Policy Analysis in 750 Words: how much impact can you expect from your analysis?

This post forms one part of the Policy Analysis in 750 words series overview.

Throughout this series you may notice three different conceptions about the scope of policy analysis:

1. ‘Ex ante’ (before the event) policy analysis. Focused primarily on defining a problem, and predicting the effect of solutions, to inform current choice (as described by Meltzer and Schwartz and Thissen and Walker).
2. ‘Ex post’ (after the event) policy analysis. Focused primarily on monitoring and evaluating that choice, perhaps to inform future choice (as described famously by Weiss).
3. Some combination of both, to treat policy analysis as a continuous (never-ending) process (as described by Dunn).

As usual, these are not hard-and-fast distinctions, but they help us clarify expectations in relation to different scenarios.

1. The impact of old-school ex ante policy analysis

Radin provides a valuable historical discussion of policymaking with the following elements:

• a small number of analysts, generally inside government (such as senior bureaucrats, scientific experts, and – in particular- economists),
• giving technical or factual advice,
• about policy formulation,
• to policymakers at the heart of government,
• on the assumption that policy problems would be solved via analysis and action.

This kind of image signals an expectation for high impact: policy analysts face low competition, enjoy a clearly defined and powerful audience, and their analysis is expected to feed directly into choice.

Radin goes on to describe a much different, modern policy environment: more competition, more analysts spread across and outside government, with a less obvious audience, and – even if there is a client – high uncertainty about where the analysis fits into the bigger picture.

Yet, the impetus to seek high and direct impact remains.

This combination of shifting conditions but unshifting hopes/ expectations helps explain a lot of the pragmatic forms of policy analysis you will see in this series, including:

• Keep it catchy, gather data efficiently, tailor your solutions to your audience, and tell a good story (Bardach)
• Speak with an audience in mind, highlight a well-defined problem and purpose, project authority, use the right form of communication, and focus on clarity, precision, conciseness, and credibility ( Smith)
• Address your client’s question, by their chosen deadline, in a clear and concise way that they can understand (and communicate to others) quickly (Weimer and Vining)
• Client-oriented advisors identify the beliefs of policymakers and anticipate the options worth researching (Mintrom)
• Identify your client’s resources and motivation, such as how they seek to use your analysis, the format of analysis they favour (make it ‘concise’ and ‘digestible’), their deadline, and their ability to make or influence the policies you might suggest (Meltzer and Schwartz).
• ‘Advise strategically’, to help a policymaker choose an effective solution within their political context (Thissen and Walker).
• Focus on producing ‘policy-relevant knowledge’ by adapting to the evidence-demands of policymakers and rejecting a naïve attachment to ‘facts speaking for themselves’ or ‘knowledge for its own sake’ (Dunn).

2. The impact of research and policy evaluation

Many of these recommendations are familiar to scientists and researchers, but generally in the context of far lower expectations about their likely impact, particularly if those expectations are informed by policy studies (compare Oliver & Cairney with Cairney & Oliver).

In that context, Weiss’ work is a key reference point. It gives us a menu of ways in which policymakers might use policy evaluation (and research evidence more widely):

• to inform solutions to a problem identified by policymakers
• as one of many sources of information used by policymakers, alongside ‘stakeholder’ advice and professional and service user experience
• as a resource used selectively by politicians, with entrenched positions, to bolster their case
• as a tool of government, to show it is acting (by setting up a scientific study), or to measure how well policy is working
• as a source of ‘enlightenment’, shaping how people think over the long term (compare with this discussion of ‘evidence based policy’ versus ‘policy based evidence’).

In other words, researchers may have a role, but they struggle (a) to navigate the politics of policy analysis, (b) find the right time to act, and (c) to secure attention, in competition with many other policy actors.

3. The potential for a form of continuous impact

Dunn suggests that the idea of ‘ex ante’ policy analysis is misleading, since policymaking is continuous, and evaluations of past choices inform current choices. Think of each policy analysis steps as ‘interdependent’, in which new knowledge to inform one step also informs the other four. For example, routine monitoring helps identify compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly, and if we can make a causal link between the policy solutions and outcomes. Its impact is often better seen as background information with intermittent impact.

Key conclusions to bear in mind

1. The demand for information from policy analysts may be disproportionately high when policymakers pay attention to a problem, and disproportionately low when they feel that they have addressed it.
2. Common advice for policy analysts and researchers often looks very similar: keep it concise, tailor it to your audience, make evidence ‘policy relevant’, and give advice (don’t sit on the fence). However, unless researchers are prepared to act quickly, to gather data efficiently (not comprehensively), to meet a tight brief for a client, they are not really in the impact business described by most policy analysis texts.
3. A lot of routine, continuous, impact tends to occur out of the public spotlight, based on rules and expectations that most policy actors take for granted.

Further reading

See the Policy Analysis in 750 words series overview to continue reading on policy analysis.

See the ‘evidence-based policymaking’ page to continue reading on research impact.

Bristol powerpoint: Paul Cairney Bristol EBPM January 2020

Policy Concepts in 1000 Words: how do policy theories describe policy change?

The 1000 words and 500 words series already show how important but difficult it is to define and measure policy change. In this post, Dr Leanne Giordono and I dig deeper into the – often confusingly different – ways in which different researchers conceptualise this process. We show why there is such variation and provide a checklist of questions to ask of any description of policy change.

Measuring policy change is more difficult than it looks

The measurement of policy change is important. Most ‘what is policy?’ discussions remind us that there can be a huge difference between policy as a (a)  statement of intent, (b) strategy, (c) collection of tools/ instruments and (d) contributor to policy outcomes.

Policy theories remind us that, while politicians and political parties often promise to sweep into office and produce radical departures from the past, most policy change is minor. There is a major gap between stated intention and actual outcomes, partly because policymakers do not control the policy process for which they are responsible. Instead, they inherit the commitments of their predecessors and make changes at the margins.

The 1000 words and 500 words posts suggest that we address this problem of measurement by identifying the use of a potentially large number of policy instruments or policy tools such as regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal.

Then, they suggest that we tell a story of policy change, focusing on (a) what problem policymakers were trying to solve, and the size of their response in relation to the size of the problem, and (b) the precise nature of specific changes, or how each change contributes to the ‘big picture’.

This recommendation highlights a potentially major problem: as researchers, we can produce very different narratives of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data than others.

Three ways to navigate different approaches to imagining and measuring change

Researchers use many different concepts and measures to define and identify policy change. It would be unrealistic – and perhaps unimaginative – to solve this problem with a call for one uniform approach.

Rather, our aim is to help you (a) navigate this diverse field by (b) identifying the issues and concepts that will help you interpret and compare different ways to measure change.

1. Check if people are ‘showing their work’

Pay close attention to how scholars are defining their terms. For example, be careful with incomplete definitions that rely on a reference to evolutionary change (which can mean so many different things) or incremental change (e.g. does an increment mean small or non-radical)? Or, note that frequent distinctions between minor versus major change seem useful, but we are often trying to capture and explain a confusing mixture of both.

2. Look out for different questions

Multiple typologies of change often arise because different theories ask and answer different questions:

• The Advocacy Coalition Framework distinguishes between minor and major change, associating the former with routine ‘policy-oriented learning’, and the latter with changes in core policy beliefs, often caused by a ‘shock’ associated with policy failure or external events.
• Innovation and Diffusion models examine the adoption and non-adoption of a specific policy solution over a specific period of time in multiple jurisdictions as a result of learning, imitation, competition or coercion.
• Classic studies of public expenditure generated four categories to ask if the ‘budgetary process of the United States government is equivalent to a set of temporally stable linear decision rules’. They describe policy change as minor and predictable and explain outliers as deviations from the norm.
• Punctuated Equilibrium Theory identifies a combination of (a) huge numbers of small policy change and (b) small numbers of huge change as the norm, in budgetary and other policy changes.
• Hall distinguishes between (a) routine adjustments to policy instruments, (b) changes in instruments to achieve existing goals, and (c) complete shifts in goals. He compares long periods in which (1) some ideas dominate and institutions do not change, with (2) ‘third order’ change in which a profound sense of failure contributes to a radical shift of beliefs and rules.
• More recent scholarship identifies a range of concepts – including layering, drift, conversion, and displacement – to explain more gradual causes of profound changes to institutions.

These approaches identify a range of possible sources of measures:

1. a combination of policy instruments that add up to overall change
2. the same single change in many places
3. change in relation to one measure, such as budgets
4. a change in ideas, policy instruments and/ or rules.

As such, the potential for confusion is high when we include all such measures under the single banner of ‘policy change’.

3. Look out for different measures

Spot the different ways in which scholars try to ‘operationalize’ and measure policy change, quantitatively and/ or qualitatively, with reference to four main categories.

1. Size can be measured with reference to:

• A comparison of old and new policy positions.
• A change observed in a sample or whole population (using, for example, standard deviations from the mean).
• An ‘ideal’ state, such as an industry or ‘best practice’ standard.

2. Speed describes the amount of change that occurs over a specific interval of time, such as:

• How long it takes for policy to change after a specific event or under specific conditions.
• The duration of time between commencement and completion (often described as ‘sudden’ or ‘gradual’).
• How this speed compares with comparable policy changes in other jurisdictions (often described with reference to ‘leaders’ and ‘laggards’).

3. Direction describes the course of the path from one policy state to another. It is often described in comparison to:

• An initial position in one jurisdiction (such as an expansion or contraction).
• Policy or policy change in other jurisdictions (such as via ‘benchmarking’ or ‘league tables’)
• An ‘ideal’ state (such as with reference to left or right wing aims).

4. Substance relates to policy change in relations to:

• Relatively tangible instruments such as legislation, regulation, or public expenditure.
• More abstract concepts such as in relation to beliefs or goals.

Take home points for students

Be thoughtful when drawing comparisons between applications, drawn from many theoretical traditions, and addressing different research questions.  You can seek clarity by posing three questions:

1. How clearly has the author defined the concept of policy change?
2. How are the chosen theories and research questions likely to influence the author’s operationalization of policy change?
3. How does the author operationalize policy change with respect to size, speed, direction, and/or substance?

However, you should also note that the choice of definition and theory may affect the meaning of measures such as size, speed, direction, and/or substance.

A general theory of public policy

This is a placeholder for future work and discussion. It tails off at the end.

People sometimes talk about a ‘general theory’ of public policy to put in our minds a comparison with the physical sciences. Usually, the punchline is that there are ‘no general theories of public policy that are not bounded by space or time’ (p21). There may be some reference to the accumulation of knowledge or wisdom in policy studies, but based rarely on the understanding that policy studies contain the equivalent of general laws (I can only think of one possible exception).

This outcome is not too surprising in the social sciences, in which context really matters and we would expect a lot of variation in policy, policymaking, and outcomes.

On the other hand, we still need a way to communicate our findings, relate them to other studies, compare them, and wonder what it all adds up to. Few people go as far as expressing the sense that every study is unique (to the point of non-comparability) and that every description of policymaking does not compare to another.

In other words, we may be looking for a happy medium, to reject the idea of general laws but encourage – when appropriate or necessary – enough of a sense of common outlook and experience to help us communicate with each other (without descending too quickly into heated debate on our cross-purposes). Or, we can at least tell a story of policy studies and invite others to learn from, or challenge, its insights.

In my case, there are two examples in which it is necessary to project some sense of a common and initially-not-too-complicated story:

1. When describing policy theory insights to students, on the assumption that it may be their gateway to more reading.

It is possible to choose how many words to devote to each topic, including 500 Words, 1000 Words, a 9000 word Understanding Public Policy chapter, more in the source material, and even more if students start to ‘snowball’.

It is also possible, if you have a clearly defined audience, to introduce some level of uncertainty about these descriptions and their limitations.

For example, I try to describe ‘the policy process’ in 500 words and 1000 words, but in the context of a wider discussion of images of the policy process.

It is also possible to provide more context, such as in this kind of introductory box, coupled with 12 things to know about studying public policy

(from Chapter 1)

You can also get into the idea that my story is one of many, particularly after students have invested in many versions of that story by the end of an introductory book

(from Chapter 13)

2. When describing these insights to people – from other disciplines or professions – who do not have the time, inclination, or frame of reference to put in that kind of work.

