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Foresight for income and employment: What can we learn for agricultural research for development

Author

Listed:
  • Kruseman, Gideon
  • Dermawan, Ahmad
  • Diagne, Mandiaye
  • Enahoro, Dolapo
  • Frija, Aymen
  • Gatto, Marcel
  • Gbegbelegbe, Sika
  • Komarek, Adam M.
  • Mausch, Kai

    (World Agroforestry (ICRAF))

  • Mottaleb, Khondoker

Abstract

Challenges related to poverty, hunger, nutrition, health, and the environment are widespread and urgent. One way to stress the urgency of making the right decisions about the future of the global food systems now is to better understand and more clearly articulate the alternative scenarios that food systems face. Developing, synthesizing, and presenting such alternatives to decision makers in a clear way is the ultimate goal of e CGIAR Foresight team. No single source of information focuses regularly and systematically on the future of food and agriculture, and challenges facing developing countries. Our work aims to fill that gap with a focus on agricultural income and employment. group systematically collects information about past, on-going and planned foresight activities across CGIAR centers and their partners, spanning the global agricultural research for development arena We present a comprehensive overview and synthesis of the results of relevant foresight research, which through the tagging with metadata allows for customized investigations in greater detail. The cross-cutting nature of this work allows for a more comprehensive picture and assessments of possible complementarities/trade-offs. Potential users of this report and associated activities include CGIAR science leaders and scientists as well as the broader research community, national and international development partners, national governments and research organizations, funders, and the private sector. The approach developed by the CGIAR foresight group is used to make foresight study results accessible across organizations and domains in order to aid policy and decision makers for strategic planning. The approach allows visualization of both the available information across multiple entry points as well as the identification of critical knowledge gaps.

Suggested Citation

  • Kruseman, Gideon & Dermawan, Ahmad & Diagne, Mandiaye & Enahoro, Dolapo & Frija, Aymen & Gatto, Marcel & Gbegbelegbe, Sika & Komarek, Adam M. & Mausch, Kai & Mottaleb, Khondoker, 2021. "Foresight for income and employment: What can we learn for agricultural research for development," SocArXiv 783rw_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:783rw_v1
    DOI: 10.31219/osf.io/783rw_v1
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