GenderUp in practice: Barriers and opportunities for responsible scaling in agricultural research for development

CONTEXT,To encourage agri-food system change, Agricultural Research for Development (AR4D) organizations emphasize the integration of gender and social diversity into innovation design and scaling, but translating these commitments into practice remains challenging. Although scaling decision support tools (SDSTs) look promising, research on their practical effects is limited.,OBJECTIVE,This study assesses GenderUp, a dialogue-based Scaling Decision Support Tool (SDST) designed to identify relevant social diversity, anticipate differentiated consequences, and adapt scaling strategies for equity, by (i) eliciting its underlying mechanisms of change through which it is expected to influence scaling processes and (ii) examining how and under what conditions it contributes to socially inclusive scaling.,METHODS,We adopted a realist evaluation approach—using document analysis, observations of a two-day GenderUp workshop, follow-up observations of 5 days-long project inception meetings one year and six months after the workshop, and interviews and focus group discussions with stakeholders across the value chain—to examine and test GenderUp’s elicited mechanisms of change in the context of scaling high-quality cassava peel (HQCP) mash technology in Nigeria.,RESULTS AND CONCLUSIONS,GenderUp triggered critical reflection enabling teams to identify diversity dimensions, articulate intersectional at-risk profiles, and revise scaling-strategy elements. However, donor requirements and consortium structures shaped the translation of insights into actionable strategies, enabling participation but constraining implementation of re-designed scaling strategies by prioritizing quantitative targets. Limited local representation meant that outcomes reflected national-level assumptions rather than local realities; and insufficient historical reflexivity left key barriers—e.g. feed adulteration—undetected.,SIGNIFICANCE,The study provides empirical insight into how SDSTs can advance inclusive scaling in AR4D and highlights key enabling conditions and methodological improvements such as: enhancing participant selection guidance, incorporating local cross-checking and information gathering , and engaging donors and consortium partners more explicitly. These can strengthen the contextual validity and institutional uptake of findings generated through tools like GenderUp.