Could policy theories help to understand and facilitate the pursuit of equity (or reduction of unfair inequalities)?
We are producing a series of literature reviews to help answer that question, beginning with the study of equity policy and policymaking in health, education, and gender research.
Each field has a broadly similar focus. Most equity researchers challenge the ‘neoliberal’ approaches to policy that favour low state action in favour of individual responsibility and market forces. They seek ‘social justice’ approaches, favouring far greater state intervention to address the social and economic causes of unfair inequalities, via redistributive or regulatory measures. They seek policymaking reforms to reflect the fact that most determinants of inequalities are not contained to one policy sector and cannot be solved in policy ‘silos’. Rather, equity policy initiatives should be mainstreamed via collaboration across (and outside of) government. Each field also projects a profound sense of disenchantment with limited progress, including a tendency to describe a too-large gap between their aspirations and actual policy outcomes. They describe high certainty about what needs to happen, but low confidence that equity advocates have the means to achieve it (or to persuade powerful politicians to change course).
Policy theories could offer some practical insights for equity research, but not always offer the lessons that some advocates seek. In particular, health equity researchers seek to translate insights on policy processes into a playbook for action, such as to frame policy problems to generate more attention to inequalities, secure high-level commitment to radical change, and improve the coherence of cross-cutting policy measures. Yet, policy theories are more likely to identify the dominance of unhelpful policy frames, the rarity of radical change, and the strong rationale for uncoordinated policymaking across a large number of venues. Rather than fostering technical fixes with a playbook, they encourage more engagement with the inescapable dilemmas and trade-offs inherent to policy choice. This focus on contestation (such as when defining and addressing policy problems) is more of a feature of education and gender equity research.
While we ask what policy theories have to offer other disciplines, in fact the most useful lessons emerge from cross-disciplinary insights. They highlight two very different approaches to transformational political change. One offers the attractive but misleading option of radical change through non-radical action, by mainstreaming equity initiatives into current arrangements and using a toolbox to make continuous progress. Yet, each review highlights a tendency for radical aims to be co-opted and often used to bolster the rules and practices that protect the status quo. The other offers radical change through overtly political action, fostering continuous contestation to keep the issue high on the policy agenda and challenge co-option. There is no clear step-by-step playbook for this option, since political action in complex policymaking systems is necessarily uncertain and often unrewarding. Still, insights from policy theories and equity research shows that grappling with these challenges is inescapable.
Ultimately, we conclude that advocates of profound social transformation are wasting each other’s time if they seek short-cuts and technical fixes to enduring political problems. Supporters of policy equity should be cautious about any attempt to turn a transformational political project into a technical process containing a ‘toolbox’ or ‘playbook’.
You can read the original research in Policy & Politics:
My contribution to this interdisciplinary academic-practitioner discussion is to present insights from political science and policy process research, which required me to define some terms (background) before identifying three cautionary messages.
However, note the verb/noun distinction, and common architectural metaphor, to distinguish between the (a) act of design, and (b) the output (e.g. the blueprints).
In terms of the outputs, tools can be defined narrowly as policy instruments – including tax/spending, regulations, staff and other resources for delivery, information sharing, ‘nudging’, etc. – or more widely to include the processes involved in their formulation (such as participatory and deliberative). Therefore, we could be describing:
A highly centralized process, involving very few people, to produce the equivalent of a blueprint.
A decentralized, and perhaps uncoordinated, process involving many people, built on the principle that to seek a blueprint would be to miss the point of participation and deliberation.
Policymaking research tends to focus on
(1) measuring policy change with reference to the ‘policy mix’ of these tools/ instruments, and generally showing that most policy change is minor (and some is major) (link1, link2, link3, link4), and/ or
(2) how to understand the complex policymaking systems or environments in which policy design processes take place.
These studies are the source of my messages of doom.
Three cautionary messages about new policy design
There is a major gap between the act of policy design and actual policies and policy processes. This issue led to the decline of old policy design studies in the 1980s.
While ‘new policy design’ scholars seek to reinvigorate the field, the old issues serve as a cautionary tale, reminding us that (1) policy design is not new, and (2) its decline did not relate to the lack of sophisticated skills or insights among policy designers.
In other words, these old problems will not simply be solved by modern scientific, methodological, or policy design advances. Rather, I encourage policy designers to pay particular attention to:
1. The gap between functional requirements and real world policymaking.
Policy analysts and designers often focus on what they need, or require to get their job done or produce the outcomes they seek.
Policy process researchers identify the major, inevitable, gaps between those requirements and actual policy processes (to the extent that the link between design and policy is often difficult to identify).
2. The strong rationale for the policy processes that undermine policy design.
Policy processes – and their contribution to policy mixes – may seem incoherent from a design perspective. However, they make sense to the participants involved.
Some relate to choice, including to share responsibility for instruments across many levels or types of government (without focusing on how those responsibilities will connect or be coordinated).
Some result from necessity, to delegate responsibility to many policy communities spread across government, each with their own ways to define and address problems (without the ability to know how those responsibilities will be connected).
3. The policy analysis and design dilemmas that cannot be solved by design methods alone.
When seen from the ‘top down’, design problems often relate to the perceived lack of delivery or follow-through in relation to agreed high level design outputs (great design, poor delivery).
When seen from the ‘bottom up’, they represent legitimate ways to incorporate local stakeholder and citizen perspectives. This process will inevitably produce a gap between different sources and outputs of design, making it difficult to separate poor delivery (bad?) from deviation (good?).
Such dynamics are solved via political choice rather than design processes and techniques.
You can hear my presentation below (it took a while to get going because I wasn’t sure who could hear me):
Notes on the workshop discussion
The workshop discussion prompted us initially to consider how many different people would define it. The range of responses included seeing policy design as:
a specific process with specific tools to produce a well-defined output (applied to specific areas conducive to design methods)
a more general philosophy or way of thinking about things like policy issues (compare with systems thinking)
a means to encourage experimentation (such as to produce a prototype policy instrument, use it, and reflect or learn about its impact) or change completely how people think about an issue
the production of a policy solution, or one part of a large policy mix
a niche activity in one unit of government, or something mainstreamed across governments
something done in government, or inside and outside of government
producing something new (like writing on a blank sheet of paper), adding to a pile of solutions, or redesigning what exists
primarily a means to empower people to tell their story, or as a means to improve policy advocacy (as in discussions of narrative/ storytelling)
something done with authoritative policymakers like government ministers (in other words, people with the power to make policy changes after they participate in design processes) or given to them (in other words, the same people but as the audience for the outcomes of design)
These definitions matter since they have very different implications for policy and practice. Take, for example, the link – made by Professor Liz Richardson – between policy design and the idea of evidence-based policymaking, to consider two very different scenarios:
A minister is directly involved in policy design processes. They use design thinking to revisit how they think about a policy problem (and target populations), seek to foster participation and deliberation, and use that process – perhaps continuously – to consider how to reconcile very different sources of evidence (including, say, new data from randomized control trials and powerful stories from citizens, stakeholders, service users). I reckon that this kind of scenario would be in the minds of people who describe policy design optimistically.
A minister is the intended audience of a report on the outcomes of policy design. You assume that their thoughts on a policy problem are well-established. There is no obvious way for them to reconcile different sources of policy-relevant evidence. Crucially, the fruits of your efforts have made a profound impact on the people involved but, for the minister, the outcome is just one of too-many sources of information (likely produced too soon before or after they want to consider the issue).
The second scenario is closer to the process that I describe in the main post, although policy studies would warn against seeing someone like a government minister as authoritative in the sense that they reside in the centre of government. Rather, studies of multi-centric policymaking remind us that there are many possible centres spread across political systems. If so, policy design – according to approaches like the IAD – is about ways to envisage a much bigger context in which design success depends on the participation and agreement of a large number of influential actors (who have limited or no ability to oblige others to cooperate).
By James Nicholls and Paul Cairney, for the University of Stirling MPH and MPP programmes.
There are strong links between the study of public health and public policy. For example, public health scholars often draw on policy theories to help explain (often low amounts of) policy change to foster population health or reduce health inequalities. Studies include a general focus on public health strategies (such as HiAP) or specific policy instruments (such as a ban on smoking in public places). While public health scholars may seek to evaluate or influence policy, policy theories tend to focus on explaining processes and outcomes.
To demonstrate these links, we present:
A long-read blog post to (a) use an initial description of a key alcohol policy instrument (minimum unit pricing, adopted by the Scottish Government but not the UK Government) to (b) describe the application of policy concepts and theories and reflect on the empirical and practical implications. We then added some examples of further reading.
A 45 minute podcast to describe and explain these developments (click below or scroll to the end)
Minimum Unit Pricing in Scotland: background and development
Minimum Unit Pricing for alcohol was introduced in Scotland in 2018. In 2012, the UK Government had also announced plans to introduce MUP, but within a year dopped the policy following intense industry pressure. What do these two journeys tell us about policy processes?
