Policy in 500 words and Policy Analysis in 750 words: writing about policy

This post is a shortened version of The Politics of Policy Analysis Annex A. It shows how to use insights from policy process research in policy analysis and policymaking coursework (much like the crossover between Scooby-Doo and Batman). It describes a range of exercises, including short presentations, policy analysis papers, blog posts, and essays. In each case, it explains the rationale for each exercise and the payoff to combining them.

If you prefer me to describe these insights less effectively, there is also a podcast:

[See also Writing About Policy 2: Write Harder, which describes how to write a 10000 word dissertation]

One step to combining policy analysis and policy process research is to modify the former according to the insights of the latter. In other words, consider how a ‘new policy sciences’ inspired policy analysis differs from the analyses already provided by 5-step guides.

It could turn out that the effects of our new insights on a policy briefing could be so subtle that you might blink and miss them. Or, there are so many possibilities from which to choose that it is impossible to provide a blueprint for new policy science advice. Therefore, I encourage students to be creative in their policy analysis and reflective in their assessment of their analysis. Our aim is to think about the skills you need to analyse policy, from producing or synthesising evidence, to crafting an argument based on knowing your audience, and considering how your strategy might shift in line with a shifting context.

To encourgage creativity, I set a range of tasks so that students can express themselves in different ways, to different audiences, with different constraints. For example, we can learn how to be punchy and concise from a 3-minute presentation or 500-word blog, and use that skill to get to the point more quickly in policy analysis or clarify the research question in the essay.

The overall effect should be that students can take what they have learned from each exercise and use it for the others.

In each section below, I reproduce the ways in which I describe this mix of coursework to students then, in each box, note the underlying rationale.

1. A 3-minute spoken presentation to your peers in a seminar.

In 3 minutes, you need to identify a problem, describe one or more possible solutions, and end your presentation in a convincing way. For example, if you don’t make a firm recommendation, what can you say to avoid looking like you are copping out? Focus on being persuasive, to capture your audience’s imagination. Focus on the policy context, in which you want to present a problem as solvable (who will pay attention to an intractable problem?) but not make inflated claims about how one action can solve a major problem. Focus on providing a memorable take home message.

The presentation can be as creative as you wish, but it should not rely on powerpoint in the room. Imagine that none of the screens work or that you are making your pitch to a policymaker as you walk along the street: can you make this presentation engaging and memorable without any reference to someone else’s technology? Can you do it without just reading out your notes? Can you do it well in under 3 minutes? We will then devote 5 minutes to questions from the audience about your presentation. Being an active part of the audience – and providing peer review – is as important as doing a good presentation of your own.

BOX A1: Rationale for 3-minute presentation.

If students perform this task first (before the coursework is due), it gives them an initial opportunity to see how to present only the most relevant information, and to gauge how an audience responds to their ideas. Audience questions provide further peer-driven feedback. I also plan a long seminar to allow each student (in a group of 15-20 people) to present, then ask all students about which presentation they remember and why. This exercise helps students see that they are competing with each other for limited policymaker attention, and learn from their peers about what makes an effective pitch. Maybe you are wondering why I discourage powerpoint. It’s largely because it will cause each presenter to go way over time by cramming in too much information, and this problem outweighs the benefit of being able to present an impressive visualisation. I prefer to encourage students to only tell the audience what they will remember (by only presenting what they remember).

2. A policy analysis paper, and 3. A reflection on your analysis

Provide a policy analysis paper which has to make a substantive argument or recommendation in approximately two pages (1000 words), on the assumption that busy policymakers won’t read much else before deciding whether or not to pay attention to the problem and your solutions. Then provide a reflection paper (also approximately 1000 words) to reflect your theoretical understanding of the policy process. You can choose how to split the 2000 word length, between analysis and reflection. You can give each exercise 1000 each (roughly a 2-page analysis), provide a shorter analysis and more reflection, or widen the analysis and reject the need for conceptual reflection. The choice is yours to make, as long as you justify your choice in your reflection.

When writing policy analysis, I ask you to keep it super-short on the assumption that you have to make your case quickly to people with 99 other things to do. For example, what can you tell someone in one paragraph or a half-page to get them to read all 2 pages?  It is tempting to try to tell someone everything you know, because everything is connected and to simplify is to describe a problem simplistically. Instead, be smart enough to know that such self-indulgence won’t impress your audience. In person, they might smile politely, but their eyes are looking at the elevator lights. In writing, they can skim your analysis or simply move on. So, use these three statements to help you focus less on your need to supply information and more on their demand:

1. Your aim is not to give a full account of a problem. It is to get powerful people to care about it.
2. Your aim is not to give a painstaking account of all possible solutions. It is to give a sense that at least one solution is feasible and worth pursuing.
3. Your guiding statement should be: policymakers will only pay attention to your problem if they think they can solve it, and without that solution being too costly.

Otherwise, I don’t like to give you too much advice because I want you to be creative about your presentation; to be confident enough to take chances and feel that you’ll see the reward of making a leap. At the very least, you have three key choices to make about how far you’ll go to make a point:

1. Who is your audience? Our discussion of the limits to centralised policymaking suggest that your most influential audience will not necessarily be an elected policymaker, but who else would it be?
2. How ‘manipulative’ should you be? Our discussions of ‘bounded rationality’ and ‘evidence-based policymaking’ suggest that policymakers combine ‘rational’ and ‘irrational’ shortcuts to gather information and make choices. So, do you appeal to their desire to set goals and gather a lot of scientific information, make an emotional appeal, or rely on Riker-style heresthetics?
3. What is your role? Contemporary discussions of science advice to government highlight unresolved debates about the role of unelected advisors: should you simply lay out some possible solutions or advocate one solution strongly?

For our purposes, there are no wrong answers to these questions. Instead, I want you to make and defend your decisions. That is the aim of your policy paper ‘reflection’: to ‘show your work’. You still have some room to be creative in your reflection: tell me what you know about policy theory and how it informed your decisions. Here are some examples, but it is up to you to decide what to highlight:

1. Show how your understanding of policymaker psychology helped you decide how to present information on problems and solutions.
2. Extract insights from policy theories, such as from punctuated equilibrium theory on policymaker attention, multiple streams analysis on timing and feasibility, or the NPF on how to tell persuasive stories.
3. Explore the implications of the lack of ‘comprehensive rationality’ and absence of a ‘policy cycle’: feasibility is partly about identifying the extent to which a solution is ‘doable’ when central governments have limited powers. What ‘policy style’ or policy instruments would be appropriate for the solution you favour?

I use the following questions to guide the marking on the policy paper: Tailored properly to a clearly defined audience? Punchy and concise summary? Clearly defined problem? Good evidence or argument behind the solution? Clear recommendations backed by a sense that the solution is feasible? Evidence of substantial reading, accompanied by well explained further reading?

