Realizing Inclusive SAI: Contextualizing indicators to better evaluate gender and intergenerational inequity in SAI processes and outcomes - Cases from Southern and Western Africa
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Zulu, L., Djenontin, I.N.S., Darkwah, A., Kamoto, J., Kampanje-Phiri, J., Fischer, G., Grabowski, P. and Egyir, I. 2020. Realizing Inclusive SAI: Contextualizing indicators to better evaluate gender and intergenerational inequity in SAI processes and outcomes–Cases from Southern and Western Africa. International Journal of Agricultural Sustainability
Permanent link to cite or share this item: https://hdl.handle.net/10568/109101
Despite increasing sustainable agricultural intensification (SAI) investments, indicators for detecting gender and intergenerational inequities in SAI costs and benefits sharing often remain overgeneralized, theoretical, or locally irrelevant. We examine the relative value of, and how to, customize standard SAI indicators to detect such inequities in specific socio-cultural contexts to enhance data collection for evidence-based decision making in fostering gender/youth inclusive SAI. Using focus-group discussions and key informant interviews among farmers and diverse government, NGO, private sector, and academic stakeholders in two districts in Malawi and three in Ghana, we assess the perceived roles, differentiated needs/ priorities of men, women and youth, and the sharing of SAI burdens and benefits within farming households. We investigate what context-appropriate questions to ask, to whom, and how, to collect reliable information on indicators of SAIinvestment inequities. Results illuminate context-specific, gendered and intergenerational factors shaping access to and ownership of productive resources, household decision making, SAI participation, and appropriateness of selected indicators. Combining farmers’ and local field-expert’ perspectives offers practical insights for customizing inequity indicators. Findings highlight advantages of local contextualization of SAI indicators, including insights on appropriate data-collection approaches that challenge orthodox survey/quantitative methods for detecting and assessing gender/age inequities to foster inclusive SAI.