1. Data coherence challenges in using gender responsive data for planning Case of Uganda
Presentation by
Uganda Bureau of statistics
24 February 2011, North Lawn Building, Conf. Rm D.

2. Introduction
Increased demand for gender statistics confirms that ‘gender’ is not only a social issue but also a development issue. Women and men experience life’s circumstances differently; i.e. culturally, socially, economically and politically. Without measuring the concerns regarding social roles and relationships, the magnitude of gender discrimination and inequality are a challenge to policy makers and society at large.

3. Gender Responsive Statistics
Producing gender statistics consists of:
(i) Sex-disaggregation of individual data to reveal the differences and inequalities between Women and Men, Girls and Boys;
(ii) collecting data on issues that show attributes, responsibilities, culturally assigned roles, opportunities and privileges for women and men, girls and boys. These reveal the gender relations

4. Gender Responsive Statistics (Contd)
collecting gender responsive data goes beyond merely disaggregating data by sex, it takes account of the power relationships between women and men; boys and girls.

5. Key Dimensions of Gender Responsive Statistics
Attributes – sex, age, children, elderly,etc.
Roles – Who does what?
Responsibilities – societal expectations
Opportunities – control over resources, time use, etc
Privileges – inheritance, mobility, entitlement, participation,etc

6. Scope of Gender responsive Statistics
Population composition and change
Household headship, Marital status and Fertility rates
Education and Literacy
Health services and nutrition
Agriculture
Economic activity and Labour force participation
Access (and ownership) to land, equipment and credit
Legal rights and access to justice
Violence (Including Gender Based Violence)
Participation in decision making and politics etc

7. Data gaps Lack of gender statistics on;
Some dimensions of disability, literacy, time use, rights, etc.
Key sectors of the economy like construction, energy, roads, etc
Lack of prioritised needs for gender responsive data by Users

8. Challenges
Use of proxies to measure different dimensions of gender relations e.g. awareness, equity, empowerment etc.
Conflicting gender concepts and definitions adopted by different stakeholders
Limited involvement of women in the definition of key frameworks

9. Challenges Inadequate gender responsive data management
Inadequate gender statistical infrastructure in the NSS eg. classifications, concepts, definitions and methods
Limited understanding and awareness about gender related issues
Ignoring non-Sex-disaggregated data that reveals gender issues like the time taken to fetch water

10. Way forward
Develop positions, arguments, messages and alternatives with empirical gender inequality evidence for;
Decision making, planning and resource allocation
Empowerment of women through capacity development
Resource commitment towards reducing the gender gap

11. THANK YOU