The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.
The study used Havos AI machine learning models to extract information from each publication based on a series of modular questions. Graphical maps of the data provide policymakers and funders with a more nuanced view of the information available, which can help them to prioritize and coordinate international funding and research efforts.
This shift in thinking will require major shifts in policy, research, and investment. But where should these investments go? What foundations should be strengthened? Which gaps need filling? What’s working? What’s not?
In order to answer these questions in an...
The paper takes a critical look at two key interventions identified to deliver the PAEPARD capacity strengthening strategy. Firstly, the training of a pool of agricultural innovation facilitators (AIF) to broker relations between relevant stakeholders for the consolidation of effective...
In order to realize the potential of agricultural innovation in family farming, national priorities of sustainably increasing food production and productivity, and reducing hunger and poverty, require rural knowledge institutions to be stronger and communication processes to be improved. This...
Ce document analyse de façon critique deux interventions majeures identifiées pour mettre en œuvre la stratégie de renforcement des capacités de PAEPARD. La première intervention est la formation d’un vivier de facilitateurs de l’innovation agricole (FIA) pour assurer une médiation...
Undertaking Capacity Needs Assessment (CNA) is critical for organizing appropriate capacity development interventions. AESA organised four workshops on CNA of EAS in India, Sri Lanka, Bangladesh and Nepal with the following objectives.
1. Identify capacity gaps among EAS providers
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