When MUP was first proposed by Scottish Health Action on Alcohol Problems in 2007, it was a novel policy idea. Public health advocates had long argued that raising the price of alcohol could help tackle harmful consumption. However, conventional tax increases were not always passed onto consumers, so would not necessarily raise prices in the shops (and the Scottish Government did not have such taxation powers). MUP appeared to present a neat solution to this problem. It quickly became a prominent policy goal of public health advocates in Scotland and across the UK, while gaining increasing attention, and support, from the global alcohol policy community.
In 2008, the UK Minister for Health, Dawn Primarolo, had commissioned researchers at the University of Sheffield to look into links between alcohol pricing and harm. The Sheffield team developed economic models to analysis the predicted impact of different systems. MUP was included, and the ‘Sheffield Model’ would go on to play a decisive role in developing the case for the policy.
What problem would MUP help to solve?
Descriptions of the policy problem often differed in relation to each government. In the mid-2000s, alcohol harm had become a political problem for the UK government. Increasing consumption, alongside changes to the night-time economy, had started to gain widespread media attention. In 2004, just as a major liberalisation of the licensing system was underway in England, news stories began documenting the apparent horrors of ‘Binge Britain’: focusing on public drunkenness and disorder, but also growing rates of liver disease and alcohol-related hospital admissions.
Politicians began to respond, and the issue became especially useful for the Conservatives who were developing a narrative that Britain was ‘broken’ under New Labour. Labour’s liberalising reforms of alcohol licensing could conveniently be linked to this political framing. The newly formed Alcohol Health Alliance, a coalition set up under the leadership of Professor Sir Ian Gilmore, was also putting pressure on the UK Government to introduce stricter controls. In Scotland, while much of the debate on alcohol focused on crime and disorder, Scottish advocates were focused on framing the problem as one of public health. Emerging evidence showed that Scotland had dramatically higher rates of alcohol-related illness and death than the rest of Europe – a situation strikingly captured in a chart published in the Lancet.
The notion that Scotland faced an especially acute public health problem with alcohol was supported by key figures in the increasingly powerful Scottish National Party (in government since 2007), which, around this time, had developed working relationships with Alcohol Focus Scotland and other advocacy groups.
What happened next?
The SNP first announced that it would support MUP in 2008, but it did not implement this change until 2018. There are two key reasons for the delay:
Its minority government did not achieve enough parliamentary support to pass legislation. It then formed a majority government in 2011, and its legislation to bring MUP into law was passed in 2012.
Court action took years to resolve. The alcohol industry, which is historically powerful in Scotland, was vehemently opposed. A coalition of industry bodies, led by the Scotch Whisky Association, took the Scottish Government to court in an attempt to prove the policy was illegal. Ultimately, this process would take years, and conclude in rulings by the European Court of Justice (2016), Scottish Court of Session Inner House (2016), and UK Supreme Court (2017) which found in favour of the Scottish Government.
This public campaign was accompanied by intense behind-the-scenes lobbying, aided by the fact that the leadership of industry groups had close ties to Government and that the All-Party Parliamentary Group on Beer had the largest membership of any APPG in Westminster. The industry campaign made much of the fact there was little evidence to suggest MUP would reduce crime, but also argued strongly that the modelling produced by Sheffield University was not valid evidence in the first place. A year after the adopting the policy, the UK Government announced a U-turn and MUP was dropped.
How can we use policy theories and concepts to interpret these dynamics?
Here are some examples of using policy theories and concepts as a lens to interpret these developments.
1. What was the impact of evidence in the case for policy change?
Third, policymakers do not control the policy process.
There is no centralised and orderly policy cycle. Rather, policymaking involves policymakers and influencers spread across many authoritative ‘venues’, with each venue having its own rules, networks, and ways of thinking.
In that context, policy theories identify the importance of contestation between policy actors, and describe the development of policy problems, and how evidence fits in. Approaches include:
The acceptability of a policy solution will often depend on how the problem is described. Policymakers use evidence to reduce uncertainty, or a lack of information around problems and how to solve them. However, politics is about exercising power to reduce ambiguity, or the ability to interpret the same problem in different ways.
By suggesting MUP would solve problems around crime, the UK Government made it easier for opponents to claim the policy wasn’t evidence-based. In Scotland, policymakers and advocates focused on health, where the evidence was stronger. In addition, the SNP’s approach fitted within a wider political independence frame, in which more autonomy meant more innovation.
Policy actors tell stories to appeal to the beliefs (or exploit the cognitive shortcuts) of their audiences. A narrative contains a setting (the policy problem), characters (such as the villain who caused it, or the victim of its effects), plot (e.g. a heroic journey to solve the problem), and moral (e.g. the solution to the problem).
Supporters of MUP tended to tell the story that there was an urgent public health crisis, caused largely by the alcohol industry, and with many victims, but that higher alcohol prices pointed to one way out of this hole. Meanwhile opponents told the story of an overbearing ‘nanny state’, whose victims – ordinary, moderate drinkers – should be left alone by government.
Policymakers make strategic and emotional choices, to identify ‘good’ populations deserving of government help, and ‘bad’ populations deserving punishment or little help. These judgements inform policy design (government policies and practices) and provide positive or dispiriting signals to citizens.
For example, opponents of MUP rejected the idea that alcohol harms existed throughout the population. They focused instead on dividing the majority of moderate drinkers from irresponsible minority of binge drinkers, suggesting that MUP would harm the former more than help the latter.
This competition to frame policy problems takes place in political systems that contain many ‘centres’, or venues for authoritative choice. Some diffusion of power is by choice, such as to share responsibilities with devolved and local governments. Some is by necessity, since policymakers can only pay attention to a small proportion of their responsibilities, and delegate the rest to unelected actors such as civil servants and public bodies (who often rely on interest groups to process policy).
For example, ‘alcohol policy’ is really a collection of instruments made or influenced by many bodies, including (until Brexit) European organisations deciding on the legality of MUP, UK and Scottish governments, as well as local governments responsible for alcohol licensing. In Scotland, this delegation of powers worked in favour of MUP, since Alcohol Focus Scotland were funded by the Scottish Government to help deliver some of their alcohol policy goals, and giving them more privileged access than would otherwise have been the case.
The role of evidence in MUP
In the case of MUP, similar evidence was available and communicated to policymakers, but used and interpreted differently, in different centres, by the politicians who favoured or opposed MUP.
In Scotland, the promotion, use of, and receptivity to research evidence – on the size of the problem and potential benefit of a new solution – played a key role in increasing political momentum. The forms of evidence were complimentary. The ‘hard’ science on a potentially effective solution seemed authoritative (although few understood the details), and was preceded by easily communicated and digested evidence on a concrete problem:
There was compelling evidence of a public health problem put forward by a well-organised ‘advocacy coalition’ (see below) which focused clearly on health harms. In government, there was strong attention to this evidence, such as the Lancet chart which one civil servant described as ‘look[ing] like the north face of the Eiger’. There were also influential ‘champions’ in Government willing to frame action as supporting the national wellbeing.
Reports from Sheffield University appeared to provide robust evidence that MUP could reduce harm, and advocacy was supported by research from Canada which suggested that similar policies there had been successful elsewhere.
Advocacy in England was also well-organised and influential, but was dealing with a larger – and less supportive – Government machine, and the dominant political frame for alcohol harms remained crime and disorder rather than health.
Debates on MUP modelling exemplify these differences in evidence communication and use. Those in favour appealed to econometric models, but sometimes simplifying their complexity and blurring the distinction between projected outcomes and proof of efficacy. Opponents went the other way and dismissed the modelling as mere speculation. What is striking is the extent to which an incredibly complex, and often poorly understand, set of econometric models – and the ’Sheffield Model’ in particular – came to occupy centre stage in a national policy debate. Katikireddi and colleagues talked about this as an example of evidence as rhetoric:
Support became less about engagement with the econometric modelling, and more an indicator of general concern about alcohol harm and the power of the industry.
Scepticism was often viewed as the ‘industry position’, and an indicator of scepticism towards public health policy more broadly.
2. Who influences policy change?
Advocacy plays a key role in alcohol policy, with industry and other actors competing with public health groups to define and solve alcohol policy problems. It prompts our attention to policy networks, or the actors who make and influence policy.
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. Beliefs about how to interpret policy problems 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.
MUP became a highly charged focus of contestation between a coalition of public health advocates, who saw themselves as fighting for the wellbeing of the wider community (and who believed fundamentally that government had a duty to promote population health), and a coalition of industry actors who were defending their commercial interests, while depicting public health policies as illiberal and unfair.
3. Was there a ‘window of opportunity’ for MUP?
Policy theories – including Punctuated Equilibrium Theory – describe a tendency for policy change to be minor in most cases and major in few. Paradigmatic policy change is rare and may take place over decades, as in the case of UK tobacco control where many different policy instruments changed from the 1980s. Therefore, a major change in one instrument could represent a sea-change overall or a modest adjustment to the overall approach.
Multiple Streams Analysis is a popular way to describe the adoption of a new policy solution such as MUP. It describes disorderly policymaking, in which attention to a policy problem does not produce the inevitable development, implementation, and evaluation of solutions. Rather, these ‘stages’ should be seen as separate ‘streams’. A ‘window of opportunity’ for policy change occurs when the three ‘streams’ come together:
Problem stream. There is high attention to one way to define a policy problem.
