CCAFS+Science+meeting+2013

= CCAFS-ILRI Workshop 'Achieving more impact through connecting, engaging and learning with communities and other key actors' = toc 18-19 March 2013 Bodega Bay Lodge, Davis, CA

**Objectives**

 * To showcase past and on-going participatory work and experiences from CCAFS and the wider CGIAR
 * To develop ways in which participatory (social learning) approaches could inform and improve current and future CCAFS work

[[image:ccsl/IMG_5316.JPG width="320" height="424" align="right"]]
See the results of the and read the.

**Participants**

 * List of participants
 * [[file:Additional Information on Participants_18Mar13.doc|Additional information]] about participants (based on profile survey sent to all participants prior to the meeting)

**Documentation**
The official meeting documentation is available in the notes below the agenda.
 * Blog posts** written in relation to this workshop:
 * Cultivate the future! How learning together can mean learning better and faster-speeding…
 * Farmers and scientists: better together in the fight against climate change
 * Transformative partnerships for a food-secure world
 * The world’s ‘wicked problems’ need wickedly good solutions: Social learning could speed their spread
 * Climate change and agricultural experts gather in California this week to search for the holy grail of global food security

The **whiteboard video** 'Transformative partnerships for a food secure world', which was showed for the first time during the CCAFS science meeting is available ** here **.

=**Agenda**=

The 2013 Science Meeting runs from the afternoon of 18 March and all day on 19 March.

**Monday 18 March - Understanding New Ways of Approaching SLOs to Effect Behavioural Change**

 * **Time** || **Session** || **Objectives / outputs** ||
 * 14.00 || Welcome and Director’s introduction (Bruce Campbell) || Explain the objectives of the workshop and how it fits in CCAFS overall strategy ||
 * 14.15 || Introduction of the agenda and participants (Ewen Le Borgne) || Get to know each other, surface assumptions and expectations and to create a friendly atmosphere ||
 * 15.00 || System level outcomes, intermediate development outcomes and the behavioural changes CCAFS is looking to effect (Phil Thornton) || Explain how the theme of social learning fits under the overall picture with IDOs and SLOs ||
 * 15.15 || //Coffee break// ||  ||
 * 15.45 || Introduction of the (full) CCAFS social learning narrative (Patti Kristjanson) || Give a comprehensive overview of the rationale and opportunities behind social learning in climate change work. ||
 * 16.15 || Social learning research experiences in CGIAR/CCAFS or otherwise, building upon participants' own experiences (Ewen Le Borgne) || Introduce the first part of Julian Gonsalves stock take of social learning that highlights the long tradition of social learning within CGIAR ||
 * 17.15 || Teasing out key opportunities (and constraints) of these experiences to affect behavioral change || Develop a good understanding of where we stand (in CCAFS) and where we think there are opportunities to exploit. ||
 * 17.45 || Close ||  ||

== Tuesday 19 March - Working Towards Ways of Integrating Social Learning into Ongoing Activities ==

Participation and social learning in the CGIAR (Ewen Le Borgne) || Welcome to Day 2 and reiterate today's process Complete the presentation from Day 1 and let participants have a look at various suggestions of social learning approaches that CCAFS might want to invest in. || >
 * **Time** || **Session** || **Objectives / outputs** ||
 * 08:30 || Introduction and Recap of Agenda for Day 2 (Wiebke Foerch)
 * 08.45 || Ongoing CCSL opportunities and social learning activities (bus stop): sandbox, social differentiation, local innovation, timescales, M&E of social learning || To highlight the depth of work that CCAFS has already done in climate change and social learning (i.e. processes followed and preliminary results) and explore how CCAFS group might invest further in social learning. ||
 * 09.15 || Conversation: what could be potential areas for investment in social learning || Take stock of all work done so far and getting a sense of where CCAFS might want to go with social learning, in current initiatives and beyond ||
 * 09.45 || //Coffee break// ||  ||
 * 10:15 || rallel sessions organized and chaired by resource persons
 * [[file:ccsl/CCAFS Science meeting 2013_SideSession_JVEtten-ANewsham.docx|Vulnerability and safety nets]] (J. van Etten & Andy Newsham)
 * [[file:CCAFS Science meeting 2013_SideSession_MRufino.docx|Assessing impacts across scales: mixing methods to frame research questions on the future of households and communities]] (M. Rufino) combined with... [[file:ccsl/CCAFS Science meeting 2013_SideSession_SRidaura - ELB - AJC.docx|The response of agricultural systems to climate and integrated assessment across spatial scales]] (S. Ridaura et al.)


 * [[file:CCAFS Science meeting 2013_SideSession_PEricksen.docx|Developing metrics to evaluate the impact of adaptation interventions across food systems on food security, livelihoods and ecosystem services]] (P. Ericksen)


 * [[file:CCAFS Science meeting 2013_SideSession_TRosenstock_16Mar13.doc|Scalable technologies and practices: Identifying transferable climate-smart technologies for donor investment]] (T. Rosenstock)


 * [[file:CCAFS Science meeting 2013_SideSession_CJackson.docx|Connecting, Engaging and Learning with CCAFS Innovators]] (C. Jackson and E. Le Borgne) || To explore in depth current initiatives to improve the development impact of climate change and agricultural research. Topics were solicited from all CCAFS Centre Contact Points and CCAFS team members during January 2013 ||
 * 13:00 || //Lunch break// ||  ||
 * 14:00 || Parallel sessions: feedback ||  ||
 * 14:30 || Focused conversation in regional groups:
 * How to achieve SLOs and IDOs better using social learning approaches, generally?
 * Where can social learning help the CCAFS themes in the regions __concretely__?
 * What are initial steps to take and early wins along the way?
 * Scaling social learning up and out

For non-CCAFS group:
 * How should CCAFS __concretely__engage with other networks and organizations to reach the potential of social learning:
 * In the CCAFS regions?
 * Globally, around specific themes? || To connect social learning with IDOs/SLOs, and develop and prioritize strong ideas on how social learning could concretely take shape and support ongoing or upcoming work ||
 * 15.45 || //Coffee break// ||  ||
 * 16.15 || Feedback about the focused conversations || Get a collective sense of direction in using social learning across CCAFS regions ||
 * 16.45 || Final collective reflections about the theme, the event and the personal experience || Collect final impressions about what was achieved with the event ||
 * 17.45 || Close ||  ||

