Evidence-based policymaking and the ‘new policy sciences’

[I wasn’t happy with the first version, so this is version 2, to be enjoyed with the ppt & MP3 ]

In the ‘new policy sciences’, Chris Weible and I advocate:

• a return to Lasswell’s vision of combining policy analysis (to recommend policy change) and policy theory (to explain policy change), but
• focusing on a far larger collection of actors (beyond a small group at the centre),
• recognising new developments in studies of the psychology of policymaker choice, and
• building into policy analysis the recognition that any policy solution is introduced in a complex policymaking environment over which no-one has control.

However, there is a lot of policy theory out there, and we can’t put policy theory together like Lego to produce consistent insights to inform policy analysis.

Rather, each concept in my image of the policy process represents its own literature: see these short explainers on the psychology of policymaking, actors spread across multi-level governance, institutions, networks, ideas, and socioeconomic factors/ events.

What the explainers don’t really project is the sense of debate within the literature about how best to conceptualise each concept. You can pick up their meaning in a few minutes but would need a few years to appreciate the detail and often-fundamental debate.

Ideally, we would put all of the concepts together to help explain policymaker choice within a complex policymaking environment (how else could I put up the image and present is as one source of accumulated wisdom from policy studies?). Peter John describes such accounts as ‘synthetic’. I have also co-authored work with Tanya Heikkila – in 2014 and 2017 to compare the different ways in which ‘synthetic’ theories conceptualise the policy process.

However, note the difficulty of putting together a large collection of separate and diverse literatures into one simple model (e.g. while doing a PhD).

On that basis, I’d encourage you to think of these attempts to synthesise as stories. I tell these stories a lot, but someone else could describe theory very differently (perhaps by relying on fewer male authors or US-derived theories in which there is a very specific reference points and positivism is represented well).

The example of EBPM

I have given a series of talks to explain why we should think of ‘evidence-based policymaking’ as a myth or political slogan, not an ideal scenario or something to expect from policymaking in the real world. They usually involve encouraging framing and storytelling rather than expecting evidence to speak for itself, and rejecting the value of simple models like the policy cycle. I then put up an image of my own and encourage people to think about the implications of each concept:

I describe the advice as simple-sounding and feasible at first glance, but actually a series of Herculean* tasks:

• There are many policymakers and influencers spread across government, so find out where the action is, or the key venues in which people are making authoritative decisions.
• Each venue has its own ‘institutions’ – the formal and written, or informal and unwritten rules of policymaking – so learn the rules of each venue in which you engage.
• Each venue is guided by a fundamental set of ideas – as paradigms, core beliefs, monopolies of understanding – so learn that language.
• Each venue has its own networks – the relationships between policy makers and influencers – so build trust and form alliances within networks.
• Policymaking attention is often driven by changes in socioeconomic factors, or routine/ non-routine events, so be prepared to exploit the ‘windows of opportunity’ to present your solution during heightened attention to a policy problem.

Further, policy theories/ studies help us understand the context in which people make such choices. For example, consider the story that Kathryn Oliver and I tell about the role of evidence in policymaking environments:

If there are so many potential authoritative venues, devote considerable energy to finding where the ‘action’ is (and someone specific to talk to). Even if you find the right venue, you will not know the unwritten rules unless you study them intensely. Some networks are close-knit and difficult to access because bureaucracies have operating procedures that favour some sources of evidence. Research advocates can be privileged insiders in some venues and excluded completely in others. If your evidence challenges an existing paradigm, you need a persuasion strategy good enough to prompt a shift of attention to a policy problem and a willingness to understand that problem in a new way. You can try to find the right time to use evidence to exploit a crisis leading to major policy change, but the opportunities are few and chances of success low.  In that context, policy studies recommend investing your time over the long term – to build up alliances, trust in the messenger, knowledge of the system, and to seek ‘windows of opportunity’ for policy change – but offer no assurances that any of this investment will ever pay off

As described, this focus on the new policy sciences and synthesising insights helps explain why ‘the politics of evidence-based policymaking’ is equally important to civil servants (my occasional audience) as researchers (my usual audience).

To engage in skilled policy analysis, and give good advice, is to recognise the ways in which policymakers combine cognition/emotion to engage with evidence, and must navigate a complex policymaking environment when designing or selecting technically and politically feasible solutions. To give good advice is to recognise what you want policymakers to do, but also that they are not in control of the consequences.

From one story to many?

However, I tell these stories without my audience having the time to look further into each theory and its individual insights. If they do have a little more time, I go into the possible contribution of individual insights to debate.

For example, they adapt insights from psychology in different ways …

• PET shows the overall effect of policymaker psychology on policy change: they combine cognition and emotion to pay disproportionate attention to a small number of issues (contributing to major change) and ignore the rest (contributing to ‘hyperincremental’ change).
• The IAD focuses partly on the rules and practices that actors develop to build up trust in each other.
• The ACF describes actors going into politics to turn their beliefs into policy, forming coalitions with people who share their beliefs, then often romanticising their own cause and demonising their opponents.
• The NPF describes the relative impact of stories on audiences who use cognitive shortcuts to (for example) identify with a hero and draw a simple moral.
• SCPD describes policymakers drawing on gut feeling to identify good and bad target populations.
• Policy learning involves using cognition and emotion to acquire new knowledge and skills.

… even though the pace of change in psychological research often seems faster than the ways in which policy studies can incorporate new and reliable insights.

They also present different conceptions of the policymaking environment in which actors make choices. See this post for more on this discussion in relation to EBPM.

My not-brilliant conclusion is that:

1. Policy theory/ policy studies has a lot to offer other disciplines and professions, particularly in field like EBPM in which we need to account for politics and, more importantly, policymaking systems, but
2. Beware any policy theory story that presents the source literature as coherent and consistent.
3. Rather, any story of the field involves a series of choices about what counts as a good theory and good insight.
4. In other words, the exhortation to think more about what counts as ‘good evidence’ applies just as much to political science as any other.

Postscript: well, that is the last of the posts for my ANZOG talks. If I’ve done this properly, there should now be a loop of talks. It should be possible to go back to the first one and see it as a sequel to this one!

Or, for more on theory-informed policy analysis – in other words, where the ‘new policy sciences’ article is taking us – here is how I describe it to students doing a policy analysis paper (often for the first time).

Or, have a look at the earlier discussion of images of the policy process. You may have noticed that there is a different image in this post (knocked up in my shed at the weekend). It’s because I am experimenting with shapes. Does the image with circles look more relaxing? Does the hexagonal structure look complicated even though it is designed to simplify? Does it matter? I think so. People engage emotionally with images. They share them. They remember them. So, I need an image more memorable than the policy cycle.

Paul Cairney Brisbane EBPM New Policy Sciences 25.10.18

*I welcome suggestions on another word to describe almost-impossibly-hard

Evidence-based policymaking and the ‘new policy sciences’

I have given a series of talks to explain why we should think of ‘evidence-based policymaking’ as a myth or political slogan, not an ideal scenario or something to expect from policymaking in the real world. They usually involve encouraging framing and storytelling rather than expecting evidence to speak for itself, and rejecting the value of simple models like the policy cycle. I then put up an image of my own and encourage people to think about the implications of each concept:

I describe the advice as simple-sounding and feasible at first glance, but actually a series of Herculean* tasks:

• There are many policymakers and influencers spread across government, so find out where the action is, or the key venues in which people are making authoritative decisions.
• Each venue has its own ‘institutions’ – the formal and written, or informal and unwritten rules of policymaking – so learn the rules of each venue in which you engage.
• Each venue is guided by a fundamental set of ideas – as paradigms, core beliefs, monopolies of understanding – so learn that language.
• Each venue has its own networks – the relationships between policy makers and influencers – so build trust and form alliances within networks.
• Policymaking attention is often driven by changes in socioeconomic factors, or routine/ non-routine events, so be prepared to exploit the ‘windows of opportunity’ to present your solution during heightened attention to a policy problem.

In most cases, we don’t have time to discuss a more fundamental issue (at least for researchers using policy theory and political science concepts):

From where did these concepts come, and how well do we know them?

To cut a long story short, each concept represents its own literature: see these short explainers on the psychology of policymaking, actors spread across multi-level governance, institutions, networks, ideas, and socioeconomic factors/ events. What the explainers don’t really project is the sense of debate within the literature about how best to conceptualise each concept. You can pick up their meaning in a few minutes but would need a few years to appreciate the detail and often-fundamental debate.

Ideally, we would put all of the concepts together to help explain policymaker choice within a complex policymaking environment (how else could I put up the image and present is as one source of accumulated wisdom from policy studies?). Peter John describes such accounts as ‘synthetic’. I have also co-authored work with Tanya Heikkila – in 2014 and 2017 to compare the different ways in which ‘synthetic’ theories conceptualise the policy process. However, note the difficulty of putting together a large collection of separate and diverse literatures into one simple model (e.g. while doing a PhD).

The new policy sciences

More recently, in the ‘new policy sciences’, Chris Weible and I present a more provocative story of these efforts, in which we advocate:

• a return to Lasswell’s vision of combining policy analysis (to recommend policy change) and policy theory (to explain policy change), but
• focusing on a far larger collection of actors (beyond a small group at the centre),
• recognising new developments in studies of the psychology of policymaker choice, and
• building into policy analysis the recognition that any policy solution is introduced in a complex policymaking environment over which no-one has control.

This focus on psychology is not new …

• PET shows the overall effect of policymaker psychology on policy change: they combine cognition and emotion to pay disproportionate attention to a small number of issues (contributing to major change) and ignore the rest (contributing to ‘hyperincremental’ change).
• The IAD focuses partly on the rules and practices that actors develop to build up trust in each other.
• The ACF describes actors going into politics to turn their beliefs into policy, forming coalitions with people who share their beliefs, then often romanticising their own cause and demonising their opponents.
• The NPF describes the relative impact of stories on audiences who use cognitive shortcuts to (for example) identify with a hero and draw a simple moral.
• SCPD describes policymakers drawing on gut feeling to identify good and bad target populations.
• Policy learning involves using cognition and emotion to acquire new knowledge and skills.

… but the pace of change in psychological research often seems faster than the ways in which policy studies can incorporate new and reliable insights.