In my experience of marking, successful students gave a very clear and detailed account of the nature and size of the policy problem. The best reports used graphics and/ or statistics to describe the problem in several ways. Some identified a multi-faceted problem – such as in health outcomes, and health inequalities – without presenting confusing analysis. Some were able to present an image of urgency, to separate this problem from the many others that might grab policymaker attention. Successful students presented one or more solutions which seemed technically and/ or politically feasible. By technically feasible, I mean that there is a good chance that the policy will work as intended if implemented. For example, they provided evidence of its success in a comparable country (or in the past) or outlined models designed to predict the effects of specific policy instruments. By politically feasible, I mean that you consider how open your audience would be to the solution, and how likely the suggestion is to be acceptable to key policymakers. Some students added to a good discussion of feasibility by comparing the pros/ cons of different scenarios. In contrast, some relatively weak reports proposed solutions which were vague, untested, and/ or not likely to be acted upon.

BOX A2: Rationale for policy analysis and reflection

Students already have 5-step policy analysis texts at their disposal, and they give some solid advice about the task. However, I want to encourage students to think more about how their knowledge of the policy process will guide their analysis. First, what do you do if you think that one audience will buy your argument, and another reject it wholeheartedly? Just pretend to be an objective analyst and put the real world in the ‘too hard’ pile? Or, do you recognise that policy analysts are political actors and make your choices accordingly? For me, an appeal to objectivity combined with insufficient recognition of the ways in which people respond emotionally to information, is a total cop-out. I don’t want to contribute to a generation of policy analysts who provide long, rigorous, and meticulous reports that few people read and fewer people use. Instead, I want students to show me how to tell a convincing story with a clear moral, or frame policy analysis to grab their audience’s attention and generate enthusiasm to try to solve a problem. Then, I want them to reflect on how they draw the line between righteous persuasion and unethical manipulation.

Second, how do you account for policymaking complexity? You can’t assume that there is a cycle in which a policymaker selects a solution and it sets in train a series of stages towards successful implementation. Instead, you need to think about the delivery of your policy as much as the substance. Students have several choices. In some cases, they will describe how to deliver policy in a multi-level or multi-centric environment, in which, say, a central government actor will need to use persuasion or cooperation rather than command-and-control. Or, if they are feeling energetic, they might compare a top-down delivery option with support for Ostrom-style polycentric arrangements. Maybe they’ll recommend pilots and/ or trial and error, to monitor progress continuously instead of describing a one-shot solution.  Maybe they’ll reflect on multiple streams analysis and think about how you can give dependable advice in a policy process containing some serendipity. Who knows? Policy process research is large and heterogeneous, which opens the possibility for some creative solutions that I won’t be able to anticipate in advance.

4. One kind of blog post (for the policy analysis)

Write a short and punchy blog post which recognises the need to make an argument succinctly and grab attention with the title and first sentence/ paragraph, on the assumption that your audience will be reading it on their phone and will move on to something else quickly. In this exercise, your blog post is connected to your policy analysis. Think, for example, about how you would make the same case for a policy solution to a wider ‘lay’ audience. Or, use the blog post to gauge the extent to which your client could sell your policy solution. If they would struggle, should you make this recommendation in the first place?

Your blog post audience is wider than your policy analysis audience. You are trying to make an argument that will capture the attention of a larger group of people who are interested in politics and policy, but without being specialists. They will likely access your post from Twitter/ Facebook or via a search engine. This constraint produces a new requirement, to: present a punchy title which sums up the whole argument in under 280 characters (a statement is often better than a vague question); to summarise the whole argument in approximately 100 words in the first paragraph (what is the problem and solution?); then, to provide more information up to a maximum of 500 words. The reader can then be invited to read the whole policy analysis.

The style of blog posts varies markedly, so you should consult many examples before attempting your own (for example, compare the LSE with The Conversation and newspaper blogs to get a sense of variations in style). When you read other posts, take note of their strengths and weaknesses. For example, many posts associated with newspapers introduce a personal or case study element to ground the discussion in an emotional appeal. Sometimes this works, but sometimes it causes the reader to scroll down quickly to find the main argument. Perhaps ironically, I recommend storytelling but I often skim past people’s stories. Many academic posts are too long (well beyond your 500 limit), take too long to get to the point, and do not make explicit recommendations, so you should not emulate them. You should aim to be better than the scholars whose longer work you read. You should not just chop down your policy analysis to 500 words; you need a new kind of communication.

Hopefully, by the end of this fourth task, you will appreciate the transferable life skills. I have generated some uncertainty about your task to reflect the sense among many actors that they don’t really know how to make a persuasive case and who to make it to. We can follow some basic Bardach-style guidance, but a lot of this kind of work relies on trial-and-error. I maintain a short word count to encourage you to get to the point, and I bang on about ‘stories’ in modules to encourage you to present a short and persuasive story to policymakers.

This process seems weird at first, but isn’t it also intuitive? For example, next time you’re in my seminar, measure how long it takes you to get bored and look forward to the weekend. Then imagine that policymakers have the same attention span as you. That’s how long you have to make your case! Policymakers are not magical beings with an infinite attention span. In fact, they are busier and under more pressure than us, so you need to make your pitch count.

BOX A3: Rationale for blog post 1

This exercise forces students to make their case in 500 words. It helps them understand the need to communicate in different ways to different audiences. It suggests that successful communication is largely about knowing how your audience consumes information, rather than telling people all you know. I gauge success according to questions such as: Punchy and eye grabbing title? Tailored to an intelligent ‘lay’ audience rather than a specific expert group? Clearly defined problem? Good evidence or argument behind the solution? Clear recommendations backed by a sense that the solution is feasible? Well embedded weblinks to further relevant reading?

5. Writing a theory-informed essay

I tend to set this simple-looking question for coursework in policy modules: what is policy, how much has it changed, and why? Students get to choose the policy issue, timeframe, political system, and relevant explanatory concepts.

On the face of it, it looks very straightforward. Give it a few more seconds, and you can see the difficulties:

1. We spend a lot of time in class agreeing that it seems almost impossible to define policy
2. There are many possible measures of policy change
3. There is an almost unmanageable number of models, concepts, and theories to use to explain policy dynamics.

I try to encourage some creativity when solving this problem, but also advise students to keep their discussion as simple and jargon-free as possible (often by stretching an analogy with competitive diving, in which a well-executed simple essay can score higher than a belly-flopped hard essay).

Choosing a format: the initial advice

1. Choose a policy area (such as health) or issue (such as alcohol policy).
2. Describe the nature of policy, and the extent of policy change, in a particular time period (such as in a particular era, after an event or constitutional change, or after a change in government).
3. Select one or more policy concepts or theory to help structure your discussion and help explain how and why policy has changed.

For example, a question might be: What is tobacco policy in the UK, how much has it changed since the 1980s, and why? I use this example because I try to answer that question myself, even though some of my work is too theory-packed to be a good model for a student essay (Cairney, 2007 is essentially a bad model for students).

