2.89) (t=2.476, p≤.013).
<Figure 4-72. Gap between Japan & others on gender barriers>(Unit: Points)

4.4.8.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Japan according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-81 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the Japanese respondents. No
significant difference was observed in relation to age, marital status, number of children,
occupation, and duration of career interruption. However, older respondents had aconsistent tendency to perceive a discriminatory reality less strongly.
Figure 4-73 compares the perception of a discriminatory reality by the
respondents in Japan and by those from the other countries. The level of perception ofgender discrimination in society had a score of 2.84, slightly lower than the median level
and higher only than the scores for Sri Lanka, Malaysia, and Vietnam. Women in Japan
were not substantially sensitive to discrimination against women in their society, which
is probably related to the relatively old age of the Japanese respondents.
215

<Figure 4-73. Average of Japan & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination<Table 4-81. Perception of discrimination of Japan: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
138

Average
2.84

SD

F

p

4
24
31
70

3.38
3.16
2.90
2.67

1.01
0.86
0.91
1.03

2.013

.115

31
91
7

2.78
2.92
2.04

0.96
0.99
0.70

2.732

.069

52
30
36
11

2.96
2.78
2.79
2.59

1.02
0.95
0.93
1.16

.542

.654

2
46
36
5
23
17

3.38
2.79
2.88
2.85
2.89
2.75

0.88
1.06
0.98
0.74
0.95
1.02

.187

.967

50
23
21
14
20

2.92
2.74
2.99
2.59
2.74

1.03
1.02
0.87
0.67
1.17

.518

.722

* Lower score means higher perception of discrimination

216

Discriminatory experience
For the scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Figure 4-74 compares the discriminatory experienceamong the respondents in Japan and among respondents from the other countries. The
average score of the Japanese respondents (2.91) was slightly lower than the median level,placing Japan in fourth place after India, Vietnam, and Mongolia in terms of
discriminatory experience.
<Table 4-82. Experience of discrimination of Japan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status

Cases
138

Average
2.91

SD

F

p

4
24
32
74

4.06
3.16
2.88
2.78

0.69
0.88
0.90
0.97

3.067

.030

SingleMarriedOther
No. of childrenNone12
3 or above
Occupation

32
95
7

2.82
2.97
2.50

1.02
0.95
0.72

.978

.379

55
31
37
11

2.98
2.85
2.98
2.50

1.03
0.99
0.82
0.92

.886

.450

Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

2
48
38
5
23
18

3.00
2.91
3.04
2.60
2.80
2.86

0.35
0.96
1.00
1.05
0.91
1.02

.306

.909

50
24
23
14
20

2.97
2.90
3.08
2.80
2.65

1.00
1.06
0.78
0.73
0.98

.636

.638

* Lower score means more discrimination experienced

217

<Figure 4-74. Average of Japan & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Table 4-82 provides the results of ANOVA of whether discriminatory experiencevaries depending on the personal variables of the Japanese respondents. Different ages
resulted in a significant difference. Discriminatory experience was reported consistently
more by older respondents (4.06 for 20s; 3.16 for 30s; 2.88 for 40s; 2.78 for 50s) (F=3.067,
p≤.030). This tendency is opposite to the result of perception of a discriminatory reality
discussed earlier. No significant difference was observed for marital status, number ofchildren, occupation, and duration of career interruption.
Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-75 compares attitudes toward genderroles among the respondents in Japan and among respondents from the other countries.
The average score for the sub-scale of gender role attitudes was 3.22 out of 5, slightly
higher than the median, placing Japan in sixth place after Pakistan, Mongolia, Bangladesh,
Vietnam, and Malaysia.
Table 4-83 provides the results of ANOVA of whether gender role ideology varies
depending on the personal variables of the Japanese respondents. Except for occupation,
variables such as age, marital status, number of children, and career interruption did not
produce a significant difference. Still, we observed a consistently more progressive
attitude toward gender roles among younger respondents. By marital status, the othergroup was most progressive, followed by the married and single respondents; however,the difference did reach statistical significance. By occupation, students (4.25) proved
most progressive, followed by teachers/professors (3.58), researchers (3.28),
healthcare/medical professionals (2.95), and engineers (2.71) (F=2.620, p≤.027).
218

<Figure 4-75. Average of Japan & others on Gender role stereotypes>(unit: points)* Higher score means more progressive<Table 4-83. Gender role stereotypes of Japan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
* Higher score means more progressive

219

Cases
138

Average
3.22

SD

F

p

4
23
34
75

4.13
3.61
3.24
3.05

0.32
1.10
1.12
1.26

2.100

.103

33
95
8

2.99
3.29
3.44

1.34
1.14
1.30

.871

.421

57
32
36
11

3.04
3.41
3.30
3.39

1.25
1.26
1.09
1.09

.829

.480

2
48
38
5
25
18

4.25
3.58
3.28
2.95
2.71
2.85

0.35
1.09
1.09
1.82
1.22
1.27

2.620

.027

52
24
22
14
20

3.16
3.48
3.15
3.46
3.29

1.26
1.24
1.27
0.75
1.13

.436

.782

Career prospects
As can be seen in Figure 4-76, the respondents in Japan demonstrated a relatively
low average score of 2.96, which represents the lowest score among all the surveyedcountries. This is probably because the Japanese respondents were relatively old.
<Table 4-84. Career outlook of Japan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
138

Average
2.96

SD

F

p

4
24
34
75

3.50
3.13
2.85
2.92

0.58
1.30
1.10
1.12

.595

.619

33
96
8

2.70
3.05
2.88

1.21
1.08
1.46

1.224

.297

57
32
37
11

2.79
3.19
3.03
2.91

1.13
1.26
1.07
1.04

.903

.442

2
48
38
5
26
18

3.00
2.96
2.97
2.60
2.92
3.06

0.00
1.01
1.15
1.14
1.32
1.30

.128

.986

52
24
23
14
20

2.94
3.08
3.04
3.21
2.75

1.11
1.25
1.15
0.97
1.16

.434

.784

* Higher score means a more positive outlook

Table 4-84 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Japanese respondents. The difference by age
was insignificant; so were the differences by marital status, number of children, andduration of career interruption. By occupation (except for the others), the group most
optimistic about career prospects were students, and healthcare/medical professionals
were most pessimistic; however, the difference was not significant.
220

<Figure 4-76. Average of Japan & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Policy demand
As can be seen in Figure 4-77, the average score of the Japanese respondents forpolicy demand was 3.15 out of 5, slightly higher than the median level. However,considering that this score is lowest of all 12 countries, the scientists and engineers in Japan
seem to have a poor understanding of or a skeptical view about the importance of policy.
Table 4-85 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Japanese respondents. In Japan, no personalvariables had a statistically significant relevance to policy demand. By age, the older the
respondents, the lower policy demand becomes. Likewise, those with more children
tended to voice more policy demands; however, the difference was not significant.
<Figure 4-77. Average of Japan & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

221

<Table 4-85. Policy needs of Japan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
138

Average
3.15

SD

F

p

4
24
33
75

4.00
3.29
3.15
3.05

0.00
1.08
1.58
1.52

.642

.589

33
95
8

3.15
3.14
3.25

1.33
1.48
1.75

.022

.978

56
32
37
11

3.05
3.09
3.24
3.45

1.38
1.53
1.46
1.63

.307

.820

2
48
38
5
25
18

4.00
3.29
3.21
3.00
2.84
3.00

0.00
1.29
1.40
1.87
1.70
1.61

.512

.767

52
24
23
14
20

3.13
3.29
2.91
4.14
2.85

1.40
1.46
1.53
1.03
1.46

2.157

.078

* Higher score means higher needs for policy support

Gender equality
ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Japan to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-86). First of all, sucha belief was correlated to the respondents’ age. Those in their 20s agreed most with thestatement that equal opportunity was a sufficient factor of gender equality, and those in
their 40s agreed least (F=2.703, p≤.048). The average by marital status was insignificant;so were the difference according to the number of children, occupation, and duration ofcareer interruption.

222

<Table 4-86. Equality concept of Japan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
138

Average
3.26

SD

F

p

4
23
34
75

1.50
3.39
3.41
3.25

0.58
0.99
1.23
1.42

2.703

.048

33
95
8

3.39
3.26
2.75

1.25
1.31
1.75

.766

.467

57
32
36
11

3.25
3.44
3.39
2.45

1.23
1.39
1.29
1.51

1.706

.169

2
48
38
5
25
18

3.00
3.04
3.13
3.60
3.92
3.17

1.41
1.30
1.30
1.14
1.04
1.62

1.736

.131

52
24
22
14
20

3.15
3.00
3.55
3.00
3.45

1.26
1.41
1.44
1.18
1.28

.790

.534

<Figure 4-78. Average of Japan & others on Equality concept>(unit: points)

223

As can be seen in Figure 4-78, the Japanese respondents agreed less strongly thanthe median level with the statement that full gender equality would be realized once
women were granted equal opportunity (average of 3.26; a lower score represents stronger
agreement), with the highest average score among the 12 countries.
4.4.9 Taiwan
4.4.9.1 Respondent profile
A total of 79 respondents participated in the survey in Taiwan (see Table 4-87.
Most of them were in their 50s (39.2%), followed by 20s (31.6%), 30s (16.5%), and 40s(12.7%). By marital status, the single participants accounted for 44.3%, the married for
48.1%, and the other group for 7.6%. In terms of the number of children, 63.3% of all
respondents in Taiwan had no children; 21.5% had two children; 10.1% had three or more;
and 65.1% had one child. By occupation, teachers/professors were majority (30.4%),
followed by students (26.6%), researchers (16.5%), others (13.9%), engineers (7.6%),
and healthcare/medical professionals (5.1%). Most of the respondents did not have any
career interruption (67.1%); 12.7% had at least three years of interruption; and 7.6% had
one to two years. Those experiencing an interruption of less than one year and two to
three years accounted for 5.1% each.
4.4.9.2 Difference of gender barriers in Taiwan and other countries: Overview
Table 4-88 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Taiwan with that perceived by their counterparts inthe other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 2.65 in Taiwan, showing a significant
difference from the score of 2.59 among the other 11 countries (a lower score is translated
as stronger agreement with the perception of discriminatory reality). We analyzed eachof the four questions included in this sub-scale. With regard to the statement “Boys are
more encouraged than girls to choose the STEM fields,” the respondents in Taiwan
showed no significant difference from the result in the other countries. Conversely,
Taiwanese women agreed less strongly (2.89), compared with their counterparts in theother countries (2.49), with the statement “Compared with men, women with the sameabilities face greater difficulty finding a job in the STEM fields” (t=2.984, p≤.004.) This
result implies that Taiwanese women tend to less strongly perceive a discriminatory
reality. For the statements “Women scientists have more difficulty than their malecounterparts in becoming full-time professors or managers” and “Women receive lesswages compared with the men doing the same work,” the Taiwanese respondents did not
produce a significant difference.