In this case, one presentation or article may be the limit. People may want to know the answer to a question – e.g. Why don’t policymakers listen to your evidence? – rather than hear all about the explanation for the answer.

You do your best, and then – if there is time – you talk about what you missed out.

For example, in this talk, the first question was: why didn’t you mention the role of power?

 

A general theory or a general understanding? Two key issues

That was a long-winded introduction to a more philosophical point about what we might want from general theories. My impression is that you might be seeking one of these two possibilities:

1. To use theories and concepts to describe material reality. In producing a general theory, we seek a general understanding of the ways in which the real world works. If so, we may focus primarily on how well these concepts describe the world, and the extent to which we can produce methods to produce systematic and consistent findings. The lack of a general theory denotes too much complexity and context.
2. To use theories and concepts to represent a useful story. In producing a general understanding, we focus on the ways in which people generate and communicate their understanding. If so, we may focus more on how people come together to produce and share meaning through concepts. The lack of a general theory could reflect the lack of agreement on how to study policymaking. Or, the presence of a general understanding could represent the exercise of power, to set the agenda and limit scholarly attention to a small number of theories.

I describe this distinction in the following audio clip, produced halfway through a run with the dogs, while jetlagged. The large gap in the middle happens when I am trying to see if the voice to text is working well enough for me to copy/paste it here (no).

Key examples of the exercise of power include:

1. The act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge (discussed in power and knowledge and Chapter 3).
2. Ongoing discussions about how we deal with (a) a relatively new focus (among the most-established policy theories) on policy studies in countries in the Global South, given that (b) the dominant interpretations of policymaking come from experiences in the Global North.

So, if you read these posts or Chapter 13 you will find a story of a general understanding of policy followed, almost immediately, by a list of reasons for why you should engage with it critically and perhaps not accept it. I’m setting your agenda but also reminding you that I’m doing it.

That’s it really. To be continued.

Understanding Public Policy 2nd edition

All going well, it will be out in November 2019. We are now at the proofing stage.

I have included below the summaries of the chapters (and each chapter should also have its own entry (or multiple entries) in the 1000 Words and 500 Words series).

 

Evidence-informed policymaking: context is everything

I thank James Georgalakis for inviting me to speak at the inaugural event of IDS’ new Evidence into Policy and Practice Series, and the audience for giving extra meaning to my story about the politics of ‘evidence-based based policymaking’. The talk (using powerpoint) and Q&A is here:

 

James invited me to respond to some of the challenges raised to my talk – in his summary of the event – so here it is.

I’m working on a ‘show, don’t tell’ approach, leaving some of the story open to interpretation. As a result, much of the meaning of this story – and, in particular, the focus on limiting participation – depends on the audience.

For example, consider the impact of the same story on audiences primarily focused on (a) scientific evidence and policy, or (b) participation and power.

Normally, when I talk about evidence and policy, my audience is mostly people with scientific or public health backgrounds asking why do policymakers ignore scientific evidence? I am usually invited to ruffle feathers, mostly by challenging a – remarkably prevalent – narrative that goes like this:

• We know what the best evidence is, since we have produced it with the best research methods (the ‘hierarchy of evidence’ argument).
• We have evidence on the nature of the problem and the most effective solutions (the ‘what works’ argument).
• Policymakers seems to be ignoring our evidence or failing to act proportionately (the ‘evidence-policy barriers’ argument).
• Or, they cherry-pick evidence to suit their agenda (the ‘policy based evidence’ argument).

In that context, I suggest that there are many claims to policy-relevant knowledge, policymakers have to ignore most information before making choices, and they are not in control of the policy process for which they are ostensibly in charge.

Limiting participation as a strategic aim

Then, I say to my audience that – if they are truly committed to maximising the use of scientific evidence in policy – they will need to consider how far they will go to get what they want. I use the metaphor of an ethical ladder in which each rung offers more influence in exchange for dirtier hands: tell stories and wait for opportunities, or demonise your opponents, limit participation, and humour politicians when they cherry-pick to reinforce emotional choices.

It’s ‘show don’t tell’ but I hope that the take-home point for most of the audience is that they shouldn’t focus so much on one aim – maximising the use of scientific evidence – to the detriment of other important aims, such as wider participation in politics beyond a reliance on a small number of experts. I say ‘keep your eyes on the prize’ but invite the audience to reflect on which prizes they should seek, and the trade-offs between them.

Limited participation – and ‘windows of opportunity’ – as an empirical finding

I did suggest that most policymaking happens away from the sphere of ‘exciting’ and ‘unruly’ politics. Put simply, people have to ignore almost every issue almost all of the time. Each time they focus their attention on one major issue, they must – by necessity – ignore almost all of the others.

For me, the political science story is largely about the pervasiveness of policy communities and policymaking out of the public spotlight.

The logic is as follows. Elected policymakers can only pay attention to a tiny proportion of their responsibilities. They delegate the rest to bureaucrats at lower levels of government. Bureaucrats lack specialist knowledge, and rely on other actors for information and advice. Those actors trade information for access. In many cases, they develop effective relationships based on trust and a shared understanding of the policy problem.

Trust often comes from a sense that everyone has proven to be reliable. For example, they follow norms or the ‘rules of the game’. One classic rule is to contain disputes within the policy community when actors don’t get what they want: if you complain in public, you draw external attention and internal disapproval; if not, you are more likely to get what you want next time.

For me, this is key context in which to describe common strategic concerns:

• Should you wait for a ‘window of opportunity’ for policy change? Maybe. Or, maybe it will never come because policymaking is largely insulated from view and very few issues reach the top of the policy agenda.
• Should you juggle insider and outsider strategies? Yes, some groups seem to do it well and it is possible for governments and groups to be in a major standoff in one field but close contact in another. However, each group must consider why they would do so, and the trade-offs between each strategy. For example, groups excluded from one venue may engage (perhaps successfully) in ‘venue shopping’ to get attention from another. Or, they become discredited within many venues if seen as too zealous and unwilling to compromise. Insider/outsider may seem like a false dichotomy to experienced and well-resourced groups, who engage continuously, and are able to experiment with many approaches and use trial-and-error learning. It is a more pressing choice for actors who may have only one chance to get it right and do not know what to expect.

Where is the power analysis in all of this?

I rarely use the word power directly, partly because – like ‘politics’ or ‘democracy’ – it is an ambiguous term with many interpretations (see Box 3.1). People often use it without agreeing its meaning and, if it means everything, maybe it means nothing.

However, you can find many aspects of power within our discussion. For example, insider and outsider strategies relate closely to Schattschneider’s classic discussion in which powerful groups try to ‘privatise’ issues and less powerful groups try to ‘socialise’ them. Agenda setting is about using resources to make sure issues do, or do not, reach the top of the policy agenda, and most do not.

These aspects of power sometimes play out in public, when:

• Actors engage in politics to turn their beliefs into policy. They form coalitions with actors who share their beliefs, and often romanticise their own cause and demonise their opponents.
• Actors mobilise their resources to encourage policymakers to prioritise some forms of knowledge or evidence over others (such as by valuing scientific evidence over experiential knowledge).
• They compete to identify the issues most worthy of our attention, telling stories to frame or define policy problems in ways that generate demand for their evidence.

However, they are no less important when they play out routinely:

• Governments have standard operating procedures – or institutions – to prioritise some forms of evidence and some issues routinely.
• Many policy networks operate routinely with few active members.
• Certain ideas, or ways of understanding the world and the nature of policy problems within it, becomes so dominant that they are unspoken and taken for granted as deeply held beliefs. Still, they constrain or facilitate the success of new ‘evidence based’ policy solutions.

In other words, the word ‘power’ is often hidden because the most profound forms of power often seem to be hidden.

In the context of our discussion, power comes from the ability to define some evidence as essential and other evidence as low quality or irrelevant, and therefore define some people as essential or irrelevant. It comes from defining some issues as exciting and worthy of our attention, or humdrum, specialist and only relevant to experts. It is about the subtle, unseen, and sometimes thoughtless ways in which we exercise power to harness people’s existing beliefs and dominate their attention as much as the transparent ways in which we mobilise resources to publicise issues. Therefore, to ‘maximise the use of evidence’ sounds like an innocuous collective endeavour, but it is a highly political and often hidden use of power.

See also:

I discussed these issues at a storytelling workshop organised by the OSF:

See also:

Policy in 500 Words: Power and Knowledge

The politics of evidence-based policymaking

Palgrave Communications: The politics of evidence-based policymaking

Using evidence to influence policy: Oxfam’s experience

The UK government’s imaginative use of evidence to make policy

 

Taking lessons from policy theory into practice: 3 examples

Notes for ANZSOG/ ANU Crawford School/ UNSW Canberra workshop. Powerpoint here. The recording of the lecture (skip to 2m30) and Q&A is here (right click to download mp3 or dropbox link):

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:

1. Central government policymakers may accept the descriptive accuracy of policy theories emphasising limited central control, but not the recommendation that they should let go, share power, and describe their limits to the public.
2. Scientists may accept key limitations to ‘evidence based policymaking’ but reject the idea that they should respond by becoming better storytellers or more manipulative operators.
3. Researchers and practitioners struggle to resolve hard choices when combining evidence and ‘coproduction’ while ‘scaling up’ policy interventions. Evidence choice is political choice. Can we do more than merely encourage people to accept this point?

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:

• If we insist on keeping the cycle metaphor, it is more accurate to see the process as a huge set of policy cycles that connect with each other in messy and unpredictable ways.
• The cycle approach also links strongly to the idea of ‘comprehensive rationality’ in which a small group of policymakers and analysts are in full possession of the facts and full control of the policy process. They carry out their aims through a series of stages.

Policy theories provide more descriptive and explanatory usefulness. Their insights include:

• Limited choice. Policymakers inherit organisations, rules, and choices. Most ‘new’ choice is a revision of the old.
• Limited attention. Policymakers must ignore almost all of the policy problems for which they are formally responsible. They pay attention to some, and delegate most responsibility to civil servants. Bureaucrats rely on other actors for information and advice, and they build relationships on trust and information exchange.
• Limited central control. Policy may appear to be made at the ‘top’ or in the ‘centre’, but in practice policymaking responsibility is spread across many levels and types of government (many ‘centres’). ‘Street level’ actors make policy as they deliver. Policy outcomes appear to ‘emerge’ locally despite central government attempts to control their fate.
• Limited policy change. Most policy change is minor, made and influenced by actors who interpret new evidence through the lens of their beliefs. Well-established beliefs limit the opportunities of new solutions. Governments tend to rely on trial-and-error, based on previous agreements, rather than radical policy change based on a new agenda. New solutions succeed only during brief and infrequent windows of opportunity.

However, the cycle metaphor endures because:

• It provides a simple model of policymaking with stages that map onto important policymaking functions.
• It provides a way to project policymaking to the public. You know how we make policy, and that we are in charge, so you know who to hold to account.

In that context, we may want to be pragmatic about our advice:

1. One option is via complexity theory, in which scholars generally encourage policymakers to accept and describe their limits:

• Accept routine error, reduce short-term performance management, engage more in trial and error, and ‘let go’ to allow local actors the flexibility to adapt and respond to their context.
• However, would a government in the Westminster tradition really embrace this advice? No. They need to balance (a) pragmatic policymaking, and (b) an image of governing competence.

2. Another option is to try to help improve an existing approach.

• Koski and Workman build on PET to recommend ways to process information more effectively.
• Studies built on MSA tend to focus on ‘entrepreneurs’ having a technically and politically feasible solution ready for the next window of opportunity.
• Sanderson describes the skills required for ‘intelligent policymaking’.
• I sum up these approaches in ‘How Can Policy Theory Have an Impact on Policy Making?’ Teaching Public Administration, 33, 1, 22-39 

Further reading (blog posts):

The language of complexity does not mix well with the language of Westminster-style accountability

Making Sense of Policymaking: why it’s always someone else’s fault and nothing ever changes

Two stories of British politics: the Westminster model versus Complex Government

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.

So, I wrote The Politics of Evidence-Based Policymaking and one zillion blog posts to help identify the ways in which policy theories could help explain the relationship between evidence and policy.

