julian f. gonsalves phd. 1 twelve propositions resulting from the stocktaking exercise draft for...

Julian F. Gonsalves PhD.

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Twelve Propositions Resulting from the

Stocktaking Exercise

Draft for DiscussionScience Meeting

March 2013

The reformed CGIAR, especially the CRP structures are helping foster increased inter-center collaboration and cooperation among scientists.

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The current AR4D focus with its emphasis on addressing poverty, food security, environment and particularly climate change implies that it simply cannot be business as usual and involving a diversity of stakeholders (with different perspectives and sometimes competing interests).

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A new demand for supporting social learning-related areas is naturally expected to arise.

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There is also an “all time high” awareness of the limited uptake of research products and processes – the gap between R & D, resulting in the wider promotion of partnership-based platforms directed primarily at demonstrating the relevance of an innovation perspective and aimed at enhancing research uptake/use.

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There is wider acceptance and bigger emphasis of the scientific community on the importance and legitimacy of doing research on issues related to upscaling and outscaling. Learning and participatory communication come “into play” in a bigger way.

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Methodological innovations and new work modalities are needed in order to respond increasing complexities of partnership-based and trans-disciplinary research required for better uptake. However, biases still characterize some of the work of some CG centers.

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New research modalities must recognize the value of bringing stakeholders across the RD spectrum with special emphasis on strategic and purposive integration of the national research sectors. AR4D cannot succeed without a genuine and empowering engagement of the national research sector.

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Resulting primarily from the CRP orientation, emerging partnerships, new work arrangements, ICT tools and related increased networking are providing new opportunities for demonstrating the value of social learning approaches. However, there is a risk that if this is not done in an organized, coordinated, reflective and consultative manner, these approaches will not have a lasting impact.

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The past should inform the future. The social and institutional issues associated with an AR4D in a changing climate contest are often not always new. There are similarities with past CG efforts in natural resources management research and collective action and pockets of work on participatory and adaptive management research, upscaling research, etc.

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CCAFs can indeed rely on well demonstrated past models to build on its adaptive management work.

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Models for effective community engagement – of relevance to any adaptation work – of relevance to any subsequent upscaling efforts are best developed through effective researcher engagement at the local level. The value of FFS, CIALs and ACM/Co-Management as relevant approaches for researchers to engage local communities has been proven.

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Efforts to address institutional issues associated with climate change can draw heavily from a rich and long tradition of research on collective action (http://www.capri.cgiar.org)

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Models for outscaling at the higher level have also been demonstrated through such approaches as Learning Alliances and other multistakeholder platforms. (http://www.capri.cgiar.org)

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A community of practice on areas related to social learning may be considered building on champions within each CRP.

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A compilation for wider sharing and promotion of the diverse range of field tested tools and past and current approaches, currently widely dispersed and remaining unknown to the wider community, would be a logical early step to take.

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Two key reminders are essential.

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Social learning in AR4D out of necessity implies frequent, equal exposure and substantive interaction to lower level stakeholders (e.g. communities, farmer groups).

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Social learning efforts are knowledge and time intensive – involving cycles of learning and reflection – and cannot be rushed. Social learning efforts are likely to generate “real” results at the local level only if adequate investment of time and effort in community level engagement is undertaken before upscaling is attempted.