Category Archives: Evidence Based Policymaking (EBPM)

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.

Powerpoint: Paul Cairney A4UE UCL 2017

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Speaking truth to power: a sometimes heroic but often counterproductive strategy

Our MPP class started talking about which Tom Cruise character policy analysts should be.

It started off as a point about who not to emulate: Tom Cruise in A Few Good Men. I used this character (inaccurately) to represent the archetype of someone ‘speaking truth to power’ (yes, I know TC actually said ‘I want the truth’ and JN said ‘you can’t handle the truth’).

The story of ‘speaking truth to power’ comes up frequently in discussions of the potentially heroic nature of researchers committed to (a) producing the best scientific evidence, (b) maximising the role of scientific evidence in policy, and (b) telling off policymakers if they don’t use evidence to inform their decisions. They can’t handle the truth.

Yet, as I argue in this article with Richard Kwiatkowski (for this series on evidence/policy) ‘without establishing legitimacy and building trust’ it can prove to be counterproductive. Relevant sections include:

This involves showing simple respect and seeking ways to secure their trust, rather than feeling egotistically pleased about ‘speaking truth to power’ without discernible progress. Effective engagement requires preparation, diplomacy, and good judgement as much as good evidence.

and

One solution [to obstacles associated with organizational psychology, discussed by Larrick] is ‘task conflict’ rather than ‘relationship conflict’, to encourage information sharing without major repercussions. It requires the trust and ‘psychological safety’ that comes with ‘team development’ … If successful, one can ‘speak truth to power’ … or be confident that your presentation of evidence, which challenges the status quo, is received positively.  Under such circumstances, a ‘battle of ideas’ can genuinely take place and new thinking can be possible. If these circumstances are not present, speaking truth to power may be disastrous.

The policy analyst would be better as the Tom Cruise character in Live, Die, Repeat. He exhibits a lot of relevant behaviour:

  • Engaging in trial and error to foster practical learning
  • Building up trust with, and learning from, key allies with more knowledge and skills
  • Forming part of, and putting faith in, a team of which he is a necessary but insufficient part

In The New Policy Sciences, Chris Weible and I put it this way:

focus on engagement for the long term to develop the resources necessary to maximize the impact of policy analysis and understand the context in which the information is used. Among the advantages of long-term engagement are learning the ‘rules of the game’ in organizations, forming networks built on trust and a track record of reliability, learning how to ‘soften’ policy solutions according to the beliefs of key policymakers and influencers, and spotting ‘windows of opportunity’ to bring together attention to a problem, a feasible solution, and the motive and opportunity of policymakers to select it …In short, the substance of your analysis only has meaning in relation to the context in which it is used. Further, generating trust in the messenger and knowing your audience may be more important to success than presenting the evidence.

I know TC was the hero, but he couldn’t have succeeded without training by Emily Blunt and help from that guy who used to be in Eastenders. To get that help, he had to stop being an arse when addressing thingy from Big Love.

In real world policymaking, individual scientists should not see themselves as heroes to be respected instantly and simply for their knowledge. They will only effective in several venues – from the lab to public and political arenas – if they are humble enough to learn from others and respect the knowledge and skills of other people. ‘Speaking truth to power’ is catchy and exciting but it doesn’t capture the sense of pragmatism we often need to be effective.

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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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A 5-step strategy to make evidence count

5 stepsLet’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.

cycle

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:

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.

how-to-be-heard

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

Table 1 Three ideal types EBBP

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

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Policy Concepts in 500 Words: Social Construction and Policy Design

Why would a democratic political system produce ‘degenerative’ policy that undermines democracy? Social Construction and Policy Design (SCPD) describes two main ways in which policymaking alienates many citizens:

1. The Social Construction of Target Populations

High profile politics and electoral competition can cause alienation:

  1. Political actors compete to tell ‘stories’ to assign praise or blame to groups of people. For example, politicians describe value judgements about who should be rewarded or punished by government. They base them on stereotypes of ‘target populations’, by (a) exploiting the ways in which many people think about groups, or (b) making emotional and superficial judgements, backed up with selective use of facts.
  2. These judgements have a ‘feed-forward’ effect: they are reproduced in policies, practices, and institutions. Such ‘policy designs’ can endure for years or decades. The distribution of rewards and sanctions is cumulative and difficult to overcome.
  3. Policy design has an impact on citizens, who participate in politics according to how they are characterised by government. Many know they will be treated badly; their engagement will be dispiriting.

