The future of public health policymaking after COVID-19: lessons from Health in All Policies

Behold Paul’s attempt to make our faces the same size

Paul Cairney, Emily St Denny, Heather Mitchell 

This post summarises new research on the health equity strategy Health in All Policies. As our previous post suggests, it is common to hope that a major event will create a ‘window of opportunity’ for such strategies to flourish, but the current COVID-19 experience suggests otherwise. If so, what do HIAP studies tell us about how to respond, and do they offer any hope for future strategies? The full report is on Open Research Europe, accompanied by a brief interview on its contribution to the Horizon 2020 project – IMAJINE – on spatial justice.

COVID-19 should have prompted governments to treat health improvement as fundamental to public policy

Many had made strong rhetorical commitments to public health strategies focused on preventing a pandemic of non-communicable diseases (NCDs). To do so, they would address the ‘social determinants’ of health and health inequalities, defined by the WHO as ‘the unfair and avoidable differences in health status’ that are ‘shaped by the distribution of money, power and resources’ and ‘the conditions in which people are born, grow, live, work and age’.

COVID-19 reinforces the impact of the social determinants of health. Health inequalities result from factors such as income and social and environmental conditions, which influence people’s ability to protect and improve their health. COVID-19 had a visibly disproportionate impact on people with (a) underlying health conditions associated with NCDs, and (b) less ability to live and work safely.

Yet, the opposite happened. The COVID-19 response side-lined health improvement

Health departments postponed health improvement strategies and moved resources to health protection.

This experience shows that the evidence does not speak for itself

The evidence on social determinants is clear to public health specialists, but the idea of social determinants is less well known or convincing to policymakers.

It also challenges the idea that the logic of health improvement is irresistible

Health in All Policies (HIAP) is the main vehicle for health improvement policymaking, underpinned by: a commitment to health equity by addressing the social determinants of health; the recognition that the most useful health policies are not controlled by health departments; the need for collaboration across (and outside) government; and, the search for high level political commitment to health improvement.

Its logic is undeniable to HIAP advocates, but not policymakers. A government’s public commitment to HIAP does not lead inevitably to the roll-out of a fully-formed HIAP model. There is a major gap between the idea of HIAP and its implementation. It is difficult to generate HIAP momentum, and it can be lost at any time.

Instead, we need to generate more realistic lessons from health improvement and promotion policy

However, most HIAP research does not provide these lessons. Most HIAP research combines:

1. functional logic (here is what we need)
2. programme logic (here is what we think we need to do to achieve it), and
3. hope.

Policy theory-informed empirical studies of policymaking could help produce a more realistic agenda, but very few HIAP studies seem to exploit their insights.

To that end, this review identifies lessons from studies of HIAP and policymaking

It summarises a systematic qualitative review of HIAP research. It includes 113 articles (2011-2020) that refer to policymaking theories or concepts while discussing HIAP.

We produced these conclusions from pre-COVID-19 studies of HIAP and policymaking, but our new policymaking context – and its ironic impact on HIAP – is impossible to ignore.

It suggests that HIAP advocates produced a 7-point playbook for the wrong game

The seven most common pieces of advice add up to a plausible but incomplete strategy:

1. adopt a HIAP model and toolkit
2. raise HIAP awareness and support in government
3. seek win-win solutions with partners
4. avoid the perception of ‘health imperialism’ when fostering intersectoral action
5. find HIAP policy champions and entrepreneurs
6. use HIAP to support the use of health impact assessments (HIAs)
7. challenge the traditional cost-benefit analysis approach to valuing HIAP.

Yet, two emerging pieces of advice highlight the limits to the current playbook and the search for its replacement:

1. treat HIAP as a continuous commitment to collaboration and health equity, not a uniform model; and,
2. address the contradictions between HIAP aims.

As a result, most country studies report a major, unexpected, and disappointing gap between HIAP commitment and actual outcomes

These general findings are apparent in almost all relevant studies. They stand out in the ‘best case’ examples where: (a) there is high political commitment and strategic action (such as South Australia), or (b) political and economic conditions are conducive to HIAP (such as Nordic countries).

These studies show that the HIAP playbook has unanticipated results, such as when the win-win strategy leads to  HIAP advocates giving ground but receiving little in return.

HIAP strategies to challenge the status quo are also overshadowed by more important factors, including (a) a far higher commitment to existing healthcare policies and the core business of government, and (b) state retrenchment. Additional studies of decentralised HIAP models find major gaps between (a) national strategic commitment (backed by national legislation) and (b) municipal government progress.

Some studies acknowledge the need to use policymaking research to produce new ways to encourage and evaluate HIAP success

Studies of South Australia situate HIAP in a complex policymaking system in which the link between policy activity and outcomes is not linear.  

Studies of Nordic HIAP show that a commitment to municipal responsibility and stakeholder collaboration rules out the adoption of a national uniform HIAP model.

However, most studies do not use policymaking research effectively or appropriately

Almost all HIAP studies only scratch the surface of policymaking research (while some try to synthesise its insights, but at the cost of clarity).

Most HIAP studies use policy theories to:

1. produce practical advice (such as to learn from ‘policy entrepreneurs’), or
2. supplement their programme logic (to describe what they think causes policy change and better health outcomes).

Most policy theories were not designed for this purpose.

Policymaking research helps primarily to explain the HIAP ‘implementation gap’

Its main lesson is that policy outcomes are beyond the control of policymakers and HIAP advocates. This explanation does not show how to close implementation gaps.

Its practical lessons come from critical reflection on dilemmas and politics, not the reinvention of a playbook

It prompts advocates to:

• Treat HIAP as a political project, not a technical exercise or puzzle to be solved.
• Re-examine the likely impact of a focus on intersectoral action and collaboration, to recognise the impact of imbalances of power and the logic of policy specialisation.
• Revisit the meaning-in-practice of the vague aims that they take for granted without explaining, such as co-production, policy learning, and organisational learning.
• Engage with key trade-offs, such as between a desire for uniform outcomes (to produce health equity) but acceptance of major variations in HIAP policy and policymaking.
• Avoid reinventing phrases or strategies when facing obstacles to health improvement.

We describe these points in more detail here:

Our Open Research Europe article (peer reviewed) The future of public health policymaking… (europa.eu)

Paul summarises the key points as part of a HIAP panel: Health in All Policies in times of COVID-19

ORE blog on the wider context of this work: forthcoming

The COVID-19 exams fiasco across the UK: why did policymaking go so wrong?

This post first appeared on the LSE British Politics and Policy blog, and it summarises our new article: Sean Kippin and Paul Cairney (2021) ‘The COVID-19 exams fiasco across the UK: four nations and two windows of opportunity’, British Politics, PDF & Annex. The focus on inequalities of attainment is part of the IMAJINE project on spatial justice and territorial inequalities.

In the summer of 2020, after cancelling exams, the UK and devolved governments sought teacher estimates on students’ grades, but supported an algorithm to standardise the results. When the results produced a public outcry over unfair consequences, they initially defended their decision but reverted quickly to teacher assessment. These experiences, argue Sean Kippin and Paul Cairney, highlight the confluence of events and choices in which an imperfect and rejected policy solution became a ‘lifeline’ for four beleaguered governments. 

In 2020, the UK and devolved governments performed a ‘U-turn’ on their COVID-19 school exams replacement policies. The experience was embarrassing for education ministers and damaging to students. There are significant differences between (and often within) the four nations in terms of the structure, timing, weight, and relationship between the different examinations. However, in general, the A-level (England, Northern Ireland, Wales) and Higher/ Advanced Higher (Scotland) examinations have similar policy implications, dictating entry to further and higher education, and influencing employment opportunities. The Priestley review, commissioned by the Scottish Government after their U-turn, described this as an ‘impossible task’.

Initially, each government defined the new policy problem in relation to the need to ‘credibly’ replicate the purpose of exams to allow students to progress to tertiary education or employment. All four quickly announced their intentions to allocate in some form grades to students, rather than replace the assessments with, for example, remote examinations. However, mindful of the long-term credibility of the examinations system and of ensuring fairness, each government opted to maintain the qualifications and seek a similar distribution of grades to previous years. A key consideration was that UK universities accept large numbers of students from across the UK.

One potential solution open to policymakers was to rely solely on teacher grading (CAG). CAGs are ‘based on a range of evidence including mock exams, non-exam assessment, homework assignments and any other record of student performance over the course of study’. Potential problems included the risk of high variation and discrepancies between different centres, the potential overload of the higher education system, and the tendency for teacher predicted grades to reward already privileged students and punish disabled, non-white, and economically deprived children.

A second option was to take CAGs as a starting point, then use an algorithm to produce ‘standardisation’, which was potentially attractive to each government as it allowed students to complete secondary education and to progress to the next level in similar ways to previous (and future) cohorts. Further, an emphasis on the technical nature of this standardisation, with qualifications agencies taking the lead in designing the process by which grades would be allocated, and opting not share the details of its algorithm were a key part of its (temporary) viability. Each government then made similar claims when defending the problem and selecting the solution. Yet this approach reduced both the debate on the unequal impact of this process on students, and the chance for other experts to examine if the algorithm would produce the desired effect. Policymakers in all four governments assured students that the grading would be accurate and fair, with teacher discretion playing a large role in the calculation of grades.

To these governments, it appeared at first that they had found a fair and efficient (or at least defendable) way to allocate grades, and public opinion did not respond negatively to its announcement. However, these appearances proved to be profoundly deceptive and vanished on each day of each exam result. The Scottish national mood shifted so intensely that, after a few days, pursuing standardisation no longer seemed politically feasible. The intense criticism centred on the unequal level of reductions of grades after standardisation, rather than the unequal overall rise in grade performance after teacher assessment and standardisation (which advantaged poorer students).