Clouds of change - initial remarks, questions and expectations about this agenda
The 'clouds of change' (based on 'river of life' exercises) are available here:
 * Serendipity of how each came to climate change
 * We are here to learn about social learning
 * Making use of social information unbiased
 * What is a sandbox?
 * Learning how participatory and social learning overlap?
 * We are climate aware since 1974!
 * It's about how to get science into use

Reflections about social learning enablers and barriers

 * || **Enablers** || **Barriers** ||
 * **1** || * Champions (group of people), farmers, politicians & scientists
 * Exposure / working together in field / immersion
 * Creating dialogue / spaces to share knowledge
 * Feeding back results / returning results
 * Doing together / not just workshops but using info
 * Technology which helps engage / contribute / learn (e.g. telephone)
 * Well balanced teams with recognition of importance of distinct roles (more social scientists) || * Losing lessons learned and institutional memory (lessons & knowledge being lost)
 * Big male egos!! Closed-mindedness
 * Disciplinary silos
 * Not recognising cultural/religious issues related to access to information
 * Not just one way of doing research but acknowledging all types of knowledge / brokering ||
 * **2** || * Clear purpose
 * Good definitions of scope
 * Use of exclusion and inclusion
 * Inclusion of divers knowledge --> demand-driven, research --> implementation
 * Importance of facilitated and mediated processes
 * Empowerment and positive feedback
 * Context-specific (understanding context properly is a real enabler) || * Power status __can__ be a barrier
 * Knowledge gained from one elite group might not transfer easily
 * Cognitive abilities vary so much
 * Champions / gatekeepers
 * Ideology (SL is a __methodology__, not an ideology) ||
 * **3** || * We know a lot of tools
 * We appreciate what we are already doing
 * Empowerment
 * We always do it: fundamental good practice
 * Clarifying role(s) of research
 * ?? understanding how you learn and apply it
 * Identify networks and social channels
 * Facilitator
 * Spectrum
 * Extreme events
 * Food security
 * Urgency?
 * Regional / geographic focus
 * Intention || * Power embedded
 * Transaction costs & need for a long time
 * Need to know when to use social learning
 * Linear delivery models
 * Confusing social learning as a tool AND an outcome
 * Do we know what SL looks like?
 * High level goal of institutional change
 * Can we visualise the level of behavior change needed under uncertainty?
 * Spectrum
 * What is the compelling narrative related to extreme events?
 * Urgency?
 * Intention ||
 * **4** || * Diverse views (1+1=3)
 * Equal access to knowledge and reciprocity
 * Empowerment / long term relationships based on mutual understanding and trust
 * Frequent / equal exposure and interaction with lower level stakeholders || * Complexity
 * Missing right channels and well tailored products
 * Lack of understanding of the context
 * Bridging partnerships
 * Resources: time, money, structures ||
 * **5** || * Communities understand that climate is changing and has positive impact on agriculture
 * Social learning makes research a dynamic process
 * SL promotes ownership of processes at all levels
 * CRPs (CGIAR research programs) serve as platforms for complementarities and synergies for SL
 * Technology and tools (ICT) provide opportunity for social learning || * Some communities do not understand that climate is changing
 * Whether all actors will be involved continuously and sustainably
 * Cost element for having more actors
 * Lack of capacity
 * Complex power strata may block SL
 * Difficulties in implementing all views - need to do some sorting and prioritizing
 * Complexity in coordination ||
 * **6** || * Local champion
 * Learning loops
 * Participation
 * Partnerships
 * Open access
 * Well established extension systems
 * Process of coming to common understanding can help unify people + lead to practical solutions
 * Embrace unpredictability
 * Openness to possible solutions || * Linear research
 * Power structures and politics
 * Disconnect between information supply and demand
 * Information is not like knowledge
 * Too much information
 * Different understanding of concepts (related to process of coming to common understanding in left column)
 * Rigid outcome orientation could prevent innovation and learning
 * Too many views can complicate decision making ||
 * **7** || * Partnerships
 * Stakeholder engagement (facilitation)
 * Honest dialog
 * Breaking hierarchies
 * Appreciate what farmers (or others) are doing
 * Finding and supporting key people to spread information (but not making them the gatekeeper)
 * Acknowledge the importance/value of working with stakeholders
 * Lots of opportunities - horizontal transmission
 * Linking SL to knowledge exchange
 * Having general principles but not necessarily detailed plans (about the process)
 * Personal reflections to system-level reflections of the process
 * Institutional credibility of SL
 * Common language || * No common definition of social learning
 * Lack of evidence base (does it lead to transformation?)
 * Lack of understanding (scientists need to understand the public)
 * Differences in priorities (farmers vs. climate change scientists)
 * Differences in scales + what is important to different actors / participants
 * No feedback loops
 * Time & effort
 * No clear problem or methods (conceptual framework)
 * Different groups, backgrounds, understandings (finding common ground) - right people with interests
 * Dis-incentives (CG centres)
 * The term 'social learning'
 * Scaling up:
 * Changing roles
 * Power relationships
 * Attribution may diminish
 * Learning together vs. capacity building (that can put people at higher + lower levels)
 * Hierarchies ("lower levels") ||
 * __Public commentary about enablers and barriers to social learning__**:
 * Polly: Barrier: Embracing social learning and doing it well: are we able to visualize the level of behavioral change that’s needed to adapt to climate change given that it under uncertainty? Why grow bananas over potatoes and vice versa given x levels of precipitation, y temperature, etc.?
 * Andy N: Barrier: We could use social learning around why people grow potato instead of banana in changing climate. People prioritize uncertainty.
 * Aden: There can be social learning on the limitation of collecting information on whether climate changing or not.
 * Sonja: Humans are the barriers to social learning.
 * Vanessa: Although often we’re constraint by a lack of common understanding of underlying issues. The process of arriving at common understanding can contribute to unifying people and to the solutions.
 * Beare: Social learning has achieved its goal: many people in the planet know that smoking is harmful to their health but they still smoke. Achieving social goals doesn’t mean that expected outcome(s) are achieved.
 * Michael victor: Access to knowledge: How can people access the knowledge that scientist have? Since social learning is about behavioral change, our behavior (as scientists) also needs to change. It’s not a one-way communication.
 * Jennifer: Appreciating that these barriers are at different levels and that we’re all learning together.
 * Tegan: Important to understand the power barriers that exist and an opportunity to shape the group to know who is making decisions and who is not.
 * Mark Lundy: Important to understand the incentives and disincentives in our organizations around creating spaces for social learning.
 * Michael: Barriers: One of the biggest constraints is male egos. 1 or 2 people can spoil social learning process, mostly men 
 * Marc Schut: Focusing too much on rigid outcomes constraints the flexibility of social learning.
 * Boru: Enabler: Clarifying different roles that research has in social learning in order to understand how research and joint inquiry resulting in a joint process to lead to social learning. Clarify what the research piece of social learning in the CG is.
 * Roberto: As in the example of smoking being harmful to one’s health, hard evidence and picture evidence is important for social learning.
 * Aden: Social learning is not good by itself; it needs to be an operational system where goods and services are delivered.
 * Polly: Internalizing social learning. We as researchers do a lot of social learning already so we need to appreciate what we’re already doing.
 * Lini: Important to have a geographic hub – let’s have communities of practice (floating/structured spaces to enhance a community sense).
 * Unidentified: Social learning outlines the importance of common climate spaces’ excluding and including strategies.
 * Joost: Social learning is a platform to respond to power differences.
 * Andy N: Beware of the power structures that allow people to say what they want, could go too far.
 * Jacob: Social learning is not only about procedure; it is also about goal orientation, improvement and includes basic principle and moral dimension (ex. human rights). It helps in understanding and shaping context to bring transformation in relationships, and includes social science. It informs how to shape the social learning process.
 * Alain: Social learning informs decision makers on how to engineer it so that its substantial section is existential.
 * Ann: Social learning is happening, it is important to identify the best point for the CG to make its inputs to make this happen.
 * Michael: We’re often reinventing the terms, the institutional memory and learning within the CG that social learning is lost within what the role of CG is versus that of the NGO.