Choosing a format: the cautionary advice

You may be surprised about how difficult it is to answer a simple question like ‘what is policy?’ and I will give you a lot of credit for considering how to define and measure it; by identifying, for example, the use of legislation/ regulation, funding, staff, and information sharing, and/ or by considering the difference between, say, policy as a statement of intent or a long term outcome. In turn, a good description and explanation of policy change is difficult. If you are feeling ambitious, you can go further, to compare, say, two issues (such as tobacco and alcohol) or places (such UK Government policy and the policy of another country), but sometimes a simple and narrow discussion can be more effective. Similarly, you can use many theories or concepts to aid explanation, but one theory may do. Note that (a) your description of your research question, and your essay structure, is more important than (b) your decision on what topic or concepts to use.

BOX A4: Rationale for the essay

The wider aim is to encourage students to think about the relationship between differentperspectives on policy theory and analysis. For example, in a blog and policy analysis paper they try to generate attention to a policy problem and advocate a solution. Then, they draw on policy theories and concepts to reflect on their papers, highlighting (say): the need to identify the most important audience; the importance of framing issues with a mixture of evidence and emotional appeals; and, the need to present ‘feasible’ solutions.

The reflection can provide a useful segue to the essay, since we’re already identifying important policy problems, advocating change, reflecting on how best to encourage it – such as by presenting modest objectives – and then, in the essay, trying to explain (say) why governments have not taken that advice in the past. Their interest in the policy issue can prompt interest in researching the issue further; their knowledge of the issue and the policy process can help them develop politically-aware policy analysis. All going well, it produces a virtuous circle.

BOX A5: Rationale for blog post 2

I get students to do the analysis/reflection/blog combination in the first module, and an essay/ blog combo in the second module. The second blog post has a different aim. Students use the 500 words to present a jargon-free analysis of policy change. The post represents a useful exercise in theory translation. Without it, students tend to describe a large amount of jargon because I am the audience and I understand it. By explaining the same thing to a lay audience, they are obliged to explain key developments in a plain language. This requirement should also help them present a clearer essay, because people (academics and students) often use jargon to cover the fact that they don’t really know what they are saying.

Policy Analysis in 750 words: Wil Thissen and Warren Walker (2013) Public Policy Analysis

Please see the Policy Analysis in 750 words series overview before reading the summary. Please note that this is an edited book and the full list of authors (PDF) is here. I’m using the previous sentence as today’s excuse for not sticking to 750 words.

Wil Thissen and Warren Walker (editors) (2013) Public Policy Analysis: New Developments (Springer)

Our premise is that there is no single, let alone ‘one best’, way of conducting policy analyses (Thissen and Walker, 2013: 2)

Thissen and Walker (2013: 2) begin by identifying the proliferation of (a) policy analysts inside and outside government, (b) the many approaches and methods that could count as policy analysis (see Radin), and therefore (c) a proliferation of concepts to describe it.

Like Vining and Weimar, they distinguish between:

1. Policy analysis, as the advice given to clients before they make a choice. Thissen and Walker (2013: 4) describe analysts working with a potential range of clients, when employed directly by governments or organisations, or acting more as entrepreneurs with multiple audiences in mind (compare with Bardach, Weimer & Vining, Mintrom).
2. Policy process research, as the study of such actors within policymaking systems (see 500 and 1000).

Policy theory: implications for policy analysis

Policy process research informs our understanding of policy analysis, identifying what analysts and their clients (a) can and cannot do, which informs (b) what they should do.

As Enserink et al (2012: 12-3) describe, policy analysis (analysis for policy) will differ profoundly if the policy process is ‘chaotic and messy’ rather than ‘neat and rational’.

The range of policy concepts and theories (analysis of policy) at our disposal helps add meaning to policy analysis as a practice. Like Radin, Enserink et al trace historic attempts to seek ‘rational’ policy analysis then conclude that modern theories – describing policymaking complexity – are ‘more in line with political reality’ (2012: 13-6).

As such, policy analysis shifts from:

(a) A centralised process with few actors inside government, to (b) a messy process including many policymakers and influencers, inside and outside government

(a) Translating science into policy, to (b) a competition to frame issues and assess policy-relevant knowledge

(a) An ‘optimal’ solution from one perspective, to (b) a negotiated solution based on many perspectives (in which optimality is contested)

(a) Analysing a policy problem/ solution with a common metric (such as cost benefit analysis), to (b) developing skills relating to: stakeholder analysis, network management, collaboration, mediation or conflict resolution based on sensitivity to the role of different beliefs, and the analysis of policymaking institutions to help resolve fragmentation (2013: 17-34).

Their Table 2.1 (2012: 35) outlines these potential differences (pop your reading glasses on …. now!):

In many cases, the role of an analyst remains uncertain. If we follow the ACF story, does an analyst appeal to one coalition or seek to mediate between them? If we follow MSA, do they wait for a ‘window of opportunity’ or seek to influence problem definition and motivation to adopt certain solutions?

Policy Analysis: implications for policy theory

In that context, rather than identify a 5-step plan for policy analysis, Mayer et al (2013: 43-50) suggest that policy analysts tend to perform one or more of six activities:

1. ‘Research and analyze’, to collect information relevant to policy problems.
2. ‘Design and recommend’, to produce a range of potential solutions.
3. ‘Clarify values and arguments’, to identify potential conflicts and facilitate high quality debate.
4. ‘Advise strategically’, to help a policymaker choose an effective solution within their political context.
5. ‘Democratize’, to pursue a ‘normative and ethical objective: it should further equal access to, and influence on, the policy process for all stakeholders’ (2013: 47)
6. ‘Mediate’, to foster many forms of cooperation between governments, stakeholders (including business), researchers, and/ or citizens.

Styles of policy analysis

Policy analysts do not perform these functions sequentially or with equal weight.

Rather, Mayer et al (2013: 50-5) describe ‘six styles of policy analysis’ that vary according to the analyst’s ‘assumptions about science (epistemology), democracy, learning, and change’ (and these assumptions may change during the process):

1. Rational, based on the idea that we can conduct research in a straightforward way within a well-ordered policy process (or modify the analysis to reflect limits to research and order).
2. Argumentative, based on a competition to define policy problems and solutions (see Stone).
3. Client advice, based on the assumption that analysis is part of a ‘political game’, and analysts bring knowledge of political strategy and policymaking complexity.
4. Participatory, to facilitate a more equal access to information and debate among citizens.
5. Process, based on the idea that the faithful adherence to good procedures aids high quality analysis (and perhaps mitigates an ‘erratic and volatile’ policy process)
6. Interactive, based on the idea that the rehearsal of many competing perspectives is useful to policymaker deliberations (compare with reflexive learning).

