My new year’s resolution was to make a blog entry for every academic
article published from 2013, since the article may be behind a paywall
(although if you contact me, I will see you right) and the article’s ideas may
be expressed in a relatively inaccessible way (although we don’t all spew
jargon-filled group-closure nonsense).
The aim is to get people interested enough to go from a short tweet to a
larger blog to the high bar of reading (or the holy grail of citing) the
article itself.
This article is called ‘Standing on the Shoulders of Giants’ because I wanted to give the impression that we are
discussing the accumulation of scientific knowledge; our aim is to build on the
insights and knowledge produced by others rather than start from scratch each
time. As stated, this is fairly
uncontroversial and we might find that most people can get behind the project
(in fact, they are already doing so, implicitly or explicitly). The more problematic and debatable part of
this task relates to the details: *how* do we do it?
The article focuses on this task
in the policy literature, but the themes extend to political, social and, in
most cases, the so called ‘hard’ sciences.
In fact, for many of us, it may be reminiscent of postgraduate
discussions of the philosophy of science, in which we consider the inadequacy
of most explanations of how knowledge is accumulated (from the ‘strawman’ of
inductivism to the often-caricatured position of Popper (on falsification), to
the idea of paradigm shift made famous by Kuhn and the rather-misleading ‘anything
goes’ description of the approach by Feyerabend – a discussion captured neatly
by Chalmers). Many of us will have concluded two things:
(1) we believe that we are in the business of accumulating knowledge/ we know
much more about the world now than we did in the past, and we have acted
accordingly; but, (2) we have no idea *how* that has happened because all of
the explanations of knowledge accumulation are problematic, while some suggest
that one body of knowledge *replaces* another rather than building on it.
In that broad context, the
article (a) outlines three main ways in which scholars address this issue in
policy studies and political science; and, (b) highlights the problems that may
arise in each case:
2. The ‘Complementary’ Approach. In this case, you accept that people have these differences and so you accommodate them – you entertain a range of theories/ concepts and explore the extent to which they explain the same thing in different ways. This is a popular approach associated with people like Allison (who compared three different explanations of the Cuban missile crisis) and used by several others to compare policy events. One key problem with this approach is that it is difficult to do full justice to each theory. Most theories have associated methods which are labour intensive and costly, putting few in the position to make meaningful comparisons. Instead, the comparisons tend to be desktop exercises based on a case study and the authors’ ability to consider how each theory would explain it.
3. The ‘Contradictory’ Approach. In that context, another option is to encourage the independence of such theories. You watch as different research teams produce their own studies and you simply try to find some way to compare and combine their insights. Of course, it is impossible to entertain an infinite number of theories, so we also need some way to compare them; to select some and reject others. This is the approach that we may be most familiar with, since it involves coming up with a set of rules or criteria to make sure that each theory can be accepted (at least initially) by the scientific community. You may see such rules described as follows:
- A theory's methods should be explained so
that they can be replicated by others.
- Its concepts should be clearly defined,
logically consistent, and give rise to empirically falsifiable hypotheses.
- Its propositions should be as general as
possible.
- It should set out clearly what the causal
processes are.
- It should be subject to empirical testing and
revision.
For me, this is
where the task becomes very interesting because, on the one hand, most of us
will find these aims to be intuitively appealing – but, on the other, they are
incredibly problematic for the following reasons:
- Few, if any, theories or research projects live up to these expectations.
- The principles give a misleading impression of most (social?) scientific research which is largely built on trust rather than constant replication by others.
- Many of the most famous proponents of this approach do something a bit different – such as when they subject their ‘secondary hypotheses’ to rigorous testing but insulate their ‘hard core’ from falsification.
- The study of complex phenomenon may not allow us to falsify, since we can interpret our findings in very different ways.
- Few theories are currently popular simply because they adhere to these principles. In fact, science is much more of a social enterprise than the principles suggest.
Of course, by
now you may have identified a key problem with this argument: it is all
beginning to sound a bit ‘postpositivist’ (which, in my mind, is still more of
a term of abuse than ‘you, my friend, are a positivist’). However, it does not need to be taken this
way. It is OK to highlight problems with
scientific principles and admit that science is about the methods and beliefs
accepted by a particular scientific community because, if you like, you can
still assert that those principles and beliefs are *correct*. Many, many,
people do. In fact, perhaps we all do
it, because we have to find a way to accept some theories, approaches and
evidence and reject others. We seek a
way to produce some knowledge ourselves and find a common language and set of
principles to make sure that we can compare our knowledge with the knowledge of
others. We seek a way to sift through an
almost infinite number of ‘signals’ from our environment, to pay attention to
very few and ignore most. That task
requires rules which are problematic but necessary.
All I suggest we
do (which is a bit of a bland recommendation) is to reject the unthinking and
too-rigid application of rules that hold us all up to a standard that no-one
will meet. Rather, people in different disciplines
might discuss and negotiate those rules with each other. This is more of an art
than a science.
I also argue
that (a) if we are serious about these rules, and the need to submit theories and
evidence to rigorous testing; but (b) we accept that most of this is done on
trust rather than replication; then (c) we should take on some of that burden ourselves
by subjecting our own evidence to a form of testing, in which we consider the
extent to which our findings can be interpreted in different, and equally
plausible, ways. The article talks about producing different ‘narratives’
of the same evidence, but I won’t talk about that too much in case you confuse
me with the presenter of Jackanory.
Full reference: Cairney, P. (2013) 'Standing on the Shoulders of Giants: How Do We Combine the Insights of Multiple Theories in Public Policy Studies?' Policy Studies Journal, 41, 1, 1-21
TY - JOUR
AU - Cairney, Paul
TI - Standing on the Shoulders of Giants: How Do We Combine the Insights of Multiple Theories in Public Policy Studies?
JO - Policy Studies Journal
JA - Policy Stud J
VL - 41
IS - 1
SN - 1541-0072
DO - 10.1111/psj.12000
SP - 1
EP - 21
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