All going well, it will be out in November 2019. We are now at the proofing stage.
Writing a dissertation can be daunting. It is likely the longest piece of work you will plan as an undergraduate (10000 words plus bibliography) but, when you are done, it will not seem long enough.
On the one hand, it is a joyous exploration of research, in which you receive supervision but are in charge. On the other, you don’t want it to go horribly wrong.
It seems unlikely that reading my blog will spark joy, but I can at least give you some tips to avoid unnecessary problems and make your dissertation manageable.
Other advice (such as the reading in your module guide) is available, and I suggest you take it. Indeed, whenever I speak with colleagues about my approach to supervision, it seems relatively conservative and joyless.
On the other hand, why not play it safe with the dissertation then use all the time you’ve saved by seeking joy in a lovely meadow or a summer’s day?
Most undergraduate coursework involves answering your lecturer’s rather generic question. Your task is to produce something a bit different, with some of these characteristics:
Compare with Halperin and Heath’s (p164) criteria, in which it should be important, ‘researchable’, and it has not been ‘answered definitively’.
(also compare with Dunleavy’s call for full narrative titles)
For example, many projects that I supervise follow roughly the same format: what is policy, how much has it changed, and why?
We can then narrow it down in several ways by choosing a specific issue, political system, time period, and/ or aspect of policy change.
This narrowing can make the difference between:
(a) feeling the need to explain many theories in the literature review, versus
(b) limiting theory selection by focusing on a small number of political system dynamics.
Action point 1
Describe your initial question or theme with your supervisor, and work with them until you are both happy with the question.
Many people suggest that your first main piece of work should be the literature review, for quite good reasons:
I suggest that your first piece of work should be the abstract and introduction for these reasons:
Action point 2
Write the question/ title and abstract, share it with your likely supervisor, and talk about how coherent and feasible your plan looks.
In some cases, the potentially relevant literature is vast if you have, for example:
Action point 3.
Make sure to connect your research question to a well-defined literature (and do a preliminary literature search to see what is out there)
Halperin and Heath’s chapter 7 goes into some depth about the principles of research design:
They also describe the types of design you can likely not do (well, 1 and 2) in a UG dissertation, but can get the data to analyse:
Then they describe data gathering strategies that you might be tempted to do (subject to ethical clearance):
In the lecture, I will put on my dour face and warn you against most of these methods, for reasons such as:
I won’t try to put you off entirely. Rather, I will encourage you to ask yourself:
Action point 4
Discuss your choice of data collection with your supervisor.
This part tends to make the difference between a very good or an excellent dissertation.
Put most simply, simple description involves summarising things. Analysis is about telling the reader what the results mean. For example, you might:
Action point 5
Clarify the difference between summary and analysis
Don’t just to the dissertation equivalent of saying ‘cheerio’ (or, my favourite thing, leaving without saying cheerio).
The conclusion differs from:
Don’t think of it as saying: ‘as I have said before …’
Think of it as saying: ‘here is what it all adds up to …’
Remember to add your bibliography and ask yourself if you need an appendix for your data (which does not count towards the word count).
PS some of my supervisees write policy analysis reports, which differ somewhat from regular dissertations. If you are keen, please see me and/ or read more here.
The context for this workshop is the idea that policy theories could be more helpful to policymakers/ practitioners if we could all communicate more effectively with each other. Academics draw general and relatively abstract conclusions from multiple cases. Practitioners draw very similar conclusions from rich descriptions of direct experience in a smaller number of cases. How can we bring together their insights and use a language that we all understand? Or, more ambitiously, how can we use policy theory-based insights to inform the early career development training that civil servants and researchers receive?
The first step is to translate policy theories into a non-technical language by trying to speak with an audience beyond our immediate peers (see for example Practical Lessons from Policy Theories).
However, translation is not enough. A second crucial step is to consider how policymakers and practitioners are likely to make sense of theoretical insights when they apply them to particular aims or responsibilities. For example:
I discuss these examples below because they are closest to my heart (especially example 1). Note throughout that I am presenting one interpretation about: (1) the most promising insights, and (2) their implications for practice. Other interpretations of the literature and its implications are available. They are just a bit harder to find.
Example 1: the policy cycle endures despite its descriptive inaccuracy
The policy cycle does not describe and explain the policy process well:
Policy theories provide more descriptive and explanatory usefulness. Their insights include:
However, the cycle metaphor endures because:
In that context, we may want to be pragmatic about our advice:
Further reading (blog posts):
Example 2: how to deal with a lack of ‘evidence based policymaking’
I used to read many papers on tobacco policy, with the same basic message: we have the evidence of tobacco harm, and evidence of which solutions work, but there is an evidence-policy gap caused by too-powerful tobacco companies, low political will, and pathological policymaking. These accounts are not informed by theories of policymaking.
I then read Oliver et al’s paper on the lack of policy theory in health/ environmental scholarship on the ‘barriers’ to the use of evidence in policy. Very few articles rely on policy concepts, and most of the few rely on the policy cycle. This lack of policy theory is clear in their description of possible solutions – better communication, networking, timing, and more science literacy in government – which does not describe well the need to respond to policymaker psychology and a complex policymaking environment.
Since then, the highest demand to speak about the book has come from government/ public servant, NGO, and scientific audiences outside my discipline. The feedback is generally that: (a) the book’s description sums up their experience of engagement with the policy process, and (b) maybe it opens up discussion about how to engage more effectively.
But how exactly do we turn empirical descriptions of policymaking into practical advice?
For example, scientist/ researcher audiences want to know the answer to a question like: Why don’t policymakers listen to your evidence? and so I focus on three conversation starters:
We can then consider many possible responses in the sequel What can you do when policymakers ignore your evidence?
Example 3: how to encourage realistic evidence-informed policy transfer
This focus on EBPM is useful context for discussions of ‘policy learning’ and ‘policy transfer’, and it was the focus of my ANZOG talk entitled (rather ambitiously) ‘teaching evidence-based policy to fly’.
I’ve taken a personal interest in this one because I’m part of a project – called IMAJINE – in which we have to combine academic theory and practical responses. We are trying to share policy solutions across Europe rather than explain why few people share them!
For me, the context is potentially overwhelming:
So, when we start to focus on sharing lessons, we will have three things to discover:
To be honest, when one of our external assessors asked me how well I thought I would do, we both smiled because the answer may be ‘not very’. In other words, the most practical lesson may be the hardest to take, although I find it comforting: the literature suggests that policymakers might ignore you for 20 years then suddenly become very (but briefly) interested in your work.
The slides are a bit wonky because I combined my old ppt to the Scottish Government with a new one for UNSW Paul Cairney ANU Policy practical 22 October 2018
I wanted to compare how I describe things to (1) civil servants (2) practitioners/ researcher (3) me, but who has the time/ desire to listen to 3 powerpoints in one go? If the answer is you, let me know and we’ll set up a Zoom call.
1. Synthesis – we combine the insights of multiple theories, concepts or models to produce a single theory (in fact, the article discusses the difference between ‘synthesis’ and ‘super-synthesis’, but I don’t want to undermine my “we don’t all spew jargon-filled group-closure nonsense”). 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?
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: