Wouldn’t it be nice if policy scholars and professionals could have frequent and fruitful discussions about policy and policymaking? Both professions could make valuable contributions to our understanding of policy design in a wider political context.
However, it is notoriously difficult to explain what policy is and how it is made, and academics and practitioners may present very different perspectives on what policymakers or governments do. Without a common reference point, how can they cooperate to discuss how to (say) improve policy or policymaking?
One starting point is to visualize policymaking to identify overlaps in perspectives. To that end, if academics and policymakers were to describe ‘the policy process’, could they agree on what it looks like? To help answer this question, in this post I’m presenting some commonly-used images in policy research, then inviting you to share images that you would use to sum up policy work.
Why produce different images of policy processes?
One obstacle to a shared description is that we need different images for different aims, including:
To describe and explain what policymakers do. Academics describe one part of a complex policy process, accompanied by a technical language to understand each image.
To describe what policymakers need to do. Practitioners visualise a manageable number of aims or requirements (essential steps, stages, or functions), accompanied by a professional in-house language (such as in the Green Book).
To describe what they would like to do. Governments produce images of policymaking to tell stakeholders or citizens what they do, accompanied by an aspirational language related to what is expected of elected governments.
Why seek a common image? Would it help or hinder discussion?
If we have such different aims, is it (a) possible, and (b) desirable to produce an image that satisfies each aim? For example, it is possible but undesirable to use the policy cycle image to that end.
This image may be shared by academics and practitioners, but it means something different each time:
1.Most policy scholars use the cycle to describe what does not happen. It is a teaching tool, to (a) describe the ideal-type, (b) explain its descriptive inaccuracy, and (c) introduce the search for better models, which (d) might help to visualise a messier reality (for example, by using Spirograph).
2. Practitioners often find it more useful to sum up the steps they need to take – to get from defining to addressing a policy problem. For example, the ROAMEF cycle looks fairly similar to the one in my textbook. However, most policymakers would describe their actual steps in different ways or – more importantly – accept that no-one really makes policy this way.
3. Policymakers find it useful to project to the public that their process is orderly. You will find many versions of this image in UK government and European Commission documents, using images to summarise how they would like to be seen.
In each case, the policy cycle image represents a confusing mix of (1) valuable to prompt further discussion, and (2) not valuable because it is so misleading. Indeed, even (one small part of) the European Commission presents a very different image, to superimpose an unwieldy mess onto the traditional cyclical image.
What images do academics use to explain complexity?
While an image of messy policymaking makes a simple point well (policymaking is far messier than the cycle suggests), it does not do much else. What other images convey this complexity while also providing specific insights to guide research or action?
The multiple streams framework: much like a space launch, major policy change will not happen unless many requirements come together simultaneously. In policymaking, the requirements are: attention rises to a problem, a feasible solution already exists, and policymakers have the motive and opportunity to select it. Policy entrepreneurs may help, but as surfers riding a wave, not controllers of the sea (apologies for the mixed metaphors).
Take home message from image 1: ‘stages’ of a policy cycle matter, but the process (1) is not linear, and (2) does not lead inevitably to policy change.
Punctuated equilibrium theory: this image sums up the distribution of policy change in liberal democracies: there is a huge number of very small changes, and a very small number of huge changes. This distribution is akin to the frequency and magnitude of earthquakes! What is the cause? (1) Policymaker attention to problems does not relate strongly to (a) the size of the problem, or (b) the available information. (2) A lack of attention results – in most cases – in limited change (since high attention may be required to help overcome existing rules and practices).
Take home message from image 2: Policymaking is largely about governments managing existing policies which can change very little for long periods. Major changes can happen, but they are rare. They can be explained, but are not easy to predict.
Visualising important factors
The advocacy coalition framework flow diagram: people join ‘advocacy coalitions’ to turn their beliefs into policy and they compete with other coalitions to influence policy in subsystems (specialist networks of policymakers and influencers). Policy change relates to how coalitions manage internal dynamics (such as learning from policy failure) or deal with external events (such as a crisis or change of government).
Take home message from image 3: Most policy is processed in a large number of specialist policy networks, which are more or less insulated from the wider political system.
Visualising concepts in a non-threatening way
The blue turtle: – my aim is to introduce concepts in a visually pleasing way (to compete with the policy cycle). The image provides an introductory story about how policymakers deliberate and make choices (drawing on psychology to show how they frame problems and identify trusted sources of information) while surrounded by their policymaking environment (consisting of many policy actors spread across many venues, each with their own rules, networks, and reference points).
Take home message from image 4: Policy is processed by many different ‘centres’ – each with their own ways of working – rather than one single central government. The overall effect cannot be summed up by one single cycle of activity, and the overall ‘policy mix’ does not emerge from one source.
What images do you find more useful?
My main aim has been to present these images to prompt discussion: what does each image say about how we describe policymaking, our role in policy processes, and how we would like others to understand what we do? Do you prefer other images, such as to describe the ‘strategic triangle’?
I would welcome your thoughts in the comments below. Or, if you have some valuable images to share, please send them to email@example.com
The next post
My plan is to write a follow-up post to collate many more images, with early suggestions including:
When we teach policy analysis, we focus on how to be a policy analyst or how to situate the act of policy analysis within a wider policymaking context. Ideally, students would learn about both. This aim is central to Lasswell’s vision for the policy sciences, in which the analysis of policy and policymaking informs analysis for policy, and both are essential to the pursuit of human equality and dignity (Lasswell, 1951; 1956; 1971; see Cairney and Weible, 2017).
There is the potential to achieve this vision for the policy sciences. Policy analysis texts focus on the individual and professional skills required to act efficiently and effectively in a time-pressured political environment. Further, they are supported by the study of policy analysts to reflect on how analysis takes place, and policy is made, in the real world (Radin, 2019; Brans et al, 2017; Thissen and Walker, 2013; Geva-May, 2005). The next steps would be to harness the wealth of policy concept- and theory-informed studies to help understand how real-world contexts inform policy analysis insights.
First, almost all mainstream policy theories assume or demonstrate that there is no such thing as a policy cycle. It would be misleading to suggest that the policy process consists of clearly defined and well-ordered stages of policymaking, from defining problems and generating solutions to implementing solutions and evaluating their effects. If so, there is no clear route to influence via analysis unless we understand a far messier reality. In that context, how can policy analysts understand their complex policymaking environment, and what skills and strategies do they need to develop to engage effectively? These discussions may be essential to preventing the demoralisation of analysts: if they do not learn in advance about the processes and factors that can minimise their influence, how can they generate realistic expectations?
Second, if the wider aim is human equality and dignity, insights from critical policy analysis are essential. They help analysts think about what those values mean, how to identify and support marginalised populations, and how policy analysis skills and techniques relate to those aims. In particular, they warn against treating policy analysis as a technocratic profession devoid of politics. This rationalist story may contribute to exclusive research gathering practices, producing too-narrow definitions of problems, insufficient consideration of feasible solutions, and recommendations made about target populations without engaging with the people they claim to serve (Bacchi, 2009; Stone, 2012).
However, this aim is much easier described than achieved. Policy analysis texts, focusing on how to do it, often use insights from policy studies but without fully explaining key concepts and theories or exploring their implications. There is not enough time and space to do justice to every element, from the technical tools of policy analysis (including cost-benefit analysis) to the empirical findings from policy theories and normative insights from critical policy analysis approaches (e.g. Weimer and Vining, 2017 is already 500 pages long). Policy process research, focusing on what happens, may have practical implications for analysts. However, they are often hidden behind layers of concepts and jargon, and most of their authors seem uninterested in describing the normative importance of, or practical lessons from, theory-informed empirical studies. The cumulative size of this research is overwhelming and beyond the full understanding of experienced specialist scholars. Further, it is difficult to recommend a small number of texts to sum up each approach, which makes it difficult to predict how much time and energy it would take to understand this field, or to demonstrate the payoff from that investment. In addition, critical policy analysis is essential, but often ignored in policy analysis texts, and the potential for meaningful conversations between critical or interpretive versus mainstream policy scholars remains largely untapped (e.g. Durnova and Weible, 2020) or resisted (e.g. Jones and Radaelli, 2016).
In that context, policy analysis students embody the problem of ‘bounded rationality’ described famously by Simon (1976). Simon’s phrase ‘to satisfice’ sums up a goal-oriented response to bounded rationality: faced with the inability to identify, process, or understand all relevant information, they seek ways to gather enough information to inform ‘good enough’ choices. More recently, policy studies have sought to incorporate insights from individual human, social, and organisational psychology to understand (1) the cognitive shortcuts that humans use, including gut-level instinct, habit, familiarity with an issue, deeply-held beliefs, and emotions, and (2) their organisation’s equivalents (organisations use rules and standard operating procedures to close off information searches and limit analysis – Koski and Workman, 2018). Human cognitive shortcuts can be described negatively as cognitive biases or more positively as ‘thinking fast and slow’ (Kahneman, 2012) or ‘fast and frugal heuristics’ (Gigerenzer, 2001). However, the basic point remains: if people seek shortcuts to information, we need to find ways to adapt to their ways of thinking, rather than holding onto an idealised version of humans that do not exist in the real world (Cairney and Kwiatkowski, 2017).