Perhaps more importantly, policy studies help us understand the context in which people make such choices. For example, consider the story that Kathryn Oliver and I tell about the role of evidence in policymaking environments:

If there are so many potential authoritative venues, devote considerable energy to finding where the ‘action’ is (and someone specific to talk to). Even if you find the right venue, you will not know the unwritten rules unless you study them intensely. Some networks are close-knit and difficult to access because bureaucracies have operating procedures that favour some sources of evidence. Research advocates can be privileged insiders in some venues and excluded completely in others. If your evidence challenges an existing paradigm, you need a persuasion strategy good enough to prompt a shift of attention to a policy problem and a willingness to understand that problem in a new way. You can try to find the right time to use evidence to exploit a crisis leading to major policy change, but the opportunities are few and chances of success low.  In that context, policy studies recommend investing your time over the long term – to build up alliances, trust in the messenger, knowledge of the system, and to seek ‘windows of opportunity’ for policy change – but offer no assurances that any of this investment will ever pay off

Then, have a look at this discussion of ‘synthetic’ policy theories, designed to prompt people to consider how far they would go to get their evidence into policy.

Theory-driven policy analysis

As described, this focus on the new policy sciences helps explain why ‘the politics of evidence-based policymaking’ is equally important to civil servants (my occasional audience) as researchers (my usual audience).

To engage in skilled policy analysis, and give good advice, is to recognise the ways in which policymakers combine cognition/emotion to engage with evidence, and must navigate a complex policymaking environment when designing or selecting technically and politically feasible solutions. To give good advice is to recognise what you want policymakers to do, but also that they are not in control of the consequences.

Epilogue

Well, that is the last of the posts for my ANZOG talks. If I’ve done this properly, there should now be a loop of talks. It should be possible to go back to the first one in Auckland and see it as a sequel to this one in Brisbane!

Or, for more on theory-informed policy analysis – in other words, where the ‘new policy sciences’ article is taking us – here is how I describe it to students doing a policy analysis paper (often for the first time).

Or, have a look at the earlier discussion of images of the policy process. You may have noticed that there is a different image in this post (knocked up in my shed at the weekend). It’s because I am experimenting with shapes. Does the image with circles look more relaxing? Does the hexagonal structure look complicated even though it is designed to simplify? Does it matter? I think so. People engage emotionally with images. They share them. They remember them. So, I need an image more memorable than the policy cycle.

 

Paul Cairney Brisbane EBPM New Policy Sciences 25.10.18

 

 

*I welcome suggestions on another word to describe almost-impossibly-hard

Theory and Practice: How to Communicate Policy Research beyond the Academy

Notes (and audio) for my first talk at the University of Queensland, Wednesday 24th October, 12.30pm, Graduate Centre, room 402.

Here is the powerpoint that I tend to use to inform discussions with civil servants (CS). I first used it for discussion with CS in the Scottish and UK governments, followed by remarkably similar discussions in parts of New Zealand and Australian government. Partly, it provides a way into common explanations for gaps between the supply of, and demand for, research evidence. However, it also provides a wider context within which to compare abstract and concrete reasons for those gaps, which inform a discussion of possible responses at individual, organisational, and systemic levels. Some of the gap is caused by a lack of effective communication, but we should also discuss the wider context in which such communication takes place.

I begin by telling civil servants about the message I give to academics about why policymakers might ignore their evidence:

1. There are many claims to policy relevant knowledge.
2. Policymakers have to ignore most evidence.
3. There is no simple policy cycle in which we all know at what stage to provide what evidence.

In such talks, I go into different images of policymaking, comparing the simple policy cycle with images of ‘messy’ policymaking, then introducing my own image which describes the need to understand the psychology of choice within a complex policymaking environment.

Under those circumstances, key responses include:

• framing evidence in terms of the ways in which your audience understands policy problems
• engaging in networks to identify and exploit the right time to act, and
• venue shopping to find sympathetic audiences in different parts of political systems.

However, note the context of those discussions. I tend to be speaking with scientific researcher audiences to challenge some preconceptions about: what counts as good evidence, how much evidence we can reasonably expect policymakers to process, and how easy it is to work out where and when to present evidence. It’s generally a provocative talk, to identify the massive scale of the evidence-to-policy task, not a simple ‘how to do it’ guide.

In that context, I suggest to civil servants that many academics might be interested in more CS engagement, but might be put off by the overwhelming scale of their task, and – even if they remained undeterred – would face some practical obstacles:

1. They may not know where to start: who should they contact to start making connections with policymakers?
2. The incentives and rewards for engagement may not be clear. The UK’s ‘impact’ agenda has changed things, but not to the extent that any engagement is good engagement. Researchers need to tell a convincing story that they made an impact on policy/ policymakers with their published research, so there is a notional tipping point of engagement in which it reaches a scale that makes it worth doing.
3. The costs are clearer. For example, any time spent doing engagement is time away from writing grant proposals and journal articles (in other words, the things that still make careers).
4. The rewards and costs are not spread evenly. Put most simply, white male professors may have the most opportunities and face the fewest penalties for engagement in policymaking and social media. Or, the opportunities and rewards may vary markedly by discipline. In some, engagement is routine. In others, it is time away from core work.

In that context, I suggest that CS should:

• provide clarity on what they expect from academics, and when they need information
• describe what they can offer in return (which might be as simple as a written and signed acknowledgement of impact, or formal inclusion on an advisory committee).
• show some flexibility: you may have a tight deadline, but can you reasonably expect an academic to drop what they are doing at short notice?
• Engage routinely with academics, to help form networks and identify the right people you need at the right time

These introductory discussions provide a way into common descriptions of the gap between academic and policymaker:

• Technical languages/ jargon to describe their work
• Timescales to supply and demand information
• Professional incentives (such as to value scientific novelty in academia but evidential synthesis in government
• Comfort with uncertainty (often, scientists project relatively high uncertainty and don’t want to get ahead of the evidence; often policymakers need to project certainty and decisiveness)
• Assessments of the relative value of scientific evidence compared to other forms of policy-relevant information
• Assessments of the role of values and beliefs (some scientists want to draw the line between providing evidence and advice; some policymakers want them to go much further)

To discuss possible responses, I use the European Commission Joint Research Centre’s ‘knowledge management for policy’ project in which they identify the 8 core skills of organisations bringing together the suppliers and demanders of policy-relevant knowledge

However, I also use the following table to highlight some caution about the things we can achieve with general skills development and organisational reforms. Sometimes, the incentives to engage will remain low. Further, engagement is no guarantee of agreement.

In a nutshell, the table provides three very different models of ‘evidence-informed policymaking’ when we combine political choices about what counts as good evidence, and what counts as good policymaking (discussed at length in teaching evidence-based policy to fly). Discussion and clearer communication may help clarify our views on what makes a good model, but I doubt it will produce any agreement on what to do.

In the latter part of the talk, I go beyond that powerpoint into two broad examples of practical responses:

1. Storytelling

The Narrative Policy Framework describes the ‘science of stories’: we can identify stories with a 4-part structure (setting, characters, plot, moral) and measure their relative impact.  Jones/ Crow and Crow/Jones provide an accessible way into these studies. Also look at Davidson’s article on the ‘grey literature’ as a rich source of stories on stories.

On one hand, I think that storytelling is a great possibility for researchers: it helps them produce a core – and perhaps emotionally engaging – message that they can share with a wider audience. Indeed, I’d see it as an extension of the process that academics are used to: identifying an audience and framing an argument according to the ways in which that audience understands the world.

On the other hand, it is important to not get carried away by the possibilities:

• My reading of the NPF empirical work is that the most impactful stories are reinforcing the beliefs of the audience – to mobilise them to act – not changing their minds.
• Also look at the work of the Frameworks Institute which experiments with individual versus thematic stories because people react to them in very different ways. Some might empathise with an individual story; some might judge harshly. For example, they discusse stories about low income families and healthy eating, in which they use the theme of a maze to help people understand the lack of good choices available to people in areas with limited access to healthy food.

See: Storytelling for Policy Change: promise and problems

2. Evidence for advocacy

The article I co-authored with Oxfam staff helps identify the lengths to which we might think we have to go to maximise the impact of research evidence. Their strategies include:

1. Identifying the policy change they would like to see.
2. Identifying the powerful actors they need to influence.
3. A mixture of tactics: insider, outsider, and supporting others by, for example, boosting local civil society organisations.
4. A mix of ‘evidence types’ for each audience

5. Wider public campaigns to address the political environment in which policymakers consider choices
6. Engaging stakeholders in the research process (often called the ‘co-production of knowledge’)
7. Framing: personal stories, ‘killer facts’, visuals, credible messenger
8. Exploiting ‘windows of opportunity’
9. Monitoring, learning, trial and error

In other words, a source of success stories may provide a model for engagement or the sense that we need to work with others to engage effectively. Clear communication is one thing. Clear impact at a significant scale is another.

See: Using evidence to influence policy: Oxfam’s experience

 

 

 

 

 

 

 

Evidence-based policymaking: political strategies for scientists living in the real world

Note: I wrote the following discussion (last year) to be a Nature Comment but it was not to be!

Nature articles on evidence-based policymaking often present what scientists would like to see: rules to minimise bias caused by the cognitive limits of policymakers, and a simple policy process in which we know how and when to present the best evidence.[1]  What if neither requirement is ever met? Scientists will despair of policymaking while their competitors engage pragmatically and more effectively.[2]

Alternatively, if scientists learned from successful interest groups, or by using insights from policy studies, they could develop three ‘take home messages’: understand and engage with policymaking in the real world; learn how and when evidence ‘wins the day’; and, decide how far you should go to maximise the use of scientific evidence. Political science helps explain this process[3], and new systematic and thematic reviews add new insights.[4] [5] [6] [7]

Understand and engage with policymaking in the real world

Scientists are drawn to the ‘policy cycle’, because it offers a simple – but misleading – model for engagement with policymaking.[3] It identifies a core group of policymakers at the ‘centre’ of government, perhaps giving the impression that scientists should identify the correct ‘stages’ in which to engage (such as ‘agenda setting’ and ‘policy formulation’) to ensure the best use of evidence at the point of authoritative choice. This is certainly the image generated most frequently by health and environmental scientists when they seek insights from policy studies.[8]

Yet, this model does not describe reality. Many policymakers, in many levels and types of government, adopt and implement many measures at different times. For simplicity, we call the result ‘policy’ but almost no modern policy theory retains the linear policy cycle concept. In fact, it is more common to describe counterintuitive processes in which, for example, by the time policymaker attention rises to a policy problem at the ‘agenda setting’ stage, it is too late to formulate a solution. Instead, ‘policy entrepreneurs’ develop technically and politically feasible solutions then wait for attention to rise and for policymakers to have the motive and opportunity to act.[9]

Experienced government science advisors recognise this inability of the policy cycle image to describe real world policymaking. For example, Sir Peter Gluckman presents an amended version of this model, in which there are many interacting cycles in a kaleidoscope of activity, defying attempts to produce simple flow charts or decision trees. He describes the ‘art and craft’ of policy engagement, using simple heuristics to deal with a complex and ‘messy’ policy system.[10]

Policy studies help us identify two such heuristics or simple strategies.

