Tag Archives: Evidence-based medicine

Why don’t policymakers listen to your evidence?

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

I tend to provide three main answers.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Reading

The politics of evidence-based policymaking

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

Images of the policy process

How to communicate effectively with policymakers

Forthcoming special issue in Policy and Politics called ‘Practical lessons from policy theories’, which includes my discussion of how to be a ‘policy entrepreneur’.

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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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A 5-step strategy to make evidence count

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

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

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

Step 1. Respect the positive role of politics

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

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

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

Step 2. Reject simple models of evidence-based policymaking

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

cycle

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

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

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

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

Step 3. Tell a simple story about your evidence

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

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

how-to-be-heard

Step 4.  Tailor your story to many audiences

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

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

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

Table 1 Three ideal types EBBP

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

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

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

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

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

If you prefer a 3-step take home message:

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

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

Powerpoint Paul Cairney @ GES GSRS 2017

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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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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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