Despite some recognition that similar problems were afoot elsewhere, this shift of problem definition did not happen in the rest of the UK until (a) their published exam results highlighted similar problems regarding the role of previous school performance on standardised results, and (b) the Scottish Government had already changed course. Upon the release of grades outside Scotland, it became clear that downgrades were also concentrated in more deprived areas. For instance, in Wales, 42% of students saw their A-Level results lowered from their Centre Assessed Grades, with the figure close to a third for Northern Ireland.

Each government thus faced similar choices between defending the original system by challenging the emerging consensus around its apparent unfairness; modifying the system by changing the appeal system; or abandoning it altogether and reverting to solely teacher assessed grades. Ultimately, all three governments followed the same path. Initially, they opted to defend their original policy choice. However, by 17 August, the UK, Welsh, and Northern education secretaries announced (separately) that examination grades would be based solely on CAGs – unless the standardisation process had generated a higher grade (students would receive whichever was highest).

Scotland’s initial experience was instructive to the rest of the UK and its example provided the UK government with a blueprint to follow (eventually). It began with a new policy choice – reverting to teacher assessed grades – sold as fairer to victims of the standardisation process. Once this precedent had been set, a different course for policymakers at the UK level became difficult to resist, particularly when faced with a similar backlash. The UK’s government’s decision in turn influenced the Welsh and Northern Irish governments.

In short, we can see that the particular ordering of choices created a cascading effect across the four governments which created initially one policy solution, before triggering a U-turn. This focus on order and timing should not be lost during the inevitable inquiries and reports on the examinations systems. The take-home message is to not ignore the policy process when evaluating the long-term effect of these policies. Focus on why the standardisation processes went wrong is welcome, but we should also focus on why the policymaking process malfunctioned, to produce a wildly inconsistent approach to the same policy choice in such a short space of time. Examining both aspects of this fiasco will be crucial to the grading process in 2021, given that governments will be seeking an alternative to exams for a second year.

__________________________

Note: the above draws on the authors’ published work in British Politics.

Policy Concepts in 1000 Words: Policy Change

Christopher M. Weible & Paul Cairney

Policy change is a central concern of policy research and practice. Some want to explain it. Some want to achieve it.

Explanation begins with the ‘what is policy?’ question, since we cannot observe something without defining it.  However, we soon find that: no single definition can capture all forms of policy change, the absence of policy change is often more important, and important changes can be found in the everyday application of rules and practices related to public policies.  Further, studies often focus on changes in public policies without a focus on societal outcomes or effects.

One pragmatic solution is to define public policies as decisions made by policymakers or policymaking venues such as legislatures, executives, regulatory agencies, courts, national and local governments (and, in some countries, citizen-led policy changes).  Focusing on this type of policy change, two major categories of insights unfold:

1. Patterns of Policy Change: incrementalism, punctuations, and drift

A focus on decisions suggests that most policymaking venues contribute primarily to incremental policy change, or often show little change from year to year but with the occasional punctuation of major policymaking activity.  This pattern reflects a frequent story about governments doing too much or nothing at all. The logic is that policymaking attention is always limited, so a focus on one issue in any policymaking venue requires minimal focus on others.  Then, when attention shifts, we see instances of major policy change as attempts to compensate (or overcompensate) for what was ignored for too long.

An additional focus on institutions highlights factors such as policy drift, to describe slow and small changes to policies, or to aspects of their design, that accumulate eventually and can have huge impacts on outcomes and society.  These drifts often happen outside the public eye or are overlooked as being negative but trivial.  For example, rising economic inequality in the US resulted from the slow accumulation of policies – related to labor unions, tax structures, and corporate governance – as well as globalization and labor-saving technologies.

2. Factors Associated with Policy Change

Many factors help us understand instances of policy change. We can separate them analytically (as below) but, in practice, they occur simultaneously or sequentially, and can reinforce or stifle each other.

Context

Context includes history, biophysical conditions, socio-economic conditions, culture, and basic institutional structures (such as a constitution).  For example, historical and geographic conditions are often viewed as funneling or constraining the type of policy decisions made by a government.

Events 

Policymaking venues are often described as being resistant to change or in a state of equilibrium of competing political forces.  As a result, one common explanation for change is a focusing event or shock.  Events by themselves don’t create policy change. Rather, they present an opportunity for people or coalitions to exploit.   Focusing events might include disasters or crises, tragic incidents, a terrorist attack, disruptive changes in technology, or more routine events such as elections. Events may have tangible qualities, but studies tend to highlight the ways in which people frame events to construct their meaning and implications for policy.

Public Opinion 

The relationship between public opinion and policy change is a difficult one to assess.  Some research shows that the preferences of the general public only matter when they coincide with the preferences of the elite or major interest groups.  Or, it matters only when the topic is salient and the public is paying attention. Little evidence suggests that public opinion matters when few are paying attention.  Others describe public opinion as setting the boundaries within which the government operates.

Learning

Learning is a process of updating understandings of the world in response to signals from the environment.  Learning is a political activity rather than simply a technical exercise in which people learn from teachers. Learning could involve becoming aware of the severity of a policy problem, evaluating outcomes to determine if a government intervention works, and learning to trust an opponent and reach compromise. For example, certain types of rules in a collaborative process can shape the ways in which individuals gain new knowledge and change their views about the scientific evidence informing a problem.

Diffusion of Ideas 

Sometimes governments learn from or transfer policies from other governments. For example, in collections of policymaking venues (such as US state governments or EU member states) it is common for one venue to adopt a policy and prompt this policy to spread across other venues in a process of diffusion.  There are many explanations for diffusion including learning, a response to competition, mimicking, and coercion. In each case, the explanation for policy change comes from an external impetus and an internal context.

Champions and Political Associations

All policy change is driven, to some extent, by individual or group agency.  Key players include public policy champions in the form of policy entrepreneurs or in groups of government and/or non-government entities in the form of coalitions, social movements, epistemic communities, and political parties.  In each case, individuals or organizations mobilize resources, capitalize on opportunities, and apply pressure to formulate and adopt public policies.

 

The presence of these factors does not always lead to policy change, and no single study can capture a full explanation of policy change. Instead, many quantitative studies focus on multiple instances of policy change and are often broad in geographic scope or spans of time, while many case study or qualitative studies focus intensely on a very particular instance of policy change. Both approaches are essential.

See also:

Policy in 500 Words: what is public policy and why does it matter?

Policy in 500 Words: how much does policy change?

Policy Concepts in 1000 Words: Policy change and measurement (podcast download)

Policy Concepts in 1000 Words: how do policy theories describe policy change?

 

 

Policy Analysis in 750 Words: how much impact can you expect from your analysis?

This post forms one part of the Policy Analysis in 750 words series overview.

Throughout this series you may notice three different conceptions about the scope of policy analysis:

1. ‘Ex ante’ (before the event) policy analysis. Focused primarily on defining a problem, and predicting the effect of solutions, to inform current choice (as described by Meltzer and Schwartz and Thissen and Walker).
2. ‘Ex post’ (after the event) policy analysis. Focused primarily on monitoring and evaluating that choice, perhaps to inform future choice (as described famously by Weiss).
3. Some combination of both, to treat policy analysis as a continuous (never-ending) process (as described by Dunn).

As usual, these are not hard-and-fast distinctions, but they help us clarify expectations in relation to different scenarios.

1. The impact of old-school ex ante policy analysis

Radin provides a valuable historical discussion of policymaking with the following elements:

• a small number of analysts, generally inside government (such as senior bureaucrats, scientific experts, and – in particular- economists),
• giving technical or factual advice,
• about policy formulation,
• to policymakers at the heart of government,
• on the assumption that policy problems would be solved via analysis and action.

This kind of image signals an expectation for high impact: policy analysts face low competition, enjoy a clearly defined and powerful audience, and their analysis is expected to feed directly into choice.

Radin goes on to describe a much different, modern policy environment: more competition, more analysts spread across and outside government, with a less obvious audience, and – even if there is a client – high uncertainty about where the analysis fits into the bigger picture.

Yet, the impetus to seek high and direct impact remains.

This combination of shifting conditions but unshifting hopes/ expectations helps explain a lot of the pragmatic forms of policy analysis you will see in this series, including:

• Keep it catchy, gather data efficiently, tailor your solutions to your audience, and tell a good story (Bardach)
• Speak with an audience in mind, highlight a well-defined problem and purpose, project authority, use the right form of communication, and focus on clarity, precision, conciseness, and credibility ( Smith)
• Address your client’s question, by their chosen deadline, in a clear and concise way that they can understand (and communicate to others) quickly (Weimer and Vining)
• Client-oriented advisors identify the beliefs of policymakers and anticipate the options worth researching (Mintrom)
• Identify your client’s resources and motivation, such as how they seek to use your analysis, the format of analysis they favour (make it ‘concise’ and ‘digestible’), their deadline, and their ability to make or influence the policies you might suggest (Meltzer and Schwartz).
• ‘Advise strategically’, to help a policymaker choose an effective solution within their political context (Thissen and Walker).
• Focus on producing ‘policy-relevant knowledge’ by adapting to the evidence-demands of policymakers and rejecting a naïve attachment to ‘facts speaking for themselves’ or ‘knowledge for its own sake’ (Dunn).

2. The impact of research and policy evaluation

Many of these recommendations are familiar to scientists and researchers, but generally in the context of far lower expectations about their likely impact, particularly if those expectations are informed by policy studies (compare Oliver & Cairney with Cairney & Oliver).

In that context, Weiss’ work is a key reference point. It gives us a menu of ways in which policymakers might use policy evaluation (and research evidence more widely):

• to inform solutions to a problem identified by policymakers
• as one of many sources of information used by policymakers, alongside ‘stakeholder’ advice and professional and service user experience
• as a resource used selectively by politicians, with entrenched positions, to bolster their case
• as a tool of government, to show it is acting (by setting up a scientific study), or to measure how well policy is working
• as a source of ‘enlightenment’, shaping how people think over the long term (compare with this discussion of ‘evidence based policy’ versus ‘policy based evidence’).

In other words, researchers may have a role, but they struggle (a) to navigate the politics of policy analysis, (b) find the right time to act, and (c) to secure attention, in competition with many other policy actors.

