Multi-level Stakeholder Influence Mapping: Visualizing Power Relations Across Actor Levels in Nepal’s Agricultural Climate Change Adaptation Regime
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Sova CA, Helfgott A, Chaudhury AS, Matthews D, Thornton TF, Vermeulen SJ. 2014. Multi-level Stakeholder Influence Mapping: Visualizing Power Relations Across Actor Levels in Nepal’s Agricultural Climate Change Adaptation Regime. Systemic Practice and Action Research
Permanent link to cite or share this item: https://hdl.handle.net/10568/49619
Where power lies and how it is conceived in studies of governance and institutions is often not discussed. This is due to the ubiquitous nature of the topic. Power is shaped by a variety of institutional factors, including the architecture of governing structures, questions of scale and level, and access to key resources including knowledge and capital, among other factors. To date, there are relatively few tools available that allow policy makers, researchers, and development practitioners to render these power dynamics explicit and thus take steps to mitigate the potentially deleterious effects of power orientations. This paper proposes a methodology, multi-level stakeholder influence mapping (MSIM), for elucidating power dynamics between actors in complex system regimes. MSIM departs from existing power mapping techniques in that it relies on individual interviews conducted across multiple actor levels and utilizes a participatory mapping process for shared system boundary critique. MSIM was piloted in Nepal’s agricultural climate change adaptation regime with actors from the central, regional, and local operational levels. The results suggest that without proper consideration of the role of power in agricultural adaptation regimes, the resulting interventions will likely be insufficient in catalyzing adaptation pathways and moderating the negative impacts of climate change. Furthermore, power analyses produced from the perspective of a single actor level or respondent type can risk sub optimization of adaptation outcomes and can misdirect the lobbying efforts of those agencies utilizing mapping outputs.
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