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:

1. they have a broader view on what counts as good evidence (see ANZSOG description)
2. they have to ignore almost all information (a nice way into bounded rationality and policymaker psychology)
3. they do not understand or control the process in which they seek to use evidence (a way into ‘the policy process’)

We can then consider many possible responses in the sequel What can you do when policymakers ignore your evidence?

Examples include:

• ‘How to do it’ advice. I compare tips for individuals (from experienced practitioners) with tips based on policy concepts. They are quite similar-looking tips – e.g. find out where the action is, learn the rules, tell good stories, engage allies, seek windows of opportunity – but I describe mine as 5 impossible tasks!
• Organisational reform. I describe work with the European Commission Joint Research Centre to identify 8 skills or functions of an organisation bringing together the supply/demand of knowledge.
• Ethical dilemmas. I use key policy theories to ask people how far they want to go to privilege evidence in policy. It’s fun to talk about these things with the type of scientist who sees any form of storytelling as manipulation.

Further reading:

Is Evidence-Based Policymaking the same as good policymaking?

A 5-step strategy to make evidence count

Political science improves our understanding of evidence-based policymaking, but does it produce better advice?

Principles of science advice to government: key problems and feasible solutions

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:

• Policy learning is a political process, and expert-driven learning is one of many possibilities, alongside dialogue, bargaining, and hierarchical models.
• Indeed, researchers often do badly because they don’t learn how to deal with the politics.
• Policy transfer can be maximal or minimal, and driven voluntarily or via coercion. A policy solution, when ‘imported’, can be mimicked, translated or transformed.
• When transfer is voluntary, receptivity to new solutions is more important than their supply.
• There are very different ‘evidence-based’ models on how to ‘scale up’ policy success.

So, when we start to focus on sharing lessons, we will have three things to discover:

1. What is the evidence for success, and from where does it come? Governments often project success without backing it up.
2. What story do policymakers tell about the problem they are trying to solve, the solutions they produced, and why? Two different governments may be framing and trying to solve the same problem in very different ways.
3. Was the policy introduced in a comparable policymaking system? People tend to focus on political system comparability (e.g. is it unitary or federal?), but I think the key is in policymaking system comparability (e.g. what are the rules and dominant ideas?).

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.

Teaching evidence based policy to fly: how to deal with the politics of policy learning and transfer

This post provides (a generous amount of) background for my ANZSOG talk Teaching evidence based policy to fly: transferring sound policies across the world.

The event’s description sums up key conclusions in the literature on policy learning and policy transfer:

1. technology and ‘entrepreneurs’ help ideas spread internationally, and domestic policymakers can use them to be more informed about global policy innovation, but
2. there can be major unintended consequences to importing ideas, such as the adoption of policy solutions with poorly-evidenced success, or a broader sense of failed transportation caused by factors such as a poor fit between the aims of the exporter/importer.

In this post, I connect these conclusions to broader themes in policy studies, which suggest that:

3. policy learning and policy transfer are political processes, not ‘rational’ or technical searches for information
4. the use of evidence to spread policy innovation requires two interconnected choices: what counts as good evidence, and what role central governments should play.
5. the following ’11 question guide’ to evidence based policy transfer serves more as a way to reflect than a blueprint for action.

As usual, I suggest that we focus less on how we think we’d like to do it, and more on how people actually do it.

Policy transfer describes the use of evidence about policy in one political system to help develop policy in another. Taken at face value, it sounds like a great idea: why would a government try to reinvent the wheel when another government has shown how to do it?

Therefore, wouldn’t it be nice if I turned up to the lecture, equipped with a ‘blueprint’ for ‘evidence based’ policy transfer, and declared how to do it in a series of realistic and straightforward steps? Unfortunately, there are three main obstacles:

1. ‘Evidence based’ is a highly misleading description of the use of information in policy.
2. To transfer a policy blueprint completely, in this manner, would require all places and contexts to be the same, and for the policy process to be technocratic and apolitical.
3. There are general academic guides on how to learn lessons from others systematically – such as Richard Rose’s ‘practical guide’  – but most academic work on learning and transfer does not suggest that policymakers follow this kind of advice.

Instead, policy learning is a political process – involving the exercise of power to determine what and how to learn – and it is difficult to separate policy transfer from the wider use of evidence and ideas in policy processes.

Let’s take each of these points in turn, before reflecting on their implications for any X-step guide:

3 reasons why ‘evidence based’ does not describe policymaking

In a series of ANZSOG talks on ‘evidence based policymaking’ (EBPM), I describe three main factors, all of which are broadly relevant to transfer:

1. There are many forms of policy-relevant evidence and few policymakers adhere to a strict ‘hierarchy’ of knowledge.

Therefore, it is unclear how one government can, or should, generate evidence of another government’s policy success.

2. Policymakers must find ways to ignore most evidence – such as by combining ‘rational’ and ‘irrational’ cognitive shortcuts – to be able to act quickly.

The generation of policy transfer lessons is a highly political process in which actors adapt to this need to prioritise information while competing with each other. They exercise power to: prioritise some information and downplay the rest, define the nature of the policy problem, and evaluate the success of another government’s solutions. There is a strong possibility that policymakers will import policy solutions without knowing if, and why, they were successful.

3. They do not control the policy process in which they engage.

We should not treat ‘policy transfer’ as separate from the policy process in which policymakers and influencers engage. Rather, the evidence of international experience competes with many other sources of ideas and evidence within a complex policymaking system.

The literature on ‘policy learning’ tells a similar story

Studies of the use of evaluation evidence (perhaps to answer the question: was this policy successful?) have long described policymakers using the research process for many different purposes, from short term problem-solving and long-term enlightenment, to putting off decisions or using evidence cynically to support an existing policy.

We should therefore reject the temptation to (a) equate ‘policy learning’ with a simplistic process that we might associate with teachers transmitting facts to children, or (b) assume that adults simply change their beliefs when faced with new evidence. Rather, Dunlop and Radaelli describe policy learning as a political process in the following ways:

1.It is collective and rule-bound

Individuals combine cognition and emotion to process information, in organisations with rules that influence their motive and ability to learn, and in wider systems, in which many actors cooperate and compete to establish the rules of evidence gathering and analysis, or policymaking environments that constrain or facilitate their action.

2.’Evidence based’ is one of several types of policy learning

• Epistemic. Primarily by scientific experts transmitting knowledge to policymakers.
• Reflection. Open dialogue to incorporate diverse forms of knowledge and encourage cooperation.
• Bargaining. Actors learn how to cooperate and compete effectively.
• Hierarchy. Actors with authority learn how to impose their aims; others learn the limits to their discretion.

3.The process can be ‘dysfunctional’: driven by groupthink, limited analysis, and learning how to dominate policymaking, not improve policy.

Their analysis can produce relevant take-home points such as:

• Experts will be ineffective if they assume that policy learning is epistemic. The assumption will leave them ill-prepared to deal with bargaining.
• There is more than one legitimate way to learn, such as via deliberative processes that incorporate more perspectives and forms of knowledge.

What does the literature on transfer tell us?

‘Policy transfer’ can describe a spectrum of activity:

• driven voluntarily, by a desire to learn from the story of another government’s policy’s success. In such cases, importers use shortcuts to learning, such as by restricting their search to systems with which they have something in common (such as geography or ideology), learning via intermediaries such as ‘entrepreneurs’, or limiting their searches for evidence of success.
• driven by various forms of pressure, including encouragement by central (or supranational) governments, international norms or agreements, ‘spillover’ effects causing one system to respond to innovation by another, or demands by businesses to minimise the cost of doing business.

In that context, some of the literature focuses on warning against unsuccessful policy transfer caused by factors such as:

• Failing to generate or use enough evidence on what made the initial policy successful
• Failing to adapt that policy to local circumstances
• Failing to back policy change with sufficient resources

However, other studies highlight some major qualifications:

• If the process is about using ideas about one system to inform another, our attention may shift from ‘transfer’ to ‘translation’ or ‘transformation’, and the idea of ‘successful transfer’ makes less sense
• Transfer success is not the same as implementation success, which depends on a wider range of factors
• Nor is it the same as ‘policy success’, which can be assessed by a mix of questions to reflect political reality: did it make the government more re-electable, was the process of change relatively manageable, and did it produce intended outcomes?

The use of evidence to spread policy innovation requires a combination of profound political and governance choices

When encouraging policy diffusion within a political system, choices about: (a) what counts as ‘good’ evidence of policy success have a major connection to (b) what counts as good governance.

For example, consider these ideal-types or models in table 1:

In one scenario, we begin by relying primarily on RCT evidence (multiple international trials) and import a relatively fixed model, to ensure ‘fidelity’ to a proven intervention and allow us to measure its effect in a new context. This choice of good evidence limits the ability of subnational policymakers to adapt policy to local contexts.

In another scenario, we begin by relying primary on governance principles, such as to respect local discretion as well as incorporate practitioner and user experience as important knowledge claims. The choice of governance model relates closely to a less narrow sense of what counts as good evidence, but also a more limited ability to evaluate policy success scientifically.

In other words, the political choice to privilege some forms of evidence is difficult to separate from another political choice to privilege the role of one form of government.

Telling a policy transfer story: 11 questions to encourage successful evidence based policy transfer  

In that context, these steps to evidence-informed policy transfer serve more to encourage reflection than provide a blueprint for action. I accept that 11 is less catchy than 10.

1. What problem did policymakers say they were trying to solve, and why?
2. What solution(s) did they produce?
3. Why?

Points 1-3 represent the classic and necessary questions from policy studies: (1) ‘what is policy?’ (2)  ‘how much did policy change?’ and (3) why? Until we have a good answer, we do not know how to draw comparable lessons. Learning from another government’s policy choices is no substitute for learning from more meaningful policy change.

4. Was the project introduced in a country or region which is sufficiently comparable? Comparability can relate to the size and type of country, the nature of the problem, the aims of the borrowing/ lending government and their measures of success.

5. Was it introduced nationwide, or in a region which is sufficiently representative of the national experience (it is not an outlier)?

6. How do we account for the role of scale, and the different cultures and expectations in each policy field?

Points 4-6 inform initial background discussions of case study reports. We need to focus on comparability when describing the context in which the original policy developed. It is not enough to state that two political systems are different. We need to identify the relevance and implications of the differences, from another government’s definition of the problem to the logistics of their task.

7. Has the project been evaluated independently, subject to peer review and/ or using measures deemed acceptable to the government?

8. Has the evaluation been of a sufficient period in proportion to the expected outcomes?

9. Are we confident that this project has been evaluated the most favourably – i.e. that our search for relevant lessons has been systematic, based on recognisable criteria (rather than reputations)?

10. Are we identifying ‘Good practice’ based on positive experience, ‘Promising approaches’ based on positive but unsystematic findings, ‘Research–based’ or based on ‘sound theory informed by a growing body of empirical research’, or ‘Evidence–based’, when ‘the programme or practice has been rigorously evaluated and has consistently been shown to work’?

Points 7-10 raise issues about the relationships between (a) what evidence we should use to evaluate success or potential, and (b) how long we should wait to declare success.

11. What will be the relationship between evidence and governance?

Should we identify the same basic model and transfer it uniformly, tell a qualitative story about the model and invite people to adapt it, or focus pragmatically on an eclectic range of evidential sources and focus on the training of the actors who will implement policy?

In conclusion

Information technology has allowed us to gather a huge amount of policy-relevant information across the globe. However, it has not solved the limitations we face in defining policy problems clearly, gathering evidence on policy solutions systematically, and generating international lessons that we can use to inform domestic policy processes.

This rise in available evidence is not a substitute for policy analysis and political choice. These choices range from how to adjudicate between competing policy preference, to how to define good evidence and good government. A lack of attention to these wider questions helps explain why – at least from some perspectives – policy transfer seems to fail.

Paul Cairney Auckland Policy Transfer 12.10.18

 

 

Why don’t policymakers listen to your evidence?

Since 2016, my most common academic presentation to interdisciplinary scientist/ researcher audiences is a variant of the question, ‘why don’t policymakers listen to your evidence?’

I tend to provide three main answers.

