Category Archives: Storytelling

Beware the well-intentioned advice of unusually successful academics

This post – by Dr Kathryn Oliver and me – originally appeared on the LSE Impact Blog. I have replaced the picture of a thumb up with a cat hanging in there. 

Many academics want to see their research have an impact on policy and practice, and there is a lot of advice on how to seek it. It can be helpful to take advice from experienced and successful people. However, is this always the best advice? Guidance based on best practice and success stories in particular, often reflect unequal access to policymakers, institutional support, and credibility attached to certain personal characteristics.

To take stock of the vast amount of advice being offered to academics, we decided to compare it with the more systematic analyses available in the peer-reviewed literature, on the ‘barriers’ between evidence and policy, and policy studies. This allowed us to situate this advice in a wider context, see whether it was generalisable across settings and career stages, and to think through the inconsistencies and dilemmas which underlie these suggestions.

The advice: Top tips on influencing policy

The key themes and individual recommendations we identified from the 86 most-relevant publications are:

  1. Do high quality research: Use well-established research designs, methods, or metrics.
  2. Make your research relevant and readable: Provide easily-understandable, clear, relevant and high-quality research. Aim for the general reader. Produce good stories based on emotional appeals or humour.
  3. Understand the policymaking context. Note the busy and constrained lives of policy actors. Maximise established ways to engage, such as in advisory committees. Be pragmatic, accepting that research rarely translates directly into policy.
  4. Be ‘accessible’ to policymakers. This may involve discussing topics beyond your narrow expertise. Be humble, courteous, professional, and recognise the limits to your skills.
  5. Decide if you want to be an ‘issue advocate’. Decide whether to simply explain the evidence, remain an ‘honest broker, or recommend specific policy options. Negative consequences may include peer criticism, being seen as an academic lightweight, being used to add legitimacy to a policy position, and burnout.
  6. Build relationships (and ground rules) with policymakers: Relationship-building requires investment and skills, but working collaboratively is often necessary. Academics could identify policy actors to provide insights into policy problems, act as champions for their research, and identify the most helpful policy actors.
  7. Be ‘entrepreneurial’ or find someone who is. Be a daring, persuasive scientist, comfortable in policy environments and available when needed. Or, seek brokers to act on your behalf.
  8. Reflect continuously: should you engage, do you want to, and is it working? Academics may enjoy the work or are passionate about the issue. Even so, keep track of when and how you have had impact, and revise your practices continuously.

hang-in-there-baby

Inconsistencies and dilemmas

This advice tends not to address wider issues. For example, there is no consensus over what counts as good evidence for policy, or therefore how best to communicate good evidence. We know little about how to gain the wide range of skills that researchers and policymakers need to act collectively, including to: produce evidence syntheses, manage expert communities, ‘co-produce’ research and policy with a wide range of stakeholders, and be prepared to offer policy recommendations as well as scientific advice. Further, a one-size fits-all model won’t help researchers navigate a policymaking environment where different venues have different cultures and networks. Researchers therefore need to decide what policy engagement is for—to frame problems or simply measure them according to an existing frame—and how far researchers should go to be useful and influential. If academics need to go ‘all in’ to secure meaningful impact, we need to reflect on the extent to which they have the resources and support to do so. This means navigating profound dilemmas:

Source: The dos and don’ts of influencing policy: a systematic review of advice to academics

 

Can academics try to influence policy? The financial costs of seeking impact are prohibitive for junior or untenured researchers, while women and people of colour may be more subject to personal abuse. Such factors undermine the diversity of voices available.

How should academics influence policy? Many of these new required skills – such as storytelling – are not a routine part of academic training, and may be looked down on by our colleagues.  

What is the purpose of academics engagement in policymaking? To go beyond tokenistic and instrumental engagement is to build genuine rapport with policymakers, which may require us to co-produce knowledge and cede some control over the research process. It involves a fundamentally different way of doing public engagement: one with no clear aim in mind other than to listen and learn, with the potential to transform research practices and outputs.

Where is the evidence that this advice helps us improve impact?

The existing advice offered to academics on how to create impact is – although often well-meaning – not based on systematic research or comprehensive analysis of empirical evidence. Few advice-givers draw clearly on key literatures on policymaking or evidence use. This leads to significant misunderstandings, which can have potentially costly repercussions for research, researchers and policy.  These limitations matter, as they lead to advice which fails to address core dilemmas for academics—whether to engage, how to engage, and why—which have profound implications for how scientists and universities should respond to the calls for increased impact.

