Search results for 'Uncertainty' (try it on Scholar)

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  1. Tomasz Żuradzki (2016). Meta-Reasoning in Making Moral Decisions Under Normative Uncertainty. In Dima Mohammed & Marcin Lewiński (eds.), Argumentation and Reasoned Action. College Publications 1093-1104.
    I analyze recent discussions about making moral decisions under normative uncertainty. I discuss whether this kind of uncertainty should have practical consequences for decisions and whether there are reliable methods of reasoning that deal with the possibility that we are wrong about some moral issues. I defend a limited use of the decision theory model of reasoning in cases of normative uncertainty.
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  2. John Pittard & Alex Worsnip (forthcoming). Metanormative Contextualism and Normative Uncertainty. Mind:fzv208.
    We offer a new argument in favor of metanormative contextualism, the thesis that the semantic value of a normative ‘ought’ claim of the form ‘S ought to Φ’ depends on the value of one or more parameters whose values vary in a way that is determined by the context of utterance. The debate over this contextualist thesis has centered on cases that involve ‘ought’ claims made in the face of uncertainty regarding certain descriptive facts. Contextualists, relativists, and invariantists all (...)
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  3. Alessandro Giordani & Luca Mari (2014). Modeling Measurement: Error and Uncertainty. In Marcel Boumans, Giora Hon & Arthur Petersen (eds.), Error and Uncertainty in Scientific Practice. Pickering & Chatto 79-96.
    In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus alternative with (...)
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  4. J. Smith, W. Shields & D. Washburn (2003). The Comparative Psychology of Uncertainty Monitoring and Metacognition. Behavioral and Brain Sciences 26 (3):317-339.
    Researchers have begun to explore animals' capacities for uncertainty monitoring and metacognition. This exploration could extend the study of animal self-awareness and establish the relationship of self-awareness to other-awareness. It could sharpen descriptions of metacognition in the human literature and suggest the earliest roots of metacognition in human development. We summarize research on uncertainty monitoring by humans, monkeys, and a dolphin within perceptual and metamemory tasks. We extend phylogenetically the search for metacognitive capacities by considering studies that have (...)
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  5.  84
    Christian Barry & Patrick Tomlin (2016). Moral Uncertainty and Permissibility: Evaluating Option Sets. Canadian Journal of Philosophy 46 (6):1-26.
    In this essay, we explore an issue of moral uncertainty: what we are permitted to do when we are unsure about which moral principles are correct. We develop a novel approach to this issue that incorporates important insights from previous work on moral uncertainty, while avoiding some of the difficulties that beset existing alternative approaches. Our approach is based on evaluating and choosing between option sets rather than particular conduct options. We show how our approach is particularly well-suited (...)
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  6. Tomasz Żuradzki (2014). Moral Uncertainty in Bioethical Argumentation: A New Understanding of the Pro-Life View on Early Human Embryos. Theoretical Medicine and Bioethics 35 (6):441-457.
    In this article, I present a new interpretation of the pro-life view on the status of early human embryos. In my understanding, this position is based not on presumptions about the ontological status of embryos and their developmental capabilities but on the specific criteria of rational decisions under uncertainty and on a cautious response to the ambiguous status of embryos. This view, which uses the decision theory model of moral reasoning, promises to reconcile the uncertainty about the ontological (...)
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  7.  46
    Charles T. Sebens & Sean M. Carroll (forthcoming). Self-Locating Uncertainty and the Origin of Probability in Everettian Quantum Mechanics. British Journal for the Philosophy of Science:axw004.
    A longstanding issue in attempts to understand the Everett (Many-Worlds) approach to quantum mechanics is the origin of the Born rule: why is the probability given by the square of the amplitude? Following Vaidman, we note that observers are in a position of self-locating uncertainty during the period between the branches of the wave function splitting via decoherence and the observer registering the outcome of the measurement. In this period it is tempting to regard each branch as equiprobable, but (...)
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  8.  30
    Susan L. Joslyn & Jared E. LeClerc (2016). Climate Projections and Uncertainty Communication. Topics in Cognitive Science 8 (1):222-241.
    Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists’ estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested (...)
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  9.  70
    Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane (2010). Coherent Choice Functions Under Uncertainty. Synthese 172 (1):157 - 176.