1. Many policymakers have many different ideas about what counts as good evidence

Few policymakers know or care about the criteria developed by some scientists to describe a hierarchy of scientific evidence. For some scientists, at the top of this hierarchy is the randomised control trial (RCT) and the systematic review of RCTs, with expertise much further down the list, followed by practitioner experience and service user feedback near the bottom.

Yet, most policymakers – and many academics – prefer a wider range of sources of information, combining their own experience with information ranging from peer reviewed scientific evidence and the ‘grey’ literature, to public opinion and feedback from consultation.

While it may be possible to persuade some central government departments or agencies to privilege scientific evidence, they also pursue other key principles, such as to foster consensus driven policymaking or a shift from centralist to localist practices.

Consequently, they often only recommend interventions rather than impose one uniform evidence-based position. If local actors favour a different policy solution, we may find that the same type of evidence may have more or less effect in different parts of government.

2. Policymakers have to ignore almost all evidence and almost every decision taken in their name

Many scientists articulate the idea that policymakers and scientists should cooperate to use the best evidence to determine ‘what works’ in policy (in forums such as INGSA, European Commission, OECD). Their language is often reminiscent of 1950s discussions of the pursuit of ‘comprehensive rationality’ in policymaking.

The key difference is that EBPM is often described as an ideal by scientists, to be compared with the more disappointing processes they find when they engage in politics. In contrast, ‘comprehensive rationality’ is an ideal-type, used to describe what cannot happen, and the practical implications of that impossibility.

The ideal-type involves a core group of elected policymakers at the ‘top’, identifying their values or the problems they seek to solve, and translating their policies into action to maximise benefits to society, aided by neutral organisations gathering all the facts necessary to produce policy solutions. Yet, in practice, they are unable to: separate values from facts in any meaningful way; rank policy aims in a logical and consistent manner; gather information comprehensively, or possess the cognitive ability to process it.

Instead, Simon famously described policymakers addressing ‘bounded rationality’ by using ‘rules of thumb’ to limit their analysis and produce ‘good enough’ decisions. More recently, punctuated equilibrium theory uses bounded rationality to show that policymakers can only pay attention to a tiny proportion of their responsibilities, which limits their control of the many decisions made in their name.

More recent discussions focus on the ‘rational’ short cuts that policymakers use to identify good enough sources of information, combined with the ‘irrational’ ways in which they use their beliefs, emotions, habits, and familiarity with issues to identify policy problems and solutions (see this post on the meaning of ‘irrational’). Or, they explore how individuals communicate their narrow expertise within a system of which they have almost no knowledge. In each case, ‘most members of the system are not paying attention to most issues most of the time’.

This scarcity of attention helps explain, for example, why policymakers ignore most issues in the absence of a focusing event, policymaking organisations make searches for information which miss key elements routinely, and organisations fail to respond to events or changing circumstances proportionately.

In that context, attempts to describe a policy agenda focusing merely on ‘what works’ are based on misleading expectations. Rather, we can describe key parts of the policymaking environment – such as institutions, policy communities/ networks, or paradigms – as a reflection of the ways in which policymakers deal with their bounded rationality and lack of control of the policy process.

3. Policymakers do not control the policy process (in the way that a policy cycle suggests)

Scientists often appear to be drawn to the idea of a linear and orderly policy cycle with discrete stages – such as agenda setting, policy formulation, legitimation, implementation, evaluation, policy maintenance/ succession/ termination – because it offers a simple and appealing model which gives clear advice on how to engage.

Indeed, the stages approach began partly as a proposal to make the policy process more scientific and based on systematic policy analysis. It offers an idea of how policy should be made: elected policymakers in central government, aided by expert policy analysts, make and legitimise choices; skilful public servants carry them out; and, policy analysts assess the results with the aid of scientific evidence.

Yet, few policy theories describe this cycle as useful, while most – including the advocacy coalition framework , and the multiple streams approach – are based on a rejection of the explanatory value of orderly stages.

Policy theories also suggest that the cycle provides misleading practical advice: you will generally not find an orderly process with a clearly defined debate on problem definition, a single moment of authoritative choice, and a clear chance to use scientific evidence to evaluate policy before deciding whether or not to continue. Instead, the cycle exists as a story for policymakers to tell about their work, partly because it is consistent with the idea of elected policymakers being in charge and accountable.

Some scholars also question the appropriateness of a stages ideal, since it suggests that there should be a core group of policymakers making policy from the ‘top down’ and obliging others to carry out their aims, which does not leave room for, for example, the diffusion of power in multi-level systems, or the use of ‘localism’ to tailor policy to local needs and desires.

Now go to:

What can you do when policymakers ignore your evidence?

Further Reading

The politics of evidence-based policymaking

The politics of evidence-based policymaking: maximising the use of evidence in policy

Images of the policy process

How to communicate effectively with policymakers

Special issue in Policy and Politics called ‘Practical lessons from policy theories’, which includes how to be a ‘policy entrepreneur’.

See also the 750 Words series to explore the implications for policy analysis

Policy in 500 words: uncertainty versus ambiguity

In policy studies, there is a profound difference between uncertainty and ambiguity:

• Uncertainty describes a lack of knowledge or a worrying lack of confidence in one’s knowledge.
• Ambiguity describes the ability to entertain more than one interpretation of a policy problem.

Both concepts relate to ‘bounded rationality’: policymakers do not have the ability to process all information relevant to policy problems. Instead, they employ two kinds of shortcut:

• ‘Rational’. Pursuing clear goals and prioritizing certain sources of information.
• ‘Irrational’. Drawing on emotions, gut feelings, deeply held beliefs, and habits.

I make an artificially binary distinction, uncertain versus ambiguous, and relate it to another binary, rational versus irrational, to point out the pitfalls of focusing too much on one aspect of the policy process:

1. Policy actors seek to resolve uncertainty by generating more information or drawing greater attention to the available information.

Actors can try to solve uncertainty by: (a) improving the quality of evidence, and (b) making sure that there are no major gaps between the supply of and demand for evidence. Relevant debates include: what counts as good evidence?, focusing on the criteria to define scientific evidence and their relationship with other forms of knowledge (such as practitioner experience and service user feedback), and what are the barriers between supply and demand?, focusing on the need for better ways to communicate.

2. Policy actors seek to resolve ambiguity by focusing on one interpretation of a policy problem at the expense of another.

Actors try to solve ambiguity by exercising power to increase attention to, and support for, their favoured interpretation of a policy problem. You will find many examples of such activity spread across the 500 and 1000 words series:

• Actors combine facts with emotional appeals to draw attention to their issues, at the expense of attention to other issues in a crowded political environment.
• Actors form coalitions with people who share their beliefs. They romanticise their own cause and demonise their opponents.
• Actors tell simple stories with a hero and moral to appeal to the emotional and ideological biases of policymakers.
• Policy entrepreneurs use skills of persuasion to frame problems, make sure their favoured solutions are feasible, and exploit times when policymakers have the motive and opportunity to act.
• Dominant ways of thinking act as a lens through which we process information.
• Policymakers exploit stereotypes of target populations.

A focus on reducing uncertainty gives the impression that policymaking is a technical process in which people need to produce the best evidence and deliver it to the right people at the right time.

In contrast, a focus on reducing ambiguity gives the impression of a more complicated and political process in which actors are exercising power to compete for attention and dominance of the policy agenda. Uncertainty matters, but primarily to describe the role of a complex policymaking system in which no actor truly understands where they are or how they should exercise power to maximise their success.

Further reading:

For a longer discussion, see Fostering Evidence-informed Policy Making: Uncertainty Versus Ambiguity (PDF)

Or, if you fancy it in French: Favoriser l’élaboration de politiques publiques fondées sur des données probantes : incertitude versus ambiguïté (PDF)

Framing

The politics of evidence-based policymaking

To Bridge the Divide between Evidence and Policy: Reduce Ambiguity as Much as Uncertainty

How to communicate effectively with policymakers: combine insights from psychology and policy studies

Here is the relevant opening section in UPP:

The UK government’s imaginative use of evidence to make policy

This post describes a new article published in British Politics (Open Access). Please find:

(1) A super-exciting video/audio powerpoint I use for a talk based on the article

(2) The audio alone (link)

(3) The powerpoint to download, so that the weblinks work (link) or the ppsx/ presentation file in case you are having a party (link)

(4) A written/ tweeted discussion of the main points

May I have your attention as I describe to you my new article, 'The UK government’s imaginative use of evidence to make policy'? https://t.co/AD4BZBRsUf pic.twitter.com/c4P1NHJgNF

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

In retrospect, I think the title was too subtle and clever-clever. I wanted to convey two meanings: imaginative as a euphemism for ridiculous/ often cynical and to argue that a government has to be imaginative with evidence. The latter has two meanings: imaginative (1) in the presentation and framing of evidence-informed agenda, and (2) when facing pressure to go beyond the evidence and envisage policy outcomes.

So I describe two cases in which its evidence-use seems cynical, when:

1. Declaring complete success in turning around the lives of ‘troubled families’
2. Exploiting vivid neuroscientific images to support ‘early intervention’

Then I describe more difficult cases in which supportive evidence is not clear:

1. Family intervention project evaluations are of limited value and only tentatively positive
2. Successful projects like FNP and Incredible Years have limited applicability or ‘scalability’

As scientists, we can shrug our shoulders about the uncertainty, but elected policymakers in government have to do something. So what do they do?

At this point of the article it will look like I have become an apologist for David Cameron’s government. Instead, I’m trying to demonstrate the value of comparing sympathetic/ unsympathetic interpretations and highlight the policy problem from a policymaker’s perspective:

I suggest that they use evidence in a mix of ways to: describe an urgent problem, present an image of success and governing competence, and provide cover for more evidence-informed long term action.

The result is the appearance of top-down ‘muscular’ government and ‘a tendency for policy to change as is implemented, such as when mediated by local authority choices and social workers maintaining a commitment to their professional values when delivering policy’

I conclude by arguing that ‘evidence-based policy’ and ‘policy-based evidence’ are political slogans with minimal academic value. The binary divide between EBP/ PBE distracts us from more useful categories which show us the trade-offs policymakers have to make when faced with the need to act despite uncertainty.

As such, it forms part of a far wider body of work …

The article is part of (1) a larger project on ‘the politics of evidence-based policymaking’https://t.co/0haxkUcdba pic.twitter.com/jIPjBfqleW

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

The article is also part of (2) a larger project on politics, prevention, and early intervention in the lives of children and adults, with @EmilyStDenny https://t.co/rUTi1UIyGI pic.twitter.com/blIbLbkjbd

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

In both cases, the common theme is that, although (1) the world of top-down central government gets most attention, (2) central governments don’t even know what problem they are trying to solve, far less (3) how to control policymaking and outcomes.

In that wider context, it is worth comparing this talk with the one I gave at the IDS (which, I reckon is a good primer for – or prequel to – the UK talk):

@CairneyPaul came to @IDS_UK and challenged our assumptions about evidence use – are we just generating evidence with people who already agree with us? Watch https://t.co/EwvySbqLQs @TransformUre @JordanTchil @mleach_ids @JohnGaventa

— James Georgalakis (@Bloggs74) January 17, 2019

See also:

Early intervention policy, from ‘troubled families’ to ‘named persons’: problems with evidence and framing ‘valence’ issues

Why doesn’t evidence win the day in policy and policymaking?

(found by searching for early intervention)

See also:

Here’s why there is always an expectations gap in prevention policy

Social investment, prevention and early intervention: a ‘window of opportunity’ for new ideas?

(found by searching for prevention)

Powerpoint for guest lecture: Paul Cairney UK Government Evidence Policy

The global study of governance and public policy

I was invited by Dr Emamian from the Governance and Policy Think Tank to deliver this short lecture at the first ‘governance and public policy conference’ in Iran. I was unable to attend, so recorded a set of short video presentations supplemented by blog discussion. The topics to be covered include the importance of a scholarly network for policy studies, the need for a set of core policy concepts to act as a technical language for that network, and the need to apply that language to explain shifts in government and regulation towards ‘regulatory governance’.

Please note that my choice to record the videos in my garden (while I look up) seemed good at the time, for some very good reasons that I won’t get into. However, you will see that I become increasingly cold and annoyed at being cold. I can only apologize for my face and the fact that I was too cold to remember to put on my professional voice.

