Enhanced Learning from AFSI Research: Notes for the Field

www.monash.edu/research/sustainability-institute

Enhancing learning from AFSI research: Notes for the field

MSI Report 13/10December 2013

Ray Ison, Philip Wallis, Caroline Bruce, Richard Stirzaker & Yiheyis Maru

http://www.monash.edu/research/sustainability-institute/

Published by the Monash Sustainability Institute

The Monash Sustainability Institute (MSI) delivers solutions to key sustainability challenges through research, education and action. For government, business and community organisations, MSI is a gateway to the extensive and varied expertise in sustainability research and practice across Monash’s faculties and research institutes.

Acknowledgement

The ‘Learning Project’ has been funded by the CSIRO-AusAID Africa Food Security Initiative. AFSI is focused on lifting food security and agricultural productivity in Africa.

MSI Report 13/10, December 2013ISBN: 978-0-9875677-3-4

Authors

Ray Ison¹, Philip Wallis¹, Caroline Bruce², Richard Stirzaker² & Yiheyis Maru²1 Monash Sustainability Institute, Monash University2 CSIRO

Citation

To be cited as: Ison, R.L., Wallis, P. Bruce, C., Stirzaker, R. and Maru, Y. (2013) Enhancing learning from AFSI research: Notes for the Field. MSI Report 13/10, Monash Sustainability Institute, Melbourne, Australia.

Contact

Professor Ray IsonSystemic Governance Research Program - Program LeaderMonash Sustainability InstituteBuilding 74, Clayton CampusMonash University, Victoria 3800, AustraliaE: [email protected]: www.monash.edu/research/sustainability-institute/

Disclaimer

Monash University disclaims all liability for any error, loss or consequence which may arise from relying on any information in this publication.

Cover image

Taken by Ray Ison in 2012 in Senegal for the ‘Learning Project’ Africa Food Security Initiative.

http://www.monash.edu/research/sustainability-institute

Enhancing learning from AFSI research: Notes for the Field i | P a g e

Enhancing learning from AFSI research: Notes for the Field

1. Introduction ................................................................................................................................................................. 1

1.1. What is the „Learning Project‟ ............................................................................................................................ 1

1.2. Why enhancing and capturing your „learning‟ will assist with this project ........................................................... 1

1.3. How to use these notes ...................................................................................................................................... 1

1.4. A conceptual framework ..................................................................................................................................... 2

2. Making the framework practical .................................................................................................................................. 3

2.1. P: You – the researcher/practitioner................................................................................................................... 3

2.2. F: Frameworks of ideas ...................................................................................................................................... 4

2.2.1. IAR4D ........................................................................................................................................................ 5

2.2.2. Innovation Platforms .................................................................................................................................. 7

2.2.3. Effective performances (social learning) ................................................................................................... 8

2.3. M: Method - methodology ................................................................................................................................ 11

2.3.1. Most Significant Change – an adaptation ................................................................................................ 12

2.3.2. Social learning ......................................................................................................................................... 14

2.3.3. Pathways to impact ................................................................................................................................. 20

2.4. T: A bag of tricks – Techniques for the field ..................................................................................................... 21

2.4.1. System mapping ...................................................................................................................................... 21

2.4.2. Conversation mapping ............................................................................................................................ 22

2.4.3. Multiple cause diagramming .................................................................................................................... 24

2.4.4. Rich pictures............................................................................................................................................ 25

2.4.5. Root definition statements: PQR ............................................................................................................. 26

2.4.6. Identifying purpose: CATWOE / TWOCAGES......................................................................................... 27

2.4.7. Interviewing ............................................................................................................................................. 28

2.5. S: The research situation(s) ............................................................................................................................. 28

2.5.1. Managing strategic risk and reputation .................................................................................................... 29

2.5.2. Framings ................................................................................................................................................. 29

2.5.3. History of situation ................................................................................................................................... 31

2.5.4. Patterns and trends ................................................................................................................................. 31

2.6. C: Scaffolding our joint learning – Confluence ................................................................................................. 32

3. Levels and dimensions of learning ............................................................................................................................ 33

3.1. O: Other researchers and partners .................................................................................................................. 33

3.2. A: Action research, participatory action research and systemic action research .............................................. 34

4. Assimilating the learning ........................................................................................................................................... 36

4.1. A: Assimilating the learning .............................................................................................................................. 36

5. Protocols, ethics and cultural sensitivities ................................................................................................................. 37

6. References ............................................................................................................................................................... 39

Annex 1. A systemic set of prompts for learning in the field ............................................................................................... 41

Annex 2. Trip Report to Mali and Kenya (7-20 November 2011) and Other Reflections .................................................... 44

Annex 3. What is IAR4D? .................................................................................................................................................. 51

Enhancing learning from AFSI research: Notes for the Field ii | P a g e

Figures

FIGURE 1. A WAY OF THINKING ABOUT INDIVIDUAL RESEARCH PRACTICE ........................................................................ 2

FIGURE 2. MICHAEL LEUNIG’S CARTOON ABOUT THE UNDERSTANDASCOPE .................................................................... 4

FIGURE 3. AN ABSTRACT REPRESENTATION OF A CO-INNOVATION PLATFORM ................................................................. 7

FIGURE 4. SOCIAL LEARNING CHARACTERISES AN EFFECTIVE PERFORMANCE ................................................................ 10

FIGURE 5. SOME OF THE DIFFERENCES BETWEEN TECHNIQUE, METHOD AND METHODOLOGY .................................... 12

FIGURE 6. THE MOST SIGNIFICANT CHANGE APPROACH TO PARTICIPATORY MONITORING AND EVALUATION. ............. 13

FIGURE 7. A MAP OF THE INSTITUTIONAL COMPLEXITY FACED BY SENIOR MANAGERS OF A CMA IN VICTORIA ............ 16

FIGURE 8. RESEARCHER AS ENABLER/FACILITATOR IN SITUATIONAL TRANSFORMATION ................................................ 17

FIGURE 9. EXTRACTS FROM A PRESENTATION TO THE AGSI TEAM ................................................................................... 20

FIGURE 10. A DRAFT SYSTEM MAP OF THE AFSI RESEARCHING SYSTEM. ........................................................................ 22

FIGURE 11. A COMPLETED CONVERSATION MAP BY AFSI RESEARCHERS ......................................................................... 23

FIGURE 12. SOME OF THE MULTIPLE CAUSES AND EFFECTS OF TRAFFIC GROWTH ......................................................... 24

FIGURE 13. TWO RICH PICTURES FROM THE FIRST AFSI LEARNING PROJECT WORKSHOP .............................................. 25

FIGURE 14. MAKING CHOICES ABOUT HOW TO ‘FRAME’ A SITUATION OF CONCERN FOR RESEARCH ACTION ............... 30

FIGURE 15. PATTERN ANALYSIS AS USED IN AGRO-ECOSYSTEMS ANALYSIS ..................................................................... 32

FIGURE 16. AN EXAMPLE OF TEAM LEARNING IN A PROJECT TEAM ................................................................................ 34

FIGURE 17. A REPRESENTATION OF LEARNING ACROSS A WHOLE PROGRAM ................................................................. 34

FIGURE 18. A TYPOLOGY OF RESEARCH APPROACHES...................................................................................................... 35

FIGURE 19. THE HAWKESBURY SPIRAL OF RESEARCH APPROACHES RELATING TO DIFFERENT FORMS OF LEARNING .... 36

FIGURE 20. DIFFERENT MODES OF USING THE THEORETICAL FRAMEWORK ................................................................... 37

Boxes

BOX 1. THINGS THAT THE RESEARCHERS USING AN IAR4D APPROACH NEED TO DO DIFFERENTLY ................................... 8

BOX 2. STATIONARITY/LINEARITY ........................................................................................................................................ 9

BOX 3. SOME IMPLICATIONS OF AFSI INITIAL STARTING CONDITIONS ............................................................................. 14

BOX 4. SAMPLE STORY - RESEARCHER R9: 4 AUGUST 2011 .............................................................................................. 15

BOX 5. DIFFERENT WAYS OF KNOWING AND SOME IMPLICATIONS ................................................................................. 18

BOX 6. EXTRACT FROM THE CONSENT FORM TO BE SIGNED BY ALL AFSI COLLABORATORS ........................................... 38

Enhancing learning from AFSI research: Notes for the Field 1 | P a g e

1. Introduction

1.1. What is the ‘Learning Project’

The purpose of the Learning Project is to enrich the formal monitoring and evaluation requirements of the African Food Security Initiative (AFSI) by supporting personal reflection, sharing and capture of learning from researchers' experiences. There is also a strategic intent – to aid CSIRO to engage in Integrated Agricultural Research for Development (IAR4D) more effectively, now and into the future to enable continual growth and positive impact.

1.2. Why enhancing and capturing your ‘learning’ will assist with this project

In addition to your AFSI trip reports, the lessons, insights, inspirations and reflections you gather during your involvement with AFSI can enable us to collectively improve the way we conduct and evaluate our integrated research for development. This is not about documenting our experiences for the sake of „ticking a box‟; rather, that we can enable deeper personal and institutional learning.

1.3. How to use these notes

These 'Notes for the Field' present a theoretical and practical approach to both inform and consolidate the insights from AFSI – ultimately underpinning the Learning Project.

These 'Notes for the Field' can help make the most of your experiences in the field and when learning together in your project team, at the partnership level or when working with international partners. Annex 1 contains a set of prompts and a template for recording your reflections.

The conceptual framework presented here summarises six elements that structure research practice. Making these elements apparent, thinking about them and learning so as to be more effective, creates an individual's learning platform:

P – you, the researcher / practitioner,

F – frameworks of ideas,

M – methodology,

T – techniques for the field,

S – the research situation(s), and

C – capturing the learning.

This document is also designed to meet the first deliverable of the Learning Project which is:

A theoretical framework against which the impacts from the AFSI initiative is assessed

However, what we propose is not a fixed, static, framework, but a starting point to a framework to be co-developed and tested with AFSI researchers in an action research mode. As several AFSI researchers have already noted, not everything can be recorded and analysed. That is why a meta-framework is needed to begin to have a research conversation across AFSI that operates at a higher level of abstraction and that captures learning both within and across individual projects.

Richard Stirzaker outlines how these notes might best be used:

“Attached is my end of year summary, where I used my last trip report to reflect on the wider issues. There are many points where your „notes for the field‟ document intersects with what I have written.”

An edited version of Richard‟s end of year summary is included as Annex 2. He goes on to say:


“Do you think we could put the conceptual framework you presented us with [see below] across the African farming system projects? Namely, P – the researcher, F – frameworks, M – methodology, T – techniques for the field, S – the research situation and C – capturing the learning.

For example, from the “P” perspective the problem looks simple. A negative nutrient balance means yields are declining, leading to shorter fallows, faster loss of OM [organic matter] which reinforces the vicious cycle, exacerbated by an increasing demand for land by a fast growing population. The solution appears simple (add fertiliser) but something about the value chain does not allow this to happen.

I have just gone through the documentation for the PRA [participatory rural appraisal] and baseline surveys for one of the projects. I found this really stimulating and it will provide a completely different view of the situation to mine. If we are explicit about our own PFMTS it may help us to recognise where others are coming from and hence to learn faster?‟

The answer to Richard‟s query is yes! Of course there are no reasons the framework should be confined to just the CORAF/WECARD projects in West Africa – of which Richard is referring.

We encourage everyone who goes to the field to take this framework and to put it to use. If you can make some entries into Confluence1, then so much the better, but do not let this act as a constraint.

1.4. A conceptual framework

The conceptual framework shown in Figure 1 is designed to assist CSIRO and invited partner researchers to engage knowingly in processes of learning by considering these key elements, customised for individuals engaged in AFSI.

Figure 1. A way of thinking about individual research practice involving a set of interrelated elements comprising practitioner/researcher (P), theoretical framework (F), methodology(ies) (M), research situation (S) tools or techniques (T) and capturing the learning through Confluence (C) (Source:

1 Confluence is a purpose-designed on-line learning environment developed for use by AFSI Learning Project

members.


adapted from Ison 2010).

2. Making the framework practical

The essence of Figure 1 is an invitation for you to see research practice as made up a set of elements that, together (i.e. systemically), give rise to a „research performance‟. This systemic perspective moves away from just focusing on outputs and outcomes, important though these are.

This figure also carries with it five other invitations:

(i) an invitation to responsibility by taking charge of your own learning;

(ii) an invitation to understand and/or use this framework and, based on your experience (learning), to suggest or develop adaptations to it;

(iii) an invitation to consider inviting your research partners to participate in the use of this framework with you;

(iv) an invitation to use this framework as a „launch pad‟ into a parallel or subsidiary inquiry that can be published as rigorous research (Richard‟s proposal above could be seen in this light);

(v) an invitation to share your insights to underpin a more personal emphasis and tone to communication activities through „story-telling‟.

The different elements of Figure 1 are now unpacked. Where they exist, examples from recent reports of AFSI field visits are used in a manner consistent with the ethics framework that has been adopted.2

2.1. P: You – the researcher/practitioner

In some circles it is quite a radical suggestion to include the researcher in the research situation. Often research practitioners, implicitly or explicitly see themselves completely outside the research situation. This perspective may be associated with an understanding of what it is to be „objective‟ or 'subjective'. On the other hand few would argue, from a systemic perspective, that the researcher is not part of the „researching system‟.