Policy stream. A technically and politically feasible solution already exists (and is often pushed by a ‘policy entrepreneur’ with the resources and networks to exploit opportunities).
Politics stream. Policymakers have the motive and opportunity to choose that solution.
However, these windows open and close, often quickly, and often without producing policy change.
This approach can help to interpret different developments in relation to Scottish and UK governments:
The Scottish Government paid high attention to public health crises, including the role of high alcohol consumption.
The UK government paid often-high attention to alcohol’s role in crime and anti-social behaviour (‘Binge Britain’ and ‘Broken Britain’)
In Scotland, MUP connected strongly to the dominant framing, offering a technically feasible solution that became politically feasible in 2011.
The UK Prime Minister David Cameron’s made a surprising bid to adopt MUP in 2012, but ministers were divided on its technical feasibility (to address the problem they described) and its political feasibility seemed to be more about distracting from other crises than public health.
The Scottish Government was highly motivated to adopt MUP. MUP was a flagship policy for the SNP; an opportunity to prove its independent credentials, and to be seen to address a national public health problem. It had the opportunity from 2011, then faced interest group opposition that delayed implementation.
The Coalition Government was ideologically more committed to defending commercial interests, and to framing alcohol harms as one of individual (rather than corporate) responsibility. It took less than a year for the alcohol industry to successfully push for a UK government U-turn.
As a result, MUP became policy (eventually) in Scotland, but the window closed (without resolution) in England.
Paul Cairney and Donley Studlar (2014) ‘Public Health Policy in the United Kingdom: After the War on Tobacco, Is a War on Alcohol Brewing?’ World Medical and Health Policy, 6, 3, 308-323PDF
Niamh Fitzgerald and Paul Cairney (2022) ‘National objectives, local policymaking: public health efforts to translate national legislation into local policy in Scottish alcohol licensing’, Evidence and Policy, https://doi.org/10.1332/174426421X16397418342227, PDF
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By James Nicholls and Paul Cairney, for the University of Stirling MPH and MPP programmes.
There are strong links between the study of public health and public policy. For example, public health scholars often draw on policy theories to help explain (often low amounts of) policy change to foster population health or reduce health inequalities. Studies include a general focus on public health strategies (such as HiAP) or specific policy instruments (such as a ban on smoking in public places). While public health scholars may seek to evaluate or influence policy, policy theories tend to focus on explaining processes and outcomes,.
To demonstrate these links, we present this podcast and blog post to (1) use an initial description of a key alcohol policy instrument (minimum unit pricing in Scotland) to (2) describe the application of policy concepts and theories and reflect on the empirical and practical implications.
Using policy theories to interpret public health case studies: the example of a minimum unit price for alcohol | Paul Cairney: Politics & Public Policy (wordpress.com)
It would be a mistake to equate public policy with whatever a government says it is doing (or wants to do).
The most obvious, but often unhelpful, explanation for this statement is that politicians are not sincere when making policy promises, or not competent enough to see them through.
This focus on sincerity and ‘political will’ can be useful, but only scratches the surface of explanation.
The bigger source of explanation comes from the routine, pervasive, and inevitable contradictions of policy and policymaking.
The basic idea of contradictory aims and necessary trade-offs
I want to eat crisps and lose weight, but making a commitment to both does not achieve both. Rather, I cycle between each aim, often unpredictably, producing what might appear to be an inconsistent approach to my wellbeing.
These problems only get worse when more people and aims are involved. Indeed, a general description of ‘politics’ regards trying to find ways to resolve the many different preferences of many people in the same society. These preferences are intransitive, prompting policy actors to try to manipulate choice situations, or produce effective stories or narratives, to encourage one choice over another. Even if successful in once case, the overall impact of political action is not consistent.
The inevitable result of politics is that policymakers want to prioritise many policy aims and the aims that undermine them. When they pursue many contradictory aims, they have to make trade-offs and prioritise some aims over others. Sometimes, this choice is explicit. Sometimes, you have to work out what a government’s real priorities are when they seem sincerely committed to so many things. If so, we should not deduce government policy overall from specific statements and policies.
This basic idea plays out in many different ways, including:
Policymakers need to address many contradictory demands
Contradictions are inevitable when policymakers seek to offer policy benefits to many different groups for different reasons. Some benefits are largely rhetorical, others more substantive.
Ambiguity allows policy actors to downplay contradictions (temporarily) when generating support.
Contradictions are masked by ambiguity, such as when many different actors support the same vague ambition for very different reasons.
Policy silos contribute to contradictory action
Contradictions are exacerbated by inevitable and pervasive policy silos or ‘communities’ that seem immune to ‘holistic’ government. They multiply when governments have many departments pursuing many different aims. There may be a vague hope for joined-up policy, but a strong rationale for policy communities to specialise and become insulated.
The power to make policies – or create or amend policy instruments – is spread across many different venues of authority. If so, a key aim – stated often – is to find ways to cooperate to avoid contradictory policies and practices. The logical consequence of this distribution of powers, and the continuous search for meaningful cooperation, is that such contradictions are routine features, not bugs, of political systems.
Some of these outcomes simply emerge from routine policy delivery, when the actors carrying out policy have different ideas than the actors sending them instructions. Or, implementing actors do not have the resources or clarity to do what they think they are being told.
Examples of contradictions in policy and policymaking
Most governments are committed rhetorically (and often sincerely) to the public health agenda ‘Health in All Policies’ but also the social and economic policies that undermine it. The same goes for the more general aim of ‘prevention’.
In these kinds of cases, it is tempting to conclude that governments make promises energetically as a substitute for – not a signal of – action.
Levin et al note that the governments seeking to reduce climate change are also responsible for its inevitability.
The US and EU have subsidised the production and/or encouraged the sale of tobacco (to foster economic aims) at the same time as seeking tobacco control and discouraging smoking (to foster public health aims).
Policy studies and policy analysis guidebooks identify the importance of feasible policy solutions:
Technical feasibility: will this solution work as intended if implemented?
Political feasibility: will it be acceptable to enough powerful people?
For example, Kingdon treats feasibility as one of three conditions for major policy change during a ‘window of opportunity’: (1) there is high attention to the policy problem, (2) a feasible solution already exists, and (3) key policymakers have the motive and opportunity to select it.
Guidebooks relate this requirement initially to your policymaker client: what solutions will they rule out, to the extent that they are not even worth researching as options (at least for the short term)?
Further, this assessment relates to types of policy ‘tool’ or ‘instrument’: one simple calculation is that ‘redistributive’ measures are harder to sell than ‘distributive’, while both may be less attractive than regulation (although complex problems likely require a mix of instruments).
Incremental analysis. It is better to research in-depth a small number of feasible options than spread your resources too thinly to consider all possibilities.
Strategic analysis. The feasibility of a solution relates strongly to current policy. The more radical a departure from the current negotiated position, the harder it will be to sell.
As many posts in the Policy Analysis in 750 words series describe, this advice is not entirely useful for actors who seek rapid and radical departures from the status quo. Lindblom’s response to such critics was to seek radical change via a series of non-radical steps (at least in political systems like the US), which (broadly speaking) represents one of two possible approaches.
While incrementalism is not as popular as it once was (as a description of, or prescription for, policymaking), it tapped into the enduring insight that policymaking systems produce huge amounts of minor change. Rapid and radical policy change is rare, and it is even rarer to be able to connect it to influential analysis and action (at least in the absence of a major event). This knowledge should not put people off trying, but rather help them understand the obstacles that they seek to overcome.
Relating feasible solutions and strategies to ‘policy success’
One way to incorporate this kind of advice is to consider how (especially elected) policymakers would describe their own policy success. The determination of success and failure is a highly contested and political process (not simply a technical exercise called ‘evaluation’), and policymakers may refer – often implicitly – to the following questions when seeking success:
Political. Will this policy boost my government’s credibility and chances of re-election?
Process. Will it be straightforward to legitimise and maintain support for this policy?
Programmatic. Will it achieve its stated objectives and produce beneficial outcomes if implemented?
The benefit to analysts, in asking themselves these questions, is that they help to identify the potential solutions that are technically but not politically feasible (or vice versa).
The absence of clear technical feasibility does not necessarily rule out solutions with wider political benefits (for example, it can be beneficial to look like you are trying to do something good). Hence the popular phrase ‘good politics, bad policy’.
Nor does a politically unattractive option rule out a technically feasible solution (not all politicians flee the prospect of ‘good policy, bad politics’). However, it should prompt attention to hard choices about whose support to seek, how long to wait, or how hard to push, to seek policy change. You can see this kind of thinking as ‘entrepreneurial‘ or ‘systems thinking’ depending on how much faith you have in agency in highly-unequal political contexts.