In turn, these styles prompt different questions to evaluate the activities associated with analysis (2013: 56):

In relation to the six policy analysis activities,

• the criteria for good policy analysis include: the quality of knowledge, usefulness of advice to clients and stakeholders, quality of argumentation, pragmatism of advice, transparency of processes, and ability to secure a mediated settlement (2013: 58).
• The positive role for analysts includes ‘independent scientist’ or expert, ‘ethicist’, ‘narrator’, ‘counsellor’, ‘entrepreneur’,’ democratic advocate’, or ‘facilitator’ (2013: 59).

Further, their – rather complicated – visualisations of these roles (e.g. p60; compare with the Appendix) project the (useful) sense that (a) individuals face a trade-off between roles (even if they seek to combine some), and (b) many people making many trade-offs adds up to a complex picture of activity.

Therefore, we should bear in mind that

(a) there exist some useful 5-step guides for budding analyst, but

(b) even if they adopt a simple strategy, analysts will also need to find ways to understand and engage with a complex policymaking systems containing a huge number of analysts, policymakers, and influencers.

Policy Analysis styles: implications for problem definition and policy design

Thissen (2013: 66-9) extends the focus on policymaking context and policy analysis styles to problem definition, including:

1. A rational approach relies on research knowledge to diagnose problems (the world is knowable, use the best scientific methods to produce knowledge, and subject the results to scientific scrutiny).
2. A ‘political game model’ emphasises key actors and their perspectives, value conflicts, trust, and interdependence (assess the potential to make deals and use skills of mediation and persuasion to secure them).

These different starting points influence they ways in which analysts might take steps to identify: how people perceive policy problems, if other definitions are more useful, how to identify a problem’s cause and effect, and the likely effect of a proposed solution, communicate uncertainty, and relate the results to a ‘policy arena’ with its own rules on resolving conflict and producing policy instruments (2013: 70-84; 93-4).

Similarly, Bots (2013: 114) suggests that these styles inform a process of policy design, constructed to change people’s minds during repeated interactions with clients (such as by appealing to scientific evidence or argumentation).

Bruijn et al (2013: 134-5) situate such activities in modern discussions of policy analysis:

1. In multi-centric systems, with analysts focused less on ‘unilateral decisions using command and control’ and more on ‘consultation and negotiation among stakeholders’ in networks.

• The latter are necessary because there will always be contestation about what the available information tells us about the problem, often without a simple way to negotiate choices on solutions.

2. In relation to categories of policy problems, including

• ‘tamed’ (high knowledge/ technically solvable, with no political conflict)
• ‘untamed ethical/political’ (technically solvable, with high moral and political conflict)
• ‘untamed scientific’ (high consensus but low scientific knowledge)
• ‘untamed’ problems (low consensus, low knowledge).

Put simply, ‘rational’ approaches may help address low knowledge, while other skills are required to manage processes such as conflict resolution and stakeholder engagement (2013: 136-40)

Policy Analysis styles: implications for models

Part 2 of the book relates such styles (and assumptions about how ‘rational’ and comprehensive our analyses can be) to models of policy analysis. For example,

1. Walker and van Daalen (2013: 157-84) explore models designed to compare the status quo with a future state, often based on the (shaky) assumption that the world is knowable and we can predict with sufficient accuracy the impact of policy solutions.
2. Hermans and Cunningham (2013: 185-213) describe models to trace agent behaviour in networks and systems, and create multiple possible scenarios, which could help explore the ‘implementability’ of policies.
3. Walker et al (2013: 215-61) relate policy analysis styles to how analysts might deal with uncertainty.

• Some models may serve primarily to reduce ‘epistemic’ uncertainty associated with insufficient knowledge about the future (perhaps with a focus on methods and statistical analysis).
• Others may focus on resolving ambiguity, in which many actors may define/ interpret problems and feasible solutions in different ways.

Overall, this book contains one of the most extensive discussions of 101 different technical models for policy analysis, but the authors emphasise their lack of value without initial clarity about (a) our beliefs regarding the nature of policymaking and (b) the styles of analysis we should use to resolve policy problems. Few of these initial choices can be resolved simply with reference to scientific analysis or evidence.

Policy Analysis in 750 words: Linda Tuhiwai Smith (2012) Decolonizing Methodologies

Please see the  Policy Analysis in 750 words series overview before reading the summary. The reference to 750 words is increasingly misleading.

Linda Tuhiwai Smith (2012) Decolonizing Methodologies 2^nd edition (London: Zed Books)

 ‘Whose research is it? Who owns it? Whose interests does it serve? Who will benefit from it? Who has designed its questions and framed its cope? Who will carry it out? Who will write it up? How will its results be disseminated?’ (Smith, 2012: 10; see also 174-7)

Many texts in this series highlight the politics of policy analysis, but few (such as Bacchi) identify the politics of the research that underpins policy analysis.

You can find some discussion of these issues in the brief section on ‘co-production’, in wider studies of co-produced research and policy, and ‘evidence based policymaking’, and in posts on power and knowledge and feminist institutionalism. However, the implications rarely feed into standard policy analysis texts. This omission is important, because the production of knowledge – and the exercise of power to define whose knowledge counts – is as political as it gets.

Smith (2012) demonstrates this point initially by identifying multiple, often hidden, aspects of politics and power that relate to ‘research’ and ‘indigenous peoples’:

 

1. The term ‘indigenous peoples’ is contested, and its meaning-in-use can range from

• positive self-identification, to highlight common international experiences and struggles for self-determination but distinctive traditions; other terms include ‘First Nations’ in Canada or, in New Zealand, ‘Maori’ as opposed to ‘Pakeha’ (the colonizing population) (2012: 6)
• negative external-identification, including – in some cases – equating ‘indigenous’ (or similar terms) with ‘dirtiness, savagery, rebellion and, since 9/11, terrorism’ (2012: xi-xii).

 

2. From the perspective of ‘the colonized’, “the term ‘research’ is inextricably linked to European imperialism and colonialism” (2012: 1; 21-6). Western research practices (and the European ‘Enlightenment’) reflect and reinforce political practices associated with colonial rule (2012: 2; 23).

‘To the colonized, the ways in which academic research has been implicated in the throes of imperialism remains a painful memory’ (2012: back cover).

“The word itself, ‘research’, is probably one of the dirtiest words in the indigenous world’s vocabulary” (2012: xi).

 

3. People in indigenous communities describe researchers who exploit ‘their culture, their knowledge, their resources’ (and, in some cases, their bodies) to bolster their own income, career or profession (2012: xi; 91-4; 102-7), in the context of a long history of subjugation and slavery that makes such practices possible (2012: 21-6; 28-9; 176-7), and “justified as being for ‘the good of mankind’” (2012: 26).

 

 

4. Western researchers think – hubristically – that they can produce a general understanding of the practices and cultures of indigenous peoples (e.g. using anthropological methods). Instead, they produce – irresponsibly or maliciously – negative and often dehumanizing images that feed into policies ‘employed to deny the validity of indigenous peoples’ claim to existence’ and solve the ‘indigenous problem’ (2012: 1; 8-9; 26-9; 62-5; 71-2; 81-91; 94-6).