3. The potential for a form of continuous impact

Dunn suggests that the idea of ‘ex ante’ policy analysis is misleading, since policymaking is continuous, and evaluations of past choices inform current choices. Think of each policy analysis steps as ‘interdependent’, in which new knowledge to inform one step also informs the other four. For example, routine monitoring helps identify compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly, and if we can make a causal link between the policy solutions and outcomes. Its impact is often better seen as background information with intermittent impact.

Key conclusions to bear in mind

1. The demand for information from policy analysts may be disproportionately high when policymakers pay attention to a problem, and disproportionately low when they feel that they have addressed it.
2. Common advice for policy analysts and researchers often looks very similar: keep it concise, tailor it to your audience, make evidence ‘policy relevant’, and give advice (don’t sit on the fence). However, unless researchers are prepared to act quickly, to gather data efficiently (not comprehensively), to meet a tight brief for a client, they are not really in the impact business described by most policy analysis texts.
3. A lot of routine, continuous, impact tends to occur out of the public spotlight, based on rules and expectations that most policy actors take for granted.

Further reading

See the Policy Analysis in 750 words series overview to continue reading on policy analysis.

See the ‘evidence-based policymaking’ page to continue reading on research impact.

Bristol powerpoint: Paul Cairney Bristol EBPM January 2020

Policy Analysis in 750 Words: what you need as an analyst versus policymaking reality

This post forms one part of the Policy Analysis in 750 words series overview. Note for the eagle eyed: you are not about to experience déjà vu. I’m just using the same introduction.

When describing ‘the policy sciences’, Lasswell distinguishes between:

1. ‘knowledge of the policy process’, to foster policy studies (the analysis of policy)
2. ‘knowledge in the process’, to foster policy analysis (analysis for policy)

The lines between each approach are blurry, and each element makes less sense without the other. However, the distinction is crucial to help us overcome the major confusion associated with this question:

Does policymaking proceed through a series of stages?

The short answer is no.

The longer answer is that you can find about 40 blog posts (of 500 and 1000 words) which compare (a) a stage-based model called the policy cycle, and (b) the many, many policy concepts and theories that describe a far messier collection of policy processes.

In a nutshell, most policy theorists reject this image because it oversimplifies a complex policymaking system. The image provides a great way to introduce policy studies, and serves a political purpose, but it does more harm than good:

1. Descriptively, it is profoundly inaccurate (unless you imagine thousands of policy cycles interacting with each other to produce less orderly behaviour and less predictable outputs).
2. Prescriptively, it gives you rotten advice about the nature of your policymaking task (for more on these points, see this chapter, article, article, and series).

Why does the stages/ policy cycle image persist? Two relevant explanations

 

1. It arose from a misunderstanding in policy studies

In another nutshell, Chris Weible and I argue (in a secret paper) that the stages approach represents a good idea gone wrong:

• If you trace it back to its origins, you will find Lasswell’s description of decision functions: intelligence, recommendation, prescription, invocation, application, appraisal and termination.
• These functions correspond reasonably well to a policy cycle’s stages: agenda setting, formulation, legitimation, implementation, evaluation, and maintenance, succession or termination.
• However, Lasswell was imagining functional requirements, while the cycle seems to describe actual stages.

In other words, if you take Lasswell’s list of what policy analysts/ policymakers need to do, multiple it by the number of actors (spread across many organisations or venues) trying to do it, then you get the multi-centric policy processes described by modern theories. If, instead, you strip all that activity down into a single cycle, you get the wrong idea.

2. It is a functional requirement of policy analysis

This description should seem familiar, because the classic policy analysis texts appear to describe a similar series of required steps, such as:

1. define the problem
2. identify potential solutions
3. choose the criteria to compare them
4. evaluate them in relation to their predicted outcomes
5. recommend a solution
6. monitor its effects
7. evaluate past policy to inform current policy.

However, these texts also provide a heavy dose of caution about your ability to perform these steps (compare Bardach, Dunn, Meltzer and Schwartz, Mintrom, Thissen and Walker, Weimer and Vining)

In addition, studies of policy analysis in action suggest that:

• an individual analyst’s need for simple steps, to turn policymaking complexity into useful heuristics and pragmatic strategies,

should not be confused with

• what actually happens when many policy analysts, influencers, and policymakers interact in policy processes (see Radin, and Brans, Geva-May, and Howlett).

What you need versus what you can expect

Overall, this discussion of policy studies and policy analysis reminds us of a major difference between:

1. Functional requirements. What you need from policymaking systems, to (a) manage your task (the 5-8 step policy analysis) and (b) understand and engage in policy processes (the simple policy cycle).
2. Actual processes and outcomes. What policy concepts and theories tell us about bounded rationality (which limit the comprehensiveness of your analysis) and policymaking complexity (which undermines your understanding and engagement in policy processes).

Of course, I am not about to provide you with a solution to these problems.

Still, this discussion should help you worry a little bit less about the circular arguments you will find in key texts: here are some simple policy analysis steps, but policymaking is not as ‘rational’ as the steps suggest, but (unless you can think of an alternative) there is still value in the steps, and so on.

See also:

The New Policy Sciences

Policy Analysis in 750 words: William Dunn (2017) Public Policy Analysis

Please see the Policy Analysis in 750 words series overview before reading the summary. This book is a whopper, with almost 500 pages and 101 (excellent) discussions of methods, so 800 words over budget seems OK to me. If you disagree, just read every second word.  By the time you reach the cat hanging in there baby you are about 300 (150) words away from the end.

William Dunn (2017) Public Policy Analysis 6^th Ed. (Routledge)

‘Policy analysis is a process of multidisciplinary inquiry aiming at the creation, critical assessment, and communication of policy-relevant knowledge … to solve practical problems … Its practitioners are free to choose among a range of scientific methods, qualitative as well as quantitative, and philosophies of science, so long as these yield reliable knowledge’ (Dunn, 2017: 2-3).

Dunn (2017: 4) describes policy analysis as pragmatic and eclectic. It involves synthesising policy relevant (‘usable’) knowledge, and combining it with experience and ‘practical wisdom’, to help solve problems with analysis that people can trust.

This exercise is ‘descriptive’, to define problems, and ‘normative’, to decide how the world should be and how solutions get us there (as opposed to policy studies/ research seeking primarily to explain what happens).

Dunn contrasts the ‘art and craft’ of policy analysts with other practices, including:

1. The idea of ‘best practice’ characterised by 5-step plans.

• In practice, analysis is influenced by: the cognitive shortcuts that analysts use to gather information; the role they perform in an organisation; the time constraints and incentive structures in organisations and political systems; the expectations and standards of their profession; and, the need to work with teams consisting of many professions/ disciplines (2017: 15-6)
• The cost (in terms of time and resources) of conducting multiple research and analytical methods is high, and highly constrained in political environments (2017: 17-8; compare with Lindblom)

2. The too-narrow idea of evidence-based policymaking

• The naïve attachment to ‘facts speak for themselves’ or ‘knowledge for its own sake’ undermines a researcher’s ability to adapt well to the evidence-demands of policymakers (2017: 68; 4 compare with Why don’t policymakers listen to your evidence?).

To produce ‘policy-relevant knowledge’ requires us to ask five questions before (Qs1-3) and after (Qs4-5) policy intervention (2017: 5-7; 54-6):

1. What is the policy problem to be solved?

• For example, identify its severity, urgency, cause, and our ability to solve it.
• Don’t define the wrong problem, such as by oversimplifying or defining it with insufficient knowledge.
• Key aspects of problems including ‘interdependency’ (each problem is inseparable from a host of others, and all problems may be greater than the sum of their parts), ‘subjectivity’ and ‘artificiality’ (people define problems), ‘instability’ (problems change rather than being solved), and ‘hierarchy’ (which level or type of government is responsible) (2017: 70; 75).
• Problems vary in terms of how many relevant policymakers are involved, how many solutions are on the agenda, the level of value conflict, and the unpredictability of outcomes (high levels suggest ‘wicked’ problems, and low levels ‘tame’) (2017: 75)
• ‘Problem-structuring methods’ are crucial, to: compare ways to define or interpret a problem, and ward against making too many assumptions about its nature and cause; produce models of cause-and-effect; and make a problem seem solve-able, such as by placing boundaries on its coverage. These methods foster creativity, which is useful when issues seem new and ambiguous, or new solutions are in demand (2017: 54; 69; 77; 81-107).
• Problem definition draws on evidence, but is primarily the exercise of power to reduce ambiguity through argumentation, such as when defining poverty as the fault of the poor, the elite, the government, or social structures (2017: 79; see Stone).

2. What effect will each potential policy solution have?

• Many ‘forecasting’ methods can help provide ‘plausible’ predictions about the future effects of current/ alternative policies (Chapter 4 contains a huge number of methods).
• ‘Creativity, insight, and the use of tacit knowledge’ may also be helpful (2017: 55).
• However, even the most-effective expert/ theory-based methods to extrapolate from the past are flawed, and it is important to communicate levels of uncertainty (2017: 118-23; see Spiegelhalter).

