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In recent years a set of new ‘postempiricist’ approaches to public policy, drawing on discursive analysis and participatory deliberative practices, have come to challenge the dominant technocratic, empiricist models in policy analysis. In this book, Frank Fischer brings together this work for the first time and critically examines its implications for the field of public policy studies. He describes the theoretical, methodological and political dimensions of this emerging approach to policy research. The book includes a discussion of the social construction of policy problems, the role of interpretation and narrative analysis in policy inquiry, the dialectics of policy argumentation, and the uses of participatory policy analysis. After an introductory chapter, ten further chapters are arranged in four parts: Part I, Public Policy and the Discursive Construction of Reality (two chapters), introduces the re-emergence of interest in ideas and discourse. It then turns to the postempiricist or constructionist view of social reality, presenting public policy as a discursive construct that turns on multiple interpretations. Part II, Public Policy as Discursive Politics (two chapters), examines more specifically the nature of discursive politics and discourse theory and illustrates through a particular disciplinary debate the theoretical, methodological, and political implications of such a conceptual reframing of policy inquiry. Part III, Discursive Policy Inquiry: Resituating Empirical Analysis (four chapters), offers a postempiricist methodology for policy inquiry based on the logic of practical discourse, and explores specific methodological perspectives pertinent to such an orientation, in particular the role of interpretation in policy analysis, narrative policy analysis, and the dialectics of policy argumentation. Part IV, Deliberative Governance (two chapters), discusses the participatory implications of such a method and the role of the policy analyst as facilitator of citizen deliberation .

Critical policy studies, as illustrated in this handbook, challenges the conventional approaches of public policy inquiry. But it offers important innovations as well, in particular its focus on discursive politics, policy argumentation and deliberation and interpretive modes of analysis. This volume offers a compilation of critical work that assesses past developments and appraises emerging issues.

Simulation-based learning offers a wide range of opportunities to practice complex skills in higher education and to implement different types of scaffolding to facilitate effective learning. This meta-analysis includes 145 empirical studies and investigates the effectiveness of different scaffolding types and technology in simulation-based learning environments to facilitate complex skills. The simulations had a large positive overall effect: g = 0.85, SE = 0.08; CIs [0.69, 1.02]. Technology use and scaffolding had positive effects on learning. Learners with high prior knowledge benefited more from reflection phases; learners with low prior knowledge learned better when supported by examples. Findings were robust across different higher education domains (e.g., medical and teacher education, management). We conclude that (1) simulations are among the most effective means to facilitate learning of complex skills across domains and (2) different scaffolding types can facilitate simulation-based learning during different phases of the development of knowledge and skills.