First, respond to policymaker psychology by adapting to the short cuts they use to gather enough information quickly: ‘rational’, via trusted sources of oral and written evidence, and ‘irrational’, via their beliefs, emotions, and habits. Policy theories describe many interest group or ‘advocacy coalition’ strategies, including a tendency to combine evidence with emotional appeals, romanticise their own cause and demonise their opponents, or tell simple emotional stories with a hero and moral to exploit the biases of their audience.[11]

Second, adapt to complex ‘policy environments’ including: many policymakers at many levels and types of government, each with their own rules of evidence gathering, network formation, and ways of understanding policy problems and relevant socioeconomic conditions.[2] For example, advocates of international treaties often find that the evidence-based arguments their international audience takes for granted become hotly contested at national or subnational levels (even if the national government is a signatory), while the same interest groups presenting the same evidence of a problem can be key insiders in one government department but ignored in another.[3]

Learn the conditions under which evidence ‘wins the day’ in policymaking

Consequently, the availability and supply of scientific evidence, on the nature of problems and effectiveness of solutions, is a necessary but insufficient condition for evidence-informed policy. Three others must be met: actors use scientific evidence to persuade policymakers to pay attention to, and shift their understanding of, policy problems; the policy environment becomes broadly conducive to policy change; and, actors exploit attention to a problem, the availability of a feasible solution, and the motivation of policymakers, during a ‘window of opportunity’ to adopt specific policy instruments.10

Tobacco control represents a ‘best case’ example (box 1) from which we can draw key lessons for ecological and environmental policies, giving us a sense of perspective by highlighting the long term potential for major evidence-informed policy change. However, unlike their colleagues in public health, environmental scientists have not developed a clear sense of how to produce policy instruments that are technically and politically feasible, so the delivery of comparable policy change is not inevitable.[12]

Box 1: Tobacco policy as a best case and cautionary tale of evidence-based policymaking

Tobacco policy is a key example – and useful comparator for ecological and environmental policies – since it represents a best case scenario and cautionary tale.[13] On the one hand, the scientific evidence on the links between smoking, mortality, and preventable death forms the basis for modern tobacco control policy. Leading countries – and the World Health Organisation, which oversees the Framework Convention on Tobacco Control (FCTC) – frame tobacco use as a public health ‘epidemic’ and allow their health departments to take the policy lead. Health departments foster networks with public health and medical groups at the expense of the tobacco industry, and emphasise the socioeconomic conditions – reductions in (a) smoking prevalence, (b) opposition to tobacco control, and (c) economic benefits to tobacco – most supportive of tobacco control. This framing, and conducive policymaking environment, helps give policymakers the motive and opportunity to choose policy instruments, such as bans on smoking in public places, which would otherwise seem politically infeasible.

On the other hand, even in a small handful of leading countries such as the UK, it took twenty to thirty years to go from the supply of the evidence to a proportionate government response: from the early evidence on smoking in the 1950s prompting major changes from the 1980s, to the evidence on passive smoking in the 1980s prompting public bans from the 2000s onwards. In most countries, the production of a ‘comprehensive’ set of policy measures is not yet complete, even though most signed the FCTC.

Decide how far you’ll go to maximise the use of scientific evidence in policymaking

These insights help challenge the naïve position that, if policymaking can change to become less dysfunctional[1], scientists can be ‘honest brokers’[14] and expect policymakers to use their evidence quickly, routinely, and sincerely. Even in the best case scenario, evidence-informed change takes hard work, persistence, and decades to achieve.

Since policymaking will always appear ‘irrational’ and complex’[3], scientists need to think harder about their role, then choose to engage more effectively or accept their lack of influence.

To deal with ‘irrational’ policymakers, they should combine evidence with persuasion, simple stories, and emotional appeals, and frame their evidence to make the implications consistent with policymakers’ beliefs.

To deal with complex environments, they should engage for the long term to work out how to form alliances with influencers who share their beliefs, understand in which ‘venues’ authoritative decisions are made and carried out, the rules of information processing in those venues, and the ‘currency’ used by policymakers when they describe policy problems and feasible solutions.[2] In other words, develop skills that do not come with scientific training, avoid waiting for others to share your scientific mindset or respect for scientific evidence, and plan for the likely eventuality that policymaking will never become ‘evidence based’.

This approach may be taken for granted in policy studies[15], but it raises uncomfortable dilemmas regarding how far scientists should go, to maximise the use of scientific evidence in policy, using persuasion and coalition-building.

These dilemmas are too frequently overshadowed by claims – more comforting to scientists – that politicians are to blame because they do not understand how to generate, analyse, and use the best evidence. Scientists may only become effective in politics if they apply the same critical analysis to themselves.

[1] Sutherland, W.J. & Burgman, M. Nature 526, 317–318 (2015).

[2] Cairney, P. et al. Public Administration Review 76, 3, 399-402 (2016)

[3] Cairney, P. The Politics of Evidence-Based Policy Making (Palgrave Springer, 2016).

[4] Langer, L. et al. The Science of Using Science (EPPI, 2016)

[5] Breckon, J. & Dodson, J. Using Evidence. What Works? (Alliance for Useful Evidence, 2016)

[6] Palgrave Communications series The politics of evidence-based policymaking (ed. Cairney, P.)

[7] Practical lessons from policy theories (eds. Weible, C & Cairney, P.) Policy and Politics April 2018

[8] Oliver, K. et al. Health Research Policy and Systems, 12, 34 (2016)

[9] Kingdon, J. Agendas, Alternatives and Public Policies (Harper Collins, 1984)

[10] Gluckmann, P. Understanding the challenges and opportunities at the science-policy interface

[11] Cairney, P. & Kwiatkowski, R. Palgrave Communications.

[12] Biesbroek et al. Nature Climate Change, 5, 6, 493–494 (2015)

[13] Cairney, P. & Yamazaki, M. Journal of Comparative Policy Analysis

[14] Pielke Jr, R. originated the specific term The honest broker (Cambridge University Press, 2007) but this role is described more loosely by other commentators.

[15] Cairney, P. & Oliver, K. Health Research Policy and Systems 15:35 (2017)

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 Politics of Evidence revisited

This is a guest post by Dr Justin Parkhurst, responding to a review of our books by Dr Joshua Newman, and my reply to that review.

I really like that Joshua Newman has done this synthesis of 3 recent books covering aspects of evidence use in policy. Too many book reviews these days just describe the content, so some critical comments are welcome, as is the comparative perspective.

I’m also honoured that my book was included in the shortlist (it is available here, free as an ebook: bit.ly/2gGSn0n for interested readers) and I’d like to follow on from Paul to add some discussion points to the debate here – with replies to both Joshua and Paul (hoping first names are acceptable).

Have we heard all this before?

Firstly, I agree with Paul that saying ‘we’ve heard this all before’ risks speaking about a small community of active researchers who study these issues, and not the wider community. But I’d also add that what we’ve heard before is a starting point to many of these books, not where they end up.

In terms of where we start: I’m sure many of us who work in this field are somewhat frustrated at meetings when we hear people making statements that are well established in the literature. Some examples include:

• “There can be many types of evidence, not just scientific research…”
• “In the legal field, ‘evidence’ means something different…”
• “We need evidence-based policy, not policy-based evidence…”
• “We need to know ‘what works’ to get evidence into policy…”

Thus, I do think there is still a need to cement the foundations of the field more strongly – in essence, to establish a disciplinary baseline that people weighing in on a subject should be expected to know about before providing additional opinions. One way to help do this is for scholars to continue to lay out the basic starting points in our books – typically in the first chapter or two.

Of course, other specialist fields and disciplines have managed to establish their expertise to a point that individuals with opinions on a subject typically have some awareness that there is a field of study out there which they don’t necessarily know about. This is most obvious in the natural sciences (and perhaps in economics). E.g. most people (current presidents of some large North American countries aside?) are aware that don’t know a lot about engineering, medicine, or quantum physics – so they won’t offer speculative or instinctive opinions about why airplanes stay in the air, how to do bypass surgery, or what was wrong with the ‘Ant-Man’ film. Or when individuals do offer views, they are typically expected to know the basics of the subject.

For the topic of evidence and policy, I often point people to Huw Davies, Isabel Walter, and Sandra Nutley’s book Using Evidence, which is a great introduction to much of this field, as well as Carol Weiss’ insights from the late 70s on the many meanings of research utilisation. I also routinely point people to read The Honest Broker by Roger Pielke Jr. (which I, myself, failed to read before writing my book and, as such, end up repeating many of his points – I’ve apologised to him personally).

So yes, I think there is space for work like ours to continue to establish a baseline, even if some of us know this, because the expertise of the field is not yet widely recognised or established. Yet I think is it not accurate for Joshua to argue we end up repeating what is known, considering our books diverge in key ways after laying out some of the core foundations.

Where do we go from there?

More interesting for this discussion, then, is to reflect on what our various books try to do beyond simply laying out the basics of what we know about evidence use and policy. It is here where I would disagree with Joshua’s point claiming we don’t give a clear picture about the ‘problem’ that ‘evidence-based policy’ (his term – one I reject) is meant to address. Speaking only for my own book, I lay out the problem of bias in evidence use as the key motivation driving both advocates of greater evidence use as well as policy scholars critical of (oversimplified) knowledge translation efforts. But I distinguish between two forms of bias: technical bias – whereby evidence is used in ways that do not adhere to scientific best practice and thus produce sub-optimal social outcomes; and issue bias – whereby pieces of evidence, or mechanisms of evidence use, can obscure the important political choices in decision making, skewing policy choices towards those things that have been measured, or are conducive to measurement. Both of these forms of bias are violations of widely held social values – values of scientific fidelity on the one hand, and of democratic representation on the other. As such, for me, these are the problems that I try to consider in my book, exploring the political and cognitive origins of both, in order to inform thinking on how to address them.

That said, I think Joshua is right in some of the distinctions he makes between our works in how we try to take this field forward, or move beyond current challenges in differing ways. Paul takes the position that researchers need to do something, and one thing they can do is better understand politics and policy making. I think Paul’s writings about policy studies for students is superb (see his book and blog posts about policy concepts). But in terms of applying these insights to evidence use, this is where we most often diverge. I feel that keeping the focus on researchers puts too much emphasis on achieving ‘uptake’ of researcher’s own findings. In my view, I would point to three potential (overlapping) problems with this.

