LIST OF WORKSHOPS

Context
The complexity of the world and inevitability of human error make learning essential for overcoming challenges that emerge when dealing with politics and public policy. People learn about the severity and causes of problems that trouble a society and, given crowded agendas, adjust their political strategies for attracting the attention of government officials. The policy process is about power, but it is also an attempt to create, validate, assemble and distribute learning about public policies.

The formulation of public policies builds on learning from experiences of other policies, and the design and implementation of policies are constantly adapted over time through various feedback mechanisms. Learning from past mistakes at home and from abroad represents a hope that better policies will develop in the future. Although this is desirable, and is foundational to the aspirations of the evidence-based policy agenda of many governments, that’s not how learning typically happens in the real world of public policy. Politicians may learn how to tweak policies to win the next elections rather than to improve. Policy bureaucracies may look at the wrong examples, they may not learn the right lessons, and they often extrapolate from the past and from abroad without taking into account the mechanisms of learning and the role of the institutional context.

Add to this that although we have seen many recent examples of attempts to advance the theory of policy learning, we still have some building blocks but not a theory of why learning emerges or fails, and its consequences for power, policy improvement, and the quality of democracy. In short, this is an exciting moment in the development of the field, but we need to be more systematic on causes and consequences of learning if this has to become a new theory of the policy process. Even if our ambition is more modestly to perfect our knowledge of learning within the established theories of the policy process, rather than creating a new one, we have to assemble the building blocks more systematically, in terms of micro-foundations, learning in organizations, and how group learning becomes policy learning and, sometimes, social learning. Another important claim we make is that political science needs the contribution of other disciplines: interdisciplinary work is not an added dimension to our work in this field, it is essential to the development of the field.

Let us briefly see how we got where are now. Policy learning designates the cognitive and social dynamic leading policy actors to revise or strengthen their policy beliefs and preferences over time (Dunlop & Radaelli, 2013; Moyson & Scholten, 2018). Karl W. Deutsch was arguably the first to express concern for learning in politics and policy in his cybernetic theory of government, where the role of ‘feedback’ and ‘steering’ to explain (and enhance) governmental ‘learning capacity’ was pinpointed (Deutsch 1963). The attention for learning resonates in Heclo’s work, who emphasized that politics is not only about power but also about beliefs and the management of uncertainty (Heclo 1974). For institutions to operate or for policies to be made, a better understanding of public problems and of their possible solutions is necessary. For this, knowledge must be created, assimilated, and organized. Consequently, policy actors puzzle over policy problems and solutions, as well as ‘powering’. At a similar period, Walker (1974) showed that the ‘management of ideas’ also allows to exert power. Controlling ideas means controlling uncertainties. In other words, we need to explain the process which “leads actors to select a different view of how things happen (‘learning that’) and what courses of action should be taken (‘learning how’)” (Zito and Schout 2009: 1104).

In the 1990s, authors like Bennet, Howlett, May and others developed the categorical approach to policy learning. Essentially, they broke down the single entity of learning by considering different types, and identified the prima facie evidence that would lead us to recognize a type of learning as ‘political’, ‘social’, or ‘instrumental’. This was the period where the interest in the politics of policy learning emerged consistently in the field. At the same time, another strand of literature looked at the cross-national diffusion of learning, or more exactly at the consequences of spatial interdependence for learning processes and outcomes.

Concepts like ‘policy transfer’ (Dolowitz and Marsh 2000), ‘policy diffusion’ (Marsh and Sharman 2009), ‘lesson-drawing’ (Rose 1991), and ‘policy convergence’ (Bennett 1991; Knill 2005) have become popular. These concepts refer to processes through which decisions are made in one institutional setting according to decisions previously made in another one. Policy transfer has early been referred to as a process in which the decision-makers in one institutional setting ‘learn’ from the policy decisions made in another setting (Dolowitz and Marsh 2000). Learning from early adopters is also widely recognized as a mechanism of policy diffusion next to competition, imitation and coercion (e.g. Shipan and Volden 2008). However, serious consideration for individual and collective learning processes allowing transfer has emerged only recently (Gilardi 2010; Meseguer 2004; Volden et al. 2008). ‘Lesson drawing’ (Rose 1991) And extrapolation models (Bardach, 2004) have received much of the attention because they involve an ideal-typical form of learning: this concept translates the will, effective cognitive ability, and practical capacity to draw lessons from other institutional settings in order to meet a given objective in one’s own institutional setting (e.g. Gilardi et al. 2009).

