Promoting informed decision-making is a recurring theme in improving the efficacy and responsiveness of government. Consistent with this theme is the assumption that decision-makers face an information deficit – that if decision-makers simply had access to the right knowledge that they would make better decisions. There exists an overarching normative consensus that more information in the policy process is generally good, but there are limits to how much decision-makers can process. Scholars of public policy, and particularly agenda setting, have tended to find that the central problem of policymaking is not a deficit of information, but instead, an oversupply of information. Very often, then, the central problem confronting decision-making is prioritising among this information. Information-processing, specifically attention, is seen as the driver of policy change in theories of agenda-setting such as multiple streams (see Cairney, this issue) and particularly so in punctuated equilibrium theory (PET). PET scholars have long understood that policy and institutional design are critical to information-processing (Baumgartner and Jones, 1993). This chapter represents a guide for scholars wishing to bridge the divide between PET theory and the practice of institutional design.
The engine of information processing in policy systems are subgovernments. Subgovernments are defined collections of policy actors in government, and around government, who develop and make policy within substantively specific issues. Usually, these subgovernments will contain an authoritative body (for example, a city council or congressional committee), an administrative unit for implementing policy (for example, the ministry of transportation or the police department), and supportive constellations of those interested in the policy issue (for example, Greenpeace or the Chamber of Commerce).
The literature on policy learning has generated a huge amount of heat (and some light) producing policy learning taxonomies, concepts and methods, yet the efforts to demonstrate why we should think about policy processes in terms of learning have been rare and mostly in the past (Dunlop, Radaelli and Trein, 2018). Additionally, policy learning has progressed in different sub-fields, such as the study of diffusion, transfer, individual and collective learning, social learning, and knowledge utilisation (see the family tree of learning in Dunlop, Radaelli and Trein, 2018; and the fragmentation in sub-fields portrayed in Goyal and Howlett, 2018). This has discouraged the tasks of communicating, comparing and combining insights that, the editors of this special issue remind us, are fundamental to translate research to a wider audience, avoiding jargon and obfuscation.
We offer this chapter to both an audience of academics and to actors involved in policy-processes, be they elected politicians, public managers, activists or pressure groups. We address the academic audience made up of specialists in policy analysis by arguing that the quality of our findings should be judged in terms of ‘translation reach’. We set out to show how we can combine and integrate research on learning so that it can be translated to a wider audience of social scientists looking for cumulative findings, typical lessons, concepts that travel across fields.
There is plenty of science, philosophy, and literature pointing to the importance of narrative in human affairs. One way to understand the findings and arguments presented is that people, by nature, are inclined to impose meaning on the world and that when they do, they rely on information shortcuts (heuristics) to develop quick and easy emotional renderings of the world that fit with who they think they are and what they know. People’s preferred way of meaning-making is through story (see Jones et al, 2014b). The essence of these interdisciplinary findings is captured by Hardy:
For we dream in narrative, daydream in narrative, remember, anticipate, hope, despair, believe, doubt, plan, revise, criticise, construct, gossip, learn, hate and love by narrative. In order to really live, we make up stories about ourselves and others, about the personal as well as the social past and future. (1968, 5)
If this is true of individuals, it should not be surprising that narrative also matters in public policy. Public policy is navigated by a system of actors who are vying for their preferred policy goals. Within this system, policy actors wield narratives to help achieve their goals, communicate problems and solutions, and citizens use them to communicate their preferences to policy elites, among other uses. However, much of this storytelling is governed by intuition, anecdote, and ad hoc theorising, which is not to malign policy actors – there is little else to go on.
Public policies are institutional arrangements that set the official rules of the game for society as we work together to provide public goods and solve complex social dilemmas, such as maintaining orderly and healthy communities, educating the public, protecting vulnerable populations, and sustaining natural resources. Designing policies to manage these complex social problems can be challenging. In part, this is because the institutional arrangements that comprise policies can be complex and may affect a diverse set of actors and issues in ways that may be uncertain or difficult to predict. Scholarship on institutional analysis, particularly from the research that employs the Institutional Analysis and Development (IAD) framework, can offer useful tools to help understand and assess this complexity. Previous assessments and descriptions of the IAD framework, however, have not clearly explained how insights from the IAD can enhance the practical relevance of scholarly research on policy design.
