Building Organizational Political Capacity Through Policy Learning: Communicating with Citizens on Health and Safety in the UK

This is the author accepted manuscript. The final version is available from Palgrave Macmillan via the DOI in this record In this chapter, we examine how agencies build organizational political capacities (OPC) for reputation management, where capacity building is treated as a challenge underpinned by the learning relationships that exist between key governance actors. This challenge requires the development of four types of OPC: absorptive capacity (ACAP); administrative capacity (ADCAP); analytical capacity (ANCAP) and communicative capacity (COMCAP). Analytically, we link each of these capacities to one particular type of policy learning—reflexive learning—which characterizes politicized situations where an agency’s reputation is under threat and citizens are the main governance partners. Empirically, we demonstrate how agencies learn to develop these OPCs with governance partners using the case of the UK Health and Safety Executive (HSE) which increasingly aims to engage citizens in a dialogue to combat the negative images attached to health and safety regulation. We conclude by asking what a learning approach tells us about how agencies can develop OPC.European CommissionEconomic and Social Research Council (ESRC

If Evaluation is the Solution, What is the Problem?

This is the author accepted manuscript. The final version is available from Routledge via the link in this record.Over the years, there has been a proliferation of initiatives, methods and tools for evaluation in the European Union (EU). In 2015, the Commission produced a set of integrated guidelines and a single toolbox for better regulation, with the ambitious aim of closing the policy cycle, that is, to draw on evaluation methods systematically from the stage of policy formulation to (a) the end of a project or (b) the moment of ex-post regulatory review. The idea of ‘closing the policy cycle’ is intuitively attractive, but in practice it raises issues of who is exercising control and oversight of different evaluation approaches and tools inside the Commission, the relationship between the Member States and the Commission, and the inter-institutional relations that define power within ‘better regulation’. We examine across time the emergence of different types of evaluation (ex ante and ex post, regulatory evaluations and more traditional approaches to expenditure evaluation) as ‘solutions’, and associate them to problems. We find that the goal of closing the policy cycle is a very tall order for the Commission and the EU more generally, given the historical development of different problems-solutions combinations. The rise of ‘better regulation’ provides the ideational cement for this re-configuration of evaluation ‘to close the policy cycle’ but there are critical issues with tools, methods and scope of evaluation. In the end, today the pieces do not fall into place and the puzzle of ‘evaluation for whom and for what purposes’ has not been solved yet. This less-than-Cartesian puzzle, with its odd de-coupled pieces of different evaluations is not efficient if the problem is to close the policy cycle. But ambiguity is organizationally acceptable if the problem is to generate local power equilibria that can be exploited within the Commission and externally. Evaluation, in fact, is also a frame of reference and praxis where the Member States, the Sec Gen, the DGs of the Commission, the European Parliament test and constantly re-define the question of who has control over EU policy

Policy Learning in Comparative Policy Analysis

This article explores how policy learning can improve comparative policy analysis by focusing on causality in learning processes. After summarizing the comparative credentials of the policy learning literature, the article outlines a framework of four learning modes, relating it to three approaches of causality: deterministic, probabilistic, and set-theoretic. It then builds on this to explore different approaches to causation and learning in relation to: policy change, political contexts, and, finally, the temporal and spatial dimensions of comparative policy analysis. The article concludes by showing how these challenges are addressed and suggesting implications for further research

The lessons of policy learning: types, triggers, hindrances and pathologies (article)

This is the author accepted manuscript. The final version is available from Policy Press via the DOI in this record.Policy learning is an attractive proposition, but who learns and for what purposes? Can we learn the wrong lesson? And why do so many attempts to learn what works often fail? In this article, we provide three lessons. First, there are four different modes in which constellations of actors learn. Hence our propositions about learning are conditional on which of the four contexts we refer to. Second, policy learning does not just happen; there are specific hindrances and triggers. Thus, learning can be facilitated by knowing the mechanisms to activate and the likely obstacles. Third, learning itself is a conditional final aim: although the official aspiration of public organizations and politicians is to improve on public policy, policy learning can also be dysfunctional – for an organization, a policy, a constellation of actors or even democracy.The conceptual work was informed by two European Research Council (ERC) projects: Analysis of Learning in Regulatory Governance (ALREG) (grant # 230267) and Procedural Tools for Effective Governance (PROTEGO) (grant # 694632)

Regulation and Corruption: Claims, Evidence and Explanations

This is the author accepted manuscript. The final version is available from Edward Elgar via the DOI in this record.Does regulation cause corruption? In a field dominated by economics, the public administration literature has opened the peripheral view of social scientists by bringing evidence to bear on three different claims: that regulation causes corruption but under certain conditions; that it is the quality of regulation to hinder corruption; and, that anti-corruption regulation can aggravate the problem of corruption. After having reviewed and discussed the claims, we turn to recent advances in the literature and make suggestions for future research. We make the case for drawing more attention to regulatory policy instruments and point to the crucial stage of rulemaking. Next, we introduce novel ways to model causality and identify how regulation may explain corruption, contrasting the statistical worldview with set-theoretic explanations. Finally, we critically discuss the state of play with measures of corruption and how to improve.European Commissio