224

<Table 4-87. Profile of participants from Taiwan>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

25
13
10
31

31.6
16.5
12.7
39.2

35
38
6

44.3
48.1
7.6

50
4
17
8

63.3
5.1
21.5
10.1

21
24
13
4
6
11

26.6
30.4
16.5
5.1
7.6
13.9

53
4
6
4
10

67.1
5.1
7.6
5.1
12.7

As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Taiwan with that experienced by respondents in theother countries, the average score in Taiwan was 3.19, representing no significant
difference from the average of 3.05 in the other countries (lower scores refer to moreexperience of discrimination). Examining the differences for each of the four questions
constituting this sub-scale, we found no particular difference with respect to thediscriminatory experience of Taiwanese women in all questions from the respondents inthe other countries. The Taiwanese respondents had relatively less difficulty inparticipating in research projects or becoming research managers and less disadvantage
in winning research grants or scholarships; however, the difference did reach statisticalsignificance.
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Taiwan had an average score of 3.87,
representing a relatively progressive attitude. This score represents a significantly more225

progressive attitude, compared with the average of 3.37 in the other countries (t=5.034,p≤.000). The Taiwanese respondents had a more progressive attitude toward gender roles
than the participants in the other countries with regard to the questions included in thissub-scale, except for the idea that men are bread-winners of a household. Regarding thisquestion, the average in Taiwan was slightly higher, but without a significant difference.
The Taiwanese respondents (3.80) agreed less strongly than the other respondents (3.31)
with the idea that women have an inherent ability to take care of babies (t=3.375, p≤.001).
For the statement that husbands should have more power and authority than their wives
to maintain order and peace within the family, women in Taiwan (4.33) expressed lessagreement than the others (3.74) (t=5.261, p≤.000). Lastly, the Taiwanese women (3.56)
were more progressive than those in the other countries (2.88) with respect to the ideathat men and women should have respectively suitable jobs since men are rational andwomen emotional (t=4.233, p≤.000).
For career prospects, the Taiwanese respondents had an average score of 3.78,
above the median level, showing only a slight difference from the average of women in
the other 11 countries (3.69). Next, as a result of analysis of differences between Taiwan
and the other countries, the Taiwanese participants had a slightly lower average (3.87) for
policy demand than the respondents in the other countries (4.08); however, the difference
was not significant. Lastly, the perception of the concept of equality among the womensurveyed in Taiwan was not notably different from that among the other participants.
Figure 4-79 illustrates the overall difference in perception of gender barriers
between the respondents in Taiwan and those in the other countries.
<Figure 4-79. Gap between Taiwan & others on gender barriers>(Unit: Points)

226

<Table 4-88. Gap between Taiwan & others on gender barriers>(unit: points)
Item

Perception of
discrimination

Experience of
discrimination

Gender role
stereotypes

Career outlook
Policy needs
Equality
concept

1. Boys are encouraged more than girls to go into the
STEM field.
2. It is more difficult for a woman to get a job in the
STEM field than for a man even with the same
qualifications.
3. Becoming a tenured professor, being promoted or
becoming a principal investigator is more difficult
for female scientists than for male scientists.
4. Women in STEM generally receive less pay for
equal work, compared with their equally-qualified
male colleagues.
Sub-scales
5. I have experienced disadvantages in leading or
participating in research projects because I am awoman.
6. I have experienced disadvantages in receiving
research funds or scholarships because I am awoman.
7. I have experienced sexual harassment or unfair
treatments sometime in my career.
8. Balancing work and life (marriage and family) has
been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care of financial
obligations) of households should be men.
10. Women are born to have a way of caring
children that men are not capable of in the sameway.
11. In order to maintain the order and peace of afamily, the husband should have greater power
and authority than the wife.
12. In a relative sense, men are rational while womenare emotional and thus, they ought to complement
each other by doing what is appropriate forthemselves.
Sub-scales
13. I believe things will turn out fine in my future
career.
14. It is crucial to have strong policy support to solve
gender inequality in the STEM field.
15. I believe gender equality will be fully achieved
only if women are given equal opportunities asmen.

Taiwan(n=94)

ExceptTaiwan(n=1,285)

t

(p)

2.44

2.47

-.157

.875

2.86

2.49

2.984

.004

2.48

2.51

-.170

.865

2.81

2.94

-.960

.339

2.65

2.59

.489

.625

3.27

2.98

1.947

.052

3.59

3.30

2.492

.014

3.24

3.31

-.490

.625

2.65

2.60

.338

.735

3.19

3.05

1.395

.163

3.80

3.54

1.978

.051

3.80

3.31

3.375

.001

4.33

3.74

5.261

.000

3.56

2.88

4.233

.000

3.87

3.37

5.034

.000

3.78

3.69

.764

.445

3.87

4.08

-1.686

.092

2.24

2.12

.898

.369

* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

227

4.4.9.3 Analysis of individual questions
Here, we will examine the gender barriers perceived and experienced by womenscientists and engineers in Taiwan according to the personal variables of the respondents
and compare the results with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Figure 4-80 compares the perception of a discriminatory reality by
the respondents in Taiwan and by those from the other countries. The level of perceptionof gender discrimination in Taiwanese society had a score of 2.65, ranking fifth lowest
after Sri Lanka, Malaysia, Vietnam, and Japan.
<Figure 4-80. Average of Taiwan & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Table 4-89 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Taiwanese respondents. By age, younger
respondents tended to more strongly perceive a discriminatory reality; however, thedifference not did reach statistical significance. The difference by marital status was not
significant, either. Whereas the respondents with more children tended to more strongly
perceive a discriminatory reality, the difference was not significant. No statisticalrelevance was observed either for differences by occupation and duration of careerinterruption.

228

<Table 4-89. Perception of discrimination of Taiwan: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
79

Average
2.65

SD

F

p

25
13
10
31

2.74
2.71
2.73
2.52

0.54
0.92
1.02
1.05

.337

.799

35
38
6

2.69
2.51
3.33

0.75
0.86
1.41

2.443

.094

50
4
17
8

2.75
2.50
2.57
2.28

0.84
1.40
0.98
0.54

.741

.531

21
24
13
4
6
11

2.64
2.59
2.73
2.13
2.92
2.73

0.54
1.15
1.00
0.32
0.58
0.88

.440

.819

53
4
6
4
10

2.67
2.13
2.71
2.88
2.63

0.93
0.75
1.20
0.14
0.70

.419

.794

* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-90 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of the
Taiwanese respondents. Different ages did not result in a notable difference in theexperiences of gender discrimination. The same was the case with the differences by
marital status and the number of children. Still, we were able to find a tendency for amore experiences of discrimination among those who had more children. By occupation,
healthcare/medical professionals reported the most discriminatory experience; the least
was reported by students; however, the difference was not significant. Lastly, no
statistical significance was observed from the difference by the length of careerinterruption.
229

<Table 4-90. Experience of discrimination of Taiwan : Demographic differences>(unit: person, points)

Classifications

Cases
79

Average
3.19

SD

F

p

25
13
10
31

3.40
3.13
3.43
2.96

0.60
1.11
1.12
0.96

1.344

.267

SingleMarriedOther
No. of children

35
38
6

3.30
3.01
3.63

0.83
0.95
1.08

1.665

.196

None
1
2
3 or above
Occupation

50
4
17
8

3.34
3.19
3.10
2.44

0.89
1.13
1.02
0.26

2.390

.075

Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career break

21
24
13
4
6
11

3.39
3.09
3.29
2.25
3.13
3.25

0.61
0.98
1.11
0.20
0.61
1.19

1.159

.338

None
Less than 1 year
1~2 years
2~3 years
3 years or more

53
4
6
4
10

3.12
3.50
3.96
3.19
2.90

0.90
1.14
1.01
1.05
0.79

1.499

.212

Total
Age
29 or below
30~39
40~49
50 or above
Marital status* Lower score means more discrimination experienced

The average score of the Taiwanese participants (2.65) was above the median level(see Figure 4-81). Just like the perception of a discriminatory reality, experience of gender
discrimination among the women scientists and engineers in Taiwan placed them in thefifth lowest rank, following Sri Lanka, Malaysia, Pakistan, and Nepal.

230

<Figure 4-81. Average of Taiwan & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology

In the sub-scale of gender role beliefs, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-82 compares attitudes toward genderroles among the respondents in Taiwan and among respondents from the other countries.
The average score in the sub-scale of gender role ideology was 3.87 out of 5, above themedian level. Relatively speaking, the respondents in Taiwan had the fourth mostprogressive attitude toward gender roles, following India, New Zealand, and Nepal.
<Figure 4-82. Average of Taiwan & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

231

Table 4-91 provides the results of ANOVA whether gender role ideology varies
depending on the personal variables of the Taiwanese respondents. Except for occupation,
variables such as age, marital status, number of children and career interruption did not
produce a significant difference. By age, those in their 20s and 30s tended to be moreprogressive than those in their 40s and 50s. Also with marital status, the single
respondents proved more progressive than the married or the other group. A significant
difference was found with the variable of occupation. Engineers (4.33) were mostprogressive toward gender roles, followed by researchers (4.29), teachers/professors(3.91), students (3.86), and healthcare/medical professionals (3.44) (F=2.736, p≤.025).
<Table 4-91. Gender role stereotypes of Taiwan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
* Higher score means more progressive

232

Cases
79

Average
3.87

SD

F

p

25
13
10
31

4.00
4.00
3.75
3.75

0.69
1.07
0.89
0.87

.559

.644

35
38
6

4.12
3.70
3.46

0.72
0.95
0.40

3.121

.050

50
4
17
8

3.93
4.38
3.82
3.34

0.81
1.09
0.79
1.03

1.631

.189

21
24
13
4
6
11

3.86
3.91
4.29
3.44
4.33
3.23

0.65
0.84
0.53
1.14
0.58
1.18

2.735

.025

53
4
6
4
10

3.89
3.69
4.08
3.88
3.80

0.85
0.94
0.98
1.05
0.90

.150

.963

Career prospects
Table 4-92 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Taiwanese respondents. The difference by age
showed that those in their 40s and 50s held more optimistic views as to career prospects
than younger respondents; however, the difference was not significant. The results
examined by marital status, number of children, and occupation were not statisticallysignificant, either. However, the average score obtained by healthcare/medical
professionals and engineers implies their optimistic view to career prospects, whilestudents and researchers were relatively less optimistic. Lastly, the difference by the
duration of career interruption was not significant.
<Table 4-92. Career outlook of Taiwan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
79

Average
3.78

SD

F

p

25
13
10
31

3.60
3.77
3.90
3.90

1.08
1.17
0.99
0.94

.446

.721

35
38
6

3.63
4.00
3.33

1.19
0.84
0.82

1.881

.159

50
4
17
8

3.68
4.25
3.71
4.38

1.06
0.96
0.92
0.92

1.398

.250

21
24
13
4
6
11

3.52
3.88
3.54
4.00
4.00
4.18

1.12
1.03
0.88
0.82
1.10
0.98

.877

.501

53
4
6
4
10

3.72
4.25
3.67
4.25
4.00

1.06
0.96
0.82
0.50
1.15

.578

.680

* Higher score means a more positive outlook233

As can be seen in Figure 4-83, the respondents in Taiwan demonstrated relative
optimism about their career prospects, with an average score of 3.78. This puts thecountry in sixth place, following Bangladesh, Sri Lanka, Pakistan, Mongolia, and
Nepal.
<Figure 4-83. Average of Taiwan & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Policy demand
As can be seen in Figure 4-84, the average score of the scientists and engineers
in Taiwan was 3.87 out of 5, which places the country in the third lowest rank after Japanand Malaysia.
<Figure 4-84. Average of Taiwan & others on Policy needs>(unit: points)* Higher score means higher needs for policy support234

