Tag Archives: defining evidence

Policy Analysis in 750 words: Deborah Stone (2012) Policy Paradox

Please see the Policy Analysis in 750 words series overview before reading the summary. This post is 750 words plus a bonus 750 words plus some further reading that doesn’t count in the word count even though it does.

Stone policy paradox 3rd ed cover

Deborah Stone (2012) Policy Paradox: The Art of Political Decision Making 3rd edition (Norton)

‘Whether you are a policy analyst, a policy researcher, a policy advocate, a policy maker, or an engaged citizen, my hope for Policy Paradox is that it helps you to go beyond your job description and the tasks you are given – to think hard about your own core values, to deliberate with others, and to make the world a better place’ (Stone, 2012: 15)

Stone (2012: 379-85) rejects the image of policy analysis as a ‘rationalist’ project, driven by scientific and technical rules, and separable from politics. Rather, every policy analyst’s choice is a political choice – to define a problem and solution, and in doing so choosing how to categorise people and behaviour – backed by strategic persuasion and storytelling.

The Policy Paradox: people entertain multiple, contradictory, beliefs and aims

Stone (2012: 2-3) describes the ways in which policy actors compete to define policy problems and public policy responses. The ‘paradox’ is that it is possible to define the same policies in contradictory ways.

‘Paradoxes are nothing but trouble. They violate the most elementary principle of logic: something can’t be two different things at once. Two contradictory interpretations can’t both be true. A paradox is just such an impossible situation, and political life is full of them’ (Stone, 2012: 2).

This paradox does not refer simply to a competition between different actors to define policy problems and the success or failure of solutions. Rather:

  • The same actor can entertain very different ways to understand problems, and can juggle many criteria to decide that a policy outcome was a success and a failure (2012: 3).
  • Surveys of the same population can report contradictory views – encouraging a specific policy response and its complete opposite – when asked different questions in the same poll (2012: 4; compare with Riker)

Policy analysts: you don’t solve the Policy Paradox with a ‘rationality project’

Like many posts in this series (Smith, Bacchi, Hindess), Stone (2010: 9-11) rejects the misguided notion of objective scientists using scientific methods to produce one correct answer (compare with Spiegelhalter and Weimer & Vining). A policy paradox cannot be solved by ‘rational, analytical, and scientific methods’ because:

Further, Stone (2012: 10-11) rejects the over-reliance, in policy analysis, on the misleading claim that:

  • policymakers are engaging primarily with markets rather than communities (see 2012: 35 on the comparison between a ‘market model’ and ‘polis model’),
  • economic models can sum up political life, and
  • cost-benefit-analysis can reduce a complex problem into the sum of individual preferences using a single unambiguous measure.

Rather, many factors undermine such simplicity:

  1. People do not simply act in their own individual interest. Nor can they rank-order their preferences in a straightforward manner according to their values and self-interest.
  • Instead, they maintain a contradictory mix of objectives, which can change according to context and their way of thinking – combining cognition and emotion – when processing information (2012: 12; 30-4).
  1. People are social actors. Politics is characterised by ‘a model of community where individuals live in a dense web of relationships, dependencies, and loyalties’ and exercise power with reference to ideas as much as material interests (2012: 10; 20-36; compare with Ostrom, more Ostrom, and Lubell; and see Sousa on contestation).
  2. Morals and emotions matter. If people juggle contradictory aims and measures of success, then a story infused with ‘metaphor and analogy’, and appealing to values and emotions, prompts people ‘to see a situation as one thing rather than another’ and therefore draw attention to one aim at the expense of the others (2012: 11; compare with Gigerenzer).

Policy analysis reconsidered: the ambiguity of values and policy goals

Stone (2012: 14) identifies the ambiguity of the criteria for success used in 5-step policy analyses. They do not form part of a solely technical or apolitical process to identify trade-offs between well-defined goals (compare Bardach, Weimer and Vining, and Mintrom). Rather, ‘behind every policy issue lurks a contest over conflicting, though equally plausible, conceptions of the same abstract goal or value’ (2012: 14). Examples of competing interpretations of valence issues include definitions of:

  1. Equity, according to: (a) which groups should be included, how to assess merit, how to identify key social groups, if we should rank populations within social groups, how to define need and account for different people placing different values on a good or service, (b) which method of distribution to use (competition, lottery, election), and (c) how to balance individual, communal, and state-based interventions (2012: 39-62).
  2. Efficiency, to use the least resources to produce the same objective, according to: (a) who determines the main goal and how to balance multiple objectives, (a) who benefits from such actions, and (c) how to define resources while balancing equity and efficiency – for example, does a public sector job and a social security payment represent a sunk cost to the state or a social investment in people? (2012: 63-84).
  3. Welfare or Need, according to factors including (a) the material and symbolic value of goods, (b) short term support versus a long term investment in people, (c) measures of absolute poverty or relative inequality, and (d) debates on ‘moral hazard’ or the effect of social security on individual motivation (2012: 85-106)
  4. Liberty, according to (a) a general balancing of freedom from coercion and freedom from the harm caused by others, (b) debates on individual and state responsibilities, and (c) decisions on whose behaviour to change to reduce harm to what populations (2012: 107-28)
  5. Security, according to (a) our ability to measure risk scientifically (see Spiegelhalter and Gigerenzer), (b) perceptions of threat and experiences of harm, (c) debates on how much risk to safety to tolerate before intervening, (d) who to target and imprison, and (e) the effect of surveillance on perceptions of democracy (2012: 129-53).