Feedback about the [|whiteboard video 'Transformative partnerships for a food secure world]'
Nuances are difficult to put in a 5' video. It's interesting to test what other organisations and particularly NGOs would think about it. The video took 10-12 people to contribute to the message and to focus. There are 47 versions of the narrative.
 * ** Positive ** || ** To improve ** ||
 * * It is inspirational!
 * It's useful to explain climate change to farmers (with some adaptation) as they might be recognising themselves.
 * 60% of the people here would share this video
 * It's a good conversation starter
 * It's great for schools!
 * The visual linking the continents reinforces the messages of the video
 * It's good for our partners to know better || * What is CCAFS trying to address?
 * This is not targeted enough and it seems costly
 * The California meeting shouldn't be mentioned
 * It seems like a lot of work for a small targeted group (the scientists in this meeting)
 * It lacks a motivational message for the next level (e.g. elaborate more on who learned, in an example)
 * In CGIAR need, therer is a prior need to motivate engagement on climate change itself
 * Our social learning reality is about conflict and that is not included in this video
 * It should focus on what we can do better ||

.

Parallel sessions
==== (J. van Etten & Andy Newsham) - See the  ====

City governments often more conscious of climate change than are national governments. Tools being developed for local governments to analyse what causes vulnerability at local level, what needs to be taken into account in local-level planning? With GIZ, IDS was involved in a multi-scale vulnerability analysis in Mexico in a biological corridor to set up a coherent agenda for conservation and ecosystems-based adaptation. It was working at local level, facilitating vulnerability analysis at three sites. It developed a toolkit for primarily qualitative vulnerability analysis. Bioversity and IDS are collaborating in translating and adapting this for the CCAFS context, to be tested in CCAFS benchmark sites. The project will work in East Africa and India; the field sites have not yet been narrowed down.
 * Intro**:

Vulnerability definition: IPCC 2007. The comment was made that this definition is focused on climate change but we should be looking at vulnerability more broadly.

IDS is doing a review of similar types of tools, e.g. exploring food security aspects, which can be used by local governments.

The toolkit explores the ecological and social dimensions of vulnerability. It describes for non-specialists how to do vulnerability analysis using participatory visual methods, to use the analysis process to change what local participants do. The focus is on livelihood adaptation strategies. It consists of a sequence of methods that feed into each other: transect walks, spoken maps, seasonal calendars, wellbeing ranking using local categories, semi-structured interviews, key informant interviews, Venn diagrams. Perceptions of change are explored through two timeline exercises: 1) a timeline mapping big changes in the community; climate impacts come into this; and 2) a timeline showing general trends, and including exploration of how local communities have adapted to change, e.g. growing two crops of maize per year because no freezing in winter. These trends could be taken forward into planning future adaptation. The toolkit includes a matrix showing which methods are most suitable for which purposes, e.g. for understanding governance.


 * Issues raised**:
 * Time and skills needed: The exercise need eight researchers working for one week, but fewer people could also do it over several weeks, working with local NGOs and students.
 * The toolkit has not yet been used for monitoring changes in levels of vulnerability over time.
 * How to connect local perceptions of climate change with scientific knowledge? It is difficult to disaggregate farmers’ response to climate-related and non climate-related changes.

Context: Central Uganda, 2.5 h from Kampala, village with elementary school, some people working on own land, some wage labourers working on other people’s land, some people working for the local government, some migrating to Kampala to work.
 * Group exercise: seasonal calendar**

//**Assignment of roles**//:
 * Jenny: woman farmer, whose husband migrates to Kampala
 * James: landless male working on commercial farm; wife does petty trade
 * KPC: male farmer on own land
 * Joost: woman teacher
 * Iannis: 12-year-old female student in elementary school; father smallholder, mother petty trade
 * Jakob: big landowner, mayor, has 200 head of cattle
 * Tegan: man who migrates to Kampala in dry season to do construction work, spend wet season drinking in village; wife does some farming
 * Robert: male priest and traditional healer
 * Andy: female health worker
 * Alain: migrant from elsewhere charcoal dealer and honey producer (non-timber forest products); no land rights

//**Brainstorming on sources of livelihoods in village**//: various field crops, horticulture, livestock-keeping, NTFPs, farmer labour, small-scale retailing, civil servant, off-farm labour, migrant labour, local food processing (see flipchart).