Table 4-93 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Taiwanese respondents. With regard to policy
demand, no statistical significance was found for any of the personal variables such asage, marital status, number of children, occupation, and the length of career interruption.
By occupation, the average was highest among healthcare/medical professionals andlowest among students; however, the difference was not significant. This was also thecase with career interruption: those with no interruption or interruption of less than one
year had higher policy demand than the other respondents; however, the difference did
not reach statistical significance.
<Table 4-93. Policy needs of Taiwan : Demographic differences>(unit: person, points)

Classifications

Cases
79

Average
3.87

Total
Age
29 or below
25
3.80
30~39
13
4.00
40~49
10
3.80
50 or above
31
3.90
Marital status
Single35
3.89
Married
38
3.95
Other
6
3.33
No. of children
None
50
3.84
1
4
4.00
2
17
3.82
3 or above
8
4.13
Occupation
Student
21
3.76
Teacher/professor
24
3.79
Researcher
13
4.00
Medical personnel
4
4.25
Engineer
6
4.00
Other
11
3.91
Duration of career break
None
53
4.06
Less than 1 year
44.00
1~2 years63.50
2~3 years
4
3.50
3 years or more
10
3.40
* Higher score means higher needs for policy support

235

SD

F

p

1.08
1.22
0.92
1.16

.113

.953

1.13
0.90
1.97

.804

.451

1.22
0.82
0.95
0.83

.178

.911

1.14
1.14
1.41
0.96
0.63
0.94

.204

.960

1.12
1.15
1.22
0.58
1.07

1.116

.356

Gender equality
As can be seen in Figure 4-85, the participants in Taiwan had a greater tendency
to believe that full gender equality would be realized once women were granted an equal
opportunity (average of 2.24; a lower score represents stronger agreement). This ranks
the country in fifth place after Japan, Korea, Sri Lanka, and Malaysia.
<Table 4-94. Equality concept of Taiwan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
79

Average
2.24

SD

F

p

25
13
10
31

2.28
2.38
2.00
2.23

1.02
1.50
1.05
1.12

.225

.879

35
38
6

2.23
2.18
2.67

1.24
0.98
1.51

.465

.630

50
4
17
8

2.32
1.50
2.12
2.38

1.22
1.00
0.99
0.92

.746

.528

21
24
13
4
6
11

2.43
2.29
2.31
1.50
2.00
2.09

1.12
1.16
1.44
0.58
0.63
1.14

.551

.737

53
4
6
4
10

2.30
1.75
2.33
1.75
2.20

1.23
0.96
1.03
0.50
1.03

.404

.805

ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Taiwan to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-94). First, such a belief
did not prove to be correlated to the respondents’ age. No significant difference wasobserved for the average scores by marital status. The difference according to the numberof children and duration of career interruption was not significant, either. By occupation,236

the concept of equal opportunity was accepted most by healthcare/medical professionals
and least by students; however, the difference was not statistically significant.
<Figure 4-85. Average of Taiwan & others on Equality concept>(unit: points)

4.4.10 Pakistan
4.4.10.1 Respondent profile
A total of 102 participants responded to the survey in Pakistan (see Table 4-95).
Most respondents were in their 20s (47.1%), followed by 30s (37.3%), 50s (8.8%), and40s (6.9%). By marital status, the single respondents accounted for 40.2%, the marriedfor 56.9%, and the other group for 2.9%. In terms of the number of children, mostparticipants did not have children (54.9%), followed by those with one child (19.6%), twochildren (16.7%), and three or more children (8.8%). By occupation, most wereteachers/professors (43.1%), followed by researchers (16.7%), engineers (15.7%), and theother group (10.8%; students and healthcare/medical students accounted for the smallest
share (6.9% each). Those without any career interruption accounted for 54.9%, followedby those experiencing interruption for less than one year and one to two years (13.7%each), two to three years (9.8%), and three years or longer (7.8%).
4.4.10.2 Difference of gender barriers in Pakistan and other countries: Overview
Table 4-96 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Pakistan with that perceived by their counterpartsin the other 11 countries. To begin with, the sub-scale of the perception of discriminatory
reality against women had an average score of 2.64 in Pakistan, showing a significant
difference from the score of 2.59 among the other 11 countries (a lower score is translated
as a stronger perception of discriminatory reality). We analyzed each of the four questions
included in this sub-scale. With regard to the statement “Boys are more encouraged than
girls to choose the STEM fields,” the respondents in Pakistan demonstrated moreagreement with a significantly lower average of 2.11, compared with the average (2.49)
237

of the other countries (t=-3.564, p≤.001.). Conversely, Pakistani women showed nosignificant difference, compared with their counterparts in the other countries, for thestatement “Compared with men, women with the same abilities face greater difficultyfinding a job in the STEM fields.” Also, for the statement “Women scientists have moredifficulty than their male counterparts in becoming full-time professors or managers,” thePakistani respondents did not produce a significant difference from the other countries.
Lastly, regarding the statement “Women receive less wages for the same work than men,”
women in Pakistan agreed less strongly (3.32) compared with the respondents in the othercountries (2.90), showing a significant difference (t=3.159, p≤.002).
<Table 4-95. Profile of participants from Pakistan>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

48
38
7
9

47.1
37.3
6.9
8.8

41
58
3

40.2
56.9
2.9

56
20
17
9

54.9
19.6
16.7
8.8

7
44
17
7
16
11

6.9
43.1
16.7
6.9
15.7
10.8

56
14
14
10
8

54.9
13.7
13.7
9.8
7.8

As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Pakistan with that experienced by respondents in theother countries, the average score in Pakistan was 3.31, significantly lower than the238average of 3.03 in the other countries (lower scores represent more experience of
discrimination). We examined the differences for each of the four questions constituting
this sub-scale. First, between the Pakistani respondents and those in the other countries,
no significant difference was found with respect to experiencing more difficulty as
women in participating in research projects or becoming research managers. However,
women in Pakistan reported significantly less experience of disadvantage of winningresearch grants or scholarships (3.60 versus 3.29) (t=2.419, p≤.016). The experience ofsexual harassment or other disadvantage at work was reported significantly less by the
Pakistani respondents (3.60) than by the other participants in the survey (3.28) (t=2.273,
p≤.023). Lastly, the experience of having work-life balance as a handicap showed nosignificant difference.
With respect to the sub-scale of gender role ideology (higher scores refer to moreprogressive attitudes), the respondents in Pakistan had an average score of 2.40,
representing a relatively conservative attitude. This demonstrates a significantly moreconservative attitude compared with the average of 3.48 in the other countries (t=-10.501,
p≤.000). The scientists and engineers surveyed in Pakistan expressed a relatively moreconservative attitude toward gender roles in all of the four questions included in this subscale. First, the Pakistani respondents (2.32) agreed more with the statement that men are
bread-winners of a household, compared with women in the other countries (3.65) (t=9.931, p≤.000). They (1.93) expressed relatively stronger agreement with the idea thatwomen have an inherent ability to take care of babies than the others (3.45) (t=-13.395,p≤.000). In addition, the Pakistani women (2.95) agreed more than the others (3.84) with
the idea that husbands should have more power and authority than their wives to maintainpeace within the family (t=-6.649, p≤.000). Lastly, with regard to the statement that men
and women should have respectively suitable jobs since men are rational and women
emotional, the Pakistani women (2.41) were more conservative than the respondents inthe other countries (2.96) (t=-4.367, p≤.000).
The average score in Pakistan for career prospects were 4.02 out of 5, which issignificantly higher than the average of 3.67 in the 11 other countries (t=3.233, p≤.001).
We examined whether Pakistan had a different attitude toward policy demand to address
the problem of gender inequality in the STEM areas. As a result, we observed an almost
similar result to that found in the other countries. Lastly, regarding the concept of equality,
the Pakistani respondents (1.71) tended to believe, significantly more than the others(2.16), that equal opportunity was a sufficient factor of gender equality (t=-5.444, p≤.000).
Figure 4-86 illustrates the overall difference in perception of gender barriers
between the respondents in Pakistan and those in the other countries.

239

<Table 4-96. Gap between Pakistan & others on gender barriers(unit: points)

Item

ExceptPakistan Pakistan(n=94) (n=1,285)t(p)

1. Boys are encouraged more than girls to
go into the STEM field.

2.11

2.49

-3.564.001

2. It is more difficult for a woman to get a
job in the STEM field than for a maneven with the same qualifications.

2.48

2.51

-.290

.773

3. Becoming a tenured professor, being
promoted or becoming a principal
investigator is more difficult for female
scientists than for male scientists.

2.66

2.49

1.299

.194

4. Women in STEM generally receive lesspay for equal work, compared with theirequally-qualified male colleagues.

3.32

2.90

3.159

.002

Sub-scales
5. I have experienced disadvantages inleading or participating in research
projects because I am a woman.
6. I have experienced disadvantages inreceiving research funds or scholarships
because I am a woman.
Experience of
discrimination 7. I have experienced sexual harassment or
unfair treatments sometime in my career.
8. Balancing work and life (marriage andfamily) has been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care offinancial obligations) of households
should be men.
10. Women are born to have a way ofcaring children that men are not capableof in the same way.
11.
In order to maintain the order and peace
Gender roleof a family, the husband should havestereotypes
greater power and authority than the wife.
12. In a relative sense, men are rational
while women are emotional and thus,
they ought to complement each other by
doing what is appropriate for themselves.
Sub-scales

2.64

2.59

.605

.547

3.23

2.98

1.899

.058

3.60

3.29

2.419

.016

3.60

3.28

2.273

.023

2.81

2.58

1.840

.066

3.31

3.03

3.087

.002

2.32

3.65

-9.931

.000

1.93

3.45

-13.395 .000

2.95

3.84

-6.649

.000

2.41

2.96

-4.367

.000

2.40

3.48

-10.501 .000

13. I believe things will turn out fine in myfuture career.
14. It is crucial to have strong policy
support to solve gender inequality in the
STEM field.
15. I believe gender equality will be fully
achieved only if women are given equal
opportunities as men.

