Reinventing Development : The Sceptical Change Agent

303 Pages·2017·2.39 MB·English

by  Adam Fforde (auth.)

adam fforde
r e i n v e n t i n g
d e v e l o p m e n t
The Sceptical Change Agent
Reinventing Development
Adam Fforde
Reinventing
Development
The Sceptical Change Agent
Adam Fforde
Victoria Institute of Strategic Economic Studies
Victoria University
Melbourne, Victoria, Australia
ISBN 978-3-319-50226-7 ISBN 978-3-319-50227-4 (eBook)
DOI 10.1007/978-3-319-50227-4
Library of Congress Control Number: 2017931966
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To Gilly
p
reface
The ScepTical change agenT
This book is based upon extensive reflection on the problems facing those
who wish to influence social change. The following quote puts, in a nut-
shell, the issue:
Politics [‘development’] is the art of the possible. The political scientist
[‘expert’] wants to think he is right. The politician [‘practitioner’] likes to
think he is effective. Being effective is not only a question of having the
right answer to a problem but is also a matter of translating the answer
into successful action. That will usually mean persuading others to accept
the suggested solution and approve the proposed answer. [Hasluck (1997),
Introduction by Nicholas Hasluck, p. 15; additions in brackets by Adam
Fforde]
These problems have been bedevilled by deep and often unquestioned
assumptions. As a case study, the book examines these problems in the
context of a practice that, I argue, brings them into stark prominence:
international development—aid work. But these are problems that go well
beyond aid work. Development studies, in that it grapples systematically
with how to influence social change, and arguments about it, is a rich
source. My stance is sceptical in a precise sense that I develop in the book
but is focussed upon disbelief that knowledges deployed to influence social
change views interventions in predictively knowable cause–effect terms.
Most if not all books about development, however, are not sceptical:
they assert some enthusiasm—usually for the value of a set of ideas about
vii
viii PREFACE
what development is (their authors say) and how it should be done (they
say). Development practitioners and students are well aware, for example,
of early studies from the 1950s asserting the importance of capital and
technical knowledge transfers, of Robert Chambers’ work in the 1970s
supporting Participatory Rapid Appraisal (PRA) and Rapid Rural Appraisal
(RRA) methods, of studies such as the 1990s’ World Bank ‘Miracle Study’
asserting that export-oriented industrialisation was the way to go (World
Bank 1993) and more recent books such as Banerjee and Duflo’s Poor
Economics (2011) enthusing about randomised trials and Ramalingam’s
Aid on the Edge of Chaos (2013) that says that theoretical approaches
designed to cope with high levels of complexity show the way forward.
All these studies assert what development is and how to do it. They
almost all disagree. They are all certain that they offer better understand-
ings of development than those already existing, and that their under-
standings best explain success (and failure), and so should guide how to
‘do development’.
The problem for the practitioner, though, is not to understand, but
how to be effective in some justifiable way. None of these studies really
explain how to cope with the evident instability of enthusiasms, other
than saying that they are right and the others are wrong. Many practi-
tioners have therefore learnt to adapt to regular shifts in new beliefs and
new practices. They also learnt, however, that whilst official Western
donors, through the Development Advisory Committee (DAC) of the
Organisation of Economic Cooperation and Development (OECD),
require that aid interventions be founded on predictive knowledge of
what will cause what, in fact such knowledge is absent. They cope. But
the situation, though familiar, erodes authority and increases awareness
that each new enthusiasm does not actually solve the problem. Students
of development studies typically go from critically studying the range of
approaches to implementing one of them; this again creates familiar ten-
sions and the ‘madmen, mercenaries or missionaries’ phenomenon. I do
not think this is different from the situation facing others wishing to be
change agents who, having critically studied approaches to, say, economic
growth or social work, find themselves limited to one approach.
What is different about this book is that, using international devel-
opment—aid work—as a case study, it cuts through this Gordian knot
by justifying and explaining the value of a sceptical approach: in essence
that all these studies are wrong as they assert they can predict—if we use
their particular approach—what causes success. They almost all assume
PREFACE ix
that interventions should be construed in terms of knowable cause–effect
relationships. My book does not argue that we cannot ever know in this
sense, but that the OECD’s DAC, like the studies just mentioned and
reflecting common approaches outside the limited field of international
development, assumes that we always can predict and so requires inter-
ventions to be based upon such knowledge. The book therefore explains
to practitioners how we got into this situation, what that situation is and
what assumptions it is based upon. A ‘right to scepticism’ is asserted: the
right, in chosen circumstances, to organise as though there is no predictive
knowledge of ‘what will cause what’. This right is justified on a solid and
accessible intellectual foundation. The methodology used is quite conven-
tional, drawing on my original training in mathematics and engineering
science.
This approach brings a heady draft of oxygen into discussions of prac-
tice. It allows evaluations of interventions such as aid projects, for exam-
ple, to be treated as trustworthy surveys of stakeholders’ views rather than
statements of ‘what really happened: what caused what’. It explains to
the reader the epistemological traditions and deep assumptions (those
underpinning the various enthusiasms I mentioned). And above all it seeks
to return theories—knowledges—to being servants of practice by allow-
ing practitioners to argue (back) that simply because a theory ‘increases
understanding’ it does not have to mean it should be paid for.
a perSonal noTe