As its name suggests, institutions are at the heart of the IAD framework. Institutions are the rules, norms, and shared strategies that structure human behaviour and choices, and are collectively created, adapted, monitored, and enforced (Ostrom, 2005). Thus, by ‘institutional arrangements’, we are not referring to bricks-and- mortar buildings or political venues. While institutions can be formalised, as written into policy documents, they often are defined by what people have agreed with one another about what they may, must or must not do in relation to other people or to their environment.
First published as a special issue of Policy & Politics, this critical and practical volume challenges policy theory scholars to change the way they produce and communicate research.
Leading academics propose eight ways to synthesise and translate state of the art knowledge to equip scholars to communicate their insights with each other and a wider audience. Chapters consider topics such as narratives as tools for influencing policy change, essential habits of successful policy entrepreneurs, and applying cultural theory to navigate the policy process.
Providing theoretical clarity and accumulated knowledge, this text highlights the vital importance of translating policy research in practical and understandable ways.
The articles on which Chapters 2, 3 and 5 are based are available Open Access under CC-BY-NC licence.
Collective action dilemmas, or the misalignment of individual incentives and desired collective outcomes, are prevalent across every scale of social interaction. These dilemmas are exacerbated in systems of fragmented authority or overlapping jurisdictions. The intractable, ‘wicked problems’ – climate change, global terrorism, health crises, crime, or poverty – facing governments are seldom contained within a jurisdiction and require interorganisational efforts to address them (Head and Alford, 2015; Martin and Guarneros-Meza, 2013), although even many common governing tasks are not suited to hierarchies. Whether contracting out social services, restoring an ecosystem in a shared watershed, lowering barriers to international trade, or coordinating sustainability activities across a municipality, policymakers confront obstacles to collaboration that hinder more efficient and effective governance.
As centralised versus decentralised approaches to deal with fragmentation have long been debated (Lyons and Lowery, 1989; Ostrom et al, 1961), collective action theories have explained how semi-autonomous governments can work together and overcome problematic externalities or ‘spillovers’ (that is, positive or negative consequences of an activity that affect third parties) that arise from fragmentation, while preserving local autonomy that can spur innovation and limit the expansion of bureaucracy.
The Institutional Collective Action (ICA) framework (Feiock, 2007; 2013) has emerged as an analytical lens for understanding collaboration in fragmented governance. ‘ICA dilemmas’, or situations in which an authority’s incentives do not align with collectively desired outcomes, arise from spillovers of policy choice and design that transcend jurisdictions. ICA dilemmas stemming from fragmentation can lead to inefficient behaviour, such as free riding and service duplication, as well as normatively undesirable outcomes such as urban sprawl (Jimenez, 2016).
We challenge policy theory scholars to change the way we produce and communicate research: translate our findings to a wider audience to gauge the clarity and quality of our findings. Policy theories have generated widespread knowledge of the policy process, but the field is vast and uncoordinated, and too many scholars hide behind a veil of jargon and obfuscation. Some of the most visible outcomes – such as limited relevance to practitioners, and anxiety and confusion among students or early career researchers with a limited grasp of a complex field – reflects a less visible but more worrying academic problem: we often assume, rather than demonstrate, that policy process research contains insights that add cumulative and comparable knowledge to the field.
Yet, if we do not take the time to check if we understand the state of the art, and can share a common understanding with our peers, how can we state that we are accumulating knowledge collectively rather than producing work of limited relevance beyond our own narrow individual concerns? Is there genuinely a cohesive, advancing, field of policy theories or are we each producing our own theories and assuming they are useful to others? We need to ask these searching questions more often and place them front and centre of academic debate.
Some thematic reviews already try to compare insights across many theories (Heikkila and Cairney, 2017) but they only scratch the surface and provide limited assurance about a coherent policy process research agenda. We need more work from theory-specific experts to explain their theories and empirical knowledge clearly enough to help others gauge progress and compare it to progress among other approaches.
We began this edited volume by challenging policy scholars to translate their findings to a wider audience and improve communication among academics. This volume tackled this challenge through its eight chapters that sought to draw practical lessons from various theoretical approaches.
