Julian F. Gonsalves PhD.

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Propositions Resulting from the Social Learning

Stocktaking Exercise

Revised25 February 2013

The reformed CGIAR, especially the CRP structures are helping foster increased inter-center collaboration and cooperation among scientists.CRPs with increased funding is creating an environment favoring change

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The current AR4D focus with its emphasis on addressing poverty, food security, environment and climate change implies that it simply cannot be business as usual.

There is a consequently a new awareness of the diversity and complexity of the challenges. Complex problems need a knowledge intensive approach.

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A diversity of stakeholders (with different perspectives and sometimes competing interests) need to be engaged in order to deliver results in any AR4D approach.

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At the same time, there is an acute realization of the limited uptake of past research products and processes – resulting in a growing awareness of value for innovation platforms, alliances and partnerships.

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Somewhat related is the wider acceptance of the value, importance and legitimacy of doing research on issues related to upscaling and outscaling.

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We now increasingly focus on challenges characterized by multiple stakeholders with often divergent perspectives and competing goals.

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New work modalities and methodological innovations are needed in order to respond to these increasing complexities of partnership-based and trans-disciplinary research.

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New research modalities must recognize the value of bringing stakeholders across the RD spectrum with special attention devoted to strategic and purposive integration of the national research and rural advisory sectors.

AR4D cannot succeed without a genuine and empowering engagement of these national research sectors.

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Opportunities have grown for the inclusion of social learning in AR4D. Researchers might be engaged in social learning for different reasons. Hence the diversity of approaches. We need to grant that this accounts for a range of approaches.

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Though there are new opportunities for demonstrating the value of social learning approaches, 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 therefore rely on well demonstrated past models to build on its adaptive management work.

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BUILDING ON CG EXPERIENCES TO SHAPE SL APPROACHES FOR CCAFS CLIMATE CHANGE RESEARCH

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Social Learning for Climate

Change Research

Participatory Communications

(ICT, participatory video, etc.)

Participatory Plant Breeding, and

Participatory Varietal Selection,

Community Biodiversity

Management

Impact Pathway Approaches,

Horizontal Evaluation

Multi stakeholder dialogue

platforms

Farmer Field Schools/ CIALS

Innovation

Platforms

Participatory Market Chain

Analysis/Value

Learning

Alliances

Adaptive Collaborative Management, CBM,

and Co-Management and Conflict Resolution

Mechanisms

Gender analysis/ Gender

differentiation

Decision-based approaches eg.

Adaptation Pathways-WorldFish

J.F. Gonsalves 2012

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In a AR4D framework, a research related interventions are needed in at least three levels:•INDIVIDUAL FARMER LEVEL: Farmer engagement in diagnosis (PRA type) or in evaluating technologies, to more complex participatory breeding programs•COMMUNITY LEVEL: Community-based biodiversity management, adaptive co-management, co-management, etc.•MULTISCALE LEVEL: Innovation platforms, learning alliances, multistakeholder platforms, etc.

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Model Building for effective community engagement – of relevance to any adaptation work and 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 already 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 out-scaling at the higher levels have also been demonstrated through such approaches as Learning Alliances, Innovation Platforms and other related multistakeholder platforms.(http://webapp.ciat.cgiar.org/agroempresas/pdf/learning_alliances.pdf)

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In conclusion , key reminders are offered.

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Social learning in AR4D out of necessity implies frequent exposure and substantive interaction and learning with 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 is made at the community level engagement is undertaken. • Similarly upscaling and outscaling is contingent on

sound evidence generated locally.

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Optimism for the future:“ We are seeing better collaboration and

cooperation among centers than had been the norm over my long full time involvement with the CGIAR---so I’m cautiously optimistic about improved uptake of such approaches. I think the relevance certainly remains as high as ever”.

- Carol J. Pierce Colfer