Year: 2026
Type: article
Abstract: Introduction Over 15 years of Climate-Smart Agriculture (CSA) practice have generated substantial investment in Agricultural Research for Development (AR4D), yet translating research outputs into sustained impact at scale remains one of the field's most persistent challenges. Social capital, understood as the trust, relational closeness, and social support among actors, has been identified as a key enabler of scaling processes, yet its treatment within climate-oriented AR4D has received limited systematic attention. This study addresses that gap by examining how scaling and social capital are reflected in the documented outcomes of the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). Conceptual basis Scaling is conceptualized through three interacting pathways: scaling out (reaching more people and places), scaling up (influencing institutions and policies), and scaling deep (transforming relational norms and practices), following Moore et al. (2015). Social capital is understood as a multidimensional relational resource encompassing trust, relational closeness, and social support, expressed through bonding, bridging, and linking ties. These frameworks are applied as interpretive lenses for reading thematic patterns, rather than as pre-specified categories imposed on the data. Methods Latent Dirichlet Allocation (LDA) topic modeling was applied to 273 CCAFS outcome reports covering 261 AR4D projects across 12 research programs from 2018 to 2021. The 17 topics identified were grouped into four thematic clusters: agricultural systems, climate change adaptation, climate change mitigation, and enabling environments. A document-level co-occurrence analysis assessed how frequently scaling and social capital themes appear together within the same outcome report. Results Scaling appears in only 1.8% of outcome reports and does so retrospectively as a reported result rather than as a planned process. Social capital terms are prevalent across the enabling environment cluster, appearing in 45.4% of reports, yet are rarely articulated as a distinct mechanism of change. Critically, only 0.7% of reports show meaningful co-occurrence of both themes. This near-absence is the study's central empirical contribution: it reveals a systematic disconnection between the relational conditions that enable scaling in practice and the way scaling is conceptualized and monitored in AR4D outcome reporting, pointing to concrete opportunities for programmatic and reporting redesign.
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDGs: Climate action, Zero hunger
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7214061539