3. Which solutions should we choose, and why?

• ‘Prescription’ methods help provide a consistent way to compare each potential solution, in terms of its feasibility and predicted outcome, rather than decide too quickly that one is superior (2017: 55; 190-2; 220-42).
• They help to combine (a) an estimate of each policy alternative’s outcome with (b) a normative assessment.
• Normative assessments are based on values such as ‘equality, efficiency, security, democracy, enlightenment’ and beliefs about the preferable balance between state, communal, and market/ individual solutions (2017: 6; 205 see Weimer & Vining, Meltzer & Schwartz, and Stone on the meaning of these values).
• For example, cost benefit analysis (CBA) is an established – but problematic – economics method based on finding one metric – such as a $ value – to predict and compare outcomes (2017: 209-17; compare Weimer & Vining, Meltzer & Schwartz, and Stone)
• Cost effectiveness analysis uses a $ value for costs, but compared with other units of measurement for benefits (such as outputs per $) (2017: 217-9)
• Although such methods help us combine information and values to compare choices, note the inescapable role of power to decide whose values (and which outcomes, affecting whom) matter (2017: 204)

4. What were the policy outcomes?

• ‘Monitoring’ methods help identify (say): levels of compliance with regulations, if resources and services reach ‘target groups’, if money is spent correctly (such as on clearly defined ‘inputs’ such as public sector wages), and if we can make a causal link between the policy inputs/ activities/ outputs and outcomes (2017: 56; 251-5)
• Monitoring is crucial because it is so difficult to predict policy success, and unintended consequences are almost inevitable (2017: 250).
• However, the data gathered are usually no more than proxy indicators of outcomes. Further, the choice of indicators reflect what is available, ‘particular social values’, and ‘the political biases of analysts’ (2017: 262)
• The idea of ‘evidence based policy’ is linked strongly to the use of experiments and systematic review to identify causality (2017: 273-6; compare with trial-and-error learning in Gigerenzer, complexity theory, and Lindblom).

5. Did the policy solution work as intended? Did it improve policy outcomes?

• Although we frame policy interventions as ‘solutions’, few problems are ‘solved’. Instead, try to measure the outcomes and the contribution of your solution, and note that evaluations of success and ‘improvement’ are contested (2017: 57; 332-41).  
• Policy evaluation is not an objective process in which we can separate facts from values.
• Rather, values and beliefs are part of the criteria we use to gauge success (and even their meaning is contested – 2017: 322-32).
• We can gather facts about the policy process, and the impacts of policy on people, but this information has little meaning until we decide whose experiences matter.

Overall, the idea of ‘ex ante’ (forecasting) policy analysis is a little misleading, since policymaking is continuous, and evaluations of past choices inform current choices.

Policy analysis methods are ‘interdependent’, and ‘knowledge transformations’ describes the impact of knowledge regarding one question on the other four (2017: 7-13; contrast with Meltzer & Schwartz, Thissen & Walker).

Developing arguments and communicating effectively

Dunn (2017: 19-21; 348-54; 392) argues that ‘policy argumentation’ and the ‘communication of policy-relevant knowledge’ are central to policymaking’ (See Chapter 9 and Appendices 1-4 for advice on how to write briefs, memos, and executive summaries and prepare oral testimony).

He identifies seven elements of a ‘policy argument’ (2017: 19-21; 348-54), including:

• The claim itself, such as a description (size, cause) or evaluation (importance, urgency) of a problem, and prescription of a solution
• The things that support it (including reasoning, knowledge, authority)
• Incorporating the things that could undermine it (including any ‘qualifier’, the communication of uncertainty about current knowledge, and counter-arguments).

The key stages of communication (2017: 392-7; 405; 432) include:

1. ‘Analysis’, focusing on ‘technical quality’ (of the information and methods used to gather it), meeting client expectations, challenging the ‘status quo’, albeit while dealing with ‘political and organizational constraints’ and suggesting something that can actually be done.
2. ‘Documentation’, focusing on synthesising information from many sources, organising it into a coherent argument, translating from jargon or a technical language, simplifying, summarising, and producing user-friendly visuals.
3. ‘Utilization’, by making sure that (a) communications are tailored to the audience (its size, existing knowledge of policy and methods, attitude to analysts, and openness to challenge), and (b) the process is ‘interactive’ to help analysts and their audiences learn from each other.

 

 

Policy analysis and policy theory: systems thinking, evidence based policymaking, and policy cycles

Dunn (2017: 31-40) situates this discussion within a brief history of policy analysis, which culminated in new ways to express old ambitions, such as to:

1. Use ‘systems thinking’, to understand the interdependence between many elements in complex policymaking systems (see also socio-technical and socio-ecological systems).

• Note the huge difference between (a) policy analysis discussions of ‘systems thinking’ built on the hope that if we can understand them we can direct them, and (b) policy theory discussions that emphasise ‘emergence’ in the absence of central control (and presence of multi-centric policymaking).
• Also note that Dunn (2017: 73) describes policy problems – rather than policymaking – as complex systems. I’ll write another post (short, I promise) on the many different (and confusing) ways to use the language of complexity.

2. Promote ‘evidence based policy’, as the new way to describe an old desire for ‘technocratic’ policymaking that accentuates scientific evidence and downplays politics and values (see also 2017: 60-4).

In that context, see Dunn’s (47-52) discussion of comprehensive versus bounded rationality:

• Note the idea of ‘erotetic rationality’ in which people deal with their lack of knowledge of a complex world by giving up on the idea of certainty (accepting their ‘ignorance’), in favour of a continuous process of ‘questioning and answering’.
• This approach is a pragmatic response to the lack of order and predictability of policymaking systems, which limits the effectiveness of a rigid attachment to ‘rational’ 5 step policy analyses (compare with Meltzer & Schwartz).

Dunn (2017: 41-7) also provides an unusually useful discussion of the policy cycle. Rather than seeing it as a mythical series of orderly stages, Dunn highlights:

1. Lasswell’s original discussion of policymaking functions (or functional requirements of policy analysis, not actual stages to observe), including: ‘intelligence’ (gathering knowledge), ‘promotion’ (persuasion and argumentation while defining problems), ‘prescription’, ‘invocation’ and ‘application’ (to use authority to make sure that policy is made and carried out), and ‘appraisal’ (2017: 42-3).
2. The constant interaction between all notional ‘stages’ rather than a linear process: attention to a policy problem fluctuates, actors propose and adopt solutions continuously, actors are making policy (and feeding back on its success) as they implement, evaluation (of policy success) is not a single-shot document, and previous policies set the agenda for new policy (2017: 44-5).

In that context, it is no surprise that the impact of a single policy analyst is usually minimal (2017: 57). Sorry to break it to you. Hang in there, baby.

 

Can A Government Really Take Control Of Public Policy?

This post first appeared on the MIHE blog to help sell my book.

During elections, many future leaders give the impression that they will take control of public policy. They promise major policy change and give little indication that anything might stand in their way.

This image has been a major feature of Donald Trump’s rhetoric on his US Presidency. It has also been a feature of campaigns for the UK withdrawal from the European Union (‘Brexit’) to allow its leaders to take back control of policy and policymaking. According to this narrative, Brexit would allow (a) the UK government to make profound changes to immigration and spending, and (b) Parliament and the public to hold the UK government directly to account, in contrast to a distant EU policy process less subject to direct British scrutiny.

Such promises are built on the false image of a single ‘centre’ of government, in which a small number of elected policymakers take responsibility for policy outcomes. This way of thinking is rejected continuously in the modern literature. Instead, policymaking is ‘multi-centric’: responsibility for policy outcomes is spread across many levels and types of government (‘centres’), and shared with organisations outside of government, to the extent that it is not possible to simply know who is in charge and to blame. This arrangement helps explain why leaders promise major policy change but most outcomes represent a minor departure from the status quo.

Some studies of politics relate this arrangement to the choice to share power across many centres. In the US, a written constitution ensures power sharing across different branches (executive, legislative, judicial) and between federal and state or local jurisdictions. In the UK, central government has long shared power with EU, devolved, and local policymaking organisations.

However, policy theories show that most aspects of multi-centric governance are necessary. The public policy literature provides many ways to describe such policy processes, but two are particularly useful.

The first approach is to explain the diffusion of power with reference to an enduring logic of policymaking, as follows:

• The size and scope of the state is so large that it is always in danger of becoming unmanageable. Policymakers manage complexity by breaking the state’s component parts into policy sectors and sub-sectors, with power spread across many parts of government.
• Elected policymakers can only pay attention to a tiny proportion of issues for which they are responsible. They pay attention to a small number and ignore the rest. They delegate policymaking responsibility to other actors such as bureaucrats, often at low levels of government.
• At this level of government and specialisation, bureaucrats rely on specialist organisations for information and advice. Those organisations trade that information/advice and other resources for access to, and influence within, the government.
• Most public policy is conducted primarily through small and specialist ‘policy communities’ that process issues at a level of government not particularly visible to the public, and with minimal senior policymaker involvement.

This description suggests that senior elected politicians are less important than people think, their impact on policy is questionable, and elections may not provide major changes in policy. Most decisions are taken in their name but without their intervention.

A second, more general, approach is to show that elected politicians deal with such limitations by combining cognition and emotion to make choices quickly. Although such action allows them to be decisive, they occur within a policymaking environment over which governments have limited control. Government bureaucracies only have the coordinative capacity to direct policy outcomes in a small number of high priority areas. In most other cases, policymaking is spread across many venues, each with their own rules, networks, ways of seeing the world, and ways of responding to socio-economic factors and events.

In that context, we should always be sceptical when election candidates and referendum campaigners (or, in many cases, leaders of authoritarian governments) make such promises about political leadership and government control.

A more sophisticated knowledge of policy processes allows us to identify the limits to the actions of elected policymakers, and develop a healthier sense of pragmatism about the likely impact of government policy. The question of our age is not: how can governments take back control? Rather, it is: how can we hold policymakers to account in a complex system over which they have limited knowledge and even less control?

Policy Analysis in 750 words: Beryl Radin, B (2019) Policy Analysis in the Twenty-First Century

Please see the Policy Analysis in 750 words series overview before reading the summary. As usual, the 750-word description is more for branding than accuracy.

Beryl Radin (2019) Policy Analysis in the Twenty-First Century (Routledge)

‘The basic relationship between a decision-maker (the client) and an analyst has moved from a two-person encounter to an extremely complex and diverse set of interactions’ (Radin, 2019: 2).

Many texts in this series continue to highlight the client-oriented nature of policy analysis (Weimer and Vining), but within a changing policy process that has altered the nature of that relationship profoundly.

This new policymaking environment requires new policy analysis skills and training (see Mintrom), and limits the applicability of classic 8-step (or 5-step) policy analysis techniques (2019: 82).