**Comments while making partial seasonal calendar (see flipchart)**:
 * No difference in seasonal work for commercial and smallholder maize, as no irrigation, but differences in amount of investment
 * No seasonality in growth and harvest of plantains but seasonality in work on crop protection; heavy work in preparing holes for new plants before the main rainy season
 * When commercial farmer/landowner is spending money, e.g. on crop protection measures for which labour needs to be hired, the labourers are earning money
 * Because of such differences within the community, it is difficult to make a seasonal calendar reflecting an average at community level; the average may reflect something that does not exist
 * In livestock, the parasite load increases during the wet season; male offspring are likely to be sold to pay for school fees; seasonality in production and earning from sales is higher in the case of milk compared with animals/meat
 * The exercise revealed the complexity of assessing livelihood sources
 * Using such participatory assessment tools gives everyone insight, is important for capacity building at community level and stimulates social learning
 * Seasonality is a good entry point for discussing and tackling climate change
 * During such exercises, there may be a problem that people keep up appearances and it will not be easy to find out about illegal activities such as smuggling or prostitution


 * Assessment of usefulness of this tool**:
 * Structural way to tease out information on the agricultural system
 * Gives baseline about how climate is linked to household-related activities
 * Can be related to how climate is likely to change and to see how climate change is likely to have an impact on livelihoods
 * Can be combined with future climate scenarios; local-level vulnerability analysis could help with identifying some of indicators
 * Provides a record of extreme weather events over time
 * Should be linked with historical weather data – what happens in the short term may not be what happens in the long term; need to identify the “game changers” that influence development
 * May be useful to make seasonal calendars for good and bad years
 * Can lead to discussions about the adaptive capacities people are already using
 * Similar toolkits are already being used within CCAFS, e.g. the IUCN toolkit used in West Africa.

**Next steps**: Andy will summarise what comes out of this session, will collect and share information about different toolkits and tools that can be used as local level or vulnerability analysis, using email addresses of all participants in this group.

__ Impact across scales __
==== (M. Rufino) combined with...  (A. Challinor, S. Ridaura et al.) ====
 * Provide examples of climate resilient farming activities
 * Learn from farmers' historical knowledge (social learning element)
 * Continue to collaborate on cross-scale thinking.
 * Put a visual face to scenarios so we can better communicate with different stakeholders (social learning element)

//No summary made available yet by this group//.

--
==== (P. Ericksen) ====

Polly walked through the food systems framework used by the GECAFS project, in order to explain to the group how a such a framework helps in tracing causal pathways among drivers of change, food system activities, and food system outcomes. Next she outlined the standard “adaptation intervention” design approach of vulnerability assessment followed by adaptation intervention followed by an impact assessment. Next she discussed the difference between process and outcome indicators and asked her main question:
 * Intro**:

“How can we use indicators to promote learning about adaptation?”

She highlighted that many adaptation projects either 1) stimulate adaptation interventions or deliver adaptive actions or 2) enhance adaptive capacity.

She gave an example of how one could use the food systems approach to identify the food security outcome of interest, then understand how climate change will affect this, and then design the necessary adaptive action.

**Discussion**:

We found that thinking of the outcome pathways as testable hypotheses helped.

We then discussed topics that “CCAFS needs” Setting indicators comes last, after you know your outcomes and the pathway to get there.
 * 1) First we talked about indicators within the CGIAR CRP reporting framework and agreed that the SLOs are IMPACT; the IDOs are outcomes, and that we need some sort of process indicators measured on an annual basis to help us monitor our progress towards the IDOs.
 * 2) Adaptive capacity? What is successful adaptation? CCAFS IDO 1 looks for the “ability to innovate and find solutions”.. we can measure this looking at novelty, interactions and networks, and the selections or choices actors make (reference the “innovation ecologies” approach of the AAS CRP. Monitor whether these choices are leading to positive or negative adaptation…. We can develop an index for these short term outcomes. What about the longer term? How about using narratives? Most significant change?
 * 3) Using M&E to foster adaptive management: Allow for learning and change, using the outcome pathway and adjusting if your indicators go “off target”. We need to make sure we have outcome pathways that are long enough to see the change we want. Also we discussed that often the fast variables are the easier to measure/ monitor, but we also have to connect to the slower change variables eventually. Know where we are in the process.

--

[[file:CCAFS Science meeting 2013_SideSession_TRosenstock_16Mar13.doc|Scalable technologies and practices: Identifying transferable climate-smart technologies for donor investment]] (T. Rosenstock)
This session seeks to define the characteristics of scalable climate-smart technologies, design a decision support system that can help identify them, with greater certainty, for donor investment, and determine the challenges for creating a system under CCAFS.

IFAD ASAP investment design:
 * Presentation by IFAD: Prioritizing and targeting investments in Climate Smart Technologies (Gernot Laganda)**


 * Understand climate problems, current and projected (countries already know this from their national communications to UNFCCC)
 * Define the vulnerability baseline in the target area
 * Devise “multiple benefit” actions to reduce vulnerability
 * Establish M&E framework
 * Measure the benefits of climate finance

How does research input come into play in this process?
 * Big picture analysis (econometric analysis, cost benefit analysis)
 * Baseline information (who is vulnerable and where) comes into play in designing the project concept. Remote sensing makes obtaining the biophysical info a bit easier, but socioeconomic is a bit harder to come by.
 * Technical expertise comes into play in designing the project document (i.e. the design mission)
 * Technical expertise, technology transfer, evidence for policy, impact analysis comes into play in project implementation
 * Analyzing impact – what value was created for the investment

Most donors have a structure in place where they try to plug in research expertise and know-how in certain aspects of the project cycle. IFAD’s question is where can they plug in CCAFS knowledge

How are countries perceiving climate finance working through existing donor support? (e.g. the ASAP program)
 * Questions for Gernot**
 * Sometimes countries just see it as extra money that they can use to do what they were already doing (e.g. intensifying rice)
 * Donors who are providing the money need it to go to vulnerability reduction, so generally it starts from a very climate-aware place


 * Discussion on where CCAFS can fit in to the donor project design model (e.g. IFAD ASAP design):**
 * We already do this
 * Rather than regional platforms for implementing, regional platforms for learning and improving would be relevant
 * Gernot: What would be most useful for IFAD is a list of 30 experts in particular fields/regions that IFAD can approach when designing projects to ask for baseline information or opinion on projects that countries are designing. People who understand the institutional situation/context in the country and also know a lot about the particular technology. Right now, this depends too much on the project design team being clued in/networked (left to chance). It’s not institutionalized as part of the project. Using google scholar is very time consuming. What would be better is like a “brokerage” help desk where IFAD could go to get CCAFS information.
 * Maren: Need to look at what we already have.
 * How can CGIAR centers be part of the initial country programme formulation? (in the IFAD investment design)
 * This could be someone being involved for the whole project design, or just informing at various points along the way, but the desire is that it be somehow systematic.