• First – I do not think it is the role or responsibility of researchers to do this, but rather a failure to establish the right system of evidence provision;
• Second – I feel it leaves unstated the important but oft ignored normative question of how ‘should’ evidence be used to inform policy;
• Third – I believe these calls rest on often unstated assumptions about the answer to the second point which we may wish to challenge.

In terms of the first point: I’m more of an institutionalist (as Joshua points out). My view is that the problems around non-use or misuse of evidence can be seen as resulting from a failure to establish appropriate systems that govern the use of evidence in policy processes. As such, the solution would have to lie with institutional development and changes (my final chapter advocates for this) that establish systems which serve to achieve the good governance of evidence.

Paul’s response to Joshua says that researchers are demanding action, so he speaks to them. He wants researchers to develop “useful knowledge of the policy process in which they might want to engage” (as he says above).  Yet while some researchers may wish to engage with policy processes, I think it needs to be clear that doing so is inherently a political act – and can take on a role of issue advocacy by promoting those things you researched or measured over other possible policy considerations (points made well by Roger Pielke Jr. in The Honest Broker). The alternative I point towards is to consider what good systems of evidence use would look like. This is the difference between arguing for more uptake of research, vs. arguing for systems through which all policy relevant evidence can be seen and considered in appropriate ways – regardless of the political savvy, networking, or activism of any given researcher (in my book I have chapters reflecting on what appropriate evidence for policy might be, and what a good process for its use might be, based on particular widely shared values).

In terms of the second and third points – my book might be the most explicit in its discussion of the normative values guiding efforts to improve evidence, and I am more critical than some about the assumption that getting researchers work ‘used’ by policymakers is a de-facto good thing. This is why I disagree with Joshua’s conclusion that my work frames the problem as ‘bridging the gap’. Rather I’d say I frame the problem as asking the question of ‘what does a better system of evidence use look like from a political perspective?’ My ‘good governance of evidence’ discussion presents an explicitly normative framework based the two sets of values mentioned above – those around democratic accountability and around fidelity to scientific good practice – both of which have been raised as important in discussions about evidence use in political processes.

Is the onus on researchers?

Finally, I also would argue against Joshua’s conclusion that my work places the burden of resolving the problems on researchers. Paul argues above that he does this but with good reason. I try not to do this. This is again because my book is not making an argument for more evidence to be ‘used’ per se. (and I don’t expect policy makers to just want to use it either). Rather I focus on identifying principles by which we can judge systems of evidence use, calling for guided incremental changes within national systems.

While I think academics can play an important role in establishing ‘best practice’ ideas, I explicitly argue that the mandate to establish, build, or incrementally change evidence advisory systems lies with the representatives of the people. Indeed, I include ‘stewardship’ as a core principle of my good governance of evidence framework to show that it should be those individuals who are accountable to the public that build these systems in different countries. Thus, the burden lies not with academics, but rather with our representatives – and, indirectly with all of us through the demands we make on them – to improve systems of evidence use.

 

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

 

Evidence based medicine provides a template for evidence based policy, but not in the way you expect

Guest post by Dr Kathryn Oliver and Dr Warren Pearce to celebrate the publication of their new Open Access article ‘Three lessons from evidence-based medicine and policy‘ in Palgrave Communications,

Part of the  Open Access series ‘politics of evidence based policymaking‘ (for which we still welcome submissions).

Hooray! New paper by me and @WarrenPearce on key questions for the EBP field- OA! https://t.co/kN8Ax7BjqN

— Kathryn Oliver (@oliver_kathryn) December 12, 2017

Evidence-based medicine (EBM) is often described as a ‘template’ for evidence-based policymaking (EBPM).

Critics of this idea would be 100% right if EBM lived up to its inaccurate caricature, in which there is an inflexible ‘hierarchy of evidence’ which dismisses too much useful knowledge and closes off the ability of practitioners to use their judgement.

In politics, this would be disastrous because there are many sources of legitimate knowledge and ‘the evidence’ cannot and should not become an alternative to political choice. And, of course, politicians must use their judgement, as – unlike medicine – there is no menu of possible answers to any problem.

Yet, modern forms of EBM – or, at least, sensible approaches to it – do not live up to this caricature. Instead, EBM began as a way to support individual decision-makers, and has evolved to reflect new ways of thinking about three main dilemmas. The answers to these dilemmas can help improve policymaking.

How to be more transparent

First, evidence-informed clinical practice guidelines lead the way in transparency. There’s a clear, transparent process to frame a problem, gather and assess evidence, and, through a deliberative discussion with relevant stakeholders, decide on clinical recommendations. Alongside other tools and processes, this demonstrates transparency which increases trust in the system.

How to balance research and practitioner knowledge

Second, dialogues in EBM help us understand how to balance research and practitioner knowledge. EBM has moved beyond the provision of research evidence, towards recognising and legitimising a negotiation between individual contexts, the expertise of decision-makers, and technical advice on interpreting research findings for different settings.

How to be more explicit about how you balance evidence, power, and values

Third, EBM helps us think about how to share power to co-produce policy and to think about how we combine evidence, values, and our ideas about who commands the most legitimate sources of power and accountability. We know that new structures for dialogue and decision-making can formalise and codify processes, but they do not necessarily lead to inclusion of a diverse set of voices. Power matters in dictating what knowledge is produced, for whom, and what is done with it. EBM has offered as many negative as positive lessons so far, particularly when sources of research expertise have been reluctant to let go enough to really co-produce knowledge or policy, but new studies and frameworks are at least keeping this debate alive.

Overall, our discussion of EBM challenges critics to identify its real-world application, not the old caricature. If so, it can help show us how one of the most active research agendas, on the relationship between high quality evidence and effective action, provides lessons for politics. In the main, the lesson is that our aim is not simply to maximise the use of evidence in policy, but to maximise the credibility of evidence and legitimacy of evidence advocates when so many other people have a legitimate claim to knowledge and authoritative action.

3 lessons from evidence-based medicine & policy:
1. be more transparent
2. balance evidence with other interests
3. understand power

New by @oliver_kathryn & me in @PalCommsOA https://t.co/z7L7qO3FFF #EBP #EBM pic.twitter.com/wDUrZLQlVh

— Warren Pearce (@WarrenPearce) December 12, 2017

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

#EU4Facts: 3 take-home points from the JRC annual conference

See EU4FACTS: Evidence for policy in a post-fact world

Evidence-based policy making in an post fact world. Follow the #EU4facts debate today https://t.co/LaszStnsgA #posttruth #fakenews pic.twitter.com/uKecgbh39r

— DigitalSingleMarket (@DSMeu) September 26, 2017

The JRC’s annual conference has become a key forum in which to discuss the use of evidence in policy. At this scale, in which many hundreds of people attend plenary discussions, it feels like an annual mass rally for science; a ‘call to arms’ to protect the role of science in the production of evidence, and the protection of evidence in policy deliberation. There is not much discussion of storytelling, but we tell each other a fairly similar story about our fears for the future unless we act now.

For me, the failure scenario is not an option.
Because every time we mistrust #science, it undermines the progress of humanity.#EU4Facts

— Carlos Moedas (@Moedas) September 26, 2017

Last year, the main story was of fear for the future of heroic scientists: the rise of Trump and the Brexit vote prompted many discussions of post-truth politics and reduced trust in experts. An immediate response was to describe attempts to come together, and stick together, to support each other’s scientific endeavours during a period of crisis. There was little call for self-analysis and reflection on the contribution of scientists and experts to barriers between evidence and policy.

This year was a bit different. There was the same concern for reduced trust in science, evidence, and/ or expertise, and some references to post-truth politics and populism, but with some new voices describing the positive value of politics, often when discussing the need for citizen engagement, and of the need to understand the relationship between facts, values, and politics.

My address to #EU4FACTS at JRC on role of science advice as a bastion against the post-truth/post-trust polemic; https://t.co/vJWoXAI7EB

— peter gluckman (@PeterGluckman) September 27, 2017

For example, a panel on psychology opened up the possibility that we might consider our own politics and cognitive biases while we identify them in others, and one panellist spoke eloquently about the importance of narrative and storytelling in communicating to audiences such as citizens and policymakers.

Excellent walk the talk example by @KuperSimon when describing policy making lessons from football. #EU4FACTS pic.twitter.com/BlDL2nSJM9

— Mona Wallin (@monawallin) September 26, 2017

A focus on narrative is not new, but it provides a challenging agenda when interacting with a sticky story of scientific objectivity. For the unusually self-reflective, it also reminds us that our annual discussions are not particularly scientific; the usual rules to assess our statements do not apply.

Storytelling & policy: lessons from (1) the grey literature https://t.co/oAgmjvR7FR (2) polsci literature https://t.co/2mpTY3Sbho #eu4facts

— ProfessorPaulCairney (@CairneyPaul) September 26, 2017

As in studies of policymaking, we can say that there is high support for such stories when they remain vague and driven more by emotion than the pursuit of precision. When individual speakers try to make sense of the same story, they do it in different – and possibly contradictory – ways. As in policymaking, the need to deliver something concrete helps focus the mind, and prompts us to make choices between competing priorities and solutions.

I describe these discussions in two ways: tables, in which I try to boil down each speaker’s speech into a sentence or two (you can get their full details in the programme and the speaker bios); and a synthetic discussion of the top 3 concerns, paraphrasing and combining arguments from many speakers:

1. What are facts?

The key distinction began as between politics-values-facts which is impossible to maintain in practice.

#EU4FACTS I hope people reflect on @senseaboutsci Tracey Brown's pt about the problematic fact v value distinction https://t.co/qf1E1LUMkW

— ProfessorPaulCairney (@CairneyPaul) September 26, 2017

Yet, subsequent discussion revealed a more straightforward distinction between facts and opinion, ‘fake news’, and lies. The latter sums up an ever-present fear of the diminishing role of science in an alleged ‘post truth’ era.

2. What exactly is the problem, and what is its cause?

The tables below provide a range of concerns about the problem, from threats to democracy to the need to communicate science more effectively. A theme of growing importance is the need to deal with the cognitive biases and informational shortcuts of people receiving evidence: communicate with reference to values, beliefs, and emotions; build up trust in your evidence via transparency and reliability; and, be prepared to discuss science with citizens and to be accountable for your advice. There was less discussion of the cognitive biases of the suppliers of evidence.