4.02

3.67

3.233

.001

4.07

4.07

-.018

.986

1.71

2.16

-5.444.000

Perception of
discrimination

Careeroutlook
Policy needs
Equality
concept* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

240

<Figure 4-86. Gap between Pakistan & others on gender barriers>(Unit: Points)

4.4.10.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Pakistan according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of Discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Figure 4-87 compares the perception of a discriminatory reality by
the respondents in Pakistan and by those from the other countries. The level of perceptionof gender discrimination in Pakistan society had a score of 2.64, ranking sixth lowest after
Sri Lanka, Malaysia, Vietnam, Japan, and Taiwan.
<Figure 4-87. Average of Pakistan & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

241

Table 4-97 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Pakistani respondents. No significant
difference was observed in terms of age, marital status, and the number of children. By
occupation, the perception of discriminatory reality was highest among engineers andlowest among healthcare/medical professionals; however, the difference was not ofstatistical significance. The difference depending on the duration of career interruption
was not significant, either.
<Table 4-97. Perception of discrimination of Pakistan: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
102

Average
2.64

SD

F

p

48
38
7
9

2.71
2.55
2.71
2.61

0.72
0.87
0.55
0.64

.321

.810

41
58
3

2.73
2.61
2.08

0.76
0.75
0.76

1.175

.313

56
20
17
9

2.66
2.43
2.91
2.53

0.72
0.70
0.86
0.81

1.364

.258

7
44
17
7
16
11

2.39
2.70
2.50
3.32
2.33
2.80

0.75
0.76
0.74
0.72
0.68
0.70

2.241

.056

56
14
14
10
8

2.75
2.70
2.30
2.28
2.88

0.73
0.87
0.64
0.70
0.81

1.824

.130

* Lower score means higher perception of discrimination

242

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-98 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of the
Pakistani respondents.
<Table 4-98. Experience of discrimination of Pakistan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
102

Average
3.31

SD

F

p

48
38
7
9

3.48
3.09
3.18
3.39

0.79
0.76
0.59
1.07

1.825

.148

41
58
3

3.43
3.24
2.92

0.87
0.75
0.95

1.055

.352

56
20
17
9

3.38
3.18
3.21
3.36

0.82
0.77
0.82
0.77

.429

.733

7
44
17
7
16
11

3.57
3.36
3.28
3.71
2.81
3.45

0.94
0.61
0.97
0.64
0.88
0.93

1.927

.097

56
14
14
10
8

3.44
3.41
3.18
3.08
2.75

0.84
0.66
0.65
0.47
1.10

1.741

.147

* Lower score means more discrimination experienced

No notable difference was found in terms of age. By marital status, whereas the
single respondents reported slightly less experience of discrimination than the married
and the other group; however, the difference was not significant. No statisticalsignificance was observed in differences according to the number of children. By
occupation, discriminatory experience was reported most by engineers, least by243healthcare/medical professionals; however, the difference was not significant. Further,although a longer duration of career interruption was associated with a higher tendencyof experiencing discrimination, the difference did reach the statistical significance level.
The average score in Pakistan for this sub-scale (3.31) was below the medianlevel (see Figure 4-88). This leaves the country in third lowest place after Sri Lanka andMalaysia.
<Figure 4-88. Average of Pakistan & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Figure 4-89 compares attitudes toward genderroles among the respondents in Pakistan and among respondents from the other countries.
The average score for the sub-scale of gender role beliefs was 2.40 out of, indicating a
relatively more conservative attitude. Indeed, the Pakistani respondents demonstrated themost conservative attitude among all 12 countries.
Table 4-99 provides the results of ANOVA of whether gender role ideology
varies depending on the personal variables of the Pakistani respondents. No significant
difference was found in terms of age, marital status, number of children, occupation, andthe length of career interruption. By marital status, the single respondents tended to be
more progressive than the married; however, the difference was not significant. By
occupation, healthcare/medical professionals proved most conservative, and students
most progressive; however, the difference was not significant.

244

<Figure 4-89. Average of Pakistan & others on Gender role stereotypes>(unit: points)* Higher score means more progressive<Table 4-99. Gender role stereotypes of Pakistan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
102

Average
2.40

SD

F

p

48
38
7
9

2.59
2.17
2.36
2.42

0.93
0.82
1.16
1.22

1.460

.230

41
58
3

2.51
2.35
2.00

0.84
1.02
0.43

.600

.551

56
20
17
9

2.46
2.45
2.21
2.36

0.88
0.98
0.96
1.24

.324

.808

7
44
17
7
16
11

2.57
2.49
2.72
1.79
2.34
1.93

0.84
0.89
0.99
0.85
0.97
0.96

1.753

.130

56
14
14
10
8

2.46
2.46
2.45
1.95
2.38

0.89
0.93
0.86
0.95
1.43

.657

.623

* Higher score means more progressive

245Career prospects
Table 4-100 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Pakistani respondents. Age did not produce asignificant difference. Whereas the single respondents held a relatively more optimistic
view regarding career prospects than the married and the other group; the difference was
not significant. By occupation, students were most optimistic, and teachers/professors
held the least optimistic view, but once again the difference was not significant enough.
Lastly, the difference in terms of the length of career interruption was not significant,either.
<Table 4-100. Career outlook of Pakistan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
102

Average
4.02

SD

F

p

48
37
7
9

4.15
3.92
4.43
3.44

1.03
1.06
0.79
1.13

1.633

.187

41
57
3

4.07
3.98
4.00

1.15
1.01
0.00

.088

.916

56
20
16
9

4.11
3.85
4.00
3.89

1.06
1.09
1.10
0.93

.346

.792

7
43
17
7
16
11

4.71
3.84
3.88
4.57
4.00
4.18

0.76
1.13
1.17
0.53
0.97
0.87

1.402

.231

56
14
14
9
8

4.07
3.93
4.07
3.78
4.00

1.13
0.83
1.27
0.97
0.53

.183

.947

* Higher score means a more positive outlook246

As can be seen in Figure 4-90, the respondents in Pakistan demonstrated relative
optimism about their career prospects, with an average score of 4.02. This puts the country
in third place, following Bangladesh, and Sri Lanka.
<Figure 4-90. Average of Pakistan & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Policy demand
As can be seen in Figure 4-91, the average score in Pakistan for policy demandwas 4.07 out of 5, but the score was still fourth lowest after Japan, Malaysia, and Taiwan.
<Figure 4-91. Average of Pakistan & others on Policy needs>(unit: points)* Higher score means higher needs for policy support

Table 4-101 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Pakistani respondents. No statisticalsignificance was observed in relation to policy demand in terms of any personal variables
such as age, marital status, number of children, occupation, and duration of career247

interruption. By marital status, the single respondents had less policy demand than themarried and the other group; however, the difference was not significant. By occupation,
the average score was highest among engineers (except for the other group), and lowest
among teachers/professors, but once again the difference was not significant enough. This
was also the case with career interruption: those without any interruption or interruptionof less than one year had less policy demand than the remaining groups; however, thedifference did reach statistical significance.
<Table 4-101. Policy needs of Pakistan : Demographic differences>(unit: person, points)

Classifications

Cases

Average

Total

102

4.07

Age
29 or below
30~39
40~49
50 or above
Marital status

48
38
7
9

SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

SD

F

p

4.13
3.92
4.29
4.22

1.00
1.17
0.76
0.67

.474

.701

41
58
3

3.80
4.22
4.67

1.17
0.90
0.58

2.606

.079

56
20
17
9

3.95
4.15
4.29
4.22

1.17
1.04
0.69
0.44

.640

.591

7
44
17
7
16
11

4.29
3.93
4.00
4.14
4.50
3.91

0.95
1.07
1.12
1.07
0.89
0.94

.853

.516

56
14
14
10
8

3.93
4.00
4.36
4.30
4.38

1.13
1.18
0.63
0.95
0.52

.852

.496

* Higher score means higher needs for policy support

248

Gender equality
As can be seen in Figure 4-92, the tendency to believe that full gender equality
would be realized once women were granted equal opportunity was relatively strong
among the Pakistani women (average of 1.71; a lower score represents stronger
agreement). This ranks the country in fourth place after India, Bangladesh, and Nepal.
<Table 4-102. Equality concept of Pakistan : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
102

Average
1.71

SD

F

p

48
38
7
9

1.63
1.68
2.00
2.00

0.73
0.87
0.82
0.50

.943

.423

41
58
3

1.73
1.69
1.67

0.78
0.80
0.58

.038

.962

56
20
17
9

1.68
1.55
2.00
1.67

0.77
0.69
1.00
0.50

1.111

.348

7
44
17
7
16
11

1.71
1.75
2.06
1.57
1.31
1.64

0.76
0.84
0.66
1.13
0.48
0.67

1.657

.153

56
14
14
10
8

1.66
1.64
2.00
1.70
1.63

0.77
0.74
0.88
0.95
0.52

.582

.676

ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Pakistan to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-102). As a result ofanalysis of such a belief by age, those in their 20s and 30s tended more to believe that
equal opportunity was sufficient than those in their 40s and 50s; however, the difference
was not statistically significant. No significant difference was observed in terms of marital
status, as was the case with the number of children and duration of career interruption.
249

By occupation, the concept of equal opportunity was accepted most by engineers and leastby researchers; however, the difference was not statistically significant.
<Figure 4-92. Average of Pakistan & others on Equality concept>(unit: points)

4.4.11 Republic of Korea
4.4.11.1 Respondent profile
A total of 135 respondents participated in the survey in Korea. Table 4-103
demonstrates the respondent profile in the nation. The respondents were evenly
distributed in all age groups: Those in their 20s accounted for 15.6%, 30s for 26.73%, 40s
for 28.1%, and 50s for 19.6%. The average age was 42.59. By marital status, the single
respondents accounted for 37%, the married for 61.5%, and the other for 1.5%. The
respondents without children accounted for 40.7%; those with one or two children
accounted for 26.7% each, and 5.2% of the respondents had three or more children.
By occupation, a majority was researchers (49.6%, followed byteachers/professors (31.9%), the other (6.7%), students (5.9%), engineers (4.4%), andhealthcare/medical professionals (0.7%). This shows that, compared with the othercountries, Korea had a small rate of engineers and healthcare/medical professionals. In
the meantime, those without any career interruption occupied the largest share (54.1%),
followed by those with interruption of one to two years (17.0%), those with less than one
year of interruption (12.6%); those with two to three years of interruption and three ormore years accounted for 7.4% each.

250

<Table 4-103. Profile of participants from Republic of Korea>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

21
36
38
40

15.6
26.7
28.1
29.6

50
83
2

37.0
61.5
1.5

55
36
36
7

40.7
26.7
26.7
5.2

8
43
67
1
6
9

5.9
31.9
49.6
.7
4.4
6.7

73
17
23
10
10

54.1
12.6
17.0
7.4
7.4

4.4.11.2 Difference of gender barriers in Korea and other countries: Overview
Table 4-104 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in South Korea with that perceived by theircounterparts in the other 11 countries. To begin with, the sub-scale of the perception of
discriminatory reality against women had an average score of 2.24 in Korea, showing asignificant difference from the score of 2.64 among the other 11 countries (t=-3.564,
p≤.001). A lower score refers to a higher perception of discriminatory reality. We
analyzed each of the four questions included in this sub-scale. With regard to thestatement “Boys are more encouraged than girls to choose the STEM fields,” therespondents in Korea (2.42) demonstrated no meaningful difference from the respondents
from other countries (2.47). Conversely, Korean women more strongly agreed (2.03),
compared with their counterparts in the other countries (2.56), with the statement“Compared with men, women with the same abilities face greater difficulty finding a jobin the STEM fields.” This significant difference indicates that the respondents in Korea
251

strongly assented to the idea that discrimination existed (t=-6.259, p≤.000).
For the statement “Women scientists have more difficulty than their malecounterparts in becoming full-time professors or managers,” the Korean respondents(1.94) revealed a significantly stronger perception than in other countries (2.57). Lastly,
regarding the statement “Women receive less wages for the same work than men,” womenin Korea more strongly agreed (2.57) compared with the respondents in the othercountries (2.97), resulting in a significant difference (t=-3.332, p≤.001).
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Korea with that experienced by respondents in the othercountries, unlike the perception of a discriminatory reality, experience of discrimination
among the Korean respondents was not significantly different from those in the othercountries. We examined the differences for each of the four questions constituting thisscale. To begin with, no significant difference was observed between Koreans and womenin the other 11 countries, with regard to the experience of difficulty in participating inresearch projects or becoming research managers. In addition, no notable difference wasfound in terms of the experience of advantage in winning research grants or scholarships.
On the other hand, experience of sexual harassment or other unfair treatment at work wassignificantly more reported by the Korean respondents (2.86) than by the others (3.35)(t=-4.350, p≤.000). Lastly, the experience of having work-life balance as a handicap
showed no significant difference.
For the sub-scale of gender role belief, a higher score represents more progressive
attitude. The average score obtained by the survey respondents in Korea was 3.61,
representing more progressiveness than the median level. This is significantly higher than
the average of 3.37 in the other countries (t=3.138, p≤.001). We examined each of thefour questions constituting this sub-scale. First, the Korean women (4.09) tended to be
more progressive than those in the other countries (3.39) regarding the statement that men
are bread-winners of a household (t=7.132, p≤.000). Conversely, for the idea that women
have an inherent ability to take care of babies, the Koreans (2.79) proved significantly
more conservative than the others (3.40) (t=-5.051, p≤.000).
In the meantime, the Korean respondents (4.18) tended to be more progressive
than the others (3.74) with respect to the idea that husbands should have more power andauthority than their wives to maintain peace within the family (t=4.762, p≤.000). Lastly,
the Koreans (3.38) were more progressive than the others (2.87) about the statement that
men and women should have respectively suitable jobs since men are rational and women
emotional (t=4.065, p≤.000).