Most tips focus on individual experience, whereas engagement between research and policy is driven by systemic factors. Many of the tips may be sensible and effective, but often only within particular settings. The advice is likely to be useful mostly to a relatively similar group of people who are confident and comfortable in policy environments, and have access and credibility within policy arenas. Thus, the current advice and structures may help reproduce and reinforce existing power dynamics and an underrepresentation of people who do not fit a very narrow mould.

The overall result may be that each generation of scientists has to fight the same battles, and learn the same lessons over again. Our best response as a profession is to interrogate current advice, shape and frame it, and to help us all to find ways to navigate the complex practical, political, moral and ethical challenges associated with being researchers today. The ‘how to’ literature can help, but only if authors are cognisant of their wider role in society and complex policymaking systems.

This blog post is based on the authors’ co-written articles, The dos and don’ts of influencing policy: a systematic review of advice to academics, published in Palgrave Communications, and ‘How should academics engage in policymaking to achieve impact?’  published in Political Studies Review 

About the authors

Kathryn Oliver is Associate Professor of Sociology and Public Health, London School of Hygiene and Tropical Medicine (@oliver_kathryn ). Her interest is in how knowledge is produced, mobilized and used in policy and practice, and how this affects the practice of research. She co-runs the research collaborative Transforming Evidence with Annette Boaz. https://transformure.wordpress.com and her writings can be found here: https://kathrynoliver.wordpress.com

Paul Cairney is Professor of Politics and Public Policy, University of Stirling, UK (@Cairneypaul).  His research interests are in comparative public policy and policy theories, which he uses to explain the use of evidence in policy and policymaking, in one book (The Politics of Evidence-Based Policy Making, 2016), several articles, and many, many blog posts: https://paulcairney.wordpress.com/ebpm/

See also:

  1. Adam Wellstead, Paul Cairney, and Kathryn Oliver (2018) ‘Reducing ambiguity to close the science-policy gap’, Policy Design and Practice, 1, 2, 115-25 PDF
  2. 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 PDF AM
  3. 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, 76, 3, 399–402 DOI:10.1111/puar.12555 PDF

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Policy in 500 Words: Power and Knowledge

Classic studies suggest that the most profound and worrying kinds of power are the hardest to observe. We often witness highly visible political battles and can use pluralist methods to identify who has material resources, how they use them, and who wins. However, key forms of power ensure that many such battles do not take place. Actors often use their resources to reinforce social attitudes and policymakers’ beliefs, to establish which issues are policy problems worthy of attention and which populations deserve government support or punishment. Key battles may not arise because not enough people think they are worthy of debate. Attention and support for debate may rise, only to be crowded out of a political agenda in which policymakers can only debate a small number of issues.

Studies of power relate these processes to the manipulation of ideas or shared beliefs under conditions of bounded rationality (see for example the NPF). Manipulation might describe some people getting other people to do things they would not otherwise do. They exploit the beliefs of people who do not know enough about the world, or themselves, to know how to identify and pursue their best interests. Or, they encourage social norms – in which we describe some behaviour as acceptable and some as deviant – which are enforced by the state (for example, via criminal justice and mental health policy), but also social groups and individuals who govern their own behaviour with reference to what they feel is expected of them (and the consequences of not living up to expectations).

Such beliefs, norms, and rules are profoundly important because they often remain unspoken and taken for granted. Indeed, some studies equate them with the social structures that appear to close off some action. If so, we may not need to identify manipulation to find unequal power relationships: strong and enduring social practices help some people win at the expense of others, by luck or design.

In practice, these more-or-less-observable forms of power co-exist and often reinforce each other:

Example 1. The control of elected office is highly skewed towards men. Male incumbency, combined with social norms about who should engage in politics and public life, signal to women that their efforts may be relatively unrewarded and routinely punished – for example, in electoral campaigns in which women face verbal and physical misogyny – and the oversupply of men in powerful positions tends to limit debates on feminist issues.

Example 2. ‘Epistemic violencedescribes the act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge. Specific discussions include: (a) the colonial West’s subjugation of colonized populations, diminishing the voice of the subaltern; (b) privileging scientific knowledge and dismissing knowledge claims via personal or shared experience; and (c) erasing the voices of women of colour from the history of women’s activism and intellectual history.

It is in this context that we can understand ‘critical’ research designed to ‘produce social change that will empower, enlighten, and emancipate’ (p51). Powerlessness can relate to the visible lack of economic material resources and factors such as the lack of opportunity to mobilise and be heard.