For example, research contributes to a tendency for governments to

• highlight, within indigenous communities, indicators of inequality (in relation to factors such as health, education, crime, and family life), and relate it to
• indigenous cultures and low intelligence, rather than
• the ways in which colonial legacy and current policy contributes to poverty and marginalisation (2012: 4; 12; compare with Social Construction and Policy Design).

 

5. Western researchers’ views on how to produce high-quality scientific evidence lead them to ‘see indigenous peoples, their values and practices as political hindrances that get in the way of good research’ (2012: xi; 66-71; compare with ‘hierarchy of evidence’). Similarly, the combination of a state’s formal laws and unwritten rules and assumptions can serve to dismiss indigenous community knowledge as not meeting evidential standards (2012: 44-9).

 

6. Many indigenous researchers need to negotiate the practices and expectations of different groups, such as if they are portrayed as:

• ‘insiders’ in relation to an indigenous community (and, for example, expected by that community to recognise the problems with Western research traditions)
• ‘outsiders’, by (a) an indigenous community in relation to their ‘Western education’ (2012: 5), or (b) by a colonizing state commissioning insider research
• less technically proficient or less likely to maintain confidentiality than a ‘non-indigenous researcher’ (2012: 12)

Can policy analysis be informed by a new research agenda?

In that context, Smith (2012: xiii; 111-25) outlines a new agenda built on the recognition that research is political and connected explicitly to political and policy aims (2012: xiii; compare with Feminism, Postcolonialism, and Critical Policy Studies)

At its heart is a commitment to indigenous community ‘self-determination’, ‘survival’, ‘recovery’, and ‘development’, aided by processes such as social movement mobilization and decolonization (2012: 121). This agenda informs the meaning of ethical conduct, signalling that research:

• serves explicit political goals and requires researchers to reflect on their role as activists in an emancipatory project, in contrast to the disingenuous argument that science or scientists are objective (2012: 138-42; 166-77; 187-8; 193-5; 198-215; 217-26)
• is not ‘something done only by white researchers to indigenous peoples’ (2012: 122),
• is not framed so narrowly, in relation to specific methods or training, that it excludes (by definition) most indigenous researchers, community involvement in research design, and methods such as storytelling (2012: 127-38; 141; for examples of methods, see 144-63; 170-1)
• requires distinctive methods and practices to produce knowledge, reinforced by mutual support during the nurturing of such practices
• requires a code of respectful conduct that extends ‘beyond issues of individual consent and confidentiality’) (2012: 124; 179-81).

Wider context: informing the ‘steps’ to policy analysis

This project informs directly the ‘steps’ to policy analysis described in Bardach, Weimer and Vining, and Mintrom, including:

Problem definition

Mintrom describes the moral and practical value of engaging with stakeholders to help frame policy problems and design solutions (as part of a similarly-worded aim to transform and improve the world).

However, Smith (2012: 228-32; 13) describes such a profound gulf, in the framing of problems, that cannot be bridged simply via consultation or half-hearted ‘co-production’ exercises.

For example, if a government policy analyst relates poor health to individual and cultural factors in indigenous communities, and people in those communities relate it to colonization, land confiscation, minimal self-determination, and an excessive focus on individuals, what could we realistically expect from set-piece government-led stakeholder analyses built on research that has already set the policy agenda (compare with Bacchi)?

Rather, Smith (2012: 15-16) describes the need, within research practices, for continuous awareness of, and respect for, a community’s ‘cultural protocols, values and behaviours’ as part of ‘an ethical and respectful approach’. Indeed, the latter could have mutual benefits which underpin the long-term development of trust: a community may feel less marginalised by the analysis-to-policy process, and future analysts may be viewed with less suspicion.

Even so, a more respectful policy process is not the same as accepting that some communities may benefit more from writing about their own experiences than contributing to someone else’s story. Writing about the past, present, and future is an exercise of power to provide a dominant perspective with which to represent people and problems (2012: 29-41; 52-9)

Analysing and comparing solutions

Imagine a cost-benefit analysis designed to identify the most efficient outcomes by translating all of the predicted impacts on people into a single unit of analysis (such as a dollar amount, or quality-adjusted-life-years). Assumptions include that we can: (a) assign the same value to a notionally similar experience, and (b) produce winners from policy and compensate losers.

Yet, this calculation hinges on the power to decide how we should understand such experiences and place relative values on outcomes, and to take a calculation of their value to one population and generalise it to others. Smith’s analysis suggests that such processes will not produce outcomes that we can describe honestly as societal improvements. Rather, they feed into a choice to produce winners from policy and fail to compensate losers in an adequate or appropriate manner.

See also:

1. In relation to policy theories

This post – Policy Concepts in 1000 Words: Feminism, Postcolonialism, and Critical Policy Studies – provides a tentative introduction to the ways in which many important approaches can inform policy theories, such as by

• identifying the unequal competition to define the rules of knowledge gathering, within
• a wider political context in which some social groups, countries, and ways of thinking dominate proceedings, from the direct exercise of power to the maintenance of ‘hegemonic’ or ‘paradigmatic’ ideas.

The 2^nd edition of Understanding Public Policy summarises these themes as follows:

2. In relation to policy analysis

If you look back to the Policy Analysis in 750 words series overview, you will see that a popular way to address policy issues is through the ‘coproduction’ of research and policy, perhaps based on a sincere commitment to widen a definition of useful knowledge/ ways of thinking and avoid simply making policy from the ‘centre’ or ‘top down’.

Yet, the post you are now reading, summarising Decolonizing Methodologies, should prompt us to question the extent to which a process could be described sincerely as ‘coproduction’ if there is such an imbalance of power and incongruence of ideas between participants.

Although many key texts do not discuss ‘policy analysis’ directly, they provide ways to reflect imaginatively on this problem. I hope that I am not distorting their original messages, but please note that the following are my stylized interpretations of key texts.

Audre Lorde (2018*) The Master’s Tools Will Never Dismantle the Master’s House (Penguin) (*written from 1978-82)

One issue with very quick client-oriented policy analysis is that it encourages analysts to (a) work with an already-chosen definition of the policy problem, and (b) use well-worn methods to collect information, including (c) engaging with ideas and people with whom they are already familiar.

Some forms of research and policy analysis may be more conducive to challenging existing frames and encouraging wider stakeholder engagement. Still, compare this mild shift from the status quo with a series of issues and possibilities identified by Lorde (2018):

• Some people are so marginalised and dismissed that they struggle to communicate – about the ways in which they are oppressed, and how they might contribute to imagining a better world – in ways that would be valued (or even noticed) during stakeholder consultation (2018: 1-5 ‘Poetry is not a luxury’).
• The ‘european-american male tradition’ only allows for narrowly defined (‘rational’) means of communication (2018: 6-15 ‘Uses of the Erotic’)

A forum can be designed ostensibly to foster communication and inclusivity, only to actually produce the opposite, by signalling to some participants that

• they are a token afterthought, whose views and experiences are – at best – only relevant to a very limited aspect of a wide discussion, and
• their differences will be feared, not celebrated, becoming a source of conflict, not mutual nurture or cooperation.

