Shopping in the scientific marketplace : COVID-19 through a policy learning lens

In this article, we explain how the COVID-19 wicked crisis context influences the quality of critically needed epistemic policy learning and undermines policy effectiveness. We explore those influences on two main dimensions: Vertically (pertaining to the selection of core scientific advice) and horizontally (pertaining to managing scientific interdisciplinarity). We apply the concept using COVID-19 policy responses from England and Belgium, offer an explanatory framework, and provide recommendations for policymakers, including (i) Crafting a policy-science-public narrative maintaining independence, openness, and trust. (ii) Outlining the limitations of science and public expectation setting. (iii) Enhancing interdisciplinarity in policy formulation by utilizing boundary and discipline-spanning structures, and systems thinking mechanisms for dynamic problem synthesis

Jonathan C. KAMKHAJI, Policy learning and the Euro. The EU's responses to the sovereign debt crisis

Why do actors in the world of policy do what they do? This remains a quintessential question in public policy scholarship. It is intriguing not only for academics, but also for a public often puzzled by trying to understand the “why” and “how” of government action as well as inaction. Policy learning scholarship tries to answer this question by investigating why policy actors do what they do as a function of what and how they learn about policy issues. In this view of the world, learning is u..

A guide to benchmarking COVID‐19 performance data

If the COVID‐19 pandemic has already taught us anything, it is that policymakers, experts and public managers need to be capable of interpreting comparative data on their government's performance in a meaningful way. Simultaneously, they are confronted with different data sources (and measurements) surrounding COVID‐19 without necessarily having the tools to assess these sources strategically . Due to the speed with which decisions are required and the different data sources, it can be challenging for any policymaker, expert or public manager to make sense of how COVID‐19 has an impact, especially from a comparative perspective. Starting from the question “How can we benchmark COVID‐19 performance data across countries?”, this article presents important indicators, measurements, and their strengths and weaknesses, and concludes with practical recommendations. These include a focus on measurement equivalence, systems thinking, spatial and temporal thinking, multilevel governance and multimethod designs

Characterization and comprehensive genome analysis of novel bacteriophage, vB_Kpn_ZCKp20p, with lytic and anti-biofilm potential against clinical multidrug-resistant Klebsiella pneumoniae

IntroductionThe rise of infections by antibiotic-resistant bacterial pathogens is alarming. Among these, Klebsiella pneumoniae is a leading cause of death by hospital-acquired infections, and its multidrug-resistant strains are flagged as a global threat to human health, which necessitates finding novel antibiotics or alternative therapies. One promising therapeutic alternative is the use of virulent bacteriophages, which specifically target bacteria and coevolve with them to overcome potential resistance. Here, we aimed to discover specific bacteriophages with therapeutic potential against multiresistant K. pneumoniae clinical isolates.Methods and ResultsOut of six bacteriophages that we isolated from urban and medical sewage, phage vB_Kpn_ZCKp20p had the broadest host range and was thus characterized in detail. Transmission electron microscopy suggests vB_Kpn_ZCKp20p to be a tailed phage of the siphoviral morphotype. In vitro evaluation indicated a high lytic efficiency (30 min latent period and burst size of ∼100 PFU/cell), and extended stability at temperatures up to 70°C and a wide range of (2-12) pH. Additionally, phage vB_Kpn_ZCKp20p possesses antibiofilm activity that was evaluated by the crystal violet assay and was not cytotoxic to human skin fibroblasts. The whole genome was sequenced and annotated, uncovering one tRNA gene and 33 genes encoding proteins with assigned functions out of 85 predicted genes. Furthermore, comparative genomics and phylogenetic analysis suggest that vB_Kpn_ZCKp20p most likely represents a new species, but belongs to the same genus as Klebsiella phages ZCKP8 and 6691. Comprehensive genomic and bioinformatics analyses substantiate the safety of the phage and its strictly lytic lifestyle.ConclusionPhage vB_Kpn_ZCKp20p is a novel phage with potential to be used against biofilm-forming K. pneumoniae and could be a promising source for antibacterial and antibiofilm products, which will be individually studied experimentally in future studies

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

Policy learning governance : a new perspective on agency across policy learning theories

The predominant ontological position on agency in policy learning literature has been relatively learner-oriented, thus focusing on policy actors puzzling about policy problems. In other words, it focuses on how actors acquire, translate, and disseminate knowledge and information to address policy problems or ‘puzzles’. However, despite its influence on learning and its outcomes, policy actors’ powering, or agency in shaping learning processes has been scarcely explored or theorised. Drawing on policy learning literature, this article explores and demarcates the concept of ‘policy learning governance’ as a supplementary perspective to the learner-oriented view of agency in policy learning research. Here, learning governance can be understood as the deliberate processes by which policy actors strategise, design, and govern policy learning processes towards achieving technical or political objectives. This article explains how integrating a learning governance perspective into existing conceptual approaches to policy learning can provide a better basis for understanding the interactions between different constitutive elements of policy learning processes and outcomes, such as policy or belief change. In this way, it offers a more robust baseline for explaining learning processes, an advancement that has significant implications for both policy learning theory and practice

Hello darkness my old friend: How policy learning can contribute to value destruction

For decades, policy learning has been often viewed as a force for the common good, a process that aims at creating value for the public through problem-solving. While learning can indeed contribute to value creation, darkness also lurks therein, where learning can also contribute to value destruction. Yet, the dark side of policy learning remains under-explored and under-theorized, particularly going beyond meso-level policy and organizational failures or “mishaps.” This article draws on policy learning and value theories to conceptualize two types of policy learning failures and plot how they can contribute to the destruction of value in the public sphere: misdirected learning design failures (non-deliberate and cybernetic) and normative failures (intentional and deontological). This is done while addressing the two key facets of value in the public sphere; public values, being the guiding principles of policymaking and governance, as well as public value, being the worth of public services delivered to the citizenry. In doing so, this contributes to the literature by addressing calls for exploring the dark side of learning, expanding our understanding of learning outcomes beyond organizational and policy level implications, and developing novel fundamental understandings of value destruction mechanisms

New development : strategic planning in interesting times : from inter-crisis to intra-crisis responses

This article discusses how emerging types of crises provide opportunities for strategic planning as a form of intra-crisis response. The article supplements existing literature and approaches to strategic planning that conventionally emphasize its value in relatively more stable conditions or mostly as a platform for pre-crisis preparedness

Practicing policy learning during creeping crises: key principles and considerations from the COVID-19 crisis

AbstractPolicy learning plays a critical role in crisis policymaking. Adequate learning can lead to effective crisis responses, while misdirected learning can derail policymaking and lead to policy fiascos, potentially with devastating effects. However, creeping crises such as the recent COVID-19 pandemic pose significant challenges for doing “good” policy learning. Such crises pose persistent threats to societal values or life‐sustaining systems. They evolve across time and space while stirring significant political and societal tensions. Given their inherent features, they are often insufficiently addressed by policymakers. Taking the COVID-19 crisis as an illustrative example, this article aims to draw practitioners’ attention to key features of creeping crises and explains how such crises can undermine critical policy learning processes. It then discusses the need for “policy learning governance” as an approach to design, administer and manage crisis policy learning processes that are able to respond to continuous crisis evolutions. In doing so, it helps practitioners engage in adaptive and agile policy learning processes toward more effective learning by introducing four key principles of policy learning governance during creeping crises. Those are: identifying optimum learning modes and types, learning across disciplines, learning across space, and learning across time. Practical tools distilled from emerging research are then introduced to help apply the proposed principles of policy learning governance during future crises