It is tempting to conclude that these obstacles to ‘good policy’ reflect the pathological nature of politics. However, if we want to make this argument, we should at least do it well:
1. You can find this kind of argument in fields such as public health and climate change studies, where researchers bemoan the gap between (a) their high-quality evidence on an urgent problem and (b) a disproportionately weak governmental response. To do it well, we need to separate analytically (or at least think about): (a) the motivation and energy of politicians (usually the source of most criticism of low ‘political will’), and (b) the policymaking systems that constrain even the most sincere and energetic policymakers. See the EBPM page for more.
1. Be pragmatic, and change things from the inside
Pragmatism is at the heart of most of the policy analysis texts in this series. They focus on the needs and beliefs of clients (usually policymakers). Policymakers are time-pressed, so keep your analysis short and relevant. See the world through their eyes. Focus on solutions that are politically as well as technically feasible. Propose non-radical steps, which may add up to radical change over the long-term.
This approach will seem familiar to students of research ‘impact’ strategies which emphasise relationship-building, being available to policymakers, and responding to the agendas of governments to maximise the size of your interested audience.
It will also ring bells for advocates of radical reforms in policy sectors such as (public) health and intersectoral initiatives such as gender mainstreaming:
Health in All Policies is a strategy to encourage radical changes to policy and policymaking to improve population health. Common advice includes to: identify to policymakers how HiAP fits into current policy agendas, seek win-win strategies with partners in other sectors, and go to great lengths to avoid the sense that you are interfering in their work (‘health imperialism’).
Gender mainstreaming is a strategy to consider gender in all aspect of policy and policymaking. An equivalent playbook involves steps to: clarify what gender equality is, and what steps may help achieve it; make sure that these ideas translate across all levels and types of policymaking; adopt tools to ensure that gender is a part of routine government business (such as budget processes); and, modify existing policies or procedures while increasing the representation of women in powerful positions.
In other words, the first approach is to pursue your radical agenda via non-radical means, using a playbook that is explicitly non-confrontational. Use your insider status to exploit opportunities for policy change.
2. Be radical, and challenge things from the outside
Challenging the status quo, for the benefit of marginalised groups, is at the heart of critical policy analysis:
Reject the idea that policy analysis is a rationalist, technical, or evidence-based process. Rather, it involves the exercise of power to (a) depoliticise problems to reduce attention to current solutions, and (b) decide whose knowledge counts.
Identify and question the dominant social constructions of problems and populations, asking who decides how to portray these stories and who benefits from their outcomes.
This approach resonates with frequent criticisms of ‘impact’ advice, emphasising the importance of producing research independent of government interference, to challenge policies that further harm already-marginalised populations.
It will also rings bells among advocates of more confrontational strategies to seek radical changes to policy and policymaking. They include steps to: find more inclusive ways to generate and share knowledge, produce multiple perspectives on policy problems and potential solutions, focus explicitly on the impact of the status quo on marginalised populations, politicise issues continuously to ensure that they receive sufficient attention, and engage in outsider strategies to protest current policies and practices.
Does this dichotomy make sense?
It is tempting to say that this dichotomy is artificial and that we can pursue the best of both worlds, such as working from within when it works and resorting to outsider action and protest when it doesn’t.
However, the blandest versions of this conclusion tend to ignore or downplay the politics of policy analysis in favour of more technical fixes. Sometimes collaboration and consensus politics is a wonderful feat of human endeavour. Sometimes it is a cynical way to depoliticise issues, stifle debate, and marginalise unpopular positions.
This conclusion also suggests that it is possible to establish what strategies work, and when, without really saying how (or providing evidence for success that would appeal to audiences associated with both approaches). Indeed, a recurrent feature of research in these fields is that most attempts to produce radical change prove to be dispiriting struggles. Non-radical strategies tend to be co-opted by more powerful actors, to mainstream new ways of thinking without changing the old. Radical strategies are often too easy to dismiss or counter.
The latter point reminds us to avoid excessively optimistic overemphasis on the strategies of analysts and advocates at the expense of context and audience. The 500 and 1000 words series perhaps tip us too far in the other direction, but provide a useful way to separate (analytically) the reasons for often-minimal policy change. To challenge dominant forms of policy and policymaking requires us to separate the intentional sources of inertia from the systemic issues that would constrain even the most sincere and energetic reformer.
For a special edition of the Journal of European Public Policy, we invite proposals for papers that reflect on the theory and practice of policy analysis. This special issue will include state of the art articles on the politics of policy analysis, and empirical studies that use theoretical insights to analyse and address real world problems.
Policy analysis is not a rationalist, technocratic, centrally managed, or ‘evidence based’ process to solve policy problems. Rather, critical policy analysis and mainstream policy studies describe contemporary policy analysis as a highly contested (but unequal) process in which many policymakers, analysts, and influencers cooperate or compete across many centres of government. Further, governments are not in the problem solving business. Instead, they inherit policies that address some problems and create or exacerbate others, benefit some groups and marginalize others, or simply describe problems as too difficult to solve. The highest profile problems, such as global public health and climate change, require the kinds of (1) cooperation across many levels of government (and inside and outside of government), and (2) attention to issues of justice and equity, of which analysts could only dream.
This description of policymaking complexity presents a conundrum. On the one hand, there exist many five-step guides to analysis, accompanied by simple stage-based descriptions of policy processes, but they describe what policy actors would need or like to happen rather than policymaking reality. On the other, policy theory-informed studies are essential to explanation, but not yet essential reading for policy analysts. Policy theorists may be able to describe policy processes – and the role of policy analysts – more accurately than simple guides, but do not offer a clear way to guide action. Practitioner audiences are receptive to accurate descriptions of policymaking reality, but also want a take-home message that they can pick up and use in their work. Critical policy analysts may appreciate insights on the barriers to policy and policymaking change, but only if there is equal attention to how to overcome them.
We seek contributions that engage with this conundrum. We welcome papers which use theories, concepts and frameworks that are considered the policy studies mainstream, but also contributions from critical studies that use research to support marginalized populations as they analyse contemporary policy problems. We focus on Europe broadly defined, but welcome contributions with direct lessons from any other region.
Potential themes include but are not limited to:
State of the art articles that use insights from policy theories and/ or critical policy analysis to guide the study and practice of policy analysis
Articles that situate the analysis of contemporary policy problems within a wider policymaking context, to replace wishful thinking with more feasible (but equally ambitious) analysis
Articles that engage critically with contemporary themes in policy analysis and design, such as how to encourage ‘entrepreneurial’ policy analysis, foster ‘co-production’ during policy analysis and design, or engage in ‘systems thinking’ without relying on jargon and gimmicks.
Articles that engage with the unrealistic idea of ‘evidence-based policymaking’ to produce more feasible (and less technocratic) images of evidence-informed policymaking.
Expressions of interest consisting of a title, author(s) names and affiliation, and a short abstract (no more than 300 words) should be sent to firstname.lastname@example.org by Feb 28th 2022. Successful authors should have a full article draft for submission into the JEPP review process by August 30th 2022.
This post forms one part of the Policy Analysis in 750 words series. It draws on work for an in-progress book on learning to reduce inequalities. Some of the text will seem familiar if you have read other posts. Think of it as an adventure game in which the beginning is the same but you don’t know the end.
Policy learning is the use of new information to update policy-relevant knowledge. Policy transfer involves the use of knowledge about policy and policymaking in one government to inform policy and policymaking in another.
These processes may seem to relate primarily to research and expertise, but they require many kinds of political choices (explored in this series). They take place in complex policymaking systems over which no single government has full knowledge or control.
Therefore, while the agency of policy analysts and policymakers still matters, they engage with a policymaking context that constrains or facilitates their action.
Two approaches to policy learning: agency and context-driven stories
Analysts compete to define problems and determine the manner and sources of learning, in a multi-centric environment where different contexts will constrain and facilitate action in different ways. For example, varying structural factors – such as socioeconomic conditions – influence the feasibility of proposed policy change, and each centre’s institutions provide different rules for gathering, interpreting, and using evidence.
Think of two different ways to respond to this description of the policy process with this lovely blue summary of concepts. One is your agency-centred strategic response. The other is me telling you why it won’t be straightforward.
There are many policy makers and influencers spread across many policymaking ‘centres’
Find out where the action is and tailor your analysis to different audiences.
There is no straightforward way to influence policymaking if multiple venues contribute to policy change and you don’t know who does what.
Each centre has its own ‘institutions’
Learn the rules of evidence gathering in each centre: who takes the lead, how do they understand the problem, and how do they use evidence?
There is no straightforward way to foster policy learning between political systems if each is unaware of each other’s unwritten rules. Researchers could try to learn their rules to facilitate mutual learning, but with no guarantee of success.
Each centre has its own networks
Form alliances with policymakers and influencers in each relevant venue.
The pervasiveness of policy communities complicates policy learning because the boundary between formal power and informal influence is not clear.
Well-established ‘ideas’ tend to dominate discussion
Learn which ideas are in good currency. Tailor your advice to your audience’s beliefs.
The dominance of different ideas precludes many forms of policy learning or transfer. A popular solution in one context may be unthinkable in another.