Policy analysis as storytelling for collective action

Actors use policy-relevant stories to influence the ways in which their audience understands (a) the nature of policy problems and feasibility of solutions, within (b) a wider context of policymaking in which people contest the proper balance between state, community, and market action. Stories can influence key aspects of collective action, including:

  1. Defining interests and mobilising actors, by drawing attention to – and framing – issues with reference to an imagined social group and its competition (e.g. the people versus the elite; the strivers versus the skivers) (2012: 229-47)
  2. Making decisions, by framing problems and solutions (2012: 248-68). Stone (2012: 260) contrasts the ‘rational-analytic model’ with real-world processes in which actors deliberately frame issues ambiguously, shift goals, keep feasible solutions off the agenda, and manipulate analyses to make their preferred solution seem the most efficient and popular.
  3. Defining the role and intended impact of policies, such as when balancing punishments versus incentives to change behaviour, or individual versus collective behaviour (2012: 271-88).
  4. Setting and enforcing rules (see institutions), in a complex policymaking system where a multiplicity of rules interact to produce uncertain outcomes, and a powerful narrative can draw attention to the need to enforce some rules at the expense of others (2012: 289-310).
  5. Persuasion, drawing on reason, facts, and indoctrination. Stone (2012: 311-30) highlights the context in which actors construct stories to persuade: people engage emotionally with information, people take certain situations for granted even though they produce unequal outcomes, facts are socially constructed, and there is unequal access to resources – held in particular by government and business – to gather and disseminate evidence.
  6. Defining human and legal rights, when (a) there are multiple, ambiguous, and intersecting rights (in relation to their source, enforcement, and the populations they serve) (b) actors compete to make sure that theirs are enforced, (c) inevitably at the expense of others, because the enforcement of rights requires a disproportionate share of limited resources (such as policymaker attention and court time) (2012: 331-53)
  7. Influencing debate on the powers of each potential policymaking venue – in relation to factors including (a) the legitimate role of the state in market, community, family, and individual life, (b) how to select leaders, (c) the distribution of power between levels and types of government – and who to hold to account for policy outcomes (2012: 354-77).

Key elements of storytelling include:

  1. Symbols, which sum up an issue or an action in a single picture or word (2012:157-8)
  2. Characters, such as heroes or villain, who symbolise the cause of a problem or source of solution (2012:159)
  3. Narrative arcs, such as a battle by your hero to overcome adversity (2012:160-8)
  4. Synecdoche, to highlight one example of an alleged problem to sum up its whole (2012: 168-71; compare the ‘welfare queen’ example with SCPD)
  5. Metaphor, to create an association between a problem and something relatable, such as a virus or disease, a natural occurrence (e.g. earthquake), something broken, something about to burst if overburdened, or war (2012: 171-78; e.g. is crime a virus or a beast?)
  6. Ambiguity, to give people different reasons to support the same thing (2012: 178-82)
  7. Using numbers to tell a story, based on political choices about how to: categorise people and practices, select the measures to use, interpret the figures to evaluate or predict the results, project the sense that complex problems can be reduced to numbers, and assign authority to the counters (2012:183-205; compare with Speigelhalter)
  8. Assigning Causation, in relation to categories including accidental or natural, ‘mechanical’ or automatic (or in relation to institutions or systems), and human-guided causes that have intended or unintended consequences (such as malicious intent versus recklessness)
  • ‘Causal strategies’ include to: emphasise a natural versus human cause, relate it to ‘bad apples’ rather than systemic failure, and suggest that the problem was too complex to anticipate or influence
  • Actors use these arguments to influence rules, assign blame, identify ‘fixers’, and generate alliances among victims or potential supporters of change (2012: 206-28).

Wider Context and Further Reading: 1. Policy analysis

This post connects to several other 750 Words posts, which suggest that facts don’t speak for themselves. Rather, effective analysis requires you to ‘tell your story’, in a concise way, tailored to your audience.

For example, consider two ways to establish cause and effect in policy analysis:

One is to conduct and review multiple randomised control trials.

Another is to use a story of a hero or a villain (perhaps to mobilise actors in an advocacy coalition).

  1. Evidence-based policymaking

Stone (2012: 10) argues that analysts who try to impose one worldview on policymaking will find that ‘politics looks messy, foolish, erratic, and inexplicable’. For analysts, who are more open-minded, politics opens up possibilities for creativity and cooperation (2012: 10).

This point is directly applicable to the ‘politics of evidence based policymaking’. A common question to arise from this worldview is ‘why don’t policymakers listen to my evidence?’ and one answer is ‘you are asking the wrong question’.

  1. Policy theories highlight the value of stories (to policy analysts and academics)

Policy problems and solutions necessarily involve ambiguity:

  1. There are many ways to interpret problems, and we resolve such ambiguity by exercising power to attract attention to one way to frame a policy problem at the expense of others (in other words, not with reference to one superior way to establish knowledge).
  1. Policy is actually a collection of – often contradictory – policy instruments and institutions, interacting in complex systems or environments, to produce unclear messages and outcomes. As such, what we call ‘public policy’ (for the sake of simplicity) is subject to interpretation and manipulation as it is made and delivered, and we struggle to conceptualise and measure policy change. Indeed, it makes more sense to describe competing narratives of policy change.

box 13.1 2nd ed UPP

  1. Policy theories and storytelling

People communicate meaning via stories. Stories help us turn (a) a complex world, which provides a potentially overwhelming amount of information, into (b) something manageable, by identifying its most relevant elements and guiding action (compare with Gigerenzer on heuristics).

The Narrative Policy Framework identifies the storytelling strategies of actors seeking to exploit other actors’ cognitive shortcuts, using a particular format – containing the setting, characters, plot, and moral – to focus on some beliefs over others, and reinforce someone’s beliefs enough to encourage them to act.

Compare with Tuckett and Nicolic on the stories that people tell to themselves.

 

 

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Filed under 750 word policy analysis, Evidence Based Policymaking (EBPM), Psychology Based Policy Studies, public policy, Storytelling

Evidence-informed policymaking: context is everything

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

 

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

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

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

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

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

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

Limiting participation as a strategic aim

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

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

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

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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Filed under agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, Psychology Based Policy Studies, public policy, Storytelling

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

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

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

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

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

slide 3 24.10.18

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

Under those circumstances, key responses include:

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

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

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

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

In that context, I suggest that CS should:

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

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

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

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

Figure 1

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

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

Table 1 3 ideal types of EBBP

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

  1. Storytelling

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

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

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

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

See: Storytelling for Policy Change: promise and problems

  1. Evidence for advocacy

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

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

oxfam table 2

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

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

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

 

 

 

 

 

 

 

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

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

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

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

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

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

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

anzog auckland transfer ad

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

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

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

Rose 10 lessons rotated

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

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

3 reasons why ‘evidence based’ does not describe policymaking

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

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

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

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

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

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

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

The literature on ‘policy learning’ tells a similar story

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

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

1.It is collective and rule-bound

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

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

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

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

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

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

What does the literature on transfer tell us?

