From complexity to clarity: A climate security vulnerability measure for policymaking
The CGIAR Focus Climate Security and The Alan Turing Institute’s Computational Social Science Group's collaboration addresses the need for a reliable and efficient approach to decision-making and policy development by developing an innovative analytical framework to construct a systemic measure that...
| Autores principales: | , , , , , |
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| Formato: | Blog Post |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/138452 |
| _version_ | 1855524530289639424 |
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| author | Liebig, Theresa Ines Guerrero, Omar Guariso, Daniele Craparo, Alessandro Carmelo William Basel, Ashleigh Taiwo, Ibukun |
| author_browse | Basel, Ashleigh Craparo, Alessandro Carmelo William Guariso, Daniele Guerrero, Omar Liebig, Theresa Ines Taiwo, Ibukun |
| author_facet | Liebig, Theresa Ines Guerrero, Omar Guariso, Daniele Craparo, Alessandro Carmelo William Basel, Ashleigh Taiwo, Ibukun |
| author_sort | Liebig, Theresa Ines |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The CGIAR Focus Climate Security and The Alan Turing Institute’s Computational Social Science Group's collaboration addresses the need for a reliable and efficient approach to decision-making and policy development by developing an innovative analytical framework to construct a systemic measure that analyzes structural features among key components of the climate security nexus, to support contextualized and climate security-sensitive decisions for policies, programs, or finance. |
| format | Blog Post |
| id | CGSpace138452 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| record_format | dspace |
| spelling | CGSpace1384522024-10-18T13:00:35Z From complexity to clarity: A climate security vulnerability measure for policymaking Liebig, Theresa Ines Guerrero, Omar Guariso, Daniele Craparo, Alessandro Carmelo William Basel, Ashleigh Taiwo, Ibukun climate change climate resilience data analysis frameworks measurement The CGIAR Focus Climate Security and The Alan Turing Institute’s Computational Social Science Group's collaboration addresses the need for a reliable and efficient approach to decision-making and policy development by developing an innovative analytical framework to construct a systemic measure that analyzes structural features among key components of the climate security nexus, to support contextualized and climate security-sensitive decisions for policies, programs, or finance. 2023-08-30 2024-01-25T09:50:11Z 2024-01-25T09:50:11Z Blog Post https://hdl.handle.net/10568/138452 en Open Access Liebig, T.; Guerrero, O.; Guariso, D.; Craparo, A.; Basel, A.; Taiwo, I. (2023) From complexity to clarity: A climate security vulnerability measure for policymaking. [Blog post] CGIAR News and Events. Published online 30 August 2023. URL: https://www.cgiar.org/news-events/news/from-complexity-to-clarity-a-climate-security-vulnerability-measure-for-policymaking/ |
| spellingShingle | climate change climate resilience data analysis frameworks measurement Liebig, Theresa Ines Guerrero, Omar Guariso, Daniele Craparo, Alessandro Carmelo William Basel, Ashleigh Taiwo, Ibukun From complexity to clarity: A climate security vulnerability measure for policymaking |
| title | From complexity to clarity: A climate security vulnerability measure for policymaking |
| title_full | From complexity to clarity: A climate security vulnerability measure for policymaking |
| title_fullStr | From complexity to clarity: A climate security vulnerability measure for policymaking |
| title_full_unstemmed | From complexity to clarity: A climate security vulnerability measure for policymaking |
| title_short | From complexity to clarity: A climate security vulnerability measure for policymaking |
| title_sort | from complexity to clarity a climate security vulnerability measure for policymaking |
| topic | climate change climate resilience data analysis frameworks measurement |
| url | https://hdl.handle.net/10568/138452 |
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