Using shared concepts in a scholarly network of policy researchers

Our aim may be to produce a global network of policy scholars, in two main ways:

1. To foster meetings and discussion, such as via this conference and others such as the ICPP and ECPR
2. To make sure that we are talking about the same thing. Most of the theories to which I refer are based on studies of countries like the US and UK. Their prominence contributes to a ‘global north’ perspective which can be useful in the abstract but with uncertain applicability across the globe.

For example, when considering the applicability of US-inspired theories, think about their taken-for-granted assumptions about the nature of a political system, in which leaders in many levels and types of government are elected regularly, there is a constitution guaranteeing a division of powers across legislative-executive-judicial branches and between federal/subnational levels, and people describe a ‘pluralist’ system in which many groups mobilise and counter-mobilise to influence policy.

What happens when we stop taking this political context for granted? Do these theories remain as relevant?

Which concepts do we use?

I describe two main abstract concepts then invite you to think about how to apply them in more concrete circumstances.

1. Bounded rationality, not comprehensive rationality.

No-one can understand fully the world in which we live. Individuals can only understand and pay attention to a tiny part of key aspects of the world such as political systems.

Indeed, a handy phrase to remember is that almost all people must ignore almost everything almost all of the time.

Yet, they must make choices despite uncertainty, perhaps by adopting ‘fast and frugal’ heuristics. In other words, we may see all human choices as flawed when compared with an ideal of perfect decision-making. On the other hand, we may marvel at the ways in which humans make often-good choices despite their limitations.

Individual policymakers use two short-cuts to gather enough information to make choices:

• ‘Rational’, in which they adopt measures to ensure that they have good enough information to inform decisions. For example, they prioritise certain written sources of information and draw on people they consider to be experts.
• ‘Irrational’, in which they rely on things like gut instinct, habit, and emotion to make snap decisions.

In that context, policy scholarship involves the study of how people make and influence those choices. One part is about the role of evidence, in which people produce information to reduce uncertainty about the nature of the world. However, the more important study is of how people understand the world in the first place. As policy scholars, we focus on ambiguity, to describe the many ways in which people choose to understand the same problems, and the exercise of power to influence those choices.

2. A complex policymaking environment, not a policy cycle.

Things get more complicated when we move from the analysis of (a) key individuals to (b) the interaction between many individuals and organisations in a complex policymaking ‘system’ or ‘environment’. Policy scholars describe this environment in many different ways, using different concepts, but we can identify a core set of terms on which to focus:

• Actors. There are many policy influencers and policymakers in many authoritative venues spread across many levels and types of government.
• Institutions. Each venue has its own rules, including the formal, written-down, and easy to understand rules, versus the informal norms, cultures, and practices which are difficult to identify and describe.
• Networks. Policymakers and influencers form relationships based on factors such as trust, authority, and the exchange of resources such as information and support.
• Ideas. People communicate their beliefs, about policy problems and potential solutions, within a wider understanding of the world (often described as a paradigm or hegemony). Some of that understanding is taken-for-granted and not described, and people limit their analysis and argument according to the ways in which they think other people see the world.
• Socioeconomic context and events. Policymakers often have to respond to policy conditions and events over which they have limited control, such geographic, demographic, and economic factors. These factors help produce non-routine ‘events’ alongside more predictable events such as elections (or other means to ensure a change of government).

In that context, policy scholarship focuses on producing theories to explain what happens when policymakers have limited control over their political systems and policymaking environments.

How far do these concepts travel?

As you can see, these concepts are widely applicable because they are abstract. What happens when we try to apply them to specific countries or case studies? For example:

1. We talk about policymakers using cognitive, moral, and emotional shortcuts, but those shortcuts can vary profoundly across the globe.
2. Each political system has a different collection of authoritative venues, formal and informal rules of politics, networks of power, ways to describe how the world works and should work, and socioeconomic context.

This is where our global network becomes valuable, to help us describe how we make sense of the same concepts in very different ways, and consider the extent to which such discussions are comparable.

Example: how do governments address an ‘era of governance’?

One way to foster such discussion is to consider how governments address the limits to their powers. These limits are described in many different ways, from a focus on ‘complexity’ and policy outcomes which ‘emerge’ from local activity (despite attempts by central governments to control outcomes), to a focus on the shift from ‘government’ to ‘governance’.

As policy scholars, we can make several useful distinctions to describe these dynamics, such as to separate an actual shift in policymaking from government to governance, versus a shift in the way we now describe government.

Or, we can separate how governments can, do, and should address the limits to their powers.

I’d say that most policy scholarship focuses on how governments operate: how they actually address problems and what are the – intended and unintended – consequences.

However, these studies are trying to describe the tensions between what governments can do, given the limits I describe, and what they think they should do, given their position of authority and their need to describe their success.

For example, some systems may be more conducive to the support for ‘polycentric governance’, in which many authoritative venues cooperate to address problems, while others are built on the idea of central control and the concentration of authority in a small group of actors.

Therefore, the study of actual policymaking and outcomes will vary markedly according to the ways in which government actors feel they need to assert an image of control over a policy environment which is almost immune to control.

Perhaps an ‘era of governance’ describes some recognition by many governments that they need to find new ways to address their limited control over policy outcomes, both domestically and globally. However, an enduring theme in political science and policy studies is that we do not explain policymaking well if we restrict our attention to the ‘rational’ decisions of a small number of actors. Let’s not make too many assumptions about their power and motive.

Further reading:

The New Policy Sciences

How to Communicate Effectively with Policymakers

The Politics of Evidence Based Policymaking

Comparison of Theories of the Policy Process

Key policy theories and concepts in 1000 words.

Debating the politics of evidence-based policy

My new essay on evidence-based policy is now out in the current issue of Public Administration: https://t.co/6qabMyvYa6. Nothing personal, @CairneyPaul @justinparkhurst @ProfStoker @MarkEvansACT… hope to continue the debate!

— Joshua Newman (@_joshuanewman) December 20, 2017

Joshua Newman has provided an interesting review of three recent books on evidence/ policy (click here). One of those books is mine: The Politics of Evidence-Based Policy Making (which you can access here).

His review is very polite, for which I thank him. I hope my brief response can be seen in a similarly positive light (well, I had hoped to make it brief). Maybe we disagree on one or two things, but often these discussions are about the things we emphasize and the way we describe similar points.

There are 5 points to which I respond because I have 5 digits on my right hand. I’d like you to think of me counting them out on my fingers. In doing so, I’ll use ‘Newman’ throughout, because that’s the academic convention, but I’d also like to you imagine me reading my points aloud and whispering ‘Joshua’ before each ‘Newman’.

1. Do we really need to ‘take the debate forward’ so often?

I use this phrase myself, knowingly, to keep a discussion catchy, but I think it’s often misleading. I suggest not to get your hopes up too high when Newman raises the possibility of taking the debate forward with his concluding questions. We won’t resolve the relationship between evidence, politics & policy by pretending to reframe the same collection of questions about the prospect of political reform that people have been asking for centuries. It is useful to envisage better political systems (the subject of Newman’s concluding remarks) but I don’t think we should pretend that this is a new concern or that it will get us very far.

Indeed, my usual argument is that researchers need to do something (such as improve how we engage in the policy process) while we wait for political system reforms to happen (while doubting if they will ever happen).

Further, Newman does not produce any political reforms to address the problems he raises. Rather, for example, he draws attention to Trump to describe modern democracies as ‘not pluralist utopias’ and to identify examples in which policymakers draw primarily on beliefs, not evidence. By restating these problems, he does not solve them. So, what are researchers supposed to do after they grow tired of complaining that the world does not meet their hopes or expectations?

In other words, for me, (a) promoting political change and (b) acting during its absence are two sides of the same coin. We go round and round more often than we take things forward.

2. What debate are we renaming?

Newman’s ‘we’ve heard it before’ argument seems more useful, but there is a lot to hear and relatively few people have heard it. I’d warn against the assumption that ‘I’ve heard this before’ can ever equal ‘we’ve heard it before’ (unless ‘we’ refers to a tiny group of specialists talking only to each other).

Rather, one of the most important things we can do as academics is to tell the same story to each other (to check if we understand the same story, in the same way, and if it remains useful) and to wider audiences (in a way that they can pick up and use without dedicating their career to our discipline).

Some of our most important insights endure for decades and they sometimes improve in the retelling. We apply them to new eras, and often come to the same basic conclusions, but it seems unhelpful to criticise a lack of complete novelty in individual texts (particularly when they are often designed to be syntheses). Why not use them to occasionally take a step back to discuss and clarify what we know?

Perhaps more importantly, I don’t think Newman is correct when he says that each book retells the story of the ‘research utilization’ literature. I’m retelling the story of policy theory, which describes how policymakers deal with bounded rationality in a complex policymaking environment. Policy theory’s intellectual histories often provide very different perspectives – of the policymaker trying to make good enough decisions, rather than the researcher trying to improve the uptake of their research – than the agenda inspired by Weiss et al (see for example The New Policy Sciences).

3. Don’t just ‘get political’; understand the policy process

I draw on policy theory because it helps people understand policymaking. It would be a mistake to conclude from my book that I simply want researchers to ‘get political’. Rather, I want them to develop useful knowledge of the policy process in which they might want to engage. This knowledge is not freely available; it takes time to understand the discipline and reflect on policy dynamics.

Yet, the payoff can be profound, if only because it helps people think about the difference between two analytically separate causes of a notional ‘evidence policy gap’: (a) individuals making choices based on their beliefs and limited information (which is relatively easy to understand but also to caricature), and (b) systemic or ‘environmental’ causes (which are far more difficult to conceptualise and explain, but often more useful to understand).

4. Don’t throw out the ‘two communities’ phrase without explaining why

Newman criticises the phrase ‘two communities’ as a description of silos in policymaking versus research, partly because (a) many policymakers use research frequently, and (b) the real divide is often between users/ non-users of research within policymaking organisations. In short, there are more than two communities.

I’d back up his published research with my anecdotal experience of giving talks to government audiences: researchers and analysts within government are often very similar in outlook to academics and they often talk in the same way as academics about the disconnect between their (original or synthetic) research and its use by their ‘operational’ colleagues.

Still, I’m not sure why Newman concludes that the ‘two communities’ phrase is ‘deeply flawed and probably counter-productive’. Yes, the world is more nuanced and less binary than ‘two communities’ suggests. Yes, the real divide may be harder to spot. Still, as Newman et al suggest: ‘Policy makers and academics should focus on bridging instruments that can bring their worlds closer together’. This bullet point from their article seems, to me, to be the point of using the phrase ‘two communities’. Maybe Caplan used the phrase differently in 1979, but to assert its historic meaning then reject the phrase’s use in modern discussion seems less useful than simply clarifying the argument in ways such as:

• There is no simple policymaker/ academic divide but, … note the major difference in requirements between (a) people who produce or distribute research without taking action, which allows them (for example) to be more comfortable with uncertainty, and (b) people who need to make choices despite having incomplete information to hand.
• You might find a more receptive audience in one part of government (e.g. research/ analytical) than another (e.g. operational), so be careful about generalising from singular experiences.

5. Should researchers engage in the policy process?

Newman says that each book, ‘unfairly places the burden of resolving the problem in the hands of an ill-equipped group of academics, operating outside the political system’.

I agree with Newman when he says that many researchers do not possess the skills to engage effectively in the policy process. Scientific training does not equip us with political skills. Indeed, I think you could read a few of my blog posts and conclude, reasonably, that you would like nothing more to do with the policy process because you’d be more effective by focusing on research.

The reason I put the onus back on researchers is because I am engaging with arguments like the one expressed by Newman (in other words, part of the meaning comes from the audience). Many people conclude their evidence policy discussions by identifying (or ‘reframing’) the problem primarily as the need for political reform. For me, the focus on other people changing to suit your preferences seems unrealistic and misplaced. In that context, I present the counter-argument that it may be better to adapt effectively to the policy process that exists, not the one you’d like to see. Sometimes it’s more useful to wear a coat than complain about the weather.

See also:  The Politics of Evidence 

The Politics of Evidence revisited

 

What do we need to know about the politics of evidence-based policymaking?