‘Policy transfer’ can describe a spectrum of activity:

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

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

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

However, other studies highlight some major qualifications:

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

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

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

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

Table 1 3 ideal types of EBBP

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

In conclusion

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

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

Paul Cairney Auckland Policy Transfer 12.10.18

 

 

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The Politics of Evidence-Based Policymaking: ANZSOG talks

This post introduces a series of related talks on ‘the politics of evidence-based policymaking’ (EBPM) that I’m giving as part of larger series of talks during this ANZOG-funded/organised trip.

The EBPM talks begin with a discussion of the same three points: what counts as evidence, why we must ignore most of it (and how), and the policy process in which policymakers use some of it. However, the framing of these points, and the ways in which we discuss the implications, varies markedly by audience. So, in this post, I provide a short discussion of the three points, then show how the audience matters (referring to the city as a shorthand for each talk).

The overall take-home points are highly practical, in the same way that critical thinking has many practical applications (in other words, I’m not offering a map, toolbox, or blueprint):

  • If you begin with (a) the question ‘why don’t policymakers use my evidence?’ I like to think you will end with (b) the question ‘why did I ever think they would?’.
  • If you begin by taking the latter as (a) a criticism of politics and policymakers, I hope you will end by taking it as (b) a statement of the inevitability of the trade-offs that must accompany political choice.
  • We may address these issues by improving the supply and use of evidence. However, it is more important to maintain the legitimacy of the politicians and political systems in which policymakers choose to ignore evidence. Technocracy is no substitute for democracy.

3 ways to describe the use of evidence in policymaking

  1. Discussions of the use of evidence in policy often begin as a valence issue: who wouldn’t want to use good evidence when making policy?

However, it only remains a valence issue when we refuse to define evidence and justify what counts as good evidence. After that, you soon see the political choices emerge. A reference to evidence is often a shorthand for scientific research evidence, and good often refers to specific research methods (such as randomised control trials). Or, you find people arguing very strongly in the almost-opposite direction, criticising this shorthand as exclusionary and questioning the ability of scientists to justify claims to superior knowledge. Somewhere in the middle, we find that a focus on evidence is a good way to think about the many forms of information or knowledge on which we might make decisions, including: a wider range of research methods and analyses, knowledge from experience, and data relating to the local context with which policy would interact.

So, what begins as a valence issue becomes a gateway to many discussions about how to understand profound political choices regarding: how we make knowledge claims, how to ‘co-produce’ knowledge via dialogue among many groups, and the relationship between choices about evidence and governance.

  1. It is impossible to pay attention to all policy relevant evidence.

There is far more information about the world than we are able to process. A focus on evidence gaps often gives way to the recognition that we need to find effective ways to ignore most evidence.

There are many ways to describe how individuals combine cognition and emotion to limit their attention enough to make choices, and policy studies (to all intents and purposes) describe equivalent processes – described, for example, as ‘institutions’ or rules – in organisations and systems.

One shortcut between information and choice is to set aims and priorities; to focus evidence gathering on a small number of problems or one way to define a problem, and identify the most reliable or trustworthy sources of evidence (often via evidence ‘synthesis’). Another is to make decisions quickly by relying on emotion, gut instinct, habit, and existing knowledge or familiarity with evidence.

Either way, agenda setting and problem definition are political processes that address uncertainty and ambiguity. We gather evidence to reduce uncertainty, but first we must reduce ambiguity by exercising power to define the problem we seek to solve.

  1. It is impossible to control the policy process in which people use evidence.

Policy textbooks (well, my textbook at least!) provide a contrast between:

  • The model of a ‘policy cycle’ that sums up straightforward policymaking, through a series of stages, over which policymakers have clear control. At each stage, you know where evidence fits in: to help define the problem, generate solutions, and evaluate the results to set the agenda for the next cycle.
  • A more complex ‘policy process’, or policymaking environment, of which policymakers have limited knowledge and even less control. In this environment, it is difficult to know with whom engage, the rules of engagement, or the likely impact of evidence.

Overall, policy theories have much to offer people with an interest in evidence-use in policy, but primarily as a way to (a) manage expectations, to (b) produce more realistic strategies and less dispiriting conclusions. It is useful to frame our aim as to analyse the role of evidence within a policy process that (a) we don’t quite understand, rather than (b) we would like to exist.

The events themselves

Below, you will find a short discussion of the variations of audience and topic. I’ll update and reflect on this discussion (in a revised version of this post) after taking part in the events.

Social science and policy studies: knowledge claims, bounded rationality, and policy theory

For Auckland and Wellington A, I’m aiming for an audience containing a high proportion of people with a background in social science and policy studies. I describe the discussion as ‘meta’ because I am talking about how I talk about EBPM to other audiences, then inviting discussion on key parts of that talk, such as how to conceptualise the policy process and present conceptual insights to people who have no intention of deep dives into policy theory.

I often use the phrase ‘I’ve read it, so you don’t have to’ partly as a joke, but also to stress the importance of disciplinary synthesis when we engage in interdisciplinary (and inter-professional) discussion. If so, it is important to discuss how to produce such ‘synthetic’ accounts.

I tend to describe key components of a policymaking environment quickly: many policy makers and influencers spread across many levels and types of government, institutions, networks, socioeconomic factors and events, and ideas. However, each of these terms represents a shorthand to describe a large and diverse literature. For example, I can describe an ‘institution’ in a few sentences, but the study of institutions contains a variety of approaches.

Background post: I know my audience, but does my other audience know I know my audience?

Academic-practitioner discussions: improving the use of research evidence in policy

For Wellington B and Melbourne, the audience is an academic-practitioner mix. We discuss ways in which we can encourage the greater use of research evidence in policy, perhaps via closer collaboration between suppliers and users.

Discussions with scientists: why do policymakers ignore my evidence?

Sydney UNSW focuses more on researchers in scientific fields (often not in social science).  I frame the question in a way that often seems central to scientific researcher interest: why do policymakers seem to ignore my evidence, and what can I do about it?

Then, I tend to push back on the idea that the fault lies with politics and policymakers, to encourage researchers to think more about the policy process and how to engage effectively in it. If I’m trying to be annoying, I’ll suggest to a scientific audience that they see themselves as ‘rational’ and politicians as ‘irrational’. However, the more substantive discussion involves comparing (a) ‘how to make an impact’ advice drawn from the personal accounts of experienced individuals, giving advice to individuals, and (b) the sort of advice you might draw from policy theories which focus more on systems.

Background post: What can you do when policymakers ignore your evidence?