What can be said in general terms about you, the researcher? At the risk of stating the obvious, you:

are unique, with your own social/cultural and biological history

live in language i.e., language is key to almost everything humans do

knowingly or not use a range of theories - from when you developed language as a child you began to accept and reject explanations and in the process took on or rejected various theories about your world and the world (see Figure 2)

have a history that influences how you „see‟ and thus engage with the world – this includes in particular your disciplinary background3 as well as gender, socio-economic background etc

2 Many within the AFSI Learning Project will recognise who has said what in this document despite the use of coding as

adopted here. As this is a co-learning action research project and all will have signed consent forms, this is not a major

issue. This is not a research report as such and any quotes used here are merely to help elaborate the ideas being

proposed. However, once released this essentially becomes a public document so good practice is required.

3 In our research, we refer to this history as a tradition of understanding out of which each person thinks and acts –

see Russell & Ison 2007.


can learn and thus change and you can generate explanations that others may, or may not accept.

Figure 2. Michael Leunig’s cartoon about the understandascope is a metaphor for how humans engage with the world around them.

To communicate what we have inside our heads, in our own unique 'understandascopes', relies on our use of language and on how we perceive or make sense of our experiences in the world. In science the use of words, writing, numbers and models are most prevalent. But often the meaning that an individual will intend in what they say or write may be misinterpreted by a listener or reader. Thus for communication to be effective, to move towards positions where groups hold common meanings, takes time or the use of special techniques to hasten the process. Some of these techniques are introduced below.

No one goes about what they do theory free. Said another way, all of us have theoretical frameworks which come into play when we do what we do. Sometimes these frameworks are known or conscious, sometimes not. When researching in the social sciences, or doing action research a lot of attention is paid to making either (i) a taken-for-granted theoretical framework apparent or (ii) an explicit choice to use and test a particular theoretical framework (or several).

For example, on a recent field visit R2 was asked to respond to a gender specific issue by a Minister. The request concerned:

“refuge crops for cotton – to promote the use of women-friendly crops (e.g. sunflowers) as the designated refuge crop for Bt cotton. At the moment conventional cotton acts as the refuge (planted near Bt cotton to prevent resistance developing) – BF has 70% Bt and 30% conventional whereas Oz produces almost 100% Bt and uses other crops as refuge.” (R2.1)

This request brought into consideration a research design that explicitly acknowledges gender; it thus creates a need to be informed by theoretical ideas that might not otherwise have been taken into account.

2.2. F: Frameworks of ideas

In the first instance, three theoretical frameworks are proposed. They are proposed because they are likely to be helpful as sense making „tools' when you are in the field, or when reflecting on your experiences of being in the field. In exploring only three we are not trying to be restrictive but to offer a minimum set that can help build a meaningful conversation across AFSI.


2.2.1. IAR4D

AFSI can be understood as a joint AUSAID-CSIRO research contribution to IAR4D (Integrated Agricultural Research for Development). Members of the CORAF team at the joint program meeting in Brisbane will have seen Richard Stirzaker‟s presentation which outlined the rationale for AFSI engaging with the IAR4D literature and discourse. His arguments for adopting an IAR4D approach are made in his paper included here as Annex 3.

Richard summarises why he considers IAR4D as relevant in the following terms:

IAR4D makes the „problem space‟ bigger and in doing so creates opportunities for different solutions

IAR4D picks an entry point and geographical location in order to target the actors in the value chain and assemble relevant stakeholders into an Innovation Platform (see below)

The Innovation Platform is multi-disciplinary, uses participatory „learning-by-doing‟ approaches and focuses on pathways to change (i.e., it addresses where the biggest impact can potentially occur)

IAR4D avoids the linear technology transfer model of researcher-extension-farmer. Instead it relies on non-linear iterative collaborative interaction amongst diverse stakeholders to generate more durable solutions

However in order to have a chance of success the process:

must make it worthwhile for the stakeholders to engage (e.g., the researchers are paid – what do the other actors get out of it?)

requires good leadership and facilitation skills

needs drivers or champions for change

requires participatory and learning approaches that support collective action

There are claims made that IAR4D attends to the factors outlined in Box 1.

Box 1. Things that the researchers using an IAR4D approach need to do differently when using IAR4D in practice (Source: http://wikieducator.org/IAR4D_Educational_Content)

• Researchers together with farmers and stakeholders continuously assess and prioritise needs, opportunities and identify a high-quality research demand

• Researchers pro-actively seek and strengthen partnerships, collaboration and networking to increase plurality in research

• Researchers develop flexible and dynamic research agendas responding to stakeholders‟ demands while integrally incorporating market-focus, sustainable natural resource management and food security, interdisciplinarity and social differentiation

• Researchers engage with farmers and other stakeholders in participatory research processes as a major approach responding to demand and build joint ownership and accountability to the clients and local authorities

• Researchers engage with farmers and other stakeholders in integrated natural resource management as a foundation for market-oriented agriculture

• Researchers integrate market research with a focus on market chain integration into all research work

• Researchers engage into policy research in the context of market chain integration, NRM and food security

• Researchers ensure the availability of technologies to a wide array of stakeholders and users

• Researchers support private sector, and other clients through information, training, facilitation, backstopping and skill building in production, marketing, value adding

• Researchers are continuously improving their strategy and approaches to enhance commercialization of agriculture towards marketing and exports


• Researchers monitor the impact of their and others intervention on a differentiated clientele and use the results to inform the process and adapt/re-plan their intervention

• Researchers and management regularly assess their competence and continuously seek to improve it in response to emerging challenges and demands

• Research management develops and implements strategies for attracting and retaining high quality and performing staff


2.2.2. Innovation Platforms

This concept has a mixed history. It now features strongly in international agricultural R&D. Innovation platforms are a cornerstone of the UK‟s current approach as exemplified by the UK‟s Technology Strategy Board, in which:

“The Sustainable Agriculture and Food Innovation Platform will see investment of up to £75 million over the next five years in innovative technological research and development in areas such as crop productivity, sustainable livestock production, waste reduction and management, and greenhouse gas reduction.”4

In the UK context an innovation platform is described as:

“[an institutional invention designed to] focus on specific societal challenges where the UK Government is taking action through policy, regulation, procurement or fiscal measures to tackle the problem. By improving co-ordination between the key players from industry, academia and government, innovation platforms can identify barriers to meeting the challenge, map possible routes to overcoming the barriers and align activities to support innovative solutions. Innovation platforms aim to fundamentally change the ability of UK businesses to provide solutions for the global marketplace, boost UK economic performance, and provide higher quality of public services.”

Another lineage sees „innovation platforms‟ as arrangements designed to achieved open innovation (Linux is often cited as the classic example of open source innovation), rather than the more traditional closed forms of innovation.5

Figure 3 depicts how innovation platforms are conceptualised by some within the IAR4D community. Posthumus et al. (undated) argue that:

“An innovation systems perspective is therefore needed to tackle the challenges of CA [conservation agriculture]. The active participation of farmers in iterative technology development through action research to facilitate co-learning and co-innovation may be a promising approach to promote CA in sub- Saharan Africa.”

Figure 3. An abstract representation of a co-innovation platform and its possible fields of interaction. The identified ‘Other stakeholders’ will be different for each situation and include

4 See http://www.innovateuk.org/ourstrategy/innovationplatforms/sustainableagricultureandfood.ashx

5 See http://en.wikipedia.org/wiki/Open_innovation

http://www.innovateuk.org/ourstrategy/innovationplatforms/sustainableagricultureandfood.ashx

http://en.wikipedia.org/wiki/Open_innovation


the government, the private sector and/or other organisations involved in the process.6

As yet it is unclear the extent to which AFSI researchers are drawing on innovation platform (IP) theoretical ideas and IAR4D. However these ideas help make sense of R2‟s recent reflections:

“Seeds systems project – we met with participants in the AFSI seeds/inputs project and visited a trial site in both countries. The critical issue in our discussions was getting the innovation platforms established and functioning … both countries have made good progress with meetings already undertaken in BF and planned for Mali (X, a prominent agro-dealer, is leading this event). [It was] decided to devote a full day to IPs at the project‟s annual meeting in March 2012.

Cotton systems – Private sector input – having J and M along provided real benefits in assessing possible intervention options for smallholders via the private sector. Both have worked in multi-national companies supplying services to smallholder farmers in developing countries. I think there will be real benefits to our R4D efforts in partnering with guys such as these who far better understand the drivers in the private sector‟ (R2.2)

Of course no theory should be accepted uncritically, and this goes equally for the three described here. Later the idea of „framing‟ and the need to explore some of the systemic consequences of framing choices will be raised. This is particularly the case given R2‟s report that:

“The BF [Burkina Faso] Minister of Research & Innovation wants to run a cross-ministry workshop on Innovation Platforms [IP]. He is so impressed by what X has done and the logic, he thinks that the whole Government could benefit from this approach and so wants to sponsor a workshop on how different Ministries could adopt this approach. He‟s invited AFSI to join the workshop and help sponsor it – it would cost us $20k. To me, this is a great investment both in promoting Australian support at high levels in Government, in demonstrating impacts and in progressing the IP thinking.” (R2.3)

2.2.3. Effective performances (social learning)

How learning is understood and enacted is central to most, but not all, conceptions of social learning. Social learning encompasses (but is not limited to) considerations of how people learn collectively and how the social context influences learning amongst individuals. For these reasons (and others) social learning is increasingly being applied to issues of resource and environmental management. Social learning is more than participation (as in participatory R&D, or participatory action research) and it breaks away from historical commitments to stationarity and linearity that characterise much R&D practice (see Box 2).

The overall effectiveness of AFSI will be more than the sum of its parts, where the parts can be considered as the 13 individual projects and the African Biosciences Challenge Fund (ABCF) that go to make up the BecA and CORAF partnership. Designing and doing research projects is never straight forward even in a familiar cultural context, yet alone one that is very unfamiliar. This realisation presents a challenge as well as an opportunity: the challenge is to not fall into the trap of thinking that what has been done in the past is relevant to the new situation. The opportunity is to consider how those with experience of the new research

6 See http://aciar.gov.au/files/node/14068/enhancing_adoption_of_conservation_agriculture_pra_96301.pdf

http://aciar.gov.au/files/node/14068/enhancing_adoption_of_conservation_agriculture_pra_96301.pdf


situation (e.g., African partners and researchers) can help you to see what they see and vice versa. In other words a learning-based approach, both individually and collectively, has relevance in the AFSI context.

Here is an example, drawn from Ray‟s research with staff of the Environment Agency of England & Wales (EA). The research was concerned with making implementation of a major new policy, the European Water Framework Directive (WFD) more effective. Those involved had a mainly technical background i.e., engineering, hydrology, water quality. In follow-up evaluation after working with the River Basin Planning Group for three years this is what some of the Senior EA managers said:

„After months of work, it was such a relief finding out that the WFD was difficult and it was not just me being stupid‟

„We use the word integration all the time. But this is the first time we‟ve ever had a conversation about its meaning!‟

„We need to learn our way into this because we‟ve never done anything like this before; and it‟s obviously a new form of learning that involves doing it together. So it‟s social rather than technical‟

A lot has been written about social learning. The key points to appreciate are that:

(i) It can be understood in two different but related ways – as a process, much as occurs when a research team starts to function effectively through the dynamics and relationships of those involved and because the organisational/institutional setting is conducive, and as a governance mechanism (an entity) that can be invested in, and around which training and capability-building programs can be developed. Figure 4 depicts what is involved. A jazz ensemble can be understood as an entity – it can have backers, patrons, managers etc., just as a research program can be seen to have funders, backers, patrons etc. But what the funders are paying for is the capacity of a group of individuals to come together and create a good performance that is fit for purpose and suited to the context e.g., a particular audience. The creation of a good performance is a dynamic, social

Box 2 Stationarity/Linearity

In the water field, historically dominated by engineers and water technologists, Milly et al. (2008) outline how historically, „stationarity‟, the idea that natural systems fluctuate within an unchanging envelope of variability, „… is dead and should no longer serve as a central, default assumption in water-resource risk assessment and planning‟ and „finding a suitable successor is crucial for human adaptation to changing climate‟. Performances and designs built on stationarity and fixed knowledge forms give rise to systematic (i.e. linear, step by step) practice rather than systemic practice that is relational, recursive and circular and characterised by learning and adaptation (Ison 2010).

Arguments for investment in „social learning‟, as an alternative environmental governance mechanism, rest on similar conceptual assumptions to those arguing for the „death of stationarity‟ Ostrom et al. (2007) also caution against the belief that „scholars can generate simple models of linked social–ecological systems and deduce general solutions to the overuse of resources‟ (p.15176) and posit two false assumptions made by advocates of panaceas (ibid): „(i) that all problems, whether they are different challenges within a single resource system or across a diverse set of resources, are similar enough to be represented by a small class of formal models; and (ii) that the set of preferences, the possible roles of information, and individual perceptions and reactions are assumed to be the same as those found in developed Western market economies‟ (p. 15176).


process which can be influenced by many factors. In R&D the M&E component of projects or programs is, in theory at least, the means by which the effectiveness of a performance is judged.

