GENDER DIMENSIONS
Dr Lawrence Ikamari
Population Studies and Research Institute
University of Nairobi
likamari@uonbi.ac.ke
1
Outline of the Presentation






Objectives of the presentation
Introduction: Definitions & importance of gender
disaggregated data
Gender dimensions in key demographic
parameters
Gender dimensions in education and labour force
Gender dimensions in disability
Concluding remarks
2
Objective of the Presentation

Goal: The purpose of the Session on Gender
Dimensions is to enable the participants to appreciate
the importance of taking gender dimensions into
account in development planning at all levels and to
equip the participants with the knowledge and skills
on how to carry out analysis of Census Data from
different gender perspectives.
3
Objective of the Presentation
At the end of the session participants will be able to:
 State the rationale for gender disaggregated data
 Describe the key gender concepts
 Describe how to prepare data for gender analysis.
 Describe how to carry out gender analysis
 Describe how to present gender disaggregated data
4
Introduction: definitions
Key Concept in Gender Perspectives
• Gender
• Sex
• Gender Analysis
• Gender relations
• Gender issues
• Women issues
• Gender inequality
5
Introduction: definitions
Key Concept in Gender Perspectives
• Gender Parity Index
• Gender Gaps
• Gender Development Index (GDI)
• Gender aware planning/gender mainstreaming
6
Introduction: definitions

Gender
Gender is a socio-cultural construct of the society that
determines the identity, roles or obligations/duties,
and entitlements of women and men and girls and
boys in the society. It therefore defines women and
men’s position in their society. Gender classification
changes with time, space and needs of a society
7
Introduction: definitions

Sex
Sex is a biological identification of females and males
based on their physiological characteristics. Sex
characteristics are natural and determined during
conception; compared to gender which identifies
qualities that are shaped through the history of social
relations and interactions in society
8
Introduction: definitions of concepts

Sex ratio
Sex ratio is the number of males per 100 women,
and is sometimes also referred to as the gender ratio
9
Introduction: definitions

Gender relations
Gender relations are social-cultural relationships
between men and women in a given society. They are
socially constructed and not derived from biology.
Gender relations distinguish social relations between
men and women from those characteristics which can
be derived from biological differences
10
Introduction: definitions


Gender inequality
Gender inequality means unequal access to resources
and benefits by women and men and therefore holds
back the growth of individuals in society
Gender gaps
Gender gaps refer to the differences between women
and men in relation to their participation in and benefits
from different socio-economic sectors. Gender gaps
come about as a result of unequal power relations
between women and men and between boys and girls
11
Introduction: definitions

The gender gap measures the magnitude of disparities and
is normally computed in percentage points or the difference
between percentage for females and percentage for males.
Gender Parity Index
Gender Parity Index (GPI) is a socioeconomic index usually
designed to measure the relative access to education for
both females and males. It is calculated as the ratio of the
number of female students enrolled at primary, secondary
and tertiary levels of education to the number of male
students in each level
12
Introduction: definitions

Gender analysis
This is the process of examining roles and responsibilities
or any other situation in regard to women, men, boys and
girls, with a view to identifying gaps, raising concern and
addressing them, investigating and identifying specific
needs for policy and programme development and
implementation
13
Introduction: definitions

Gender-Aware Planning
This is the process of taking gender into consideration
(gender mainstreaming) in development planning;
planning with women/girls and men/boys in mind.
14
Introduction: definitions


Gender issues
Gender issues refers to opportunities, challenges and
constraints that affect both women, men, girls and boys
in the society. Gender issues are not synonymous with
women’s issues
Women’s issues
Women issues refer to opportunities, challenges and
constraints that affect women/girls only
15
Rationale for Gender disaggregated data

International and national commitment to promote gender
equality and women empowerment
• Many international conventions and instruments such as CEDAW,
•
•

Beijing Platform for Action, and the United Nations Universal
Declaration of Human Rights
ICPD 1994 Plan of Action
Millennium Development Goals
Enactment of various laws and policy frameworks, and set
up several bodies at national and lower levels in order to
advance, coordinate and monitor Gender issues. E.G;
16
Rationale for Gender disaggregated data
• Provision of Freed Education
•
•
•
•
•
Affirmative action in recruitment, employment appointment in
public service
Development of the development of a National Policy on Gender
and Development;
the establishment and strengthening of institutions to address
Gender issues (including National Commission on Gender and
Development)
Gender units in all line Ministries and state corporations
Inclusion of an indicator on Gender mainstreaming in the
Performance Contract Guidelines in the public sector
17
Rationale for Gender disaggregated data
• the
•
Political Parties Act (2007) provides for at least one third
representation of either Gender in political parties
the Employment Act of 2007 prohibits termination of employment
on account of pregnancy and provides for three months maternity
leave and two weeks of paternity leave with full pay
• The New Constitution
• Has several provisions for affirmative action
• Vision 2030
• aims at providing high quality of life to all citizens by the year 2030
18
Rationale for Gender disaggregated data
• Lack
of gender disagregated data at the various planning
levels
19
3: Gender dimensions