252

<Table 4-104. Gap between Republic of Korea & others on gender barriers>

Item
1. Boys are encouraged more than girls to go
into the STEM field.
2. It is more difficult for a woman to get a job in
the STEM field than for a man even with thesame qualifications.
3. Becoming a tenured professor, being
Perception ofpromoted or becoming a principal
discrimination
investigator is more difficult for female
scientists than for male scientists.
4. Women in STEM generally receive less pay
for equal work, compared with their equallyqualified male colleagues.
Sub-scales
5. I have experienced disadvantages in leadingor participating in research projects because I
am a woman.
6. I have experienced disadvantages in receiving
research funds or scholarships because I am awoman.
Experience of
discrimination 7. I have experienced sexual harassment or
unfair treatments sometime in my career.
8. Balancing work and life (marriage andfamily) has been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care offinancial obligations) of households should bemen.
10. Women are born to have a way of caring
children that men are not capable of in thesame way.
Gender role 11. In order to maintain the order and peace of afamily, the husband should have greater
stereotypes
power and authority than the wife.
12. In a relative sense, men are rational while
women are emotional and thus, they ought tocomplement each other by doing what is
appropriate for themselves.
Sub-scales
13.
I
believethingswill turn out fine in my
Career outlook
future career.
It is crucial to have strong policy support to
Policy needs 14.solve
gender inequality in the STEM field.
Equality
concept

15. I believe gender equality will be fully
achieved only if women are given equal
opportunities as men.

(unit: points)
Republic Except Republicof Koreaof Koreat(p)(n=94)(n=1,285)
2.42
2.47-.465 .643
2.03

2.56

-6.259 .000

1.94

2.57

-6.901 .000

2.57

2.97

-3.332 .001

2.24

2.64

-5.951 .000

3.07

2.99

.755

3.46

3.30

1.646 .102

2.86

3.35

-4.350 .000

2.56

2.61

-.510

.611

2.99

3.06

-.954

.340

4.09

3.49

7.132 .000

2.79

3.40

-5.051 .000

4.18

3.74

4.762 .000

3.38

2.87

4.065 .000

3.61

3.37

3.138 .002

3.39

3.73

-3.679 .000

4.19

4.06

1.564 .119

3.12

2.02

11.003 .000

* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

253

.451

The average score of the Korean respondents was 3.39 for career prospects,
which is slightly above the median level. This is significantly lower than the average of
3.67 in the other 11 countries (t=-3.679, p≤.001). We examined whether Korea had adifferent attitude toward policy demand to address the problem of gender inequality in
the STEM areas. As a result, we observed an almost similar result to that found in theother countries. Lastly, regarding the concept of equality, the Korean respondents (3.12)
tended to believe significantly less than the others (2.02) that equal opportunity was asufficient factor for achieving gender equality (t=11.033, p≤.000).
Figure 4-93 illustrates the overall difference in perception of gender barriers
between the respondents in Korea and those in the other countries.
Figure 4-93. Gap between Republic of Korea & others on gender barriers(Unit: Points)

4.4.11.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Korea according to the personal variables of the respondents and compare
the results with those obtained in the other countries
Perception of discriminatory reality
For this scale, a lower score translates into a stronger perception of adiscriminatory reality. Table 4-105 provides the results of ANOVA of whether thisperception varies depending on the personal variables of the Korean respondents. No
significant difference was observed in terms of age and marital status. According to thenumber of children, the respondents without children or with one child tended to perceivea discriminatory reality less strongly than those with two or more children; however, the254difference was not significant. By occupation, the perception of a discriminatory reality
was highest among engineers and lowest among researchers; however, the difference was
not of statistical significance. The difference depending on the length of careerinterruption was not significant, either.
<Table 4-105. Perception of discrimination of Republic of Korea: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
135

Average
2.24

SD

F

p

21
36
38
40

2.24
2.33
2.20
2.20

0.71
0.77
0.69
0.66

.254

.859

50
83
2

2.24
2.25
2.13

0.74
0.69
0.18

.032

.969

55
36
36
7

2.28
2.30
2.17
1.89

0.77
0.62
0.67
0.78

.818

.486

8
43
67
1
6
9

1.91
2.14
2.39
2.25
1.83
2.33

0.74
0.69
0.66

1.622

.159

73
17
23
10
10

2.33
2.21
2.07
2.30
2.03

0.80
0.63
0.60
0.59
0.36

.918

.456

0.56
0.92

* Lower score means higher perception of discrimination

Figure 4-94 compares the perception of a discriminatory reality by the
respondents in Korea and by those from the other countries. The level of perception ofgender discrimination in society had a score of 2.64, higher than the median level andthird highest after India and Mongolia.

255

<Figure 4-94. Average of Republic of Korea & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Discriminatory experience
For the sub-scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. As illustrated in Figure 4-95, the average score of
the Korean women (2.99) was around the median level. Experience of discrimination
against women ranked Korea in fifth place after India, Vietnam, Mongolia and Japan.
Table 4-106 provides the results of ANOVA of whether discriminatory
experience varies depending on the personal variables of the Korean respondents. By age,experience of discrimination was reported most by the respondents in their 40s and 50s(2.80 and 2.81, respectively), followed by 30s (3.01), and least by those in their 20s (3.62)(F=5.902, p≤.001). By marital status, most discriminatory experience was reported by theother group (1.63), followed by the married (2.89) and single respondents (3.21) (F=5.444,p≤.005). Although those with more children tended to report more discriminatory
experience, the difference was not statistically significant.
A significant difference was found according to the respondents’ occupation.
Experience of discrimination was most prevalent among engineers (1.88), followed byhealthcare/medical professionals (2.50), (excluding the other group) teachers/professors(2.76), researchers (3.20), and students (3.59) (F=5.424, p≤.005). With frequently
reported experience of discrimination, the occupations of engineer andhealthcare/medical professional in Korea represent the most notable male-dominatedareas. In terms of career interruption, more experience of discrimination was reported bythose experiencing longer interruptions (F=3.276, p≤.014).

256

<Figure 4-95. Average of Republic of Korea & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced<Table 4-106. Experience of discrimination of Republic of Korea: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
135

Average
2.99

SD

F

p

21
36
38
40

3.62
3.01
2.80
2.81

0.66
0.71
0.82
0.88

5.902

.001

50
83
2

3.21
2.89
1.63

0.91
0.74
0.18

5.444

.005

55
36
36
7

3.18
2.97
2.76
2.61

0.94
0.63
0.78
0.75

2.455

.066

8
43
67
1
6
9

3.59
2.76
3.20
2.50
1.88
2.92

0.63
0.85
0.75

5.424

.000

73
17
23
10
10

3.18
2.96
2.84
2.83
2.28

0.91
0.54
0.69
0.60
0.72

3.276

.014

* Lower score means more discrimination experienced

257

0.54
0.59

Gender role ideology
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. Table 4-107 provides the results of ANOVA ofwhether perceived gender role ideology varies depending on the personal variables of the
Korean respondents. The difference according to age was significant: the attitude toward
gender roles became more conservative among older respondents (F=3.708, p≤.013). No
significant difference was found for marital status and the number of children. By
occupation, students proved relatively most progressive, and (excluding the other group)
researchers and teachers/professors were similarly most conservative; however, thedifference was not statistically significant. The difference by the duration of careerinterruption was not significant.

<Figure 4-96. Average of Republic of Korea & others on Gender role stereotypes>(unit: points)* Higher score means more progressive

Figure 4-96 compares attitudes toward gender roles among the respondents in
Korea and among respondents from the other countries. The average score for gender roleideology in Korea was 3.61 out of 5, representing a fairly progressive attitude. This makes
Korea the fifth most progressive nation after India, New Zealand, Nepal, and Taiwan.

258

<Table 4-107. Gender role stereotypes of Republic of Korea: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
135

Average
3.61

SD

F

p

21
36
38
40

3.80
3.76
3.72
3.27

0.69
0.69
0.84
0.81

3.708

.013

50
83
2

3.66
3.57
3.75

0.75
0.83
0.71

.221

.802

55
36
36
7

3.68
3.56
3.46
4.04

0.75
0.80
0.84
0.83

1.314

.273

8
43
67
1
6
9

4.06
3.60
3.59
3.75
3.92
3.28

0.69
0.89
0.76

1.039

.398

73
17
23
10
10

3.65
3.66
3.62
3.50
3.38

0.80
0.71
0.74
0.91
1.00

.331

.857

0.68
0.57

* Higher score means more progressive

Career prospects
As can be seen in Figure 4-97, the respondents in Korea demonstrated relative
optimism about their career prospects, with an average score of 3.39. When compared tothe other countries, however, Korea had the third lowest average, following Japan and
Vietnam.