We can use Radin’s work to present two main stories of policy analysis:

1. The old ways of making policy resembled a club, or reflected a clear government hierarchy, involving:

• a small number of analysts, generally inside government (such as senior bureaucrats, scientific experts, and – in particular- economists),
• giving technical or factual advice,
• about policy formulation,
• to policymakers at the heart of government,
• on the assumption that policy problems would be solved via analysis and action.

2. Modern policy analysis is characterised by a more open and politicised process in which:

• many analysts, inside and outside government,
• compete to interpret facts, and give advice,
• about setting the agenda, and making, delivering, and evaluating policy,
• across many policymaking venues,
• often on the assumption that governments have a limited ability to understand and solve complex policy problems.

As a result, the client-analyst relationship is increasingly fluid:

In previous eras, the analyst’s client was a senior policymaker, the main focus was on the analyst-client relationship, and ‘both analysts and clients did not spend much time or energy thinking about the dimensions of the policy environment in which they worked’ (2019: 59). Now, in a multi-centric policymaking environment:

1. It is tricky to identify the client.

• We could imagine the client to be someone paying for the analysis, someone affected by its recommendations, or all policy actors with the ability to act on the advice (2019: 10).
• If there is ‘shared authority’ for policymaking within one political system, a ‘client’ (or audience) may be a collection of policymakers and influencers spread across a network containing multiple types of government, non-governmental actors, and actors responsible for policy delivery (2019: 33).
• The growth in international cooperation also complicates the idea of a single client for policy advice (2019: 33-4)
• This shift may limit the ‘face-to-face encounters’ that would otherwise provide information for – and perhaps trust in – the analyst (2019: 2-3).

2. It is tricky to identify the analyst

• Radin (2019: 9-25) traces, from the post-war period in the US, a major expansion of policy analysts, from the notional centre of policymaking in federal government towards analysts spread across many venues, inside government (across multiple levels, ‘policy units’, and government agencies) and congressional committees, and outside government (such as in influential think tanks).
• Policy analysts can also be specialist external companies contracted by organisations to provide advice (2019: 37-8).
• This expansion shifted the image of many analysts, from a small number of trusted insiders towards many being treated as akin to interest groups selling their pet policies (2019: 25-6).
• The nature – and impact – of policy analysis has always been a little vague, but now it seems more common to suggest that ‘policy analysts’ may really be ‘policy advocates’ (2019: 44-6).
• As such, they may now have to work harder to demonstrate their usefulness (2019: 80-1) and accept that their analysis will have a limited impact (2019: 82, drawing on Weiss’ discussion of ‘enlightenment’).

Consequently, the necessary skills of policy analysis have changed:

Although many people value systematic policy analysis (and many rely on economists), an effective analyst does not simply apply economic or scientific techniques to analyse a problem or solution, or rely on one source of expertise or method, as if it were possible to provide ‘neutral information’ (2019: 26).

Indeed, Radin (2019: 31; 48) compares the old ‘acceptance that analysts would be governed by the norms of neutrality and objectivity’ with

(a) increasing calls to acknowledge that policy analysis is part of a political project to foster some notion of public good or ‘public interest’, and

(b)  Stone’s suggestion that the projection of reason and neutrality is a political strategy.

In other words, the fictional divide between political policymakers and neutral analysts is difficult to maintain.

Rather, think of analysts as developing wider skills to operate in a highly political environment in which the nature of the policy issue is contested, responsibility for a policy problem is unclear, and it is not clear how to resolve major debates on values and priorities:

• Some analysts will be expected to see the problem from the perspective of a specific client with a particular agenda.
• Other analysts may be valued for their flexibility and pragmatism, such as when they acknowledge the role of their own values, maintain or operate within networks, communicate by many means, and supplement ‘quantitative data’ with ‘hunches’ when required (2019: 2-3; 28-9).

Radin (2019: 21) emphasises a shift in skills and status

The idea of (a) producing new and relatively abstract ideas, based on high control over available information, at the top of a hierarchical organisation, makes way for (b) developing the ability to:

• generate a wider understanding of organisational and policy processes, reflecting the diffusion of power across multiple policymaking venues
• identify a map of stakeholders,
• manage networks of policymakers and influencers,
• incorporate ‘multiple and often conflicting perspectives’,
• make and deliver more concrete proposals (2019: 59-74), while recognising
• the contested nature of information, and the practices sued to gather it, even during multiple attempts to establish the superiority of scientific evidence (2019: 89-103),
• the limits to a government’s ability to understand and solve problems (2019: 95-6),
• the inescapable conflict over trade-offs between values and goals, which are difficult to resolve simply by weighting each goal (2019: 105-8; see Stone), and
• do so flexibly, to recognise major variations in problem definition, attention and networks across different policy sectors and notional ‘stages’ of policymaking (2019: 75-9; 84).

Radin’s (2019: 48) overall list of relevant skills include:

1. ‘Case study methods, Cost- benefit analysis, Ethical analysis, Evaluation, Futures analysis, Historical analysis, Implementation analysis, Interviewing, Legal analysis, Microeconomics, Negotiation, mediation, Operations research, Organizational analysis, Political feasibility analysis, Public speaking, Small- group facilitation, Specific program knowledge, Statistics, Survey research methods, Systems analysis’

They develop alongside analytical experience and status, from the early career analyst trying to secure or keep a job, to the experienced operator looking forward to retirement (2019: 54-5)

A checklist for policy analysts

Based on these skills requirements, the contested nature of evidence, and the complexity of the policymaking environment, Radin (2019: 128-31) produces a 4-page checklist of – 91! – questions for policy analysts.

For me, it serves two main functions:

1. It is a major contrast to the idea that we can break policy analysis into a mere 5-8 steps (rather, think of these small numbers as marketing for policy analysis students, akin to 7-minute abs)
2. It presents policy analysis as an overwhelming task with absolutely no guarantee of policy impact.

To me, this cautious, eyes-wide-open, approach is preferable to the sense that policy analysts can change the world if they just get the evidence and the steps right.

Further Reading:

1. Iris Geva-May (2005) ‘Thinking Like a Policy Analyst. Policy Analysis as a Clinical Profession’, in Geva-May (ed) Thinking Like a Policy Analyst. Policy Analysis as a Clinical Profession (Basingstoke: Palgrave)

Although the idea of policy analysis may be changing, Geva-May (2005: 15) argues that it remains a profession with its own set of practices and ways of thinking. As with other professions (like medicine), it would be unwise to practice policy analysis without education and training or otherwise learning the ‘craft’ shared by a policy analysis community (2005: 16-17). For example, while not engaging in clinical diagnosis, policy analysts can draw on 5-step process to diagnose a policy problem and potential solutions (2005: 18-21). Analysts may also combine these steps with heuristics to determine the technical and political feasibility of their proposals (2005: 22-5), as they address inevitable uncertainty and their own bounded rationality (2005: 26-34; see Gigerenzer on heuristics). As with medicine, some aspects of the role – such as research methods – can be taught in graduate programmes, while others may be better suited to on the job learning (2005: 36-40). If so, it opens up the possibility that there are many policy analysis professions to reflect different cultures in each political system (and perhaps the venues within each system).

2. Vining and Weimar’s take on the distinction between policy analysis and policy process research

 

Policy Concepts in 1000 Words: how do policy theories describe policy change?

The 1000 words and 500 words series already show how important but difficult it is to define and measure policy change. In this post, Dr Leanne Giordono and I dig deeper into the – often confusingly different – ways in which different researchers conceptualise this process. We show why there is such variation and provide a checklist of questions to ask of any description of policy change.

Measuring policy change is more difficult than it looks

The measurement of policy change is important. Most ‘what is policy?’ discussions remind us that there can be a huge difference between policy as a (a)  statement of intent, (b) strategy, (c) collection of tools/ instruments and (d) contributor to policy outcomes.

Policy theories remind us that, while politicians and political parties often promise to sweep into office and produce radical departures from the past, most policy change is minor. There is a major gap between stated intention and actual outcomes, partly because policymakers do not control the policy process for which they are responsible. Instead, they inherit the commitments of their predecessors and make changes at the margins.

The 1000 words and 500 words posts suggest that we address this problem of measurement by identifying the use of a potentially large number of policy instruments or policy tools such as regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal.

Then, they suggest that we tell a story of policy change, focusing on (a) what problem policymakers were trying to solve, and the size of their response in relation to the size of the problem, and (b) the precise nature of specific changes, or how each change contributes to the ‘big picture’.

This recommendation highlights a potentially major problem: as researchers, we can produce very different narratives of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data than others.

Three ways to navigate different approaches to imagining and measuring change

Researchers use many different concepts and measures to define and identify policy change. It would be unrealistic – and perhaps unimaginative – to solve this problem with a call for one uniform approach.

Rather, our aim is to help you (a) navigate this diverse field by (b) identifying the issues and concepts that will help you interpret and compare different ways to measure change.

1. Check if people are ‘showing their work’

Pay close attention to how scholars are defining their terms. For example, be careful with incomplete definitions that rely on a reference to evolutionary change (which can mean so many different things) or incremental change (e.g. does an increment mean small or non-radical)? Or, note that frequent distinctions between minor versus major change seem useful, but we are often trying to capture and explain a confusing mixture of both.

2. Look out for different questions

Multiple typologies of change often arise because different theories ask and answer different questions:

• The Advocacy Coalition Framework distinguishes between minor and major change, associating the former with routine ‘policy-oriented learning’, and the latter with changes in core policy beliefs, often caused by a ‘shock’ associated with policy failure or external events.
• Innovation and Diffusion models examine the adoption and non-adoption of a specific policy solution over a specific period of time in multiple jurisdictions as a result of learning, imitation, competition or coercion.
• Classic studies of public expenditure generated four categories to ask if the ‘budgetary process of the United States government is equivalent to a set of temporally stable linear decision rules’. They describe policy change as minor and predictable and explain outliers as deviations from the norm.
• Punctuated Equilibrium Theory identifies a combination of (a) huge numbers of small policy change and (b) small numbers of huge change as the norm, in budgetary and other policy changes.
• Hall distinguishes between (a) routine adjustments to policy instruments, (b) changes in instruments to achieve existing goals, and (c) complete shifts in goals. He compares long periods in which (1) some ideas dominate and institutions do not change, with (2) ‘third order’ change in which a profound sense of failure contributes to a radical shift of beliefs and rules.
• More recent scholarship identifies a range of concepts – including layering, drift, conversion, and displacement – to explain more gradual causes of profound changes to institutions.