Early career researchers: the need to build ‘impact’ into career development

Canberra UNSW is more focused on early career researchers. I think this is the most difficult talk because I don’t rely on the same joke about my role: to turn up at the end of research projects to explain why they failed to have a non-academic impact.  Instead, my aim is to encourage intelligent discussion about situating the ‘how to’ advice for individual researchers into a wider discussion of policymaking systems.

Similarly, Brisbane A and B are about how to engage with practitioners, and communicate well to non-academic audiences, when most of your work and training is about something else entirely (such as learning about research methods and how to engage with the technical language of research).

Background posts:

What can you do when policymakers ignore your evidence? Tips from the ‘how to’ literature from the science community

What can you do when policymakers ignore your evidence? Encourage ‘knowledge management for policy’

See also:

  1. A similar talk at LSHTM (powerpoint and audio)

2. European Health Forum Gastein 2018 ‘Policy in Evidence’ (from 6 minutes)

https://webcasting.streamdis.eu/Mediasite/Play/8143157d976146b4afd297897c68be5e1d?catalog=62e4886848394f339ff678a494afd77f21&playFrom=126439&autoStart=true

 

See also:

Evidence-based policymaking and the new policy sciences

 

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

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

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

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

Understand and engage with policymaking in the real world

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(2) The audio alone (link)

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

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

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

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

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

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

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

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

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

Cairney 2018 British Politics discussion section

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

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

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

Cairney British Politics 2018 Table 1

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

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

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

See also:

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

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

(found by searching for early intervention)

See also:

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

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

(found by searching for prevention)

Powerpoint for guest lecture: Paul Cairney UK Government Evidence Policy

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The Politics of Evidence revisited

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

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

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

Have we heard all this before?

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

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

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

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

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

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

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

Where do we go from there?

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

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

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

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

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

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

Is the onus on researchers?

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

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

 

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

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

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

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

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

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

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

How to be more transparent

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

How to balance research and practitioner knowledge

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

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

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

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

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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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#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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The Politics of Evidence

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Parkhurst

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

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

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

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

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

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

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

Two audiences in the study of ‘evidence based policymaking’

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

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

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

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

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

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

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

If you want to know more, see:

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

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

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

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

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

 

 

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Filed under Academic innovation or navel gazing, agenda setting, Evidence Based Policymaking (EBPM), Psychology Based Policy Studies, public policy, Storytelling

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

See also our project website IMAJINE.

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

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

So, what should we do?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

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

Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?

“There is extensive health and public health literature on the ‘evidence-policy gap’, exploring the frustrating experiences of scientists trying to secure a response to the problems and solutions they raise and identifying the need for better evidence to reduce policymaker uncertainty. We offer a new perspective by using policy theory to propose research with greater impact, identifying the need to use persuasion to reduce ambiguity, and to adapt to multi-level policymaking systems”.

We use this table to describe how the policy process works, how effective actors respond, and the dilemmas that arise for advocates of scientific evidence: should they act this way too?

We summarise this argument in two posts for:

The Guardian If scientists want to influence policymaking, they need to understand it

Sax Institute The evidence policy gap: changing the research mindset is only the beginning

The article is part of a wider body of work in which one or both of us considers the relationship between evidence and policy in different ways, including:

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 PDF

Paul Cairney (2016) The Politics of Evidence-Based Policy Making (PDF)

Oliver, K., Innvar, S., Lorenc, T., Woodman, J. and Thomas, J. (2014a) ‘A systematic review of barriers to and facilitators of the use of evidence by policymakers’ BMC health services research, 14 (1), 2. http://www.biomedcentral.com/1472-6963/14/2

Oliver, K., Lorenc, T., & Innvær, S. (2014b) ‘New directions in evidence-based policy research: a critical analysis of the literature’, Health Research Policy and Systems, 12, 34 http://www.biomedcentral.com/content/pdf/1478-4505-12-34.pdf

Paul Cairney (2016) Evidence-based best practice is more political than it looks in Evidence and Policy

Many of my blog posts explore how people like scientists or researchers might understand and respond to the policy process:

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

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

Policy Concepts in 1000 Words: ‘Evidence Based Policymaking’

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

How far should you go to secure academic ‘impact’ in policymaking?

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

Psychology Based Policy Studies: 5 heuristics to maximise the use of evidence in policymaking

What 10 questions should we put to evidence for policy experts?

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

We all want ‘evidence based policy making’ but how do we do it?

How can political actors take into account the limitations of evidence-based policy-making? 5 key points

The Politics of Evidence Based Policymaking:3 messages

The politics of evidence-based best practice: 4 messages

The politics of implementing evidence-based policies

There are more posts like this on my EBPM page

I am also guest editing a series of articles for the Open Access journal Palgrave Communications on the ‘politics of evidence-based policymaking’ and we are inviting submissions throughout 2017.

There are more details on that series here.

And finally ..

… if you’d like to read about the policy theories underpinning these arguments, see Key policy theories and concepts in 1000 words and 500 words.

 

 

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

Long read for Political Studies Association annual conference 2017 panel Rethinking Impact: Narratives of Research-Policy Relations. There is a paper too, but I’ve hidden it in the text like an Easter Egg hunt.

I’ve watched a lot of film and TV dramas over the decades. Many have the same basic theme, characters, and moral:

  1. There is a villain getting away with something, such as cheating at sport or trying to evict people to make money on a property deal.
  2. There are some characters who complain that life is unfair and there’s nothing they can do about it.
  3. A hero emerges to inspire the other characters to act as a team/ fight the system and win the day. Think of a range from Wyldstyle to Michael Corleone.

For many scientists right now, the villains are people like Trump or Farage, Trump’s election and Brexit symbolise an unfairness on a grand scale, and there’s little they can do about it in a ‘post-truth’ era in which people have had enough of facts and experts. Or, when people try to mobilise, they are unsure about what to do or how far they are willing to go to win the day.

These issues are playing out in different ways, from the March for Science to the conferences informing debates on modern principles of government-science advice (see INGSA). Yet, the basic question is the same when scientists are trying to re-establish a particular role for science in the world: can you present science as (a) a universal principle and (b) unequivocal resource for good, producing (c) evidence so pure that it speaks for itself, regardless of (d) the context in which specific forms of scientific evidence are produced and used?

