INNOVATION

Empowering Women in Agriculture

The potential of women in agriculture in Africa remains largely untapped due to systemic obstacles and economic constraints to full women
inclusion in the agricultural development process. With the conviction that African women are crucial to agricultural transformation, for growth
and sustained development in Africa, women representative from the 55 organizations of the Gender is my Agenda Campaign (GIMAC) network,
coordinated by Femmes Africa Solidarité (FAS), have mobilized to address this challenge and have put together an innovative, action-oriented
strategy called Empowering Women in Agriculture Initiative (EWA), bringing together public-private partnerships, international organizations

active on the continent along with civil society. The EWA initiative, launched on the sidelines of the 19th AU Summit in 2012 aims to implement strategic capacity-building programs in key areas to support women farmers and maximize their crucial role in the sector by promoting their equitable access to key resources (land, finance, technology), thus improving their livelihoods and their contribution to sustainable development in Africa. Since his inception a series of activities have been undertaken to move the EWA initiative forward. Some of the achievements of the initiative include:

This year, the programme was focused on coordination, partnership building, and resource mobilization. A High-Level Breakfast Meeting
on the initiative Empowering Women in Agriculture (EWA) will take place in Addis Ababa, Ethiopia in January 2018, on the margins of the 30th African Union Summit. On this occasion, space will be provided to EWA rural women in Agri-business to present and showcases good models and practices in their sector. This activity will bring Head of States of the 9 pilot countries, partners, as well as women farmers in order to strengthen the EWA Champions Platform in sharing the progress made, revitalizing the strategies to build partnerships, and promoting potential women business models in agriculture

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