No other book or article gathers as many theoretical perspectives with the goal of extracting practical insights, although past efforts have focused on single theoretical approaches (for example, Shipan and Volden, 2012) or synthesized lessons at a high scale of abstraction and generalizability for example, Weible et al, 2012; Cairney, 2015). In doing so, we hope to shift academic focus back towards a bugbear in public policy scholarship: relevance. Relevance has long served as a key founding aim of the field (Lasswell, 1951) but has also contributed to acrimonious debates about whether relevance should be an aim and whether the field even comes close to realising it (deLeon, 1997).
The challenge today is not whether policy theories should make their work relevant but how it should be done. This edited volume provides a number of different ways to do so. We organise them into three categories for new and experienced policy process scholars interested in translating practical lessons from policy theories.
Each chapter summarises the state of the art developments of different theories. They help new students understand the field for the first time and experienced scholars seeking to learn what each theory now represents (since many have changed dramatically since their first exposition).
The multiple streams approach (MSA) is one of policy scholarship’s biggest successes. Kingdon’s (1984) study is one the highest cited books in policy studies, there is a thriving programme of empirical application and theoretical refinement, its lessons are applied regularly in interdisciplinary studies, and it is relatively well known and enjoyed by practitioners and students (Herweg et al, 2015; 2017; Zahariadis, 2007; 2014; Jones et al, 2016).
Yet, its success is built on shaky foundations because its alleged strength – its flexible metaphor of streams and windows of opportunity – is actually its weakness. Most scholars describe MSA superficially, fail to articulate the meaning of its metaphor, do not engage with state of the art developments, and struggle to apply its concepts systematically to empirical research (Jones et al, 2016). These limitations create an acute scientific problem: most scholars apply MSA without connecting it to a coherent research agenda. Consequently, it is difficult to produce new knowledge systematically or describe with confidence the accumulated wisdom of MSA. As the special issue on ‘Practical lessons from policy theories’ shows, this problem is a feature of many policy theories which have expanded far beyond their original intentions (Weible and Cairney, 2018).
There have been some recent attempts to solve this problem by encouraging conceptual clarity via hypothesis production and testing (Cairney and Jones, 2016; Cairney and Zahariadis, 2016; Herweg et al, 2015). However, this solution only appeals to a niche audience of MSA scholars. Most readers and users of MSA draw on Kingdon’s (1984) classic metaphor without taking their research to the next level by engaging with over 30 years of subsequent research and theoretical refinement. Kingdon’s study of US federal politics in the 1980s can only take us so far.
Lasswell’s (1951) seminal notion of effective policy analysis combines the ‘technical’ tasks of ‘the scientific study of problems’ and ‘policymaking around these problems’ (Turnbull, 2008). Yet uncertainty and complexity are widely acknowledged to structure contemporary policy-making environments (for example, Geyer and Cairney, 2015). Phenomena such as bounded rationality (Simon, 1955) and ‘wicked’ policy problems (Rittel and Webber, 1973) mean that sense-making often relies on more than simply scientific analysis. Grint (2005, 1473) therefore observes that to make progress in confronting often intractable problems, ‘the task is to ask the right questions rather than provide the right answers’. Complexity therefore places a premium on not only evidence and judgement, but also the ability to question, learn and adapt.
In the face of this complexity, institutions matter. Policymakers use institutions to establish and prioritise particular values, norms, rules and roles, thereby reducing the complexity of choice. Sometimes this can be a very positive process, inspiring a flow of ideas and fast-thinking-type solutions to policy problems that ‘fit’ with the policy context. However, sometimes institutions can get in the way – reinforcing values, systems and practices that no longer fit so well, and acting as blinders to emerging issues. So how do policymakers develop effective policymaking strategies when they are so limited by bounded rationality? Do their ‘cognitive frailties’ make them over- reliant on a combination of rational and irrational informational shortcuts to act quickly and make adequate decisions? If so, should institutions be designed to limit their autonomous powers, or instead should their ability to develop such heuristics be celebrated, and work be undertaken with them to refine such techniques? This chapter mobilises Cultural Theory (CT) to address such questions, allowing researchers to examine the role of institutions in structuring how policy actors make sense of their environment.