Many policy conditions (historic-geographic, technological, social and economic factors) command the attention of policymakers and are out of their control. Routine events and non-routine crises prompt policymaker attention to lurch unpredictably.
The policy conditions may be so different in each system that policy learning is limited and transfer would be inappropriate. Events can prompt policymakers to pay disproportionately low or high attention to lessons from elsewhere, and this attention relates weakly to evidence from analysts.
Feel free to choose one or both forms of advice. One is useful for people who see analysts and researchers as essential to major policy change. The other is useful if it serves as a source of cautionary tales rather than fatalistic responses.
The latter descriptions, reflecting multi-centric policymaking, seem particularly relevant to major contemporary policy problems – such as global public health and climate crises – in which cooperation across (and outside of) many levels and types of government is essential.
Resolving ambiguity in policy analysis texts
This context helps us to interpret common (Step 1) advice in policy analysis textbooks: define a policy problem for your client, using your skills of research and persuasion but tailoring your advice to your client’s interests and beliefs. Yet, gone are the mythical days of elite analysts communicating to a single core executive in charge of formulating and implementing all policy instruments. Many analysts engage with many centres producing (or co-producing) many instruments. Resolving ambiguity in one centre does not guarantee the delivery of your aims across many.
‘Top down’ accounts see this issue through the lens of a single central government, examining how to reassert central control by minimising implementation gaps.
Policy analysis may focus on (a) defining the policy problem, and (b) ensuring the implementation of its solution.
‘Bottom up’ accounts identify the inevitability (and legitimacy) of policy influence in multiple centres. Policy analysis may focus on how to define the problem in cooperation with other centres, or to set a strategic direction and encourage other centres to make sense of it in their context.
This terminology went out of fashion, but note the existence of each tendency in two ideal-type approaches to contemporary policy problems:
1. Centralised and formalised approaches.
Seek clarity and order to address urgent policy problems. Define the policy problem clearly, translate that definition into strategies for each centre, and develop a common set of effective ‘tools’ to ensure cooperation and delivery.
Policy analysis may focus on technical aspects, such as how to create a fine-detail blueprint for action, backed by performance management and accountability measures that tie actors to specific commitments.
The tagline may be: ambiguity is a problem to be solved, to direct policy actors towards a common goal.
Seek collaboration to make sense of, and address, problems. Reject a single definition of the problem, encourage actors in each centre (or in concert) to deliberate to make sense of problems together, and co-create the rules to guide a continuous process of collective behaviour.
Policy analysis may focus on how to contribute to a collaborative process of sense-making and rule-making.
The tagline may be: ambiguity presents an opportunity to energise policy actors, to harness the potential for innovation arising from deliberation.
Pick one approach and stick with it?
Describing these approaches in such binary terms makes the situation – and choice between approaches – look relatively straightforward. However, note the following issues:
Many policy sectors (and intersectoral agendas) are characterised by intense disagreement on which choice to make. These disagreements intersect with others (such as when people seek not only transformative policy change to solve global problems, but also equitable process and outcomes).
Some sectors seem to involve actors seeking the best of both worlds (centralise and localise, formalise and deliberate) without recognising the trade-offs and dilemmas that arise.
I have described these options as choices, but did not establish if anyone is in the position to make or contribute to that choice.
In that context, resolving ambiguity in your favour may still be the prize, but where would you even begin?
Well, that was an unsatisfying end to the post, eh? Maybe I’ll write a better one when some things are published. In the meantime, some of these papers and posts explore some of these issues:
This page describes a book and many posts on ‘prevention’ policy. We complain that governments use the phrase ‘prevention is better than cure’ without defining prevention, and that they want centralised and decentralised approaches to ‘preventive policymaking’.
We define trust as ‘a belief in the reliability of other people, organizations, or processes’, but it is one of those terms – like ‘policy’ – that defies a single comprehensive definition. The term ‘distrust’ complicates things further, since it does not simply mean the absence of trust.
Its treatment in social science also varies, which makes our statement – ‘Trust is necessary for cooperation, coordination, social order, and to reduce the need for coercive state imposition’ – one of many ways to understand its role.
A summary of key concepts
Social science accounts of trust relate it to:
1. Individual choice
I may trust someone to do something if I value their integrity (if they say they will do it, I believe them), credibility (I believe their claim is accurate and feasible), and competence (I believe they have the ability).
This perception of reliability depends on:
The psychology of the truster. The truster assesses the risk of relying on others, while combining cognition and emotion to relate that risk of making themselves vulnerable to the benefit of collective action, while drawing on an expectation of reciprocity.
The behaviour of the trustee. They demonstrate their trustworthiness in relation to past performance, which demonstrates their competence and reliability and perhaps their selflessness in favour of collective action.
Common reference points. The trustee and truster may use shortcuts to collective action, such as a reference to something they have in common (e.g. their beliefs or social background), their past interactions, or the authority of the trustee.
Rules can be formal, written, and widely understood (e.g. to help assign authority regardless of levels of interaction) or informal, unwritten, and only understood by some (e.g. resulting from interactions in some contexts).
Rules can represent low levels of trust and a focus on deterring breaches (e.g. creating and enforcing contracts) or high levels of trust (e.g. to formalize ‘effective practices built on reciprocity, emotional bonds, and/or positive expectations’).
3. Societal necessity and interdependence.
Trust is a functional requirement. We need to trust people because we cannot maintain a functional society or political system without working together. Trust-building underpins the study of collaboration (or cooperation and bargaining), such as in the Ecology of Games approach (which draws on the IAD).
In that context, trust is a resource (to develop) that is crucial to a required outcome.
Is trust good and distrust bad?
We describe trust as ‘necessary for cooperation’ and distrust as a ‘potent motivator’ that may prompt people to ignore advice or defy cooperation or instruction. Yet, neither is necessarily good or bad. Too much trust may be a function of: (1) the abdication of our responsibility to engage critically with leaders in political systems, (2) vulnerability to manipulation, and/ or (3) excessive tribalism, prompting people to romanticise their own cause and demonise others, each of which could lead us to accept uncritically the cynical choices of policymakers.
Trust is a slippery concept, and academics often make it slippier by assuming rather than providing a definition. In that context, why not read all of the 500 Words series and ask yourself where trust/ distrust fit in?
One take home message from the 750 Words series is to avoid seeing policy analysis simply as a technical (and ‘evidence-based’) exercise. Mainstream policy analysis texts break down the process into technical-looking steps, but also show how each step relates to a wider political context. Critical policy analysis texts focus more intensely on the role of politics in the everyday choices that we might otherwise take for granted or consider to be innocuous. The latter connect strongly to wider studies of the links between power and knowledge.
Power and ideas
Classic studies suggest that the most profound and worrying kinds of power are the hardest to observe. We often witness highly visible political battles and can use pluralist methods to identify who has material resources, how they use them, and who wins. However, key forms of power ensure that many such battles do not take place. Actors often use their resources to reinforce social attitudes and policymakers’ beliefs, to establish which issues are policy problems worthy of attention and which populations deserve government support or punishment. Key battles may not arise because not enough people think they are worthy of debate. Attention and support for debate may rise, only to be crowded out of a political agenda in which policymakers can only debate a small number of issues.
Studies of power relate these processes to the manipulation of ideas or shared beliefs under conditions of bounded rationality (see for example the NPF). Manipulation might describe some people getting other people to do things they would not otherwise do. They exploit the beliefs of people who do not know enough about the world, or themselves, to know how to identify and pursue their best interests. Or, they encourage social norms – in which we describe some behaviour as acceptable and some as deviant – which are enforced by (1) the state (for example, via criminal justice and mental health policy), (2) social groups, and (3) individuals who govern their own behaviour with reference to what they feel is expected of them (and the consequences of not living up to expectations).
Such beliefs, norms, and rules are profoundly important because they often remain unspoken and taken for granted. Indeed, some studies equate them with the social structures that appear to close off some action. If so, we may not need to identify manipulation to find unequal power relationships: strong and enduring social practices help some people win at the expense of others, by luck or design.
Relating power to policy analysis: whose knowledge matters?
The concept of‘epistemic violence’ is one way todescribe the act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge. Specific discussions include: (a) the colonial West’s subjugation of colonized populations, diminishing the voice of the subaltern; (b) privileging scientific knowledge and dismissing knowledge claims via personal or shared experience; and (c) erasing the voices of women of colour from the history of women’s activism and intellectual history.
It is in this context that we can understand ‘critical’ research designed to ‘produce social change that will empower, enlighten, and emancipate’ (p51). Powerlessness can relate to the visible lack of economic material resources and factors such as the lack of opportunity to mobilise and be heard.
750 Words posts examining this link between power and knowledge
Some posts focus on the role of power in research and/ or policy analysis:
These posts ask questions such as: who decides what evidence will be policy-relevant, whose knowledge matters, and who benefits from this selective use of evidence? They help to (1) identify the exercise of power to maintain evidential hierarchies (or prioritise scientific methods over other forms of knowledge gathering and sharing), and (2) situate this action within a wider context (such as when focusing on colonisation and minoritization). They reflect on how (and why) analysts should respect a wider range of knowledge sources, and how to produce more ethical research with an explicit emancipatory role. As such, they challenge the – naïve or cynical – argument that science and scientists are objective and that science-informed analysis is simply a technical exercise (see also Separating facts from values).