Of course not. Instead, we are trying to privilege the role of science and scientific evidence in politics and policymaking without always acknowledging that these activities are political acts:

(a) selling scientific values rather than self-evidence truths, and

(b) using particular values to cement the status of particular groups at the expense of others, either within the scientific profession (in which some disciplines and social groups win systematically) or within society (in which scientific experts generally enjoy privileged positions in policymaking arenas).

Politics is about exercising power to win disputes, from visible acts to win ‘key choices’, to less visible acts to keep issues off agendas and reinforce the attitudes and behaviours that systematically benefit some groups at the expense of others.

To deny this link between science, politics and power – in the name of ‘science’ – is (a) silly, and (b) not scientific, since there is a wealth of policy science out there which highlights this relationship.

Instead, academic and working scientists should make better use of their political-thinking-time to consider this basic dilemma regarding political engagement: how far are you willing to go to make an impact and get what you want?  Here are three examples.

  1. How energetically should you give science advice?

My impression is that most scientists feel most comfortable with the unfortunate idea of separating facts from values (rejected by Douglas), and living life as ‘honest brokers’ rather than ‘issue advocates’ (a pursuit described by Pielke and critiqued by Jasanoff). For me, this is generally a cop-out since it puts the responsibility on politicians to understand the implications of scientific evidence, as if they were self-evident, rather than on scientists to explain the significance in a language familiar to their audience.

On the other hand, the alternative is not really clear. ‘Getting your hands dirty’, to maximise the uptake of evidence in politics, is a great metaphor but a hopeless blueprint, especially when you, as part of a notional ‘scientific community’, face trade-offs between doing what you think is the right thing and getting what you want.

There are 101 examples of these individual choices that make up one big engagement dilemmas. One of my favourite examples from table 1 is as follows:

One argument stated frequently is that, to be effective in policy, you should put forward scientists with a particular background trusted by policymakers: white men in their 50s with international reputations and strong networks in their scientific field. This way, they resemble the profile of key policymakers who tend to trust people already familiar to them. Another is that we should widen out science and science advice, investing in a new and diverse generation of science-policy specialists, to address the charge that science is an elite endeavour contributing to inequalities.

  1. How far should you go to ensure that the ‘best’ scientific evidence underpins policy?

Kathryn Oliver and I identify the dilemmas that arise when principles of evidence-production meet (a) principles of governance and (b) real world policymaking. Should scientists learn how to be manipulative, to combine evidence and emotional appeals to win the day? Should they reject other forms of knowledge, and particular forms of governance if the think they get in the way of the use of the best evidence in policymaking?

Cairney Oliver 2017 table 1

  1. Is it OK to use psychological insights to manipulate policymakers?

Richard Kwiatkowski and I mostly discuss how to be manipulative if you make that leap. Or, to put it less dramatically, how to identify relevant insights from psychology, apply them to policymaking, and decide how best to respond. Here, we propose five heuristics for engagement:

  1. developing heuristics to respond positively to ‘irrational’ policymaking
  2. tailoring framing strategies to policymaker bias
  3. identifying the right time to influence individuals and processes
  4. adapting to real-world (dysfunctional) organisations rather than waiting for an orderly process to appear, and
  5. recognising that the biases we ascribe to policymakers are present in ourselves and our own groups

Then there is the impact agenda, which describes something very different

I say these things to link to our PSA panel, in which Christina Boswell and Katherine Smith sum up (in their abstract) the difference between the ways in which we are expected to demonstrate academic impact, and the practices that might actually produce real impact:

Political scientists are increasingly exhorted to ensure their research has policy ‘impact’, most notably in the form of REF impact case studies, and ‘pathways to impact’ plans in ESRC funding. Yet the assumptions underpinning these frameworks are frequently problematic. Notions of ‘impact’, ‘engagement’ and ‘knowledge exchange’ are typically premised on simplistic and linear models of the policy process, according to which policy-makers are keen to ‘utilise’ expertise to produce more effective policy interventions”.

I then sum up the same thing but with different words in my abstract:

“The impact agenda prompts strategies which reflect the science literature on ‘barriers’ between evidence and policy: produce more accessible reports, find the right time to engage, encourage academic-practitioner workshops, and hope that policymakers have the skills to understand and motive to respond to your evidence. Such strategies are built on the idea that scientists serve to reduce policymaker uncertainty, with a linear connection between evidence and policy. Yet, the literature informed by policy theory suggests that successful actors combine evidence and persuasion to reduce ambiguity, particularly when they know where the ‘action’ is within complex policymaking systems”.

The implications for the impact agenda are interesting, because there is a big difference between (a) the fairly banal ways in which we might make it easier for policymakers to see our work, and (b) the more exciting and sinister-looking ways in which we might make more persuasive cases. Yet, our incentive remains to produce the research and play it safe, producing examples of ‘impact’ that, on the whole, seem more reportable than remarkable.

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

cairney-southampton-evidence-win-the-dayPolitics has a profound influence on the use of evidence in policy, but we need to look ‘beyond the headlines’ for a sense of perspective on its impact.

It is tempting for scientists to identify the pathological effect of politics on policymaking, particularly after high profile events such as the ‘Brexit’ vote in the UK and the election of Donald Trump as US President. We have allegedly entered an era of ‘post-truth politics’ in which ideology and emotion trumps evidence and expertise (a story told many times at events like this), particularly when issues are salient.

Yet, most policy is processed out of this public spotlight, because the flip side of high attention to one issue is minimal attention to most others. Science has a crucial role in this more humdrum day-to-day business of policymaking which is far more important than visible. Indeed, this lack of public visibility can help many actors secure a privileged position in the policy process (and further exclude citizens).

In some cases, experts are consulted routinely. There is often a ‘logic’ of consultation with the ‘usual suspects’, including the actors most able to provide evidence-informed advice. In others, scientific evidence is often so taken for granted that it is part of the language in which policymakers identify problems and solutions.

In that context, we need better explanations of an ‘evidence-policy’ gap than the pathologies of politics and egregious biases of politicians.

To understand this process, and appearance of contradiction between excluded versus privileged experts, consider the role of evidence in politics and policymaking from three different perspectives.

The perspective of scientists involved primarily in the supply of evidence

Scientists produce high quality evidence only for politicians often ignore it or, even worse, distort its message to support their ideologically-driven policies. If they expect ‘evidence-based policymaking’ they soon become disenchanted and conclude that ‘policy-based evidence’ is more likely. This perspective has long been expressed in scientific journals and commentaries, but has taken on new significance following ‘Brexit’ and Trump.