While these insights focus on policymakers, they are also essential to engaging with students. Gone – I hope – are the days of lecturers giving students an overwhelmingly huge reading list and expecting them to devour every source before each class. This approach may help some students but demoralise many others, especially since it seems inevitable that students’ first engagement with specialist texts and technical jargon will already induce fears about their own ignorance. Rather, we should base teaching on a thoughtful exploration of how much students can learn about the wider policy analysis context, focusing on (1) the knowledge and skills they already possess, (2) the time they have to learn, and (3) how new knowledge or skills would relate to their ambitions. For example, if students are seeking fast and frugal heuristics to learn about policy analysis, how can we help?
To help answer this question, I focus on what students should learn, can learn, and how blog posts and coursework can contribute to that learning. First, I describe the valuable intersection between policy analysis, policy process research, and critical policy analysis to demonstrate the potential payoffs to wider insights. In other words, what should policy analysis students learn from mainstream policy process research and critical policy analysis? Second, I describe the rationale for the blog that I developed in tandem with teaching public policy. I taught initially at an undergraduate level as part of a wider politics programme, before developing a Master of Public Policy and contributing to shorter executive courses and one-off workshops. This range of audiences matters, since the answer to the question ‘what can people learn?’ will vary according to their existing knowledge and time. Third, I summarise the rationale for the coursework that I use to encourage the application of public policy theories and knowledge to policy analysis (as part of a wider degree programme), including skills in critical thinking about policymaking dilemmas, to accompany more specialist research and analytical skills.
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).
This post is a shortened version of The Politics of Policy Analysis Annex A. It shows how to use insights from policy process research in policy analysis and policymaking coursework (much like the crossover between Scooby-Doo and Batman). It describes a range of exercises, including short presentations, policy analysis papers, blog posts, and essays. In each case, it explains the rationale for each exercise and the payoff to combining them.
If you prefer me to describe these insights less effectively, there is also a podcast:
One step to combining policy analysis and policy process research is to modify the former according to the insights of the latter. In other words, consider how a ‘new policy sciences’ inspired policy analysis differs from the analyses already provided by 5-step guides.
It could turn out that the effects of our new insights on a policy briefing could be so subtle that you might blink and miss them. Or, there are so many possibilities from which to choose that it is impossible to provide a blueprint for new policy science advice. Therefore, I encourage students to be creative in their policy analysis and reflective in their assessment of their analysis. Our aim is to think about the skills you need to analyse policy, from producing or synthesising evidence, to crafting an argument based on knowing your audience, and considering how your strategy might shift in line with a shifting context.
To encourgage creativity, I set a range of tasks so that students can express themselves in different ways, to different audiences, with different constraints. For example, we can learn how to be punchy and concise from a 3-minute presentation or 500-word blog, and use that skill to get to the point more quickly in policy analysis or clarify the research question in the essay.
The overall effect should be that students can take what they have learned from each exercise and use it for the others.
In each section below, I reproduce the ways in which I describe this mix of coursework to students then, in each box, note the underlying rationale.
1. A 3-minute spoken presentation to your peers in a seminar.
In 3 minutes, you need to identify a problem, describe one or more possible solutions, and end your presentation in a convincing way. For example, if you don’t make a firm recommendation, what can you say to avoid looking like you are copping out? Focus on being persuasive, to capture your audience’s imagination. Focus on the policy context, in which you want to present a problem as solvable (who will pay attention to an intractable problem?) but not make inflated claims about how one action can solve a major problem. Focus on providing a memorable take home message.
The presentation can be as creative as you wish, but it should not rely on powerpoint in the room. Imagine that none of the screens work or that you are making your pitch to a policymaker as you walk along the street: can you make this presentation engaging and memorable without any reference to someone else’s technology? Can you do it without just reading out your notes? Can you do it well in under 3 minutes? We will then devote 5 minutes to questions from the audience about your presentation. Being an active part of the audience – and providing peer review – is as important as doing a good presentation of your own.
BOX A1: Rationale for 3-minute presentation.
If students perform this task first (before the coursework is due), it gives them an initial opportunity to see how to present only the most relevant information, and to gauge how an audience responds to their ideas. Audience questions provide further peer-driven feedback. I also plan a long seminar to allow each student (in a group of 15-20 people) to present, then ask all students about which presentation they remember and why. This exercise helps students see that they are competing with each other for limited policymaker attention, and learn from their peers about what makes an effective pitch. Maybe you are wondering why I discourage powerpoint. It’s largely because it will cause each presenter to go way over time by cramming in too much information, and this problem outweighs the benefit of being able to present an impressive visualisation. I prefer to encourage students to only tell the audience what they will remember (by only presenting what they remember).
2. A policy analysis paper, and 3. A reflection on your analysis
Provide a policy analysis paper which has to make a substantive argument or recommendation in approximately two pages (1000 words), on the assumption that busy policymakers won’t read much else before deciding whether or not to pay attention to the problem and your solutions. Then provide a reflection paper (also approximately 1000 words) to reflect your theoretical understanding of the policy process. You can choose how to split the 2000 word length, between analysis and reflection. You can give each exercise 1000 each (roughly a 2-page analysis), provide a shorter analysis and more reflection, or widen the analysis and reject the need for conceptual reflection. The choice is yours to make, as long as you justify your choice in your reflection.
When writing policy analysis, I ask you to keep it super-short on the assumption that you have to make your case quickly to people with 99 other things to do. For example, what can you tell someone in one paragraph or a half-page to get them to read all 2 pages? It is tempting to try to tell someone everything you know, because everything is connected and to simplify is to describe a problem simplistically. Instead, be smart enough to know that such self-indulgence won’t impress your audience. In person, they might smile politely, but their eyes are looking at the elevator lights. In writing, they can skim your analysis or simply move on. So, use these three statements to help you focus less on your need to supply information and more on their demand:
Your aim is not to give a full account of a problem. It is to get powerful people to care about it.
Your aim is not to give a painstaking account of all possible solutions. It is to give a sense that at least one solution is feasible and worth pursuing.
Your guiding statement should be: policymakers will only pay attention to your problem if they think they can solve it, and without that solution being too costly.
Otherwise, I don’t like to give you too much advice because I want you to be creative about your presentation; to be confident enough to take chances and feel that you’ll see the reward of making a leap. At the very least, you have three key choices to make about how far you’ll go to make a point:
Who is your audience? Our discussion of the limits to centralised policymaking suggest that your most influential audience will not necessarily be an elected policymaker, but who else would it be?
How ‘manipulative’ should you be? Our discussions of ‘bounded rationality’ and ‘evidence-based policymaking’ suggest that policymakers combine ‘rational’ and ‘irrational’ shortcuts to gather information and make choices. So, do you appeal to their desire to set goals and gather a lot of scientific information, make an emotional appeal, or rely on Riker-style heresthetics?
What is your role? Contemporary discussions of science advice to government highlight unresolved debates about the role of unelected advisors: should you simply lay out some possible solutions or advocate one solution strongly?
For our purposes, there are no wrong answers to these questions. Instead, I want you to make and defend your decisions. That is the aim of your policy paper ‘reflection’: to ‘show your work’. You still have some room to be creative in your reflection: tell me what you know about policy theory and how it informed your decisions. Here are some examples, but it is up to you to decide what to highlight:
Show how your understanding of policymaker psychology helped you decide how to present information on problems and solutions.
Extract insights from policy theories, such as from punctuated equilibrium theory on policymaker attention, multiple streams analysis on timing and feasibility, or the NPF on how to tell persuasive stories.
Explore the implications of the lack of ‘comprehensive rationality’ and absence of a ‘policy cycle’: feasibility is partly about identifying the extent to which a solution is ‘doable’ when central governments have limited powers. What ‘policy style’ or policy instruments would be appropriate for the solution you favour?
I use the following questions to guide the marking on the policy paper: Tailored properly to a clearly defined audience? Punchy and concise summary? Clearly defined problem? Good evidence or argument behind the solution? Clear recommendations backed by a sense that the solution is feasible? Evidence of substantial reading, accompanied by well explained further reading?
In my experience of marking, successful students gave a very clear and detailed account of the nature and size of the policy problem. The best reports used graphics and/ or statistics to describe the problem in several ways. Some identified a multi-faceted problem – such as in health outcomes, and health inequalities – without presenting confusing analysis. Some were able to present an image of urgency, to separate this problem from the many others that might grab policymaker attention. Successful students presented one or more solutions which seemed technically and/ or politically feasible. By technically feasible, I mean that there is a good chance that the policy will work as intended if implemented. For example, they provided evidence of its success in a comparable country (or in the past) or outlined models designed to predict the effects of specific policy instruments. By politically feasible, I mean that you consider how open your audience would be to the solution, and how likely the suggestion is to be acceptable to key policymakers. Some students added to a good discussion of feasibility by comparing the pros/ cons of different scenarios. In contrast, some relatively weak reports proposed solutions which were vague, untested, and/ or not likely to be acted upon.