    We discuss several features of coherent choice functions —where the admissible options in a decision problem are exactly those that maximize expected utility for some probability/utility pair in fixed set S of probability/utility pairs. In this paper we consider, primarily, normal form decision problems under uncertainty—where only the probability component of S is indeterminate and utility for two privileged outcomes is determinate. Coherent choice distinguishes between each pair of sets of probabilities regardless the “shape” or “connectedness” of the sets (...)
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  10.  28
    Mirta Galesic, Astrid Kause & Wolfgang Gaissmaier (2016). A Sampling Framework for Uncertainty in Individual Environmental Decisions. Topics in Cognitive Science 8 (1):242-258.
    Decisions in the environmental and in particular the climate domain are burdened with uncertainty. Here, we focus on uncertainties faced by individuals when making decisions about environmental behavior, and we use the statistical sampling framework to develop a classification of different sources of uncertainty they encounter. We then map these sources to different public policy strategies aiming to help individuals cope with uncertainty when making environmental decisions.
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  11. Paul Égré & Denis Bonnay (2010). Vagueness, Uncertainty and Degrees of Clarity. Synthese 174 (1):47 - 78.
    In this paper we compare different models of vagueness viewed as a specific form of subjective uncertainty in situations of imperfect discrimination. Our focus is on the logic of the operator “clearly” and on the problem of higher-order vagueness. We first examine the consequences of the notion of intransitivity of indiscriminability for higher-order vagueness, and compare several accounts of vagueness as inexact or imprecise knowledge, namely Williamson’s margin for error semantics, Halpern’s two-dimensional semantics, and the system we call Centered (...)
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  12. Maurice A. De Gosson (2009). The Symplectic Camel and the Uncertainty Principle: The Tip of an Iceberg? [REVIEW] Foundations of Physics 39 (2):194-214.
    We show that the strong form of Heisenberg’s inequalities due to Robertson and Schrödinger can be formally derived using only classical considerations. This is achieved using a statistical tool known as the “minimum volume ellipsoid” together with the notion of symplectic capacity, which we view as a topological measure of uncertainty invariant under Hamiltonian dynamics. This invariant provides a right measurement tool to define what “quantum scale” is. We take the opportunity to discuss the principle of the symplectic camel, (...)
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  13.  75
    Antonio Di Domenico, Andreas Gabriel, Beatrix C. Hiesmayr, Florian Hipp, Marcus Huber, Gerd Krizek, Karoline Mühlbacher, Sasa Radic, Christoph Spengler & Lukas Theussl (2012). Heisenberg's Uncertainty Relation and Bell Inequalities in High Energy Physics. Foundations of Physics 42 (6):778-802.
    An effective formalism is developed to handle decaying two-state systems. Herewith, observables of such systems can be described by a single operator in the Heisenberg picture. This allows for using the usual framework in quantum information theory and, hence, to enlighten the quantum features of such systems compared to non-decaying systems. We apply it to systems in high energy physics, i.e. to oscillating meson–antimeson systems. In particular, we discuss the entropic Heisenberg uncertainty relation for observables measured at different times (...)
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  14.  45
    Kevin A. Smith & Edward Vul (2013). Sources of Uncertainty in Intuitive Physics. Topics in Cognitive Science 5 (1):185-199.
    Recent work suggests that people predict how objects interact in a manner consistent with Newtonian physics, but with additional uncertainty. However, the sources of uncertainty have not been examined. In this study, we measure perceptual noise in initial conditions and stochasticity in the physical model used to make predictions. Participants predicted the trajectory of a moving object through occluded motion and bounces, and we compared their behavior to an ideal observer model. We found that human judgments cannot be (...)
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  15. Jean E. Burns (2012). The Action of Consciousness and the Uncertainty Principle. Journal of Nonlocality 1 (1).
    The term action of consciousness is used to refer to an influence, such as psychokinesis or free will, that produces an effect on matter that is correlated to mental intention, but not completely determined by physical conditions. Such an action could not conserve energy. But in that case, one wonders why, when highly accurate measurements are done, occasions of non-conserved energy (generated perhaps by unconscious PK) are not detected. A possible explanation is that actions of consciousness take place within the (...)
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  16. Ralph Wedgwood (2013). Akrasia and Uncertainty. Organon F: Medzinárodný Časopis Pre Analytickú Filozofiu 20 (4):483–505.