The perspective of elected politicians

Elected politicians are involved primarily in managing government and maximising public and organisational support for policies. So, scientific evidence is one piece of a large puzzle. They may begin with a manifesto for government and, if elected, feel an obligation to carry it out. Evidence may play a part in that process but the search for evidence on policy solutions is not necessarily prompted by evidence of policy problems.

Further, ‘evidence based policy’ is one of many governance principles that politicians should feel the need to juggle. For example, in Westminster systems, ministers may try to delegate policymaking to foster ‘localism’ and/ or pragmatic policymaking, but also intervene to appear to be in control of policy, to foster a sense of accountability built on an electoral imperative. The likely mix of delegation and intervention seems almost impossible to predict, and this dynamic has a knock-on effect for evidence-informed policy. In some cases, central governments roll out the same basic policy intervention and limit local discretion; in others, it identifies broad outcomes and invites other bodies to gather evidence on how best to meet them. These differences in approach can have profound consequences on the models of evidence-informed policy available to us (see the example of Scottish policymaking).

Political science and policy studies provide a third perspective

Policy theories help us identify the relationship between evidence and policy by showing that a modern focus on ‘evidence-based policymaking’ (EBPM) is one of many versions of the same fairy tale – about ‘rational’ policymaking – that have developed in the post-war period. We talk about ‘bounded rationality’ to identify key ways in which policymakers or organisations could not achieve ‘comprehensive rationality’:

  1. They cannot separate values and facts.
  2. They have multiple, often unclear, objectives which are difficult to rank in any meaningful way.
  3. They have to use major shortcuts to gather a limited amount of information in a limited time.
  4. They can’t make policy from the ‘top down’ in a cycle of ordered and linear stages.

Limits to ‘rational’ policymaking: two shortcuts to make decisions

We can sum up the first three bullet points with one statement: policymakers have to try to evaluate and solve many problems without the ability to understand what they are, how they feel about them as a whole, and what effect their actions will have.

To do so, they use two shortcuts: ‘rational’, by pursuing clear goals and prioritizing certain kinds and sources of information, and ‘irrational’, by drawing on emotions, gut feelings, deeply held beliefs, habits, and the familiar to make decisions quickly.

Consequently, the focus of policy theories is on the links between evidence, persuasion, and framing issues to produce or reinforce a dominant way to define policy problems. Successful actors combine evidence and emotional appeals or simple stories to capture policymaker attention, and/ or help policymakers interpret information through the lens of their strongly-held beliefs.

Scientific evidence plays its part, but scientists often make the mistake of trying to bombard policymakers with evidence when they should be trying to (a) understand how policymakers understand problems, so that they can anticipate their demand for evidence, and (b) frame their evidence according to the cognitive biases of their audience.

Policymaking in ‘complex systems’ or multi-level policymaking environments

Policymaking takes place in less ordered, less hierarchical, and less predictable environment than suggested by the image of the policy cycle. Such environments are made up of:

  1. a wide range of actors (individuals and organisations) influencing policy at many levels of government
  2. a proliferation of rules and norms followed by different levels or types of government
  3. close relationships (‘networks’) between policymakers and powerful actors
  4. a tendency for certain beliefs or ‘paradigms’ to dominate discussion
  5. shifting policy conditions and events that can prompt policymaker attention to lurch at short notice.

These five properties – plus a ‘model of the individual’ built on a discussion of ‘bounded rationality’ – make up the building blocks of policy theories (many of which I summarise in 1000 Word posts). I say this partly to aid interdisciplinary conversation: of course, each theory has its own literature and jargon, and it is difficult to compare and combine their insights, but if you are trained in a different discipline it’s unfair to ask you devote years of your life to studying policy theory to end up at this point.

To show that policy theories have a lot to offer, I have been trying to distil their collective insights into a handy guide – using this same basic format – that you can apply to a variety of different situations, from explaining painfully slow policy change in some areas but dramatic change in others, to highlighting ways in which you can respond effectively.

We can use this approach to help answer many kinds of questions. With my Southampton gig in mind, let’s use some examples from public health and prevention.

Why doesn’t evidence win the day in tobacco policy?

My colleagues and I try to explain why it takes so long for the evidence on smoking and health to have a proportionate impact on policy. Usually, at the back of my mind, is a public health professional audience trying to work out why policymakers don’t act quickly or effectively enough when presented with unequivocal scientific evidence. More recently, they wonder why there is such uneven implementation of a global agreement – the WHO Framework Convention on Tobacco Control – that almost every country in the world has signed.

We identify three conditions under which evidence will ‘win the day’:

  1. Actors are able to use scientific evidence to persuade policymakers to pay attention to, and shift their understanding of, policy problems. In leading countries, it took decades to command attention to the health effects of smoking, reframe tobacco primarily as a public health epidemic (not an economic good), and generate support for the most effective evidence-based solutions.
  2. The policy environment becomes conducive to policy change. A new and dominant frame helps give health departments (often in multiple venues) a greater role; health departments foster networks with public health and medical groups at the expense of the tobacco industry; and, they emphasise the socioeconomic conditions – reductions in smoking prevalence, opposition to tobacco control, and economic benefits to tobacco – supportive of tobacco control.
  3. Actors exploit ‘windows of opportunity’ successfully. A supportive frame and policy environment maximises the chances of high attention to a public health epidemic and provides the motive and opportunity of policymakers to select relatively restrictive policy instruments.

So, scientific evidence is a necessary but insufficient condition for major policy change. Key actors do not simply respond to new evidence: they use it as a resource to further their aims, to frame policy problems in ways that will generate policymaker attention, and underpin technically and politically feasible solutions that policymakers will have the motive and opportunity to select. This remains true even when the evidence seems unequivocal and when countries have signed up to an international agreement which commits them to major policy change. Such commitments can only be fulfilled over the long term, when actors help change the policy environment in which these decisions are made and implemented. So far, this change has not occurred in most countries (or, in other aspects of public health in the UK, such as alcohol policy).

Why doesn’t evidence win the day in prevention and early intervention policy?