BOX A2: Rationale for policy analysis and reflection
Students already have 5-step policy analysis texts at their disposal, and they give some solid advice about the task. However, I want to encourage students to think more about how their knowledge of the policy process will guide their analysis. First, what do you do if you think that one audience will buy your argument, and another reject it wholeheartedly? Just pretend to be an objective analyst and put the real world in the ‘too hard’ pile? Or, do you recognise that policy analysts are political actors and make your choices accordingly? For me, an appeal to objectivity combined with insufficient recognition of the ways in which people respond emotionally to information, is a total cop-out. I don’t want to contribute to a generation of policy analysts who provide long, rigorous, and meticulous reports that few people read and fewer people use. Instead, I want students to show me how to tell a convincing story with a clear moral, or frame policy analysis to grab their audience’s attention and generate enthusiasm to try to solve a problem. Then, I want them to reflect on how they draw the line between righteous persuasion and unethical manipulation.
Second, how do you account for policymaking complexity? You can’t assume that there is a cycle in which a policymaker selects a solution and it sets in train a series of stages towards successful implementation. Instead, you need to think about the delivery of your policy as much as the substance. Students have several choices. In some cases, they will describe how to deliver policy in a multi-level or multi-centric environment, in which, say, a central government actor will need to use persuasion or cooperation rather than command-and-control. Or, if they are feeling energetic, they might compare a top-down delivery option with support for Ostrom-style polycentric arrangements. Maybe they’ll recommend pilots and/ or trial and error, to monitor progress continuously instead of describing a one-shot solution. Maybe they’ll reflect on multiple streams analysis and think about how you can give dependable advice in a policy process containing some serendipity. Who knows? Policy process research is large and heterogeneous, which opens the possibility for some creative solutions that I won’t be able to anticipate in advance.
4. One kind of blog post (for the policy analysis)
Write a short and punchy blog post which recognises the need to make an argument succinctly and grab attention with the title and first sentence/ paragraph, on the assumption that your audience will be reading it on their phone and will move on to something else quickly. In this exercise, your blog post is connected to your policy analysis. Think, for example, about how you would make the same case for a policy solution to a wider ‘lay’ audience. Or, use the blog post to gauge the extent to which your client could sell your policy solution. If they would struggle, should you make this recommendation in the first place?
Your blog post audience is wider than your policy analysis audience. You are trying to make an argument that will capture the attention of a larger group of people who are interested in politics and policy, but without being specialists. They will likely access your post from Twitter/ Facebook or via a search engine. This constraint produces a new requirement, to: present a punchy title which sums up the whole argument in under 280 characters (a statement is often better than a vague question); to summarise the whole argument in approximately 100 words in the first paragraph (what is the problem and solution?); then, to provide more information up to a maximum of 500 words. The reader can then be invited to read the whole policy analysis.
The style of blog posts varies markedly, so you should consult many examples before attempting your own (for example, compare the LSE with The Conversation and newspaper blogs to get a sense of variations in style). When you read other posts, take note of their strengths and weaknesses. For example, many posts associated with newspapers introduce a personal or case study element to ground the discussion in an emotional appeal. Sometimes this works, but sometimes it causes the reader to scroll down quickly to find the main argument. Perhaps ironically, I recommend storytelling but I often skim past people’s stories. Many academic posts are too long (well beyond your 500 limit), take too long to get to the point, and do not make explicit recommendations, so you should not emulate them. You should aim to be better than the scholars whose longer work you read. You should not just chop down your policy analysis to 500 words; you need a new kind of communication.
Hopefully, by the end of this fourth task, you will appreciate the transferable life skills. I have generated some uncertainty about your task to reflect the sense among many actors that they don’t really know how to make a persuasive case and who to make it to. We can follow some basic Bardach-style guidance, but a lot of this kind of work relies on trial-and-error. I maintain a short word count to encourage you to get to the point, and I bang on about ‘stories’ in modules to encourage you to present a short and persuasive story to policymakers.
This process seems weird at first, but isn’t it also intuitive? For example, next time you’re in my seminar, measure how long it takes you to get bored and look forward to the weekend. Then imagine that policymakers have the same attention span as you. That’s how long you have to make your case! Policymakers are not magical beings with an infinite attention span. In fact, they are busier and under more pressure than us, so you need to make your pitch count.
BOX A3: Rationale for blog post 1
This exercise forces students to make their case in 500 words. It helps them understand the need to communicate in different ways to different audiences. It suggests that successful communication is largely about knowing how your audience consumes information, rather than telling people all you know. I gauge success according to questions such as: Punchy and eye grabbing title? Tailored to an intelligent ‘lay’ audience rather than a specific expert group? Clearly defined problem? Good evidence or argument behind the solution? Clear recommendations backed by a sense that the solution is feasible? Well embedded weblinks to further relevant reading?
5. Writing a theory-informed essay
I tend to set this simple-looking question for coursework in policy modules: what is policy, how much has it changed, and why? Students get to choose the policy issue, timeframe, political system, and relevant explanatory concepts.
On the face of it, it looks very straightforward. Give it a few more seconds, and you can see the difficulties:
We spend a lot of time in class agreeing that it seems almost impossible to define policy
There are many possible measures of policy change
There is an almost unmanageable number of models, concepts, and theories to use to explain policy dynamics.
I try to encourage some creativity when solving this problem, but also advise students to keep their discussion as simple and jargon-free as possible (often by stretching an analogy with competitive diving, in which a well-executed simple essay can score higher than a belly-flopped hard essay).
Choosing a format: the initial advice
Choose a policy area (such as health) or issue (such as alcohol policy).
Describe the nature of policy, and the extent of policy change, in a particular time period (such as in a particular era, after an event or constitutional change, or after a change in government).
Select one or more policy concepts or theory to help structure your discussion and help explain how and why policy has changed.
For example, a question might be: What is tobacco policy in the UK, how much has it changed since the 1980s, and why? I use this example because I try to answer that question myself, even though some of my work is too theory-packed to be a good model for a student essay (Cairney, 2007 is essentially a bad model for students).
Choosing a format: the cautionary advice
You may be surprised about how difficult it is to answer a simple question like ‘what is policy?’ and I will give you a lot of credit for considering how to define and measure it; by identifying, for example, the use of legislation/ regulation, funding, staff, and information sharing, and/ or by considering the difference between, say, policy as a statement of intent or a long term outcome. In turn, a good description and explanation of policy change is difficult. If you are feeling ambitious, you can go further, to compare, say, two issues (such as tobacco and alcohol) or places (such UK Government policy and the policy of another country), but sometimes a simple and narrow discussion can be more effective. Similarly, you can use many theories or concepts to aid explanation, but one theory may do. Note that (a) your description of your research question, and your essay structure, is more important than (b) your decision on what topic or concepts to use.
BOX A4: Rationale for the essay
The wider aim is to encourage students to think about the relationship between differentperspectives on policy theory and analysis. For example, in a blog and policy analysis paper they try to generate attention to a policy problem and advocate a solution. Then, they draw on policy theories and concepts to reflect on their papers, highlighting (say): the need to identify the most important audience; the importance of framing issues with a mixture of evidence and emotional appeals; and, the need to present ‘feasible’ solutions.
The reflection can provide a useful segue to the essay, since we’re already identifying important policy problems, advocating change, reflecting on how best to encourage it – such as by presenting modest objectives – and then, in the essay, trying to explain (say) why governments have not taken that advice in the past. Their interest in the policy issue can prompt interest in researching the issue further; their knowledge of the issue and the policy process can help them develop politically-aware policy analysis. All going well, it produces a virtuous circle.
BOX A5: Rationale for blog post 2
I get students to do the analysis/reflection/blog combination in the first module, and an essay/ blog combo in the second module. The second blog post has a different aim. Students use the 500 words to present a jargon-free analysis of policy change. The post represents a useful exercise in theory translation. Without it, students tend to describe a large amount of jargon because I am the audience and I understand it. By explaining the same thing to a lay audience, they are obliged to explain key developments in a plain language. This requirement should also help them present a clearer essay, because people (academics and students) often use jargon to cover the fact that they don’t really know what they are saying.
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.
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.
The 1000 words and 500 words series already show how important but difficult it is to define and measure policy change. In this post, Leanne Giordono and I dig deeper into the – often confusingly different – ways in which different researchers conceptualise this process. We show why there is such variation and provide a checklist of questions to ask of any description of policy change.
Measuring policy change is more difficult than it looks
The measurement of policy change is important. Most ‘what is policy?’ discussions remind us that there can be a huge difference between policy as a (a) statement of intent, (b) strategy, (c) collection of tools/ instruments and (d) contributor to policyoutcomes.
The 1000 words and 500 words posts suggest that we address this problem of measurement by identifying the use of a potentially large number of policy instruments or policy tools such as regulation (including legislation) and resources (money and staffing) to accentuate the power at policymaker’s disposal.