A Sleeping Giant Awakes? The Rise of the Institutional Grammar Tool (IGT) in Policy Research

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThe institutional grammar tool (IGT) is an important and relatively recent innovation in policy theory and analysis. It is conceptualized to empirically operationalize the insights of the Institutional Analysis and Development (IAD) framework. In the last decade, political scientists have offered a number of applications of the IGT, mainly focused on disclosing and scrutinizing in-depth the textual configurations of policy documents. These efforts, involving micro-level analyses of syntax as well as more general classifications of institutional statements according to rule types, have underpinned empirical projects mainly in the area of environmental and common-pool resources. Applications of IGT are still in their infancy, yet the growing momentum is sufficient for us to review what has been learned so far. We take stock of this recent, fast-growing literature, analysing a corpus of 26 empirical articles employing IGTs published between 2008 and 2017. We examine these in terms of their empirical domain, hypotheses, and methods of selection and analysis of institutional statements. We find that the empirical applications do not add much to explanation, unless they are supported by research questions and hypotheses grounded in theory. We offer three conclusions. First, to exploit the IGT researchers need to go beyond the descriptive, computational approach that has dominated the field until now. Second, IGT studies grounded in explicit hypotheses have more explanatory leverage, and therefore should be encouraged when adopting the IGT outside the Western world. Third, the domain of rules is where researchers can capture findings that are more explanatory and less microscopic.European Commissio

Can't get no learning: the Brexit fiasco through the lens of policy learning

It seems paradoxical to suggest that theories of learning might be used to explain policy failure. Yet the Brexit fiasco connects with recent approaches linking varieties of policy learning to policy pathologies. This article sets out to explain the UK government’s (mis)management of the Brexit process from June 2016 to May 2019 from a policy learning perspective. Drawing on interviews with UK policy-makers and stakeholders, we ask how did the UK government seek to learn during the Brexit negotiations? We consider four modes of learning: reflexivity, epistemic, hierarchical, and bargaining. By empirically tracing the policy process and scope conditions for each of these, we argue that learning through the first three modes proved highly dysfunctional. This forced the government to rely on bargaining between competing factions, producing a highly political form of learning which stymied the development of a coherent Brexit strategy. We argue that the analysis of Brexit as a policy process – rather than a political event – reveals how policy dynamics play an important role in shaping the political context within which they are located. The article concludes that public policy analysis can, therefore, add significant value to our understanding of Brexit by endogenising accounts of macro political developments

Can’t Get No Learning: The Brexit Fiasco through the Lens of Policy Learning

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordIt seems paradoxical to suggest that theories of learning might be used to explain policy failure. Yet the Brexit fiasco connects with recent approaches linking four varieties of policy learning to policy pathologies (Dunlop, 2017; Dunlop and Radaelli, 2013, 2018). This article sets out to explain the UK government’s (mis)management of the Brexit process from June 2016 to May 2019. Drawing on interviews with UK policy makers and stakeholders, we ask how did the UK government seek to learn during the Brexit negotiations? We consider four modes of learning: reflexivity, epistemic, hierarchical, and bargaining. By empirically tracing the policy process and scope conditions for each of these, we argue that learning through the first three modes proved highly dysfunctional. This forced the government to rely on bargaining between competing factions, producing a highly short-termist form of learning which stymied the development of a coherent Brexit strategy. We argue that the analysis of Brexit as a policy process (rather than a political event) reveals how policy dynamics play an important role in shaping the political context within which they are located. The article concludes that public policy analysis can therefore serve to endogenise existing accounts of macro political developments like Brexit.European Commissio

Does Policy Learning Meet the Standards of an Analytical Framework of the Policy Process

Reference to policy learning is commonplace in the public policy literature but the question of whether it qualifies as an analytical framework applicable to the policy process has yet to be systematically addressed. We therefore appraise learning as analytical framework in relation to four standards: assumptions and micro‐foundations, conceptual apparatus, observable implications, normative applications. We find that policy learning meets the four standards, although its theoretical leverage varies across them. Since we are not aware of theories of the policy process that meet all of these standards all the time, we conclude that policy learning fares reasonably well and it's worth investing intellectual resources in this field

Policy learning in comparative policy analysis

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recordWe explore how policy learning can improve comparative policy analysis by focussing on causality in learning processes. After summarising the comparative credentials of the policy learning literature, we outline a framework of four learning modes relating it to three approaches of causality: deterministic, probabilistic and set-theoretic. We then build on this to explore different approaches to causation and learning in relation to: policy change, political contexts, and, finally, the temporal and spatial dimensions of comparative policy analysis. We conclude showing how these challenges are addressed and suggest implications for further research.European CommissionBritish Counci