(ii) Learning is understood as occurring in social interaction (i.e., a social theory of learning) not just in the head of an individual. Learning is driven by changes in understanding, practices and social relations of those involved.

(iii) When engaging with social learning research, researchers can adopt one of three roles – research as (i) observer (the most typical); (ii) researcher as enabler (of others) and (iii) co-researcher – as joint designer of the research process with others.

(iv) Relational capital is the special, dynamic form of capital that emerges from on-going collaborative effort (from repeated performances) and is the glue that holds together and utilises the other forms of capital (natural, social etc).

Figure 4. Social learning characterises an effective performance, including contextual improvisation; it occurs through changes in understanding and/or practices of those who work together to transform situations for the better. It is both an entity and a process (i.e. it is a duality). SLIM (Social Learning for the Integrated Management of water at catchment scale) was a European Union funded Fifth Framework research program; a heuristic is something conceptual that aids learning.

This reflection from R1 based on a field trip to Burkina Faso can be interpreted through a social learning lens:

“Something I found out later, which is relevant here: Unlike the .. team in Mali, the different groups in … are not yet 1 real team (1). This originates from the fact that 2 different projects have been merged into the current .. project (2). For Mali, it was the same … team involved in both projects; For Burkina 1 project involved the team in K, whereas the other project involved the B team. (don‟t know for the Senegal and Niger cases). Although the 2 have been merged in theory, I could sense that the different teams are still not completely on the same wavelength (3). An example: the B team has more of a systems approach and proposes to work on the “cascade of interventions” comprising feed-animal-manure-soil fertility (B1); implementing all four on the experimental farms. The K team is thinking of sets of experiments (A) that address single components at the time; so one farmer could work on forages, whereas another could work on manure, according to his/her interest (B2). The latter


team is behind the “shopping list” of experiments (the famous D7), including detailed protocols. Although Z said that the D7 is … .. kept there to please the team during the merging, I think this might not be 100% true, as the K guys are still planning to go with this (although they admit it can be modified based on farmers‟ interests (4)) (R1.1).

This reflection by R1 touches on several facets of social learning theory, as is outlined later. It is very useful evidence that refers to factors that may, or may not affect, the emergence of an effective research performance. Relevant phrases are highlighted and numbered; items 1 to 4 draw on social learning theory (see below) whereas items A and B refer to the overall model of research practice:

1. This claim may relate to a failure of facilitation?

2. This statement relates to the history of the situation?

3. Relates to the theoretical and perhaps epistemological differences in the teams?

4. Relates to building stakeholding by farmers?

A. A methodology issue (see below)

B. B1 and B2 seem to represent different ways of bounding the research system and thus the components and relationships?

It would be useful to come back to this list after reading the section below about social learning.

2.3. M: Method - methodology

Most researchers are trained in ways that mean they understand „research methods‟. The following reflections from R2 exemplify this understanding by referencing „on-farm trials‟, a particular methodological approach to field research. Models are also referred to which is another methodological approach.

“On-farm trials – both trials I visited (Pouni in BF; Kolokani in Mali) were well implemented and maintained, so well done by our collaborators. BUT, their value will be limited … one largely failed due to drought; the other gave known responses; both had trees in their midst! Across AFSI West African projects, I can‟t see great returns coming from the trials, especially with a limited number of years. Best if they provide a focus for collaborator efforts, they help ground our models (APSIM/IAT) and so form the basis for engagements in the Innovation Platform discussions. In reality, much greater returns will be in accessing good trial datasets collected over many years by others … several are being offered” (R2.4)


Figure 5. Some of the differences between technique, method and methodology. (Source: Ison 2010).

R5 also refers to innovations in research methodology:

“The … project approach is quite new (looking at the whole system and using a participatory approach). Stakeholders in the whole value chain are being asked for input to variety evaluation. This is unusual for B.” (R5.1)

A research challenge is thus to design, conduct or test, and evaluate the methodology. As Figure 5 outlines, there are important differences between techniques, methods and methodology. Logframes, which play a prominent role in the CORAF/WECARD component of AFSI and many development projects comprise a series of techniques which combine to give an overall method. All too often Logframes are very methodical, i.e., sequential or linear, rather than being adapted to their context. If they were adapted then it might be possible to claim that Logframes were being used methodologically. Methodology is the enactment of method in context sensitive ways. In CORAF/WECARD the Logframes act as a type of „meta-method‟. One of the objectives of the Learning Project is to develop complementary „meta-methods‟ capable of transcending individual project methods. Some possibilities are now introduced.

The Most Significant Change (MSC) approach introduced below was developed as a response to experiences of using Logframes. Importantly MSC does not replace Logframes but extends and enhances them.

2.3.1. Most Significant Change – an adaptation

In the two AFSI meetings in which the Learning Project was discussed, several CSIRO researchers expressed some concerns about the constraints of Logframes as a sole basis for project planning and for subsequent monitoring and evaluation (M&E). For this reason an additional methodological approach to M&E is proposed for AFSI staff in the field. This is something we could learn about, and adapt together? The approach is called Most Significant Change (MSC).


“The most significant change (MSC) technique is a form of participatory monitoring and evaluation. It is participatory because many project stakeholders are involved both in deciding the sorts of change to be recorded and in analysing the data. It is a form of monitoring because it occurs throughout the program cycle and provides information to help people manage the program. It contributes to evaluation because it provides data on impact and outcomes that can be used to help assess the performance of the program as a whole.

Essentially, the process involves the collection of significant change (SC) stories emanating from the field level, and the systematic selection of the most significant of these stories by panels of designated stakeholders or staff. The designated staff and stakeholders are initially involved by „searching‟ for project impact. Once changes have been captured, various people sit down together, read the stories aloud and have regular and often in-depth discussions about the value of these reported changes. When the technique is implemented successfully, whole teams of people begin to focus their attention on program impact” (Davies and Dart 2005).7

As Davies and Hart (2005) note: MSC has had several names since it was conceived with each emphasising a different aspect. These include:

Monitoring-without-indicators

MSC does not make use of pre-defined indicators, especially ones that have to be counted and measured.

The ‘story’ approach

The answers to the central question about change are often in the form of stories of who did what, when and why – and the reasons why the event was important.

Figure 6 captures some of the key aspects of the approach, which seems highly suited to the overall Learning Project aims.

Figure 6. The Most Significant Change approach to participatory monitoring and evaluation.

7 The ‘Most Significant Change’ (MSC) Technique A Guide to Its Use’ by Rick Davies and Jess Dart


2.3.2. Social learning

In this section methodological aspects of social learning theory are explored. Examples from AFSI field visits are used as much as possible.

(i) History and pathway dependencies

History impacts in several different ways. It can explain how extant social relations in a group, organisation or nation have come about. Reading novels based in unfamiliar countries or published histories are useful and relatively easy ways to gain some insights. For a scientist how certain ideas, theories and explanations came to prevail and how these differ across disciplines is particularly relevant. For example theories of plant succession held sway until the late 1970s but then came to be questioned and replaced, in some situations by state and transition explanations of plant dynamics. Ideas relevant at one historical moment can be incorporated into institutional arrangements which account for present day features e.g. the landscape patterns on either side of the Murray River in Victoria and NSW differ because one State‟s surveyors chose true north to lay out the subdivisions and roads whilst the other chose magnetic north. R5 when in the field noted the following which illustrates this „variable‟:

“C) The relationship between breeders and extension officers is not very good. Apparently breeders like to “tell” and “order” extension officers. D) Also, the relationship between extension officers and farmers is poor. I was told many farmers see extension officers as equivalent to the police, because they come and shout at them what they have to do (farmers then don‟t do whatever they were told!). Both points C and D are probably related to colonial histories and training (my guess).” (R5.2)

It is easy to realise that people‟s history (experience) shapes how they think and act and thus what they are capable of doing at a given moment. As research involves collaboration with people with different experiences then it is easy to understand how this mix could create unfavourable initial starting conditions for a project unless purpose designed activities to create a more level „playing field‟ were pursued or some starting assumptions were explored and, if needed „unpacked‟. As outlined in the CORAF group at our first joint meeting, the initial starting conditions for AFSI as a whole had certain implications – these are depicted in the two schemas shown in Box 2.

Box 3 Some implications of AFSI initial starting conditions

Schemas developed in Learning Workshop 1 by R4 (notes to be added by R4).


This concern about initial starting conditions has also helped to shape a specific piece of research by R9 (Box 4).

Box 4. Sample Story - Researcher R9: 4 August 2011 (from a personal perspective)

Within the African Swine Fever (ASF) and Peste Petite Ruminant (PPR) projects, social aspects of the research were initially under-conceptualised and under-costed and no social scientists had been closely involved in project development. Observations and discussions during scoping field trips involving two CSIRO scientists (including one social) and ILRI personnel and other people familiar with communities and conditions „on the ground‟ made it apparent that adoption by farmers of the technical innovations to be developed in the projects would absolutely depend on achieving change in farmers‟ behaviours and those of other value chain actors, which would in turn depend on researchers engaging these people in the research and developing good understanding of their circumstances, motivations, needs and aspirations. Arising from this experience, CSIRO and ILRI collaborators have now recognised the importance of better incorporating social science into project design, as evidenced by revisions underway to project planning.

Why the story is significant The story illustrates

that shared experience (in this case, reconnaissance field work involving CSIRO and in-country collaborators) is important to coming to a shared understanding.

that shared experience can help to bridge the perspectives of people with varied disciplinary specialisation and institutional contexts, as is important for interdisciplinary research.

that social science expertise and considerations should not be treated as an „add-on‟ in R4D projects but fully integrated into project design.

Domain of change The story relates to change in organisational cultures (rather than, e.g., in „on the ground‟ project impacts).

(ii) Institutions and institutional complexity

An institution is a norm, rule, regulation, policy etc that humans have invented and that shape much of what we do either knowingly or not. The following quotes from R2 show how important certain institutions associated with visas (which are themselves an institution) are to getting the AFSI collaborations functional.

“One learning was that we easily gained a tourist visa on arrival for Mali (US$40) without the need to show any invitation letter” (R2.5)

“Just arrived in Ouaga … learnt a few things on the way (need to visit Police in Mali to get visa; costs US$220 for a visa in BF but free for official passport” (R2.6)

“we asked for a visa on arrival in Mali and were refused; which meant leaving Mali was a pain; because we had to gain a back-dated visa – potentially affecting our ability to meet our flight.” (R21.2)

In these quotes the following institutions can be found – visa, official passport, tourist visa, invitation letter. From a research perspective, the police office which manages visas may also be considered an institution.

In recently published research Phil and Ray show how systems mapping can be used to reveal the institutional complexity of a water catchment managing situation within the


Murray-Darling Basin (see Figure 7).

Figure 7. A map of the institutional complexity faced by senior managers of a CMA in Victoria (Source Wallis and Ison 2011).

(iii) Stakeholders and stakeholding

It is easy enough, and now quite common to do a stakeholder map in a situation of concern. A systems map is a good tool to use (see below) and doing it in a group, or asking people with different perspectives or „takes‟ to do one can be revealing. These can be further developed into a power analysis (e.g. see Wallis and Ison 2011). But this „variable‟ is more than understanding who the stakeholders are, or could be. It is also concerned with the active processes of building stakeholding in an issue or project in ways that enhance learning. A challenge for the learning Project itself is how stakeholding might be built given the heavy demands already made on the researchers associated with AFSI.

Strong features relating to building stakeholding comes through many of the reflective pieces that have been written in the field thus far; these include: (i) active listening – to local farmers, counterparts. When done well those involved are left with the experience of being listened to, and understood. This is a powerful way to build stakeholding; (ii) being open to the circumstances – it is possible to see this operating in terms of a researcher‟s own stakes in the research being developed, e.g. when R3 says:

“I think I must be an idiot, because travelling in West Africa is hard enough, and you have very long days. Losing my gear again on the same trip is a pain in the backside. But for some stupid reason I am still enjoying the work so much. It is full of great surprises and I have loved going to the trial sites, meeting the farmers and INERA staff, talking about sampling techniques and local cropping.” (R3.1)

(iv) Facilitation and mediation

Facilitation can be carried out by a person who may or not be trained in group process and facilitation skills. Effective leadership (in its many manifestations) can be seen as a subset of


facilitation. Facilitation can also be carried out by non-human „actors‟ sometimes referred to as a „mediating object‟. A new technology can sometimes act as, or be understood as a mediating object. Figure 8 depicts how a researcher might take an enabling role within a social learning approach (SLIM 2004).

Figure 8. Researcher as enabler/facilitator in situational transformation with other stakeholders as part of a social learning approach (Source: SLIM 2004).

R3 reported the following from a field trip to West Africa:

“The conversation was quite long, because we have to translate from English, through French to the local language and back again, so I may well have been asking them what their favourite colour hat was.” (R3.2)

This is indicative of some of the difficulties that are encountered and have to be addressed in processes of facilitation that cross language and cultural divides. To do this well requires patience and good listening skills. Ray in his experience finds trying to read the emotional underpinnings of the exchanges to be insightful.