Today, I’m helping to deliver a new course – Engaging Policymakers Training Programme – piloted by the Alliance for Useful Evidence and the UCL. Right now, it’s for UCL staff (and mostly early career researchers). My bit is about how we can better understand the policy process so that we can engage in it more effectively.  I have reproduced the brief guide below (for my two 2-hour sessions as part of a wider block). If anyone else is delivering something similar, please let me know. We could compare notes. 

This module will be delivered in two parts to combine theory and practice

Part 1: What do we need to know about the politics of evidence-based policymaking?

Policy theories provide a wealth of knowledge about the role of evidence in policymaking systems. They prompt us to understand and respond to two key dynamics:

1. Policymaker psychology. Policymakers combine rational and irrational shortcuts to gather information and make good enough decisions quickly. To appeal to rational shortcuts and minimise cognitive load, we reduce uncertainty by providing syntheses of the available evidence. To appeal to irrational shortcuts and engage emotional interest, we reduce ambiguity by telling stories or framing problems in specific ways.
2. Complex policymaking environments. These processes take place in the context of a policy environment out of the control of individual policymakers. Environments consist of: many actors in many levels and types of government; engaging with institutions and networks, each with their own informal and formal rules; responding to socioeconomic conditions and events; and, learning how to engage with dominant ideas or beliefs about the nature of the policy problem. In other words, there is no policy cycle or obvious stage in which to get involved.

In this seminar, we discuss how to respond effectively to these dynamics. We focus on unresolved issues:

1. Effective engagement with policymakers requires storytelling skills, but do we possess them?
2. It requires a combination of evidence and emotional appeals, but is it ethical to do more than describe the evidence?
3. The absence of a policy cycle, and presence of an ever-shifting context, requires us to engage for the long term, to form alliances, learn the rules, and build up trust in the messenger. However, do we have and how should we invest the time?

The format will be relatively informal. Cairney will begin by making some introductory points (not a powerpoint driven lecture) and encourage participants to relate the three questions to their research and engagement experience.

Gateway to further reading:

• Paul Cairney and Richard Kwiatkowski (2017) ‘How to communicate effectively with policymakers: combine insights from psychology and policy studies’, Palgrave Communications
• Paul Cairney and Kathryn Oliver (2017) ‘Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?’ Health Research Policy and Systems (HARPS), DOI: 10.1186/s12961-017-0192-x
• Paul Cairney, Kathryn Oliver, and Adam Wellstead (2016) ‘To Bridge the Divide between Evidence and Policy: Reduce Ambiguity as Much as Uncertainty’, Public Administration Review, Early View (forthcoming) DOI:10.1111/puar.12555 PDF

Part 2: How can we respond pragmatically and effectively to the politics of EBPM?

In this seminar, we move from abstract theory and general advice to concrete examples and specific strategies. Each participant should come prepared to speak about their research and present a theoretically informed policy analysis in 3 minutes (without the aid of powerpoint). Their analysis should address:

1. What policy problem does my research highlight?
2. What are the most technically and politically feasible solutions?
3. How should I engage in the policy process to highlight these problems and solutions?

After each presentation, each participant should be prepared to ask questions about the problem raised and the strategy to engage. Finally, to encourage learning, we will reflect on the memorability and impact of presentations.

• See: How to write theory-driven policy analysis

Powerpoint: Paul Cairney A4UE UCL 2017

How to write theory-driven policy analysis

Writing theory driven policy analysis 10.11.17

(or right click to download this lecture which accompanies my MPP)

Here is a guide to writing theory-driven policy analysis. Your aim is to identify a policy problem and solution, know your audience, and account for the complexity of policymaking.

At first, it may seem like daunting task to put together policy analysis and policy theory. On its own, policy analysis seems difficult but relatively straightforward: use evidence to identify and measure a policy problem, compare the merits of one or more solution, and make a recommendation on the steps to take us from policy to action.

However, policy process research tells us that people will engage emotionally with that evidence, and that policymakers operate in a complex system of which they have very limited knowledge and control.

So, how can we produce a policy analysis paper to which people will pay attention, and respond positively and effectively, under such circumstances? I focus on developing the critical analysis that will help you produce effective and feasible analysis. To do so, I show how policy analysis forms part of a collection of exercises to foster analysis informed by theory and reflection.

Aims of this document:

1. Describe the context. There are two fields of study – theory and analysis – which do not always speak to each other. Theory can inform analysis, but it is not always clear how. I show the payoff to theory-driven policy analysis and the difference between it and regular analysis. Note the two key factors that policy analysis should address: your audience will engage emotionally with your analysis, and the feasibility of your solutions depends on the complexity of the policy environment.
2. Describe how the coursework helps you combine policy theory and policy analysis. Policy analysis is one of four tasks. There is a reflection, to let you ‘show your work’; how your knowledge of policy theory guides your description of a problem and feasible solutions. The essay allows you to expand on theory, to describe how and why policy changes (and therefore what a realistic policy analysis would look like). The blogs encourage new communication skills. In one, you explore how you would expect a policy maker or influencer to sell the recommendations in your policy analysis. In another, you explain complex concepts to a non-academic audience.

Background notes.

I have written this document as if part of a book to be called Teaching Public Policy and co-authored with Dr Emily St Denny.

For that audience, I have two aims: (1) to persuade policy scholars-as-teachers to adopt this kind of coursework in their curriculum; and, (2) to show students how to complete it effectively.

If you prefer shorter advice, see Writing a policy paper and blog post and Writing an essay on politics, policymaking, and policy change.

If you are interested in more background reading, see: The New Policy Sciences (by Paul Cairney and Chris Weible) which describes the need to combine policy theory-driven research with policy analysis; and, Practical Lessons from Policy Theories which describes eight attempts by scholars to translate policy theory into lessons that can be used for policy analysis.

The theories make more sense if you have read the corresponding 1000 Words posts (based on Cairney, 2012). Some of the forthcoming text will look familiar if you read my blog because I am consolidating several individual posts into an overall discussion.

I’m not quite there yet (the chapter is a first draft, a bit scrappy at times, and longer than a chapter should be), so all comments welcome (in the comments bit).

Writing theory driven policy analysis 10.11.17

Evidence based policymaking: 7 key themes

I looked back at my blog posts on the politics of ‘evidence based policymaking’ and found that I wrote quite a lot (particularly from 2016). Here is a list based on 7 key themes.

1. Use psychological insights to influence the use of evidence

My most-current concern. The same basic theme is that (a) people (including policymakers) are ‘cognitive misers’ seeking ‘rational’ and ‘irrational’ shortcuts to gather information for action, so you won’t get far if you (b) bombard them with information, or (c) call them idiots.

Three ways to communicate more effectively with policymakers (shows how to use psychological insights to promote evidence in policymaking)

Using psychological insights in politics: can we do it without calling our opponents mental, hysterical, or stupid? (yes)

The Psychology of Evidence Based Policymaking: Who Will Speak For the Evidence if it Doesn’t Speak for Itself? (older paper, linking studies of psychology with studies of EBPM)

Older posts on the same theme:

Is there any hope for evidence in emotional debates and chaotic government? (yes)

We are in danger of repeating the same mistakes if we bemoan low attention to ‘facts’

These complaints about ignoring science seem biased and naïve – and too easy to dismiss

How can we close the ‘cultural’ gap between the policymakers and scientists who ‘just don’t get it’?

2. How to use policy process insights to influence the use of evidence

I try to simplify key insights about the policy process to show to use evidence in it. One key message is to give up on the idea of an orderly policy process described by the policy cycle model. What should you do if a far more complicated process exists?

Why don’t policymakers listen to your evidence?

The Politics of Evidence Based Policymaking: 3 messages (3 ways to say that you should engage with the policy process that exists, not a mythical process that will never exist)

Three habits of successful policy entrepreneurs (shows how entrepreneurs are influential in politics)

Why doesn’t evidence win the day in policy and policymaking? and What does it take to turn scientific evidence into policy? Lessons for illegal drugs from tobacco and There is no blueprint for evidence-based policy, so what do you do? (3 posts describing the conditions that must be met for evidence to ‘win the day’)

Writing for Impact: what you need to know, and 5 ways to know it (explains how our knowledge of the policy process helps communicate to policymakers)

How can political actors take into account the limitations of evidence-based policy-making? 5 key points (presentation to European Parliament-European University Institute ‘Policy Roundtable’ 2016)

Evidence Based Policy Making: 5 things you need to know and do (presentation to Open Society Foundations New York 2016)

What 10 questions should we put to evidence for policy experts? (part of a series of videos produced by the European Commission)

3. How to combine principles on ‘good evidence’, ‘good governance’, and ‘good practice’

My argument here is that EBPM is about deciding at the same time what is: (1) good evidence, and (2) a good way to make and deliver policy. If you just focus on one at a time – or consider one while ignoring the other – you cannot produce a defendable way to promote evidence-informed policy delivery.

Kathryn Oliver and I have just published an article on the relationship between evidence and policy (summary of and link to our article on this very topic)

We all want ‘evidence based policy making’ but how do we do it? (presentation to the Scottish Government on 2016)

The ‘Scottish Approach to Policy Making’: Implications for Public Service Delivery

The politics of evidence-based best practice: 4 messages

The politics of implementing evidence-based policies

Policy Concepts in 1000 Words: the intersection between evidence and policy transfer

Key issues in evidence-based policymaking: comparability, control, and centralisation

The politics of evidence and randomised control trials: the symbolic importance of family nurse partnerships

What Works (in a complex policymaking system)?

How Far Should You Go to Make Sure a Policy is Delivered?

4. Face up to your need to make profound choices to pursue EBPM

These posts have arisen largely from my attendance at academic-practitioner conferences on evidence and policy. Many participants tell the same story about the primacy of scientific evidence challenged by post-truth politics and emotional policymakers. I don’t find this argument convincing or useful. So, in many posts, I challenge these participants to think about more pragmatic ways to sum up and do something effective about their predicament.

Political science improves our understanding of evidence-based policymaking, but does it produce better advice? (shows how our knowledge of policymaking clarifies dilemmas about engagement)

The role of ‘standards for evidence’ in ‘evidence informed policymaking’ (argues that a strict adherence to scientific principles may help you become a good researcher but not an effective policy influencer)

How far should you go to secure academic ‘impact’ in policymaking? From ‘honest brokers’ to ‘research purists’ and Machiavellian manipulators (you have to make profound ethical and strategic choices when seeking to maximise the use of evidence in policy)

Principles of science advice to government: key problems and feasible solutions (calling yourself an ‘honest broker’ while complaining about ‘post-truth politics’ is a cop out)

What sciences count in government science advice? (political science, obvs)

I know my audience, but does my other audience know I know my audience? (compares the often profoundly different ways in which scientists and political scientists understand and evaluate EBPM – this matters because, for example, we rarely discuss power in scientist-led debates)

Is Evidence-Based Policymaking the same as good policymaking? (no)

Idealism versus pragmatism in politics and policymaking: … evidence-based policymaking (how to decide between idealism and pragmatism when engaging in politics)

Realistic ‘realist’ reviews: why do you need them and what might they look like? (if you privilege impact you need to build policy relevance into systematic reviews)

‘Co-producing’ comparative policy research: how far should we go to secure policy impact? (describes ways to build evidence advocacy into research design)

The Politics of Evidence (review of – and link to – Justin Parkhurt’s book on the ‘good governance’ of evidence production and use)

5. For students and researchers wanting to read/ hear more

These posts are relatively theory-heavy, linking quite clearly to the academic study of public policy. Hopefully they provide a simple way into the policy literature which can, at times, be dense and jargony.

