John Gargani , Petronella Chaminuka , Robert McLean
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引用次数: 0
Abstract
CONTEXT
Innovators want to scale the impact of innovations responsibly, but the meaning of “responsible” is elusive. It entails the high-level inclusion of stakeholders, but there is no agreed-upon standard that defines a “good-enough” level.
OBJECTIVE
Our objectives are to (1) provoke a conversation about what it means to scale the impact of agricultural innovations responsibly and (2) suggest dynamic evaluation as one way to promote responsible scaling because it facilitates the leadership of the people affected.
METHODS
Over 200 projects funded by IDRC to scale the impact of research for development in the Global South were reviewed. Research products were iteratively developed with Southern innovators and Northern funders who offered structured feedback.
RESULTS AND CONCLUSIONS
The dynamic scaling systems model is one research product. It can guide the people affected as they lead a process of “conjecturing” about scaling effects in complex settings. The resulting conjectures inform the dynamic evaluation of scaling, as well as planning and management. We illustrate the application of the model with a hypothetical and real example.
SIGNIFICANCE
Scaling is an integral part of agricultural innovation, and dynamism is an emerging concept that informs the evaluation, planning, and management of scaling. The dynamic scaling systems model supports the high-level inclusion of the people affected in ways that respect local knowledge and the risks associated with complex settings. It helps innovators scale more responsibly, even though the precise meaning of “responsible” remains elusive.
期刊介绍:
Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments.
The scope includes the development and application of systems analysis methodologies in the following areas:
Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making;
The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment;
Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems;
Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.