    According to John Broome, akrasia consists in a failure to intend to do something that one believes one ought to do, and such akrasia is necessarily irrational. In fact, however, failing to intend something that one believes one ought to do is only guaranteed to be irrational if one is certain of a maximally detailed proposition about what one ought to do; if one is uncertain about any part of the full story about what one ought to do, it could (...)
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  17.  29
    Arthur Petersen (2014). Uncertainty and God: A Jamesian Pragmatist Approach to Uncertainty and Ignorance in Science and Religion. Zygon 49 (4):808-828.
    This article picks up from William James's pragmatism and metaphysics of experience, as expressed in his “radical empiricism,” and further develops this Jamesian pragmatist approach to uncertainty and ignorance by connecting it to phenomenological thought. The Jamesian pragmatist approach avoids both a “crude naturalism” and an “absolutist rationalism,” and allows for identification of intimations of the sacred in both scientific and religious practices—which all, in their respective ways, try to make sense of a complex world. Analogous to religious practices, (...)
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  18. Roger M. Cooke (1991). Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press.
    This book is an extensive survey and critical examination of the literature on the use of expert opinion in scientific inquiry and policy making. The elicitation, representation, and use of expert opinion is increasingly important for two reasons: advancing technology leads to more and more complex decision problems, and technologists are turning in greater numbers to "expert systems" and other similar artifacts of artificial intelligence. Cooke here considers how expert opinion is being used today, how an expert's uncertainty is (...)
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  19.  30
    Louise Cummings (2002). Reasoning Under Uncertainty: The Role of Two Informal Fallacies in an Emerging Scientific Inquiry. Informal Logic 22 (2).
    lt is now commonplace in fallacy inquiry for many of the traditional informal fallacies to be viewed as reasonable or nonfallacious modes of argument. Central to this evaluative shift has been the attempt to examine traditional fallacies within their wider contexts of use. However, this pragmatic turn in fallacy evaluation is still in its infancy. The true potential of a contextual approach in the evaluation of the fallacies is yet to be explored. I examine how, in the context of scientific (...)
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  20. Tal Linzen & T. Florian Jaeger (2016). Uncertainty and Expectation in Sentence Processing: Evidence From Subcategorization Distributions. Cognitive Science 40 (6):1382-1411.
    There is now considerable evidence that human sentence processing is expectation based: As people read a sentence, they use their statistical experience with their language to generate predictions about upcoming syntactic structure. This study examines how sentence processing is affected by readers' uncertainty about those expectations. In a self-paced reading study, we use lexical subcategorization distributions to factorially manipulate both the strength of expectations and the uncertainty about them. We compare two types of uncertainty: uncertainty about (...)
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  21.  24
    Regula Valérie Burri (2007). Deliberating Risks Under Uncertainty: Experience, Trust, and Attitudes in a Swiss Nanotechnology Stakeholder Discussion Group. NanoEthics 1 (2):143-154.
    Scientific knowledge has not stabilized in the current, early, phase of research and development of nanotechnologies creating a challenge to ‘upstream’ public engagement. Nevertheless, the idea that the public should be involved in deliberative discussions and assessments of emerging technologies at this early stage is widely shared among governmental and nongovernmental stakeholders. Many forums for public debate including focus groups, and citizen juries, have thus been organized to explore public opinions on nanotechnologies in a variety of countries over the past (...)
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  22.  84
    Ron Aboodi, Adi Borer & and David Enoch (2008). Deontology, Individualism, and Uncertainty, a Reply to Jackson and Smith. Journal of Philosophy 105 (5):259-272.
    How should deontological theories that prohibit actions of type K — such as intentionally killing an innocent person — deal with cases of uncertainty as to whether a particular action is of type K? Frank Jackson and Michael Smith, who raise this problem in their paper "Absolutist Moral Theories and Uncertainty" (2006), focus on a case where a skier is about to cause the death of ten innocent people — we don’t know for sure whether on purpose or (...)
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  23.  48
    Sven Ove Hansson (2006). Uncertainty and the Ethics of Clinical Trials. Theoretical Medicine and Bioethics 27 (2):149-167.
    A probabilistic explication is offered of equipoise and uncertainty in clinical trials. In order to be useful in the justification of clinical trials, equipoise has to be interpreted in terms of overlapping probability distributions of possible treatment outcomes, rather than point estimates representing expectation values. Uncertainty about treatment outcomes is shown to be a necessary but insufficient condition for the ethical defensibility of clinical trials. Additional requirements are proposed for the nature of that uncertainty. The indecisiveness of (...)