3. What is the role of scientists in relation to this problem?

Not all speakers described scientists as the heroes of this story:

• Some described scientists as the good people acting heroically to change minds with facts.
• Some described their potential to co-produce important knowledge with citizens (although primarily with like-minded citizens who learn the value of scientific evidence?).
• Some described the scientific ego as a key barrier to action.
• Some identified their low confidence to engage, their uncertainty about what to do with their evidence, and/ or their scientist identity which involves defending science as a cause/profession and drawing the line between providing information and advocating for policy. This hope to be an ‘honest broker’ was pervasive in last year’s conference.
• Some (rightly) rejected the idea of separating facts/ values and science/ politics, since evidence is never context free (and gathering evidence without thought to context is amoral).

Often in such discussions it is difficult to know if some scientists are naïve actors or sophisticated political strategists, because their public statements could be identical. For the former, an appeal to objective facts and the need to privilege science in EBPM may be sincere. Scientists are, and should be, separate from/ above politics. For the latter, the same appeal – made again and again – may be designed to energise scientists and maximise the role of science in politics.

Yet, energy is only the starting point, and it remains unclear how exactly scientists should communicate and how to ‘know your audience’: would many scientists know who to speak to, in governments or the Commission, if they had something profoundly important to say?

MEP Rubig: the attitude ‘I have made up my mind, don’t bother me with facts’ undermines quality of policy making #EU4FACTS @EU_ScienceHub

— Maive Rute (@MaiveRute) September 26, 2017

Keynotes and introductory statements from panel chairs

Vladimír Šucha: We need to understand the relationship between politics, values, and facts. Facts are not enough. To make policy effectively, we need to combine facts and values.

Tibor Navracsics: Politics is swayed more by emotions than carefully considered arguments. When making policy, we need to be open and inclusive of all stakeholders (including citizens), communicate facts clearly and at the right time, and be aware of our own biases (such as groupthink).

Sir Peter Gluckman: ‘Post-truth’ politics is not new, but it is pervasive and easier to achieve via new forms of communication. People rely on like-minded peers, religion, and anecdote as forms of evidence underpinning their own truth. When describing the value of science, to inform policy and political debate, note that it is more than facts; it is a mode of thinking about the world, and a system of verification to reduce the effect of personal and group biases on evidence production. Scientific methods help us define problems (e.g. in discussion of cause/ effect) and interpret data. Science advice involves expert interpretation, knowledge brokerage, a discussion of scientific consensus and uncertainty, and standing up for the scientific perspective.

Carlos Moedas: Safeguard trust in science by (1) explaining the process you use to come to your conclusions; (2) provide safe and reliable places for people to seek information (e.g. when they Google); (3) make sure that science is robust and scientific bodies have integrity (such as when dealing with a small number of rogue scientists).

Pascal Lamy: 1. ‘Deep change or slow death’ We need to involve more citizens in the design of publicly financed projects such as major investments in science. Many scientists complain that there is already too much political interference, drowning scientists in extra work. However, we will face a major backlash – akin to the backlash against ‘globalisation’ – if we do not subject key debates on the future of science and technology-driven change (e.g. on AI, vaccines, drone weaponry) to democratic processes involving citizens. 2. The world changes rapidly, and evidence gathering is context-dependent, so we need to monitor regularly the fitness of our scientific measures (of e.g. trade).

Jyrki Katainen: ‘Wicked problems’ have no perfect solution, so we need the courage to choose the best imperfect solution. Technocratic policymaking is not the solution; it does not meet the democratic test. We need the language of science to be understandable to citizens: ‘a new age of reason reconciling the head and heart’.

Former commissioner Kuneva We need evidence to govern better as we cannot afford to fail #EU4Facts #evidence4gov We need better policies

— Stephane Jacobzone (@SJacobzone) September 26, 2017

Panel: Why should we trust science?

Jonathan Kimmelman: Some experts make outrageous and catastrophic claims. We need a toolbox to decide which experts are most reliable, by comparing their predictions with actual outcomes. Prompt them to make precise probability statements and test them. Only those who are willing to be held accountable should be involved in science advice.

Johannes Vogel: We should devote 15% of science funding to public dialogue. Scientific discourse, and a science-literature population, is crucial for democracy. EU Open Society Policy is a good model for stakeholder inclusiveness.

Tracey Brown: Create a more direct link between society and evidence production, to ensure discussions involve more than the ‘usual suspects’. An ‘evidence transparency framework’ helps create a space in which people can discuss facts and values. ‘Be open, speak human’ describes showing people how you make decisions. How can you expect the public to trust you if you don’t trust them enough to tell them the truth?

Francesco Campolongo: Claude Juncker’s starting point is that Commission proposals and activities should be ‘based on sound scientific evidence’. Evidence comes in many forms. For example, economic models provide simplified versions of reality to make decisions. Economic calculations inform profoundly important policy choices, so we need to make the methodology transparent, communicate probability, and be self-critical and open to change.

Frmr comm'r Geoghegan-Quinn stresses importance of "winning hearts & minds" 2combat posttruth. Scientists must communicate better #EU4Facts pic.twitter.com/g2luVqR55h

— Graeme Taylor (@leekandpotato) September 26, 2017

Panel: the politician’s perspective

Janez Potočnik: The shift of the JRC’s remit allowed it to focus on advocating science for policy rather than policy for science. Still, such arguments need to be backed by an economic argument (this policy will create growth and jobs). A narrow focus on facts and data ignores the context in which we gather facts, such as a system which undervalues human capital and the environment.

Máire Geoghegan-Quinn: Policy should be ‘solidly based on evidence’ and we need well-communicated science to change the hearts and minds of people who would otherwise rely on their beliefs. Part of the solution is to get, for example, kids to explain what science means to them.

EC Audiovisual Service – Video https://t.co/YpdDxsCb5D via @EC_AVService#eu4facts@michaelbossetta@simonkuper

— Mary I. William (@MIWilliamauthor) September 26, 2017

Panel: Redesigning policymaking using behavioural and decision science

Steven Sloman: The world is complex. People overestimate their understanding of it, and this illusion is burst when they try to explain its mechanisms. People who know the least feel the strongest about issues, but if you ask them to explain the mechanisms their strength of feeling falls. Why? People confuse their knowledge with that of their community. The knowledge is not in their heads, but communicated across groups. If people around you feel they understand something, you feel like you understand, and people feel protective of the knowledge of their community. Implications? 1. Don’t rely on ‘bubbles’; generate more diverse and better coordinated communities of knowledge. 2. Don’t focus on giving people full information; focus on the information they need at the point of decision.

Stephan Lewandowsky: 97% of scientists agree that human-caused climate change is a problem, but the public thinks it’s roughly 50-50. We have a false-balance problem. One solution is to ‘inoculate’ people against its cause (science denial). We tell people the real figures and facts, warn them of the rhetorical techniques employed by science denialists (e.g. use of false experts on smoking), and mock the false balance argument. This allows you to reframe the problem as an investment in the future, not cost now (and find other ways to present facts in a non-threatening way). In our lab, it usually ‘neutralises’ misinformation, although with the risk that a ‘corrective message’ to challenge beliefs can entrench them.

Françoise Waintrop: It is difficult to experiment when public policy is handed down from on high. Or, experimentation is alien to established ways of thinking. However, our 12 new public innovation labs across France allow us to immerse ourselves in the problem (to define it well) and nudge people to action, working with their cognitive biases.

Simon Kuper: Stories combine facts and values. To change minds: persuade the people who are listening, not the sceptics; find go-betweens to link suppliers and recipients of evidence; speak in stories, not jargon; don’t overpromise the role of scientific evidence; and, never suggest science will side-line human beings (e.g. when technology costs jobs).

2 page recap of 10 hours of debate for those who could not participate in #EU4Facts https://t.co/jqzN3M4FPF

— Vladimir Sucha (@VladimirSucha) September 26, 2017

Panel: The way forward

Jean-Eric Paquet: We describe ‘fact based evidence’ rather than ‘science based’. A key aim is to generate ‘ownership’ of policy by citizens. Politicians are more aware of their cognitive biases than we technocrats are.

Anne Bucher: In the European Commission we used evidence initially to make the EU more accountable to the public, via systematic impact assessment and quality control. It was a key motivation for better regulation. We now focus more on generating inclusive and interactive ways to consult stakeholders.

Ann Mettler: Evidence-based policymaking is at the heart of democracy. How else can you legitimise your actions? How else can you prepare for the future? How else can you make things work better? Yet, a lot of our evidence presentation is so technical; even difficult for specialists to follow. The onus is on us to bring it to life, to make it clearer to the citizen and, in the process, defend scientists (and journalists) during a period in which Western democracies seem to be at risk from anti-democratic forces.

Mariana Kotzeva: Our facts are now considered from an emotional and perception point of view. The process does not just involve our comfortable circle of experts; we are now challenged to explain our numbers. Attention to our numbers can be unpredictable (e.g. on migration). We need to build up trust in our facts, partly to anticipate or respond to the quick spread of poor facts.

Rush Holt: In society we can find the erosion of the feeling that science is relevant to ‘my life’, and few US policymakers ask ‘what does science say about this?’ partly because scientists set themselves above politics. Politicians have had too many bad experiences with scientists who might say ‘let me explain this to you in a way you can understand’. Policy is not about science based evidence; more about asking a question first, then asking what evidence you need. Then you collect evidence in an open way to be verified.

What can EU learn from US experience in trying to reconcile the worlds of #science & #politics? Listen to @RushHolt, @aaas CEO #EU4Facts pic.twitter.com/U7GuFjMLkE

— EU_ScienceHub (@EU_ScienceHub) September 27, 2017

Phew!

That was 10 hours of discussion condensed into one post. If you can handle more discussion from me, see:

Psychology and policymaking: Three ways to communicate more effectively with policymakers

The role of evidence in policy: EBPM and How to be heard  

Practical Lessons from Policy Theories

The generation of many perspectives to help us understand the use of evidence

How to be an ‘entrepreneur’ when presenting evidence

 

 

 

A 5-step strategy to make evidence count

Let’s imagine a heroic researcher, producing the best evidence and fearlessly ‘speaking truth to power’. Then, let’s place this person in four scenarios, each of which combines a discussion of evidence, policy, and politics in different ways.