Then, they suggest that we tell a story of policy change, focusing on (a) what problem policymakers were trying to solve, and the size of their response in relation to the size of the problem, and (b) the precise nature of specific changes, or how each change contributes to the ‘big picture’.
This recommendation highlights a potentially major problem: as researchers, we can produce very different narratives of policy change from the same pool of evidence, by accentuating some measures and ignoring others, or putting more faith in some data than others.
Three ways to navigate different approaches to imagining and measuring change
Researchers use many different concepts and measures to define and identify policy change. It would be unrealistic – and perhaps unimaginative – to solve this problem with a call for one uniform approach.
Rather, our aim is to help you (a) navigate this diverse field by (b) identifying the issues and concepts that will help you interpret and compare different ways to measure change.
Check if people are ‘showing their work’
Pay close attention to how scholars are defining their terms. For example, be careful with incomplete definitions that rely on a reference to evolutionary change (which can mean so many different things) or incremental change (e.g. does an increment mean small or non-radical)? Or, note that frequent distinctions between minor versus major change seem useful, but we are often trying to capture and explain a confusing mixture of both.
Look out for different questions
Multiple typologies of change often arise because different theories ask and answer different questions:
The Advocacy Coalition Framework distinguishes between minor and major change, associating the former with routine ‘policy-oriented learning’, and the latter with changes in core policy beliefs, often caused by a ‘shock’ associated with policy failure or external events.
Innovation and Diffusion models examine the adoption and non-adoption of a specific policy solution over a specific period of time in multiple jurisdictions as a result of learning, imitation, competition or coercion.
Classic studies of public expenditure generated four categories to ask if the ‘budgetary process of the United States government is equivalent to a set of temporally stable linear decision rules’. They describe policy change as minor and predictable and explain outliers as deviations from the norm.
Punctuated Equilibrium Theory identifies a combination of (a) huge numbers of small policy change and (b) small numbers of huge change as the norm, in budgetary and other policy changes.
Hall distinguishes between (a) routine adjustments to policy instruments, (b) changes in instruments to achieve existing goals, and (c) complete shifts in goals. He compares long periods in which (1) some ideas dominate and institutions do not change, with (2) ‘third order’ change in which a profound sense of failure contributes to a radical shift of beliefs and rules.
This is a placeholder for future work and discussion. It tails off at the end.
People sometimes talk about a ‘general theory’ of public policy to put in our minds a comparison with the physical sciences. Usually, the punchline is that there are ‘no general theories of public policy that are not bounded by space or time’ (p21). There may be some reference to the accumulation of knowledge or wisdom in policy studies, but based rarely on the understanding that policy studies contain the equivalent of general laws (I can only think of one possible exception).
This outcome is not too surprising in the social sciences, in which context really matters and we would expect a lot of variation in policy, policymaking, and outcomes.
On the other hand, we still need a way to communicate our findings, relate them to other studies, compare them, and wonder what it all adds up to. Few people go as far as expressing the sense that every study is unique (to the point of non-comparability) and that every description of policymaking does not compare to another.
In other words, we may be looking for a happy medium, to reject the idea of general laws but encourage – when appropriate or necessary – enough of a sense of common outlook and experience to help us communicate with each other (without descending too quickly into heated debate on our cross-purposes). Or, we can at least tell a story of policy studies and invite others to learn from, or challenge, its insights.
In my case, there are two examples in which it is necessary to project some sense of a common and initially-not-too-complicated story:
When describing policy theory insights to students, on the assumption that it may be their gateway to more reading.
It is possible to choose how many words to devote to each topic, including 500 Words, 1000 Words, a 9000 word Understanding Public Policy chapter, more in the source material, and even more if students start to ‘snowball’.
It is also possible, if you have a clearly defined audience, to introduce some level of uncertainty about these descriptions and their limitations.
You do your best, and then – if there is time – you talk about what you missed out.
For example, in this talk, the first question was: why didn’t you mention the role of power?
A general theory or a general understanding? Two key issues
That was a long-winded introduction to a more philosophical point about what we might want from general theories. My impression is that you might be seeking one of these two possibilities:
To use theories and concepts to describe material reality. In producing a general theory, we seek a general understanding of the ways in which the real world works. If so, we may focus primarily on how well these concepts describe the world, and the extent to which we can produce methods to produce systematic and consistent findings. The lack of a general theory denotes too much complexity and context.
To use theories and concepts to represent a useful story. In producing a general understanding, we focus on the ways in which people generate and communicate their understanding. If so, we may focus more on how people come together to produce and share meaning through concepts. The lack of a general theory could reflect the lack of agreement on how to study policymaking. Or, the presence of a general understanding could represent the exercise of power, to set the agenda and limit scholarly attention to a small number of theories.
I describe this distinction in the following audio clip, produced halfway through a run with the dogs, while jetlagged. The large gap in the middle happens when I am trying to see if the voice to text is working well enough for me to copy/paste it here (no).
Key examples of the exercise of power include:
The act of dismissing an individual, social group, or population by undermining the value of their knowledge or claim to knowledge (discussed in power and knowledge and Chapter 3).
Ongoing discussions about how we deal with (a) a relatively new focus (among the most-established policy theories) on policy studies in countries in the Global South, given that (b) the dominant interpretations of policymaking come from experiences in the Global North.
So, if you read these posts or Chapter 13 you will find a story of a general understanding of policy followed, almost immediately, by a list of reasons for why you should engage with it critically and perhaps not accept it. I’m setting your agenda but also reminding you that I’m doing it.
The IAD provides a language, and way of thinking, about the ways in which different institutions foster collective action. The language is so complicated that I have cheated by summarising key terms in this box (and describing polycentric governance in a different post) to stay within the 1000 words limit:
Governing the Commons
For me, the best way to understand the IAD is through the lens of Governing the Commons (and the research agenda it inspired), which explains how to rethink ‘tragedies of the commons’ and encourage better management of common pool resources (CPRs).
Ostrom rejects the uncritical use of rational choice games to conclude – too quickly – that disastrous collective action problems are inevitable unless we ‘privatize’ commons or secure major government intervention (which is tricky anyway when global problems require international cooperation). The tragedy of the commons presents a too-bleak view of humanity, in which it would be surprising to find cooperation even when the fate of the world is in human hands.
Alternatively, what if there is evidence that people often work collectively and effectively without major coercion? People are social beings who share information, build trust by becoming known as reliable and predictable, and come together to produce, monitor and enforce rules for the group’s benefit. They produce agreements with each other that could be enforced if necessary.
The IAD helps us analyse these cooperative arrangements. Ostrom describes 8 ‘design principles’ of enduring and effective CPR management shared by many real world examples:
CPRs have clear boundaries. Users know what they are managing, and can identify legitimate users.
The rules suit local conditions. Users know what they (a) are expected to contribute to management and (b) receive from CPRs.
The actors affected by the rules help shape them (at low cost).
CPR monitors are users or accountable to users. They monitor (a) the conduct of users and (b) the state of the CPR. The costs of mutual monitoring are low, and their consequences felt quickly.
The penalties for rule-breaking are low if the choice is a one-off and understandable under the circumstances (to avoid alienating the user). The penalties are high if the choice is part of a pattern which makes other users feel like ‘suckers’, or if rule-breaking would be catastrophic.
Conflict resolution is frequent, rapid and low cost.
Users have the right to self-organise without too much outside interference.
Many projects are connected geographically and at different scales – local, regional, national – in ways that do not undermine individual projects.
These design principles help explain why some communities manage CPRs successfully. They allow users to share the same commitment and expect the long-term benefits to be worthwhile.
However, Ostrom stressed that there is no blueprint – no hard and fast rules – to CPR management. There are three particular complications:
Good management requires high trust to encourage norms of reciprocity. Trust is crucial to minimizing the costs of compliance monitoring and enforcement. Trust may develop when participants communicate regularly, share an understanding of their common interests, reciprocate each other’s cooperation, and have proven reliable in the past.
Design principles are important to developing trust and solidarity, but so are ‘evolutionary’changes to behaviour. Actors have often learned about rule efficacy – to encourage cooperation and punish opportunism – through trial-and-error over a long period, beginning with simple, low-cost operational rules producing quick wins.
Rules, rules on rules, more rules, then even more rules
Institutions contain a large, complicated set of rules that serve many different purposes, and need to be understood and analysed in different ways.
Different purposes include:
how many actors are part of an action situation, and the role they play
what they must/ must not do
who is eligible to participate
who can move from one role to another
who controls membership, and how
how many participants are involved in a choice
what will happen if there is no agreement
how to manage and communicate information
the rewards or sanctions
the range of acceptable actions or outcomes from action.
We also need to analyse the relative costs and simplicity of different rules, and the rules about the other rules, including
‘operational’ rules on day-to-day issues (such as specific payoffs/ sanctions for behaviour)
‘collective choice’ rules about how to make those rules
‘constitutional’ rules on who can decide those rules and who can monitor and enforce, and
‘metaconstitutional’ analysis of how to design these constitutions with reference to the wider political and social context.