These approaches identify a range of possible sources of measures:

1. a combination of policy instruments that add up to overall change
2. the same single change in many places
3. change in relation to one measure, such as budgets
4. a change in ideas, policy instruments and/ or rules.

As such, the potential for confusion is high when we include all such measures under the single banner of ‘policy change’.

3. Look out for different measures

Spot the different ways in which scholars try to ‘operationalize’ and measure policy change, quantitatively and/ or qualitatively, with reference to four main categories.

1. Size can be measured with reference to:

• A comparison of old and new policy positions.
• A change observed in a sample or whole population (using, for example, standard deviations from the mean).
• An ‘ideal’ state, such as an industry or ‘best practice’ standard.

2. Speed describes the amount of change that occurs over a specific interval of time, such as:

• How long it takes for policy to change after a specific event or under specific conditions.
• The duration of time between commencement and completion (often described as ‘sudden’ or ‘gradual’).
• How this speed compares with comparable policy changes in other jurisdictions (often described with reference to ‘leaders’ and ‘laggards’).

3. Direction describes the course of the path from one policy state to another. It is often described in comparison to:

• An initial position in one jurisdiction (such as an expansion or contraction).
• Policy or policy change in other jurisdictions (such as via ‘benchmarking’ or ‘league tables’)
• An ‘ideal’ state (such as with reference to left or right wing aims).

4. Substance relates to policy change in relations to:

• Relatively tangible instruments such as legislation, regulation, or public expenditure.
• More abstract concepts such as in relation to beliefs or goals.

Take home points for students

Be thoughtful when drawing comparisons between applications, drawn from many theoretical traditions, and addressing different research questions.  You can seek clarity by posing three questions:

1. How clearly has the author defined the concept of policy change?
2. How are the chosen theories and research questions likely to influence the author’s operationalization of policy change?
3. How does the author operationalize policy change with respect to size, speed, direction, and/or substance?

However, you should also note that the choice of definition and theory may affect the meaning of measures such as size, speed, direction, and/or substance.

A general theory of public policy

This is a placeholder for future work and discussion. It tails off at the end.

People sometimes talk about a ‘general theory’ of public policy to put in our minds a comparison with the physical sciences. Usually, the punchline is that there are ‘no general theories of public policy that are not bounded by space or time’ (p21). There may be some reference to the accumulation of knowledge or wisdom in policy studies, but based rarely on the understanding that policy studies contain the equivalent of general laws (I can only think of one possible exception).

This outcome is not too surprising in the social sciences, in which context really matters and we would expect a lot of variation in policy, policymaking, and outcomes.

On the other hand, we still need a way to communicate our findings, relate them to other studies, compare them, and wonder what it all adds up to. Few people go as far as expressing the sense that every study is unique (to the point of non-comparability) and that every description of policymaking does not compare to another.

In other words, we may be looking for a happy medium, to reject the idea of general laws but encourage – when appropriate or necessary – enough of a sense of common outlook and experience to help us communicate with each other (without descending too quickly into heated debate on our cross-purposes). Or, we can at least tell a story of policy studies and invite others to learn from, or challenge, its insights.

In my case, there are two examples in which it is necessary to project some sense of a common and initially-not-too-complicated story:

1. When describing policy theory insights to students, on the assumption that it may be their gateway to more reading.

It is possible to choose how many words to devote to each topic, including 500 Words, 1000 Words, a 9000 word Understanding Public Policy chapter, more in the source material, and even more if students start to ‘snowball’.

It is also possible, if you have a clearly defined audience, to introduce some level of uncertainty about these descriptions and their limitations.

For example, I try to describe ‘the policy process’ in 500 words and 1000 words, but in the context of a wider discussion of images of the policy process.

It is also possible to provide more context, such as in this kind of introductory box, coupled with 12 things to know about studying public policy

(from Chapter 1)

You can also get into the idea that my story is one of many, particularly after students have invested in many versions of that story by the end of an introductory book

(from Chapter 13)

2. When describing these insights to people – from other disciplines or professions – who do not have the time, inclination, or frame of reference to put in that kind of work.

In this case, one presentation or article may be the limit. People may want to know the answer to a question – e.g. Why don’t policymakers listen to your evidence? – rather than hear all about the explanation for the answer.

You do your best, and then – if there is time – you talk about what you missed out.

For example, in this talk, the first question was: why didn’t you mention the role of power?

 

A general theory or a general understanding? Two key issues

That was a long-winded introduction to a more philosophical point about what we might want from general theories. My impression is that you might be seeking one of these two possibilities:

1. To use theories and concepts to describe material reality. In producing a general theory, we seek a general understanding of the ways in which the real world works. If so, we may focus primarily on how well these concepts describe the world, and the extent to which we can produce methods to produce systematic and consistent findings. The lack of a general theory denotes too much complexity and context.
2. To use theories and concepts to represent a useful story. In producing a general understanding, we focus on the ways in which people generate and communicate their understanding. If so, we may focus more on how people come together to produce and share meaning through concepts. The lack of a general theory could reflect the lack of agreement on how to study policymaking. Or, the presence of a general understanding could represent the exercise of power, to set the agenda and limit scholarly attention to a small number of theories.

I describe this distinction in the following audio clip, produced halfway through a run with the dogs, while jetlagged. The large gap in the middle happens when I am trying to see if the voice to text is working well enough for me to copy/paste it here (no).

Key examples of the exercise of power include:

1. The act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge (discussed in power and knowledge and Chapter 3).
2. Ongoing discussions about how we deal with (a) a relatively new focus (among the most-established policy theories) on policy studies in countries in the Global South, given that (b) the dominant interpretations of policymaking come from experiences in the Global North.

So, if you read these posts or Chapter 13 you will find a story of a general understanding of policy followed, almost immediately, by a list of reasons for why you should engage with it critically and perhaps not accept it. I’m setting your agenda but also reminding you that I’m doing it.

That’s it really. To be continued.

Understanding Public Policy 2nd edition

All going well, it will be out in November 2019. We are now at the proofing stage.

I have included below the summaries of the chapters (and each chapter should also have its own entry (or multiple entries) in the 1000 Words and 500 Words series).

 

Policy in 500 Words: The advocacy coalition framework

Here is the ACF story.

People engage in politics to turn their beliefs into policy. They form advocacy coalitions with people who share their beliefs, and compete with other coalitions. The action takes place within a subsystem devoted to a policy issue, and a wider policymaking process that provides constraints and opportunities to coalitions.

The policy process contains multiple actors and levels of government. It displays a mixture of intensely politicized disputes and routine activity. There is much uncertainty about the nature and severity of policy problems. The full effects of policy may be unclear for over a decade. The ACF sums it up in the following diagram:

Policy actors use their beliefs to understand, and seek influence in, this world. Beliefs about how to interpret the cause of and solution to policy problems, and the role of government in solving them, act as a glue to bind actors together within coalitions.

If the policy issue is technical and humdrum, there may be room for routine cooperation. If the issue is highly charged, then people romanticise their own cause and demonise their opponents.

The outcome is often long-term policymaking stability and policy continuity because the ‘core’ beliefs of coalitions are unlikely to shift and one coalition may dominate the subsystem for long periods.

There are two main sources of change.

1. Coalitions engage in policy learning to remain competitive and adapt to new information about policy. This process often produces minor change because coalitions learn on their own terms. They learn how to retain their coalition’s strategic advantage and use the information they deem most relevant.
2. ‘Shocks’ affect the positions of coalitions within subsystems. Shocks are the combination of events and coalition responses. External shocks are prompted by events including the election of a new government with different ideas, or the effect of socioeconomic change. Internal shocks are prompted by policy failure. Both may prompt major change as members of one coalition question their beliefs in the light of new evidence. Or, another coalition may adapt more readily to its new policy environment and exploit events to gain competitive advantage.

The ACF began as the study of US policymaking, focusing largely on environmental issues. It has changed markedly to reflect the widening of ACF scholarship to new policy areas, political systems, and methods.

For example, the flow diagram’s reference to the political system’s long term coalition opportunity structures is largely the response to insights from comparative international studies:

• A focus on the ‘degree of consensus needed for major policy change’ reflects applications in Europe that highlighted the important of proportional electoral systems
• A focus on the ‘openness of the political system’ partly reflects applications to countries without free and fair elections, and/ or systems that do not allow people to come together easily as coalitions to promote policy change.

As such, like all theories in this series, the ACF discusses elements that it would treat as (a) universally applicable, such as the use of beliefs to address bounded rationality, and (b) context-specific, such as the motive and opportunity of specific people to organize collectively to translate their beliefs into policy.

See also:

The 500 and 1000 Words series

Why Advocacy Coalitions Matter and How to Think about Them

Three lessons from a comparison of fracking policy in the UK and Switzerland

Bonus material

Scottish Independence and the Devil Shift

Image source: Weible, Heikkila, Ingold, and Fischer (2016: 6)

https://twitter.com/amwellstead/status/1095011852915011586

 

 

 

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

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?

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:

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

 

Taking lessons from policy theory into practice: 3 examples

Notes for ANZSOG/ ANU Crawford School/ UNSW Canberra workshop. Powerpoint here. The recording of the lecture (skip to 2m30) and Q&A is here (right click to download mp3 or dropbox link):

The context for this workshop is the idea that policy theories could be more helpful to policymakers/ practitioners if we could all communicate more effectively with each other. Academics draw general and relatively abstract conclusions from multiple cases. Practitioners draw very similar conclusions from rich descriptions of direct experience in a smaller number of cases. How can we bring together their insights and use a language that we all understand? Or, more ambitiously, how can we use policy theory-based insights to inform the early career development training that civil servants and researchers receive?

