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.

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.

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

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.

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

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

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

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

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

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

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