Gender dimensions by key demographic
parameters
o
Population age and sex
20
Methodology


In the 2009 Kenya Population and Housing Census
Questionnaire, the information on Gender was
captured using question (P-11) on the gender of
members of the household where, 1=Male and
2=Female
There are two approaches to measuring Gender
gaps. First is the incident approach where the
denominator is the total female or male in a
particular sector
21
Population distribution by age
and sex
Data required:
 Population distributed by a specified age group (e.g. 5 year
group, 0-14, 15-24, 15-64, 65+ and by sex (either absolute
or percentage)
 Population distributed by a specified age group (e.g. 5 year
age group, 0-14, 15-24, 15-64, 65+ by sex and by province
(either absolute figures or percentages)
Method:
Then graph the figures using a bar chart using excel
22
Population distribution by age and sex, Kenya, 2009
75++
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
3,000,000
2,000,000
1,000,000
0
Male
1,000,000
2,000,000
3,000,000
Female
23
Percentage distribution of population distribution aged 0-14
years by sex and province, Kenya, 2009
Female
Male
Percent
54.3
50.7
49.3
50.5
50.5
49.5
49.5
49.7
50.8
50.6
50.3
50.2
49.8
49.4
50.1
49.2
49.9
45.7
KENYA
NAIROBI
CENTRAL
COAST
EASTERN
NORTH
EASTERN
NYANZA
RIFT VALLEY
Province
24
WESTERN
Percentage distribution of population aged 15-24 by
sex and province, Kenya 2009
53 47 51 49 52
Pe rcent
59
51 49 56
51 49 53
50
50
47
44
41
Province
Female
Male
25
48
Percentage of the population aged aged 65+ by
Sex, Kenya: 2009
26
Population distribution by marital status and sex
Basic measures of marriage:
 Marital status: Percentage distribution of the
population by current marital status classified by sex
and other attributes of interest
 Singulate Mean Age at Marriage (SMAM): This is an
estimate of the average number of years lived in a
single status by those who ever marry before age 50. A
high SMAM therefore means a later age at first
marriage
(Show formula for calculating SMAM)
27
Population distribution by marital status and sex,
Kenya, 2009
28
Singulate Age at First Marriage