The first step is to translate policy theories into a non-technical language by trying to speak with an audience beyond our immediate peers (see for example Practical Lessons from Policy Theories).

However, translation is not enough. A second crucial step is to consider how policymakers and practitioners are likely to make sense of theoretical insights when they apply them to particular aims or responsibilities. For example:

1. Central government policymakers may accept the descriptive accuracy of policy theories emphasising limited central control, but not the recommendation that they should let go, share power, and describe their limits to the public.
2. Scientists may accept key limitations to ‘evidence based policymaking’ but reject the idea that they should respond by becoming better storytellers or more manipulative operators.
3. Researchers and practitioners struggle to resolve hard choices when combining evidence and ‘coproduction’ while ‘scaling up’ policy interventions. Evidence choice is political choice. Can we do more than merely encourage people to accept this point?

I discuss these examples below because they are closest to my heart (especially example 1). Note throughout that I am presenting one interpretation about: (1) the most promising insights, and (2) their implications for practice. Other interpretations of the literature and its implications are available. They are just a bit harder to find.

Example 1: the policy cycle endures despite its descriptive inaccuracy

The policy cycle does not describe and explain the policy process well:

• If we insist on keeping the cycle metaphor, it is more accurate to see the process as a huge set of policy cycles that connect with each other in messy and unpredictable ways.
• The cycle approach also links strongly to the idea of ‘comprehensive rationality’ in which a small group of policymakers and analysts are in full possession of the facts and full control of the policy process. They carry out their aims through a series of stages.

Policy theories provide more descriptive and explanatory usefulness. Their insights include:

• Limited choice. Policymakers inherit organisations, rules, and choices. Most ‘new’ choice is a revision of the old.
• Limited attention. Policymakers must ignore almost all of the policy problems for which they are formally responsible. They pay attention to some, and delegate most responsibility to civil servants. Bureaucrats rely on other actors for information and advice, and they build relationships on trust and information exchange.
• Limited central control. Policy may appear to be made at the ‘top’ or in the ‘centre’, but in practice policymaking responsibility is spread across many levels and types of government (many ‘centres’). ‘Street level’ actors make policy as they deliver. Policy outcomes appear to ‘emerge’ locally despite central government attempts to control their fate.
• Limited policy change. Most policy change is minor, made and influenced by actors who interpret new evidence through the lens of their beliefs. Well-established beliefs limit the opportunities of new solutions. Governments tend to rely on trial-and-error, based on previous agreements, rather than radical policy change based on a new agenda. New solutions succeed only during brief and infrequent windows of opportunity.

However, the cycle metaphor endures because:

• It provides a simple model of policymaking with stages that map onto important policymaking functions.
• It provides a way to project policymaking to the public. You know how we make policy, and that we are in charge, so you know who to hold to account.

In that context, we may want to be pragmatic about our advice:

1. One option is via complexity theory, in which scholars generally encourage policymakers to accept and describe their limits:

• Accept routine error, reduce short-term performance management, engage more in trial and error, and ‘let go’ to allow local actors the flexibility to adapt and respond to their context.
• However, would a government in the Westminster tradition really embrace this advice? No. They need to balance (a) pragmatic policymaking, and (b) an image of governing competence.

2. Another option is to try to help improve an existing approach.

• Koski and Workman build on PET to recommend ways to process information more effectively.
• Studies built on MSA tend to focus on ‘entrepreneurs’ having a technically and politically feasible solution ready for the next window of opportunity.
• Sanderson describes the skills required for ‘intelligent policymaking’.
• I sum up these approaches in ‘How Can Policy Theory Have an Impact on Policy Making?’ Teaching Public Administration, 33, 1, 22-39 

Further reading (blog posts):

The language of complexity does not mix well with the language of Westminster-style accountability

Making Sense of Policymaking: why it’s always someone else’s fault and nothing ever changes

Two stories of British politics: the Westminster model versus Complex Government

Example 2: how to deal with a lack of ‘evidence based policymaking’

I used to read many papers on tobacco policy, with the same basic message: we have the evidence of tobacco harm, and evidence of which solutions work, but there is an evidence-policy gap caused by too-powerful tobacco companies, low political will, and pathological policymaking. These accounts are not informed by theories of policymaking.

I then read Oliver et al’s paper on the lack of policy theory in health/ environmental scholarship on the ‘barriers’ to the use of evidence in policy. Very few articles rely on policy concepts, and most of the few rely on the policy cycle. This lack of policy theory is clear in their description of possible solutions – better communication, networking, timing, and more science literacy in government – which does not describe well the need to respond to policymaker psychology and a complex policymaking environment.

So, I wrote The Politics of Evidence-Based Policymaking and one zillion blog posts to help identify the ways in which policy theories could help explain the relationship between evidence and policy.

Since then, the highest demand to speak about the book has come from government/ public servant, NGO, and scientific audiences outside my discipline. The feedback is generally that: (a) the book’s description sums up their experience of engagement with the policy process, and (b) maybe it opens up discussion about how to engage more effectively.

But how exactly do we turn empirical descriptions of policymaking into practical advice?

For example, scientist/ researcher audiences want to know the answer to a question like: Why don’t policymakers listen to your evidence? and so I focus on three conversation starters:

1. they have a broader view on what counts as good evidence (see ANZSOG description)
2. they have to ignore almost all information (a nice way into bounded rationality and policymaker psychology)
3. they do not understand or control the process in which they seek to use evidence (a way into ‘the policy process’)

We can then consider many possible responses in the sequel What can you do when policymakers ignore your evidence?

Examples include:

• ‘How to do it’ advice. I compare tips for individuals (from experienced practitioners) with tips based on policy concepts. They are quite similar-looking tips – e.g. find out where the action is, learn the rules, tell good stories, engage allies, seek windows of opportunity – but I describe mine as 5 impossible tasks!
• Organisational reform. I describe work with the European Commission Joint Research Centre to identify 8 skills or functions of an organisation bringing together the supply/demand of knowledge.
• Ethical dilemmas. I use key policy theories to ask people how far they want to go to privilege evidence in policy. It’s fun to talk about these things with the type of scientist who sees any form of storytelling as manipulation.

Further reading:

Is Evidence-Based Policymaking the same as good policymaking?

A 5-step strategy to make evidence count

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

Principles of science advice to government: key problems and feasible solutions

Example 3: how to encourage realistic evidence-informed policy transfer

This focus on EBPM is useful context for discussions of ‘policy learning’ and ‘policy transfer’, and it was the focus of my ANZOG talk entitled (rather ambitiously) ‘teaching evidence-based policy to fly’.

I’ve taken a personal interest in this one because I’m part of a project – called IMAJINE – in which we have to combine academic theory and practical responses. We are trying to share policy solutions across Europe rather than explain why few people share them!

For me, the context is potentially overwhelming:

• Policy learning is a political process, and expert-driven learning is one of many possibilities, alongside dialogue, bargaining, and hierarchical models.
• Indeed, researchers often do badly because they don’t learn how to deal with the politics.
• Policy transfer can be maximal or minimal, and driven voluntarily or via coercion. A policy solution, when ‘imported’, can be mimicked, translated or transformed.
• When transfer is voluntary, receptivity to new solutions is more important than their supply.
• There are very different ‘evidence-based’ models on how to ‘scale up’ policy success.

So, when we start to focus on sharing lessons, we will have three things to discover:

1. What is the evidence for success, and from where does it come? Governments often project success without backing it up.
2. What story do policymakers tell about the problem they are trying to solve, the solutions they produced, and why? Two different governments may be framing and trying to solve the same problem in very different ways.
3. Was the policy introduced in a comparable policymaking system? People tend to focus on political system comparability (e.g. is it unitary or federal?), but I think the key is in policymaking system comparability (e.g. what are the rules and dominant ideas?).

To be honest, when one of our external assessors asked me how well I thought I would do, we both smiled because the answer may be ‘not very’. In other words, the most practical lesson may be the hardest to take, although I find it comforting: the literature suggests that policymakers might ignore you for 20 years then suddenly become very (but briefly) interested in your work.

 

The slides are a bit wonky because I combined my old ppt to the Scottish Government with a new one for UNSW Paul Cairney ANU Policy practical 22 October 2018

I wanted to compare how I describe things to (1) civil servants (2) practitioners/ researcher (3) me, but who has the time/ desire to listen to 3 powerpoints in one go? If the answer is you, let me know and we’ll set up a Zoom call.

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:

3. policy learning and policy transfer are political processes, not ‘rational’ or technical searches for information
4. the use of evidence to spread policy innovation requires two interconnected choices: what counts as good evidence, and what role central governments should play.
5. 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.

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.

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.

2. 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.

3. 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:

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

 

 

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.

2. 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.

3. 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)

Now available as a live recording (of the powerpoint and sound; the hand waving exists only in our memories and our hearts) https://t.co/UcK5IdVL0R https://t.co/tKFt0OcSYC

— Professor Paul Cairney (@CairneyPaul) November 21, 2018

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

 

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 (see this post on the meaning of ‘irrational’). 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.

Now go to:

What can you do when policymakers ignore your evidence?

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

Special issue in Policy and Politics called ‘Practical lessons from policy theories’, which includes how to be a ‘policy entrepreneur’.

See also the 750 Words series to explore the implications for policy analysis

Policy in 500 words: uncertainty versus ambiguity

In policy studies, there is a profound difference between uncertainty and ambiguity:

• Uncertainty describes a lack of knowledge or a worrying lack of confidence in one’s knowledge.
• Ambiguity describes the ability to entertain more than one interpretation of a policy problem.

Both concepts relate to ‘bounded rationality’: policymakers do not have the ability to process all information relevant to policy problems. Instead, they employ two kinds of shortcut:

• ‘Rational’. Pursuing clear goals and prioritizing certain sources of information.
• ‘Irrational’. Drawing on emotions, gut feelings, deeply held beliefs, and habits.