259

<Figure 4-97. Average of Republic of Korea & others on Career outlook>(unit: points)* Higher score means a more positive outlook<Table 4-108. Career outlook of Republic of Korea : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
135

Average
3.39

SD

F

p

21
36
38
40

3.14
3.42
3.45
3.43

0.85
1.00
0.89
1.06

.527

.664

50
83
2

3.26
3.46
3.50

0.99
0.95
0.71

.671

.513

55
36
36
7

3.29
3.64
3.17
4.00

1.03
0.83
0.94
0.82

2.663

.051

8
43
67
1
6
9

3.63
3.86
3.13
3.00
3.00
3.11

1.06
1.01
0.87

3.827

.003

73
17
23
10
10

3.41
3.29
3.43
3.40
3.20

1.00
0.92
1.20
0.52
0.63

.154

.961

* Higher score means a more positive outlook

260

0.63
0.78

Table 4-108 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Korean respondents. Age did not produce asignificant difference. Whereas the group of single respondents held a relatively more
optimistic view regarding career prospects than the married and the other group, thedifference was not significant. The difference according to the number of children was
not significant as well. By occupation, teachers/professors (3.86) held the most optimistic
view to career prospects, followed by students (3.63) and researchers (3.13).
Healthcare/medical professionals and engineers proved least optimistic (3.00 each)(F=3.827, p≤.003). Lastly, no significant difference was found in terms of the duration ofcareer interruption.
Policy demand
Table 4-109 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Korean respondents. No statistical significancewas observed in relation to policy demand in terms of any personal variables such as age,marital status, number of children, occupation, and duration of career interruption. By
marital status, the group of single respondents had less policy demand than the married
and the other group; however, the difference was not significant. By occupation, theaverage score was highest among healthcare/medical professionals and lowest among
researchers, but once again the difference was not significant. No significant difference
was found in terms of the duration of career interruption.
<Figure 4-98. Average of Republic of Korea & others on Policy needs>(unit: points)* Higher score means higher needs for policy support261

<Table 4-109. Policy needs of Republic of Korea : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
135

Average
4.19

SD

F

p

21
36
38
40

3.86
4.19
4.16
4.38

1.20
0.79
0.86
0.74

1.652

.180

50
83
2

4.04
4.25
5.00

0.99
0.79
0.00

1.831

.164

55
36
36
7

4.07
4.19
4.31
4.57

0.96
0.82
0.82
0.53

.990

.400

8
43
67
1
6
9

3.75
4.33
4.12
5.00
4.33
4.11

1.58
0.71
0.88

.910

.477

73
17
23
10
10

4.05
4.29
4.48
3.90
4.40

0.94
0.77
0.59
1.20
0.52

1.552

.191

0.82
0.78

* Higher score means higher needs for policy support

As can be seen in Figure 4-98, the average score obtained by the scientists andengineers surveyed in Korea was 4.19 out of 5, which was quite a high score. However,relatively compared with the other countries, Korea ranked sixth lowest after Japan,
Malaysia, Taiwan, Pakistan, and Sri Lanka.
Gender equality
As can be seen in Figure 4-99, the Korean respondents’ agreement with the ideathat full gender equality would be realized once women were granted equal opportunity
was below the median level (average of 3.12; a lower score represents stronger
agreement). This places Korea in the second lowest rank after Japan. In other words,
compared with the other countries, the respondents in Korea tended to believe that equal262opportunity was not sufficient in achieving gender equality in the field of science andtechnology.
<Figure 4-99. Average of Republic of Korea & others on Equality concept>(unit: points)<Table 4-110. Equality concept of Republic of Korea : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more
263

Cases
135

Average
3.12

SD

F

p

21
36
38
40

3.14
3.28
3.08
3.00

0.96
1.14
1.05
1.11

.443

.723

50
83
2

3.14
3.10
3.50

1.07
1.09
0.71

.152

.859

55
36
36
7

3.15
3.22
3.11
2.43

1.10
1.02
1.04
1.40

1.084

.358

8
43
67
1
6
9

2.75
2.77
3.42
1.00
3.00
3.22

1.04
1.17
0.96

3.187

.010

73
17
23
10
10

3.12
3.06
3.04
3.30
3.20

1.05
1.20
1.15
0.67
1.03

.129

.972

0.89
0.97

ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Korea to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-110). As a result ofanalyzing this belief according to respondent age, no significant difference was observed.
Personal variables such as marital status, number of children, and duration of careerinterruption did not produce any significant difference in average scores. On the other
hand, the difference by occupation was significant. The concept of equal opportunity was
accepted most by healthcare/medical professionals (1.00), followed by students (2.75),
teachers/professors (2.77), engineers (3.00), and researchers (3.42) (F=3.187, p≤.010).
4.4.12 Bangladesh
4.4.12.1 Respondent profile
A total of 101 respondents participated in the survey in Bangladesh.
Table 4-111 provides the respondent profile of the country. The age distribution was
notably uneven among the participants, with those in their 20s accounting for 87.1% and
30s for 10.9%. By marital status, the single respondents accounted for 74.3% and themarried for 25.7%. In terms of the number of children, 78.2% had no children; 6.9% had
one; and 3.0% had two children. By occupation, a majority (35.6%) were
healthcare/medical professionals, and the second largest group was students (29.7%).
Researchers accounted for 13.9%, the other group for 7.9%, teachers/professors for 6.9%,
and engineers for 5.9%. In terms of career interruption, 73.3% of the respondents reported
no interruption; those with one to two years of interruption accounted for 9.9%; thosewith interruption of less than one year and three years or longer accounted for 5.9% each,and the smallest group (1.0%) had two to three years of interruption.
4.4.12.2 Difference of gender barriers in Bangladesh and other countries: Overview
Table 4-112 shows the results of a t-test comparing the gender barriers perceived
by women scientists and engineers in Bangladesh with that perceived by theircounterparts in the other 11 countries. To begin with, the sub-scale of the perception of
discriminatory reality against women had an average score of 2.29 in Bangladesh, which
is significantly lower than the average (2.62) of the other 11 countries (t=-4.037, p≤.000).
A lower score means higher perception of discriminatory reality. We analyzed each of
the four questions included in this sub-scale. With regard to the statement “Boys are moreencouraged than girls to choose the STEM fields,” the respondents in Bangladesh
demonstrated more agreement with a significantly higher average of 2.03, compared withthe average (2.50) of the other countries (t=-3.890, p≤.000). In addition, women in
Bangladesh more strongly agreed (2.07), compared with their counterparts in the othercountries (2.54), with the statement “Compared with men, women with the same abilities
face greater difficulty finding a job in the STEM fields.” This significant differenceindicates that the respondents in Bangladesh strongly assented to the idea that
discrimination existed (t=-4.071, p≤.000).
264

<Table 4-111. Profile of participants from Bangladesh>(unit: person, %)Classifications
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

N

%

88
11
1
1

87.1
10.9
1.0
1.0

75
26

74.3
25.7

79
7
3

78.2
6.9
3.0

30
7
14
36
6
8

29.7
6.9
13.9
35.6
5.9
7.9

74
6
10
1
6

73.3
5.9
9.9
1.0
5.9

<Figure 4-100. Gap between Bangladesh & others on gender barriers>(Unit: Points)

265

<Table 4-112. Gap between Bangladesh & others on gender barriers>(unit: points)

Item

ExceptBangladesh Bangladesh(n=101)(n=1,278)t(p)

1. Boys are encouraged more than girls to go into
the STEM field.
2. It is more difficult for a woman to get a job in
the STEM field than for a man even with thesame qualifications.
3. Becoming a tenured professor, being promoted
Perception ofor becoming a principal investigator is more
discriminationdifficult for female scientists than for malescientists.
4. Women in STEM generally receive less pay for
equal work, compared with their equallyqualified male colleagues.

2.03

2.50

-3.890

.000

2.07

2.54

-4.071

.000

2.32

2.52

-1.583

.114

2.75

2.94

-1.391.164

Sub-scales
5. I have experienced disadvantages in leading or
participating in research projects because I am awoman.
6. I have experienced disadvantages in receiving
research funds or scholarships because I am awoman.
Experience of
discrimination 7. I have experienced sexual harassment or unfair
treatments sometime in my career.
8. Balancing work and life (marriage and family)
has been a handicap for me.
Sub-scales
9. Primary breadwinners (who take care offinancial obligations) of households should bemen.
10. Women are born to have a way of caring
children that men are not capable of in the sameway.
Gender role 11. In order to maintain the order and peace of afamily, the husband should have greater power
stereotypes
and authority than the wife.
12. In a relative sense, men are rational while
women are emotional and thus, they ought tocomplement each other by doing what is
appropriate for themselves.

2.29

2.62

-4.037

.000

3.03

2.99

.280

.780

3.60

3.29

2.457

.014

3.50

3.29

1.391

.167

2.58

2.60

-.141

.888

3.18

3.04

1.316

.191

2.97

3.60

-4.549

.000

3.21

3.35

-.870

.386

3.86

3.77

.576

.566

2.21

2.98

-5.409.000

Sub-scales
13.
I
believethingswill turn out fine in my future
Career outlook
career.

3.06

3.42

-3.403

.001

4.37

3.64

6.797

.000
.125

Policy needs

14. It is crucial to have strong policy support tosolve gender inequality in the STEM field.

4.23

4.06

1.535

Equality
concept

15. I believe gender equality will be fully achieved
only if women are given equal opportunities as
men.

1.41

2.18

-10.371 .000

* Perception of discrimination : Lower score means higher perception of discrimination* Experience of discrimination : Lower score means more discrimination experienced* Gender role stereotypes : Higher score means more progressive* Career outlook : Higher score means a more positive outlook* Policy needs : Higher score means higher needs for policy support

266

For the statement “Women scientists have more difficulty than their malecounterparts in becoming full-time professors or managers,” the respondents in
Bangladesh did not produce a significant difference from the other countries. Lastly,
regarding the statement “Women receive less wages for the same work than men,” womenin Bangladesh did not produce a statistically significant difference, either.
As a result of conducting a t-test to compare the gender discrimination
experienced by the respondents in Bangladesh with that experienced by respondents inthe other countries, unlike the perception of a discriminatory reality, experience of
discrimination among the Bangladeshi respondents was not significantly different fromthose in the other countries. We examined the differences for each of the four questions
constituting this sub-scale. First, no significant difference was found for Bangladeshi
women’s experience of the difficulty in participating in research projects or becoming
research managers. However, the respondents in Bangladesh (3.60) reported asignificantly less experience of disadvantage in winning research grants or scholarships
than women in the other 11 countries (3.29) (t=2.457, p≤.014). No notable difference wasobserved between those in Bangladesh and the other countries with respect to sexual
harassment and other unfair treatment at work. Lastly, the experience of having work-lifebalance as a handicap showed no significant difference.
In the sub-scale of gender role ideology, a higher score translates into a moreprogressive attitude toward gender roles. The average score of the women scientists andengineers in Bangladesh was 3.06, near the median level. This indicates that women in
Bangladesh are significantly more conservative compared with the average of 3.42 among
respondents in the other countries surveyed. We examined each of the four questions forthis sub-scale. First, the Bangladeshi respondents (2.97) proved to be more conservative
than the other respondents (3.60) regarding the statement that men are bread-winners ofa household (t=-4.549, p≤.000). No particular difference was found, however, for the ideathat women have an inherent ability to take care of babies. In addition, no significant
difference in the average score was observed with respect to the statement that husbands
should have more power and authority than their wives to maintain peace within thefamily. Lastly, for the idea that men and women should have respectively suitable jobs
since men are rational and women emotional, women in Bangladesh (2.21) were moreconservative than the others (2.98) (t=-5.409, p≤.000).
In terms of career prospects, the average score in Bangladesh was 4.37 out of 5,which was significantly higher than the average of 3.64 in the other countries (t=6.797,
p≤.000). Next, we examined whether Bangladesh had a different attitude toward policy
demand to address the problem of gender inequality in the STEM areas. As a result, weobserved an almost similar result to that found in the other countries. Lastly, regarding
the concept of equality, the Bangladeshi respondents (1.41) tended to believe,267

significantly more than the others (2.18), that equal opportunity was a sufficient factor
for achieving gender equality (t=-10.371, p≤.000).
Figure 4-100 illustrates the overall difference in perception of gender barriers
between the respondents in Bangladesh and those in the other countries.
4.4.12.3 Analysis of individual questions
Here, we will examine the gender barriers perceived by women scientists andengineers in Bangladesh according to the personal variables of the respondents andcompare the results with those obtained in the other countries
Perception of discriminatory reality
For this sub-scale, a lower score translates into a stronger perception of adiscriminatory reality. Figure 4-101 compares the perception of a discriminatory reality
by the respondents in Bangladesh and by those from the other countries. The level ofperception of gender discrimination in society had a score of 2.29, which is fourth highest
after India, Mongolia and Korea.
<Figure 4-101. Average of Bangladesh & others on Perception of discrimination>(unit: points)* Lower score means higher perception of discrimination

