The combination of multiple theories in policy studies is like a valence issue in politics: few would disagree with the idea, largely because the sentiment is rather vague. Who would not want to combine the insights of a wide range of theories and studies to advance our knowledge? The more problematic and debatable part of this task relates to the details: how do we do it? I outline three main ways in which scholars address this issue and highlight the problems that may arise in each case:
Synthesis. We combine the insights of multiple theories, concepts or models to produce a single theory. One key problem is that when we produce a synthetic theory, from a range of other theories or concepts, we have to assume that the component parts of this new hybrid are consistent with each other. Yet, if you scratch the surface of many concepts – such as ‘new institutionalism’ or ‘policy networks’ – you find all sorts of disagreement about the nature of the world, how our concepts relate to it and how we gather knowledge of it. There are also practical problems regarding our assumption that the authors of these concepts have the same thing in mind when they describe things like ‘punctuated equilibrium’. In other words, imagine that you have constructed a new theory based on the wisdom of five other people. Then, get those people in the same room and you will find that they will share all sorts of – often intractable – disagreements with each other. In that scenario, could you honestly state that your theory was based on accumulated knowledge?
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) 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.
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 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 a set of rules or criteria to make sure that each theory can be accepted 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.
Most of us will find these aims to be intuitively appealing – but they are 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.
This argument may sound ‘postpositivist’. 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 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. That task requires rules which are problematic but necessary.
All I suggest is that we 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. 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. This is more of an art than a science.
Series: Policy Concepts in 1000 words