1. Imagine your hero presents to HM Treasury an evidence-based report concluding that a unitary UK state would be far more efficient than a union state guaranteeing Scottish devolution. The evidence is top quality and the reasoning is sound, but the research question is ridiculous. The result of political deliberation and electoral choice suggests that your hero is asking a research question that does not deserve to be funded in the current political climate. Your hero is a clown.
2. Imagine your hero presents to the Department of Health a report based on the systematic review of multiple randomised control trials. It recommends that you roll out an almost-identical early years or public health intervention across the whole country. We need high ‘fidelity’ to the model to ensure the correct ‘dosage’ and to measure its effect scientifically. The evidence is of the highest quality, but the research question is not quite right. The government has decided to devolve this responsibility to local public bodies and/ or encourage the co-production of public service design by local public bodies, communities, and service users. So, to focus narrowly on fidelity would be to ignore political choices (perhaps backed by different evidence) about how best to govern. If you don’t know the politics involved, you will ask the wrong questions or provide evidence with unclear relevance. Your hero is either a fool, naïve to the dynamics of governance, or a villain willing to ignore governance principles.        
3. Imagine two fundamentally different – but equally heroic – professions with their own ideas about evidence. One favours a hierarchy of evidence in which RCTs and their systematic review is at the top, and service user and practitioner feedback is near the bottom. The other rejects this hierarchy completely, identifying the unique, complex relationship between practitioner and service user which requires high discretion to make choices in situations that will differ each time. Trying to resolve a debate between them with reference to ‘the evidence’ makes no sense. This is about a conflict between two heroes with opposing beliefs and preferences that can only be resolved through compromise or political choice. This is, oh I don’t know, Batman v Superman, saved by Wonder Woman.
4. Imagine you want the evidence on hydraulic fracturing for shale oil and gas. We know that ‘the evidence’ follows the question: how much can we extract? How much revenue will it produce? Is it safe, from an engineering point of view? Is it safe, from a public health point of view? What will be its impact on climate change? What proportion of the public supports it? What proportion of the electorate supports it? Who will win and lose from the decision? It would be naïve to think that there is some kind of neutral way to produce an evidence-based analysis of such issues. The commissioning and integration of evidence has to be political. To pretend otherwise is a political strategy. Your hero may be another person’s villain.

Now, let’s use these scenarios to produce a 5-step way to ‘make evidence count’.

Step 1. Respect the positive role of politics

A narrow focus on making the supply of evidence count, via ‘evidence-based policymaking’, will always be dispiriting because it ignores politics or treats political choice as an inconvenience. If we:

• begin with a focus on why we need political systems to make authoritative choices between conflicting preferences, and take governance principles seriously, we can
• identify the demand for evidence in that context, then be more strategic and pragmatic about making evidence count, and
• be less dispirited about the outcome.

In other words, think about the positive and necessary role of democratic politics before bemoaning post-truth politics and policy-based-evidence-making.

Step 2. Reject simple models of evidence-based policymaking

Policy is not made in a cycle containing a linear series of separate stages and we won’t ‘make evidence count’ by using it to inform our practices.

You might not want to give up the cycle image because it presents a simple account of how you should make policy. It suggests that we elect policymakers then: identify their aims, identify policies to achieve those aims, select a policy measure, ensure that the selection is legitimised by the population or its legislature, identify the necessary resources, implement and then evaluate. Or, policymakers aided by expert policy analysts make and legitimise choices, skilful public servants carry them out, and, policy analysts assess the results using evidence.

One compromise is to keep the cycle then show how messy it is in practice:

Discussing the challenges of evidence based policy including complexity of the landscape @OECD #evidence4gov pic.twitter.com/1yu3UIKKjO

— Rob Davies (@r0bdavies) June 26, 2017

However, there comes a point when there is too much mess, and the image no longer helps you explain (a) to the public what you are doing, or (b) to providers of evidence how they should engage in political systems. By this point, simple messages from more complicated policy theories may be more useful.

Or, we may no longer want a cycle to symbolise a single source of policymaking authority. In a multi-level system, with many ‘centres’ possessing their own sources of legitimate authority, a single and simple policy cycle seems too artificial to be useful.

Step 3. Tell a simple story about your evidence

People are ‘cognitive misers’ seeking ‘rational’ and ‘irrational’ shortcuts to gather information for action, so you won’t get far if you bombard them with too much evidence. Policymakers already have too much evidence and they seek ways to reduce their cognitive load, relying on: (a) trusted sources of concise evidence relevant to their aims, and (b) their own experience, gut instinct, beliefs, and emotions.

The implication of both shortcuts is that we need to tell simple and persuasive stories about the substance and implications of the evidence we present. To say that ‘the evidence does not speak for itself’ may seem trite, but I’ve met too many people who assume naively that it will somehow ‘win the day’. In contrast, civil servants know that the evidence-informed advice they give to ministers needs to relate to the story that government ministers tell to the public.

Step 4.  Tailor your story to many audiences

In a complex or multi-level environment, one story to one audience (such as a minister) is not enough. If there are many key sources of policymaking authority – including public bodies with high autonomy, organisations and practitioners with the discretion to deliver services, and service users involved in designing services – there are many stories being told about what we should be doing and why. We may convince one audience and alienate (or fail to inspire) another with the same story.

Step 5. Clarify and address key dilemmas with political choice, not evidence

Let me give you one example of the dilemmas that must arise when you combine evidence and politics to produce policy: how do you produce a model of ‘evidence based best practice’ which combines evidence and governance principles in a consistent way? Here are 3 ideal-type models which answer the question in very different ways

The table helps us think through the tensions between models, built on very different principles of good evidence and governance.

In practice, you may want to combine different elements, perhaps while arguing that the loss of consistency is lower than the gain from flexibility. Or, the dynamics of political systems limit such choice or prompt ad hoc and inconsistent choices.

I built a lot of this analysis on the experiences of the Scottish Government, which juggles all three models, including a key focus on improvement method in its Early Years Collaborative.

However, Kathryn Oliver and I show that the UK government faces the same basic dilemma and addresses it in similar ways.

The example freshest in my mind is Sure Start. Its rationale was built on RCT evidence and systematic review. However, its roll-out was built more on local flexibility and service design than insistence on fidelity to a model. More recently, the Troubled Families programme initially set the policy agenda and criteria for inclusion, but increasingly invites local public bodies to select the most appropriate interventions, aided by the Early Intervention Foundation which reviews the evidence but does not insist on one-best-way. Emily St Denny and I explore these issues further in our forthcoming book on prevention policy, an exemplar case study of a field in which it is difficult to know how to ‘make evidence count’.

If you prefer a 3-step take home message:

1. I think we use phrases like ‘impact’ and ‘make evidence count’ to reflect a vague and general worry about a decline in respect for evidence and experts. Certainly, when I go to large conferences of scientists, they usually tell a story about ‘post-truth’ politics.
2. Usually, these stories do not acknowledge the difference between two different explanations for an evidence-policy gap: (a) pathological policymaking and corrupt politicians, versus (b) complex policymaking and politicians having to make choices despite uncertainty.
3. To produce evidence with ‘impact’, and know how to ‘make evidence count’, we need to understand the policy process and the demand for evidence within it.

*Background. This is a post for my talk at the Government Economic Service and Government Social Research Service Annual Training Conference (15th September 2017). This year’s theme is ‘Impact and Future-Proofing: Making Evidence Count’. My brief is to discuss evidence use in the Scottish Government, but it faces the same basic question as the UK Government: how do you combine principles of evidence quality and governance principles? In other words, if you were in a position to design an (a) evidence-gathering system and (b) a political system, you’d soon find major points of tension between them. Resolving those tensions involves political choice, not more evidence. Of course, you are not in a position to design both systems, so the more complicated question is: how do you satisfy principles of evidence and governance in a complex policy process, often driven by policymaker psychology, over which you have little control?  Here are 7 different ‘answers’.

Powerpoint Paul Cairney @ GES GSRS 2017

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 (@LisaC_Research) 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

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 role of evidence in UK policymaking after Brexit

Join us for free panel discussion on policmaking post-Brexit today at 15:30 with @CairneyPaul & @jameswilsdon et al https://t.co/D9oWn9QNpR

— Palgrave Comms (@PalCommsOA) June 22, 2017

We are launching a series of papers on evidence and policy in Palgrave Communications. Of course, we used Brexit as a hook, to tap into current attention to instability and major policy change. However, many of the issues we discuss are timeless and about surprising levels of stability and continuity in policy processes, despite periods of upheaval.

In my day, academics would build their careers on being annoying, and sometimes usefully annoying. This would involve developing counterintuitive insights, identifying gaps in analysis, and challenging a ‘common wisdom’ in political studies. Although not exactly common wisdom, the idea of ‘post truth’ politics, a reduction in respect for ‘experts’, and a belief that Brexit is a policymaking game-changer, are great candidates for some annoyingly contrary analysis.

In policy studies, many of us argue that things like elections, changes of government, and even constitutional changes are far less important than commonly portrayed. In media and social media accounts, we find hyperbole about the destabilising and changing impact of the latest events. In policy studies, we often stress stability and continuity.  My favourite old example regards the debates from the 1970s about electoral reform. While some were arguing that first-past-the-post was a disastrous electoral system since it produces swings of government, instability, and incoherent policy change, Richardson and Jordan would point out surprisingly high levels of stability and continuity.

In part, this is because the state is huge, policymakers can only pay attention to a tiny part of it, and therefore most of it is processed as a low level of government, out of the public spotlight.

These insights still have profound relevance today, for two key reasons.

1. The role of experts is more important than you think

This larger process provides far more opportunities for experts than we’d associate with ‘tip of the iceberg’ politics.

Some issues are salient. They command the interest of elected politicians, and those politicians often have firm beliefs that limit the ‘impact’ of any evidence that does not support their beliefs.

However, most issues are not salient. They command minimal interest, they are processed by other policymakers, and those policymakers are looking for information and advice from reliable experts.

Indeed, a lot of policy studies highlight the privileged status of certain experts, at the expense of most members of the public (which is a useful corrective to the story, associated with Brexit, that the public is too emotionally driven, too sceptical of experts, and too much in charge of the future of constitutional change).

So, Brexit will change the role of experts, but expect that change to relate to the venue in which they engage, and the networks of which they are a part, more than the practices of policymakers. Much policymaking is akin to an open door to government for people with useful information and a reputation for being reliable in their dealings with policymakers.

2. Provide less evidence for more impact

If the problem is that policymakers can only pay attention to a tiny proportion of their responsibilities, the solution is not to bombard them with a huge amount of evidence. Instead, assume that they seek ways to ignore almost all information while still managing to make choices. The trick may be to provide just enough information to prompt demand for more, not oversupply evidence on the assumption that you have only one chance for influence.

With Richard Kwiatkoswki, I draw on policy and psychology studies to help us understand how to supply evidence to anyone using ‘rational’ and ‘irrational’ ways to limit their attention, information processing, and thought before making decisions.