‘Evidence-based Policymaking’ and the Study of Public Policy

Policy Concepts in 1000 Words: ‘Evidence Based Policymaking’

Practical Lessons from Policy Theories (series of posts on the policy process, offering potential lessons for advocates of evidence use in policy)

Writing a policy paper and blog post 

12 things to know about studying public policy

Can you want evidence based policymaking if you don’t really know what it is? (defines each word in EBPM)

Can you separate the facts from your beliefs when making policy? (no, very no)

Policy Concepts in 1000 Words: Success and Failure (Evaluation) (using evidence to evaluate policy is inevitably political)

Policy Concepts in 1000 Words: Policy Transfer and Learning (so is learning from the experience of others)

Four obstacles to evidence based policymaking (EBPM)

What is ‘Complex Government’ and what can we do about it? (read about it)

How Can Policy Theory Have an Impact on Policy Making? (on translating policy theories into useful advice)

The role of evidence in UK policymaking after Brexit (argues that many challenges/ opportunities for evidence advocates will not change after Brexit)

Why is there more tobacco control policy than alcohol control policy in the UK? (it’s not just because there is more evidence of harm)

Evidence Based Policy Making: If You Want to Inject More Science into Policymaking You Need to Know the Science of Policymaking and The politics of evidence-based policymaking: focus on ambiguity as much as uncertainty and Revisiting the main ‘barriers’ between evidence and policy: focus on ambiguity, not uncertainty and The barriers to evidence based policymaking in environmental policy (early versions of what became the chapters of the book)

6. Using storytelling to promote evidence use

This is increasingly a big interest for me. Storytelling is key to the effective conduct and communication of scientific research. Let’s not pretend we’re objective people just stating the facts (which is the least convincing story of all). So far, so good, except to say that the evidence on the impact of stories (for policy change advocacy) is limited. The major complication is that (a) the story you want to tell and have people hear interacts with (b) the story that your audience members tell themselves.

Combine Good Evidence and Emotional Stories to Change the World

Storytelling for Policy Change: promise and problems

Is politics and policymaking about sharing evidence and facts or telling good stories? Two very silly examples from #SP16

7. The major difficulties in using evidence for policy to reduce inequalities

These posts show how policymakers think about how to combine (a) often-patchy evidence with (b) their beliefs and (c) an electoral imperative to produce policies on inequalities, prevention, and early intervention. I suggest that it’s better to understand and engage with this process than complain about policy-based-evidence from the side-lines. If you do the latter, policymakers will ignore you.

The UK government’s imaginative use of evidence to make policy 

What do you do when 20% of the population causes 80% of its problems? Possibly nothing.

The theory and practice of evidence-based policy transfer: can we learn how to reduce territorial inequalities?

We need better descriptions than ‘evidence-based policy’ and ‘policy-based evidence’: the case of UK government ‘troubled families’ policy

How can you tell the difference between policy-based-evidence and evidence-based-policymaking?

Early intervention policy, from ‘troubled families’ to ‘named persons’: problems with evidence and framing ‘valence’ issues

Key issues in evidence-based policymaking: comparability, control, and centralisation

The politics of evidence and randomised control trials: the symbolic importance of family nurse partnerships

Two myths about the politics of inequality in Scotland

Social investment, prevention and early intervention: a ‘window of opportunity’ for new ideas?

A ‘decisive shift to prevention’: how do we turn an idea into evidence based policy?

Can the Scottish Government pursue ‘prevention policy’ without independence?

Note: these issues are discussed in similar ways in many countries. One example that caught my eye today:

"Changing concepts of 'evidence'" visual summary @fletchermj @PowerToPersuade @PSResearchG #P2P2017 pic.twitter.com/6M9QgTXAyW

— Lisa Carson (@DrLisaCResearch) August 23, 2017

 

All of this discussion can be found under the EBPM category: https://paulcairney.wordpress.com/category/evidence-based-policymaking-ebpm/T

See also the special issue on maximizing the use of evidence in policy

How can governments better collaborate to address complex problems?

This is a guest post by William L. Swann (left) and Seo Young Kim (right), discussing how to use insights from the Institutional Collective Action Framework to think about how to improve collaborative governance. The full paper has been submitted to the series for Policy and Politics called Practical Lessons from Policy Theories.

Many public policy problems cannot be addressed effectively by a single, solitary government. Consider the problems facing the Greater Los Angeles Area, a heavily fragmented landscape of 88 cities and numerous unincorporated areas and special districts. Whether it is combatting rising homelessness, abating the country’s worst air pollution, cleaning the toxic L.A. River, or quelling gang violence, any policy alternative pursued unilaterally is limited by overlapping authority and externalities that alter the actions of other governments.

Problems of fragmented authority are not confined to metropolitan areas. They are also found in multi-level governance scenarios such as the restoration of Chesapeake Bay, as well as in international relations as demonstrated by recent global events such as “Brexit” and the U.S.’s withdrawal from the Paris Climate Agreement. In short, fragmentation problems manifest at every scale of governance, horizontally, vertically, and even functionally within governments.

What is an ‘institutional collective action’ dilemma?

In many cases governments would be better off coordinating and working together, but they face barriers that prevent them from doing so. These barriers are what the policy literature refers to as ‘institutional collective action’ (ICA) dilemmas, or collective action problems in which a government’s incentives do not align with collectively desirable outcomes. For example, all governments in a region benefit from less air pollution, but each government has an incentive to free ride and enjoy cleaner air without contributing to the cost of obtaining it.

The ICA Framework, developed by Professor Richard Feiock, has emerged as a practical analytical instrument for understanding and improving fragmented governance. This framework assumes that governments must match the scale and coerciveness of the policy intervention (or mechanism) to the scale and nature of the policy problem to achieve efficient and desired outcomes.

For example, informal networks (a mechanism) can be highly effective at overcoming simple collective action problems. But as problems become increasingly complex, more obtrusive mechanisms, such as governmental consolidation or imposed collaboration, are needed to achieve collective goals and more efficient outcomes. The more obtrusive the mechanism, however, the more actors’ autonomy diminishes and the higher the transaction costs (monitoring, enforcement, information, and agency) of governing.

Three ways to improve institutional collaborative governance

We explored what actionable steps policymakers can take to improve their results with collaboration in fragmented systems. Our study offers three general practical recommendations based on the empirical literature that can enhance institutional collaborative governance.

First, institutional collaboration is more likely to emerge and work effectively when policymakers employ networking strategies that incorporate frequent, face-to-face interactions.

Government actors networking with popular, well-endowed actors (“bridging strategies”) as well as developing closer-knit, reciprocal ties with a smaller set of actors (“bonding strategies”) will result in more collaborative participation, especially when policymakers interact often and in-person.

Policy network characteristics are also important to consider. Research on estuary governance indicates that in newly formed, emerging networks, bridging strategies may be more advantageous, at least initially, because they can provide organizational legitimacy and access to resources. However, once collaboratives mature, developing stronger and more reciprocal bonds with fewer actors reduces the likelihood of opportunistic behavior that can hinder collaborative effectiveness.

Second, policymakers should design collaborative arrangements that reduce transaction costs which hinder collaboration.

Well-designed collaborative institutions can lower the barriers to participation and information sharing, make it easier to monitor the behaviors of partners, grant greater flexibility in collaborative work, and allow for more credible commitments from partners.

Research suggests policymakers can achieve this by

1. identifying similarities in policy goals, politics, and constituency characteristics with institutional partners
2. specifying rules such as annual dues, financial reporting, and making financial records reviewable by third parties to increase commitment and transparency in collaborative arrangements
3. creating flexibility by employing adaptive agreements with service providers, especially when services have limited markets/applications and performance is difficult to measure.

Considering the context, however, is crucial. Collaboratives that thrive on informal, close-knit, reciprocal relations, for example, may be severely damaged by the introduction of monitoring mechanisms that signal distrust.

Third, institutional collaboration is enhanced by the development and harnessing of collaborative capacity.

Research suggests signaling organizational competencies and capacities, such as budget, political support, and human resources, may be more effective at lowering barriers to collaboration than ‘homophily’ (a tendency to associate with similar others in networks). Policymakers can begin building collaborative capacity by seeking political leadership involvement, granting greater managerial autonomy, and looking to higher-level governments (e.g., national, state, or provincial governments) for financial and technical support for collaboration.

What about collaboration in different institutional contexts?

Finally, we recognize that not all policymakers operate in similar institutional contexts, and collaboration can often be mandated by higher-level authorities in more centralized nations. Nonetheless, visible joint gains, economic incentives, transparent rules, and equitable distribution of joint benefits and costs are critical components of voluntary or mandated collaboration.

Conclusions and future directions

The recommendations offered here are, at best, only the tip of the iceberg on valuable practical insight that can be gleaned from collaborative governance research. While these suggestions are consistent with empirical findings from broader public management and policy networks literatures, much could be learned from a closer inspection of the overlap between ICA studies and other streams of collaborative governance work.

Collaboration is a valuable tool of governance, and, like any tool, it should be utilized appropriately. Collaboration is not easily managed and can encounter many obstacles. We suggest that governments generally avoid collaborating unless there are joint gains that cannot be achieved alone. But the key to solving many of society’s intractable problems, or just simply improving everyday public service delivery, lies in a clearer understanding of how collaboration can be used effectively within different fragmented systems.

The Politics of Evidence

This is a draft of my review of Justin Parkhurst (2017) The Politics of Evidence (Routledge, Open Access)

Justin Parkhurst’s aim is to identify key principles to take forward the ‘good governance of evidence’. The good governance of scientific evidence in policy and policymaking requires us to address two fundamentally important ‘biases’:

1. Technical bias. Some organisations produce bad evidence, some parts of government cherry-pick, manipulate, or ignore evidence, and some politicians misinterpret the implications of evidence when calculating risk. Sometimes, these things are done deliberately for political gain. Sometimes they are caused by cognitive biases which cause us to interpret evidence in problematic ways. For example, you can seek evidence that confirms your position, and/ or only believe the evidence that confirms it.
2. Issue bias. Some evidence advocates use the mantra of ‘evidence based policy’ to depoliticise issues or downplay the need to resolve conflicts over values. They also focus on the problems most conducive to study via their most respected methods such as randomised control trials (RCTs). Methodological rigour trumps policy relevance and simple experiments trump the exploration of complex solutions. So, we lose sight of the unintended consequences of producing the ‘best’ evidence to address a small number of problems, and making choices about the allocation of research resources and attention. Again, this can be deliberate or caused by cognitive biases, such as to seek simpler and more answerable questions than complex questions with no obvious answer.

To address both problems, Parkhurst seeks pragmatic ways to identify principles to decide what counts as ‘good evidence to inform policy’ and ‘what constitutes the good use of evidence within a policy process’:

‘it is necessary to consider how to establish evidence advisory systems that promote the good governance of evidence – working to ensure that rigorous, sys­tematic and technically valid pieces of evidence are used within decision-making processes that are inclusive of, representative of and accountable to the multiple social interests of the population served’ (p8).

Parkhurst identifies some ways in which to bring evidence and policy closer together. First, to produce evidence more appropriate for, or relevant to, policymaking (‘good evidence for policy’):

1. Relate evidence more closely to policy goals.
2. Modify research approaches and methods to answer policy relevant questions.
3. Ensure that the evidence relates to the local or relevant context.

Second, to produce the ‘good use of evidence’, combine three forms of ‘legitimacy’:

1. Input, to ensure democratic representative bodies have the final say.
2. Throughput, to ensure widespread deliberation.
3. Output, to ensure proper consideration the use of the most systematic, unbiased and rigorously produced scientific evidence relevant to the problem.

In the final chapter, Parkhurst suggests that these aims can be pursued in many ways depending on how governments want to design evidence advisory systems, but that it’s worth drawing on the examples of good practice he identifies. Parkhurst also explores the role for Academies of science, or initiatives such as the Cochrane Collaboration, to provide independent advice. He then outlines the good governance of evidence built on key principles: appropriate evidence, accountability in evidence use, transparency, and contestability (to ensure sufficient debate).

The overall result is a book full of interesting discussion and very sensible, general advice for people new to the topic of evidence and policy. This is no mean feat: most readers will seek a clearly explained and articulate account of the subject, and they get it here.

For me, the most interesting thing about Parkhurst’s book is the untold story, or often-implicit reasoning behind the way in which it is framed. We can infer that it is not a study aimed primarily at a political science or social science audience, because most of that audience would take its starting point for granted: the use of evidence is political, and politics involves values. Yet, Parkhurst feels the need to remind the reader of this point, in specific (“it is worth noting that the US presidency is a decidedly political role”, p43) and general circumstances (‘the nature of policymaking is inherently political’, p65). Throughout, the audience appears to be academics who begin with a desire for ‘evidence based policy’ without fully thinking through the implications, either about the lack of a magic bullet of evidence to solve a policy problem, how we might maintain a political system conducive to democratic principles and good evidence use, how we might design a system to reduce key ‘barriers’ between the supply of evidence by scientists and its demand by policymakers, and why few such designs have taken off.