(v) Different knowledges (epistemologies)

There are likely to be powerful local knowledges and ways of knowing that can illuminate or sometimes obfuscate attempts to generate „scientific knowledge‟. For research practice to be effective they have to be acknowledged, and as much as is possible understood. Consider the understandings which arise from Australian Aboriginal culture or that from research in the Congo by Mary Douglas (Box 5).


Box 5. Different ways of knowing and some implications

Vignette 1

Ethnographer, Deborah Bird Rose (cited in Knudtson and Suzuki 1992) articulated four

transcendent rules which shaped the „ways of knowing‟ of the Yarralin aboriginal

community in Australia. These were:

(i) Balance - a system cannot be life enhancing if it is out of kilter, and each part shares

in the responsibility of sustaining itself and balancing others.

(ii) Response - communication is reciprocal. There is here a moral obligation: to learn to

understand, to pay attention, and to respond.

(iii) Symmetry - in opposing and balancing each other, parts must be equivalent because

the purpose is not to "win" or to dominate, but to block thereby producing further

balance.

(iv) Autonomy: no species, no group, or country is "boss" for another; each adheres to its

own Law. Authority and dependence are necessary within parts, but not between parts.

Vignette 2

Mary Douglas (1973) tells an insightful story of how significant different cultural

perspectives can be in relation to „the environment‟. She says: „I worked in the Congo on

the left bank of the Kasai River among the Lele. On the other bank on the same river

lived the Bushong. ... Here were two tribes, next door neighbours, who celebrated their

cold and hot seasons at opposite points in the calendar. ... The Lele regarded the short

dry season as unbearably hot. ... They longed for the first rains as relief from the heat.

On the other bank of the Kasai, the Bushong agreed with the Belgians that the dry

season was pleasantly cool and they dreaded the onset of the first rains. .... the Belgians

had made excellent meteorological records, and I found that in terms of solar radiation,

diurnal and nocturnal temperatures, cloud cover etc., there was very little objective

difference.‟

Ways of knowing can be extended into ways of being associated with cultural practices as exemplified in this reflection by R3:

“At … I was treated on arrival to about 50 locals playing music and dancing, of which I had to take part. After our trial inspection and BD sampling I went to the village to meet the chief and there were more people with more dancing by me (unfortunately there is video evidence). I presented the chief with a gift of cola nuts and beer, and was presented with a mask and a live chicken. N‟s daughter cooked the chicken that night and it was delicious.” (R3.3)

This reflection by R3 also reveals gendered ways of knowing that have significant implications for how power, in that context, operates:

„N as leader is right for the project (she must be a strong woman, they tell me openly in front of her that women are not as important as men!)‟ (R3.4)

(vi) Social relations – relational capital

When R5 reported that the relationships were not good between extension workers and farmers (see quote above), not only was the history of the situation being evoked, but also the poor quality of the social relations within the „research system‟. With further research it is


likely that the inadequacy of the theoretical and thus practical models that extension workers were following might be revealed. This „hypothesis‟ is based on research in Australia and other parts of the world about some of the unintended consequences of the linear model of R&D. R5 suggests this is the case:

“Because of the linear approach, there is no link between the farmers and the breeders. Breeders are selecting solely on yield on their research stations, with the obvious problem that if the research station soils and environment are not representative of the farmers fields, research station yields may not be realised by the farmers (for example nutrient use efficiency, which is most likely a valuable trait, might not be being selected for on research stations if their soils are good)” (R5.3)

So this important observation could also impinge on the knowledge/epistemologies variable as well. When people work together well, over time, then changes in appreciation of each other‟s understandings and practices also occur – trust may emerge; effective performances may emerge; new understandings and explanations may be accepted; and new practices adopted. A positive change in these types of dynamics can be understood as improved relational capital – the key to good performances. It is difficult to build but easy to destroy. The three year project cycle is not very helpful.

(vii) Learning processes

Social learning approaches demand some understanding of the theoretical bases of learning as well as how it can be studied (researched) and enabled or facilitated. The following extract comes from members of the European-based LEARN group who have been researching in this area for many years:

“By theory we mean how we construct and organise concepts to form a coherent explanation of a phenomenon we want to understand. For example, if we were behavioural psychologists we might represent learning using operant conditioning – concepts about stimulation (e.g. rewards and punishments) and concepts about the learner‟s response to stimulations (e.g. repeat or avoid) which would be organised so that learning behaviour would be described in terms of a conditioning process that is based on new stimulus-response routines. To hold such a view of learning requires a certain view of the learners and the world within which they act. It is also based on a particular view of knowledge and truth.

Such a behavioural perspective is currently absent within the works carried on in the European Group of the International Farming Systems Association (IFSA). Indeed, it is noticeable that this community views learning mainly as the way people make sense of their actions with respect to particular situations or issues, whether in everyday life or in a professional specialisation, with a view to taking further action on the issue. From this perspective, practice and learning are emergent properties of peoples‟ actions. They are also constitutive of each other. Learning is understood as a process which emerges from acting in an uncertain and changing environment and which might result in the emergence of new practices or new perspectives on situations. Learning is experiential or/and social and is considered as occurring in an action-oriented practice rather than in classrooms. To quote Wenger (1998) “the concept of learning is not absent from the... office, but it is used mainly for trainees....One reason they do not think of their job as learning is that what they learn is their practice ....What they learn is not a static subject matter but the very process of being engaged in, and participating in developing, an ongoing practice." Learning is not the purpose of a dedicated practice. Rather it occurs while developing new practices or new perspectives on situations.” (Blackmore et al. 2012).


This is a large and complex field of scholarship and practice. Perhaps the main point to be made is that good science does not necessarily lead to good learning by those who need to effect change in a situation of concern. This has led some scientists to ask the question: how can my scientific findings be used to design a learning system for others (e.g. Toderi et al. 2007)? Part of the philosophy of the APSRI Group within CSIRO has been to address how modelling can enhance learning (see Whitbread et al. 2009).

2.3.3. Pathways to impact

There is an inescapable logic built into the AFSI design captured by Peter Carberry in Figure

9. The Logframe approaches adopted by AusAID and other development agencies are often something that has to be lived with and, in part, this is the case with AFSI.

Figure 9. Extracts from a presentation to the AGSI team conveying the logic of the pathways to impact in general terms (slides 1-2) and specifically for the seeds project (slide 3) with one model of the action research/learning model (slide 4).

The first figure depicts the main design logic of CORAF/WECARD which is then unpacked in respect of one project in the next two figures. The fourth of these figures, (lower right) is a model of participatory action research, which in part underpins the Learning Project and which offers also, an opportunity to break out of the strictures of the linear model.

The logic behind the BecA pathways to impact is pending clearance and will be incorporated in future revisions. As outlined three core functions or businesses are central and are tied with its anticipated impact.

Capacity strengthening through research - effectively capacity building in


biosciences research capacity through training and mentoring African scientists and students, predominantly funded by international development agencies.

Research and research related services conducted through a variety of Hosted Projects and Hosted Programs; these are predominantly funded by various clients‟ research grants and/or hosted institutions. Research related services are funded on a fee for service basis, with full cost recovery, from BecA‟s internal and external clients, within and beyond Africa.

Product incubation and innovation: Predominantly funded by clients‟ product development programs that are particularly attracted to BecA in order to more efficiently and effectively generate new products for use in African agriculture. This is a relatively new component of BecA‟s client-base but needs to be given substantial strategic attention.

A perspective on these matters is that it:

“certainly … seems CSIRO generally has defined (although we are now re-thinking/redefining this) „impact pathways‟ that have historically been depicted as „linear‟ – but I don‟t really see the AFSI projects like this (certainly not in the East) – whilst the log-frames are used, I think in practice the evolution of the projects have been much less linear; and the partnership has enabled this to happen through flexibility in project design and evolution as new partners have been identified/come on board..” (R21.2)

One of the opportunities this project provides is to widen understanding of the possible pathways to impact. There seems to be underlying differences in background theory and practice in the Eastern and Western partnerships, along with different manners of doing the science. Exploring these differences is a potentially rich vein of learning.

2.4. T: A bag of tricks – Techniques for the field

While methodologies present a general approach to inquiry into a situation, it helps to have a grab-bag of low-tech, but effective, techniques that can be easily used in the field. Many of these Techniques (and more) can be found in „Techniques for Environmental Decision Making‟ published by the Open University (UK). This is by no means an exhaustive list. One outcome of this project could be that the techniques that researchers use in the field during AFSI could be written up. We can develop a place on Confluence to do this.

2.4.1. System mapping

System mapping is the process of identifying and organising all of the elements of a particular situation. Typically, this involves thinking of all of the institutional arrangements that comprise a particular system. It works best when done in a group, to build up the most comprehensive understanding of a situation.

Materials: Table or whiteboard, sticky notes, marker pens, camera

Process: Clear a table or whiteboard and stand around, each with a marker and pad of sticky notes. A useful starting point is to talk about the various organisations involved in your system of interest. As you identify each organisation, write it down on a sticky note and paste anywhere on the table or board. Other topics to discuss include the names of projects, laws, regulations, rules or strategies – any institutional arrangement you think is relevant to the system under consideration. Once you have run out of ideas, start to organise the notes into clusters of similar types. Below is an example of a system map in draft form (Figure 10).


Mechanisms for Increasing Impact

East African Partnership

West African Partnership

FAO G20

ACIAR

Ministry

CHOGM DFAT

AfricanUnion

International

HighCommissioners

AusAIDExecutive

DFAT TravelAdvisories

Australian Embassies Ambassadors

ProjectTemplates

Review of AidEffectiveness

Partnership /Australian Government

& H. CommEngagement Strategy

ProjectEngagement

Strategy

RegionalCommunication

Strategy

Impact ofProgress Stories Media

Strategy

Capacity Buildingin Africa

Comms Program

AfricanGovernment

Briefings

CommunicationProtocols

Project Visuals

Project Videos

PapersProjectWebsite

SharepointPlatform

ProjectBrochure

LearningProject

ConfluencePlatform

BECA

ILRI

ChallengeFund

CapacityBuilding

Uganda

Tanzania

Cameroon DRC

KenyaIndigenousMushrooms

ProjectBurundi

CBPP

NationalStakeholders

CaviesProject

Swine VirusVaccine Project

RegionalStakeholders

PPRProject

AmaranthProject

AflatoxinProject

Food Securityand Rural

Development Policy

CAADP

AfricanCountries

IAR4D

InnovationPlatforms

LocalMarketsSmall-holder

Farms

FARA

APESSProject

CSIRGhana

CGIAR

Universities

ITRAD

NARS

IERIRAD

ISRA

CORAFProjects

AGROHYMET

Proposalsfrom NARS

Improved SeedSystems Project

DAFFCotton

SustainableAgricultureFlagship

PIFFSMonash Uni

UQ QAFFI

DEEDIWECARD

AusAID-CSIROPartnership

AusAIDAfricaPolicy

AusAIDScholarships

CrawfordFund

CORAF

AFSI

AusAID

CSIRO

AusAID In-houseThink Tanks

African Food Security Initiative Researching System (v1.0)

Figure 10. A draft system map of the AFSI researching system.

With a little practice systems maps are easy to do. They effectively capture a systemic snapshot in time about a particular situation, reveal your own boundary judgements (what is I and out of the system, or subsystems) and can be used as a tool to communicate with others and explore if they understand the situation in the same way, or not. For example, the following extract from R1, from Burkina Faso, could easily have been reported as a system map:

“INERA is structured in 4 departments, including (1) natural resource management and production systems, (2) animal production, (3) crop production, (4) forestry. (1) and (2) are implied in the EI project. The departmental chiefs are all based on K. Each department is divided into programs, which are commodity oriented. Different zones of the country (INERA has identified 5) will have different programs (e.g. there is a cotton program at B, but not at K). ......Together with 3 other institutes, INERA forms part of the Ministry of Research and Innovation (until very recently, this was part of the same ministry together with Education; now separate).” (R1.2)

2.4.2. Conversation mapping

Conversation mapping is a workshop technique that takes participants through „divergent‟ and „convergent‟ phases. In other words, the divergent phase is about enabling diversity of views, and the convergent phase is about condensing and synthesising those views. This is a technique designed to identify „emergent‟ themes – ideas that emerge from different perspectives.

Materials: Large sheets of paper (flip chart paper is best), sticky tape, to stick the sheets of paper together (paper masking tape is best), whiteboard markers of different colour (best to aim for one colour per person), post-it notes, of two different colours


Process: The main objective of conversation mapping is to enable a diversity of view to be expressed and written down on paper. You will want to maximise diversity because a conversation between a group of like-minded and similar individuals can give you less insight than a mixed-up group. To ensure that you achieve a good diversity of perspectives, keep in mind the following points: 6-7 people per table; Gender balance; A mix of ages, organisations, backgrounds at each table. Participants can be allocated to tables in any way you please – this can include a door list, colour coded name badges, nameplates on tables and more.

Groups should begin by writing down the „conversation trigger‟ in a circle in the middle of the paper. Conversations should start branching off from the trigger question. You can either use the same conversation trigger for each table, or assign different triggers to each table to maximise responses. Hopefully each table will end up as a colourful mess of ideas.

(2) Sticky-tape

along joins

(1) Start with four

sheets of paper

(3) You can add extra

sheets of paper to this

edge if needed

(4) Flip the sheet

over when done,

so the sticky-tape

is underneath

Figure 11. A completed conversation map by AFSI researchers.