Table 4-113 provides the results of ANOVA of whether this perception varies
depending on the personal variables of the Bangladeshi respondents. No significant
difference was found based on age. By marital status, the group of single respondents
reported weaker perception of a discriminatory reality; however, the difference was of no
statistical significance. The number of children did not result in a significant difference,either. By occupation, the perception of a discriminatory reality was highest among
healthcare/medical professionals and lowest among engineers; however, the difference
was not of statistical significance. The difference depending on the duration of career268

interruption was not significant, either.
<Table 4-113. Perception of discrimination of Bangladesh: Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
2.29

SD

88
11
1
1

2.24
2.55
3.50
2.75

0.75
0.94

75
26

2.28
2.33

0.73
0.90

79
7
3

2.26
2.43
2.75

0.76
0.93
1.30

30
7
14
36
6
8

2.38
2.46
2.23
2.12
2.50
2.53

0.83
1.06
0.87
0.64
0.96
0.51

74
6
10
1
6

2.22
2.88
2.30
2.25
2.46

0.75
1.00
0.88

F

p

1.465

.229

.070

.792

.685

.507

.762

.579

1.056

.383

0.84

* Lower score means higher perception of discrimination

Discriminatory experience
For the scale of discriminatory experience, a lower score represents moreexperience of gender discrimination. Table 4-114 provides the results of ANOVA ofwhether discriminatory experience varies depending on the personal variables of the
Bangladeshi respondents. No significant difference was found for the personal variableof age, but it is important to remember that 87% of the respondents in Bangladesh was intheir 20s. Marital status and the number of children did not produce a significant
difference, either. By occupation, discriminatory experience was reported most by
researchers and least by engineers; however, the difference did reach statisticalsignificance. In terms of career interruption, experience of discrimination was reported269

most by those with interruption of three years or more (3.00) and those without any
interruption (3.01), and least by those experiencing interruption for less than one year
(4.54) (F=3.979, p≤.005). As illustrated in Figure 4-102, the average score (3.18) for thissub-scale in Bangladesh was below the median level. In terms of discriminatory
experience, Bangladesh was in the sixth lowest place after Sri Lanka, Malaysia, Pakistan,
Nepal, and Taiwan.
<Table 4-114. Experience of discrimination of Bangladesh : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
3.18

SD

88
11
1
1

3.09
3.80
4.75
2.75

0.99
0.95

75
26

3.16
3.25

0.99
1.09

79
7
3

3.10
3.82
3.75

0.98
1.04
1.15

30
7
14
36
6
8

3.29
3.21
3.20
2.86
3.79
3.69

1.05
1.06
1.08
0.94
0.95
0.78

74
6
10
1
6

3.01
4.54
3.43
4.00
3.00

0.97
0.29
1.01

* Lower score means more discrimination experienced

270

1.08

F

p

2.568

.059

.163

.687

2.254

.111

1.692

.144

3.979

.005

<Figure 4-102. Average of Bangladesh & others on Exp. of discrimination>(unit: points)* Lower score means more discrimination experienced

Gender role ideology
Table 4-115 provides the results of ANOVA of whether gender role ideology
varies depending on the personal variables of the Bangladeshi respondents. Whereas age
did not produce a significant difference, marital status resulted in a significant difference:
the group of single respondents (3.18) were significantly more progressive than themarried (2.73) (F=4.6308, p≤.034). The number of children was not associated with asignificant difference. In the meantime, researchers (3.59) proved most progressive, andteachers/professors (2.50) most conservative (F=3.828, p≤.003). The difference in termsof career interruption was significant as well. Regarding gender role stereotypes, therespondents who experienced interruption of less than one year expressed the mostconservative attitude, while most progressive attitude was observed among thoseexperiencing two to three years of interruption (F=2.740, p≤.033).
Figure 4-103 compares attitudes toward gender roles among the respondents in
Bangladesh and among respondents from the other countries. In the sub-scale of genderrole ideology, a higher score translates into a more progressive attitude toward genderroles. The average score of Bangladesh for gender role beliefs was 3.06 out of 5, whichmakes Bangladesh the third most conservative country after Pakistan and Mongolia.

271

<Table 4-115. Gender role stereotypes of Bangladesh : Demographic differences>(unit: person, points)

Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
3.06

SD

88
11
1
1

3.11
2.59
3.50
4.00

0.92
0.95

75
26

3.18
2.73

0.92
0.89

79
7
3

3.17
2.54
2.75

0.83
1.06
1.15

30
7
14
36
6
8

3.38
2.50
3.59
2.68
3.21
3.06

0.71
0.96
0.52
1.12
0.49
0.66

74
6
10
1
6

2.95
2.46
3.50
4.25
3.67

0.95
0.49
0.67

F

p

1.445

.234

4.630

.034

2.030

.138

3.828

.003

2.740

.033

0.38

* Higher score means more progressive<Figure 4-103. Average of Bangladesh & others on Gender role stereotypes>(unit: points)* Higher score means more progressive272

Career prospects
As can be seen in Figure 4-104, the respondents in Bangladesh demonstrated
relative optimism about their career prospects, with an average score of 4.37. This puts
the country in first place among all 12 countries.
<Table 4-116. Career outlook of Bangladesh : Demographic differences>(unit: person, points)
Classifications
Total
Age
29 or below
30~39
40~49
50 or above
Marital status
SingleMarriedOther
No. of childrenNone12
3 or above
Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

Cases
101

Average
4.37

SD

88
11
1
1

4.35
4.36
5.00
5.00

0.98
0.67

75
26

4.36
4.38

0.92
1.02

79
7
3

4.33
4.57
4.00

1.00
0.53
1.00

30
7
14
36
6
8

4.20
4.29
4.64
4.42
4.33
4.38

1.00
0.76
0.84
1.00
0.82
1.06

74
6
10
1
6

4.32
4.17
4.50
5.00
4.67

1.04
0.75
0.53

F

p

.299

.826

.013

.910

.387

.680

.444

.816

.403

.806

0.52

* Higher score means a more positive outlook

Table 4-116 provides the results of ANOVA of whether career prospects varydepending on the personal variables of the Bangladeshi respondents. No significant
difference in average score was observed for personal variables of age, marital status,
number of children, occupation, and career interruption.

273

<Figure 4-104. Average of Bangladesh & others on Career outlook>(unit: points)* Higher score means a more positive outlook

Policy demand
Table 4-117 provides the results of ANOVA of whether policy demand varies
depending on the personal variables of the Bangladeshi respondents. No significant
difference was found for variables such as age, marital status, number of children, andoccupation. In terms of the average score by occupation, policy demand was moststrongly reported by teachers/professors, and (excluding the other group) engineers had
the weakest policy demand; however, the difference was not statistically significant. The
variable of career interruption period resulted in varying policy demand. The averagescore for policy demand was highest among those with interruption of two to three years(5.00), followed by those with one to two years of interruption (4.40), those without any
interruption (4.30), and those with at least three years of interruption (4.17). The lowest
average belonged to those with less than one year of interruption (2.67) (F=4.238, p≤.003).
<Figure 4-105. Average of Bangladesh & others on Policy needs>(unit: points)* Higher score means higher needs for policy support274

As can be seen in Figure 4-105, the average for policy demand in Bangladesh
was 4.23 out of 5, which is fairly high. Compared with the other countries, however, thecountry is in only seventh place after Japan, Malaysia, Taiwan, Pakistan, Sri Lanka, andKorea.
<Table 4-117. Policy needs of Bangladesh : Demographic differences>(unit: person, points)

Classifications

Cases
101

Average
4.23

Total
Age
29 or below
88
4.27
30~39
11
3.73
40~49
1
5.00
50 or above
1
5.00
Marital status
Single75
4.25
Married
26
4.15
Other
No. of children
None
79
4.23
1
7
3.71
2
3
5.00
3 or above
Occupation
Student30
4.03
Teacher/professor
7
4.86
Researcher
14
4.71
Medical personnel
36
4.28
Engineer
6
3.83
Other
8
3.63
Duration of career break
None
74
4.30
Less than 1 year
6
2.67
1~2 years10
4.40
2~3 years
1
5.00
3 years or more
6
4.17
* Higher score means higher needs for policy support

SD

0.92
1.62

1.01
1.05

0.95
1.60
0.00

1.16
0.38
0.61
0.78
1.17
1.69
0.92
1.63
0.97

F

p

1.339

.266

.183

.670

1.823

.168

2.288

.052

4.238

.003

0.75

Gender equality
As can be seen in Figure 4-106, the Bangladeshi women agreed less strongly thanthe median level with the idea that full gender equality would be realized once women
were granted equal opportunity (average of 1.41; a lower score represents stronger
275

agreement). This places the country in the second highest rank after India. This suggests
that, compared with the other countries, those surveyed in Bangladesh strongly believedthat equal opportunity was sufficient to address the problem of gender inequality in thefield of science and technology.
<Table 4-118. Equality concept of Bangladesh : Demographic differences>(unit: person, points)
Classifications

Cases
101

Average
1.41

SD

88
11
1
1

1.40
1.55
1.00
1.00

0.65
0.93

SingleMarriedOther
No. of children

75
26

1.40
1.42

0.62
0.86

None
1
2
3 or above

79
7
3

1.44
1.29
2.00

0.67
0.49
1.73

30
7
14
36
6
8

1.27
1.71
1.50
1.39
1.50
1.50

0.58
1.11
0.52
0.77
0.55
0.53

74
6
10
1
6

1.41
2.00
1.40
1.00
1.17

0.68
1.10
0.52

Total
Age
29 or below
30~39
40~49
50 or above
Marital status

F

p

.388

.762

.022

.882

1.102

.337

.638

.671

1.388

.244

Occupation
Student
Teacher/professor
Researcher
Medical personnel
Engineer
Other
Duration of career breakNoneLess than 1 year
1~2 years
2~3 years
3 years or more

276

0.41

<Figure 4-106. Average of Bangladesh & others on Equality concept>(unit: points)

ANOVA was conducted to identify whether personal variables resulted in adifferent level of tendency among the respondents in Bangladesh to believe that equal
opportunity was a sufficient factor of gender equality (see Table 4-118). As a result ofanalyzing this belief according to respondents’ age, no statistically significant difference
was observed. Personal variables such as marital status, number of children, duration ofcareer interruption, and occupation did not produce a significant difference. The reasons
behind this lack of difference by personal variables are partially explained by the strong
belief in the concept of equal opportunity. In addition, the results were probably affectedby the disproportionate concentration of the respondents in terms of age and the numberof children.