UK and devolved governments draw on health and economic evidence to make a strong and highly visible commitment to preventive policymaking, in which the aim is to intervene earlier in people’s lives to improve wellbeing and reduce socioeconomic inequalities and/ or public sector costs. This agenda has existed in one form or another for decades without the same signs of progress we now associate with areas like tobacco control. Indeed, the comparison is instructive, since prevention policy rarely meets the three conditions outlined above:

  1. Prevention is a highly ambiguous term and many actors make sense of it in many different ways. There is no equivalent to a major shift in problem definition for prevention policy as a whole, and little agreement on how to determine the most effective or cost-effective solutions.
  2. A supportive policy environment is far harder to identify. Prevention policy cross-cuts many policymaking venues at many levels of government, with little evidence of ‘ownership’ by key venues. Consequently, there are many overlapping rules on how and from whom to seek evidence. Networks are diffuse and hard to manage. There is no dominant way of thinking across government (although the Treasury’s ‘value for money’ focus is key currency across departments). There are many socioeconomic indicators of policy problems but little agreement on how to measure or which measures to privilege (particularly when predicting future outcomes).
  3. The ‘window of opportunity’ was to adopt a vague solution to an ambiguous policy problem, providing a limited sense of policy direction. There have been several ‘windows’ for more specific initiatives, but their links to an overarching policy agenda are unclear.

These limitations help explain slow progress in key areas. The absence of an unequivocal frame, backed strongly by key actors, leaves policy change vulnerable to successful opposition, especially in areas where early intervention has major implications for redistribution (taking from existing services to invest in others) and personal freedom (encouraging or obliging behavioural change). The vagueness and long term nature of policy aims – to solve problems that often seem intractable – makes them uncompetitive, and often undermined by more specific short term aims with a measurable pay-off (as when, for example, funding for public health loses out to funding to shore up hospital management). It is too easy to reframe existing policy solutions as preventive if the definition of prevention remains slippery, and too difficult to demonstrate the population-wide success of measures generally applied to high risk groups.

What happens when attitudes to two key principles – evidence based policy and localism – play out at the same time?

A lot of discussion of the politics of EBPM assumes that there is something akin to a scientific consensus on which policymakers do not act proportionately. Yet, in many areas – such as social policy and social work – there is great disagreement on how to generate and evaluate the best evidence. Broadly speaking, a hierarchy of evidence built on ‘evidence based medicine’ – which has randomised control trials and their systematic review at the top, and practitioner knowledge and service user feedback at the bottom – may be completely subverted by other academics and practitioners. This disagreement helps produce a spectrum of ways in which we might roll-out evidence based interventions, from an RCT-driven roll-out of the same basic intervention to a storytelling driven pursuit of tailored responses built primarily on governance principles (such as to co-produce policy with users).

At the same time, governments may be wrestling with their own governance principles, including EBPM but also regarding the most appropriate balance between centralism and localism.

If you put both concerns together, you have a variety of possible outcomes (and a temptation to ‘let a thousand flowers bloom’) and a set of competing options (outlined in table 1), all under the banner of ‘evidence based’ policymaking.

Table 1 Three ideal types EBBP

What happens when a small amount of evidence goes a very long way?

So, even if you imagine a perfectly sincere policymaker committed to EBPM, you’d still not be quite sure what they took it to mean in practice. If you assume this commitment is a bit less sincere, and you add in the need to act quickly to use the available evidence and satisfy your electoral audience, you get all sorts of responses based in some part on a reference to evidence.

One fascinating case is of the UK Government’s ‘troubled families’ programme which combined bits and pieces of evidence with ideology and a Westminster-style-accountability imperative, to produce:

  • The argument that the London riots were caused by family breakdown and bad parenting.
  • The use of proxy measures to identify the most troubled families
  • The use of superficial performance management to justify notionally extra expenditure for local authorities
  • The use of evidence in a problematic way, from exaggerating the success of existing ‘family intervention projects’ to sensationalising neuroscientific images related to brain development in deprived children …

normal brain

…but also

In other words, some governments feel the need to dress up their evidence-informed policies in a language appropriate to Westminster politics. Unless we understand this language, and the incentives for elected policymakers to use it, we will fail to understand how to act effectively to influence those policymakers.

What can you do to maximise the use of evidence?

When you ask the generic question you can generate a set of transferable strategies to engage in policymaking:

how-to-be-heard

ebpm-5-things-to-do

Yet, as these case studies of public health and social policy suggest, the question lacks sufficient meaning when applied to real world settings. Would you expect the advice that I give to (primarily) natural scientists (primarily in the US) to be identical to advice for social scientists in specific fields (in, say, the UK)?

No, you’d expect me to end with a call for more research! See for example this special issue in which many scholars from many disciplines suggest insights on how to maximise the use of evidence in policy.

Palgrave C special

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Filed under Evidence Based Policymaking (EBPM), Prevention policy, Public health, public policy, tobacco, tobacco policy

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

I was interviewed in Science, on the topic of evidence-based policymaking, and we discussed some top tips for people seeking to maximise the use of evidence in a complex policy process (or, perhaps, feel less dispirited about the lack of EBPM in many cases). If it sparks your interest, I have some other work on this topic:

I am editing a series of forthcoming articles on maximising the use of scientific evidence in policy, and the idea is that health and environmental scientists can learn from many other disciplines about how to, for example, anticipate policymaker psychology, find the right policymaking venue, understand its rules and ‘currency’ (the language people use, to reflect dominant ways of thinking about problems), and tell effective stories to the right people.

Palgrave C special

I have also completed a book, some journal articles (PAR, E&P), and some blog posts on the ‘politics of evidence-based policymaking’.

Pivot cover

Two posts appear in the Guardian political science blog (me, me and Kathryn Oliver).

One post, for practitioners, has ‘5 things you need to know’, and it links to presentations on the same theme to different audiences (Scotland, US, EU).

ebpm-5-things-to-do

In this post, I’m trying to think through in more detail what we do with such insights.

The insights I describe come from policy theory, and I have produced 25 posts which introduce each of them in 1000 words (or, if you are super busy, 500 words). For example, the Science interview mentions a spirograph of many cycles, which is a reference to the idea of a policy cycle. Also look out for the 1000-word posts on framing and narrative and think about how they relate to the use of storytelling in policy.

If you like what you see, and want to see more, have a look at my general list of offerings (home page) or list of books and articles with links to theirs PDFs (CV).

how-to-be-heard

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

We all want ‘evidence based policy making’ but how do we do it?