I make an artificially binary distinction, uncertain versus ambiguous, and relate it to another binary, rational versus irrational, to point out the pitfalls of focusing too much on one aspect of the policy process:

1. Policy actors seek to resolve uncertainty by generating more information or drawing greater attention to the available information.

Actors can try to solve uncertainty by: (a) improving the quality of evidence, and (b) making sure that there are no major gaps between the supply of and demand for evidence. Relevant debates include: what counts as good evidence?, focusing on the criteria to define scientific evidence and their relationship with other forms of knowledge (such as practitioner experience and service user feedback), and what are the barriers between supply and demand?, focusing on the need for better ways to communicate.

2. Policy actors seek to resolve ambiguity by focusing on one interpretation of a policy problem at the expense of another.

Actors try to solve ambiguity by exercising power to increase attention to, and support for, their favoured interpretation of a policy problem. You will find many examples of such activity spread across the 500 and 1000 words series:

• Actors combine facts with emotional appeals to draw attention to their issues, at the expense of attention to other issues in a crowded political environment.
• Actors form coalitions with people who share their beliefs. They romanticise their own cause and demonise their opponents.
• Actors tell simple stories with a hero and moral to appeal to the emotional and ideological biases of policymakers.
• Policy entrepreneurs use skills of persuasion to frame problems, make sure their favoured solutions are feasible, and exploit times when policymakers have the motive and opportunity to act.
• Dominant ways of thinking act as a lens through which we process information.
• Policymakers exploit stereotypes of target populations.

A focus on reducing uncertainty gives the impression that policymaking is a technical process in which people need to produce the best evidence and deliver it to the right people at the right time.

In contrast, a focus on reducing ambiguity gives the impression of a more complicated and political process in which actors are exercising power to compete for attention and dominance of the policy agenda. Uncertainty matters, but primarily to describe the role of a complex policymaking system in which no actor truly understands where they are or how they should exercise power to maximise their success.

Further reading:

For a longer discussion, see Fostering Evidence-informed Policy Making: Uncertainty Versus Ambiguity (PDF)

Or, if you fancy it in French: Favoriser l’élaboration de politiques publiques fondées sur des données probantes : incertitude versus ambiguïté (PDF)

Framing

The politics of evidence-based policymaking

To Bridge the Divide between Evidence and Policy: Reduce Ambiguity as Much as Uncertainty

How to communicate effectively with policymakers: combine insights from psychology and policy studies

Here is the relevant opening section in UPP:

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

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

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

(2) The audio alone (link)

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

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

May I have your attention as I describe to you my new article, 'The UK government’s imaginative use of evidence to make policy'? https://t.co/AD4BZBRsUf pic.twitter.com/c4P1NHJgNF

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

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

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

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

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

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

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

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

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

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

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

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

The article is part of (1) a larger project on ‘the politics of evidence-based policymaking’https://t.co/0haxkUcdba pic.twitter.com/jIPjBfqleW

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

The article is also part of (2) a larger project on politics, prevention, and early intervention in the lives of children and adults, with @EmilyStDenny https://t.co/rUTi1UIyGI pic.twitter.com/blIbLbkjbd

— Professor Paul Cairney (@CairneyPaul) January 8, 2018

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

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

@CairneyPaul came to @IDS_UK and challenged our assumptions about evidence use – are we just generating evidence with people who already agree with us? Watch https://t.co/EwvySbqLQs @TransformUre @JordanTchil @mleach_ids @JohnGaventa

— James Georgalakis (@Bloggs74) January 17, 2019

See also:

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

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

(found by searching for early intervention)

See also:

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

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

(found by searching for prevention)

Powerpoint for guest lecture: Paul Cairney UK Government Evidence Policy

The global study of governance and public policy

I was invited by Dr Emamian from the Governance and Policy Think Tank to deliver this short lecture at the first ‘governance and public policy conference’ in Iran. I was unable to attend, so recorded a set of short video presentations supplemented by blog discussion. The topics to be covered include the importance of a scholarly network for policy studies, the need for a set of core policy concepts to act as a technical language for that network, and the need to apply that language to explain shifts in government and regulation towards ‘regulatory governance’.

Please note that my choice to record the videos in my garden (while I look up) seemed good at the time, for some very good reasons that I won’t get into. However, you will see that I become increasingly cold and annoyed at being cold. I can only apologize for my face and the fact that I was too cold to remember to put on my professional voice.

Using shared concepts in a scholarly network of policy researchers

Our aim may be to produce a global network of policy scholars, in two main ways:

1. To foster meetings and discussion, such as via this conference and others such as the ICPP and ECPR
2. To make sure that we are talking about the same thing. Most of the theories to which I refer are based on studies of countries like the US and UK. Their prominence contributes to a ‘global north’ perspective which can be useful in the abstract but with uncertain applicability across the globe.

For example, when considering the applicability of US-inspired theories, think about their taken-for-granted assumptions about the nature of a political system, in which leaders in many levels and types of government are elected regularly, there is a constitution guaranteeing a division of powers across legislative-executive-judicial branches and between federal/subnational levels, and people describe a ‘pluralist’ system in which many groups mobilise and counter-mobilise to influence policy.

What happens when we stop taking this political context for granted? Do these theories remain as relevant?

Which concepts do we use?

I describe two main abstract concepts then invite you to think about how to apply them in more concrete circumstances.

1. Bounded rationality, not comprehensive rationality.

No-one can understand fully the world in which we live. Individuals can only understand and pay attention to a tiny part of key aspects of the world such as political systems.

Indeed, a handy phrase to remember is that almost all people must ignore almost everything almost all of the time.

Yet, they must make choices despite uncertainty, perhaps by adopting ‘fast and frugal’ heuristics. In other words, we may see all human choices as flawed when compared with an ideal of perfect decision-making. On the other hand, we may marvel at the ways in which humans make often-good choices despite their limitations.

Individual policymakers use two short-cuts to gather enough information to make choices:

• ‘Rational’, in which they adopt measures to ensure that they have good enough information to inform decisions. For example, they prioritise certain written sources of information and draw on people they consider to be experts.
• ‘Irrational’, in which they rely on things like gut instinct, habit, and emotion to make snap decisions.

In that context, policy scholarship involves the study of how people make and influence those choices. One part is about the role of evidence, in which people produce information to reduce uncertainty about the nature of the world. However, the more important study is of how people understand the world in the first place. As policy scholars, we focus on ambiguity, to describe the many ways in which people choose to understand the same problems, and the exercise of power to influence those choices.

2. A complex policymaking environment, not a policy cycle.

Things get more complicated when we move from the analysis of (a) key individuals to (b) the interaction between many individuals and organisations in a complex policymaking ‘system’ or ‘environment’. Policy scholars describe this environment in many different ways, using different concepts, but we can identify a core set of terms on which to focus:

• Actors. There are many policy influencers and policymakers in many authoritative venues spread across many levels and types of government.
• Institutions. Each venue has its own rules, including the formal, written-down, and easy to understand rules, versus the informal norms, cultures, and practices which are difficult to identify and describe.
• Networks. Policymakers and influencers form relationships based on factors such as trust, authority, and the exchange of resources such as information and support.
• Ideas. People communicate their beliefs, about policy problems and potential solutions, within a wider understanding of the world (often described as a paradigm or hegemony). Some of that understanding is taken-for-granted and not described, and people limit their analysis and argument according to the ways in which they think other people see the world.
• Socioeconomic context and events. Policymakers often have to respond to policy conditions and events over which they have limited control, such geographic, demographic, and economic factors. These factors help produce non-routine ‘events’ alongside more predictable events such as elections (or other means to ensure a change of government).

In that context, policy scholarship focuses on producing theories to explain what happens when policymakers have limited control over their political systems and policymaking environments.

How far do these concepts travel?

As you can see, these concepts are widely applicable because they are abstract. What happens when we try to apply them to specific countries or case studies? For example:

1. We talk about policymakers using cognitive, moral, and emotional shortcuts, but those shortcuts can vary profoundly across the globe.
2. Each political system has a different collection of authoritative venues, formal and informal rules of politics, networks of power, ways to describe how the world works and should work, and socioeconomic context.

This is where our global network becomes valuable, to help us describe how we make sense of the same concepts in very different ways, and consider the extent to which such discussions are comparable.

Example: how do governments address an ‘era of governance’?

One way to foster such discussion is to consider how governments address the limits to their powers. These limits are described in many different ways, from a focus on ‘complexity’ and policy outcomes which ‘emerge’ from local activity (despite attempts by central governments to control outcomes), to a focus on the shift from ‘government’ to ‘governance’.

As policy scholars, we can make several useful distinctions to describe these dynamics, such as to separate an actual shift in policymaking from government to governance, versus a shift in the way we now describe government.

Or, we can separate how governments can, do, and should address the limits to their powers.

I’d say that most policy scholarship focuses on how governments operate: how they actually address problems and what are the – intended and unintended – consequences.

However, these studies are trying to describe the tensions between what governments can do, given the limits I describe, and what they think they should do, given their position of authority and their need to describe their success.

For example, some systems may be more conducive to the support for ‘polycentric governance’, in which many authoritative venues cooperate to address problems, while others are built on the idea of central control and the concentration of authority in a small group of actors.

Therefore, the study of actual policymaking and outcomes will vary markedly according to the ways in which government actors feel they need to assert an image of control over a policy environment which is almost immune to control.

Perhaps an ‘era of governance’ describes some recognition by many governments that they need to find new ways to address their limited control over policy outcomes, both domestically and globally. However, an enduring theme in political science and policy studies is that we do not explain policymaking well if we restrict our attention to the ‘rational’ decisions of a small number of actors. Let’s not make too many assumptions about their power and motive.

Further reading:

The New Policy Sciences

How to Communicate Effectively with Policymakers

The Politics of Evidence Based Policymaking

Comparison of Theories of the Policy Process

Key policy theories and concepts in 1000 words.