277

278

5. Conclusion and Suggestions

5. Conclusion and Suggestions
Various international indices related to human resource development can besummarized as follows for APNN members. In terms of the Human Development Index(HDI) and the Gender Development Index (GDI) of the United Nations Development
Program, Australia, New Zealand, South Korea, and Japan all remain as countries with“outstanding” performance in human development, although these countries, except forAustralia, saw their ranks fall slightly from 2013. Meanwhile, Malaysia, Sri Lanka, andMongolia were among the countries with “excellent” human development performance,and Mongolia particularly climbed in rank from 103rd in 2013 to 90th in 2014, movingfrom the “average” to the “excellent” category. Vietnam and India remained in the“average” category, and yet they still climbed in rank from 121st and 135th in 2013 to116th and 130th in 2014, respectively. As new APNN member state that joined the APNN
last year, Bangladesh belongs to the “average” category. Nepal and Pakistan remained
quite the same as in 2013, classified as countries with “low” human development. In
particular, these two countries had less than five years of average training period. Korea
is ranked 17th for the HDI, while it is ranked 104th for the GDI, which means that thecountry’s women’s development (HDI 0.861) is substantially lower than its men’sdevelopment (HDI 0.926), despite the high overall HDI level. Considering that Korea’s
GDI ranked 85th in 2013, the 104th position in 2014 suggests a widened gap in menwomen development. Mongolia’s GDI value was larger than one, which means men’sdevelopment fell short of women’s development.
The UNDP’s Gender Inequality Index (GII) demonstrates that gender inequality
was significant in Bangladesh as well as in Nepal, Pakistan, and India. Korea’s GII ranked
23rd, slightly higher than that of Japan (ranked 26th), but the country’s maternal mortality
rate remained at the level of developing countries, with 27 deaths out of 100,000 births,
which is notably higher than the value of 6 out of 100,000 in Japan. Considering thedefinition of maternal mortality rate as “the annual number of female deaths per 100,000
live births from any cause related to or aggravated by pregnancy, childbirth, or related
complications, the statistics do not match the level of economic development Korea hasachieved. Since this can also be interpreted as a result of loopholes in social welfare policy
tailored for marginalized women, this result must be factored in when developing andimplementing policy related to women’s welfare in the future.
The Gender Gap Index (GGI) of the World Economic Forum in 2015 suggested
that New Zealand and Australia had no gender gap in educational attainment, ranking 1stin this section again after 2014. Meanwhile, New Zealand’s gender gap in politicalempowerment improved 39%; Australia improved only 19.3%. As a result, New Zealandranked 10th on the list, while Australia was far below in 36th place. Among the Asian
countries, most nations remained in the lower side of the GGI ranking, except for281

Mongolia in 56th place. Particularly, Mongolia and Sri Lanka took first place in healthand survival, but it is worth emphasizing again that this does not necessarily suggest thatthe people in these countries live longer and in a more healthy fashion than those in othercountries; rather, it suggests that each of these countries showed the less gap in values forhealth and survival for both genders. Japan, India, Nepal, Malaysia, Korea, and Pakistan
did not belong in the top 100 list for GGI ranking, and Malaysia, Mongolia, Japan, andKorea had particularly wide gender gaps in political empowerment. India’s GGI value inpolitical empowerment was 0.433, indicating the narrowest gender gap among the APNN
member nations.
According to OECD, Korea’s female labor-force participation rate rose from 55.6%
in 2013 to 57.9% in 2015, increasing at a higher rate than the OECD’s average rate ofincrease. However, the value was still lower than the OECD average by 5.1% point and27.6% point lower than Iceland’s average, resulting in Korea’s ranking 30th out of 34
countries in 2015. In Japan, the female labor-force participation rate increased from 65.0%
in 2013 to 66.7% in 2015. Although the gender gap was still large, the value is 8.8% point
higher than that of Korea, indicating that women’s economic activity was higher in Japan
than in Korea. The highest rate in labor participation for both genders was observed in
Iceland, constantly rising from 86.6% in 2013 to 87.9% in 2015. Unlike other countries,
the gap between men and women was extremely small in Iceland, with both genders
reaching a participation rate of over 80%. In addition to Iceland, all other Scandinavian
countries had a narrow gap between male-female labor-force participation rates and bothgenders participated in childcare based on highly flexible gender roles. Parental leave ismandatorily assigned to fathers as well as mothers, and wages were more likely to beretained during the period of parental leave. In Iceland, each parent must take five monthsof mandatory parental leave out of the 12-month leave, and the remaining two months
can be taken by either parent. The high labor-force participation rate and narrow gender
gap in Iceland evidently resulted from such policy support. Meanwhile, Japan and Korea
demonstrate a unique trend in which the gender gap tends to widen among more educatedpeople. Whereas the labor-force participation rate among more educated men
significantly rose to 95.6% in Japan and 92.4% in Korea in 2013, that among moreeducated women stood at 71.3% and 64.1% in Japan and Korea, respectively, only a slightincrease from the overall female labor-force participation rate. This trend further widened
the gender gap. For several years, Korea has recorded a lower labor-force participation
rate among more educated women than any other OECD member nation, which shows
Korea’s highly inefficient use of its labor force.
Following this analysis of the current status of international human resource
development, this study examined how personal variables affected perception or
experiences of gender barriers including the perception of gender discrimination, actual
experience of discrimination, and gender role ideology in women in the STEM fields in
282

APNN member countries. Furthermore, it explored how such gender barriers wereassociated with career prospects and policy demand as reported by women in science andtechnology. Analysis was conducted to observe the results encompassing all respondents
across nations and within individual nations, and to compare the results among nations.
From the viewpoint of recognizing discrimination, women in science andtechnology generally admitted that boys were more encouraged than girls to choose the
STEM fields; compared with men, women with the same abilities face greater difficultyfinding a job in the STEM fields; and women scientists have more difficulty than men
becoming full-time professors or managers in their societies.
Compared with the perception of the discriminatory experience, direct
experience of discrimination was reported less overall. The highest prevalence of
discriminatory experience was found in maintaining the balance between work and life
(marriage, family). The average scores were slightly below the median level forexperiences of discrimination or disadvantage in participating in research projects or
becoming research managers or in winning research grants or scholarships, or for sexual
harassment or other unfair treatment because of the gender.
Individual attitudes toward gender role stereotypes may work as internal genderbarriers. When measured in terms of gender role ideology regarding the role ofhousehold’s breadwinner, inherent ability to take care of children, and power relations
between wives and husbands, the respondents’ attitudes toward gender roles proved
slightly or relatively progressive. The only statement that drew a relatively conservative
attitude was that men and women should have respectively suitable jobs since men are
rational and women emotional.
The survey respondents overall held an optimistic view of future career prospects.
They also tended to believe that powerful policy support is necessary to address the
problem of gender inequality in the STEM areas. As a result of comprehensive multiple
regression analysis of the factors influencing policy demand by women in science andtechnology, it was revealed that the demand was higher among the respondents whobelieved in the importance of equal opportunity more strongly; who had more optimistic
views of their future career; who reported more discriminatory experience; and who held
more progressive attitudes toward gender roles.
If significant discrepancies exist in the distribution of the respondents by age,marital status, and occupation, it is difficult to draw out meaningful interpretations on the
differences found in gender barriers reported by women scientists and engineers in eachcountry through comparative analysis. In fact, the respondent profile varied greatly
among the countries. In terms of age, the average age of the respondents in Bangladesh
283was only 25.65, while that in Japan was 50.89. That was also the case with marital status.
In Malaysia, the single respondents accounted for 76.6%, the highest ratio, but those in
Vietnam accounted for only 1%. When classified into majors, engineering graduates
constituted an overwhelming share of 89.7% in New Zealand, whereas those in Japan
only accounted for 19.7%. Unlike the other countries, Bangladesh had the largest
proportion at 46.9% for medicine/pharmacy graduates, but social science graduates (35%)
were second only to engineering (39%) in Vietnam. Occupation also demonstrated asignificant disproportion. Although the respondents in New Zealand were
overwhelmingly engineers (85.3%), those in Vietnam were mostly teachers/professors(72%). In Korea, researchers accounted for 50%; healthcare/medical professionals
accounted for the largest share of 35.6% in Bangladesh.
For future surveys, allocation of a rough quota requirement for certain variables
such as age, marital status, and occupation is advisable, in the process of selecting survey
respondents in each country. Lastly, it is essential to conduct a parallel survey to collectobjective data and statistics on women in the STEM fields as well as to include studies
on supportive policy measures implemented in member countries, in addition to thesurvey on women themselves. A combination of such objective data and data obtained
through analysis of the awareness and experience of the respondents will lay a more solid
foundation for the development of an index system that can periodically examine thestatus of women scientists and engineers in each APNN member country.

284

References
Kong-Ju-Bock Lee & Jung Sun Kim (2014), 2014 Policy Report on Balanced Development of
Human Resources for the Future: UNDP HDI/GII and WEF GGI Status and Joint Survey of
INWES APNN Member Nations.
Association of Korean Woman Scientists and Engineers, International Cooperation Policy Research
Team (2015), The Glass Ceiling for Asian Women in STEM: The 2015 INWES APNN Joint
Survey Report.
Campbell, B., Schellenberg, E.G., & Senn, C.Y. (1997). Evaluating measures of contemporary
sexism. Psychology of Women Quarterly, 21, 89-102.
Glick, P., & Fiske, S.T. (1997). Hostile and benevolent sexism: Measuring Ambivalent sexist
toward women. Psychology of Women Quarterly, 21, 119-135.
Yang-hee Kim & Gyeong-ah Jeong (1999). Development of Korean-Style Assessment ofAwareness of Gender Equality. Korean Women’s Development Institute.
Ministry of Science, ICT and Future Planning (2015). Fact-Finding Survey of Use of Female
Workforce in Science and Technology in 2014. Korea Center for Women in Science,
Engineering, and Technology.
Morrison, A.M (1992). The New Leaders. San Francisco: Jossey-Bass. Morrison, A.M., White, R.P.,
Van Velsor, E. (1987). Breaking the Glass Ceiling. Reading, MA: Addison Wesley.
Lampe, A, (2001). Review of the book Gender in the Workplace: A Case Study Approach. Gender,
Work and Organization. 8(3), pp.346-351.
Davies-Netzley, S. A. (1998). Women above the Glass Ceiling: Perceptions on Corporate Mobility
and Strategies for Success. Gender and Society, Vol. 12, No. 3, p. 340
Federal Glass Ceiling Commission. Solid Investments: Making Full Use of the Nation's Human
Capital. Washington, D.C.: U.S. Department of Labor, November 1995.
Jong-tae Yun (2015). Necessity to Establish Busan Womenomics Center. Womenomics Center
Forum to Support Women in Science and Technology in Busan, held by Federation of Busan
Science and Technology and others. December 2015.
Ministry of Gender Equality and Family (2009). First Master Plan to Facilitate Economic Activityof Women Experiencing Career Interruption.
285

Eun-jin Oh (2015). ‘Current Status and Policy Issues of Re-Employment of Women Experiencing
Career Interruption: Seeking New Strategies in Response to Changing Policy Environment.’ 96th
Policy Forum on Gender Equality held by Korean Women’s Development Institute. Presentationmaterials. August 28, 2015.
MIT (1999). A Study on the Status of Women Faculty in Science286