Policy learning : from conceptualization to measurement

Policy learning has positioned itself as a central mechanism for informing policymaking in key and critical policy domains. The research and practice of learning has progressively gained ground with the rise of complex, multidimensional policy issues and the expansion of policy networks and subsystems. The fundamental study of learning does not only offer lessons based on past experiences for future policy, but also informs real-time policymaking in response to unfolding existential crises. As such, the field has enjoyed substantial growth. Several key works have explored unchartered territories and extended our understanding of the dynamics of policy learning, its outcomes, and its relationship with policy change. However, the field still suffers from a range of conceptual, theoretical, and empirical challenges. With a myriad of conceptual approaches, policy learning is still often viewed as an ambiguous umbrella concept, with significant fragmentation. This has contributed to challenges in the systematization of findings, difficulties in maintaining empirical consistency, creating robust and reusable measurements of learning. As such, this led to relatively slowed theoretical advancement and sparked debates as to the true extent of policy learning’s analytical utility. Hence, the puzzle around-which this doctoral study is built is how can policy learning be conceptualized, identified, systematically analysed, and measured? and in doing so, how can we distil lessons for practice on how to manage the complex process of policy learning around certain policy issue? To solve this puzzle, this doctoral study begins by offering a long-needed synthesis of the vast, burgeoning, yet fragmented policy learning literature. It takes stock of the field’s key features (including commonly employed research methods, domains, theoretical lenses, geographical dispersion of policy learning studies, etc.). It also identifies the field’s key challenges and showcases the degree of conceptual fragmentation and ambiguity it endures. Leveraging a problematized review and drawing on policy learning and policy process literatures, it then offers a novel systematized conceptualization of policy learning as the circulation and consumption of policy issue-related information and knowledge among actors in a policy system and structure, within a policy context. I then elaborate on the conceptualization’s theoretical coherence and the avenues through which it contributes to a better systematization of findings, theoretical advancement and creating policy learning measurements. From there on, through 4 different methodologically diverse studies, I focus on COVID-19 as an existential complex policy issue and empirically explore the key features and utility of this conceptualization as an analytical framework of policy learning. This applies and further empirically substantiates the conceptualization’s key features that underly policy learning processes including interactivity between systems and structures, actors, perturbations in the policymaking context, and policy issue formulation. In conclusion, findings from these studies and the broader policy learning, policy process and social sciences measurement literature are leveraged with the proposed conceptualization of learning to construct an overarching theoretically coherent framework for policy learning measurements development. In doing so, this doctoral dissertation offers policy learning scholarship a theoretically coherent framework for policy learning analysis from conceptualization to measurement and provides avenues for how this framework can be used to further advance policy learning research and theory. Furthermore, it offers practitioners a practical toolkit to scrutinize, analyse and appraise the existing and future policy learning frameworks. This dissertation encompasses seven chapters. Chapter one “Introduction” offers an overview of the background, motivation, aims, scope, scientific, societal, relevance and structure of this doctoral study. Chapter two “A Systematic Review and Conceptualization of Policy Learning”, synthesizes the burgeoning policy learning literature, offers a background conceptualization of policy learning, and highlights how this can be used as an analytical framework of policy learning processes. Starting chapter three I begin the systematic application of the proposed conceptualization as an analytical framework of policy learning processes using a case of the COVID-19 pandemic. In doing so, this doctoral study research policy learning processes within a creeping crisis context, a previously unresearched setting for policy learning. This helps us extend policy learning theory by exploring how creeping crises influence policy learning. On the practical and societal fronts, this study directly and promptly heeds the call for policy learning oriented research on the COVID-19 pandemic that provides usable takeaways for theory and practice. As the COVID-19 crisis is ongoing and with the potential of other crises to recur, this study offers insights to both researchers and practitioners into critical policy learning processes and charters avenues for how they can be better managed and streamlined within the currently ongoing and future crises. In chapter three, I explore how existing political contexts and institutional legacies influence the design and implementation of policy learning processes and policy-issue knowledge utilization using case studies from Belgium and the United Kingdom. In Chapter four “Policy learning and Multilevel Governance structures”, I explore how policy learning takes place across different levels of the multilevel governance architecture within crisis conditions. Variations across different governance levels are accounted for through exploring the role of different actors, contextual variations leading to different levels of control over the learning process, and their implications for engaging with expertise. In Chapter five “Policy Learning Type Shifts and Interactions: A storyboard of COVID-19 Policy Learning in Belgium”, I explore how the dynamism of the policy issue influences the interaction between actors, policy-issue knowledge and induce shifts in policy learning modes in relatively short periods of time. In Chapter six “Policy Learning: A framework for measurements development” with the empirical value of this analytical framework exercised, I leverage these findings and a problematized review of policy learning literature to propose a theoretically coherent framework for developing policy learning measurements that focuses on accounting for the roles of actors, structures, information and knowledge and contextual variations. Last, in Chapter seven “Discussion and Conclusions”, a reflection on the key findings of this doctoral study’s key implications for future theory, research, and practice are offered while highlighting the limitations therein