The world is too complex to break down into simple pieces
By now, you may be thinking that the IAD – and analysis of resource management – is complicated. This is true, partly because each case study – of the physical conditions and social practices regarding resource management – is different in some way. We can use the IAD to compare experiences, but accept that a profoundly successful scheme in one context may fail miserably in another.
Simplicity versus complexity: the world is complex, but should our analysis follow suit?
Indeed, this is why we need to think about rational choice games and the IAD simultaneously, to understand the analytical trade-offs.
Game theory laboratory experiments – built on simple rules and relatively small numbers of parameters – produce parsimonious analysis and results that we can understand relatively easily.
We may reject simple games as unrealistic, but what if we take this criticism to its extreme?
IAD in-depth field studies embrace complexity to try to understand the key dimensions of each study’s context. When we put them all together, there are too many concepts, variables, global applications, and variations-by-context, to contain in a simple theory.
The IAD addresses this trade off by offering a language to help organize research, encouraging people to learn it then use it to apply many different theories to explain different parts of the whole picture.
In other words, it is OK to reject simple models as unrealistic, but to embrace real-world complexity may require a rather complicated language.
Rational choice theory provides a way of thinking about collective action problems. There is great potential for choices made by individuals to have an adverse societal effect when there is an absence of trust, obligation, or other incentives to cooperate. People may have collective aims that require cooperation, but individual incentives to defect. While the action of one individual makes little difference, the sum total of individual actions may be catastrophic.
Simple ‘games’ provide a way to think about these issues logically, by limiting analysis to very specific situations under rather unrealistic conditions, before we consider possible solutions under more realistic conditions. For example, in simple games we assume that individuals pursue the best means to fulfil their preferences: they are able to act ‘optimally’ by processing all relevant information to rank-order their preferences consistently.
Go with it just now, and then we can consider what to do next.
The ‘prisoner’s dilemma’
Two people are caught red-handed and arrested for a minor crime, placed in separate rooms and invited to confess to a major crime (they both did it and the police know it but can’t prove it). The payoffs are:
If Paul confesses and Linda doesn’t, then Paul walks free and Linda receives a 10 year jail sentence (or vice versa)
If both confess they receive a much higher sentence (8 years) than if neither confesses (1 year).
Also assume that they take no benefit from the shorter sentence of the other person (a non-cooperative game).
It demonstrates a collective action problem: although the best outcome for the group requires that neither confess (both would go to jail for a total of 2 years), the actual outcome is that both confess (16 years). The latter represents the ‘Nash equilibrium’ since neither would be better off by changing their strategy unilaterally. Think of it from an individual’s perspective:
Imagine Paul will confess. Linda knows that if she stays silent, she gets suckered into 10 years. If she confesses, she gets 8.
Imagine Paul will stay silent. Linda knows that if she stays silent, she gets 1 year. If she confesses, she suckers Paul into 10.
The effect of Paul and Linda acting as individuals is that they are worse off collectively. Both ‘defect’ (confess) when they should ‘cooperate’ (stay silent).
The ‘logic of collective action’
Olson argues that, as the membership of an interest group rises, so does:
(a) the belief among individuals that their contribution to the group would make little difference and
(b) their ability to ‘free ride’.
I may applaud the actions of a group, but can – and will try to – enjoy the outcomes without leaving my sofa, paying them, or worrying that they will fail without me or punish me for not getting involved.
The ‘tragedy of the commons’
The scenario is that a group of farmers share a piece of land that can only support so many cattle before deteriorating and becoming useless. Although each farmer recognizes the collective benefit to an overall maximum number of cattle, each calculates that the marginal benefit she takes from one extra cow for herself exceeds the extra cost of over grazing to the group. Individuals place more value on the resources they extract for themselves now than the additional rewards they could all extract in the future.
The tragedy is that if all farmers act on the same calculation then they will destroy the common resource. The group is too large to track individual behaviour, individuals place more value on current over future consumption, and there is low mutual trust, with minimal motive and opportunity to produce and enforce binding agreements
This ‘tragedy’ sums up current anxieties about one of the defining problems of our time: global ‘common pool resources’ are scarce and the world’s population and consumption levels are rising; there is no magic solution; and, collective action is necessary but not guaranteed. We may value sustainable water, air, energy, forests, crops, and fishing stocks, but find it difficult to imagine how our small contribution to consumption will make much difference. As a group we fear climate change and seek to change our ways but, as individuals, contribute to the problem.
Overall, these scenarios suggest that individuals have weak incentives to cooperate even if it is in their interests and they agree to do so. This problem famously prompted Hardin (to recommend ‘mutual coercion, mutually agreed upon’ to ensure collective action.
What happens when there are many connected games?
In real life, it is almost impossible to find such self-contained and one-off games.In many repeated – or connected – games, the players know that thereare wider or longer-term consequences to defection.
In ‘nested games’, the behaviour of individuals often seems weird in one game until we recognise their involvement in a series. It may pay off to act ‘irrationally’ in the short term to support a longer-term strategy, or to lose in one to win in another.
In an ‘ecology of games’, many overlapping games take place at roughly the same time, and players to learn how to play one game while keeping an eye on many others, while some key players encourage a wider set of rules under which all games operate.
Evolutionary game theory explores how behaviour changes over multiple games to reflect factors such as (a) feedback and learning from trial and error, and (b) norms and norm enforcement.
For example, player 2 may pursue a ‘tit-for-tat’ strategy. She cooperates at first, then mimics the other player’s previous choice: defecting, to punish the other player’s defection, or cooperating if the other player cooperated. Knowledge of this strategy could provide player 1 with the incentive to cooperate. Further, norms develop when players enforce and expect sanctions for non-cooperation, foster socialisation to discourage norm violation, and some norms become laws.
In other words, this focus on the rules of repeated games gives us more hope than the tragedy of the commons. Indeed, it underpin Ostrom’s famous analysis of the conditions under which people can govern the commons more effectively.
Something I've been meaning to say about The Tragedy of the Commons. Bear with me for a small thread on why our embrace of Hardin is a stain on environmentalism. tldr: we’ve let a flawed metaphor by a racist ecologist define environmental thinking for a half century. 1/
Many theories in this 1000 words series describe multiple policymaking venues. They encourage us to give up on the idea of an all-knowing, all-powerful national central government. Instead, there are many venues in which to make authoritative choices, each contributing to what we call policy.
The word ‘multi-centric’ (coined by Professor Tanya Heikkila, with me and Dr Matt Wood) does not suggest that every venue is of equal importance or power. Rather, it prompts us not to miss something important by focusing too narrowly on one single (alleged) centre of authority.
To some extent, multi-centric policymaking results from choice. Many federal political systems have constitutions that divide power between executive, legislative, and judicial branches, or give some protection to subnational governments. Many others have become ‘quasi-federal’ more organically, by sharing responsibilities with supranational and subnational governments. In such cases, there is explicit choice to distribute power and share responsibility for making policy (albeit with some competition to assert power or shuffle-off responsibility).
However, for the most part, this series helps explain the necessity of multi-centric policymaking with reference to two concepts:
Bounded rationality. Policymakers are only able to pay attention to – and therefore understand and seek to control – a tiny proportion of their responsibilities.
Both factors combine to provide major limits to single central government control. Elected policymakers deal with bounded rationality by prioritising some issues and, necessarily, delegating responsibility for the rest. Delegation may be inside or outside of central government.
1000 Words theories describing multi-centric governmentdirectly
Multi-level governance describes the sharing of power vertically, between many levels of government, and horizontally, between many governmental, quasi-non-governmental and non-governmental organisations. Many studies focus on the diffusion of power within specific areas like the European Union – highlighting choice – but the term ‘governance’ has a wider connection to the necessity of MLG.
For example, part of MLG’s origin story is previous work to help explain the pervasiveness of policy networks:
Policymakers at the ‘top’ ask bureaucrats to research and process policy on their behalf
Civil servants seek information and advice from actors outside of government
They often form enduring relationships built on factors such as trust.
Such policymaking takes place away from a notional centre – or at least a small core executive – and with limited central attention.
Polycentricity describes (a) ‘many decision centers’ with their own separate authority, (b) ‘operating under an overarching set of rules’, but with (c) a sense of ‘spontaneous order’ in which no single centre controls the rules or outcomes. Polycentric governance describes ‘policymaking centres with overlapping authority; they often work together to make decisions, but may also engage in competition or conflict’.
This work on polycentric governance comes primarily from the Institutional Analysis and Development (IAD) framework that helps compare the effectiveness of institutions designed to foster collective action. For example, Ostrom identifies the conditions under which non-governmental institutions can help manage ‘common pool resources’ effectively, while IAD-inspired studies of municipal governance examine how many ‘centres’ can cooperate as or more effectively than a single central government.
Complexity theory has a less clear origin story, but we can identify key elements of complex systems:
They are greater than the sum of their parts
They amplify or dampen policymaking activity, so the same action can have a maximal or no impact
Small initial choices can produce major long term momentum
There are regularities of behaviour despite the ever-present potential for instability
They exhibit ‘emergence’. Local outcomes seem to defy central direction.