Some groups have the power to challenge the way they are described by policymakers (and the media and public), and receive benefits behind the scenes despite their poor image. However, many people feel powerless, become disenchanted with politics, and do not engage in the democratic process.

SCTP depicts this dynamic with a 2-by-2 table in which target populations are described positively/ negatively and more or less able to respond:

SCPD 500 words 2 by 2

2. Bureaucratic and expert politics

Most policy issues are not salient and politicised in this way. Yet, low salience can exacerbate problems of citizen exclusion. Policies dominated by bureaucratic interests often alienate citizens receiving services. Or a small elite dominates policymaking when there is high acceptance that (a) the best policy is ‘evidence based’, and (b) the evidence should come from experts.

Overall, SCPD describes a political system with major potential to diminish democracy, containing key actors (a) politicising issues to reward or punish populations or (b) depoliticising issues with reference to science and objectivity. In both cases, policy design is not informed by routine citizen participation.

Take home message for students: SCPD began as Schneider and Ingram’s description of the US political system’s failure to solve major problems including inequality, poverty, crime, racism, sexism, and effective universal healthcare and education. Think about how its key drivers apply elsewhere: (1) some people make and exploit quick and emotional judgements for political gain, and others refer to expertise to limit debate; (2) these judgements inform policy design; and, (3) policy design sends signals to citizens which can diminish or boost their incentive to engage in politics.

For more, see the 1000-word and 5000-word versions. The latter has a detailed guide to further reading.

 

 

 

 

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Three ways to encourage policy learning

Claire Claudio

This is a guest post by  Claire A. Dunlop (left) and Claudio M. Radaelli (right), discussing how to use insights from the Policy Learning literature to think about how to learn effectively or adapt to the processes of ‘learning’ in policymaking that are more about politics than education. The full paper has been submitted to the series for Policy and Politics called Practical Lessons from Policy Theories.

We often hear that university researchers are ‘all brains but no common sense’. There is often some truth to this stereotype. The literature on policy learning is an archetypal example of being high in IQ but low on street smarts. Researchers have generated a huge amount of ‘policy learning’ taxonomies, concepts and methods without showing what learning can offer policy-makers, citizens and societies.

This is odd because there is a substantive demand and need for practical insights on how to learn. Issues include economic growth, the control of corruption, and improvement in schools and health. Learning organisations range from ‘street level bureaucracies’ to international regulators like the European Union and the World Trade Organization.

To help develop a more practical agenda, we distil three major lessons from the policy learning literature.

1. Learning is often the by-product of politics, not the primary goal of policymakers

There is usually no clear incentive for political actors to learn how to improve public policy. Learning is often the by-product of bargaining, the effort to secure compliance with the law and rules, social participation, or problem-solving when there is radical uncertainty. This means that in politics we should not assume that politicians, bureaucrats, civil society organizations, experts interact to improve public policy. Consensus, participation, formal procedures, and social certification are more important.

Therefore, we have to learn how to design incentives so that the by-product of learning is actually generated. Otherwise, few actors will play the game of the policy-making process with learning as their first goal. Learning is all around us, but it appears in different forms, depending on whether the context is (a) bargaining, (b) compliance, (c) participation or (d) problem-solving under conditions of high uncertainty.

2. Each mode of learning has its triggers or hindrances

(a) Bargaining requires repeated interaction, low barriers to contract and mechanisms of preference aggregation.

(b) Compliance without trust in institutions is stymied.

(c) Participation needs its own deliberative spaces and a type of participant willing to go beyond the ‘dialogue of the deaf’. Without these two triggers, participation is chaotic, highly conflictual and inefficient.

(d) Expertise is key to problem-solving, but governments should design their advisory committees and special commissions of inquiry by recruiting a broad range of experts. The risk of excluding the next Galileo Galilei in a Ptolemaic committee is always there.