1962: SMAM: 18.5 years
1969: SMAM: 19.2 years
Male: 25.1, Female: 19.2
1979: SMAM: 20.2 years
Male: 25.3, Female: 20.2
1989: SMAM: 21.6 years
Male: 26.0, Female: 21.6
1999: SMAM: 22.3 years
Male: 26.5, Female: 22.3
2009: SMAM: 26.5 years
Male: 26.7, Female : 22.5
29
Trends in the singulate mean age at marriage, Kenya,
1989-2009 Census Data
Age group
1989
Female
15-19
20-24
25-29
30-34
35-39
40-44
45-48
1999
Male
Female
2009
Male
Female
Male
81.2
35.3
15.8
9.0
6.3
5.1
4.1
97.9
79.1
38.3
14.4
8.6
6.9
6.1
81.2
38.0
21.0
11.3
8.0
5.8
4.8
97.1
77.1
41.3
16.4
8.6
5.6
4.8
84.4
41.4
21.0
12.2
9.1
7.4
6.4
96.8
79.6
41.7
18.2
9.8
6.7
4.9
21.6
26.0
22.3
26.5
22.5
26.7
Total
30
Trends in the singulate mean age at marriage
(SMAM), Kenya and by Province; 1999-2009
Census Data
Province
1999
Female
Nairobi
Central
Coast
Eastern
Nyanza
Rifty Valley
Western
Kenya
2009
Male
Female
Male
23.5
23.7
21.3
23.1
20.5
20.9
26.8
27.5
26.7
27.2
26.5
25.4
23.7
23.2
22.0
22.9
21.8
21.4
26.8
27.8
26.7
27.7
27.1
25.5
22.1
26.3
22.4
26.7
22.3
26.5
22.5
26.7
31
Singulate Mean Age at Marriage (SMAM) by Sex and
Province, Kenya 2009
32
Infant and under mortality by sex
Measures of mortality are desirable disaggregated by sex and
other attributes of interest. These can be obtained using indirect
methods using QFIVE software. This requires basic data
• Number of children ever born classified by 5 year group of
mother and sex
• Number of children dead classified by 5 year group of mother
and sex
• Number of women aged 15-49 classified by 5 year group
33
Life expectation at birth by sex and province, Kenya:
2009
34
Gender Dimensions in Education
Data required:
•
•
School attendance among the population aged at
least 3 year classified by a specified age group, sex
and other attribute of interest
Educational attainment among the population aged
at least 3 years classified by a specified age group,
sex and other attribute of interest
35
Percentage of the population by school
attendance status by sex, Kenya: 2009
36
Percentage distribution of the population aged at
least 3 years by school attendance, sex and ruralurban residence
37
Percentage of the population attending school
by age and sex, Kenya: 2009
38
Percentage of population age at least 3
years by sex, Kenya: 2009
39
Percentage of the population with no
education by sex, residence and province,
Kenya: 2009
40
Percentage of the population with
completed primary education by sex,
residence and province, Kenya: 2009
41
Percentage of the population with at least
secondary education by sex, residence and
province, Kenya: 2009
42
Gender dimensions in Labour
force
Data required:
• Economic activity among the population aged 5
years and above classified by sex and attribute of
interest
43
Percentage of the population age at least 5 years
by sex and economic status, Kenya, 2009
44
Percentage of the population age at least 5 years
by sex, economic status, rural-urban residence,
Kenya, 2009
45
Percentage of the population by age, economic status
and sex, Kenya: 2009
Ag e
Group
Total
Total
W ork i ng
Unempl oyed
Inacti ve
W omen
M en Gender W omen
M en Gender W omen
M en Gender W omen M en Gender
Gap
Gap
Gap
Gap
50.5
49.5
1.0
46.7
53.3
-6.6
46.8
53.2
-6.4
56.0 44.0
12.0
5-9
49.3
50.7
-1.4
47.5
52.5
-5.0
0.0
0.0
0.0
49.7
50.3
-0.6
10 - 14
48.8
51.2
-2.4
46.1
53.9
-7.8
0.0
0.0
0.0
49.6
50.4
-0.8
15 - 19
49.1
50.9
-1.8
47.4
52.6
-5.2
47.0
53.0
-6.0
50.1
49.9
0.2
20 - 24
53.7
46.3
7.4
50.0
50.0
0.0
49.1
50.9
-1.8
63.7
36.3
27.4
25 - 29
52.5
47.5
5.0
46.7
53.3
-6.6
47.5
52.5
-5.0
83.4
16.6
66.8
30 - 34
50.4
49.6
0.8
45.0
55.0
-10.0
44.6
55.4
-10.8
87.8
12.2
75.6
35 - 39
50.3
49.7
0.6
45.4
54.6
-9.2
43.9
56.1
-12.2
88.1
11.9
76.2
40 - 44
49.9
50.1
-0.2
45.4
54.6
-9.2
41.4
58.6
-17.2
87.0
13.0
74.0
45 - 49
50.3
49.7
0.6
46.1
53.9
-7.8
42.3
57.7
-15.4
86.6
13.4
73.2
50 - 54
50.1
49.9
0.2
45.6
54.4
-8.8
41.8
58.2
-16.4
82.2
17.8
64.4
55 - 59
49.6
50.4
-0.8
45.4
54.6
-9.2
42.5
57.5
-15.0
73.3
26.7
46.6
60 - 64
50.2
49.8
0.4
45.5
54.5
-9.0
45.7
54.3
-8.6
70.9
29.1
41.8
65+
54.4
45.6
8.8
48.1
51.9
-3.8
52.6
47.4
5.2
68.0
32.0
36.0
46
Percentage of distribution of employed population
(15-64 years) by sex and province, Kenya, 2009
47
Percentage of the employed population by age, sex
and economic activity, Kenya: 2009
Age
Group
15 - 64
15 - 19
20 - 24
25 - 29
30 - 34
35 - 39
40 - 44
45 - 49
50 - 54
55 - 59
60 - 64
Worked for Pay
Own/ Family business
Gender
Gender
Women Men
Gap Women Men
Gap
27 44
-17
21 18
3
23 23
-1
15 14
1
32 47
-15
20 16
4
32 52
-19
24 19
5
29 50
-21
25 21
4
27 48
-21
24 20
4
25 46
-21
22 20
3
22 44
-22
21 18
2
18 40
-21
19 18
1
13 30
-18
18 18
-1
9 22
-13
16 18
-2
Own/ Agriculture
Business
Gender
Women Men
Gap
50 36
14
61 61
0
46 35
11
41 27
14
44 28
16
46 30
17
50 32
18
55 35
20
61 40
21
68 49
18
73 57
15
48
Gender Dimensions in Disability
Data required:

