Transcript Propositions Resulting from the Social Learning Stocktaking Exercise

Revised
25 February 2013
Propositions Resulting
from the Social Learning
Stocktaking Exercise
Julian F. Gonsalves PhD.
1
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
2
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.
3
A diversity of stakeholders (with different
perspectives and sometimes competing
interests) need to be engaged in order to
deliver results in any AR4D approach.
4
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.
5
Somewhat related is the wider acceptance of
the value, importance and legitimacy of doing
research on issues related to upscaling and
outscaling.
6
We now increasingly focus on challenges
characterized by multiple stakeholders with
often divergent perspectives and competing
goals.
7
New work modalities and methodological
innovations are needed in order to respond to
these increasing complexities of partnershipbased and trans-disciplinary research.
8
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.
9
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.
10
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.
11
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.
12
CCAFs can therefore rely on well
demonstrated past models to build
on its adaptive management work.
13
BUILDING ON CG EXPERIENCES TO SHAPE SL
APPROACHES FOR CCAFS CLIMATE CHANGE RESEARCH
Participatory Plant
Breeding, and
Participatory Varietal
Selection, Community
Biodiversity
Management
Participatory
Market Chain
Analysis/Value
Participatory
Communications
(ICT, participatory
video, etc.)
Multi
stakeholder
dialogue
platforms
Decision-based
approaches eg.
Adaptation
PathwaysWorldFish
Social Learning
for Climate
Change Research
Innovation
Platforms
Farmer Field
Schools/ CIALS
Gender analysis/
Gender
differentiation
Learning
Alliances
J.F. Gonsalves 2012
Adaptive Collaborative
Management, CBM,
and Co-Management
and Conflict
Resolution
Mechanisms
14
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, comanagement, etc.
• MULTISCALE LEVEL: Innovation platforms, learning
alliances, multistakeholder platforms, etc.
15
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.
16
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)
17
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/p
df/learning_alliances.pdf)
18
In conclusion , key reminders are offered.
19
Social learning in AR4D out of necessity
implies frequent exposure and substantive
interaction and learning with lower level
stakeholders (e.g. communities, farmer
groups).
20
• 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.
21
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
22