At the same time, there are specific hindrances:

(a) Bargaining stops when the winners are always the same (if you are thinking of Germany and Greece in the European Union you are spot-on).

(b) Hierarchy does not produce efficient compliance unless those at the top know exactly the solution to enforce.

(c) Incommensurable beliefs spoil participatory policy processes. If so, it’s better to switch to open democratic conflict, by counting votes in elections and referenda for example.

(d) Scientific scepticism and low policy capacity mar the work of experts in governmental bodies.

These triggers and hindrances have important lessons for design, perhaps prompting authorities (governments, regulators, public bodies) to switch from one context to another. For example, one can re-design the work of expert committees by including producers and consumers organizations or by allowing bargaining on the implementation of budgetary rules.

3. Beware the limitations of learning

We may get this precious by-product and avoid hindrances and traps, but still… learn the wrong lessons.

Latin America and Africa offer too many examples of diligent pupils who did exactly what they were supposed to do, but in the end implemented wrong policies. Perfect compliance does not provide breathing spaces to a policy and impairs the quality of innovation. We have to balance lay and professional knowledge. Bargaining does not allow us to learn about radical innovations; in some cases only a new participant can really change the nature of the game being played by the usual suspects.

So, whether the problem is learning how to fight organized crime and corruption, or to re-launch growth in Europe and development in Africa, the design of the policy process is crucial. For social actors, our analysis shows when and how they should try to change the nature of the game, or lobby for a re-design of the process. This lesson is often forgotten because social actors fight for a given policy objective, not for the parameters that define who does what and how in the policy process.

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

Prevention is the most important social policy agenda of our time. Many governments make a sincere commitment to it, backed up by new policy strategies and resources. Yet, they also make limited progress before giving up or changing tack. Then, a new government arrives, producing the same cycle of enthusiasm and despair. This fundamental agenda never seems to get off the ground. We aim to explain this ‘prevention puzzle’, or the continuous gap between policymaker expectations and actual outcomes.

What is prevention policy and policymaking?

When engaged in ‘prevention’, governments seek to:

  1. Reform policy. To move from reactive to preventive public services, intervening earlier in people’s lives to ward off social problems and their costs when they seem avoidable.
  2. Reform policymaking. To (a) ‘join up’ government departments and services to solve ‘wicked problems’ that transcend one area, (b) give more responsibility for service design to local public bodies, stakeholders, ‘communities’ and service users, and (c) produce long term aims for outcomes, and reduce short term performance targets.
  3. Ensure that policy is ‘evidence based’.

Three reasons why they never seem to succeed

We use well established policy theories/ studies to explain the prevention puzzle.

  1. They don’t know what prevention means. They express a commitment to something before defining it. When they start to make sense of it, they find out how difficult it is to pursue, and how many controversial choices it involves.
  2. They engage in a policy process that is too complex to control. They try to share responsibility with many actors and coordinate action to direct policy outcomes, without the ability to design those relationships and control policy outcomes. Yet, they need to demonstrate to the electorate that they are in control. When they make sense of policymaking, they find out how difficult it is to localise and centralise.
  3. They are unable and unwilling to produce ‘evidence based policymaking’. Policymakers seek ‘rational’ and ‘irrational’ shortcuts to gather enough information to make ‘good enough’ decisions. When they seek evidence on preventing problems before they arise, they find that it is patchy, inconclusive, often counter to their beliefs, and unable to provide a ‘magic bullet’ to help make and justify choices.

Who knows what happens when they address these problems at the same time?

We draw on empirical and comparative UK and devolved government analysis to show in detail how policymaking differs according to the (a) type of government, (b) issue, and (c) era in which they operate.

Although it is reasonable to expect policymaking to be very different in, for example, the UK versus Scottish, or Labour versus Conservative governments, and in eras of boom versus austerity, a key part of our research is to show that the same basic ‘prevention puzzle’ exists at all times. You can’t simply solve it with a change of venue or government.

Our UK book will be out in 2018, with new draft chapters appearing here soon. Our longer term agenda – via IMAJINE – is to examine how policymakers try to reduce territorial inequalities across Europe partly by pursuing prevention and reforming public services.

 

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Filed under Evidence Based Policymaking (EBPM), Prevention policy, public policy, UK politics and policy