Systems contain many actors interacting with many other actors. They follow and reproduce rules, which help explain long periods of regular behaviour. Or, many actors and rules collide when they interact, producing the potential for many bursts of instability. In each case, the system is too large and unpredictable to be subject to central control.
1000 Words theories describing multi-centric government indirectly
Many other theories in this series describe multi-centric policymaking – or aspects of it – without using this term directly. Examples include:
Punctuated equilibrium theory suggests that (a) policymakers at the ‘centre’ of government could pay attention to, and influence, most issues, but (b) they can only focus on a small number and must ignore the rest. Very few issues reach the ‘macropolitical’ agenda. Multiple policymaking organisations process the rest out of the public spotlight.
Multiple streams analysis turns the notion of a policy cycle on its head, and emphasises serendipity over control. Policy does not change until three things come together at the right ‘window of opportunity’: attention to a problem rises, a feasible solution exists, and policymakers have the motive and opportunity to act. Modern MSA studies show that such windows exist at multiple levels of government.
The advocacy coalition framework describes the interaction between many policymakers and influencers. Coalitions contain actors from many levels and types of government, cooperating and competing within subsystems (see networks). They are surrounded by a wider context – over which no single actor has direct control – that provides the impetus for ‘shocks’ to each coalition.
In such accounts, the emphasis is on high levels of complexity, the potential for instability, and the lack of central control over policymaking and policy outcomes. The policy process is not well described with reference to a small group of policymakers at the heart of government.
Democratic governance is defined by the regular rotation of elected leaders. Amidst the churn, the civil service is expected to act as the repository of received wisdom about past policies, including assessments of what works and what doesn’t. The claim is that to avoid repeating the same mistakes we need to know what happened last time and what were the effects. Institutional memory is thus central to the pragmatic task of governing.
What is institutional memory? And, how is it different to policy learning?
Despite increasing recognition of the role that memory can or should play in the policy process, the concept has defied easy scholarly definition.
In the classic account, institutional memory is the sum total of files, procedures and knowledge held by an organisation. Christopher Pollitt, who has pioneered the study of institutional memory, refers to the accumulated knowledge and experience of staff, technical systems, including electronic databases and various kinds of paper records, the management system, and the norms and values of the organizational culture, when talking about institutional memory. In this view, which is based on the key principles of the new institutionalism, memory is essentially an archive.
The problem with this definition is that it is hard to distinguish the concept from policy learning (see also here). If policy learning is in part about increasing knowledge about policy, including correcting for past mistakes, then we could perhaps conceive of a continuum from learning to memory with an inflection point where one starts and the other stops. But, this is easier to imagine than it is to measure empirically. It also doesn’t acknowledge the forms memories take and the ways memories are contested, suppressed and actively forgotten.
In our recent contribution to this debate (see here and here) we define memories as ‘representations of the past’ that actors draw on to narrate what has been learned when developing and implementing policy. When these narratives are embedded in processes they become ‘institutionalised’. It is this emphasis on embedded narratives that distinguishes institutional memory from policy learning. Institutional memory may facilitate policy learning but equally some memories may prohibit genuine adaptation and innovation. As a result, while there is an obvious affinity between the two concepts it is imperative that they remain distinct avenues of inquiry. Policy learning has unequivocally positive connotations that are echoed in some conceptualisations of institutional memory (i.e. Pollitt). But, equally, memory (at least in a ‘static’ form) can be said to provide administrative agents with an advantage over political principals (think of the satirical Sir Humphrey of Yes Minister fame). The below table seeks to distinguish between these two conceptualisations of institutional memory:
Key debates: Is institutional memory declining?
The scholar who has done the most to advance our understanding of institutional memory in government is Christopher Pollitt. His main contention is that institutional memory has declined over recent decades due to: the high rotation of staff in the civil service, changes in IT systems which prevent proper archiving, regular organisational restructuring, rewarding management skills above all others, and adopting new management ‘fads’ that favour constant change as they become popular. This combination of factors has proven to be a perfect recipe for the loss of institutional memory within organisations. The result is a contempt for the past that leads to repeated policy failure.
We came to a different view. Our argument is that one of the key reasons why institutional memory is said to have declined is that it has been conceptualised in a ‘static’ manner more in keeping with an older way of doing government. This practice has assumed that knowledge on a given topic is held centrally (by government departments) and can be made explicit for the purpose of archiving. But, if government doesn’t actually work this way (see relevant posts on networks here) then we shouldn’t expect it to remember this way either. Instead of static repositories of summative documents holding a singular ‘objective’ memory, we propose a more ‘dynamic’ people-centred conceptualisation that sees institutional memory as a composite of intersubjective memories open to change. This draws to the fore the role of actors as crucial interpreters of memory, combining the documentary record with their own perspectives to create a story about the past. In this view, institutional memory has not declined, it is simply being captured in a fundamentally different way.
Key debates: How can an institution improve how it remembers?
How an institution might improve its memory is intrinsically linked to how memory is defined and whether or not it is actually in decline. If we follow Pollitt’s view that memory is about the archive of accumulated knowledge that is being ignored or deliberately dismantled by managerialism then the answer involves returning to an older way of doing government that placed a higher value on experience. By putting a higher value on the past as a resource institutions would reduce staff turnover, stop regular restructures and changes in IT systems, etc. For those of us who work in an institution where restructuring and IT changes are the norm, this solution has obvious attractions. But, would it actually improve memory? Or would it simply make it easier to preserve the status quo (a process that involves actively forgetting disruptive but generative innovations)?
Our definition, relying as it does on a more dynamic conceptualisation of memory, is sceptical about the need to improve practices of remembering. But, if an institution did want to remember better we would favour increasing the opportunity for actors within an institution to reflect on and narrate the past. One example of this might be a ‘Wikipedia’ model of memory in which the story of a policy, it success and failure, is constructed by those involved, highlighting points of consensus and conjecture.
Corbett J, Grube D, Lovell H, Scott R. “Singular memory or institutional memories? Toward a dynamic approach”. Governance. 2018;00:1–19. https://doi.org/10.1111/gove.12340
Pollitt, C. 2009. “Bureaucracies Remember, Post‐Bureaucratic Organizations Forget?” Public Administration 87 (2): 198-218.
Pollitt, C. 2000. “Institutional Amnesia: A Paradox of the ‘Information Age’?” Prometheus 18 (1): 5-16.
We talk a lot about ‘the policy process’ without really saying what it is. If you are new to policy studies, maybe you think that you’ll learn what it is eventually if you read enough material. This would be a mistake! Instead, when you seek a definition of the policy process, you’ll find two common responses:
Both responses seem inadequate: one avoids giving an answer, and another gives the wrong answer!
However, we can combine elements of each approach to give you just enough of a sense of ‘the policy process’ to continue reading the full ‘1000 words’ series:
1. The beauty of the ‘what is policy?’ question …
… is that we don’t give you an answer. It may seem frustrating at first to fail to find a definitive answer, but eventually you’ll accept this problem! The more important outcome is to use the ‘what is policy?’ question to develop analytical skills, to allow you to define policy in more specific circumstances (such as, what are the key elements of policy in this case study?), and ask more useful and specific questions about policy and policymaking. So, look at the questions we need to ask if we begin with the definition, ‘the sum total of government action, from signals of intent to the final outcomes’: does action include statements of intent? Do we include unintended policy outcomes? Are all policymakers in government? What about the things policymakers choose not to do? And so on.
2. The beauty of the policy cycle approach …
… is that it provides a simple way to imagine policy ‘dynamics’, or events and choices producing a never-ending sequence of other events and choices. Look at the stages model to identify many different tasks within one ‘process’, and to get the sense that policymaking is continuous and often ‘its own cause’. It’s not a good description of what actually happens, but it describes what some might like to happen, and used by many governments to describe what they do. Consequently, we can’t simply ignore it, at least without providing a better description, a better plan, and a better way for governments to justify what they do.
There are more complicated but better ways of describing policymaking dynamics
This picture is the ‘policy process’ equivalent of my definition of public policy. It captures the main elements of the policy process described – albeit in different ways – by most policy theories in this series. I present it here to give you enough of an answer – to ‘what is the policy process?’ – to help you ask more questions.
In the middle is ‘policy choice’
At the heart of most policy theory is ‘bounded rationality’, which describes (a) the cognitive limits of all people, and (b) how policymakers overcome such limits to make decisions (in the absence of NZT). In short, they use ‘rational’ and ‘irrational’ shortcuts to action, but these are provocative terms to prompt further reading (on, for example, ‘evidence-based policymaking’).
‘Rational’ describes goal-oriented activity: people may have limits to their attention and ‘information processing’, but they find systematic ways to respond, by setting goals and producing criteria to find the best information. ‘Irrational’ describes aspects of psychology: people draw on habit, emotions, their ‘gut’ or intuition, well-established beliefs, and their familiarity with information to make often-almost-instant decisions.