It puts marginalised people in the position of having to work hard simply to be heard. They learn that powerful people are only willing to listen if others do the work for them, because (a) they are ignorant of experiences other than their own, and/or (b) they profess ignorance strategically to suck the energy from people whose views they fear and do not understand. No one should feel immune from such criticism even if they profess to be acting with good intentions (2018: 16-21 ‘The Master’s Tools Will Never Dismantle the Master’s House’).

• The correct response to racism is anger. Therefore, do not prioritise (a) narrow rules of civility, or the sensibilities of the privileged, if (b) your aim is to encourage conversations with people who are trying to express the ways in which they deal with overwhelming and continuous hatred, violence, and oppression (2018: 22-35, ‘Uses of Anger: Women Responding to Racism’)

Boaventura de Sousa Santos (2014) Epistemologies of the South: Justice Against Epistemicide (Routledge)

Imagine global policy processes and policy analysis, in which some countries and international organisations negotiate agreements, influenced (or not) by critical social movements in pursuit of social justice. Santos (2014) identifies a series of obstacles including:

• A tendency for Western (as part of the Global North) ways of thinking to dominate analysis, at the expense of insights from the Global South (2014: viii), producing
• A tendency for ‘Western centric’ ideas to inform the sense that some concepts and collective aims – such as human dignity and human rights – can be understood universally, rather than through the lens of struggles that are specific to some regions (2014: 21; 38)
• A lack of imagination or willingness to imagine different futures and conceptions of social justice (2014: 24)

Consequently, actors may come together to discuss major policy change on ostensibly the same terms, only for some groups to – intentionally and unintentionally – dominate thought and action and reinforce the global inequalities they propose to reduce.

Sarah Ahmed (2017) Living a Feminist Life (Duke University Press)

Why might your potential allies in ‘coproduction’ be suspicious of your motives, or sceptical about the likely outcomes of such an exchange? One theme throughout Smith’s (2012) book is that people often co-opt key terms (such as ‘decolonizing’) to perform the sense that they care about social change, to try to look like they are doing something important, while actually designing ineffective or bad faith processes to protect the status of themselves or their own institution or profession.

Ahmed (2017: 103) describes comparable initiatives – such as to foster ‘equality and diversity’ – as a public relations exercise for organisations, rather than a sincere desire to do the work. Consequently, there is a gap ‘between a symbolic commitment and a lived reality’ (2017: 90). Indeed, the aim may be to project a sense of transformation to hinder that transformation (2017: 90), coupled with a tendency to use a ‘safe’ and non-confrontational language (‘diversity’) to project the sense that we can only push people so far, at the expense of terms such as ‘racism’ that would signal challenge, confrontation, and a commitment to high impact (2017: chapter 4).

..

Putting these insights together suggests that a stated commitment to co-produced research and policy might begin with good intentions. Even so, a commitment to sincere engagement does not guarantee an audience or prevent you from exacerbating the very problems you profess to solve.

Putting it all together: dissertation research question and research design (POLU9RM)

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?

1. Ask the right research question.

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:

• You should find it interesting and want to answer it.
• It should be something that you can answer.
• It should be specific enough to help you manage your time well and answer it with the resources you have.

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.

2. Write the abstract and the introduction first?

Many people suggest that your first main piece of work should be the literature review, for quite good reasons:

• It allows you to gain enough initial knowledge to help you guide your research
• It allows you to get writing – often a major stumbling block – and then edit later

I suggest that your first piece of work should be the abstract and introduction for these reasons:

• Writing a half page abstract allows you to describe what your project adds up to.
• It really helps you discuss your plans with your supervisor
• Writing the introduction allows you to describe your research design in enough depth to reflect on it is coherence and feasibility.
• All going well, it will be only a small jump from your POLU9RM ‘research project design’ exercise.
• It allows you to make sense of a quite general format for research publications (in many fields): theory, method, results.

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.

3. Identify the relevant theory or literature.

In some cases, the potentially relevant literature is vast if you have, for example:

1. A too-general question about political parties or elections.

• One good solution is to select a subfield like ‘pledge fulfilment’

2. A too-general question about policy change.

• One good solution is to ask if (say) the advocacy coalition framework or multiple streams analysis helps explain your case study.
• Or, I have supervised many good dissertations asking: what can X government learn from Y government about solving Z policy problem?

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)

4. Identify your method to gather information.

Halperin and Heath’s chapter 7 goes into some depth about the principles of research design:

• what data collection is appropriate
• what we can deduce from certain data
• how confident you can be about cause/effect in this case (internal validity)
• and cause-and-effect more generally (external validity)
• if someone could do your research and get the same results (reliability)

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:

1. Experimental (like an RCT)
2. Cross-sectional and longitudinal
3. Comparative (for which I did a separate post)

Then they describe data gathering strategies that you might be tempted to do (subject to ethical clearance):

• Surveys
• Interviews
• Focus groups
• Ethnographic
• Discourse analysis

In the lecture, I will put on my dour face and warn you against most of these methods, for reasons such as:

• Doing a proper survey takes a lot of time and resources, someone has likely already done a better one, and it would be a shame not to find it
• You can often find things in the public record without interviewing someone (and maybe they will only repeat what is out there)
• The ethical clearance will be a major issue with ethnographic (and other) methods

I won’t try to put you off entirely. Rather, I will encourage you to ask yourself:

• Why are you choosing this method?

1. Does it relate clearly to your research question?
2. Or, have you begun with the most interesting sounding method?
3. Or, do you have some sort of connection that gets you access, which seems a shame not to use?

• Are you prepared to do a literature review on your chosen method?
• What do you realistically expect to get from your method?
• What will you do if it goes wrong?

Action point 4

Discuss your choice of data collection with your supervisor.

5. Think about how you will analyse and interpret the results.

This part tends to make the difference between a very good or an excellent dissertation.

• Raul Pacheco-Vega gives many useful examples in Distinguishing between description and analysis in academic writing

Put most simply, simple description involves summarising things. Analysis is about telling the reader what the results mean. For example, you might:

• Evaluate the size of the results according to your expectations. Does a survey result seem unusual?
• Describe how much one should rely on the results. Does the result seem important after taking into account a margin of error?
• Describe the wider context. Does the result mark a change over time, or seem different from another country?
• Relate a case study result to your literature review. Is your case unusual, or as expected?

Action point 5

Clarify the difference between summary and analysis

6. Be clear about the conclusion.

Don’t just to the dissertation equivalent of saying ‘cheerio’ (or, my favourite thing, leaving without saying cheerio).