Once the conversation has been exhausted or time is up, participants move into the „convergent phase‟ of conversation mapping. One way to do this is by identifying „emergent themes‟ – these are ideas that appear in more than one part of the conversation that connect conversational strands together. It can be useful to try and identify emergent themes that address a specific point – for example: opportunities, needs, issues, threats, strengths, weaknesses. The example above uses two


different colour post-it notes to identify opportunities and issues (Figure 11).

There are many opportunities to use conversation mapping. As R21 says: „I‟m going to use the „conversation mapping‟ exercise at the … team annual retreat in a session I‟m running on „innovative ideas for communication and engagement‟ …… will let you know how it goes.‟ (R21.3)

2.4.3. Multiple cause diagramming

Figure 12. Some of the multiple causes and effects of traffic growth (Source The Open University (UK), TU863)

A multiple-cause diagram is used to explore why a given change or class of events tends to occur. It is not intended to predict behaviour other than in a general sense, but it may be used to develop your understanding of the way in which aspects of a situation may change or be changed.

The components of a multiple-cause diagram are:

phrases

arrows, which may be labelled

title.

Each arrow carries the meaning:

[phrase at the tail of the arrow] causes/affects/leads to [phrase at the head of the arrow] (see Figure 12).

The phrases may just be the names of particular objects, but it is usually preferable to consider the relevant properties associated with those objects. Phrases may also represent events. The diagram may be entirely sequential, that is, all sequences lead one way to an effect, or there may be loops, whereby a change in properties at one point may affect the properties of an item further back in the chain.

Guidelines

1 In constructing a multiple-cause diagram you normally begin at the object/property/event to be explained and work backwards. There can be more than one such end-point. Sometimes some of the intermediate effects or causes are as interesting as the supposed end effect.

2 Because the arrows may represent different kinds of contribution/cause, it may be helpful to label them.


3 It is not necessary to put enclosing lines around phrases, although if it improves clarity you can. Boxes, with their implication that we are dealing with a „designed system‟, are best avoided.

4 It is useful to check that the nature of each individual causal link is clear. Insert any necessary intermediate variables/factors if not.

5 It is not necessary to indicate a system boundary on a multiple-cause diagram. However, drawing such a diagram may well develop your ideas about where to draw a boundary.

6 It is important to remember that this type of diagram, while superficially resembling an influence diagram, is different in that it can be read sequentially, rather than as a snapshot representation.

2.4.4. Rich pictures

Rich pictures are a technique from a branch of systems theory called Soft Systems Methodology (Checkland, 2000). They are used to portray an individual's perspective on a situation in a picture. Checkland (2000; 22) wrote that “...pictures are a better medium than linear prose for expressing relationships”. Some examples from AFSI are given below (Figure 13):

Figure 13. Two rich pictures from the first AFSI Learning Project workshop. Some recurring elements in rich pictures from this workshop include outlines of maps of Africa and Australia, elements representing travel between the two continents, time pressures (represented by clocks and calendars) and various people involved in the initiative.

To create a rich picture, you only need coloured markers and some flip chart paper. You are attempting to draw your perspective of the situation, so you should include yourself in the picture. Try to avoid using too much text, or creating links between elements of the picture. It is useful for keeping records to label the rich picture with your name, the date and location. Rich Picture can be used as part of research to capture initial concerns (benchmarking), for ongoing monitoring by making rich pictures regularly; for metaphor exploration and when done in pairs as part of team building and collaborative learning.

The real value of rich pictures comes from the explanation given to others. One CSIRO researcher (R1) gave the following elaboration of their rich picture (not shown) produced at workshop 1 of the learning project:

“I‟m standing to the right of what is meant to represent a farming system. Light bulbs represent researchers (and the bright ideas they sometimes have...). The Venn


diagrams above the farming system represent “innovation platforms”, and on the top left I‟ve drawn a scientific paper. In the right bottom corner there‟s three continents (Africa, Australia, Europe), with links to family in Europe. There‟s another person holding what is meant to be a camera. He‟s my partner, who‟s a film maker and does not yet know where he will make his next film.

So, basically, what this all means, is me juggling work and personal relations across three continents, and hoping that in the West African projects, some good work outputs will be achieved by having bright ideas, building networks with partners, and engaging in the local innovation platforms.” (R1.3)

2.4.5. Root definition statements: PQR

This is another tool that can be extracted from SSM (Checkland and Poulter 2006). To use it effectively you have to let go of the „real world‟ situation of concern for a moment and ask the question: what would a system look like, which if it were to exist, might make the situation better?” Better could mean improved or more understood, or improved systemically.

Moving into the Conceptual World

Describe a system, which, if it existed, would make the situation better.

P (what) needs to be done

Q by means of…(how)

R in order to… (why – the ultimate purpose)

Here is an example of how this tool could be used built from some reflections by R1:

„S then presents the framework as conceptualized at the … meeting. We agree that although the farm (l‟exploitation in French) is our study unit, we should not consider it in isolation from markets/value chains, institutions and policies, other strategies & motivations like off-farm work, gender, household socio-economic aspects and labour.

The team expresses the need for support with the modelling activities. They need to know what the models are like to be able to understand the data requirements. As there is not enough time during the meeting to give a quick overview of IAT, we agree that I will prepare an overview document and distribute the APSIM/IAT protocols and baseline questionnaire. In the team, ..and .. would be the modelling guys.‟ (R1.4)

From this reflection a possible „system of interest‟ could be:

„A system to study farms (l‟exploitation) embedded in markets/value chains, institutions and policies, other strategies & motivations like off-farm work, gender, household socio-economic aspects and labour by means of modelling in order to enhance overall farm productivity‟

In this notional system of interest description (called a „root definition‟) the P, Q and R are:

P = farms studied in context

Q= by means of modelling

R = in order to (produce scientific understandings) that can increase overall farm productivity.

This particular system of interest is neither right nor wrong – it is a device to tease out how what, why and how are understood in systemic terms by those involved. It can be linked to


the next tool, also part of SSM.

2.4.6. Identifying purpose: CATWOE / TWOCAGES

The following mnemonics have been developed from action research to test the adequacy of root definitions for a particular context. As much as anything these are learning devices and processes for those involved. The original CATWOE of SSM has been altered to TWOCAGES by some systems practitioners. It would be useful for you and your team members to try using the root definition (PQR) above to imagine possible answers to each of the elements of TWOCAGES. There are often not right answers to these only different answers some of which are better for the context.

TWOCAGES

T = transformation

W = world view

O = owner

C = client

A = actors

G = guardian

E = environment

S = system (a conceptual model based on activities)

In systems theory the idea of transformation is critical – it is what any system does (i.e. transforms something (inputs) into something else (outputs). Transformations can be material or abstract. In SSM it is important to consider the measures of performance of a system of interest. Five generic measures which need to be elaborated in context specific ways have commonly been used.

Measures of performance:

e1= efficacy

e2 = efficiency

e3 = effectiveness

e4 = ethicality

e5 = elegance

The different measures of performance can be related to what, why and how for any given systems of interest. Efficacy, does it work, relates to what. Efficiency relates to the how. Effectiveness relates to why. In systems theory what is the system, how is a sub-system and why is a suprasystem but these are not fixed and one person‟s what might be another person‟s why!

For example the following measures of performance might be why‟s at the AFSI system level, but not make much sense at the level of an individual project:

15% increase in household‟s purchasing power by 2013

The mortality rate among small ruminants and poultry is reduced by at least 50 %

Dairy production is increased by at least 50 %

Productions of Cereal Livestock Tree systems are improved by 30% in the project


sites

2.4.7. Interviewing

It is not possible here to describe all that one would find in a text on qualitative research methods. The important thing to realise is that field-based interviews and observation when social, institutional and biophysical aspects are potentially important will be improved if some background reading on interviewing and qualitative data gathering techniques is undertaken. For example it is important to know the difference between: (i) structured interviews; (ii) in-depth interviews; (ii) semi-structured interviews and (iv) narrative interviews.8 There are wide-range of tools and techniques for data gathering within the Rapid Rural Appraisal (RRA), Participatory Rural Appraisal (PRA) or Participatory Learning and Action (PLA) repertoires. See http://pubs.iied.org/ or one of the many web-sites on line.9

2.5. S: The research situation(s)

Most agricultural and environmental scientists because of their background and training tend to place most focus on the research situations. Situations are different, interesting or they are said to contain problems that need fixing or improving or because something of concern exists in the situation. The reflective pieces to date have rich descriptions about the various research situations e.g. These examples of research topics from R1 are essentially concerned with „typical‟ researchable situations:

- supplementary animal feeding blocks, made of local ingredients such as cowpea, maize and Faidherbia seeds and foliage

- animal market research. With the help of Diobass, a group of livestock keepers in a village has investigated the constraints and possibilities for animal marketing, even in an international context (Ivory Coast and Ghana have high demand for animals raised by their northern neighbours). Organization in unions has helped to form the bridge between traders and producers so that fair prices are obtained.

- “Zai-forestier”; Forestry Zai to aid vegetation restoration. Animals eat the tree seeds, digestions breaks the dormancy. Manure (containing the seeds) is added to the Zai pit. The first year, a cereal is grown while the tree seedling is developing.

In Ray‟s book „Systems practice: How to Act in a Climate-change World‟ considerable attention is paid to the processes by which situations are understood and named. A main argument is that we all have choices about how to engage with situations and „describing or discovering reality‟ is but one of many choices. When we experience situations with particular characteristics it makes sense to engage with these in particular ways rather than always in the same way. There are limitations to naming situations as „problems‟ (who says so? Is one person‟s problem another‟s opportunity?) and explore what can be gained by thinking of them as „complex‟, or „contested‟, or „wicked‟ or „messy‟ or applying other „invented‟ concepts such as „complex adaptive system‟, „social-ecological system‟ or merely „system‟.

Science has developed its own language to describe engagement with, and thus the nature of the situation e.g. fundamental knowledge, applied understanding, scientific facts etc. We

8 A useful background text is Thomas, A. and Mohan, G. eds (2007) Research Skills for Policy & Development.

How to find out fast. The Open University with Sage Publications

9 Sites such as http://samgar2007.blogspot.com/2010/08/participatory-rural-appraisal-tools-and.html can be

explored; it would be useful to build up some knowledge of the best sites across the AFSI community.

http://pubs.iied.org/

http://samgar2007.blogspot.com/2010/08/participatory-rural-appraisal-tools-and.html


all have choices about how to engage with situations and in the context of IAR4D in particular, it makes sense to maximise the effectiveness of these choices.

In Operations Research these concerns are commonly referred to as PSMs (problem structuring methods). In a recent special issue their concerns are described as:

„Problem structuring methods (PSMs) are a collection of participatory modelling approaches that aim to support a diverse collection of actors in addressing a problematic situation of shared concern. The situation is normally characterised by high levels of complexity and uncertainty, where differing perspectives, conflicting priorities, and prominent intangibles are the norm rather than the exception. Typically, the most challenging element in addressing these common managerial situations is the framing and definition of the critical issues that constitute the problem, as well as understanding the systemic relationships between these issues. PSMs provide analytical assistance through „on-the-hoof‟ modelling, which are used to foster dialogue, reflection and learning about the critical issues, in order to reach shared understanding and joint agreements regarding these key issues‟ (Shaw et al. 2006).

Four considerations relating to engaging with situations of concern are now outlined. Again, this is not all that could be taken on board, but is an important start.

2.5.1. Managing strategic risk and reputation

This relates to CSIRO as a whole, to the Flagship, to AFSI and to individual researcher reputation. It also has a strong ethical dimension as well as health and safety protocols. Taking researcher responsibility seriously, given many of the systemic failures associated with research for development in the past, demonstrates to others – funders, partners, international collaborators – both the seriousness and ethicality of the CSIRO stance.

In the next iteration of this document we hope that there will be a section, developed amongst AFSI researchers, that addresses how best to discuss this Learning Project with partners (i.e., reputation issues) and to enable more formal „buy in‟ by partner researchers if they are interested. AS R21 commented:

“I can really see that this Learning Project is a responsible element to our work in AFSI; and to strengthen Australian investment into RfD [Research for Development] in the future.” (R21.4)

Protocols for publications and conference presentations based on this project also have to be developed and agreed.

2.5.2. Framings

All policy and practice positions rest on underlying structures of belief, perception and appreciation which are called „frames‟ (Schön and Rein 1994). There is growing awareness of the importance of understanding historical frames and actively choosing new ones. For example, within the SAGReP (Systemic & Adaptive Governance Research Program) at Monash and in the UK our recent concerns have mainly been with situations associated with water, river and catchment managing and climate change adaptation. In recent history understanding and managing of rivers has been heavily influenced by hydrologists, engineers and physical geographers. In the past a river or a water catchment was rarely understood as if it were a human activity system. But having made this shift a river catchment or watershed exemplifies what some describe as a multi-stakeholder situation. But it is a multi-stakeholder situation of a particular type in that the connectivity, or lack of it, between humans and the biophysical dimensions are of critical importance. Thus some would choose to describe a catchment as a coupled socio-ecological system. For those who are not aware there is a growing global water crisis that is manifest in similar yet specific ways in almost all countries. It is likely that in many areas climate change will make the current situation worse. Both globally and locally these situations have many or all the


features of situations that others have described as wicked problems, messes or complex adaptive systems. Aware of this history and drawing on a literature associated with the „framing‟ of such situations as „resource dilemmas‟ we now choose to characterise river catchments in terms depicted in Figure 14. This is a framing choice. Our aim is to make the situation more tractable to research which leads to improvement.