For those (not all) who like to be told the self-reflections of the author,
explaining how I have come to the views of the book may help. Those
who dislike such things will ignore them. In part I would like to empha-
sise what I consider the power of conventional natural science as I think I
was taught it in the 1960s and early 1970s. I make this point as I want to
stress what I see as the origins of scepticism in what I see as the stress of
natural science’s normative procedures upon treating theory and models
as objects of disbelief when confronted with data, no matter the need for
a suspension of that disbelief when theorising. They are just models, and
believing in them requires self-control. One of the reasons for the mess
discussed in the book is that enthusiasm and enthusiasts are given far too
much credence, not only by readers and listeners, but also in terms of for-
mal organisation (the DAC and its OECD masters, in the case of interna-
tional development). But whilst awareness of natural science method may
x PREFACE
have been necessary, other factors needed, I think, to come into play ‘in
my journey’. I have discussed my changing personal practices in the book.
I started off as a mathematician and engineer (BA, 1973) and then
trained as an economist (MSc, 1977), but rapidly evolved to making
most of my living as a development practitioner. I wrote a PhD (1982)
on North Vietnamese agricultural cooperatives (Fforde 1989), then held
in the early 1980s a post-doctorate on Vietnamese state industry (Fforde
2007) and then from the mid-1980s did most of my development consul-
tancy work in Vietnam. Much, but not all, of this involved the assessment
and evaluation of aid projects as well as various Vietnamese state activities.
I stopped around 2013 because the country became too corrupt. I kept
publishing academically.1 I found, early, two sources of friction in my con-
sultancy work.
First, despite being an academic expert on Vietnam, some people not
only disagreed with me, but—far more interestingly—were often unwill-
ing to abandon their beliefs and engage in substantive argument. The
central axis of these tensions was that they deemed their expertise to have
general validity: what ‘worked there’ was believed to ‘work here’. The cen-
tral friction was that these beliefs were not challengeable: they would not
listen. They believed that what they believed was true. I did not; I simply
offered explanations that were empirically based and expected to abandon
my views if better ones appeared. My stance towards what I happened to
believe was, drawing on my early training in mathematics and engineering,
sceptical and inviting of challenge. In a nutshell, for me these were ‘just
models’, but not for them.
Second, whilst the studies, of which mine were part, were expressed in
logical terms, cause–effect language in them not only did not rigorously
seek to create predictive power but, far more worryingly, was neverthe-
less used to support ways of organising interventions that assumed that
‘X’ would lead to ‘Y’ and that, when evaluated, ‘X’ could be powerfully
shown to have caused ‘Y’. For me, this was like basing a bridge design
upon no more than theory. The sense that such theories make is a central
feature of this book, for they make sense, but not predictive sense.
I increasingly saw these as methodological questions, and after teaching
for two years at the National University of Singapore (2000–2001) started
publishing in related areas as a parallel to publishing on Vietnam (Fforde
2005).
In 2015, I published two articles about method, which outline, in part,
the arguments here. Both were about how the general nature of certain
PREFACE xi
sets of ideas—not the particular ideas themselves—led to unwanted out-
comes. Both looked at experiences in international development work and
suggest that the field is a useful case study.
Fforde and Seidel (2015) examined aid donors’ experiences in
Cambodia. It argued that donors’ ideas shared common features—cen-
trally, belief that cause–effect relations were knowable ex ante and thus
were embodied in their aid projects as their ‘theory of change’. Apart from
this, another shared feature was their sectarianism. Because the scientific
procedures of the experts hired by donors did not require definitive choice
between theories, the donors lived in a world of multiple truths. Therefore,
when reality hit home in some part of the developmental landscape (the
article focussed on land allocation and titling), there was no overriding
strategic vision that could be deployed to manage conflicts between dif-
ferent parts of the Western aid effort. This could then explain why, despite
apparent great superiority in terms of power and capacity compared with
the Cambodians, donors ended up unhappy with the situation there.
Fforde (2015) looked more widely at lessons from aid work. It showed
how aid work, following the canonical requirements of the DAC, was
required to be audited and be auditable in terms of cause–effect relation-
ships known before and after the event (ex ante and ex post), as a famil-
iar part of mainstream audit culture (e.g. Shore and Wright 2015). The
paper explained how these requirements were manifest in organisational
devices such as the Logical Framework Approach (LFA or log-frame,
which is the term used here), and it presented empirical evidence that
such cause–effect relations were better thought of as knowably unknown.
Statistical methods existed that could show that, for example, no robust
relationships exist between policy proxies and economic performance, glob-
ally (Fforde 2005). A good candidate for why these statistical results
exist is that the language of the datasets they analyse assumes ontological
and epistemological universality—that, for example, ‘GDP’ or ‘export-
oriented policies’ are the same things in different places and times and
can be explained by the same theory. If the assumption does not hold,
published results assuming the contrary generate spurious results. If sta-
tistical work requires the assumptions that the model works and sam-
pling is from a single population, and these do not hold, results will
be empty and unreliable. The scientific procedures are deployed to give
some idea of the empirical bases for metaphors, not to show how to
choose between different theories, as would something like a predictive
criterion (McCloskey 1985).