The difficulty with this strand was to make sure that the cross-national patterns identified empirically were truly representative of learning processes rather than other processes. Finally, over the last twenty-years governments and international organizations embraced the evidence-based policy agenda, with results that are at best mixed – possibly because of the weak and simplistic theoretical foundations of this agenda.

Another domain where there has been progress is within theories of the policy process developed by political scientists. Colleagues working on the advocacy coalition framework (ACF), the narrative policy framework, and other established theories have contributed with empirical and conceptual insights to our understanding of beliefs systems, knowledge utilization, the presentation of knowledge in policy narratives, and mechanisms of learning.

Beyond political science, there has been an exciting number of scholarly waves concerned with learning. An example is the organizational and managerial approach. Grounded in organizational theory, authors like Metcalfe (1993) Have underlined the importance of learning processes for governmental innovation. Etheredge and Short (1983) have also proposed the concept of ‘governmental learning’ to name “the process by which governments increase their intelligence and sophistication and in this manner enhance the effectiveness of their actions” (Etheredge and Short 1983: 77–8). On the other hand, the adoption of a ‘learning perspective’ on the behaviour of organizations has also contributed significantly to the field. Reviews of this field include Easterby-Smith and Lyles (2011) or Argote (2013), for example. Organizational learning is concerned with all organizations, but there is a clear niche of public administration research on specific forms of learning in public organizations (e.g. Common 2004; Gilson et al. 2009; Moynihan and Landuyt 2009). Other important disciplines include cognitive psychology, evolutionary and experimental economics, and adult education. Sociology and network theory and models have provided fundamental tools to understand learning. In conclusion, the scene is set for interdisciplinary work. Experiments have become a classic way to ascertain whether learning follows the pathways hypothesized by political scientists, or other, intriguing but less explored micro and organizational mechanisms (Kamkhaji and Radaelli 2017).

The logic of psychological biases is helpful to further our understanding of cross-coalitions relations (e.g., Fisher et al. 2016; Leach & Sabatier, 2005). Psychological heuristics show why policy learning and its consistency are rather limited (e.g. Moyson, 2017). Several recent papers provide syntheses of recent theoretical developments related to policy learning (Dunlop & Radaelli, 2013, 2017; Moyson & Scholten, 2018; Moyson et al., 2017; Heikkila & Gerlak, 2013).

Expected contributions and publication project
Building policy learning as a theory, i.e. a privileged lens to explain policy processes, decisions and outcomes, is a very exciting prospect at this moment in time, but it is still work in progress. And we need help from disciplines other than political science.

Any strong framework, or lens, or theory emerges from the right articulation of existing bodies of work and their application to new questions and/or new contexts. For this workshop we welcome political science-inspired papers on the micro-foundations of learning, its organizational dimensions, and the macro consequences of learning, in single policy domains or across countries and policies. We welcome papers on the inefficiency of learning, its power implications, and its implications for legitimacy and democracy. Its high time normative questions about learning were addressed openly and systematically.

But we also warmly invite submissions from colleagues willing to open up their analytical vision to the cognitive and behavioral sciences, as well as sociology and other social sciences. We do not privilege any type of methods or approach, although we obviously care about sound methodology, transparency in reporting findings, and the quality of research design. The papers will be both empirical and conceptual, the important element being that they contribute to cross-fertilization and to the construction of policy learning theory. We will rely on the contributions to the workshop to submit a special issue proposal to a top-ranked journal in public policy research, such as the Journal of European Public Policy, the Journal of Policy Analysis and Management, the Policy Studies Journal, or the Review of Policy Research. Our ability to do that will depend on the quality and coherence of the group of contributions. The choice of the journal will depend on the content of the contributions.

Organization of the workshop
TIMELINE

·       Day 1:

o   1st ½ of morning: Keynote on policy learning by one of the chairs

o   2nd ½ of morning + afternoon: Discussion of 5 papers

·       Day 2:

o   Discussion of 6 papers

o   Dinner

·       Day 3:

o   Discussion of 4 papers

o   General discussion on key guidelines in order to implement the publication project

PAPER DISCUSSION AND SELECTION

·       Each participant will receive feedback from the chairs by email before the workshop

·       After fifteen minutes of presentation, each paper will be discussed by the other participants (one assigned discussant + audience) during one hour.

·       Each participant will receive a notification whether panel chairs want to select his or her paper for the publication project one week after the workshop.

