Enhancing learning from AFSI
research: Notes for the field
Ray Ison, Philip Wallis, Caroline Bruce,
Richard Stirzaker & Yiheyis Maru
MSI Report 13/10
December 2013
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 2013
ISBN: 978-0-9875677-3-4
Authors
Ray Ison¹, Philip Wallis¹, Caroline Bruce², Richard Stirzaker² & Yiheyis Maru²
1
Monash Sustainability Institute, Monash University
2
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 Ison
Systemic Governance Research Program - Program Leader
Monash Sustainability Institute
Building 74, Clayton Campus
Monash University, Victoria 3800, Australia
E: ray.ison@monash.edu
W: 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.
Enhancing learning from AFSI research: Notes for the Field
1.
2.
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
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.
2.3.1.
Most Significant Change – an adaptation ................................................................................................ 12
2.3.2.
Social learning ......................................................................................................................................... 14
2.3.3.
Pathways to impact ................................................................................................................................. 20
2.4.
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
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.
4.
T: A bag of tricks – Techniques for the field ..................................................................................................... 21
2.4.1.
2.5.
3.
M: Method - methodology ................................................................................................................................ 11
C: Scaffolding our joint learning – Confluence ................................................................................................. 32
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
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
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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
ii | 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:
Enhancing learning from AFSI research: Notes for the Field
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“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.
Enhancing learning from AFSI research: Notes for the Field
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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.
Enhancing learning from AFSI research: Notes for the Field
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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.
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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
Enhancing learning from AFSI research: Notes for the Field
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•
•
•
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
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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 coinnovation 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
Enhancing learning from AFSI research: Notes for the Field
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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 crossministry 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
Enhancing learning from AFSI research: Notes for the Field
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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‟
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).
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
Enhancing learning from AFSI research: Notes for the Field
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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 ongoing 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
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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.
2.
3.
4.
A.
B.
This claim may relate to a failure of facilitation?
This statement relates to the history of the situation?
Relates to the theoretical and perhaps epistemological differences in the teams?
Relates to building stakeholding by farmers?
A methodology issue (see below)
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)
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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).
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“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
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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).
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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 incountry 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
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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
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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).
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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
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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).
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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
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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 rethinking/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).
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African Food Security Initiative Researching System (v1.0)
AusAID
Executive
High
Commissioners
AusAID
Africa
Policy
Ambassadors
UQ QAFFI
AFSI
CSIRO
Papers
African
Government
Briefings
AusAID
PIFFS
Monash Uni
WECARD
African
Union
DEEDI
AusAID
Scholarships
CORAF
Crawford
Fund
CHOGM
ACIAR
CAADP
West African
Partnership
DAFF
Cotton
Proposals
from NARS
Improved Seed
Systems Project
IRAD
ISRA
CORAF
Projects
CGIAR
Universities
AGROHYMET
Food Security
and Rural
Development Policy
IAR4D
Innovation
Platforms
IER
NARS
Project
Videos
Project
Website
APESS
Project
CSIR
Ghana
ITRAD
East African
Partnership
Aflatoxin
Project
African
Countries
Amaranth
Project
Cavies
Project
PPR
Project
Capacity
Building
ILRI
National
Stakeholders
Regional
Stakeholders
Confluence
Platform
Learning
Project
Challenge
Fund
BECA
Project
Engagement
Strategy
Project
Templates
Local
Markets
Small-holder
Farms
Regional
Communication
Strategy
Sharepoint
Platform
G20
DFAT
FARA
AusAID In-house
Think Tanks
Media
Strategy
Communication
Protocols
Project
Brochure
International
FAO
Ministry
Capacity Building
in Africa
Comms Program
Project
Visuals
Impact of
Progress Stories
Sustainable
Agriculture
Flagship
Mechanisms for Increasing Impact
Partnership /
Australian Government
& H. Comm
Engagement Strategy
Review of Aid
Effectiveness
Australian
Embassies
AusAID-CSIRO
Partnership
DFAT Travel
Advisories
Uganda
Tanzania
Cameroon
Indigenous
Mushrooms
Project
DRC
Kenya
Burundi
CBPP
Swine Virus
Vaccine Project
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
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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.
(1) Start with four
sheets of paper
(3) You can add extra
sheets of paper to this
edge if needed
(2) Sticky-tape
along joins
(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
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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.
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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
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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
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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
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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) indepth 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.
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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
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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
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
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 „wellinformed‟ 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 oneway 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 agroecosystems 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.
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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)
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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.
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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.
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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.
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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.
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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.
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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.
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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., 17:1158.
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.
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Annex 1. A systemic set of prompts for learning in the field
Based on the proposed learning project conceptual framework
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
Ask if there
are different
framings of
the situation
Identify which
framework(s)
are in play
F
Explore if different
stakeholders
name the problem
differently
Describe how
you and/or
others see
the situation
Are these
frameworks fit
for purpose?
Inquire into relevance
and efficacy of IAR4D
and innovation platforms
in your context
S
T
Monitor how your own
understandings change
while in the field
Comment on
the quality of
relationships in
your research
system
P
Identify key
relationships to
be developed/
sustained
Introduce/use
new relevant
techniques
Monitor your own
experiences, including
enthusiasms, excitement,
frustrations and fears
Suggest
revisions to
methodology
Reflect on
Record insightful
techniques
stories and/or
in use
metaphors
Judge
effectiveness
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
M
Name
methodological
approaches
and judge their
relevance to
context
S: Situation
P: Practitioner
M: Methodology
T: Techniques
F: Frameworks
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.
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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
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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?
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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.
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(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
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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
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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
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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
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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?
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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.
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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.
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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
Local participants
(farmers, advisors,
traditional leaders)
Phase 1: Researchers
•
Identif y value chain and potential entry points
•
Establish existing situation
•
Assemble players f or innovation platf orm
•
Identif y 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 f or the next cycle to phase 1
INTEREST
COLLABORATION
OWNERSHIP
Researchers
NARS, CGIAR
CSIRO
Private sector
and government
(Agribusiness /
policy)
LEADERSHIP
INTEREST
FACILITATION
COLLABORATION
SUPPORT
OPPORTUNITY
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)
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