Here are some notes for my talk to the Scottish Government on Thursday as part of its ‘inaugural ‘evidence in policy week’. The advertised abstract is as follows:

A key aim in government is to produce ‘evidence based’ (or ‘informed’) policy and policymaking, but it is easier said than done. It involves two key choices about (1) what evidence counts and how you should gather it, and (2) the extent to which central governments should encourage subnational policymakers to act on that evidence. Ideally, the principles we use to decide on the best evidence should be consistent with the governance principles we adopt to use evidence to make policy, but what happens when they seem to collide? Cairney provides three main ways in which to combine evidence and governance-based principles to help clarify those choices.

I plan to use the same basic structure of the talks I gave to the OSF (New York) and EUI-EP (Florence) in which I argue that every aspect of ‘evidence based policy making’ is riddled with the necessity to make political choices (even when we define EBPM):

ebpm-5-things-to-do

I’ll then ‘zoom in’ on points 4 and 5 regarding the relationship between EBPM and governance principles. They are going to videotape the whole discussion to use for internal discussions, but I can post the initial talk here when it becomes available. Please don’t expect a TED talk (especially the E part of TED).

EBPM and good governance principles

The Scottish Government has a reputation for taking certain governance principles seriously, to promote high stakeholder ‘ownership’ and ‘localism’ on policy, and produce the image of a:

  1. Consensual consultation style in which it works closely with interest groups, public bodies, local government organisations, voluntary sector and professional bodies, and unions when making policy.
  2. Trust-based implementation style indicating a relative ability or willingness to devolve the delivery of policy to public bodies, including local authorities, in a meaningful way

Many aspects of this image were cultivated by former Permanent Secretaries: Sir John Elvidge described a ‘Scottish Model’ focused on joined-up government and outcomes-based approaches to policymaking and delivery, and Sir Peter Housden labelled the ‘Scottish Approach to Policymaking’ (SATP) as an alternative to the UK’s command-and-control model of government, focusing on the ‘co-production’ of policy with local communities and citizens.

The ‘Scottish Approach’ has implications for evidence based policy making

Note the major implication for our definition of EBPM. One possible definition, derived from ‘evidence based medicine’, refers to a hierarchy of evidence in which randomised control trials and their systematic review are at the top, while expertise, professional experience and service user feedback are close to the bottom. An uncompromising use of RCTs in policy requires that we maintain a uniform model, with the same basic intervention adopted and rolled out within many areas. The focus is on identifying an intervention’s ‘active ingredient’, applying the correct dosage, and evaluating its success continuously.

This approach seems to challenge the commitment to localism and ‘co-production’.

At the other end of the spectrum is a storytelling approach to the use of evidence in policy. In this case, we begin with key governance principles – such as valuing the ‘assets’ of individuals and communities – and inviting people to help make and deliver policy. Practitioners and service users share stories of their experiences and invite others to learn from them. There is no model of delivery and no ‘active ingredient’.

This approach seems to challenge the commitment to ‘evidence based policy’

The Goldilocks approach to evidence based policy making: the improvement method

We can understand the Scottish Government’s often-preferred method in that context. It has made a commitment to:

Service performance and improvement underpinned by data, evidence and the application of improvement methodologies

So, policymakers use many sources of evidence to identify promising, make broad recommendations to practitioners about the outcomes they seek, and they train practitioners in the improvement method (a form of continuous learning summed up by a ‘Plan-Do-Study-Act’ cycle).

Table 1 Three ideal types EBBP

This approach appears to offer the best of both worlds; just the right mix of central direction and local discretion, with the promise of combining well-established evidence from sources including RCTs with evidence from local experimentation and experience.

Four unresolved issues in decentralised evidence-based policy making

Not surprisingly, our story does not end there. I think there are four unresolved issues in this process:

  1. The Scottish Government often indicates a preference for improvement methods but actually supports all three of the methods I describe. This might reflect an explicit decision to ‘let a thousand flowers bloom’ or the inability to establish a favoured approach.
  2. There is not a single way of understanding ‘improvement methodology’. I describe something akin to a localist model here, but other people describe a far more research-led and centrally coordinated process.
  3. Anecdotally, I hear regularly that key stakeholders do not like the improvement method. One could interpret this as a temporary problem, before people really get it and it starts to work, or a fundamental difference between some people in government and many of the local stakeholders so important to the ‘Scottish approach’.

4. The spectre of democratic accountability and the politics of EBPM

The fourth unresolved issue is the biggest: it’s difficult to know how this approach connects with the most important reference in Scottish politics: the need to maintain Westminster-style democratic accountability, through periodic elections and more regular reports by ministers to the Scottish Parliament. This requires a strong sense of central government and ministerial control – if you know who is in charge, you know who to hold to account or reward or punish in the next election.

In principle, the ‘Scottish approach’ provides a way to bring together key aims into a single narrative. An open and accessible consultation style maximises the gathering of information and advice and fosters group ownership. A national strategic framework, with cross-cutting aims, reduces departmental silos and balances an image of democratic accountability with the pursuit of administrative devolution, through partnership agreements with local authorities, the formation of community planning partnerships, and the encouragement of community and user-driven design of public services. The formation of relationships with public bodies and other organisations delivering services, based on trust, fosters the production of common aims across the public sector, and reduces the need for top-down policymaking. An outcomes-focus provides space for evidence-based and continuous learning about what works.

In practice, a government often needs to appear to take quick and decisive action from the centre, demonstrate policy progress and its role in that progress, and intervene when things go wrong. So, alongside localism it maintains a legislative, financial, and performance management framework which limits localism.

How far do you go to ensure EBPM?

So, when I describe the ‘5 things to do’, usually the fifth element is about how far scientists may want to go, to insist on one model of EBPM when it has the potential to contradict important governance principles relating to consultation and localism. For a central government, the question is starker:

Do you have much choice about your model of EBPM when the democratic imperative is so striking?

I’ll leave it there on a cliff hanger, since these are largely questions to prompt discussion in specific workshops. If you can’t attend, there is further reading on the EBPM and EVIDENCE tabs on this blog, and specific papers on the Scottish dimension

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

Paul Cairney, Siabhainn Russell and Emily St Denny (2016) “The ‘Scottish approach’ to policy and policymaking: what issues are territorial and what are universal?” Policy and Politics, 44, 3, 333-50

The politics of evidence-based best practice: 4 messages

 

 

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Filed under ESRC Scottish Centre for Constitutional Change, Evidence Based Policymaking (EBPM), public policy, Scottish politics, Storytelling