The study of public policy and the methods of policy analysis are among the most rapidly developing areas in the social sciences. Policy analysis has emerged to provide a better understanding of the policymaking process and to supply decision makers with reliable policy-relevant knowledge about pressing economic and social problems. Presenting a broad, comprehensive perspective, the Handbook of Public Policy Analysis: Theory, Politics, and Methods covers the historical development of policy analysis, its role in the policy process, and empirical methods. The handbook considers the theory generated by these methods and the normative and ethical issues surrounding their practice. Written by leading experts in the field, this book- Deals with the basic origins and evolution of public policy Examines the stages of the policy-making process Identifies political advocacy and expertise in the policy process Focuses on rationality in policy decision-making and the role of policy networks and learning Details argumentation, rhetoric, and narratives Explores the comparative, cultural, and ethical aspects of public policy Explains primary quantitative-oriented analytical methods employed in policy research Addresses the qualitative sides of policy analysis Discusses tools used to refine policy choices Traces the development of policy analysis in selected national contexts The Handbook of Public Policy Analysis: Theory, Politics, and Methods describes the theoretical debates that have recently defined the field, including the work of postpositivist, interpretivist, and social constructionist scholars. This book also explores the interplay between empirical and normative analysis, a crucial issue running through contemporary debates. HISTORICAL PERSPECTIVES The Policy Sciences at the Cross-Roads Promoting the Policy Orientation: Lasswell in Context Public Policy, Social Science and the State: An Historical Perspective POLICY PROCESSES Theories of the Policy Cycle Agenda Setting in Public Policy Policy Formulation: Design and Tools Implementing Public Policy Do Policies Determine Politics? An Analysis of Lowi's Policy Typology POLICY POLITICS, ADVOCACY, AND EXPERTISE A Guide to the Advocacy Coalition Framework Policy Communities Policy Analysis and Think Tanks POLICY DECISION MAKING: RATIONALITY, NETWORKS, AND LEARNING. Rationality in Policy Decision-Making Rational Choice in Public Policy: The Theory in Critical Perspective Taking Stock of Policy Networks: Do They Matter? Theories of Policy Learning: Agency, Structure, and Change DELIBERATIVE POLICY ANALYSIS: ARGUMENTATION, RHETORIC, AND NARRATIVES Deliberative Policy Analysis as Practical Reason: Integrating Empirical and Normative Arguments Rhetoric in Policy-Making: Between Logos, Ethos, and Pathos Narrative Policy Analysis COMPARATIVE, CULTURAL, AND ETHICAL PERSPECTIVES Comparative Public Policy Applied Cultural Theory: Tool for Policy Analysis Ethical Issues and Public Policy Public Policy and Democratic Citizenship: What Kinds of Citizenship Does Policy Promote? QUANTITATIVELY-ORIENTED POLICY METHODS Quantitative Methods for Policy Analysis The Use (and Misuse) of Survey Research in Policy Analysis Social Experiments and Public Policy Evaluation Research in Policy Analysis QUALITATIVE POLICY ANALYSIS: INTERPRETATION, MEANING, AND CONTEXT Qualitative-Interpretive Methods in Policy Research Qualitative Research and Public Policy Interpretation and Intention in Policy Analysis Context Sensitive Policy Methods POLICY DECISION TECHNIQUES Cost-Benefit Analysis Environmental Impact Assessment: Between Bureaucratic Process and Social Learning. Technology Assessment as Policy Analysis: From Expert Advice to Participatory Approaches Public Policy Mediation: From Argument to Collaboration COUNTRY PERSPECTIVES Policy Analysis in Britain Evolution of Policy Analysis in the Netherlands Policy Analysis and Evaluation in Sweden: Discovering the Limits of the Rationalistic Paradigm Policy Analysis in Germany Policy Analysis in India Policy Analysis in Korea: From Economic Efficiency to Public Participation

Sirtuins are protein deacetylases regulating metabolism and stress responses. The seven human Sirtuins (Sirt1–7) are attractive drug targets, but Sirtuin inhibition mechanisms are mostly unidentified. We report the molecular mechanism of Sirtuin inhibition by 6-chloro-2,3,4,9-tetrahydro-1H-carbazole-1-carboxamide (Ex-527). Inhibitor binding to potently inhibited Sirt1 and Thermotoga maritima Sir2 and to moderately inhibited Sirt3 requires NAD ⁺, alone or together with acetylpeptide. Crystal structures of several Sirtuin inhibitor complexes show that Ex-527 occupies the nicotinamide site and a neighboring pocket and contacts the ribose of NAD ⁺ or of the coproduct 2’- O -acetyl-ADP ribose. Complex structures with native alkylimidate and thio-analog support its catalytic relevance and show, together with biochemical assays, that only the coproduct complex is relevant for inhibition by Ex-527, which stabilizes the closed enzyme conformation preventing product release. Ex-527 inhibition thus exploits Sirtuin catalysis, and kinetic isoform differences explain its selectivity. Our results provide insights in Sirtuin catalysis and inhibition with important implications for drug development.

Sirtuins are protein deacetylases regulating metabolism, stress responses, and aging processes, and they were suggested to mediate the lifespan extending effect of a low calorie diet. Sirtuin activation by the polyphenol resveratrol can mimic such lifespan extending effects and alleviate metabolic diseases. The mechanism of Sirtuin stimulation is unknown, hindering the development of improved activators. Here we show that resveratrol inhibits human Sirt3 and stimulates Sirt5, in addition to Sirt1, against fluorophore-labeled peptide substrates but also against peptides and proteins lacking the non-physiological fluorophore modification. We further present crystal structures of Sirt3 and Sirt5 in complex with fluorogenic substrate peptide and modulator. The compound acts as a top cover, closing the Sirtuin's polypeptide binding pocket and influencing details of peptide binding by directly interacting with this substrate. Our results provide a mechanism for the direct activation of Sirtuins by small molecules and suggest that activators have to be tailored to a specific Sirtuin/substrate pair.