Interesting points coming out of this:
 * 1) Broadening scope of this effort- not just a database/stocktaking, but the idea of having a broker/linking people
 * 2) Incorporating climate finance into traditional ag finance models could be an interesting lesson for regional banks and World Bank
 * 3) Need to make sure that these programs are actually delivering something to the donors
 * 4) Overall, how can CCAFS coordinate itself to inform climate finance? Not just in IFAD, but elsewhere? Robust and available tools and knowledge


 * Notes from 2 breakout sessions to discuss how to move forward:**


 * Group 1**
 * We want to avoid becoming a “consultant” for donors and losing our impact pathway
 * Ideal would be to get involved at the beginning, during the country programme development
 * CCAFS’s comparative advantage is to convene information and look at it in an unbiased way, so that projects aren’t just being based on the preferences of one person. There is a potential to put together a database on what we know about certain technologies. But the end goal is how to support decisions- a multi-criteria decision support tool.
 * Not clear what all donor user groups want- need more information on this (list of experts? Database of tools? What types of info are available?) A focus group with climate donors (e.g. World Bank) may be useful.
 * A stocktaking of decision tools may be useful- what is out there within the CGIAR
 * What is the CG’s mandate? We are not consultants- should we be putting together lists of experts? At the same time, this is a great chance to have impact
 * Where do we as CCAFS want our impact to be? Probably at beginning and end (to influence and help evaluate), but donors probably want us somewhere in the middle.


 * Group 2**
 * Dialogue with governments, CCAFS ability to do this
 * E.g. helping with NAPs
 * CCAFS can play a role in agricultural side of things- making sure that they have the data and information that they need
 * This is because many large-scale grant programs respond to needs articulated by governments, so early dialogue with governments is key in order to influence this.
 * This works differently in every country
 * Could use meetings (such as African Ministerial Meeting on Environment) to influence country-level discussions.
 * Perhaps also targeted trainings with key government folks, but the issue is who would do this? RPLs are spread too thin, and there’s little incentive for scientists. However, it is our mandate as CCAFS.
 * Communications is key. Making headway in East Africa and Colombia.
 * CCAFS plays important role in understanding vulnerability and analyzing big picture
 * Important role for CCAFS is to discern what climate smart ag practices are worthy of investment in different contexts.
 * Adaptation cost curves
 * Scalability- what do we know on it? IFAD has a nice framework for scaling up.
 * Disconnect- because we’re scientists, when people ask us for information, we’re either gung-ho, or we say we don’t have enough information.


 * Key messages from the session**
 * 1) We would like the strong processes for learning to complement technological options
 * 2) We would like to contribute to the capacity of governments to develop concrete plans that guide climate finance
 * 3) This process happens before the donors get involved, so this is a slightly different contribution
 * 4) It might be good for CCAFS to develop and compile a portfolio of tools to screen and prioritize investments in climate-smart agriculture
 * 5) We would like to develop a learning platform that ensures and enables the above

CCAFS is not the only research organization working on climate change, so working with other such organizations is key
 * Further action**
 * Linking with climate investment partners is a clear impact pathway- there is mutual benefit

Ewen Le Borgne (ILRI) Marc Schut (Wageningen University) Patti Kristjanson (ICRAF) Mark Lundy (CIAT) Liz Carlile (IIED) Michael Victor (CPWF/WLE)
 * Participants **

The purpose of the Connecting, Engaging and Learning with CCAFS Innovators parallel session was to familiarise participants with the CCSL Sandbox (see Note 1) by road testing Co-Design as a potential approach to inform and improve current and future CCAFS work. Five participants from three CIAR centres and two external partner organisations joined the session and focused in the second half of the session on designing solutions to the challenge //How to Create a Space Where Natural Scientists Engage with Social Learning//?
 * Overview **

Following introductions, Ewen Le Borgne opened the session with a brief graphic presentation of the CCSL Sandbox which is hosted for CCAFS by the ILRI Knowledge Management and Information Services team in collaboration with Euforic Services and Westhill Knowledge. He explained that it is an online space where 73 participants from over 25 organisations (CGIAR and otherwise) have been meeting to discuss social learning (SL), participatory communication and related fields such as action research. Charting the evolution of the CCSL Sandbox, Ewen explained how it was developed in response to the need identified at the CCAFS Communications and Social Learning in Climate Change workshop (ILRI Addis Ababa 8-10 May 2012) for:
 * CCSL Sandbox **

// A social learning community of practice within the CG system for champions, mavericks and curious staff and close partners that can become a node within existing global networks on social learning and related approaches // (CSLCC Workshop Action 1)

Launched in September 2012, the CCSL Sandbox provides a facilitated online meeting place (that builds on the CGIAR Yammer platform), a document collaboration and repository space (on WikiSpaces) and a small fund to support CCAFS innovations in social learning. Ewen emphasised that, as well as supporting peer learning, the Sandbox space has been particularly good at enabling people with problems to get help in developing initial ideas towards solutions (e.g. producing stock-takes of CGIAR experience, the SL narrative and [|whiteboard video], the IDS Climate Change Knowledge Exchange ).



The Yammer space had played a key role in relation to the funding mechanism in that people seeking its support had been required to iteratively share early stage proposals, updates and finished products on Yammer to walk the talk of social learning by being open to ongoing critical feedback, reflections and advice from the CCAFS community. Everyone in CGIAR can easily join the CCSL Sandbox by joining the Yammer platform and Ewen particularly encouraged staff and partners in the CCAFS to take advantage of knowledge sharing opportunities there: [|www.yammer.com/ccsl]



Carl Jackson introduced the principles of Co-Design (see Note 2) as an opportunity to experience Sandbox type collaboration and as a potential approach to inform and improve current and future CCAFS work. Co-Design is an approach developed in industrial and architectural design practice that is hands on and collaborative, allows you to learn fast and fail safely, and promotes free thinking. The process follows four steps: 1. Come up with a visionary name for your solution to serve as a boundary within which to think freely about your problem 2. Draw on experience outside discipline/sector/job for diverse options for solving the problem 3. Make ideas tangible by building a rough physical model of the solution 4. Share your ideas using your prototype to get feedback from others
 * Co-Design Collaboration **

Participants brainstormed around challenges in making knowledge link to action and decided that two groups would both work on //How to Create a Space Where Natural Scientists Engage with Social Learning//. Each group began by coming up with a visionary name for the solution they would develop.

