UNESCO World Inequality Database on Education (WIDE)
- R Research Project/Report/Study
A Active
Key Information
Developed by the Education for All Global Monitoring Report, The World Inequality Database on Education (WIDE) highlights the powerful influence of circumstances, such as wealth, gender, ethnicity and location, over which people have little control but which play an important role in shaping their opportunities for education and life. It draws attention to unacceptable levels of education inequality across countries and between groups within countries, with the aim informing policy design and public debate. WIDE brings together data from Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), other national household surveys and learning assessments from over 170 countries. Users can compare education outcomes between countries, and between groups within countries, according to factors that are associated with inequality, including wealth, gender, and ethnicity and location. Users can also create maps, charts, infographics and tables from the data, and download, print or share them online.
Lead Implementing Organization(s)
Location(s)
Global
Activity URL
Government Affiliation
Non-governmental programYears
2010 -
Partner(s)
UNESCO Institute for Statistics, Global Education Monitoring Report
Ministry Affiliation
UnknownFunder(s)
Swiss Agency for Development and Cooperation
COVID-19 Response
UnknownGeographic Scope
Global / regionalMeets gender-transformative education criteria from the TES
UnknownAreas of Work Back to Top
Education areas
Attainment
- Post-secondary
- Primary completion
- Primary to secondary transition
- Secondary completion
Skills
- Literacy
- Numeracy
Cross-cutting areas
- Gender equality
Program participants
Other populations reached
Not applicable or unknown
Participants include
Not applicable or unknown
Program Approaches Back to Top
Women's empowerment programs
- Advocacy/action
Program Goals Back to Top
Education goals
- Education sector plans, budgets, policies, and data systems are more gender-equitable
- Gender parity and non-discrimination are promoted at all subjects/education levels
Cross-cutting goals
- Other