Generating evidence on gender sensitive Climate-Smart Agriculture to inform policy in Central America: Final technical project report
Notice bibliographique
Résumé
The overall objective of this project was to support the scaling up of gender sensitive Climate Smart Agriculture (CSA) as a mechanism to increase resilience and improve livelihoods of vulnerable households in the face of climate-related impacts. Focused on two countries, Guatemala and Honduras, it aimed to generate science-based actionable information, tools and processed that support decision making by stakeholders at different scales, from farmers to subnational, national and regional levels. Its specific objectives were: To generate knowledge and understanding on the impact of specific CSA options on the livelihoods and food security as well as adaptive capacity of vulnerable households in two countries in Central America, (with a focus on different types of households and their intra-household gender dynamics) in a context of climate variability. To provide science-based evidence of the links between gender issues and adoption factors of CSA practices/technologies; both how gender issues1 relate to adoption of CSA and how adoption impacts on gender (in)equality. To increase households’/local level organizations' capacities to plan for and access, implement and monitor gender sensitive CSA interventions that increase climate and livelihood resilience. To feed science based evidence from local level into national and regional policy dialogue and provide specific recommendations to guide the design and operationalization of gender and socially inclusive CSA strategy recently formulated by Central America Agricultural Council. It’s designed was fully aligned to build on and support the ongoing efforts from the CGIAR program on Climate Change, Agriculture and Food Security (CCAFS) and its Learning Platform on Participatory evaluation of CSA practices and technologies. The value addition and specific focus on the project was to deepen our understanding of the gender dimension that can constrain and/or enable, increased adoption that benefits equity and leads to enhanced livelihoods, food and climate related security. Project activities and ouputs targeted four types of next users or beneficiaries: farming communities, local partners and institutions, national level organisations (namely Ministries of Agriculture) but also regional bodies such as the Central America Agricultural Council (CAC) and the Council of Ministers of Women of Central America (COMMCA). At local level, the project provided the perfect ground to implement a novel Monitoring tool that generated unique information on gender disaggregated adoption trends and perceived impacts of CSA practices on farmers’ livelihoods and gender indicators in the Climate Smart Villages of Olopa (Guatemala) and Santa Rita (Honduras). It also allowed to identify temporal and spatial changes occurring in those territories and generate new insights into specific trends associated with female farmers which appear to be increasingly been affected by higher levels of vulnerability. This work also provides context specific data on adoption typologies, enabling and constraining factors that will translate into research publications but most importantly, guide improved design of gender sensitive technical and policy related interventions in the region. Leveraging on the experience form the IDRC project, their involvement into the implementation of the Climate-Smart Village approach and the technical support from CIAT/CCAFS,the two local strategic partners submitted and got approved three gender sensitive scaling projects accounting for nearly 1 million USD. An emphasis was also put into capacity strengthening as pre-condition for empowerment and sustainability. With farmers, it aimed to improve their CSA planning and decision-making in the context of a changing climate, using innovative tools such an Economic Role Game co-developed with local partners. At subnational level, project outputs contributed to an undergrad course in the local university CUNORI and, at national level, they supported the development of 2 days seminar that fed into the curriculum of the Zamorano University Master program in Sustainable Tropical Agriculture (MATS). A way to saw a gender sensitive seed for future generations! Aware of the need to support and influence the policy environment another stream of work engaged closely with Agricultural Ministries and national level institutions from Guatemala and Honduras. The main objective was to respond to their demands in the context of the need to implement the regional CSA strategy for the SICA region and more specifically the strategic line: Facilitating mechanisms for integrating the equity principle and gender equality, as well as the intergenerational and social inclusion approach in CSA actions. A successful collaborative process led to the development of the practical guide Step-by-step process to mainstream gender in climate-smart agricultural initiatives made for Guatemala and for Honduras. This initiative was widely promoted through the regional network of CAC and COMMCA and contributed to increase the dialogue between those two bodies highlighting the importance of mainstreaming a gender sensitive component in the agenda of CAC’s Climate change and Integral Risk Management Technical Group. The project fueled also two important outputs a series on capacity building Webinars on Gender and CSA and the development of a roadmap to implement the strategic “gender line”3 of regional CSA Strategy. Policymakers and decision makers at both national and regional level have acknowledged the support provided by the project team, which has increased their capacities on gender and CSA.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,086 | 0,075 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,009 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,010 | 0,005 |
| Science ouverte | 0,004 | 0,011 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».