Surrounding choice is what we’ll call the ‘policy environment’
Environment is a metaphor we’ll use to describe the combination of key elements of the policy process which (a) I describe separately in further 1000 words posts, and (b) policy theories bring together to produce an overall picture of policy dynamics.
There are 5 or 6 key elements. In the picture are 6, reflecting the way Tanya Heikkila and I describe it (and the fact that I had 7 boxes to fill). In real life, I describe 5 because I have 5 digits on each hand. If you are Count Tyrone Rugen you have more choice.
Policy environments are made up of:
A wide range of actors (which can be individuals and organisations with the ability to deliberate and act) making or influencing policy at many levels and types of government.
Institutions, defined as the rules followed by actors. Some are formal, written down, and easy to identify. Others are informal, reproduced via processes like socialisation, and difficult to spot and describe.
Networks, or the relationships between policymakers and influencers. Some are wide open, competitive, and contain many actors. Others are relatively closed, insulated from external attention, and contain few actors.
Ideas, or the beliefs held and shared by actors. There is often a tendency for certain beliefs or ‘paradigms’ to dominate discussion, constraining or facilitating the progress of new ‘ideas’ as policy solutions.
Context and events. Context describes the policy conditions – including economic, social, demographic, and technological factors – that provide the context for policy choice, and are often outside of the control of policymakers. Events can be routine and predictable, or unpredictable ‘focusing’ events that prompt policymaker attention to lurch at short notice.
This picture is only the beginning of analysis, raising further questions that will make more sense when you read further, including: should policymaker choice be at the centre of this picture? Why are there arrows in the cycle but not in my picture? Should we describe complex policymaking ‘systems’ rather than ‘environments’? How exactly does each element in the ‘policy environment’ or ‘system’ relate to the other?
The answer to the final question can only be found in each theory of the policy process, and each theory describes this relationship in a different way. Let’s not worry about that just now! We’ll return to this issue at the end, when thinking about how to combine the insights of many theories.
Imagine that your audience is a group of scientists who have read everything and are only interested in something new. You need a new theory, method, study, or set of results to get their attention.
Let’s say that audience is a few hundred people, or half a dozen in each subfield. It would be nice to impress them, perhaps with some lovely jargon and in-jokes, but almost no-one else will know or care what you are talking about.
Imagine that your audience is a group of budding scientists, researchers, students, practitioners, or knowledge-aware citizens who are new to the field and only interested in what they can pick up and use (without devoting their life to each subfield). Novelty is no longer your friend. Instead, your best friends are communication, clarity, synthesis, and a constant reminder not to take your knowledge and frame of reference for granted.
Let’s say that audience is a few gazillion people. If you want to impress them, imagine that you are giving them one of the first – if not the first – ways of understanding your topic. Reduce the jargon. Explain your problem and why people should care about how you try to solve it. Clear and descriptive titles. No more in-jokes (just stick with the equivalent of ‘I went to the doctor because a strawberry was growing in my arse, and she gave me some cream for it’).
At least, that’s what I’ve been telling myself lately. As things stand, my most-read post of all time is destined to be on the policy cycle, and most people read it because it’s the first entry on a google search. Most readers of that post may never read anything else I’ve written (over a million words, if I cheat a bit with the calculation). They won’t care that there are a dozen better ways to understand the policy process. I have one shot to make it interesting, to encourage people to read more. The same goes for the half-dozen other concepts (including multiple streams, punctuated equilibrium theory, the Advocacy Coalition Framework) which I explain to students first because I now do well in google search (go on, give it a try!).
I also say this because I didn’t anticipate this outcome when I wrote those posts. Now, a few years on, I’m worried that they are not very good. They were summaries of chapters from Understanding Public Policy, rather than first principles discussions, and lots of people have told me that UPP is a little bit complicated for the casual reader. So, when revising it, I hope to make it better, and by better I mean to appeal to a wider audience without dumping the insights. I have begun by trying to write 500-words posts as, I hope, improvements on the 1000-word versions. However, I am also open to advice on the originals. Which ones work, and which ones don’t? Where are the gaps in exposition? Where are the gaps in content?
Policymakers articulate value judgements which underpin fundamental choices about which social groups should be treated positively or negatively by government bodies. When addressing highly politicised issues, they seek to reward ‘good’ groups with government support and punish ‘bad’ groups with sanctions (Schneider et al, 2014). This judgement is often described as ‘moral reasoning’ (Haidt, 2001) or ‘fast thinking’ (Kahneman, 2012: 20). Policymakers make quick, biased, emotional judgements, then back up their actions with selective facts to pursue their understanding of a policy problem and its solution:
Likes and dislikes are not the result of individual or collective reason and deliberation but mainly the product of emotion and heuristics … judgments begin with emotional reactions … and reason is used mainly to justify initial emotion responses (Schneider et al, 2014, drawing on Kahneman, 2012 and Haidt, 2001; 2012).
Yet, social constructions can also be based on conscious bias. Policies reflect the goal-driven use of constructions, ‘strategically manipulated for political gain … to create political opportunities and avoid political risks’ or, at least, an anxiety by politicians ‘not to be caught in opposition to prevailing values’ if it affects their performance in election (Schneider and Ingram, 1997: 6; 192). They aim to receive support from the populations they describe as ‘deserving’, as well as a wider public satisfied with describing others as ‘undeserving’ (1997: 6).
These judgements can have an enduring ‘feed-forward’ effect (Ingram et al, 2007: 112). Choices based on values are reproduced in ‘policy designs’, as the ‘content or substance of public policy’:
Policy designs are observable phenomena found in statutes, administrative guidelines, court decrees, programs, and even the practices and procedures of street level bureaucrats … [they] contain specific observable elements such as target populations (the recipients of policy benefits or burdens), goals or problems to be solved (the values to be distributed), rules (that guide or constrain action), rationales (that explain or legitimate the policy), and assumptions (logical connections that tie the other elements together) (Schneider and Ingram, 1997: 2).
Examples of feed-forward effects include policy designs: signaling that ‘elderly citizens are worthy of respect and deserving of the funds they receive’, prompting ‘a level of political participation rivaled by no other group’; introducing convoluted rules to diminish participation in areas such as housing entitlement; signaling to welfare recipients that they have themselves to blame and deserve minimal support; and, restricting voting rights directly (Schneider and Sidney, 2009: 110-11)
Policy designs based on moral choices often become routine and questioned rarely in government because they are ‘automatic rather than thought through’. Emotional assignments of ‘deservingness’ act as important ‘decision heuristics’ because this process is ‘easy to use and recall and hard to change’ (Schneider et al, 2014). They are difficult to overcome, because a sequence of previous policies, based on a particular framing of target populations, helps produce ‘hegemony’: the public, media and/ or policymakers take this set of values for granted, as normal or natural, and rarely question them when engaging in politics (Pierce et al, 2014; see also Gramsci, 1971; Bachrach and Baratz, 1970; Lukes, 2005).
This signal of limited deservingness impacts on citizens and groups, who participate more or less according to how they are characterised by government (Schneider and Ingram, 1993: 334). Only some groups have the resources to mobilise and challenge or reinforce the way they are perceived by policymakers (Schneider and Ingram, 1997: 21-4; 2005: 444; Pierce et al, 2014), or to mobilise to persuade the public, media and/ or government that there is a reason to make policy on their behalf. Some groups can be categorized differently over time, but this seems to be a non-routine outcome, at least in the absence of long term change in social attitudes, even though social constructions are – in theory – ‘inherently unstable’ (Ingram and Schneider, 2005: 10). For example, it can follow a major external event such as an economic crisis or game-changing election, exploited by ‘entrepreneurs’ to change the way that policymakers view particular groups (Ingram and Schneider, 2005: 10-11). Or, it can be prompted by policy design which, for example, is modified to suit powerful populations with spillover effects for the powerless (such as when drug treatment develops as an alternative to incarceration) (Schneider and Ingram, 2005: 639).
Ingram et al (2007: 102) depict this dynamic with a table in which there are two spectrums – one describes the positive or negative ways in which groups are portrayed by policymakers, the other describes the resources available to groups to challenge or reinforce that image – producing four categories of target population: advantaged, contenders, dependents, and deviants. The powerful and positively constructed are ‘advantaged’; the powerful and negatively constructed are ‘contenders’; the powerless and positively constructed are ‘dependents’; the powerless and negatively constructed are ‘deviants’ (Ingram et al, 2007: 102)
Schneider and Ingram (1997: 3) argue that, although the (US) political system may ‘meet some standard of fairness or openness’, the policies they produce may not be ‘conducive to democracy’. US public policies have failed to solve major problems – including inequality, poverty, crime, racism, sexism, and effective universal healthcare and education – and such policy failure contributes to the sense that the political process serves special interests at the expense of the general public (1997: 4-7). Policy designs ‘are strongly implicated in the current crisis of democracy’ because they have failed and they discourage many target populations (the ‘undeserving’, ‘deviant’, or ‘demons’) from public participation: ‘These designs send messages, teach lessons, and allocate values that exacerbate injustice, trivialize citizenship, fail to solve problems, and undermine institutional cultures that might be more supportive of democratic designs’ (1997: 5-6; 192).