References

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Bennett, C. and Howlett, M. (1992). The lessons of learning: Reconciling theories of policy learning and policy change. Policy Sciences, 25, 275-294.

Challies, E., J. Newig, E. Kochskämper and N. Jager (2017). ‘Governance Change and Governance Learning in Europe: Stakeholder Participation in Environmental Policy Implementation’, Policy & Society, 36(2), 288-303.

Common, R. (2004), ‘Organisational learning in a political environment’, Policy Studies, 25 (1), 35–49.

Deutsch, K. W. (1963), The Nerves of Government: Models of Political Communication and Control, Free Press.

Dolowitz, D. P. and D. Marsh (2000), ‘Learning from Abroad: The Role of Policy Transfer in Contemporary Policy-Making’, Governance, 13 (1), 5–23.

Dunlop, C.A. (2017) ‘Epistemic communities and the irony of policy learning’, Policy and Society 36, 2: 215-232

Dunlop, C.A. (2017) ‘Pathologies of policy learning: what are they and how do they contribute to policy failure?’, Policy and Politics 45, 1: 19-3

Dunlop, C.A. (2017) ‘Policy learning and policy failure: definitions, dimensions and intersections’, Policy and Politics 45, 1: 3-18

Dunlop, C.A. and Radaelli, C. (2013). Systematising policy learning: From monolith to dimensions. Political Studies, 61, 599-619.

Dunlop, C.A. and Radaelli, C.M (2017) ‘Learning in the bathtub’, Policy and Society 36, 2: 304-319

Dunlop, C.A. and Radaelli, C.M. (2016) Policy learning in the Eurozone crisis: modes, power and functionality. Policy Sciences, 49, 2: 107-124

Easterby-Smith, M. and M. A. Lyles (2011), Handbook of Organizational Learning and Knowledge Management, John Wiley & Sons.

Etheredge, L. S. and J. Short (1983), ‘Thinking About Government Learning’, Journal of Management Studies, 20 (1), 41–58.

Fischer, M., K. Ingold, P. Sciarini and F. Varone (2016), ‘Dealing with Bad Guys: Actor- and Process-Level Determinants of the “Devil Shift” in Policymaking’, Journal of Public Policy, 36(2), 309-334.

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Gilson, C., P. Dunleavy and J. Tinkler (2009), Organizational Learning in Government Sector Organizations:Literature Review, Monograph, accessed 19 September 2017 at http://www.nao.org.uk/report/helping-government-learn/.

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Heclo, H. (1974). Modern social politics in Britain and Sweden: From relief to income maintenance. New Haven, CT / London: Yale University Press.

Heikkila, T., & Gerlak, A. (2013). Building a conceptual approach to collective learning: Lessons for public policy scholars. Policy Studies Journal, 41, 484-512.

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Jenkins-Smith, H. C., C. Nohrstedt, C. M. Weible and P. A. Sabatier (2014), ‘The Advocacy Coalition Framework: Foundations, Evolution, and Ongoing Research’, in P. A. Sabatier and C. M. Weible (eds), Theories of the Policy Process, Boulder, CO: Westview Press.

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Lachapelle, E., & Montpetit, E. (2015). Can policy actors learn from academic scientists? Implications for the Rehabilitation of Contaminated Sites. Environmental Politics, 24(5), 661-680.

Leach, W. and P. Sabatier (2005), ‘To Trust an Adversary: Integrating Rational and Psychological Models of Collaborative Policymaking’, American Political Science Review, 99(4), 491-503.

Leach, W., Weible, C., Vince, S., Sidikki, S., and Calanni, J. (2014). Fostering learning through collaboration: Knowledge acquisition and belief change in marine aquaculture partnerships. Journal of Public Administration Research and Theory, 24(3), 591-622.

Lertzman, K., Rayner, J., & Wilson, J. (1996). Learning and change in the British Columbia forest sector: A consideration of Sabatier's advocacy coalition framework. Canadian Journal of Political Science, 29(1), 111-133.

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Marsh, D. and J. C. Sharman (2009), ‘Policy diffusion and policy transfer’, Policy Studies, 30 (3), 269–88.

Meseguer, C. (2004), ‘What Role for Learning? The Diffusion of Privatisation in OECD and Latin American Countries’, Journal of Public Policy, 24 (3), 299–325.

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Moynihan, D. P. and N. Landuyt (2009), ‘How Do Public Organizations Learn? Bridging Cultural and Structural Perspectives’, Public Administration Review, 69 (6), 1097–105.