See also:

Policy Concepts in 1000 Words: Power and Ideas

Evidence-informed policymaking: context is everything

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Evidence-informed policymaking: context is everything

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

 

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

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

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

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

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

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

Limiting participation as a strategic aim

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

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

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

NASA launch

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

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

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

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

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

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

Where is the power analysis in all of this?

image policy process round 2 25.10.18

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

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

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

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

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

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

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

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

See also:

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

listening-new-york-1-11-16

See also:

Policy in 500 Words: Power and Knowledge

The politics of evidence-based policymaking

Palgrave Communications: The politics of evidence-based policymaking

Using evidence to influence policy: Oxfam’s experience

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

 

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Evidence-based policymaking and the ‘new policy sciences’

Circle image policy process 24.10.18

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:

SLIDE simple advice from hexagon image policy process 24.10.18

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

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Emotion and reason in politics: the rational/ irrational distinction

In ‘How to communicate effectively with policymakers’, Richard Kwiatkowski and I use the distinction between ‘rational’ and ‘irrational’ cognitive shortcuts ‘provocatively’. I sort of wish we had been more direct, because I have come to realise that:

  1. My attempts to communicate with sarcasm and facial gestures may only ever appeal to a niche audience, and
  2. even if you use the scare quotes – around a word like ‘irrational’ – to denote the word’s questionable use, it’s not always clear what I’m questioning, because
  3. you need to know the story behind someone’s discussion to know what they are questioning.*

So, here are some of the reference points I’m using when I tell a story about ‘irrationality’:

1. I’m often invited to be the type of guest speaker that challenges the audience, it is usually a scientific audience, and the topic is usually evidence based policymaking.

So, when I say ‘irrational’, I’m speaking to (some) scientists who think of themselves as rational and policymakers as irrational, and use this problematic distinction to complain about policy-based evidence, post-truth politics, and perhaps even the irrationality of voters for Brexit. Action based on this way of thinking would be counterproductive. In that context, I use the word ‘irrational’ as a way into some more nuanced discussions including:

  • all humans combine cognition and emotion to make choices; and,
  • emotions are one of many sources of ‘fast and frugal heuristics’ that help us make some decisions very quickly and often very well.

In other words, it is silly to complain that some people are irrational, when we are all making choices this way, and such decision-making is often a good thing.

2. This focus on scientific rationality is part of a wider discussion of what counts as good evidence or valuable knowledge. Examples include:

  • Policy debates on the value of bringing together many people with different knowledge claims – such as through user and practitioner experience – to ‘co-produce’ evidence.
  • Wider debates on the ‘decolonization of knowledge’ in which narrow ‘Western’ scientific principles help exclude the voices of many populations by undermining their claims to knowledge.

3. A focus on rationality versus irrationality is still used to maintain sexist and racist caricatures or stereotypes, and therefore dismiss people based on a misrepresentation of their behaviour.

I thought that, by now, we’d be done with dismissing women as emotional or hysterical, but apparently not. Indeed, as some recent racist and sexist coverage of Serena Williams demonstrates, the idea that black women are not rational is still tolerated in mainstream discussion.

4. Part of the reason that we can only conclude that people combine cognition and emotion, without being able to separate their effects in a satisfying way, is that the distinction is problematic.

It is difficult to demonstrate empirically. It is also difficult to assign some behaviours to one camp or the other, such as when we consider moral reasoning based on values and logic.

To sum up, I’ve been using the rational/irrational distinction explicitly to make a simple point that is relevant to the study of politics and policymaking:

  • All people use cognitive shortcuts to help them ignore almost all information about the world, to help them make decisions efficiently.
  • If you don’t understand and act on this simple insight, you’ll waste your time by trying to argue someone into submission or giving them a 500-page irrelevant report when they are looking for one page written in a way that makes sense to them.

Most of the rest has been mostly implicit, and communicated non-verbally, which is great when you want to keep a presentation brief and light, but not if you want to acknowledge nuance and more serious issues.

 

 

 

 

*which is why I’m increasingly interested in Riker’s idea of heresthetics, in which the starting point of a story is crucial. We can come to very different conclusions about a problem and its solution by choosing different starting points, to accentuate one aspect of a problem and downplay another, even when our beliefs and preferences remain basically the same.

 

 

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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.

  1. 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:

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:

p234 UPP ambiguity

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

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

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.

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.

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.

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.

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.

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?

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’.

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.

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.

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).

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.

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

 

 

 

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Filed under Evidence Based Policymaking (EBPM), Psychology Based Policy Studies, public policy, Storytelling