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  24.  3
    Sabine Roeser (2014). The Unbearable Uncertainty Paradox. Metaphilosophy 45 (4-5):640-653.
    People can be risk seeking and risk averse, but people can also be uncertainty averse: in other words, if risk is at least the possibility of an unwanted affect, then it is not only the unwanted effect that they want to avoid, it can also be the uncertainty inherent in the possibility that they wish to avoid. This uncertainty aversion can even lead to a state where someone prefers a certain outcome at all costs, even when it (...)
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  25.  69
    John Quiggin (2001). Production Under Uncertainty and Choice Under Uncertainty in the Emergence of Generalized Expected Utility Theory. Theory and Decision 51 (2/4):125-144.
    This paper presents a personal view of the interaction between the analysis of choice under uncertainty and the analysis of production under uncertainty. Interest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. This interest led to the development of generalized models including rank-dependent expected utility theory. In turn, the development of generalized expected utility models raised the question (...)
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  26.  13
    Wendy A. Rogers & Mary J. Walker (2016). Fragility, Uncertainty, and Healthcare. Theoretical Medicine and Bioethics 37 (1):71-83.
    Medicine seeks to overcome one of the most fundamental fragilities of being human, the fragility of good health. No matter how robust our current state of health, we are inevitably susceptible to future illness and disease, while current disease serves to remind us of various frailties inherent in the human condition. This article examines the relationship between fragility and uncertainty with regard to health, and argues that there are reasons to accept rather than deny at least some forms of (...)
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  27.  46
    Tony Gardner-Medwin (2011). Reasonable Doubt : Uncertainty in Education, Science and Law. In Philip Dawid, William Twining & Mimi Vasilaki (eds.), Evidence, Inference and Enquiry. OUP/British Academy 465-483.
    The use of evidence to resolve uncertainties is key to many endeavours, most conspicuously science and law. Despite this, the logic of uncertainty is seldom taught explicitly, and often seems misunderstood. Traditional educational practice even fails to encourage students to identify uncertainty when they express knowledge, though mark schemes that reward the identification of reliable and uncertain responses have long been shown to encourage more insightful understanding. In our information-rich society the ability to identify uncertainty is often (...)
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  28.  52
    George Wu (1999). Anxiety and Decision Making with Delayed Resolution of Uncertainty. Theory and Decision 46 (2):159-199.
    In many real-world gambles, a non-trivial amount of time passes before the uncertainty is resolved but after a choice is made. An individual may have a preference between gambles with identical probability distributions over final outcomes if they differ in the timing of resolution of uncertainty. In this domain, utility consists not only of the consumption of outcomes, but also the psychological utility induced by an unresolved gamble. We term this utility anxiety. Since a reflective decision maker may (...)
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  29.  19
    Patrick Suppes (2016). Qualitative Axioms of Uncertainty as a Foundation for Probability and Decision-Making. Minds and Machines 26 (1-2):185-202.
    Although the concept of uncertainty is as old as Epicurus’s writings, and an excellent quantitative theory, with entropy as the measure of uncertainty having been developed in recent times, there has been little exploration of the qualitative theory. The purpose of the present paper is to give a qualitative axiomatization of uncertainty, in the spirit of the many studies of qualitative comparative probability. The qualitative axioms are fundamentally about the uncertainty of a partition of the probability (...)
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  30.  34
    Aldo Montesano (2008). Effects of Uncertainty Aversion on the Call Option Market. Theory and Decision 65 (2):97-123.
    This article examines the effects of uncertainty aversion in competitive call option markets using a partial equilibrium model with the Choquet-expected utility setup. We find that the trading volume of a call option is negatively affected by uncertainty aversion, whereas the price of the call is practically independent of it.
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  31.  57
    John Lemons, Kristin Shrader-Frechette & Carl Cranor (1997). The Precautionary Principle: Scientific Uncertainty and Type I and Type II Errors. [REVIEW] Foundations of Science 2 (2):207-236.
    We provide examples of the extent and nature of environmental and human health problems and show why in the United States prevailing scientific and legal burden of proof requirements usually cannot be met because of the pervasiveness of scientific uncertainty. We also provide examples of how may assumptions, judgments, evaluations, and inferences in scientific methods are value-laden and that when this is not recognized results of studies will appear to be more factual and value-neutral than warranted. Further, we show (...)