Moyson, S. (2014). The individual in policy change: Policy learning in the liberalization of network industries in Belgium. PhD thesis, Université catholique de Louvain, Louvain-la-Neuve, Belgium.

Moyson, S. (2017). ‘Cognition and Policy Change: The Consistency of Policy Learning in the Advocacy Coalition Framework’, Policy & Society, 36(2), 320-344.

Moyson, S. (2017). Policy learning over a decade or more and the role of interests therein: The European liberalization policy process of Belgian network industries Public Policy and Administration

Moyson, S. and P. Scholten (2018), ‘Theories on policy learning: Existing approaches and future challenges’, in N. Dotti (ed), Knowledge, Policymaking and Learning for European Cities and Regions, New York, NY: Palgrave.

Moyson, S., P. Scholten and C. Weible (2017), ‘Policy Learning and Policy Change: Theorizing their Relations from Different Perspectives’, Policy & Society, 36(2), 161-177.

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Witting, A., & Moyson, S. (2015). Learning in post-recession framing contests: Changing UK road policy. In N. Schiffino, L. Taskin, J. Raone & C. Donis (Eds.), Organising after crisis: The challenge of learning. Brussels, Belgium: Peter Lang.

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Learning is essential to public policy. The policy process is also a process where knowledge is created, assimilated, assembled, and diffused across time and space. Recently, we have made considerable progress on the causes and consequences of policy learning, hence this is a good moment in the development of the field to be bold and attend to the construction of a theory of policy learning. Basically, the foundations of such a theory invite us to reflect and sharpen our tools for the explanation of the emergence of policy learning and the political consequences of learning. At the outset, we have challenging questions raised by the causality of learning: why does learning happen this way or another way, or does not happen at all? Can we design the policy process so that learning mechanisms take place in desirable ways?

We know that learning is not a monolith: actors process knowledge in different learning modes, and each of these modes requires its own explanation. At the same time, we need to be more precise, open and systematic in dissecting the normative dimension of learning.

Looking at the consequences, learning about policy is not always functional. It depends on what is learned exactly, by whom and in what context. Learning can increase power asymmetries and reduce the legitimacy of public policy – ‘learning for whom’?. Or we can learn the wrong lesson, from the wrong teachers, with skewed diffusion of beliefs, with consequences that decrease the quality of public policy. Thinking of outcomes, we need to tackle questions about the process which leads actors to select a different view of how things happen (‘learning that’) and what courses of action should be taken (‘learning how’). The field has to open up to questions of legitimacy and democratic quality, then re-connecting power and learning research agendas.

Any strong discipline, framework, or theory emerged from the right articulation of existing bodies of work and their application to new questions and/or new contexts. Recent studies have relied on various theoretical foundations to look at policy learning and contribute to the emergence of policy learning as an autonomous theory of the policy process. Others have made progress on learning within existing theories of the policy process, such as the advocacy coalitions framework, spatial models of diffusion, and the narrative policy framework. Most interestingly, we have seen political scientists getting increasingly curious and able to use the findings of cognitive psychology and evolutionary-experimental economics to explain some key variables at work in learning processes. The same applies to the input provided by different strands of sociology, adult education theories, ethnography and other fields in the social sciences.

In short, the establishment of policy learning as a theory, i.e. a privileged lens to explain policy processes, decisions and outcomes, is very exciting at this moment in time, but it is still work in progress. And we need help from disciplines other than political science.

Any strong framework, or lens, or theory emerges from the right articulation of existing bodies of work and their application to new questions and/or new contexts. For this workshop we welcome political science-inspired papers on the micro-foundations of learning, its organizational dimensions, and the macro consequences of learning, in single policy domains or across countries and policies. But we also warmly invite submissions from colleagues willing to open up their analytical vision to the cognitive and behavioral sciences, as well as sociology and other social sciences. We do not privilege any type of methods or approach, although we obviously care about sound methodology, transparency in reporting findings, and the quality of research design. The papers will be both empirical and conceptual, the important element being that they contribute to cross-fertilization and to the construction of policy learning theory.

Learning is essential to public policy. The policy process is also a process where knowledge is created, assimilated, assembled, and diffused across time and space. This does not necessarily mean that learning is always functional, or hasn’t got undesirable consequences in terms of power and inequalities. Controlling ideas means controlling uncertainty and meanings. In other words, we need to answer questions about the process which leads actors to select a different view of how things happen (‘learning that’) and what courses of action should be taken (‘learning how’).