The conclusion differs from:

• The introduction, because you should use it to summarise your question and approach (perhaps quite briefly) and relate it in some depth to the results.
• The analysis of results, because you relate the results much more clearly to your overall project.

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 …’

7. The end.

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.

 

 

 

 

 

 

POLU9RM Asking the right research question

When I supervise dissertation students, I try to get them to do things in a specific order:

• get the research question right
• write an abstract to see if you can answer it (and explain how you structure the dissertation to allow you to answer it)
• write the introduction to see if you can explain the whole rationale for your dissertation before you do most of the research.

Now, I don’t want to get into a big debate with the deviants who want to write or rewrite their introductions at the end. You can do what you like, pal.

Instead, I want to emphasise the benefits of the early investment. If you get the research question spot-on, in relation to the introduction, you can do the following:

• make your project manageable from the start, without learning the hard way that you’ve bitten off more than you can chew
• save a remarkably hellish amount of time on your ‘literature review’ by producing a clear sense of what is relevant/ to be skipped over
• boast to your friends that you finished on time.

There is some good advice out there on designing a question to speak to a big question and a narrow research project at the same time.

For example, most of my projects follow roughly the same format: what is policy, how much has it changed, and why?

We can then narrow it down in several ways:

• Choose, say, tobacco policy (quite specific) versus health policy (very broad indeed)
• Choose one political system or one region, or limit your comparison of systems
• Choose one time period
• Choose what aspect of change you want to explain.

The latter is often the most important, because (in my case) it can make the difference between (a) feeling the need to explain many, many theories to give the whole picture (an impossible task) or (b) narrowing down theory selection by focusing on a small number of causes/ dynamics.

Ideally, the question should be super-important and sophisticated, but a dissertation also takes a lot of time and attention. So, my best advice is to choose a question to which you actually want to know the answer. If so, you should end up very satisfied in your result. If you don’t find the question interesting, you may come to resent your dissertation.

A final thought is that students often don’t know what question to ask, and they talk quite broadly about a very general topic. In such cases, it’s important to work with your supervisor until you’re both happy with the final result. My most memorable example is a student who, above all else, wanted to write about Beyoncé (and it worked out very well indeed).

Policy in 500 Words: how much does policy change?

You should get the impression from 1000 words that most policy changes are small or not radically different from the past: Lindblom identifies incrementalism; punctuated equilibrium  highlights a huge number of small changes and small number of huge changes; the ACF compares routine learning by a dominant coalition to a ‘shock’ which prompts new subsystem and policy dynamics; and multiple streams identifies the conditions (rarely met) for major change.

Yet, I just gave you the impression that we don’t know how to define policy. If we can’t define it well, how can we measure it well enough to come to this conclusion so consistently?

Why is the measurement of policy change important?

We miss a lot if we equate policy with statements rather than outputs/ outcomes. We also miss a lot if we equate policy change with the most visible outputs such as legislation. I list 16 different policy instruments, although they tend to be grouped into smaller categories: focusing on regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal; or regulatory/ distributive/ redistributive to suggest that some policy measures are more difficult to ‘sell’ than others.

We also give a limited picture if we equate change with outputs rather than outcomes, since a key insight from policy studies is that there is generally a gap between policymaker expectations and the actual result.

What are the key issues in measurement?

So, as in defining policy change, we need to make choices about what counts as policy in this instance to measure how much it has changed. For example, I have (a) written on one output as a key exemplar of policy change –  legislation to ban smoking in public places for Scotland, England/ Wales, the UK, and (almost) EU – to show that a government is signalling major changes to come, but also (b) situated that policy instrument within a much broader discussion – of many tobacco policies in the UK and across the globe – to examine the extent to which it is already consistent with a well-established direction of travel.

To make such choices we need to consider:

• Breadth (to give the ‘big picture’) versus depth (to note important details forensically)
• How much we expect policy to change, given the size of the problem (a big feature in public health studies, which criticise government inaction)
• How radical policy change looks from the ‘top’ (at the point of central government choice) or the ‘bottom’ (longer-term delivery of policy by other bodies)
• What policies mean (what problem were policymakers trying to solve?)
• How consistent ‘policy’ seems when made of often-contradictory instruments

How do we solve the problem?

The problem is that we can produce very different accounts of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data more than others (e.g. during interviews).

Sometimes, my preferred solution is to compare more than one narrative of policy change. Another is simply to ‘show your work’.

Take home message for students: ‘show your work’ means explaining your logical process and step-by-step choices. Don’t just write that it is difficult to define policy and measure change. Instead, explain how you assess policy change in one important way, why you chose this way, and shine a light on the payoffs to your approach. Read up on how other scholars do it, to learn good practice and how to make your results comparable to theirs. Indeed, part of the benefit of using an established theory, to guide our analysis, is that we can engage in research systematically as a group.

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PS Here is the way in which I describe these issues to MPP students writing theory-driven coursework on policy and policy change (using the case study of UK tobacco policy as a guide):

 

Research design: Case studies and comparative research

My aim is to tell you about the use and value of comparative research by combining (a) a summary of your POLU9RM course reading, and (b) some examples from my research. Of course, I wouldn’t normally blow my own trumpet, but Dr Margulis insisted that I do so. Here is the podcast (25 minutes) which you can download or stream:

The reading for this session is Halperin and Heath’s chapter 9, which makes the following initial points about comparative research:

• ‘Comparative’ describes methods to identify and explain differences/ similarities between cases.
• These cases are often – but need not be – countries (for example, comparisons over time, or by policy area, can be just as illuminating).
• There are three main approaches: large-N (many cases), small-N (several cases), and single-N (or ‘case studies’).
• Comparison is not an end in itself. Rather, we need to justify, or clarify the value of, each comparison. This involves identifying a clear theoretical reason for a particular comparison (and, as in all studies, producing a clear research question that can be answered).
• It helps us avoid what Rose calls ‘false uniqueness’ (assuming rather than demonstrating that a case is exceptional) and ‘false universalism’ (assuming that a finding from one time/ place applies to all times or places).
• Comparative methods are most frequently used to determine the extent to which a theory generated from one set of cases applies to other cases.

Key issues when you apply theories to new cases

There are two interesting implications of the final bullet point.

First, note the tendency of a small number of countries to dominate academic publication. For example, a lot of the policy theories to which I refer in this ‘1000 words’ series derive from studies of the US. With many theories, you can see interesting developments when scholars apply them outside of the US:

• The ‘universal’ v ‘territorial’ issue. In my article with Michael Jones (summarised here) on Kingdon’s ‘multiple streams analysis’ we note that it began as a study of health/ transport policy in the US in the 1980s. It then morphed into a theory applied to many regions at many times. A large part of its success comes from the abstract nature of its key concepts, which can be applied at any place and time: for example, a lot of its discussion of agenda setting relates to ‘bounded rationality’ which applies to all people. Yet, there are also ‘territorial’ issues which apply to particular regions or types of government. For example, some studies adapt MSA’s concepts to explain the influence of supranational authorities or to describe the differences between EU and US policymaking.
• The ‘beyond the West’ issue. In one interesting application of MSA to China, Zhu argues that a key concept is not applicable: policy change in the US requires policy solutions to be technically feasible; in China, they only prompt change if ‘infeasible’. The example highlights the limits to the explanatory power of theories derived from studies of a small number of ‘Western’ countries (I know this description is loaded – what other terms could we use to describe countries like the US and UK?). In such cases, scholars are now exploring the implications in some depth: how well do these policy theories travel?