Of course, although there is the unpredictable potential for issues to be politicised, many are not. Yet, low salience can exacerbate these problems of citizen exclusion. Policies dominated by bureaucratic interests often alienate citizens receiving services (1997: 79). Or, experts dominate policies (and many government agencies) when there is high scientific agreement and wider acceptance that the ‘public interest’ is served largely through the production and use of evidence. The process does not include ordinary citizens routinely. Rather, ‘experts with scientific credentials aid and abet the disappearance of the public sphere’, and this is a problem when issues ‘with important social value implications’ transform into ‘a matter of elite scientific and professional concern’ (such as when official calculations of economic activity override personal experiences) (1997: 153; 167).
Overall, they describe a political system with major potential to diminish democracy, with politicians faced with the choice of politicising issues to reward or punish populations or depoliticise issues with reference to science and objectivity, and policy designs uninformed by routine citizen participation. They describe an increasingly individualistic US system with declining rates of collective political participation (at least in elections), a tendency for actors to seek benefits for their own populations, and often ‘degenerative’ policy which produces major inequalities along sex, race, and ethnicity lines (Ingram and Schneider, 2005: 22-6).
Although SCPD began as a study of US politics, many of its concepts and insights are ‘universal’. In other words, they identify ‘policymaking issues that can arise in any time or place’ (Cairney and Jones, 2016: 38):
The psychology of social construction: people make quick and emotional judgements about the populations of which they are a part, and other populations.
Policymakers seek to exploit the ‘national mood’, or other indicators of social preferences, for political reward.
These judgements inform policy design.
Policy designs help send signals to citizens which can diminish their incentive to engage in politics.
Low salience issues are often dominated by bureaucratic politics and scientific language, at a similar expense to citizen participation.
The time and place-specific nature of SCPD refers to specific social attitudes, the social construction of specific target populations (from a large list of potential constructions), and specific policy designs associated with each government.
I tend to set this simple-looking question for coursework in policy modules: what is policy, how much has it changed, and why? Students get to choose the policy issue, timeframe (and sometimes the political system), and relevant explanatory concepts.
On the face of it, it looks super-simple: A+ for everyone!
Give it a few more seconds, and you can see the difficulties:
We spent a lot of time agreeing that it seems almost impossible to define policy (explained in 1000 Words and 500 Words)
There is an almost unmanageable number of models, concepts, and theories to use to explain policy dynamics (I describe about 25 in 1000 Words each)
I try to encourage some creativity when solving this problem, but also advise students to keep their discussion as simple and jargon-free as possible (often by stretching an analogy with diving, in which a well-executed simple essay can score higher than a belly-flopped hard essay).
Choosing a format: the initial advice
Choose a policy area (such as health) or issue (such as alcohol policy).
Describe the nature of policy, and the extent of policy change, in a particular time period (such as in the post-war era, since UK devolution, or since a change in government).
Select one or more policy concept or theory to help structure your discussion and help explain how and why policy has changed.
For example, a question might be: What is tobacco policy in the UK, how much has it changed since the 1980s, and why? I use this example because I try to answer that – UK and global – question myself, even though my 2007 article on the UK is too theory-packed to be a good model for an undergraduate essay.
Choosing a format: the cautionary advice
You may be surprised about how difficult it is to answer a simple question like ‘what is policy?’ and I will give you considerable credit for considering how to define and measure it, by identifying, for example, the use of legislation/ regulation, funding, staff, and ‘nodality’ and/ or by considering the difference between, say, policy as a statement of intent or a long term outcome. In turn, a good description and explanation of policy change is difficult. If you are feeling ambitious, you can go further, to compare, say, two issues (such as tobacco and alcohol) or places (such UK Government policy and the policy of another country), but sometimes a simple and narrow discussion can be as, or more, effective. Similarly, you can use many theories or concepts to aid explanation, but often one theory will do. Note that (a) your description of your research question, and your essay structure, is more important than (b) your decision on what topic to focus or concepts to use.
Choosing a topic: the ‘joined up’ advice
The wider aim is to encourage students to think about the relationship between different perspectives on policy theory and analysis. For example, in a blog and policy analysis paper they try to generate attention to a policy problem and advocate a solution. Then, they draw on policy theories and concepts to reflect on their papers, highlighting (say): the need to identify the most important audience; the importance of framing issues with a mixture of evidence and emotional appeals; and, the need to present ‘feasible’ solutions.
The reflection can provide a useful segue to the essay, since we’re already identifying important policy problems, advocating change, reflecting on how best to encourage it – such as by presenting modest objectives – and then, in the essay, trying to explain (say) why governments have not taken that advice in the past. Their interest in the policy issue can prompt interest in researching the issue further; their knowledge of the issue and the policy process can help them develop politically-aware policy analysis. All going well, it produces a virtuous circle.
Some examples from my pet subject
Let me outline how I would begin to answer the three questions with reference to UK tobacco policy. I’m offering a brief summary of each section rather than presenting a full essay with more detail (partly to hold on to that idea of creativity – I don’t want students to use this description as a blueprint).
What is modern UK tobacco policy?
Tobacco policy in the UK is now one of the most restrictive in the world. The UK government has introduced a large number of policy instruments to encourage a major reduction of smoking in the population. They include: legislation to ban smoking in public places; legislation to limit tobacco advertising, promotion, and sponsorship; high taxes on tobacco products; unequivocal health education; regulations on tobacco ingredients; significant spending on customs and enforcement measures; and, plain packaging measures.
[Note that I selected only a few key measures to define policy. A fuller analysis might expand on why I chose them and why they are so important].
How much has policy changed since the 1980s?
Policy has changed radically since the post-war period, and most policy change began from the 1980s, but it was not until the 2000s onwards that the UK cemented its place as one of the most restrictive countries. The shift from the 1980s relates strongly to the replacement of voluntary agreements and limited measures with limited enforcement with legislative measures and stronger enforcement. The legislation to ban tobacco advertising, passed in 2002, replaced limited bans combined with voluntary agreements to (for example) keep billboards a certain distance from schools. The legislation to ban smoking in public places, passed in 2006 (2005 in Scotland), replaced voluntary measures which allowed smoking in most pubs and restaurants. Plain packaging measures, combined with large and graphic health warnings, replace branded packets which once had no warnings. Health education warnings have gone from stating the facts and inviting smokers to decide, and the promotion of harm reduction (smoke ‘low tar’), to an unequivocal message on the harms of smoking and passive smoking.
[Note that I describe these changes in broad terms. Other articles might ‘zoom’ in on specific instruments to show how exactly they changed]
Why has it changed?
This is the section of the essay in which we have to make a judgement about the type of explanation: should you choose one or many concepts; if many, do you focus on their competing or complementary insights; should you provide an extensive discussion of your chosen theory?
I normally recommend a very small number of concepts or simple discussion, largely because there is only so much you can say in an essay of 2-3000 words.
For example, a simple ‘hook’ is to ask if the main driver was the scientific evidence: did policy change as the evidence on smoking (and then passive smoking) related harm became more apparent? Is it a good case of ‘evidence based policymaking’? The answer may then note that policy change seemed to be 20-30 years behind the evidence [although I’d have to explain that statement in more depth] and set out the conditions in which this driver would have an effect.
In short, one might identify the need for a ‘policy environment’, shaped by policymakers, and conducive to a strong policy response based on the evidence of harm and a political choice to restrict tobacco use. It would relate to decisions by policymakers to: frame tobacco as a public health epidemic requiring a major government response (rather than primarily as an economic good or issue of civil liberties); place health departments or organisations at the heart of policy development; form networks with medical and public health groups at the expense of tobacco companies; and respond to greater public support for control, reduced smoking prevalence, and the diminishing economic value of tobacco.
This discussion can proceed conceptually, in a relatively straightforward way, or with the further aid of policy theories which ask further questions and help structure the answers.
For example, one might draw on punctuated equilibrium theory to help describe and explain shifts of public/media/ policymaker attention to tobacco, from low and positive in the 1950s to high and negative from the 1980s.
Or, one might draw on the ACF to explain how pro-tobacco coalitions helped slow down policy change by interpreting new scientific evidence though the ‘lens’ of well-established beliefs or approaches (examples from the 1950s include filter tips, low tar brands, and ventilation as alternatives to greater restrictions on smoking).
Well, it’s really a set of messages, geared towards slightly different audiences, and summed up by this table:
This academic journal article (in Evidence and Policy) highlights the dilemmas faced by policymakers when they have to make two choices at once, to decide: (1) what is the best evidence, and (2) how strongly they should insist that local policymakers use it. It uses the case study of the ‘Scottish Approach’ to show that it often seems to favour one approach (‘approach 3’) but actually maintains three approaches. What interests me is the extent to which each approach contradicts the other. We might then consider the cause: is it an explicit decision to ‘let a thousand flowers bloom’ or an unintended outcome of complex government?
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.