The two solution names were: The two groups drew on their experiences beyond the agricultural research sector (including films, architecture, literature, etc) to generate new choices about how to create engaging spaces where natural science and social learning would link to action. Drawing on tangential insights from how engagement happens helped the groups to create diverse options for solving the problem, rather than converging on a familiar solution too quickly. Each group had access to craft resources to develop emerging ideas into physical prototype solutions that were shared with the other groups later in the session to get their feedback on outstanding challenges.
 * Making a World of Difference – Research into Reality
 * Climate Smarts

// Climate Smarts: How to Create a Space Where Natural Scientists Engage with Social Learning //

The Climate Smarts groups explored how to operationalise or visualise social learning for natural scientist. The group visualised two modes of collaboration between different groups of researchers and societal stakeholders. Within the first mode, researchers and stakeholders do collaborate, but the foundation for collaboration is weak. Collaboration is based on external pressure, donor requirements and is project-based. Consequently, there is low resilience within the system to respond to change or crises. The second mode of collaboration has a stronger foundation based on the key principles of social learning. There are joint objectives, mutual trust, mandate, skills and incentives for collaboration and learning. Basic rules of the game are clear for all involved. The collaboration is process-based, occurs in networks and is more resilient to change or crises as the relationships and common understanding built through social learning processes contribute to strengthening the basis of work done in such partnerships. This approach highlights the critical role that collaboration and social learning play in resolving complex problems.

// Making a World of Difference – Research into Reality //

The Making a World of Difference group started with the premise that research often happens at the fringe or outside of real world development. Researchers cannot continue working at the fringes but need to be able to engage in real world problems and development activities. The circle and actors inside represent what is happening on the inside. The researchers are on the outside. The twisting ‘DNA’ spiral shows the need for researcher to engage with and link to real world problems. This DNA of research and experience coming together to find shared solutions is at the heart of transformational change. Both models represented ideas in three dimensions (e.g. exploring different combinations of relationships, communication gaps to be bridged and sequences of stakeholders, resources, activities and outputs involved in creating engaging spaces).

(1) Climate Change and Social Learning Sandbox is a community of practice with two online spaces hosted by ILRI. The CCSL space on Yammer: [|www.yammer.com/ccsl] and on WikiSpaces: www.ccsl.wikispaces.com
 * Notes:**

(2) The Co-Design method is adapted from the Human Centred Design Toolkit (2009), IDEO. Download the HCD Toolkit here you just need to register: []

East Africa
__How to achieve SLOs and IDOs better using social learning approaches, generally?__ // Current activities // Other ideas
 * Sites with activities: Participating approaches already being used
 * Supporting local and national governments—data and tools for decision making
 * Learning partnerships—sharing information
 * Multi-stakeholders learning together
 * Sharing/dissemination v. transformative learning
 * Shared spaces—multi-stakeholder
 * Individual spaces
 * Go back and forth between the spaces

//Examples of Social Learning//
 * Marc—Tanzania—multi-stakeholders get together to do systems analysis (analyze the innovation system, learning from others, how the problem is framed, etc.)
 * Bringing people together
 * Joint analysis
 * Networking
 * Ioannis (Chris & James)—scenarios—quantifying scenario work
 * Meetings with stakeholders—to develop various scenarios
 * Impact model to analyze the scenarios
 * Process of iterative learning—develop scenarios, sharing them, analyzing them, quantify the variables,
 * Not the product but the sharing and people coming together and reflect and reformulate ideas—iterative process
 * Products v. Processes
 * Involving stakeholders in the processes (of social learning) will help achieve the IDOs/SLOs.
 * Is SL the best way to get there?
 * How does SL help push forward the IDO of farmers innovating?What level?
 * PROLINNOVA—how are farmers already innovating?
 * Social learning around that
 * Others in the community
 * Scientists
 * Extensionists
 * Bringing these people together—social learning at the local level and leads up to learning among multi-stakeholders at higher levels.
 * Positive Deviance—existing innovation
 * This is not new—lots of experience in East Africa
 * Co-designing with farmers
 * SL—we can be more conscience (and reflect on the experiences) of this
 * KPC’s project—starts with the farmers
 * Social learning is a process is finding a solution to all stakeholders
 * Scaling up and adoption of technology
 * Form innovation platforms
 * Bring stakeholders together
 * Discuss watershed problems and potential solutions
 * A means to find solutions to the common/wide-known problems
 * Donors pushing for IDOs
 * 500,000 people in East Africa have doubled their incomes
 * Need national level policies, regional and international organizations to support the processes to have the big scale impacts
 * World Bank—training and visit model
 * Extension, equipment, etc.
 * Didn’t work—wasted investment—could have invested in social learning
 * Tegan—USAID
 * Social learning—participatory development
 * Scaling up
 * Relevant groups at various levels
 * As you make the transition up you work with different people
 * Scaling up means translating the information up the scale—doing different things with different groups
 * How are reflection and learning process included in this?
 * Hierarchy and power structure—barriers
 * Multi-platforms
 * People getting together but SL also happens as people working together (at various scales and levels)
 * Break the pattern—pilot and then policy workshops: Work with them from the beginning
 * What’s the policy relevance—not very good answer (from CG researchers)
 * Partnering with the policymakers and working with farmers and others throughout, we can do this better
 * EAC—regional platform
 * Role of researchers?
 * Need for institution to respect the engagement of other stakeholders (incentive structure)
 * Difficult because fewer products/outputs to point to
 * Partnerships are key: Partnerships as a performance indicators
 * Partnerships are working—PABRA
 * Example of a platform that is working
 * Designs the project together from the beginning
 * What does it mean for me at the operational level—daily work?
 * Who should I partner with and how?
 * How to start the process and the sequencing of the process?
 * Resources & collaborations
 * Social learning is not a new concept
 * Feedback to inform the different levels
 * What is different in the CCAFS strategy related to SL?
 * Need to take stock—what have others already done?
 * What can we learn from others?

__Where can social learning help the CCAFS themes in the regions concretely?__

__What are initial steps to take and early wins along the way?__
 * Partnerships: Outputs from partnerships as part of the performance appraisal
 * Mapping of the learning environment—who is working on what
 * Need to reflect on and learn from the past (and keep doing it)
 * Unpacking success
 * What has worked?
 * What can we learn from?

__ Scaling social learning up and out: how to do this? __
 * Up-scaling—can social learning help us? Not of specific varieties/technology but of a process
 * An innovation is only relevant for a relatively short time: Capacity to innovate is what leads to resilience
 * What have been the pilot successes? And, how have they been scaled up?
 * Who is responsible for scaling up/out?