Figure 14. Making choices about how to ‘frame’ a situation of concern for research action. (Source: Ison 2010).

„Framing‟ is a key issue because of:

the initial starting conditions it creates

the pathway dependencies that become built-in

the observed failure to frame appropriately e.g. „wicked situations‟

the constraints to innovation that framing failure creates, particularly though limiting choices

Some examples of how „framing‟ works include:

how situations are understood:

„wicked‟ or „tame; catchments as natural, hydrological, or social systems?

how theories (implicit; explicit) work:

theories of change

the nature of knowledge

causality – linear, circular, systemic

how language – particularly metaphors – work

metaphors of human communication

evolutionary metaphor structures – e.g. container metaphors


implications for processes of categorisation – dualism c.f. duality

An example of metaphors for human communication (which rest on different theoretical assumptions) include:

(i) The container metaphor

(ii) The conduit metaphor

(iii) The control metaphor

(iv) The transmission metaphor

(v) The war metaphor

(vi) The dance-ritual metaphor

There is a need to be aware of the entailments of each framing as they carry different practical implications (Krippendorff 1993). Recent empirical research demonstrates that an individual‟s reasoning about complex issues is heavily influenced by „even the subtlest instantiation of a metaphor‟ that then affects how „they gather information to make „well-informed‟ decisions‟ (Thibodeau and Boroditsky 2011).

For example, two clusters of metaphors for framing communication in the situation arose in workshop 1 of the Learning Project. The first cluster was about “getting the message out”, “get[ting] that information and education out into the field” and “program roll-out”, which are examples of both the container metaphor and the transmission metaphor, implying a one-way transfer of discrete packets of information.

The second, contrasting, cluster included “communication that is two way” and “policy dialogue”, which are examples of the transmission metaphor and the dance-ritual metaphor, as they imply the generation of information by more than one actor.

A classic framing dilemma in agriculture, made apparent by Gordon Conway‟s work on agro-ecosystems analysis (Conway 1983; 1984; 1985; 1987) has been the debate over research for productivity enhancement and how this relates, if at all, to other measures of system performance, which Conway named as stability, efficiency, sustainability and equity (see Pearson and Ison 2007 where these ideas are explored).

2.5.3. History of situation

The point to be made here is that history is important in „framing‟ situations. A Chinese saying is that „anyone who does not appreciate the history of their circumstances remains but a child‟. In particular, history can condition behaviour, create patterns which are not transparent or seem immutable and thus lock people in situations into particular pathways.

2.5.4. Patterns and trends

These are familiar notions to most scientists but not always in relation to how they can be used to purposefully frame situations or to better understand historical framings. Conway, in his process of Agro-ecosystems Analysis (1995) developed „pattern analysis‟ as a key part of the process (Figure 15). As depicted in the figure the key patterns of concern in engaging with, and thus understanding a situation, were space, time, flow and decisions. Rapid and Participatory Appraisal and PLA (Participatory Learning and Action) all elaborate, potentially, on this approach.


Figure 15. Pattern analysis as used in agro-ecosystems analysis (Source: Conway 1985)

In work published in Ison and Russell (2007) we sought to understand the history of the „social construction‟ or framing of the semi-arid rangelands of Australia, particularly the NSW Western Division, through use of a modified pattern analysis which sampled the historical literature at decadal intervals (Mackenzie 2007). Historical fiction can sometimes be used as a proxy but as noted on this clip (http://vimeo.com/26469276) much African „knowledge‟ is part of an oral tradition, which may require other methods.

2.6. C: Scaffolding our joint learning – Confluence

Most of us reflect on our day-to-day experiences privately in our own minds. We may share our insights by talking to each other, or sending around an email.

“It is great to see all the email reports resulting from everyone‟s experiences in Africa” (R2.7)

https://legacy.open.ac.uk/owa/redir.aspx?C=9ac0f8e878be47d8b65854cc245bf700&URL=http%3a%2f%2fvimeo.com%2f26469276


Sharing our learning experiences is a fundamental component of the Learning Project, but one that requires action! Sharing our learning experiences is also vital to the AFSI M&E program and communication efforts; consolidating these into one system is important and can enable efficiencies of time and effort.

We have set up a collaborative online environment, called Confluence, which is designed around the idea of personal and shared spaces. Essentially, each member of the project has their own personal space that is completely private and can be used to collect ideas, store copies of emails, upload photos, audio or video, and to tag and organise this content. Once you are comfortable with sharing some of this information, you can move it to the AFSI Community – a shared space where you can define which individuals can view or edit your material.

An added advantage of using Confluence is the powerful search function, which can be used as a way of synthesising information.

Access Confluence at: https://confluence-vre.its.monash.edu.au/display/AFSI/AFSI+Home

3. Levels and dimensions of learning

Learning has many dimensions, from an individual to a whole organisation. In his book The Fifth Discipline, Peter M. Senge describes learning organisations as:

“organisations where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning how to learn together.” (Senge, 1990; p.3)

Here we introduce two additional elements of working jointly with other projects and regional partners: O – other researchers and partners, and A – assimilating the learning.

3.1. O: Other researchers and partners

In AFSI, learning extends beyond the individual to project teams (Figure 16), programs (Figure 17) and the whole of AFSI (not shown). This includes CSIRO researchers, partner researchers and organisations.

Members of a project would understand the same situation in different ways through the different frameworks, methodologies and tools that they employ.

https://confluence-vre.its.monash.edu.au/display/AFSI/AFSI+Home


Figure 16. An example of team learning in a project team. This could include two or more researchers and partners interested in a particular situation.

Figure 17. A representation of learning across a whole program.

3.2. A: Action research, participatory action research and systemic action

research

The Learning Project has been largely motivated by the positive experiences of action research approaches within CSIRO, including previous research for development activity. Figure 18 is derived from a presentation made by Peter Carberry at the AFSI No.1 workshop. Drawing on Oquist (1978) different approaches to research are portrayed in a typology in which outputs and contexts of action change. Naturally methods also change. However, regardless of approach each can be done rigorously…or not. Our aim is to pursue what we do with as much rigour as we can muster.


Figure 18. A typology of research approaches, following Oquist (1978).

Some typologies, including this one are worthy of critical scrutiny and more in-depth inquiry than is possible here. If there is demand it may be possible to develop a workshop on different research approaches, including the many different variations of action research (including the one depicted in Figure 9). For those interested the following reference is recommended:

Reason, Peter & Bradbury, Hilary eds (2008) The Sage Handbook of Action Research, Participative Inquiry and Practice, Sage Publications, Los Angeles.

Another variation of Figure 18, developed and used by the Hawkesbury Group in Australia is shown in Figure 19. From a practical point of view the researcher moves up and down the spiral according to context. There is no intention to convey that one position is better than another.


Figure 19. The Hawkesbury spiral of research approaches relating to different forms of learning.

4. Assimilating the learning

4.1. A: Assimilating the learning

To assimilate learning across a diverse disciplinary and gendered group engaged in research in different cultural contexts requires language and theories to begin to make sense of the diversity. In part this can be understood as seeking emergent themes and/or patterns. The act of assimilation in the purposeful pursuit of learning amongst members of a research group, team, program or innovation platform can be understood through the lens of social learning theory. The effective assimilation and reporting of the learning can BE the effective performance. One of the main arguments advanced in these notes is that to effectively assimilate learning requires an expansion of boundary around exactly what constitutes our research concerns and being more aware of how the role the researcher adopts is critical to IAR4D. This expansion of possibility is depicted in Figure 20 where no mode is „right‟ but different, thus carry different implications as well as skills and understandings to enact.


Figure 20. Different modes of using the theoretical framework proposed here in research practice based on cyber-systemic theoretical traditions (Source: Ison 2010).

In reading this figure in is useful to appreciate that any move towards the bottom right-hand box is concerned with an expansion of possibility, not a negation of any of the other positions. It could be claimed that the ultimate way of being ethical is to act to increase the viable choices that stakeholders have in their situations of concern.

5. Protocols, ethics and cultural sensitivities

Ethics clearances are now underway at both Monash and in CSIRO for the Learning Project. As every project has to have ethics clearance you will no doubt be learning more about what is required. In Box 6 is an extract from the consent form prepared for the Monash ethics document which related to our joint use of Confluence. Consent forms have also been prepared for workshops and other group activities and another for interviews with participants.

I understand that material uploaded to my personal page on Confluence is private and unable to be accessed by anyone else. Material uploaded to shared pages will be visible to other AFSI research staff and is to be used for Monash – CSIRO AFSI collaborative research.

I understand that my participation is voluntary, that I can choose not to participate in part or all of the project, and that I can withdraw at any stage of the project without being penalised or disadvantaged in any way.


Box 6 Extract from the Consent Form to be signed by all AFSI collaborators using Confluence

I understand that any data that I as co-researcher extract from Confluence for use in reports or published findings will not, under any circumstances, contain names or identifying characteristics unless prior written agreement has been obtained from the person(s) concerned.

I understand that any information I provide is confidential to the AFSI-Confluence research community, and that no information that could lead to the identification of any individual will be disclosed in any reports on the project, or to any other party.

I further understand that protocols for publication and other use of data from the Confluence site will be developed and agreed amongst the research team.

I understand that data from Confluence will be kept in a secure storage and accessible to the research team. I also understand that the data will be destroyed after a 5 year period unless I consent to it being used in future research.

At this stage the Learning Project per se is bounded within CSIRO and Australian-based collaborators. That does not mean that the boundaries will not change. But from an ethics and protocols point of view the ethics clearances for your actual project will primarily guide your actions in the field. As we wish to encourage authentic reflections based on your experiences Confluence has private pages where you can write and post what you want. But collectively we will have to agree protocols that cascade out from the public site in Confluence to public documents and presentations that could be read or heard by anybody. The extract above is a useful starting point, as is, I hope the style adopted here in the use of material from the field. It is not the role of this document to go into detail about cultural sensitivities in the different partner countries. However, within the Learning Project there is a need to recognise that there is cultural diversity within the AFSI team and that with sensitivity this can be appreciated and used to enhance our overall learning.

Ultimately being ethical is about being responsible. Sometimes to be responsible the conditions for you to be response-able need to be created. We hope this document helps with the latter. If not please take responsibility to help make it better.


6. References

Blackmore, C.P., Cerf, M., Ison, R.L. and Paine, M. (2012) The role of action-oriented learning theories for change in agriculture and rural networks. In Ika Darnhofer, David Gibbon and Benoit Dedieu, (eds). The farming systems approach into the 21st century: The new dynamic. Springer, Berlin. (In Press)

Checkland P. (2000). Soft Systems Methodology: a 30-year retrospective. Syst. Res., 17:11-58.

Checkland, P.B. and Poulter, J. (2006) Learning for Action, John Wiley & Sons, London.

Conway, Gordon (1983) Agroecosystem Analysis. ICCET, Imperial College, London. 51pp.

Conway, Gordon (1984) The organisation of an agroecosystem analysis workshop. ICCET, Imperial College, London. 19pp.

Conway, Gordon (1985) Agroecosystems Analysis. Agricultural Administration 20, 31-35.

Conway, Gordon (1987) The properties of agroecosystems. Agricultural Systems, 24, 95-117.

Ison R (2010) Systems Practice: How to Act in a Climate-Change World, Springer, London.

Ison, R.L. & Russell, D.B. eds (2007) Agricultural Extension and Rural Development: Breaking Out of Knowledge Transfer Traditions. Cambridge University Press, Cambridge, UK. 239p.

Krippendorff, K. (1993) Major metaphors of communication and some constructivist reflections on their use, Cybernetics & Human Knowing, 2(1): 3-25.

Mackenzie, A. (2000) From theodolite to satellite: land, technology and power in the Western Division of NSW. In Ison, R.L. & Russell, D.B. eds (2007) Agricultural Extension and Rural Development: Breaking Out of Knowledge Transfer Traditions. Cambridge University Press, Cambridge, UK. pp. 80-102.

Milly P, Betancourt J, Falkenmark M, Hirsch R, Kundzewicz Z, Lettenmaier D, Stouffer R (2008) Stationarity is dead: Whither water management? Science 319, no. 5863, pp. 573-574.

Ostrom E, Janssen M, Anderies J (2007) Going beyond panaceas. Proceedings of the National Academy of Sciences of the United States of America 104: 15176-15178.

Pearson, C.J. & Ison, R.L. (1997). Agronomy of Grassland Systems. 2nd Edition Cambridge University Press, Cambridge, UK. 169 pp.

Senge,P. (1990) The Fifth Discipline: The Art and Practice of the Learning Organisation, Century Business, London.