Percentage of PWD by sex and attribute of
interest
49
Percentage distribution of PWDs by Sex,
Kenya: 2009
Sex
Number
%
Female
682,651
51.3
Male
647,715
48.7
Total
1,330,366
3.5 (of total
population)
50
Percentage of the PWDs by sex and rural-urban residence,
Kenya: 2009
51
Percentage of PWDs by type of disability,
Kenya: 2009
Type of Disability
Visual
Hearing
Speech
Physical
Mental
Self Care
Others
Total
No of PWDs
331,593
187,816
161,798
337,212
136,095
76,547
99,305
1330366
% PWD by domain
24.9
14.1
12.2
25.3
10.2
5.8
7.5
100
52
Percentage of PWDs by school attendance
status and sex, Kenya: 2009
53
Percentage of PWDs by type of disability,
school attendance and sex, Kenya: 2009
Currently Attending Previously Attended
Never Attended
DK
Gender
Gender
Gender
Gender
Type of
Disability Female Male Gap Female Male Gap Female Male Gap Female Male Gap
Visual
25
23
2
29
27
2
25
21
4
19
17
2
Hearing
20
19
1
11
10
1
15
15
0
16
13
3
Speech
17
18
-1
9
9
0
7
12
-5
12
16
-4
Physical
18
20
-2
28
31
-3
25
25
0
22
22
0
Mental
9
9
0
9
12
-3
9
14
-5
13
16
-3
Self-care
2
2
0
4
4
0
13
5
8
16
10
6
Other
9
8
1
10
7
3
6
4
2
5
5
0
54
Percentage of PWDs by education attainment
and sex, Kenya: 2009
55
Proportion of PWDs by economic Activity,
Sex, residence and province, Kenya: 2009
Working
Unemployed
Inactive
Province/
Gender
Gender
Gender
Residence Female Male Gap
Female Male Gap
Female Male Gap
Kenya
53
58
-5
6
7
-1
41
34
6
Nairobi
49
63
-14
10
9
1
40
28
13
Central
49
54
-6
4
5
-1
47
40
7
Coast
45
56
-11
7
9
-2
48
35
13
Eastern
48
55
-7
5
6
-1
46
38
8
North
Eastern
49
57
-8
16
18
-2
33
23
10
Nyanza
59
59
0
5
5
0
36
36
1
Rift
Valley
51
59
-8
6
7
-1
42
33
9
Western
60
61
-1
4
5
-1
35
34
2
Total
53
58
-5
6
7
-1
41
34
6
Rural
55
59
-4
5
6
-1
40
34
5
Urban
45
57
-12
9
9
0
45
33
12
PeriUrban
50
54
-4
6
7
-1
43
38
5
56
Appendix 1: Relevant ICPD & MDGS
ICPD & MDGS whose implementation and
monitoring require gender disaggregated data
57
A SUMMARY OF ICPD GOALS FOR 2015




Achieve universal access to and completion of primary
education, ensure the widest and earliest possible access by girls
and women to secondary education and higher levels of
education.
Provide universal access to full range of safe and reliable family
planning methods and related reproductive health services.
Reduce infant mortality to below 35 infant deaths per 1000
live births and under five mortality rates to below 45 deaths per
1000 live births
Close the gap in maternal mortality between developing and
developed countries. Aim to achieve a maternal mortality rate
of below 60 deaths per 100,000 live births.
58
A SUMMARY OF ICPD GOALS FOR 2015 CTD.
Increase life expectancy at birth to more than 75 years. In
countries with the highest mortality, aim to increase life
expectancy at birth to more than 70 years.
Sources:
• United Nations Population Fund 1994: Programme of
Action of the International Conference on Population
and Development.
• United Nations 1994. Report of the International
Conference on Population and Development , Cairo, 513 September 1994.

59
MILLENNIUM DEVELOPMENT GOALS




1 Eradicate extreme poverty and hunger
Halve, between 1990 and 2015, the proportion of people whose income is less
than $1 a day.
Halve, between 1990 and 2015, the proportion of people who suffer from
hunger.
2 Achieve universal primary education
Ensure that, by 2015, children everywhere, boys and girls alike, will be able to
complete a full course of primary schooling
3 Promote gender equality and empower women
Eliminate gender disparity in primary and secondary education preferably by
2005 and in all levels of education no later than 2015
4Reduce child mortality
Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate
60
MILLENNIUM DEVELOPMENT GOALS CTD.



5 Improve maternal health
Reduce by three-quarters, between 1990 and 2015, the maternal mortality ratio .
6 Combat HIV/AIDS, malaria, and other diseases
Have halted by 2015 and begun to reverse the spread of HIV/AIDS
Have halted by 2015 and begun to reverse the incidence of malaria and other major
diseases
7 Ensure environmental sustainability
Integrate the principles of sustainable development into country policies and program
and reverse the loss of environmental resources.
Halve, by 2015, the proportion of people without sustainable access to safe drinking
water
Have achieved, by 2020, a significant improvement in the lives of at least 100 million
slum dwellers .
61