Our working assumption is that policymakers need to gather information quickly and effectively, so they develop heuristics to allow them to make what they believe to be good choices. Their solutions often seem to be driven more by their emotions than a ‘rational’ analysis of the evidence, partly 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 our criticism as biased and naïve. Under those circumstances, restating the need for ‘evidence-based policymaking’ is futile, and naively ‘speaking truth to power’ counterproductive.

Instead, try out these strategies:

1. Develop ways to respond positively to ‘irrational’ policymaking

Instead of automatically 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 pragmatically, to pursue the kinds of evidence informed policymaking that is realistic in a complex and constantly changing policymaking environment.

2. Tailor framing strategies to policymaker cognition

The usual advice is to minimise the cognitive burden of your presentation, and use strategies tailored to the ways in which people pay attention to, and remember information.

The less usual advice includes:

• If policymakers are combining cognitive and emotive processes, combine facts with emotional appeals.
• If policymakers are making quick choices based on their values and simple moral judgements, tell simple stories with a hero and a clear moral.
• If policymakers are reflecting a ‘group emotion’, based on their membership of a coalition with firmly-held beliefs, frame new evidence to be consistent with the ‘lens’ through which actors in those coalitions understand the world.

3. Identify the right time to influence individuals and processes

Understand what it means to find the right time to exploit ‘windows of opportunity’.

‘Timing’ can refer to the right time to influence an individual, which involves how open they are to, say, new arguments and evidence.

Or, timing refers to a ‘window of opportunity’ when political conditions are aligned. I discuss the latter in a separate paper on effective ‘policy entrepreneurs’.

4. Adapt to real-world organisations rather than waiting for an orderly process to appear

Politicians may appear confident of policy and with a grasp of facts and details, but are (a) often vulnerable and therefore defensive or closed to challenging information, and/ or (b) inadequate in organisational politics, or unable to change the rules of their organisations.

So, develop pragmatic strategies: form relationships in networks, coalitions, or organisations first, then supply challenging information second. To challenge without establishing trust may be counterproductive.

5. Recognise that the biases we ascribe to policymakers are present in ourselves and our own groups.

Identifying only the biases in our competitors may help mask academic/ scientific examples of group-think, and it may be counterproductive to use euphemistic terms like ‘low information’ to describe actors whose views we do not respect. This is a particular problem for scholars if they assume that most people do not live up to their own imagined standards of high-information-led action (often described as a ‘deficit model’ of engagement).

It may be more effective to recognise that: (a) people’s beliefs are honestly held, and policymakers believe that their role is to serve a cause greater than themselves.; and, (b) a fundamental aspect of evolutionary psychology is that people need to get on with each other, so showing simple respect – or going further, to ‘mirror’ that person’s non-verbal signals – can be useful even if it looks facile.

This leaves open the ethical question of how far we should go to identify our biases, accept the need to work with people whose ways of thinking we do not share, and how far we should go to secure their trust without lying about one’s beliefs.

At the very least, we do not suggest these 5 strategies as a way to manipulate people for personal gain. They are better seen as ways to use psychology to communicate well. They are also likely to be as important to policy engagement regardless of Brexit. Venues may change quickly, but the ways in which people process information and make choices may not.

 

Three habits of successful policy entrepreneurs

This post is one part of a series – called Practical Lessons from Policy Theories and it summarizes this article (PDF).

‘Policy entrepreneurs’ invest their time wisely for future reward, and possess key skills that help them adapt particularly well to their environments. They are the agents for policy change who possess the knowledge, power, tenacity, and luck to be able to exploit key opportunities. They draw on three strategies:

1. Don’t focus on bombarding policymakers with evidence.

Scientists focus on making more evidence to reduce uncertainty, but put people off with too much information. Entrepreneurs tell a good story, grab the audience’s interest, and the audience demands information.

2. By the time people pay attention to a problem it’s too late to produce a solution.

So, you produce your solution then chase problems.

3. When your environment changes, your strategy changes.

For example, in the US federal level, you’re in the sea, and you’re a surfer waiting for the big wave. In the smaller subnational level, on a low attention and low budget issue, you can be Poseidon moving the ‘streams’. In the US federal level, you need to ‘soften’ up solutions over a long time to generate support. In subnational or other countries, you have more opportunity to import and adapt ready-made solutions.

It all adds up to one simple piece of advice – timing and luck matters when making a policy case – but policy entrepreneurs know how to influence timing and help create their own luck.

Full paper: Three habits of successful policy entrepreneurs

(Note: the previous version was friendlier and more focused on entrepreneurs)

For more on ‘multiple streams’ see:

Paul Cairney and Michael Jones (2016) ‘Kingdon’s Multiple Streams Approach: What Is the Empirical Impact of this Universal Theory?’ Policy Studies Journal, 44, 1, 37-58 PDF (Annex to Cairney Jones 2016) (special issue of PSJ)

Paul Cairney and Nikos Zahariadis (2016) ‘Multiple streams analysis: A flexible metaphor presents an opportunity to operationalize agenda setting processes’ in Zahariadis, N. (eds) Handbook of Public Policy Agenda-Setting (Cheltenham: Edward Elgar) PDF see also

I use a space launch metaphor in the paper. If you prefer different images, have a look at 5 images of the policy process. If you prefer a watery metaphor (it’s your life, I suppose), click Policy Concepts in 1000 Words: Multiple Streams Analysis

For more on entrepreneurs:

So you want to be a policy entrepreneur? https://t.co/y8RG7MOSKV by @MikeMintrom

— Professor Paul Cairney (@CairneyPaul) October 29, 2019

Practical Lessons from Policy Theories

These links to blog posts (the underlined headings) and tweets (with links to their full article) describe a new special issue of Policy and Politics, published in April 2018 and free to access until the end of May.

Practical lessons from policy theories@policy_politics special issue Guest edited by Chris @chris_weible and me, and free to download (for now) https://t.co/bSNd5LBRdF

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

In the introduction, we use the much-argued position – "many scholars hide behind a veil of jargon and obfuscation" – to encourage each author to state the contribution of their field in simple terms https://t.co/m0CxfctglA pic.twitter.com/nAQczVTdXZ

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

Three habits of successful policy entrepreneurs

In my article 'Three habits of successful policy entrepreneurs', I summarise the insights of 'multiple streams' analysis to show how entrepreneurs engage with the politics of evidence-based policymaking https://t.co/PPI3Q3orzc pic.twitter.com/nINp02ogCq

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

Telling stories that shape public policy

In 'Narratives as tools for influencing policy change', Deserai Crow and Mike Jones describe 5 key elements of good storytelling for policy https://t.co/nXTwEhc0qP pic.twitter.com/4VEzYrUdpL

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

How to design ‘maps’ for policymakers relying on their ‘internal compass’

In 'Using cultural theory to navigate the policy process', Richard Simmons describes how policymaking rules are internalised in individuals and reproduced in organisations https://t.co/IbiBqJ9qJn pic.twitter.com/hQVlRJKZSP

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

Three ways to encourage policy learning

In 'The lessons of policy learning', Claire Dunlop and @ProfCRadaelli explain the gap between policy learning as important aim but often-dysfunctional process https://t.co/IYiWAcTxVF pic.twitter.com/voc8UoJ49b

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

How can governments better collaborate to address complex problems?

In 'Practical prescriptions for governing fragmented governments', William Swann and @serena_y_kim_ use Institutional Collection Action (ICA) to explain how policymaking organisations can work together effectively https://t.co/7TIuRTfpvO pic.twitter.com/c3biW9JXYa

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

How do we get governments to make better decisions?

Policymakers have to process *too much information* (not too little). In 'Drawing practical lessons from punctuated equilibrium theory', @ckoski79 and Samuel Workman describe how organisations could process information effectively https://t.co/beNyeiDUbN pic.twitter.com/FSuBhVTnW7

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

How to navigate complex policy designs

In 'Policy design and the added-value of the institutional analysis development framework', @tanyaheikkila and Krister Andersson describe how to cooperate effectively to design good policy https://t.co/yMZhpB6Eog pic.twitter.com/acixaV6brd

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

Why advocacy coalitions matter and how to think about them

Last but not least, in 'Why advocacy coalitions matter and practical insights about them', @chris_weible and Karin Ingold explain the many ways in which people cooperate to influence politics and policy https://t.co/cYYp5tYcZO pic.twitter.com/36xsq2yAF8

— Professor Paul Cairney (@CairneyPaul) April 30, 2018

None of these abstract theories provide a ‘blueprint’ for action (they were designed primarily to examine the policy process scientifically). Instead, they offer one simple insight: you’ll save a lot of energy if you engage with the policy process that exists, not the one you want to see.

Then, they describe variations on the same themes, including:

1. There are profound limits to the power of individual policymakers: they can only process so much information, have to ignore almost all issues, and therefore tend to share policymaking with many other actors.
2. You can increase your chances of success if you work with that insight: identify the right policymakers, the ‘venues’ in which they operate, and the ‘rules of the game’ in each venue; build networks and form coalitions to engage in those venues; shape agendas by framing problems and telling good stories, design politically feasible solutions, and learn how to exploit ‘windows of opportunity’ for their selection.

Background to the special issue

Don't miss 'Political Influence: A Seminar on Drawing Practical Lessons from Policy Theory' on 15 May. Watch online: https://t.co/fwvv1Qfysl pic.twitter.com/26HFRZOTck

— Policy & Politics (@policy_politics) May 10, 2017

Chris Weible and I asked a group of policy theory experts to describe the ‘state of the art’ in their field and the practical lessons that they offer.

Our next presentation was at the ECPR in Oslo:

Our #ecprconf17 panel Practical Lessons from Theories of the Policy Process https://t.co/kEo5MCQKvh has blogs>papers https://t.co/iOVlvaVH0e

— ProfessorPaulCairney (@CairneyPaul) September 5, 2017

The final articles in this series are now complete, but our introduction discusses the potential for more useful contributions

I know my audience, but does my other audience know I know my audience?