Shaw, D., Franco, A. and Westcombe, M. (2006) Problem structuring methods: new directions in a problematic world. Journal of the Operational Research Society, 57, 757– 758

Schön, D.A. and Rein, M. (1994) Frame Reflection: Toward the Resolution of Intractable Policy Controversies. New York: Basic Books

Thibodeau, P.H. and Boroditsky, L. (2011) Metaphors we think with: The role of metaphor in reasoning. PLoS ONE, 6 (2) e16782 (see www.plosone.org)

Toderi, M., Powell, N., Seddaiu, G., Roggero, P.P., and Gibbon, D. (2007) Combining social learning with agro-ecological research practice for more effective management of nitrate pollution. Environmental Science & Policy 10 (6), 551-563.


Whitbread, A.M., Robertson, M.J., Carberry, P.S. and Dimes, J.P. (2010) How farming systems simulation can aid the development of more sustainable smallholder farming systems in southern Africa. European Journal of Agronomy 32, (1), 51-58.


Annex 1. A systemic set of prompts for learning in the field Based on the proposed learning project conceptual framework

Notes:

This is designed to be used in conjunction with the 'Notes for the Field'.

Start at the top-left: decide how you would like to record your reflections. The attached template might be useful, or you may choose to record your reflections in a different format.

If you choose to use it, the template is designed to be filled out electronically.

These are not an exhaustive set of prompts, so feel free to innovate and adapt these to your circumstances.

Think about how to best capture your learning before, during and after the field (e.g. template, ppt, photos, blog, confluence, etc...)

Identify key stakeholders

Explore if different stakeholders name the problem differently

Ask if there are different framings of the situation

Describe how you and/or others see the situation

Comment on the quality of relationships in your research system

Identify key relationships to be developed/ sustained

Monitor how your own understandings change while in the field

S

Monitor your own experiences, including enthusiasms, excitement, frustrations and fears

P

Name methodological approaches and judge their relevance to context

Suggest revisions to methodology

Reflect on techniques in use

Introduce/use new relevant techniques

Judge effectiveness

M

T

Identify which framework(s) are in play

Are these frameworks fit for purpose?

Inquire into relevance and efficacy of IAR4D and innovation platforms in your context

F

Consider how your learning can be assimilated into: (i) your own practice; (ii) your project; (iii) your program (e.g. CORAF/BeCA);(iv) AFSI; and, if relevant, (v) CSIRO-AusAID collaborations

Implement strategy – next cycle or level of activity

Record insightful stories and/or metaphors

S: SituationP: PractitionerM: MethodologyT: TechniquesF: Frameworks


Learning Project Template

1. Think about how to best capture your learning before, during and after the field (e.g. template, ppt, photos, blog, confluence, etc...)

2. Consider the situation (S):

2.1. Identify key stakeholders

2.2. Explore if different stakeholders name the problem differently

2.3. Ask if there are different framings of the situation

2.4. Describe how you and/or others see the situation

3. Comment on the quality of relationships in your research system

3.1. Identify key relationships to be developed/sustained

4. Consider your own personal experiences (P):

4.1. Monitor how your own understandings change while in the field

4.2. Monitor your own experiences, including enthusiasms, excitement, frustrations and fears

5. Consider methodology (M):

5.1. Name methodological approaches and judge their relevance to context

5.2. Suggest revisions to methodology


6. Consider techniques (T):

6.1. Reflect on techniques in use

6.2. Introduce/use new relevant techniques

6.3. Judge effectiveness

6.4. Record insightful stories and/or metaphors

7. Consider frameworks (F):

7.1. Identify which framework(s) are in play

7.2. Are these frameworks fit for purpose?

7.3. Inquire into relevance and efficacy of IAR4D and innovation platforms in your context

8. Consider how your learning can be assimilated into:

8.1. Your own practice

8.2. Your project

8.3. Your program (e.g. CORAF/BeCA)

8.4. AFSI

8.5. If relevant, CSIRO/AusAID collaborations

9. Implement strategy – next cycle or level of activity

9.1. What follow-up actions are required by whom?


Annex 2. Trip Report to Mali and Kenya (7-20 November 2011) and

Other Reflections

Richard Stirzaker

23 December 2011

This report serves four purposes; three that Richard as author has identified:

1) Trip report for Staff International Travel System (SITS)

2) My reflections on the four West Africa farming systems projects after ten months on the job (Mar – Dec 2011)

3) A contribution to the learning project: in response to Ashley‟s comment that we can‟t record everything, I will put some interpretations on my experience thus far to generate some topics around which to build further discussion

and a fourth, from the perspective of the Learning Project:

4) To exemplify how a reflection on a field trip i.e., notes from the field can be used to engage in substantive issues which can form the basis of on-going action research.

The first part of the November trip was the trial review of the six CORAF projects held in Bamako. It was a „trial review‟ because the planned formal review was cancelled due to unavailability of key reviewers. A trial review was deemed more appropriate, given that each of the partners had just received, or was in the process of receiving, their first project funds10 (this excludes the Seeds project which started in April 2011).

The review consisted of six project summary updates from the coordinators, a session on IAR4D, a field trial to look at one of the Seed Systems sites (Kolokani, 2 hours north of Bamako), a session on ethics, a session on communications and finally a strategy to take to the review, which will take place in April. Overall there was a lot of useful discussion, which contributed to an enhanced shared understanding of what we are trying to achieve together. The field trip was very beneficial, not least to familiarise ourselves with the country and to hear first hand from farmers. We came away from the three days feeling that the effort had been worthwhile.

My focus in this report is on the four farming systems projects. I was struck again at how different these four farming systems projects are from the other two (Seed systems and Ticks). The latter projects have defined scope and objectives, whereas the former are still largely unbounded. Herein lays some of our current difficulties and probably our biggest opportunity.

The farming systems and short project titles are:

(i) Dual purpose legumes

(ii) Ecological intensification

10 We had expected all the projects to start in April soon after the formal launch meetings. In

retrospect this was somewhat naïve, although it has been suggested that CORAF was able to get the contracts with the lead institutions, the sub-contracts with the collaborating institutes and the money flowing in six months – faster than the CSIRO system could have done it.


(iii) CerLiveTrees

(iv) Association for the Promotion of Livestock in the Sahel and Savanna (APESS)

….. my confidence that these projects can achieve something worthwhile has been gradually increasing. I feel that we are crawling out of a hole. To begin the substantiation of this claim, I want to spend a little time describing the hole.

First, the proposals are somewhat of an enigma. All proposals give a similar description of the basic dire and declining agricultural situation in West Africa. This analysis is paraphrased and reworded again and again under each proposal subheading. My main problem is that the goals are lofty (for example)

15% increase in household‟s purchasing power by 2013

The mortality rate among small ruminants and poultry is reduced by at least 50 %

Dairy production is increased by at least 50 %

Productions of Cereal Livestock Tree systems are improved by 30% in the project sites, but the means of achieving such goals are vague (for example)

By optimizing and evaluating synergetic interventions

The project will develop attractive options and complementary tools, strategies, and identify investment needs for improved, integrated crop-livestock system

By better integration and more intensification

I have tried re-reading proposals, reading sections very slowly and making short summaries. None of the above has helped me to identify the real substance of the proposals i.e. where the innovation lies. After talking to our partners, reading the literature and seeing more of West Africa I‟m beginning to get a better feel for why this is so. There has been no clear history of adoption of technology so there is no clear starting point. All options remain on the table.

The lowest point of the hole we are now climbing out of would have to be the grand project launch meetings in Ouagadougou in April. I know it‟s fashionable to decry the Logframe, but it‟s important to get some insight into why it was unhelpful.

I was actually looking forward to the Logframe turning the somewhat verbose proposals into something concrete, achievable and measurable. This did not happen. None of the three projects completed their Logframe over the allotted three days in April. We extended the deadline to the end on the month. No project completed. We extended the deadline to the end of May. No project completed. We then stopped asking in case this was causing a delay in contracting.

In late November I asked X to send me all the completed Logframes which (should) form the basis of the contracts. I received an unfinished Logframe for one project and nothing from the rest apart from a cut down version that was part of the original proposal – modified post the launch meetings. There had also been some use of the cut down versions for budgeting purposes.

So what‟s the problem with the Logframe? Essentially it asks us to break the overall project objective into specific objectives. Each specific objective is further broken down into result areas. To achieve each result area we need to break them down into tasks. To achieve each task we need to complete certain activities. We then have to detail the exact resourcing and time allocations to each activity.

Let‟s assume that we have two specific objectives each with five result areas, each requiring


the completion of five tasks made up of five activities - then we need to detail 5 x 5 x 5 x 2 = 250 activities. The inexorable “if-then” LOGIG of the LOGframe says that if we just do these 250 activities (and tick the boxes along the way) we get our overall objective. In other words a $2M investment into activities translates into 15% increase in the purchasing power of millions of farmers. The value proposition is unequivocal.

Our problem is that the somewhere between the scientist‟s lab, the farmer‟s field and the national statistics, the „if-then‟ logic breaks down.

Peter C has oft repeated that our system analysis tools are our competitive advantage in West Africa. I agree, but I add three cautions

1) having worked through some of the papers of Giller, Titonell, Herrero, Rufino et al it is clear that there has been a substantial amount of farming system modelling (admittedly focussed in east Africa). We need to better understand how this work has been used and its impact thus far

2) there is a big difference between farming systems analysis and livelihood analysis11

3) we have not built the link between systems analysis and IAR4D12

I believe that our strength in systems analysis needs to be realised within the R4D framework utilising the so-called “Innovation Platforms.” A short piece on IAR4D is in Annex 3 and on the CORAF website (see http://www.coraf.org/English/CS.html ). 13

When we talk innovation there are essentially two types. First there is the product innovation (technological) which gives us new tools to do new things. Second there is process (institutional) innovation which is about „how we get things done‟. We need to do both together.

We use the term “innovation” lightly and again there are two types. There is innovation that is „new to the firm.‟ This is essentially applying existing knowledge in new situations. Then there is innovation which is „new to the world.‟ This is the stuff of breakthroughs. It‟s said that 90% of the benefit of innovation comes from the first type, so we are justified in putting everything on the table, even if it is not considered particularly „new‟.

FARA give us their definition of innovation

„new ideas, technologies or processes of doing things

doing old things in new ways to ensure greater efficiency a social process of learning and acquiring knowledge for productive uses‟

11 on the field trip we found out that the new sorghum variety giving double the yields of the traditional variety

was unacceptable to farmers. It did not store well, could not be used to make a favoured dish and the head of

the farmers union said “we have to eat 8 kg of this variety to feel the same as eating 5kg of our variety”. He

also added that for seven months of the year he was employed as a bricklayer.

12 project leaders told us plainly that CSIRO wanted the projects to centre on model development and training.

We disputed this point, but they insisted, citing that modelling workshops were run before the projects even

started, but we never mentioned R4D.

13 I prefer the term “learning networks” to “Innovation Platforms” because the former has a literature to

support it. Z says you have to use Innovation Platform in CORAF

http://www.coraf.org/English/CS.html


A simple definition of an innovation platform is (Nederlof et al. 2011)14

„a broad range of stakeholders who share a common interest and come together to solve problems and develop mutually beneficial solutions‟

Their African experience suggests that IPs targeting a value chain at district level (or middle level) have the potential for most impact. Below the middle level we tend to just focus on specific local on-farm problems. Above the middle level the IPs can just end up as a talkfest, unless people with real policy changing power are involved. They go on to cite the main problems with setting up IP as getting bogged down in the theory and involving too many „outside‟ people.

“The Africa country programme experienced a difficult start. Many organisations and consultants were involved in designing the approach and in the initial decision-making process on where to intervene and how. This resulted in a long inception period, mixed messages, an over-elaboration of the approach to be followed, and a limitation of the autonomy of the Africa country programmes”.

A major goal for us is to help set up the IPs in all the countries we are working in, without getting bogged down as above. To start the process, we have organised an IAR4D workshop for all project coordinators and country program leaders for early Jan 2012. Most of our projects are working at district level, which is the easiest scale at which to build an IP across a value chain. The workshop will focus on the practical steps each country leader must take to set up their IP. Then we will nurture the IPs with results from baseline surveys and guide the conversations with our systems analysis tools.

At this point I have to say that I do not fully agree with the stated CORAF policy on IAR4D below:

“The activities of CORAF/WECARD have continued to expand over the years, with IAR4D now being the pivot of all research for development activities…….This approach ensures that all stakeholders (farming communities, research scientists, private enterprises, NGOs, extension, etc) are involved in constraint identification, research conception, design, implementation, and evaluation of research activities.”

I do not think that involving all stakeholders in research conception, design etc is necessarily a solution. What if everyone just brings their own perspective and agenda to the table? How do we get consensus? The IAR4D Innovation Platform can only work if the participants are properly able to learn from each other in a structured way. Below I append a piece from a document on building system resilience being prepared by Nicky Grigg, Brian Walker, myself and others.

„Here it is useful to draw on other experiences that point to the strong value of participatory approaches. It is not sufficient to conduct detailed analyses or model runs and present graphs and „answers‟ for people to digest, no matter how rigorous, careful and insightful such results are. There are several factors at play here. First, in the matter of communicating for the purpose of learning, Sterman and colleagues have shown that system intuition is more effectively communicated and developed via interactive models and games [cite

14 Suzanne Nederlof, Peter Gildemacher, Willem Heemskerk and Femke van der Lee (2011)

Facilitation of innovation: experiences of RIU innovation platforms in Tanzania, Rwanda and Zambia.