We develop a fully asynchronous proximal bundle method for solving non-smooth, convex optimization problems. The algorithm can be used as a drop-in replacement for classic bundle methods, i.e., the function must be given by a first-order oracle for computing function values and subgradients. The algorithm allows for an arbitrary number of master problem processes computing new candidate points and oracle processes evaluating functions at those candidate points. These processes share information by communication with a single supervisor process that resembles the main loop of a classic bundle method. All processes run in parallel and no explicit synchronization step is required. Instead, the asynchronous and possibly outdated results of the oracle computations can be seen as an inexact function oracle. Hence, we show the convergence of our method under weak assumptions very similar to inexact and incremental bundle methods. In particular, we show how the algorithm learns important structural properties of the functions to control the inaccuracy induced by the asynchronicity automatically such that overall convergence can be guaranteed.

Clinical reasoning theories agree that knowledge and the diagnostic process are associated with diagnostic success. However, the exact contributions of these components of clinical reasoning to diagnostic success remain unclear. This is particularly the case when operationalizing the diagnostic process with diagnostic activities (i.e., teachable practices that generate knowledge). Therefore, we conducted a study investigating to what extent knowledge and diagnostic activities uniquely explain variance in diagnostic success with virtual patients among medical students. The sample consisted of N  = 106 medical students in their third to fifth year of university studies in Germany (6-years curriculum). Participants completed professional knowledge tests before diagnosing virtual patients. Diagnostic success with the virtual patients was assessed with diagnostic accuracy as well as a comprehensive diagnostic score to answer the call for more extensive measurement of clinical reasoning outcomes. The three diagnostic activities hypothesis generation, evidence generation, and evidence evaluation were tracked. Professional knowledge predicted performance in terms of the comprehensive diagnostic score and displayed a small association with diagnostic accuracy. Diagnostic activities predicted comprehensive diagnostic score and diagnostic accuracy. Hierarchical regressions showed that the diagnostic activities made a unique contribution to diagnostic success, even when knowledge was taken into account. Our results support the argument that the diagnostic process is more than an embodiment of knowledge and explains variance in diagnostic success over and above knowledge. We discuss possible mechanisms explaining this finding.

Introduction Clinical reasoning has been fostered with varying case formats including the use of virtual patients. Existing literature points to different conclusions regarding which format is most beneficial for learners with diverse levels of prior knowledge. We designed our study to better understand which case format affects clinical reasoning outcomes and cognitive load, dependent on medical students’ prior knowledge. Methods Overall, 142 medical students (3 rd to 6 th year) were randomly assigned to either a whole case or serial cue case format. Participants worked on eight virtual patients in their respective case format. Outcomes included diagnostic accuracy, knowledge, and cognitive load. Results We found no effect of case format on strategic knowledge scores pre- vs post-test (whole case learning gain = 3, 95% CI. -.01 to .01, serial cue learning gain = 3, 95% CI. -.06 to .00 p  = .50). In both case formats, students with high baseline knowledge (determined by median split on the pre-test in conceptual knowledge) benefitted from learning with virtual patients (learning gain in strategic knowledge = 5, 95% CI .03 to .09, p  = .01) while students with low prior knowledge did not (learning gain = 0, 95%CI −.02 to .02). We found no difference in diagnostic accuracy between experimental conditions (difference = .44, 95% CI −.96 to .08, p  = .22), but diagnostic accuracy was higher for students with high prior knowledge compared to those with low prior knowledge (difference = .8, 95% CI 0.31 to 1.35, p  < .01). Students with low prior knowledge experienced higher extraneous cognitive load than students with high prior knowledge (multiple measurements, p  < .01). Conclusions The whole case and serial cue case formats alone did not affect students’ knowledge gain or diagnostic accuracy. Students with lower knowledge experienced increased cognitive load and appear to have learned less from their interaction with virtual patients. Cognitive load should be taken into account when attempting to help students learn clinical reasoning with virtual patients, especially for students with lower knowledge.