Learning Under Ambiguity
Author | : Larry G. Epstein |
Publisher | : |
Total Pages | : 0 |
Release | : 2002 |
Genre | : Business enterprises |
ISBN | : |
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Author | : Larry G. Epstein |
Publisher | : |
Total Pages | : 0 |
Release | : 2002 |
Genre | : Business enterprises |
ISBN | : |
Author | : Johannes Bauer |
Publisher | : Springer Science & Business Media |
Total Pages | : 280 |
Release | : 2012-03-17 |
Genre | : Education |
ISBN | : 9048139414 |
A curious ambiguity surrounds errors in professional working contexts: they must be avoided in case they lead to adverse (and potentially disastrous) results, yet they also hold the key to improving our knowledge and procedures. In a further irony, it seems that a prerequisite for circumventing errors is our remaining open to their potential occurrence and learning from them when they do happen. This volume, the first to integrate interdisciplinary perspectives on learning from errors at work, presents theoretical concepts and empirical evidence in an attempt to establish under what conditions professionals deal with errors at work productively—in other words, learn the lessons they contain. By drawing upon and combining cognitive and action-oriented approaches to human error with theories of adult, professional, and workplace learning this book provides valuable insights which can be applied by workers and professionals. It includes systematic theoretical frameworks for explaining learning from errors in daily working life, methodologies and research instruments that facilitate the measurement of that learning, and empirical studies that investigate relevant determinants of learning from errors in different professions. Written by an international group of distinguished researchers from various disciplines, the chapters paint a comprehensive picture of the current state of the art in research on human fallibility and (learning from) errors at work.
Author | : Jose M. Fernandez |
Publisher | : |
Total Pages | : 0 |
Release | : 2013 |
Genre | : |
ISBN | : |
In this paper, I present an empirical model of learning under ambiguity in the context of clinical trials. Patients are concern with learning the treatment effect of the experimental drug, but face the ambiguity of random group assignment. A two dimensional Bayesian model of learning is proposed to capture patients' beliefs on the treatment effect and group assignment. These beliefs are then used to predict patient attrition in clinical trials. Patient learning is demonstrated to be slower when taking into account group ambiguity. In addition, the model corrects for attrition bias in the estimated treatment effect.
Author | : Gideon Keren |
Publisher | : John Wiley & Sons |
Total Pages | : 1056 |
Release | : 2016-02-16 |
Genre | : Psychology |
ISBN | : 1118468392 |
A comprehensive, up-to-date examination of the most important theory, concepts, methodological approaches, and applications in the burgeoning field of judgment and decision making (JDM) Emphasizes the growth of JDM applications with chapters devoted to medical decision making, decision making and the law, consumer behavior, and more Addresses controversial topics from multiple perspectives – such as choice from description versus choice from experience – and contrasts between empirical methodologies employed in behavioral economics and psychology Brings together a multi-disciplinary group of contributors from across the social sciences, including psychology, economics, marketing, finance, public policy, sociology, and philosophy 2 Volumes
Author | : Michael Kenney |
Publisher | : Routledge |
Total Pages | : 278 |
Release | : 2017-03-02 |
Genre | : Political Science |
ISBN | : 1351913360 |
Organizational learning is an area of study that focuses on models and theories about the way an organization learns and adapts. This volume investigates how various global and regional intergovernmental organizations, states and national bureaucracies, as well as nongovernmental organizations, exploit experience and knowledge to change their understanding of the world, their policies and their behaviours. Drawing upon and synthesizing organizational, social and individual-level learning theories, the cases explicate various learning processes, learning by illicit actors, and deterrents to organizational learning. The twelve case studies of this volume consider organizational learning associated with multiple issue areas including the United States embargo against Cuba, food security in the European Union, the Russian energy sector, Colombian drug trafficking, terrorist groups, the Catholic Church, and foreign aid agencies. Based entirely on original research, the volume is relevant to international relations, comparative politics, organizational sociology and policy studies.
Author | : Glenn Shafer |
Publisher | : Princeton University Press |
Total Pages | : |
Release | : 2020-06-30 |
Genre | : Mathematics |
ISBN | : 0691214697 |
Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combination, this book constructs a new theory of epistemic probability. The theory draws on the work of A. P. Dempster but diverges from Depster's viewpoint by identifying his "lower probabilities" as epistemic probabilities and taking his rule for combining "upper and lower probabilities" as fundamental. The book opens with a critique of the well-known Bayesian theory of epistemic probability. It then proceeds to develop an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions. This rule, together with the idea of "weights of evidence," leads to both an extensive new theory and a better understanding of the Bayesian theory. The book concludes with a brief treatment of statistical inference and a discussion of the limitations of epistemic probability. Appendices contain mathematical proofs, which are relatively elementary and seldom depend on mathematics more advanced that the binomial theorem.