Many posts incorporate these discussions into many policy analysis themes.
A key argument in policy studies is that it is impossible to separate facts and values when making policy. We often treat our beliefs as facts, or describe certain facts as objective, but perhaps only to simplify our lives or support a political strategy (a ‘self-evident’ fact is very handy for an argument). People make empirical claims infused with their values and often fail to realise just how their values or assumptions underpin their claims.
This is not an easy argument to explain. One strategy is to use extreme examples to make the point. For example, Herbert Simon points to Hitler’s Mein Kampf as the ultimate example of value-based claims masquerading as facts. We can also identify historic academic research which asserts that men are more intelligent than women and some races are superior to others. In such cases, we would point out, for example, that the design of the research helped produce such conclusions: our values underpin our (a) assumptions about how to measure intelligence or other measures of superiority, and (b) interpretations of the results.
‘Wait a minute, though’ (you might say). “What about simple examples in which you can state facts with relative certainty – such as the statement ‘there are X number of words in this post’”. ‘Fair enough’, I’d say (you will have to speak with a philosopher to get a better debate about the meaning of your X words claim; I would simply say that it is trivially true). But this statement doesn’t take you far in policy terms. Instead, you’d want to say that there are too many or too few words, before you decided what to do about it.
In that sense, we have the most practical explanation of the unclear fact/ value distinction: the use of facts in policy is to underpin evaluations (assessments based on values). For example, we might point to the routine uses of data to argue that a public service is in ‘crisis’ or that there is a public health related epidemic (note: I wrote the post before COVID-19; it referred to crises of ‘non-communicable diseases’). We might argue that people only talk about ‘policy problems’ when they think we have a duty to solve them.
Or, facts and values often seem the hardest to separate when we evaluate the success and failure of policy solutions, since the measures used for evaluation are as political as any other part of the policy process. The gathering and presentation of facts is inherently a political exercise, and our use of facts to encourage a policy response is inseparable from our beliefs about how the world should work.
‘Modern science remains value-laden … even when so many people employ so many systematic methods to increase the replicability of research and reduce the reliance of evidence on individual scientists. The role of values is fundamental. Anyone engaging in research uses professional and personal values and beliefs to decide which research methods are the best; generate research questions, concepts and measures; evaluate the impact and policy relevance of the results; decide which issues are important problems; and assess the relative weight of ‘the evidence’ on policy effectiveness. We cannot simply focus on ‘what works’ to solve a problem without considering how we used our values to identify a problem in the first place. It is also impossible in practice to separate two choices: (1) how to gather the best evidence and (2) whether to centralize or localize policymaking. Most importantly, the assertion that ‘my knowledge claim is superior to yours’ symbolizes one of the most worrying exercises of power. We may decide to favour some forms of evidence over others, but the choice is value-laden and political rather than objective and innocuous’.
Implications for policy analysis
Many highly-intelligent and otherwise-sensible people seem to get very bothered with this kind of argument. For example, it gets in the way of (a) simplistic stories of heroic-objective-fact-based-scientists speaking truth to villainous-stupid-corrupt-emotional-politicians, (b) the ill-considered political slogan that you can’t argue with facts (or ‘science’), (c) the notion that some people draw on facts while others only follow their feelings, and (d) the idea that you can divide populations into super-facty versus post-truthy people.
A more sensible approach is to (1) recognise that all people combine cognition and emotion when assessing information, (2) treat politics and political systems as valuable and essential processes (rather than obstacles to technocratic policymaking), and (3) find ways to communicate evidence-informed analyses in that context. This article and 750 post explore how to reflect on this kind of communication.
One aim of this series is to combine insights from policy research (1000, 500) and policy analysis texts. How might we combine insights to think about effective communication?
1. Insights from policy analysis texts
Most texts in this series relate communication to understanding your audience (or client) and the political context. Your audience has limited attention or time to consider problems. They may have a good antennae for the political feasibility of any solution, but less knowledge of (or interest in) the technical details. In that context, your aim is to help them treat the problem as worthy of their energy (e.g. as urgent and important) and the solution as doable. Examples include:
Bardach: communicating with a client requires coherence, clarity, brevity, and minimal jargon.
Dunn: argumentation involves defining the size and urgency of a problem, assessing the claims made for each solution, synthesising information from many sources into a concise and coherent summary, and tailoring reports to your audience.
Smith: your audience makes a quick judgement on whether or not to read your analysis. Ask yourself questions including: how do I frame the problem to make it relevant, what should my audience learn, and how does each solution relate to what has been done before? Maximise interest by keeping communication concise, polite, and tailored to a policymaker’s values and interests.
2. Insights from studies of policymaker psychology
‘Rational’ shortcuts. Goal-oriented reasoning based on prioritizing trusted sources of information.
‘Irrational’ shortcuts. Emotional thinking, or thought fuelled by gut feelings, deeply held beliefs, or habits.
We can use such distinctions to examine the role of evidence-informed communication, to reduce:
Uncertainty, or a lack of policy-relevant knowledge. Focus on generating ‘good’ evidence and concise communication as you collate and synthesise information.
Ambiguity, or the ability to entertain more than one interpretation of a policy problem. Focus on argumentation and framing as you try to maximise attention to (a) one way of defining a problem, and (b) your preferred solution.
Gone are the mythical days of a small number of analysts communicating to a single core executive (and of the heroic researcher changing the world by speaking truth to power). Instead, we have many analysts engaging with many centres, creating a need to not only (a) tailor arguments to different audiences, but also (b) develop wider analytical skills (such as to foster collaboration and the use of ‘design principles’).
How to communicate effectively with policymakers
In that context, we argue that effective communication requires analysts to:
1. Understand your audience and tailor your response (using insights from psychology)
2. Identify ‘windows of opportunity’ for influence (while noting that these windows are outside of anyone’s control)
3. Engage with real world policymaking rather than waiting for a ‘rational’ and orderly process to appear (using insights from policy studies).
Several 500 Word and 1000 Word (a, b, c) posts try to define and measure policy change.
Most studies agree that policymaking systems produce huge amounts of minor change and rare instances of radical change, but not how to explain these patterns. For example:
Debates on incrementalism questioned if radical change could be managed via non-radical steps.
Punctuated equilibrium theory describes policy change as a function of disproportionately low or high attention to problems, and akin to the frequency of earthquakes (a huge number of tiny changes, and more major changes than we would see in a ‘normal distribution’).
One of the most famous accounts of major policy change is by Peter Hall. ‘Policy paradigms’ help explain a tendency towards inertia, punctuated rarely by radical change (compare with discussions of path dependence and critical junctures).
A policy paradigm is a dominant and often taken-for-granted worldview (or collection of beliefs) about: policy goals, the nature of a policy problem, and the instruments to address it.
Paradigms can operate for long periods, subject to minimal challenge or defended successfully during events that call current policies into question. Adherence to a paradigm produces two ‘orders’ of change:
1st order: frequent routine bureaucratic changes to instruments while maintaining policy goals.
2nd order: less frequent, non-routine changes (or use of new instruments) while maintaining policy goals.
Radical and rare – 3rd order – policy change may only follow a crisis in which policymakers cannot solve a policy problem or explain why policy is failing. It prompts a reappraisal and rejection of the dominant paradigm, by a new government with new ways of thinking and/or a government rejecting current experts in favour of new ones. Hall’s example was of rapid paradigm shift in UK economic policy – from ‘Keynesianism’ to ‘Monetarism’ – within very few years.
(b) A series of less radical changes that produced paradigm change over decades: from Keynesianism to ‘neo-Keynesianism’, or from state intervention to neoliberalism (such as to foster economic growth via private rather than public borrowing and spending)
3. Paul Cairney and Chris Weible (2015) ‘Comparing and Contrasting Peter Hall’s Paradigms and Ideas with the Advocacy Coalition Framework’ in (eds) M. Howlett and J. Hogan Policy Paradigms in Theory and Practice (Basingstoke: Palgrave) PDF
This post summarizes a key section of our review of education equity policymaking [see the full article for references to the studies summarized here].
One of the main themes is that many governments present a misleading image of their education policies. There are many variations on this theme, in which policymakers:
Describe the energetic pursuit of equity, and use the right language, as a way to hide limited progress.
Pursue ‘equity for all’ initiatives that ignore or downplay the specific importance of marginalization and minoritization, such as in relation to race and racism, immigration, ethnic minorities, and indigenous populations.
Pursue narrow definitions of equity in terms of access to schools, at the expense of definitions that pay attention to ‘out of school’ factors and social justice.
Minoritization is a strong theme in US studies in particular. US experiences help us categorise multiple modes of marginalisation in relation to race and migration, driven by witting and unwitting action and explicit and implicit bias:
The social construction of students and parents. Examples include: framing white students as ‘gifted’ and more deserving of merit-based education (or victims of equity initiatives); framing non-white students as less intelligent, more in need of special needs or remedial classes, and having cultural or other learning ‘deficits’ that undermine them and disrupt white students; and, describing migrant parents as unable to participate until they learn English.