In other words, the book appeals primarily to scientists trained outside social science, some of whom think about politics in their spare time, or encounter it in dispiriting encounters with policymakers. It appeals to that audience with a statement on the crucial role of high quality evidence in policymaking, highlights barriers to its use, tells scientists that they might be part of the problem, but then provides them with the comforting assurance that we can design better systems to overcome at least some of those barriers. For people trained in policy studies, this concluding discussion seems like a tall order, and I think most would read it with great scepticism.

Policy scientists might also be sceptical about the extent to which scientists from other fields think this way about hierarchies of scientific evidence and the desire to depoliticise politics with a primary focus on ‘what works’. Yet, I too hear this language regularly in interdisciplinary workshops (often while standing next to Justin!), and it is usually accompanied by descriptions of the pathology of policymaking, the rise of post-truth politics and rejection of experts, and the need to focus on the role of objective facts in deciding what policy solutions work best. Indeed, I was impressed recently by the skilled way in which another colleague prepared this audience for some provocative remarks when he suggested that the production and use of evidence is about power, not objectivity. OMG: who knew that policymaking was political and about power?!

So, the insights from this book are useful to a large audience of scientists while, for a smaller audience of policy scientists, they remind us that there is an audience out there for many of the statements that many of us would take for granted. Some evidence advocates use the language of ‘evidence based policymaking’ strategically, to get what they want. Others appear to use it because they believe it can exist. Keep this in mind when you read the book.

Three ways to communicate more effectively with policymakers

By Paul Cairney and Richard Kwiatkowski

Use psychological insights to inform communication strategies

Policymakers cannot pay attention to all of the things for which they are responsible, or understand all of the information they use to make decisions. Like all people, there are limits on what information they can process (Baddeley, 2003; Cowan, 2001, 2010; Miller, 1956; Rock, 2008).

They must use short cuts to gather enough information to make decisions quickly: the ‘rational’, by pursuing clear goals and prioritizing certain kinds of information, and the ‘irrational’, by drawing on emotions, gut feelings, values, beliefs, habits, schemata, scripts, and what is familiar, to make decisions quickly. Unlike most people, they face unusually strong pressures on their cognition and emotion.

Policymakers need to gather information quickly and effectively, often in highly charged political atmospheres, so they develop heuristics to allow them to make what they believe to be good choices. Perhaps their solutions seem to be driven more by their values and emotions than a ‘rational’ analysis of the evidence, often because we hold them to a standard that no human can reach.

If so, and if they have high confidence in their heuristics, they will dismiss criticism from researchers as biased and naïve. Under those circumstances, we suggest that restating the need for ‘rational’ and ‘evidence-based policymaking’ is futile, naively ‘speaking truth to power’ counterproductive, and declaring ‘policy based evidence’ defeatist.

We use psychological insights to recommend a shift in strategy for advocates of the greater use of evidence in policy. The simple recommendation, to adapt to policymakers’ ‘fast thinking’ (Kahneman, 2011) rather than bombard them with evidence in the hope that they will get round to ‘slow thinking’, is already becoming established in evidence-policy studies. However, we provide a more sophisticated understanding of policymaker psychology, to help understand how people think and make decisions as individuals and as part of collective processes. It allows us to (a) combine many relevant psychological principles with policy studies to (b) provide several recommendations for actors seeking to maximise the impact of their evidence.

To ‘show our work’, we first summarise insights from policy studies already drawing on psychology to explain policy process dynamics, and identify key aspects of the psychology literature which show promising areas for future development.

Then, we emphasise the benefit of pragmatic strategies, to develop ways to respond positively to ‘irrational’ policymaking while recognising that the biases we ascribe to policymakers are present in ourselves and our own groups. Instead of bemoaning the irrationality of policymakers, let’s marvel at the heuristics they develop to make quick decisions despite uncertainty. Then, let’s think about how to respond effectively. Instead of identifying only the biases in our competitors, and masking academic examples of group-think, let’s reject our own imagined standards of high-information-led action. This more self-aware and humble approach will help us work more successfully with other actors.

On that basis, we provide three recommendations for actors trying to engage skilfully in the policy process:

1. Tailor framing strategies to policymaker bias. If people are cognitive misers, minimise the cognitive burden of your presentation. If policymakers combine cognitive and emotive processes, combine facts with emotional appeals. If policymakers make quick choices based on their values and simple moral judgements, tell simple stories with a hero and moral. If policymakers reflect a ‘group emotion’, based on their membership of a coalition with firmly-held beliefs, frame new evidence to be consistent with those beliefs.
2. Identify ‘windows of opportunity’ to influence individuals and processes. ‘Timing’ can refer to the right time to influence an individual, depending on their current way of thinking, or to act while political conditions are aligned.
3. Adapt to real-world ‘dysfunctional’ organisations rather than waiting for an orderly process to appear. Form relationships in networks, coalitions, or organisations first, then supply challenging information second. To challenge without establishing trust may be counterproductive.

These tips are designed to produce effective, not manipulative, communicators. They help foster the clearer communication of important policy-relevant evidence, rather than imply that we should bend evidence to manipulate or trick politicians. We argue that it is pragmatic to work on the assumption that people’s beliefs are honestly held, and policymakers believe that their role is to serve a cause greater than themselves. To persuade them to change course requires showing simple respect and seeking ways to secure their trust, rather than simply ‘speaking truth to power’. Effective engagement requires skilful communication and good judgement as much as good evidence.

---

This is the introduction to our revised and resubmitted paper to the special issue of Palgrave Communications The politics of evidence-based policymaking: how can we maximise the use of evidence in policy? Please get in touch if you are interested in submitting a paper to the series.

Full paper: Cairney Kwiatkowski Palgrave Comms resubmission CLEAN 14.7.17

The impact of multi-level policymaking on the UK energy system

In September, we will begin a one-year UKERC project examining current and future energy policy and multi-level policymaking and its impact on ‘energy systems’. This is no mean feat, since the meaning of policy, policymaking (or the ‘policy process’), and ‘system’ are not clear, and our description of the components parts of an energy system and a complex policymaking system may differ markedly. So, one initial aim is to provide some way to turn a complex field of study into something simple enough to understand and engage with.

We do so by focusing on ‘multi-level policymaking’ – which can encompass concepts such as multi-level governance and intergovernmental relations – to reflect the fact that the responsibility for policies relevant to energy are often Europeanised, devolved, and shared between several levels of government. Brexit will produce a major effect on energy and non-energy policies, and prompt the UK and devolved governments to produce relationships, but we all need more clarity on the dynamics of current arrangements before we can talk sensibly about the future. To that end, we pursue three main work packages:

1. What is the ‘energy policymaking system’ and how does it affect the energy system?

Chaudry et al (2009: iv) define the UK energy system as ‘the set of technologies, physical infrastructure, institutions, policies and practices located in and associated with the UK which enable energy services to be delivered to UK consumers’. UK policymaking can have a profound impact, and constitutional changes might produce policy change, but their impacts require careful attention. So, we ‘map’ the policy process and the effect of policy change on energy supply and demand. Mapping sounds fairly straightforward but contains a series of tasks whose level of difficulty rises each time:

1. Identify which level or type of government is responsible – ‘on paper’ and in practice – for the use of each relevant policy instrument.
2. Identify how these actors interact to produce what we call ‘policy’, which can range from statements of intent to final outcomes.
3. Identify an energy policy process containing many actors at many levels, the rules they follow, the networks they form, the ‘ideas’ that dominate discussion, and the conditions and events (often outside policymaker control) which constrain and facilitate action. By this stage, we need to draw on particular policy theories to identify key venues, such as subsystems, and specific collections of actors, such as advocacy coalitions, to produce a useful model of activity.

2. Who is responsible for action to reduce energy demand?

Energy demand is more challenging to policymakers than energy supply because the demand side involves millions of actors who, in the context of household energy use, also constitute the electorate. There are political tensions in making policies to reduce energy demand and carbon where this involves cost and inconvenience for private actors who do not necessarily value the societal returns achieved, and the political dynamics often differ from policy to regulate industrial demand. There are tensions around public perceptions of whose responsibility it is to take action – including local, devolved, national, or international government agencies – and governments look like they are trying to shift responsibility to each other or individuals and firms.

So, there is no end of ways in which energy demand could be regulated or influenced – including energy labelling and product/building standards, emissions reduction measures, promotion of efficient generation, and buildings performance measures – but it is an area of policy which is notoriously diffuse and lacking in co-ordination. So, for the large part, we consider if Brexit provides a ‘window of opportunity’ to change policy and policymaking by, for example, clarifying responsibilities and simplifying relationships.

3: Does Brexit affect UK and devolved policy on energy supply?

It is difficult for single governments to coordinate an overall energy mix to secure supply from many sources, and multi-level policymaking adds a further dimension to planning and cooperation. Yet, the effect of constitutional changes is highly uneven. For example, devolution has allowed Scotland to go its own way on renewable energy, nuclear power and fracking, but Brexit’s impact ranges from high to low. It presents new and sometimes salient challenges for cooperation to supply renewable energy but, while fracking and nuclear are often the most politically salient issues, Brexit may have relatively little impact on policymaking within the UK.

We explore the possibility that renewables policy may be most impacted by Brexit, while nuclear and fracking are examples in which Brexit may have a minimal direct impact on policy. Overall, the big debates are about the future energy mix, and how local, devolved, and UK governments balance the local environmental impacts of, and likely political opposition to, energy development against the economic and energy supply benefits.

For more details, see our 4-page summary

Powerpoint for 13.7.17

Cairney et al UKERC presentation 23.10.17

Policy concepts in 1000 or 500 words

Imagine that your audience is a group of scientists who have read everything and are only interested in something new. You need a new theory, method, study, or set of results to get their attention.

Let’s say that audience is a few hundred people, or half a dozen in each subfield. It would be nice to impress them, perhaps with some lovely jargon and in-jokes, but almost no-one else will know or care what you are talking about.

Imagine that your audience is a group of budding scientists, researchers, students, practitioners, or knowledge-aware citizens who are new to the field and only interested in what they can pick up and use (without devoting their life to each subfield). Novelty is no longer your friend. Instead, your best friends are communication, clarity, synthesis, and a constant reminder not to take your knowledge and frame of reference for granted.

Let’s say that audience is a few gazillion people. If you want to impress them, imagine that you are giving them one of the first – if not the first – ways of understanding your topic. Reduce the jargon. Explain your problem and why people should care about how you try to solve it. Clear and descriptive titles. No more in-jokes (just stick with the equivalent of ‘I went to the doctor because a strawberry was growing in my arse, and she gave me some cream for it’).

At least, that’s what I’ve been telling myself lately. As things stand, my most-read post of all time is destined to be on the policy cycle, and most people read it because it’s the first entry on a google search. Most readers of that post may never read anything else I’ve written (over a million words, if I cheat a bit with the calculation). They won’t care that there are a dozen better ways to understand the policy process. I have one shot to make it interesting, to encourage people to read more. The same goes for the half-dozen other concepts (including multiple streams, punctuated equilibrium theory, the Advocacy Coalition Framework) which I explain to students first because I now do well in google search (go on, give it a try!).

I also say this because I didn’t anticipate this outcome when I wrote those posts. Now, a few years on, I’m worried that they are not very good. They were summaries of chapters from Understanding Public Policy, rather than first principles discussions, and lots of people have told me that UPP is a little bit complicated for the casual reader. So, when revising it, I hope to make it better, and by better I mean to appeal to a wider audience without dumping the insights. I have begun by trying to write 500-words posts as, I hope, improvements on the 1000-word versions. However, I am also open to advice on the originals. Which ones work, and which ones don’t? Where are the gaps in exposition? Where are the gaps in content?

This post is 500 words.

https://paulcairney.wordpress.com/1000-words/

https://paulcairney.wordpress.com/500-words/