Development Policy & Practice


references]. Second, in the crafting of decisions in response to system problems, delivering pre-determined „answers‟ to stakeholders is rarely as effective as approaches that engage stakeholders in an iterative dialogue that enables the exploration of multiple perspectives and options for future trajectories. The important shift in stance here is the focus on a leader in a decision-making role being an even more active listener: listening from where stakeholders are and guiding an iterative process of co-learning and decision-making to create a space to discover diverse future options”.

So why do I think the farming systems projects are crawling out of the hole? I sense that our West African partners are willing and able to go on this learning journey. My confidence stems more from conversations over breakfast, at morning teas and through email exchanges between project partners than from the formal proposals. I also think our CSIRO team is good enough to help facilitate this process, from helping to think through the on-farm experiments to the quantitative modelling and larger whole-of-system analysis.

The Bamako meeting ended with Lucy Carter‟s ethics presentation, which opened a new window for most of us on what was previously a 28 page inscrutable ethics application. She listed the four pillars of research ethics as 1) Respect for persons 2) Justice 3) Balance of benefits and risks 4) Research merit and integrity, and how the IAR4D process, done well, captures these.

The 9 common themes in research ethics are listed below, and again they provide guidelines for how we help facilitate the IPs. Following the ethical guidelines benefits the projects by fostering trust between researchers and other participants, increased retention of participants for the life cycle of the project, creation of opportunity for participants to “own” their contribution to research and by nurturing social learning

1. Informed consent

2. Managing risks (political, social, economic, etc)

3. Fair distribution of risks and benefits of participation

4. Meeting the expectations of participants

5. Full disclosure

6. Payments for participation

7. Confidentiality and Privacy

8. Recruitment strategies

9. Power relationships

I spent much of the second week in Nairobi with Z at the conference “Innovations in extension and advisory services: Linking knowledge to policy and action”

The conference was sponsored through 18 (mostly African) organisations, had over 450 delegates of whom 80% would have been from Africa. Z was presenting the paper “Innovation Platform for Technology Adoption (IPTA): Maize Value Chain in Burkina Faso” of which I was a co-author. The conference was a who‟s-who of development, with quite a number of high level policy makers, the heads of FARA, AGRA and NEPAD, and well known social scientists like Niels Rolling and Burton Swanson.

It was interesting to get a high level African take on the nature of the problems (they showed the graphs displaying Africa lagging the world) and the potential solutions. They talked about how the IMF-led structural adjustment programs of the 1980‟s had gutted the agriculture planning capability, how centrally planned extension programs could never respond to a diversity of local conditions and how there was not enough incentive at the grass roots to give farmers a business orientation.

There was quite a bit of discussion about how donors should engage in Africa, now that the


funding situation was turning around. Everyone agreed to a „plurality of approaches‟, but this did not mean a free for all and we were urged to follow the NEPAD-CAADP-FARA model. I took that as a vote of approval for CSIRO‟s mode of engagement. Monty Jones made a good point about the never ending call for more capacity building “the donors need capacity development as much as the farmers – we all do.”

I enjoyed the five point plan for food security delivered by the Kenyan Minister for Agriculture, Dr Kosgei, (below).

1) Improve availability and affordability of inputs

2) Improve access to credit services and markets

3) Invest in irrigation to increase area from 3000 to 1000 000 ha by 2030

4) Invest in country wide post harvest handling (mobile driers and storage)

5) Move towards value added products

It made me reflect back on our projects proposals where the goals and the means to reach these goals were too far apart. Our proposals do mention modelling and IAR4D as ways to aggregate from the specific to the high level general goals, but there was no real plan on how this will be achieved. I realised that the launch meetings should have focussed on the process by which we could effect change, rather than a list of activities. The above list makes sense because the intervention points are appropriate for the level of the question (food security) and the capacity of the implementing agency (government).

I spent a fascinating day with AGRA (Alliance for a Green Revolution in Africa). The phrase „public-private partnerships,‟ which usually just washes over me, came alive when we visited each part of the seed production value chain. We started at the seed production farm and they explained how they used other farmers as out-growers for certain crops and multiplied others on their facility and how the certification system worked etc. Then we visited the central grading, seed dressing, packaging facility before spending time with the retailers and finding out how they service more remote villages (through on-selling) and how they interact with farmers and extension workers.

AGRA gave a once off $200K grant (gift) to a private seed company that can provide evidence that they are multiplying a useful variety. This is to help them scale up to the point that it makes sense to mechanise. At a certain point the company becomes eligible for a low interest loan to buy graders, dressers and packaging equipment. Then they are on their own. The retailers told us how the market share of these local seed producers was increasing, and how even their local OPVs were displacing the hybrids from the multinationals Pannar and Pioneer. AGRA gave astounding figures on the increase in sales from „their‟ local seed companies (something like 7-fold increase in five years) but I suspect this has much to do with the drought (and slick marketing). Basically farmers had exhausted their own seed supply after a run of poor seasons. It‟s a good outcome nevertheless, to get certified seed into the fields.

The week ended with a meeting with A and B to plan the IAR4D training workshop for our project coordinators and country leaders. A seemed to have an excellent grasp of all the issues. She stressed that Innovation Platforms are no panacea, and although there are a few emerging success stories there has been no clear cost-benefit analysis. Yet she thought it was entirely appropriate course of action for our project and we got down to discussing the finer points i.e. not theoretical training – just the hard edged practical necessities that will allow us to get these IPs up and running as soon as possible. The workshop is schedules for the week of 16 Jan 2012.

Shortly after we got the news that A is leaving ILRI and then the worse news that K is leaving CSIRO (for Wageningen). Everyone agreed that the IAR4D training could not be delayed and fortunately ILRI found another facilitator. But how can we replace K?


A SHORT OVERVIEW

The farming systems projects can be broken down to four components

1. baseline survey / PRA

2. experimentation, mostly on-farm

3. systems analysis

4. training / capacity development / R4D

We (CSIRO) have really pushed the R4D aspects of the projects for several reasons. First, we believe it's what CORAF want because it aligns with the FARA strategy. Second, I‟m sure it‟s what AusAID want, but have not clearly articulated. Third, there is more talk about R4D than substance to date, which needs to be addressed head on. Fourth, we actually think it could greatly benefit the projects.

You could take the four points above and say it‟s just the old liner technology transfer approach i.e.

1. baseline – find out the problems

2. experimentation – solve problem locally

3. systems analysis – expand our knowledge from 2 above in space and time

4. training – tell the farmers what to do

The evidence thus far is that we are closer to the IAR4D agenda. For example, the first of the baseline surveys we‟ve been privy to (Stella‟s project) is imaginative in the techniques used to get to the nub of the constraints and to draw out the potential innovation from farmers.

We have, to date, been critical of the experimental work program. This is largely because so little of the work has been placed into a systems context, and seems to be „more of the same‟. Although we have a lot of work to do here, we have engaged all project coordinators on these issues and had a good reception. Much of the experimental work will be on-farm, and thus should draw in farmer input.

The systems analysis part is our big challenge and opportunity w.r.t. R4D. The general R4D literature postulates that innovation occurs where people of diverse interests meet around a common cause (i.e. the stakeholders in the value chain). However it‟s just as likely that the squeakiest wheel wins or the strongest personality in the room. We have to take our innovation platform through a process of structured learning i.e. all the ideas are put through a quantitative „filter‟ of various systems analysis tools. The tools don‟t dominate the discussion but they do represent a shared view of reality (mass balance, 24 hours in a day etc)

I think we can take much of point 4 – which goes under the general heading of „training‟ – and switch it to „learning‟ i.e. farmers, scientists and other value chain actors are co-learning through their interaction.

Viewed this way, all parts of the projects are on the R4D track. Lastly, the overarching model for our engagement is the long term partnership model. We have not developed a pragmatic partnership simply to communicate a particular technology, but a partnership to realise research for development. The bold(er) experiments we had once hoped to see in the famous Project Proposal section D7 will come in phase two, after the IPs have travelled some way down their learning journey. Our engagement now should keep this longer term perspective in view.


Annex 3. What is IAR4D?

Integrated Agricultural Research for Development (IAR4D) serves as the guiding principle for the CSIRO-AusAID partnership. IAR4D retains the rigour and structured learning fundamental to science, but has a much wider scope (hence the integration) and an explicit focus on farmer‟s livelihoods (hence the agriculture and development).

For most scientists, IAR4D will be different from their usual, highly focussed approach. By way of example, we can consider the problem of papayas becoming unsaleable due to a rapidly spreading disease that accelerates post-harvest. A standard scientific approach may be to identify the causal organism, find a suitable chemical control, train farmers how to control the disease before harvest and then ensure the retail chain can supply the chemicals. The elements are: (i) problem identification, (ii) problem solving, and (iii) dissemination of the solution to extension workers and farmers.

Agricultural research frequently operates at a broader level. We could use a crop model that combines weather, soil and agronomic practice to compare different crop sequences. In this case, we integrate scientific knowledge across a number of sub-systems. We can even involve the farmer to identify the various opportunities and constraints in an „action research‟ program. Now we have IAR (integrated, agriculture, research) but not necessarily D (development).

Returning to the problem of the rotting papaya; one solution may be chemical control, but a better solution may lie outside of the terms of reference of the plant pathologist working on the problem. A different solution may be to change cultivar, or irrigation practice. There may be better ways to pack or store papayas or shorter routes to market, or more profitable alternative fruit to grow. This introduces the D component because there may be other solutions that emerge from discussions amongst a wide range of stakeholders, together with feedback loops that allow adaptive learning.

Just as there can be different technical solutions to a problem, IAR4D recognises that there are different types of innovation. Apart from the technical innovation (new variety, new chemical) that arises from science, there may also be institution innovation, market innovation or policy innovation. In many cases the hoped for benefits only come when different forms of innovation are combined – for example a technical breakthrough may need a policy environment to make it mainstream and a market innovation to make it profitable.

Our ability to solve a problem arises from being able to ask the right question, which usually depends on focusing in. Since IAR4D sees the way forward as coming from technical, institutional, market or policy innovation – or some combination thereof - the first step is to make the problem space bigger. At this point we have a problem.

IAR4D typically looks outwards to a value chain and then seeks to get the perspectives of different stakeholders around a common theme. These stakeholders typically represent five areas, namely: (i) researchers, (ii) advisory / extension service, (iii) farmers and rural communities, (iv) agribusiness and processors, and (v) policy makers.

IAR4D may seem like a „fuzzy‟ process, so it helps to lay out how we might put it into practice. In our case the IAR4D is researcher-led, which means that researchers select the value chain of interest. However a value chain is a „big space‟, which only loosely defines the problem. So the researchers have to nominate an entry point as a starting place, which gives them sufficient focus to identify other stakeholder who can make a contribution. When representatives from the five areas above (research, advisory, farmers, agribusiness, policy) get together, we call it an Innovation Platform.


During the first phase of IAR4D the researchers establish the „existing situation‟ through baseline surveys for the chosen value chain / entry point. They have to engage the interests of farmers, traditional leaders and advisors on the one hand and agribusiness and policy makers on the other. This forms the basis of the Innovation Platform, which then meets to identify links, ideas and opportunities. The main task is to deepen collective understanding of the problem and to identify opportunities for actions and participatory research.

Phase 2 of the IAR4D process sees growing collaboration of all stakeholders, facilitated by the researchers. The engine of this collaboration is through various forms of participatory learning. Ideally, by Phase 3 of the IAR4D process the researchers are moving out, allowing the others partners to take over. Re-planning commences for the next cycle of IAR4D.

In summary:

IAR4D makes the „problem space‟ bigger and in doing so creates opportunities for different solutions

IAR4D picks an entry point and geographical location to in order to target the actors in the value chain and assemble relevant stakeholders into an Innovation Platform

The Innovation Platform is multi disciplinary, uses participatory „learning-by-doing‟ approaches and focuses on pathways to change

IAR4D avoids the linear technology transfer model of researcher-extension-farmer. Instead it relies on non-linear iterative collaborative interaction amongst diverse stakeholders to generate more durable solutions

However in order to have a chance of success:

The process much make it worthwhile for the stakeholders to engage (the researchers are paid – what do the other actors get out of it?)

Requires good leadership and facilitation skills

Needs drivers or champions for change

Participatory and learning approaches that support collective action

Private sector and government

(Agribusiness /

policy)

Researchers NARS, CGIAR

CSIRO

Local participants(farmers, advisors,

traditional leaders)

INTEREST INTERESTLEADERSHIP

OWNERSHIP

COLLABORATION

SUPPORT

FACILITATION COLLABORATION

OPPORTUNITY

Phase 1: Researchers

• Identify value chain and potential entry points

• Establish existing situation

• Assemble players for innovation platform

• Identify links, ideas, opportunities

Phase 2: All stakeholders

• Participatory learning and action research

• Pursue technology development and other

innovation

• M&E of I.P. progress

Phase 3: All Stakeholders

• Reassess priorities and plans

• Improving innovations

• Preparing for the next cycle to phase 1

Figure A1: An example of Researcher-led IAR4D process showing the phases of development

and how the roles of the different parties change (based on the document produced by

CORAF)

Documents

Enhanced Learning from AFSI Research: Notes for the Field