‘Know your audience’ is a key phrase for anyone trying to convey a message successfully. To ‘know your audience’ is to understand the rules they use to make sense of your message, and therefore the adjustments you have to make to produce an effective message. Simple examples include:

• The sarcasm rules. The first rule is fairly explicit. If you want to insult someone’s shirt, you (a) say ‘nice shirt, pal’, but also (b) use facial expressions or unusual speech patterns to signal that you mean the opposite of what you are saying. Otherwise, you’ve inadvertently paid someone a compliment, which is just not on. The second rule is implicit. Sarcasm is sometimes OK – as a joke or as some nice passive aggression – and a direct insult (‘that shirt is shite, pal’) as a joke is harder to pull off.
• The joke rule. If you say that you went to the doctor because a strawberry was growing out of your arse and the doctor gave you some cream for it, you’d expect your audience to know you were joking because it’s such a ridiculous scenario and there’s a pun. Still, there’s a chance that, if you say it quickly, with a straight face, your audience is not expecting a joke, and/ or your audience’s first language is not English, your audience will take you seriously, if only for a second. It’s hilarious if your audience goes along with you, and a bit awkward if your audience asks kindly about your welfare.
• Keep it simple stupid. If someone says KISS, or some modern equivalent – ‘it’s the economy, stupid’, the rule is that, generally, they are not calling you stupid (even though the insertion of the comma, in modern phrases, makes it look like they are). They are referring to the value of a simple design or explanation that as many people as possible can understand. If your audience doesn’t know the phrase, they may think you’re calling them stupid, stupid.

These rules can be analysed from various perspectives: linguistics, focusing on how and why rules of language develop; and philosophy, to help articulate how and why rules matter in sense making.

There is also a key role for psychological insights, since – for example – a lot of these rules relate to the routine ways in which people engage emotionally with the ‘signals’ or information they receive.

Think of the simple example of twitter engagement, in which people with emotional attachments to one position over another (say, pro- or anti- Brexit), respond instantly to a message (say, pro- or anti- Brexit). While some really let themselves down when they reply with their own tweet, and others don’t say a word, neither audience is immune from that emotional engagement with information. So, to ‘know your audience’ is to anticipate and adapt to the ways in which they will inevitably engage ‘rationally’ and ‘irrationally’ with your message.

I say this partly because I’ve been messing around with some simple ‘heuristics’ built on insights from psychology, including Psychology Based Policy Studies: 5 heuristics to maximise the use of evidence in policymaking .

Two audiences in the study of ‘evidence based policymaking’

I also say it because I’ve started to notice a big unintended consequence of knowing my audience: my one audience doesn’t like the message I’m giving the other. It’s a bit like gossip: maybe you only get away with it if only one audience is listening. If they are both listening, one audience seems to appreciate some new insights, while the other wonders if I’ve ever read a political science book.

The problem here is that two audiences have different rules to understand the messages that I help send. Let’s call them ‘science’ and ‘political science’ (please humour me – you’ve come this far). Then, let’s make some heroic binary distinctions in the rules each audience would use to interpret similar issues in a very different way.

I could go on with these provocative distinctions, but you get the idea. A belief taken for granted in one field will be treated as controversial in another. In one day, you can go to one workshop and hear the story of objective evidence, post-truth politics, and irrational politicians with low political will to select evidence-based policies, then go to another workshop and hear the story of subjective knowledge claims.

Or, I can give the same presentation and get two very different reactions. If these are the expectations of each audience, they will interpret and respond to my messages in very different ways.

So, imagine I use some psychology insights to appeal to the ‘science’ audience. I know that,  to keep it on side and receptive to my ideas, I should begin by being sympathetic to its aims. So, my implicit story is along the lines of, ‘if you believe in the primacy of science and seek evidence-based policy, here is what you need to do: adapt to irrational policymaking and find out where the action is in a complex policymaking system’. Then, if I’m feeling energetic and provocative, I’ll slip in some discussion about knowledge claims by saying something like, ‘politicians (and, by the way, some other scholars) don’t share your views on the hierarchy of evidence’, or inviting my audience to reflect on how far they’d go to override the beliefs of other people (such as the local communities or service users most affected by the evidence-based policies that seem most effective).

The problem with this story is that key parts are implicit and, by appearing to go along with my audience, I provoke a reaction in another audience: don’t you know that many people have valid knowledge claims? Politics is about values and power, don’t you know?

So, that’s where I am right now. I feel like I ‘know my audience’ but I am struggling to explain to my original political science audience that I need to describe its insights in a very particular way to have any traction in my other science audience. ‘Know your audience’ can only take you so far unless your other audience knows that you are engaged in knowing your audience.

If you want to know more, see:

Kathryn Oliver and I have just published an article on the relationship between evidence and policy

How far should you go to secure academic ‘impact’ in policymaking? From ‘honest brokers’ to ‘research purists’ and Machiavellian manipulators

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

The Science of Evidence-based Policymaking: How to Be Heard

When presenting evidence to policymakers, engage with the policy process that exists, not the process you wish existed

 

 

‘Co-producing’ comparative policy research: how far should we go to secure policy impact?

See also our project website IMAJINE.

Two recent articles explore the role of academics in the ‘co-production’ of policy and/or knowledge.

• Matt Flinders, Matt Wood, and Malaika Cunningham, in The politics of co-production: risks, limits and pollution, examine: the perception by some academics that co-producing knowledge with other actors ‘pollutes’ the research; and, the risks of building up the expectations of your partners when the impact of this work (and of the partners in helping to produce it) is often limited.
• Kathryn Oliver and I, in Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?, examine the dilemmas faced by researchers when they try to ‘co-produce’ evidence-informed policy, including whether to ‘frame’ evidence in relation to the beliefs of policymakers, and assert superior knowledge claims to influence policy delivery.

Both papers suggest (I think) that academic engagement in the ‘real world’ is highly valuable, and that we should not pretend that we can remain aloof from politics when producing new knowledge (research production is political even if it is not overtly party political). They also suggest that it is fraught with difficulty and, perhaps, an often-thankless task with no guarantee of professional or policy payoffs (intrinsic motivation still trumps extrinsic motivation).

So, what should we do?

I plan to experiment a little bit while conducting some new research over the next 4 years. For example, I am part of a new project called IMAJINE, and plan to speak with policymakers, from the start to the end, about what they want from the research and how they’ll use it. My working assumption is that it will help boost the academic value and policy relevance of the research.

I have mocked up a paper abstract to describe this kind of work:

In this paper, we use policy theory to explain why the ‘co-production’ of comparative research with policymakers makes it more policy relevant: it allows researchers to frame their policy analysis with reference to the ways in which policymakers frame policy problems; and, it helps them identify which policymaking venues matter, and the rules of engagement within them.  In other words, theoretically-informed researchers can, to some extent, emulate the strategies of interest groups when they work out ‘where the action is’ and how to adapt to policy agendas to maximise their influence. Successful groups identify their audience and work out what it wants, rather than present their own fixed views to anyone who will listen.

Yet, when described so provocatively, our argument raises several practical and ethical dilemmas about the role of academic research. In abstract discussions, they include questions such as: should you engage this much with politics and policymakers, or maintain a critical distance; and, if you engage, should you simply reflect or seek to influence the policy agenda? In practice, such binary choices are artificial, prompting us to explore how to manage our engagement in politics and reflect on our potential influence.

We explore these issues with reference to a new Horizon 2020 funded project IMAJINE, which includes a work package – led by Cairney – on the use of evidence and learning from the many ways in which EU, national, and regional policymakers have tried to reduce territorial inequalities.

So, in the paper we (my future research partner and I), would:

• Outline the payoffs to this engage-early approach. Early engagement will inform the research questions you ask, how you ask them, and how you ‘frame’ the results. It should also help produce more academic publications (which is still the key consideration for many academics), partly because this early approach will help us speak with some authority about policy and policymaking in many countries.
• Describe the complications of engaging with different policymakers in many ‘venues’ in different countries: you would expect very different questions to arise, and perhaps struggle to manage competing audience demands.
• Raise practical questions about the research audience, including: should we interview key advocacy groups and private sources of funding for applied research, as well as policymakers, when refining questions? I ask this question partly because it can be more effective to communicate evidence via policy influencers rather than try to engage directly with policymakers.
• Raise ethical questions, including: what if policymaker interviewees want the ‘wrong’ questions answered? What if they are only interested in policy solutions that we think are misguided, either because the evidence-base is limited (and yet they seek a magic bullet) or their aims are based primarily on ideology (an allegedly typical dilemma regards left-wing academics providing research for right-wing governments)?

Overall, you can see the potential problems: you ‘enter’ the political arena to find that it is highly political! You find that policymakers are mostly interested in (what you believe are) ineffective or inappropriate solutions and/ or they think about the problem in ways that make you, say, uncomfortable. So, should you engage in a critical way, risking exclusion from the ‘coproduction’ of policy, or in a pragmatic way, to ‘coproduce’ knowledge and maximise your chances of their impact in government?

The case study of territorial inequalities is a key source of such dilemmas …

…partly because it is difficult to tell how policymakers define and want to solve such policy problems. When defining ‘territorial inequalities’, they can refer broadly to geographical spread, such as within the EU Member States, or even within regions of states. They can focus on economic inequalities, inequalities linked strongly to gender, race or ethnicity, mental health, disability, and/ or inequalities spread across generations. They can focus on indicators of inequalities in areas such as health and education outcomes, housing tenure and quality, transport, and engagement with social work and criminal justice. While policymakers might want to address all such issues, they also prioritise the problems they want to solve and the policy instruments they are prepared to use.

When considering solutions, they can choose from three basic categories:

1. Tax and spending to redistribute income and wealth, perhaps treating economic inequalities as the source of most others (such as health and education inequalities).
2. The provision of public services to help mitigate the effects of economic and other inequalities (such as free healthcare and education, and public transport in urban and rural areas).
3. The adoption of ‘prevention’ strategies to engage as early as possible in people’s lives, on the assumption that key inequalities are well-established by the time children are three years old.

Based on my previous work with Emily St Denny, I’d expect that many governments express a high commitment to reduce inequalities – and it is often sincere – but without wanting to use tax/ spending as the primary means, and faced with limited evidence on the effectiveness of public services and prevention. Or, many will prefer to identify ‘evidence-based’ solutions for individuals rather than to address ‘structural’ factors linked to factors such as gender, ethnicity, and class. This is when the production and use of evidence becomes overtly ‘political’, because at the heart of many of these discussions is the extent to which individuals or their environments are to blame for unequal outcomes, and if richer regions should compensate poorer regions.

‘The evidence’ will not ‘win the day’ in such debates. Rather, the choice will be between, for example: (a) pragmatism, to frame evidence to contribute to well-established beliefs, about policy problems and solutions, held by the dominant actors in each political system; and, (b) critical distance, to produce what you feel to be the best evidence generated in the right way, and challenge policymakers to explain why they won’t use it. I suspect that (a) is more effective, but (b) better reflects what most academics thought they were signing up to.

For more on IMAJINE, see New EU study looks at gap between rich and poor and The theory and practice of evidence-based policy transfer: can we learn how to reduce territorial inequalities?

For more on evidence/ policy dilemmas, see Kathryn Oliver and I have just published an article on the relationship between evidence and policy