West Africa
Questions for focus conversation in regional groups – West Africa

__1. How can social learning help CCAFS in West Africa?__
 * A ot of social learning activities going on in the region, concrete examples are:
 * Standard Assessment of Mitigation Potential and Livelihoods in Smallholder Systems (SAMPLES) and GHG quantification supporting learning among the scientists in the region and building capacity (larger number of scientist)
 * Regional scenario (finalize the scenarios and quantify them, organize regional gathering with policy-makers); it is social learning and outcome oriented – downscaling scenario to national and local levels
 * National learning and exchange platforms: social learning activity involving several stakeholders (research, farmers organizations, civil society, private sector, etc.) - learning process and targeted outcome. feedback loop, iteration among stakeholders to make decisions on needs, priorities, issues of relevance to a group of actors
 * Participatory action research at community level involving CG centers, national research systems, extension, farmers and other stakeholders
 * Power relations between and within stakeholders at different levels

__2. initial steps and quick wins__
 * Need of documenting processes – people to see what is happening and to see opportunities – production of solid evidence: what are the good stories coming out of the processes and evidence (to build evidence based of what work where, how and why?)
 * Capacity development at national government level to influence learning platforms, guide and drive priorities by using a portfolio of tools/approaches to bring stakeholders around a table
 * Sharing information, database, tools, methods, etc.
 * Regional priorities” outcomes, big winners outcomes to guide the process between CG centers, national and regional stakeholders
 * Reinforce regional strategy on CC by regional stakeholders (FARA, CORAF, CILSS, ECOWAS, etc.) – share vision
 * CCAFS to get donors together, regional stakeholders learning and sharing platforms between donors, development partners involved in climate change – leverage point, much can be done – how do we do that?

__3. How can we achieve SLOs, IDOs, etc.?__
 * Capacity strengthening at national and regional levels
 * Exposing stakeholders to the SLOs, IDOs, to drive engagement, commitment and buy-in around these (with other partners non CGs).

__4. Scaling up/out__

South Asia
PA: Ongoing SL tools in program: MJ: Using traveling seminars to transfer knowledge between locations.
 * Climate-Smart Villages – can they better inform other levels of decision-making?
 * Participatory videos
 * Rural fairs
 * Climate-Smart Learning Platform

**Discussion by IDO**: IDO1: Farm scale:
 * Participatory evaluation of technologies already being used.
 * Multi-stakeholder dialogs: Local NGOs, farmer groups and government are already involved. Use Rural Fairs to involve a broad range of stakeholders.
 * Participatory variety selection, biodiversity management
 * Gender emphasis in CSVs. Working through women groups to empower.
 * Farmer Field Schools.
 * The CSV approach emphasizes farmers mobilizing themselves to address their problems.

IDO2: Local institutions:
 * Targeting local government to inform and empower.
 * KVKs – farm science centers. Each district in India has one KVK. Associated with SAUs. Links researchers with state departments of agriculture.
 * Local insurance agencies involved.
 * PA: Cited index insurance activity in CSV as an example with feedback loops between private sector, farmers and research. Seed companies use CCAFS CSV as a platform for dissemination.

IDO3: National evidence-based policy:
 * Climate-Smart Learning Platform reaches national level actors.
 * Science-Policy Public Interfaces.
 * Consult national policy, actors to identify CCAFS research priorities. Work to reconcile government and research priorities.
 * ICRISAT, increasingly CIMMYT, IRRI, IFPRI, research is largely funded by the Indian government.
 * ICRT-based dissemination influenced to national government.

PA: Exercise taught us that we do a lot of good things that we don’t communicate well. Agreed to write a blog on social learning in the SA RPL.

__Questions__:
 * 1) Already exploiting many different mechanisms.
 * 2) Farmer feedback on Climate Analogs has shaped Theme 1 strategy = > Climate Risk Analogs. Identified demand for drought-tolerant varieties.
 * Theme 2: South-South learning workshop built on India’s Agro-Advisory Service. South Asia ad-hoc group developed a strategy around extending AAS to other countries in the region. Informed T2 research questions about equity challenge when scaling up climate information dissemination.
 * 1) All initial steps have been taken.
 * 2) [Just like the S. Asia program is doing.] Involve all relevant stakeholders from the onset. Example of Haryana. Brought state government officials to CSV. They incorporated into the state’s strategy.

South East Asia
__1. How to achieve IDO’s better using social learning approaches__ How can SL help in defining/developing IDO’s and the pathways to get to them? 3 big issues Looking at what other centres are doing. e.g. Social learning as both process and outcome.
 * Interaction among centres
 * Interaction with partners
 * 1) Reducing GHG emissions/unit of ag production
 * 2) Enhancing resilience in context of rising sea levels
 * 3) Disaster risk management linked to agriculture
 * ICRAF working closely with communities
 * AAS working in Cambodia with a CC angle with CCAFS

What we are looking for is transformation. Commitment to people and place and working across scales – is our contribution. Changes in how adversarial organizations are dealing with each other (societal change) e.g. 2 different ministries.

Facilitated interactive ways of working together (essential component of how we work) – leads to institutional change IDO (No. 2 – about a state change; social learning is one of our main tools for achieving this state change). When you get to the high policy level, how do you bring together such adversarial institutions? You are not going to set up a new committee, but there are inter-ministerial committees; at lower levels, you can set up processes that bring them together, working together on small action research projects. Key is to have a development challenge e.g. Mekong – sustainable hydro power. The research process itself is a powerful way to bring people together to do something they both want to do - Climate adaptation in southern Vietnam project example.

A lot of this happens anyway; we work with partners and we go through iterations. Fixing on the output and not thinking mindfully of using research as a way to build the linkages if we are to contribute to transformative change. What can we do when we facilitate these processes; mindful of the process outcome Mekong experience – they couldn’t say we want to change their KAS Social learning – at the end of the year take stock; conscious learning cycles; within the project there could be smaller learning going on Big difference? Document the lessons/learning process; bring in researchers writing papers on these theories of change Detailed ToC’s documented well (research on impact pathways) Feedback becomes an integral part of the approach (flexibility and openness key) Before: only used feedback in a minor way Seamless process rather than a separate planning and implementation stages M&E is part of it; we do it because we need it ourselves…

__2. Where can SL help the CCAFS themes in SE Asia?__ We may not have themes soon? e.g. GRISP – calls it products and product lines. e.g.2 AAS – calls it a development challenge in a geographic location Changing cultures/norms with SL: Breaking down hierarchies and gender-blind examples of issues to address… Pathway around contributing to a thematic literature; so you do want something that pulls together thematic research across the program, and learn from your different cases across the globe e.g. salinity trials; you will be doing participatory plant breeding at the local level; farmer field schools, crowdsourcing (different types of social learning)

I.D. Specific tools and approaches linked to the IDO’s Challenge: linking across scales
 * IDO1 – farmer field schools
 * IDO2 - Learning alliances, innovation platforms
 * IDO3 - Participatory modeling

Within a country, we have to be careful in how we are approaching the institutions (e.g. asking them to work together) e.g. participatory modeling; output is the model; there is no change in that. We want to change how decisions are made; modeling is one means to an end.