Equally challenging is the set of questions raised by the causality of learning: why does learning happen this way or another way, or does not happen at all? Can we design the policy process so that learning takes place in desirable ways? Finally, learning is not a monolith: actors process knowledge in different learning modes, and each of these modes requires its own explanation.

The establishment of policy learning as a theory, i.e. a privileged lens to explain policy processes, decisions and outcomes, is still work in progress. Any strong theoretical framework emerges from the right articulation of existing bodies of work and their application to new questions and/or new contexts. For this workshop we welcome political science-inspired papers on the micro-foundations of learning, its organizational dimensions, and the macro consequences of learning, in single policy domains or across countries and policies. But we also warmly invite submissions from colleagues willing to open up their analytical vision to the cognitive and behavioral sciences, as well as sociology and other social sciences. We do not privilege any type of methods or approach, although we obviously care about sound methodology, transparency in reporting findings, and the quality of research design. The papers will be both empirical and conceptual, the important element being that they contribute to cross-fertilization and to the construction of policy learning theory.

Professor Claire A. DUNLOP (c.a.dunlop@exeter.ac.uk) is Professor of Politics at the Department of Politics at the University of Exeter, United Kingdom. A public policy and administration scholar, Claire’s main fields of interest include the politics of expertise and knowledge utilization; epistemic communities and advisory politics; risk governance; policy learning and analysis; impact assessment; and policy narratives. She explores these conceptual interests at the UK and EU levels principally, and most frequently in relation to agricultural, environmental and LGBT issues. Claire has published more than 40 peer-reviewed journal articles and book chapters – most recently in Policy and Politics, Policy Sciences, International Public Management Journal, Regulation & Governance and Journal of European Public Policy. She was co-director of the 2011 ECPR Joint Sessions Workshop on Politics and Learning in St Gallen, and has organised a wide variety of policy panels at a range of conferences – most recently ECPR, APSA, PSA (UK), ICPP and IPSA. Between 2010 and 2016, Claire was convenor of the UK Political Studies Association’s (PSA) Public Policy and Administration specialist group. In 2014, she became editor of Public Policy and Administration.

Dr. Stéphane MOYSON (stephane.moyson@uclouvain.be) is an Assistant Professor of Public Policy at the Institut de Sciences Politiques Louvain-Europe (ISPOLE) of the Université Catholique de Louvain (UCLouvain). Many of his recent conference papers (e.g., ECPR, ICPP, MPSA, IRSPM etc.) and publications focus on the role of cognition and learning in policy change processes:

Moyson, S., & Scholten, P. (2018). Theories on policy learning: Existing approaches and future challenges. In N. Dotti (Ed.), Knowledge policy-making and learning for European Regions and Cities. London, UK: Edward Elgar.

Moyson, S., Scholten, P., & Weible, C. (2017). Policy learning and policy change: Theorizing their relations from different perspectives. Policy and Society, 36(2),  161-177.

Moyson, S. (2017). Cognition and policy change: The consistency of policy learning in the advocacy coalition framework. Policy and Society, 36(2),  320-344.

Moyson, S. (2016, Early view). Policy learning and the role of interests therein: The liberalization policy process of networks industries in Belgium. Public Policy & Administration.

Professor Claudio M. RADAELLI (c.radaelli@exeter.ac.uk) is Director of the Centre for European Governance at the University of Exeter, Department of Politics, where he is professor of political science and Jean Monnet Chair in EU Political Economy. Claudio teaches modules on regulation, the single market of the European Union, and EU politics. He has also taught MA modules on research design at Exeter and at the University of Kristiansand, Norway.

He has published more than 70 articles and 18 special issues and authored-edited volumes on research design, policy learning, Europeanization, and regulation. His first ERC (European Research Council) project was calibrated around empirical and theoretical questions about learning. This project, carried out with Claire A. Dunlop, was called Analysis of Learning in Regulatory Governance (ALREG), and completed in 2014, although output from the project is still in the process of being published in academic journals and books. Claudio was chair of the ECPR Standing Group on Regulation & Governance in 2010-2012 and co-editor of the European Journal of Political Research between 2009 and 2015.

At the moment Claudio is carrying out a second large project funded by the European Research Council on Procedural Tools for Effective Governance, PROTEGO. The research team includes Alessia Damonte, Claire Dunlop, Jonathan Kamkhaji and Claudio. PROTEGO will last until 2020.