Second, consider the extent to which we are accumulating knowledge when applying the same theory to many cases. There are now some major reviews or debates of key policy theories, in which the authors highlight the difficulties of systematic research to produce a large number of comparable case studies:

• The Social Construction of Target Populations (review by Pierce et al)
• The Institutional Analysis and Development Framework (Working Together by Poteete et al)
• Multiple streams approach (review by Jones et al)
• Punctuated equilibrium theory (see the live debate on the Comparative Agendas Project)
• The Advocacy Coalition Framework (intro to special PSJ issue)

For me, the important common factor in all of these reviews is that many scholars pay insufficient attention to the theory when applying its insights to new cases. Consequently, when you try to review the body of work, you find it difficult to generate an overall sense of developments by comparing many case studies. So, in my humble opinion, we’d be a lot better off if people did a proper review of the literature – and made sure that their concepts were clear and able to be ‘operationalised’ – before jumping into case study analysis. I wrote these blog posts for established scholars and new PhD students, but the argument should also apply to you as an undergraduate: get the basics right (which includes understanding the theory you are applying) to get the comparative research right. This is just as important as your case selection.

From case study to large-N research: choosing between depth and breadth?

Case studies. It is in this context that we might understand Halperin and Heath’s point that case study research (single-N) is comparative. You might be going into much depth to identify key aspects of a single case, but also considering the extent to which it compares meaningfully with other case studies using the same theory. All that we require in such examples is that you justify your case selection. In some examples, you are trying to see if a theory drawn from one country applies to another. Or, you might be interested in how far theories travel, or how applicable they are to cases which seem unusual or ‘deviant’. In some examples, we seek the ‘crucial case study’ that is central to the ‘confirmation or disconfirmation of a theory’ (p207), but don’t make the mistake of concluding that you need a new theory because the old one can only explain so much. Further, although single case studies should not be dismissed, you can only conclude so much from them. So, be careful to spell out and justify any conclusions that you find to be ‘generalisable’ to other cases.

Example 1. In my research, I often use US-origin theories to help explain policymaking by the UK and devolved governments. For example, I used the same approach as Kingdon (documentary analysis and semi-structured interviews) to identify, in great detail, the circumstances under which 4 governments in the UK introduced the same ban on smoking in public places (the take home message: there was more to it than you might think!).

Small-N studies. The systematic comparison of several cases allows you to extend analysis often without compromising on depth. However, there is great potential to bias your outcomes by cherry-picking cases to suit particular theories. So, we look for ways to justify case selection. Halperin and Heath go to some length to identify the problems of ‘selection on the dependent variable’, which can be summed up as: don’t compare cases just because they seem to have the same outcome in common (focus instead on what causes such outcomes). Two well-established approaches are ‘most similar systems design’ (MSSD) and ‘most different systems design’ (MDSD) (p209). With MSSD, you choose cases which share key explanatory factors/ characteristics (e.g. they have the same socio-economic/ political context) so that you can track the effects of one or more difference (perhaps in the spirit of a randomised control trial, but without the substance). With MDSD you choose cases which do not share characteristics so that you can track the effect of a key similarity.

Aside from the problems of case study selection bias, it’s worth noting how difficult it is to produce a clear MSSD or MDSD research design, since you are making value judgements about which shared/ not shared characteristics are crucial (see their discussion of necessary/ sufficient factors).

Example 2. Take the example of a study I did with Karin Ingold and Manuel Fischer recently, comparing ‘fracking’ policy and policymaking in the UK and Switzerland.  We use the same theory (the ACF) and same method (documentary analysis and a survey of key actors) in both countries. We used a survey to allow us to quantify key relationships between actors: to what extent do they share the same beliefs with other actors, and how likely are they to share information frequently with their allies and competitors?

We describe the research design as MDSD because their political systems represent two contrasting political system archetypes – the ‘majoritarian’ UK and ‘consensus’ Switzerland – which Lijphart describes as key factors in their contrasting policymaking processes. Yet, central to our argument is that there are policymaking processes common to policy subsystems despite their system differences. In effect, we try to measure the effect of political system design on subsystem dynamics and find a subtle but important impact.

We also find that, although these differences exist, their policy outcomes are remarkably similar. So, ‘most different’ systems often produce very similar policymaking processes and policy outcomes. Then, we note that if we had our time again we would have extended the analysis to subnational governments in the UK. The ‘most different’ design prompted us to focus on the UK central government and Swiss Cantons (the alleged locus of power in both cases), but maybe we could have started from an assumption that they are not as different as they look. Have a look and you can see the dilemmas that still play out in (what I think is) a well-designed study.

Example 3. I face the same difficulties when comparing policy and policymaking by the UK and Scottish Governments. In some respects, they are ‘most different’: ‘new Scottish politics’ was designed to contrast with ‘old Westminster’ (particularly when it came to elections; the Scottish Parliament is also unicameral). In others, they are similar: the ‘architects of devolution’ introduced a system that seems to be of the Westminster family (particularly the executive-legislative relationships). Further, Scotland remains part of the UK, and the UK Government retains responsibility for many policies affecting Scotland. Overall, it is difficult to say for sure how similar/ different are their systems (which I discuss in a series of lectures). So, the comparison is fraught with difficulty. In such examples, they key solution is to ‘show your working’: describe these problems and state how you work within them (for example, in my case, I try to examine the extent to which policymaking reflects ‘territorial’ context or ‘universal’ drivers’, partly by interviewing policymakers in each government).

Large-N (quantitative) studies.  Halperin and Heath lay out some of the potential benefits of large-N research. For example, it is easier to come to general conclusions about many countries by studying many countries (rather than trying to generalise from a few, which might not be representative). They also highlight the pitfalls, including the problem of meaning: when you ‘operationalise’ a concept such as democracy or populism, can you provide a simple enough definition to allow you to give each system a number (to denote democratic/ undemocratic or X% democratic) that means the same thing in each case? To this problem, I would add the general issue of breadth and depth. With large-N studies you can examine the effects of a small number of variables, to explain a small part of the politics of many systems. With small-N you can study a large number of variables in a few systems. The classic trade-off is between breadth and depth. Of course, if you are doing an undergraduate dissertation the big Q is: what can you reasonably be expected to do? Maybe your highest aim should be to make sense of the studies which already exist.