__3. What are initial steps to take and early wins along the way?__ Look at CG activities in the region; try to piggyback or replicate. e.g. strong community engagement (rice-fish systems) Facilitating processes – we don’t need to be the ones facilitating community Looking for partners that do the kinds of things we need to do at the different levels Network mapping exercise
 * //Strategies//**:
 * Spend time with a few key NGO’s and really understand what and how they are approaching, say, adaptation
 * Older people retiring and setting up their own NGO’s (ex-gov’t) – engage with them
 * Engage with youth groups

__4. Scaling up and out social learning?__ This question is wrong!

To scale up, you do SL at multiple levels. SL n eeds to become a seamless process; if you think SL to the end, you no longer do step 1 (demo trial on salt-tolerant rice), then try to scale out later; needs water, so you need to work with sluice gate operators, so you need inst’l change at another level…… How do we get it better understood; fulfilling its potential? Show some good examples; show us how it is done! (e.g. a case study) Examples and analogies e.g. PROLINNOVA shifting from supporting individual innovation to supporting capacity to innovate – is like a firework being lit; you don’t see anything for awhile; then you see thousands of lights. We should do this across CRPs Scaling up (reaching DG’s) Scaling out (convincing the scientists) Need good examples - CPWF has a couple of good ones History/lessons of ILAC should be written up

Latin America
SL involves three loops: instrumental, communicative, transformative. Each loop is associated with different dimensions, the first level might be at the individual level, but the others include collective learning. The explanation of loops clarified the fact that this is not what we have been consciously doing. To be successful at transformative action, we need a SL approach, involving others. It seems that impact is impossible without SL. In fact, most scientists use SL in their daily shores, but the challenge is to include other actors in their SL networks, beyond their scientists peers, in order to reach IDOs and SLOs. In LAC, the CGIAR Centers have several examples of reaching thousands of households in a relative short term that would probably need to be assessed with SL focus and streamline the process and underline the principles.
 * How to achieve SLOs and IDOs using social learning approaches generally?**

We need to learn from existing initiatives. One of the short term challenges should be to draw lessons from case studies and start from there. It would be interesting to design a study with farmers using climate change projections and facilitating the process. This can be combined with modern visualization tools and other participatory modeling tools and artificial intelligence BUT the challenge would be to use this as a learning tool. A caveat is that the actors have their own priorities that often times are not climate change impact, and there is an important SL there. We need to remember that SL is a multiple way process. If farmers are more concerned with prices and other economic policies, we need to listen and support, rather than impose our climate change agenda. We need to “ground climate change”, linking theoretical insights with things on the ground, “participatory modeling”. Insights from such exercises will help to prioritize issues and may even radically change the questions researchers ask.
 * Where can SL help the CCAFS themes in the regions concretely?**

We propose starting itinerant courses for university professors on subjects such as meteorology, agronomy, land planning, etc. The idea would be to ask professors to share the way they teach. CCAFS will then expose the tools and methods developed, ask for feedback and ask professors to use them in their regular courses. We expect to learn from the process and disseminate CCAFS products and data bases. We also propose using farm models in some agronomy and ecology courses where climate change scenarios are given to students and they are asked to manage farms or landscapes and come up with sustainable plans. We need to innovate on the SL front, finding new ways to connect people; for instance, crowdsourcing, and the use of ICT in general. One important problem in LAC is the absence of an extension system. We need to fill this gap by working with NGOs and other partners (university students). In the context of Central America, cross-CRP collaboration will be very important.
 * What are initial steps to take and early wins along the way?**

Go beyond agriculture with the ideas described above, e.g. Ecology, business schools. We want to reiterate that there are many SL experiences in LAC that we would like to join with and create synergies. Also include existing structures, for instance, PCCMCA is a useful platform in the region and has served for 50+ years to bring agronomists together. Although in LAC much research is already done collaboratively, approaches can still be improved and upscaled. Work in Central and South America typically involves from 5000 to 50,000 families. Also, transformation could be seen from a rights-based perspective http://www.oxfamblogs.org/fp2p/?p=12853. There are fewer funds for LAC, so there is a need to show value for money and strategically choose partners to enable upscaling. Work in LAC must consider that R&D funding is dwindling and thus must reach out and include all the partners, including the private sector and large NGOs. Joint forces among CGIAR is a must.
 * Scaling social learning up and out, how to do this?**

Evaluation of the meeting
Looking back at objectives:
 * Building new partnerships?
 * Unrealistic!
 * Exposure to past experience?[[image:IMG_5328.JPG width="480" height="638" align="right"]]
 * Not so much
 * A lot is happening but is not structured nor documented
 * What was better done is the focus on current and upcoming work
 * Pull it out in practical ways!
 * Share 50 tricks to make SL work!
 * Improve CCAFS work with social learning?
 * This is useful. We do a lot. What can I do? Provide practical examples.
 * Next steps: make it practical! use examples (this was not concrete enough)
 * Yes, we have improved CCAFS work but worried that it's followed up concretely
 * Some points in the last discussion relate to how new this is compared with what we do already
 * Social learning and participatory approaches requires more consciousness and focus on the process
 * Learning about social learning touches upon systemic change. It's not a luxury, it's a necessity. We have to understand how research leads to change (ok, on the back of the '50 tricks')

Other comments:
 * Social learning is about formulating heuristics. Next year, make the agenda more practical and look at social learning concretely
 * The sandbox can be used for peer-assists!
 * Why did not more people go to that side session on social learning?
 * This science meeting happened and CCAFS focused on social learning, showing that they're serious about it.
 * In such a room to have achieved discomfort means we have learned
 * Younger people will go to the wiki to check resources but older people are more comfortable reading papers!
 * We could have done social learning without the fuss of 'social learning'. Is it about social learning or about working on other issues?


 * Bruce Campbell's reactions and last words**:
 * The science meeting is about getting new ideas.
 * Will something come out of this?
 * What about a toolkit about our investments?
 * We have to work on cross-CRP/centre work on adaptation to harness energies.

Organizers' agenda