Maintaining or failing to challenge inequitable policies. Examples include higher funding for schools and colleges with higher white populations, and tracking (segregating students according to perceived ability), which benefit white students disproportionately.
Ignoring social determinants or ‘out of school’ factors.
Creating the illusion of equity with measures that exacerbate inequalities. For example, promoting school choice policies while knowing that the rules restrict access to sought-after schools.
Promoting initiatives to ignore race, including so-called ‘color blind’ or ‘equity for all’ initiatives.
Prioritizing initiatives at the expense of racial or socio-economic equity, such as measures to boost overall national performance at the expense of targeted measures.
Game playing and policy subversion, including school and college selection rules to restrict access and improve metrics.
The wider international – primarily Global North – experience suggests that minoritization and marginalization in relation to race, ethnicity, and migration is a routine impediment to equity strategies, albeit with some uncertainty about which policies would have the most impact.
Other country studies describe the poor treatment of citizens in relation to immigration status or ethnicity, often while presenting the image of a more equitable system. Until recently, Finland’s global reputation for education equity built on universalism and comprehensive schools has contrasted with its historic ‘othering’ of immigrant populations. Japan’s reputation for containing a homogeneous population, allowing its governments to present an image of classless egalitarianism and harmonious society, contrasts with its discrimination against foreign students. Multiple studies of Canadian provinces provide the strongest accounts of the symbolic and cynical use of multiculturalism for political gains and economic ends:
As in the US, many countries use ‘special needs’ categories to segregate immigrant and ethnic minority populations. Mainstreaming versus special needs debates have a clear racial and ethnic dimension when (1) some groups are more likely to be categorised as having learning disabilities or behavioural disorders, and (2) language and cultural barriers are listed as disabilities in many countries. Further, ‘commonwealth’ country studies identify the marginalisation of indigenous populations in ways comparable to the US marginalisation of students of colour.
Overall, these studies generate the sense that the frequently used language of education equity policy can signal a range of possibilities, from (1) high energy and sincere commitment to social justice, to (2) the cynical use of rhetoric and symbolism to protect historic inequalities.
Turner, E.O., and Spain, A.K., (2020) ‘The Multiple Meanings of (In)Equity: Remaking School District Tracking Policy in an Era of Budget Cuts and Accountability’, Urban Education, 55, 5, 783-812 https://doi.org/10.1177%2F0042085916674060
Felix, E.R. and Trinidad, A. (2020) ‘The decentralization of race: tracing the dilution of racial equity in educational policy’, International Journal of Qualitative Studies in Education, 33, 4, 465-490 https://doi.org/10.1080/09518398.2019.1681538
Paul comes from a Political Science background and started off his project trying to understand why politicians don’t make good policy. He uses a lot of Political Science theory to understand the policy process (what MPP students have been learning) and theory from Public Policy about how to make the policy process better.
I come from a Social Policy background. I presume policy will be bad, and approach policy analysis from a normative position, analysing and criticising it from theoretical and critical perspectives.
I specialize in the study of public policy and policymaking. I ‘synthesise’ and use policy concepts and theories to ask: how do policy processes work, and why?
Most theories and concepts – summarized in 1000 and 500 words – engage with that question in some way.
As such, I primarily seek to describe and explain policymaking, without spending much time thinking about making it better (unless asked to do so, or unless I feel very energetic).
In particular, I can give you a decent account of how all of these policy theories relate to each other, which is more important that it first seems.
That story provides context for applications to the agendas taken forward by other disciplines or professions.
The most obvious example is ‘evidence based policymaking’: my role is to explain why it is little more than a political slogan, and why people should not expect (or indeed want) it to exist, not to lobby for its existence
Also working on similar stories in relation to policy learning and policy design: my role is to highlight dilemmas and cautionary tales, not be a policy designer.
The politics of policymaking research
Most of the theories I describe relate to theory-informed empirical projects, generally originating from the US, and generally described as ‘positivist’ in contrast to (say) ‘interpretive’ (or, say, ‘constructivist’).
However, there are some interesting qualifications:
Some argue that these distinctions are overcooked (or, I suppose, overboiled)
Some try to bring in postpositivist ideas to positivist networks (NPF)
Some emerged from ‘critical policy analysis’ (SCPD)
The initial podcast tells a story about MPP development, in which I used to ask students to write policy analyses (1st semester) without explaining what policy analysis was, or how to do it. My excuse is that the punchline of the module was: your account of the policy theories/ policy context is more important than your actual analysis (see the Annex to the book).
Since then, I have produced a webpage – 750 – which:
summarises the stories of the most-used policy analysis texts (e.g. Bardach) which identify steps including: define the problem; identify solutions; use values to compare trade-offs between solutions; predict their effects; make a recommendation
relates those texts to policy theories, to identify how bounded rationality and complexity change that story (and the story of the policy cycle)
relates both to ‘critical’ policy analysis and social science texts (some engage directly – like Stone, like Bacchi – while some provide insights – such as on critical race theory – without necessarily describing ‘policy analysis’)
A description of ‘critical’ approaches is fairly broad, but I think they tend to have key elements in common:
a commitment to use research to improve policy for marginalized populations (described by Bacchi as siding with the powerless against the powerful, usually in relation to class, race, ethnicity, gender, sexuality, disability)
analysing policy to identify: who is portrayed positively/negatively; who benefits or suffers as a result
analysing policymaking to identify: whose knowledge counts (e.g. as high quality and policy relevant), who is included or excluded
identifying ways to challenge (a) dominant and damaging policy frames and (b) insulated/ exclusive versus participatory/ inclusive forms of policymaking
If so, I would see these three approaches as ways to understand and engage with policymaking that could be complementary or contradictory. In other words, I would warn against assuming one or the other.
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 change is a central concern of policy researchand 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:
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.
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 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.
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.
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.
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.
Trust is essential during a crisis. It is necessary for cooperation. Cooperation helps people coordinate action, to reduce the need for imposition. It helps reduce uncertainty in a complex world. It facilitates social order and cohesiveness. In a crisis, almost-instant choices about who to trust or distrust make a difference between life and death.
Put simply, we need to trust: experts to help us understand and address the problem, governments to coordinate policy and make choices about levels of coercion, and each other to cooperate to minimise infection.
Yet, there are three unresolved problems with understanding trust in relation to coronavirus policy.
What does trust really mean?
Trust is one of those words that could mean everything and nothing. We feel like we understand it intuitively, but would also struggle to define it well enough to explain how exactly it works. For example, in social science, there is some agreement on the need to describe individual motivation, social relationships, and some notion of the ‘public good’:
the production of trust helps boost the possibility of cooperation, partly by
reducing uncertainty (low information about a problem) and ambiguity (low agreement on how to understand it) when making choices, partly by
helping you manage the risk of making yourself vulnerable when relying on others, particularly when
people demonstrate trustworthiness by developing a reputation for competence, honesty, and/ or reliability, and
you combine cognition and emotion to produce a disposition to trust, and
social and political rules facilitate this process, from the formal and well-understood rules governing behaviour to the informal rules and norms shaping behaviour.
As such, trust describes your non-trivial belief in the reliability of other people, organisations, or processes. It facilitates the kinds of behaviour that are essential to an effective response to the coronavirus, in which we need to:
Make judgements about the accuracy of information underpinning our choices to change behaviour (such as from scientific agencies).
Assess the credibility of the people with whom we choose to cooperate or take advice (such as more or less trust in each country’s leadership).
Measure the effectiveness of the governments or political systems to which we pledge our loyalty.
Crucially, in most cases, people need to put their trust in actions or outcomes caused by people they do not know, and the explanation for this kind of trust is very different to trusting people you know.
What does trust look like in policymaking?
Think of trust as a mechanism to boost cooperation and coalition formation, help reduce uncertainty, and minimise the ‘transactions costs’ of cooperation (for example, monitoring behaviour, or producing or enforcing contracts). However, uncertainty is remarkably high because the policy process is not easy to understand. We can try to understand the ‘mechanisms’ of trust, to boost cooperation, with reference to these statements about trustees and the trusted:
Individuals need to find ways to make choices about who to trust and distrust.
However, they must act within a complex policymaking environment in which they have minimal knowledge of what will happen and who will make it happen.
To respond effectively, people seek ways to cooperate with others systematically, such as by establishing formal and informal rules.
People seeking to make and influence policy must act despite uncertainty about the probability of success or risk of failure. In a crisis, it happens almost instantly. People generate beliefs about what they want to happen and how their reliance on others can help it happen. This calculation depends on:
Another person or organisation’s reputation for being trustworthy, allowing people the ability to increase certainty when they calculate the risk of engagement.
The psychology of trust and perceptions of another actor’s motives. To some extent, people gather information and use logic to determine someone’s competence. However, they also use gut feeling or emotion to help them decide to depend on someone else. They may also trust a particular source if the cognitive load is low, such as because (a) the source is familiar (e.g. a well-known politician or a celebrity, or oft-used source), or (b) the information is not challenging to remember or accept.
