Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report
On 1-4 October 2025, 42 representatives of National Agricultural Research and Extension System (NARES) Institutions—including researchers, policymakers, private-sector firms, and development professionals—gathered in Nairobi, Kenya, for a multistakeholder training workshop, on learning to apply the...
| Autores principales: | , , , |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/179068 |
| _version_ | 1855521278092378112 |
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| author | Mockshell, Jonathan Mosquera, Leslie Estefany Barungi, Julian Okonya, Joshua |
| author_browse | Barungi, Julian Mockshell, Jonathan Mosquera, Leslie Estefany Okonya, Joshua |
| author_facet | Mockshell, Jonathan Mosquera, Leslie Estefany Barungi, Julian Okonya, Joshua |
| author_sort | Mockshell, Jonathan |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | On 1-4 October 2025, 42 representatives of National Agricultural Research and Extension System (NARES) Institutions—including researchers, policymakers, private-sector firms, and development professionals—gathered in Nairobi, Kenya, for a multistakeholder training workshop, on learning to apply the Political Economy and Policy Analysis Artificial Intelligence (PEPA.AI) as a decision-support tool for political economy and policy analysis in agrifood systems.
The event was jointly organized by the Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), the Alliance of Bioversity International and CIAT (hereafter “the Alliance”), the International Food Policy Research Institute (IFPRI), and partners under CGIAR’s Policy Innovations Science Program and the Agroecology TRANSITIONS Private Sector Incentives and Investment project (PSII), led by Dr Jonathan Mockshell (the Alliance).
Under the auspices of ASARECA’s Comprehensive Africa Agriculture Development Programme (CAADP) ex-pillar IV (CAADP-XP4) Programme: Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) Project, and the Agroecological TRANSITIONS Program Private Sector Incentives and Investment (PSII) Project, and the CGIAR Policy Innovation Program. |
| format | Informe técnico |
| id | CGSpace179068 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1790682025-12-20T02:05:08Z Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report Mockshell, Jonathan Mosquera, Leslie Estefany Barungi, Julian Okonya, Joshua economic analysis policies agrifood systems artificial intelligence-ai (artificial intelligence) national agricultural research systems-nars On 1-4 October 2025, 42 representatives of National Agricultural Research and Extension System (NARES) Institutions—including researchers, policymakers, private-sector firms, and development professionals—gathered in Nairobi, Kenya, for a multistakeholder training workshop, on learning to apply the Political Economy and Policy Analysis Artificial Intelligence (PEPA.AI) as a decision-support tool for political economy and policy analysis in agrifood systems. The event was jointly organized by the Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), the Alliance of Bioversity International and CIAT (hereafter “the Alliance”), the International Food Policy Research Institute (IFPRI), and partners under CGIAR’s Policy Innovations Science Program and the Agroecology TRANSITIONS Private Sector Incentives and Investment project (PSII), led by Dr Jonathan Mockshell (the Alliance). Under the auspices of ASARECA’s Comprehensive Africa Agriculture Development Programme (CAADP) ex-pillar IV (CAADP-XP4) Programme: Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) Project, and the Agroecological TRANSITIONS Program Private Sector Incentives and Investment (PSII) Project, and the CGIAR Policy Innovation Program. 2025-12-19 2025-12-19T14:47:57Z 2025-12-19T14:47:57Z Report https://hdl.handle.net/10568/179068 en Open Access application/pdf Mockshell, J.; Mosquera, L.E.; Barungi, J.; Okonya, J.; (2025) Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report. 12 p. |
| spellingShingle | economic analysis policies agrifood systems artificial intelligence-ai (artificial intelligence) national agricultural research systems-nars Mockshell, Jonathan Mosquera, Leslie Estefany Barungi, Julian Okonya, Joshua Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title | Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title_full | Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title_fullStr | Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title_full_unstemmed | Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title_short | Building the capacity of National Agricultural Research Systems in applying PEPA.AI for evidence-based agrifood policy analysis: Training workshop report |
| title_sort | building the capacity of national agricultural research systems in applying pepa ai for evidence based agrifood policy analysis training workshop report |
| topic | economic analysis policies agrifood systems artificial intelligence-ai (artificial intelligence) national agricultural research systems-nars |
| url | https://hdl.handle.net/10568/179068 |
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