Gender inequality: Good with data, episode 4
In this bonus episode we explore gender inequality and the data and analysis needed to ensure that no women and girls are left behind.
In the first mini-series of Good with data we explore one of the most important issues in global development today, the Leave No One Behind Agenda; what it means, why it matters, and how we can make it a reality by improving data and making best use of existing data and evidence.
After concluding our three-part mini-series on the Leave No One Behind Agenda, our colleagues at Paris 21 got in touch and suggested we apply our data and data systems thinking to one of the oldest and most pervasive inequalities around the world – gender inequality. We thought that was a great idea, so they joined us for a bonus episode exploring this issue and the data and analysis needed to ensure that no women and girls are left behind.
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Our guests are:
- Fridah Githuku, Executive Director of GROOTS, a national movement of grassroots women-led community-based groups and Self Help Groups in Kenya.
- Emma Phiri, Gender Specialist at the Zambia Statistics Agency, a statutory body responsible for the publication of official statistics.
- Lauren Harrison, Data Ecosystems Lead at Paris 21, an organisation which promotes the better use and production of statistics to achieve national and international development goals.
For more on the subject of inequality including with respect to gender, our briefing paper explores the relationship between inequality and poverty and some key indicators and associated data issues. An accompanying factsheet draws on this data to summarise recent global inequality trends. Lastly, this report gives an overview of funding for gender equality and women and girls in humanitarian crises.
During the episode, we asked our panellists to share their recommendations for listeners to explore issues relating to gender inequality further:
- Fridah recommended publications from UN Women’s Women Count programme; GROOTS Kenya’s Gender Data Dashboard; Equal Measures 2030’s SDG Gender Index; and Paris 21’s work with national statistical offices.
- Lauren recommended exploring the Clearinghouse for Financing Development Data which includes information on funding for gender statistics, and the Gender Data Network, which aims “to raise the standard of gender data production to better link with demand, improve the effectiveness of communication of and about gender data, and encourage gender data use across participating countries.”
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Inequality: Good with data, episode 1
In this episode we discuss inequality; the focus of SDG 10 and an issue that has risen up the international development agenda in recent years. But it’s one thing to acknowledge the problem, and quite another to know what to do about it.
Inequality: Global trends
This factsheet presents trends and statistics that draw on a number of different datasets and use a variety of measures to understand the levels and trends of inequality.
Inequality, measuring it and why it matters for poverty reduction
This briefing explores the relationship between poverty and inequality, and shows that measuring, understanding and reducing inequality should be central to efforts tackle poverty, discrimination and exclusion.