If so, facilitators of trust include:
People share the same characteristics, such as beliefs, norms, or expectations.
Some people have reputations for being reliable, predictable, honest, competent, and/ or relatively selfless.
Good experiences of previous behaviour, including repeated interactions that foster rewards and help predict future risk (with face to face contact often described as particularly helpful).
People may trust people in a position of authority (or the organisation or office), such as an expert or policymaker (although perhaps the threat of rule enforcement is better understood as a substitute for trust, and in practice it is difficult to spot the difference).
High levels of trust are apparent when effective practices – built on reciprocity, emotional bonds, and/ or positive expectations – become the norms or formalised and written down for all to see and agree. High levels of distrust indicate a need to deter the breach of agreements, by introducing expectations combined with sanctions for not behaving as expected.
Who should you trust?
These concepts do not explain fully why people trust particular people more than others, or help us determine who you should trust during a crisis.
Rather, first, they help us reflect on the ways in which people have been describing their own thought processes (click here, and scroll to ‘Limiting the use of evidence’), such as trusting an expert source because they: (a) have a particular scientific background, (b) have proven to be honest and reliable in the past, (c) represent a wider scientific profession/ community, (d) are part of a systematic policymaking machinery, (e) can be held to account for their actions, (f) are open about the limits to their knowledge, and/or (g) engage critically with information to challenge simplistic rushes to judgement. Overall, note how much trust relates to our minimal knowledge about their research skills, prompting us to rely on an assessment of their character or status to judge their behaviour. In most cases, this is an informal process in which people may not state (or really know) why they trust or distrust someone so readily.
Then, we can reflect on who we trust, and why, and if we should change how we make such calculations during a crisis like the coronavirus. Examples include:
A strong identity with a left or right wing cause might prompt us only to trust people from one political party. This thought process may be efficient during elections and debates, but does it work so well during a crisis necessitating so high levels of cross-party cooperation?
People may be inclined to ignore advice because they do not trust their government, but maybe (a) high empathy for their vulnerable neighbours, and (b) low certainty about the impact of their actions, should prompt them to trust in government advice unless they have a tangible reason not to (while low empathy helps explain actions such as hoarding).
Government policy is based strongly on the extent to which policymakers trust people to do the right thing. Most debates in liberal democracies relate to the idea that (a) people can be trusted, so give advice and keep action voluntary, or cannot be trusted, so make them do the right thing, and that (b) citizens can trust their government. In other words, it must be a reciprocal relationship (see the Tweets in Step 3).
Finally, governments make policy based on limited knowledge and minimal control of the outcomes, and they often respond with trial-and-error strategies. The latter is fine if attention to policy is low and trust in government sufficiently high. However, in countries like the UK and US, each new choice prompts many people to question not only the competence of leaders but also their motivation. This is a worrying development for which everyone should take some responsibility.
Paul Cairney (2020) ‘The UK Government’s COVID-19 policy: assessing evidence-informed policy analysis in real time’, British Politicshttps://rdcu.be/b9zAk (PDF)
The coronavirus feels like a new policy problem that requires new policy analysis. The analysis should be informed by (a) good evidence, translated into (b) good policy. However, don’t be fooled into thinking that either of those things are straightforward. There are simple-looking steps to go from defining a problem to making a recommendation, but this simplicity masks the profoundly political process that must take place. Each step in analysis involves political choices to prioritise some problems and solutions over others, and therefore prioritise some people’s lives at the expense of others.
My article in British Politics takes us through those steps in the UK, and situates them in a wider political and policymaking context. This post is shorter, and only scratches the surface of analysis.
5 steps to policy analysis
Define the problem.
Perhaps we can sum up the initial UK government approach as: (a) the impact of this virus and illness will be a level of death and illness that could overwhelm the population and exceed the capacity of public services, so (b) we need to contain the virus enough to make sure it spreads in the right way at the right time, so (c) we need to encourage and make people change their behaviour (primarily via hygiene and social distancing). However, there are many ways to frame this problem to emphasise the importance of some populations over others, and some impacts over others.
Identify technically and politically feasible solutions.
Solutions are not really solutions: they are policy instruments that address one aspect of the problem, including taxation and spending, delivering public services, funding research, giving advice to the population, and regulating or encouraging changes to social behaviour. Each new instrument contributes an existing mix, with unpredictable and unintended consequences. Some instruments seem technically feasible (they will work as intended if implemented), but will not be adopted unless politically feasible (enough people support their introduction). Or vice versa. From the UK government’s perspective, this dual requirement rules out a lot of responses.
Use values and goals to compare solutions.
Typical judgements combine: (a) broad descriptions of values such as efficiency, fairness, freedom, security, and human dignity, (b) instrumental goals, such as sustainable policymaking (can we do it, and for how long?), and political feasibility (will people agree to it, and will it make me more or less popular or trusted?), and (c) the process to make choices, such as the extent to which a policy process involves citizens or stakeholders (alongside experts) in deliberation. They combine to help policymakers come to high profile choices (such as the balance between individual freedom and state coercion), and low profile but profound choices (to influence the level of public service capacity, and level of state intervention, and therefore who and how many people will die).
Predict the outcome of each feasible solution.
It is difficult to envisage a way for the UK Government to publicise all of the thinking behind its choices (Step 3) and predictions (Step 4) in a way that would encourage effective public deliberation. People often call for the UK Government to publicise its expert advice and operational logic, but I am not sure how they would separate it from their normative logic about who should live or die, or provide a frank account without unintended consequences for public trust or anxiety. If so, one aspect of government policy is to keep some choices implicit and avoid a lot of debate on trade-offs. Another is to make choices continuously without knowing what their impact will be (the most likely scenario right now).
Make a choice, or recommendation to your client.
Your recommendation or choice would build on these four steps. Define the problem with one framing at the expense of the others. Romanticise some people and not others. Decide how to support some people, and coerce or punish others. Prioritise the lives of some people in the knowledge that others will suffer or die. Do it despite your lack of expertise and profoundly limited knowledge and information. Learn from experts, but don’t assume that only scientific experts have relevant knowledge (decolonise; coproduce). Recommend choices that, if damaging, could take decades to fix after you’ve gone. Consider if a policymaker is willing and able to act on your advice, and if your proposed action will work as intended. Consider if a government is willing and able to bear the economic and political costs. Protect your client’s popularity, and trust in your client, at the same time as protecting lives. Consider if your advice would change if the problem seemed to change. If you are writing your analysis, maybe keep it down to one sheet of paper (in other words, fewer words than in this post up to this point).
Policy analysis is not as simple as these steps suggest, and further analysis of the wider policymaking environment helps describe two profound limitations to simple analytical thought and action.
Policymakers must ignore almost all evidence
The amount of policy relevant information is infinite, and capacity is finite. So, individuals and governments need ways to filter out almost all of it. Individuals combine cognition and emotion to help them make choices efficiently, and governments have equivalent rules to prioritise only some information. They include: define a problem and a feasible response, seek information that is available, understandable, and actionable, and identify credible sources of information and advice. In that context, the vague idea of trusting or not trusting experts is nonsense, and the larger post highlights the many flawed ways in which all people decide whose expertise counts.
They do not control the policy process.
Policymakers engage in a messy and unpredictable world in which no single ‘centre’ has the power to turn a policy recommendation into an outcome.
There are many policymakers and influencers spread across a political system. For example, consider the extent to which each government department, devolved governments, and public and private organisations are making their own choices that help or hinder the UK government approach.
Most choices in government are made in ‘subsystems’, with their own rules and networks, over which ministers have limited knowledge and influence.
The social and economic context, and events, are largely out of their control.
The take home messages (if you accept this line of thinking)
The coronavirus is an extreme example of a general situation: policymakers will always have very limited knowledge of policy problems and control over their policymaking environment. They make choices to frame problems narrowly enough to seem solvable, rule out most solutions as not feasible, make value judgements to try help some more than others, try to predict the results, and respond when the results do not match their hopes or expectations.
This is not a message of doom and despair. Rather, it encourages us to think about how to influence government, and hold policymakers to account, in a thoughtful and systematic way that does not mislead the public or exacerbate the problem we are seeing. No one is helping their government solve the problem by saying stupid shit on the internet (OK, that last bit was a message of despair).
The article (PDF) sets out these arguments in much more detail, with some links to further thoughts and developments.
This series of ‘750 words’ posts summarises key texts in policy analysis and tries to situate policy analysis in a wider political and policymaking context. Note the focus on whose knowledge counts, which is not yet a big feature of this crisis.
These series of 500 words and 1000 words posts (with podcasts) summarise concepts and theories in policy studies.
These posts introduce you to key concepts in the study of public policy. They are all designed to turn a complex policymaking world into something simple enough to understand. Some of them focus on small parts of the system. Others present ambitious ways to explain the system as a whole. The wide range of concepts should give you a sense of a variety of studies out there, but my aim is to show you that these studies have common themes.