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  32.  23
    Haiyan Xu, Keith W. Hipel, D. Marc Kilgour & Ye Chen (2010). Combining Strength and Uncertainty for Preferences in the Graph Model for Conflict Resolution with Multiple Decision Makers. Theory and Decision 69 (4):497-521.
    A hybrid preference framework is proposed for strategic conflict analysis to integrate preference strength and preference uncertainty into the paradigm of the graph model for conflict resolution (GMCR) under multiple decision makers. This structure offers decision makers a more flexible mechanism for preference expression, which can include strong or mild preference of one state or scenario over another, as well as equal preference. In addition, preference between two states can be uncertain. The result is a preference framework that is (...)
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  33.  65
    Jorge Wagensberg (2000). Complexity Versus Uncertainty: The Question of Staying Alive. [REVIEW] Biology and Philosophy 15 (4):493-508.
    Some real objects show a very particular tendency: that of becomingindependent with regard to the uncertainty of their surroundings. This isachieved by the exchange of three quantities: matter, energy andinformation. A conceptual framework, based on both Non-equilibriumThermodynamic and the Mathematical Theory of Communication is proposedin order to review the concept of change in living individuals. Three mainsituations are discussed in this context: passive independence inconnection with resistant living forms (such as seeds, spores, hibernation,...), active independence in connection with the (...)
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  34.  12
    Gitte Meyer, Anna Paldam Folker, Rikke Bagger Jørgensen, Martin Krayer von Krauss, Peter Sandøe & Geir Tveit (2005). The Factualization of Uncertainty: Risk, Politics, and Genetically Modified Crops – a Case of Rape. [REVIEW] Agriculture and Human Values 22 (2):235-242.
    Mandatory risk assessment is intended to reassure concerned citizens and introduce reason into the heated European controversies on genetically modified crops and food. The authors, examining a case of risk assessment of genetically modified oilseed rape, claim that the new European legislation on risk assessment does nothing of the sort and is not likely to present an escape from the international deadlock on the use of genetic modification in agriculture and food production. The new legislation is likely to stimulate the (...)
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  35.  41
    Martin Ahlbrecht & Martin Weber (1997). Preference for Gradual Resolution of Uncertainty. Theory and Decision 43 (2):167-185.
    Analyses of preference for the timing of uncertainty resolution usually assumes all uncertainty to resolve in one point in time. More realistically, uncertainty should be modelled to resolve gradually over time. Kreps and Porteus (1978) have introduced an axiomatically based model of time preference which can explain preferences for gradual uncertainty resolution. This paper presents an experimental test of the Kreps-Porteus model. We derive implications of the model relating preferences for gradual and one-time resolving lotteries. Our (...)
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  36.  21
    Carlotta Piscopo & Mauro Birattari (2008). The Metaphysical Character of the Criticisms Raised Against the Use of Probability for Dealing with Uncertainty in Artificial Intelligence. Minds and Machines 18 (2):273-288.
    In artificial intelligence (AI), a number of criticisms were raised against the use of probability for dealing with uncertainty. All these criticisms, except what in this article we call the non-adequacy claim, have been eventually confuted. The non-adequacy claim is an exception because, unlike the other criticisms, it is exquisitely philosophical and, possibly for this reason, it was not discussed in the technical literature. A lack of clarity and understanding of this claim had a major impact on AI. Indeed, (...)
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  37.  5
    Karim Bschir (forthcoming). Risk, Uncertainty and Precaution in Science: The Threshold of the Toxicological Concern Approach in Food Toxicology. Science and Engineering Ethics:1-20.
    Environmental risk assessment is often affected by severe uncertainty. The frequently invoked precautionary principle helps to guide risk assessment and decision-making in the face of scientific uncertainty. In many contexts, however, uncertainties play a role not only in the application of scientific models but also in their development. Building on recent literature in the philosophy of science, this paper argues that precaution should be exercised at the stage when tools for risk assessment are developed as well as when (...)
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  38.  35
    Anne Ingeborg Myhr & Terje Traavik (2002). The Precautionary Principle: Scientific Uncertainty and Omitted Research in the Context of GMO Use and Release. [REVIEW] Journal of Agricultural and Environmental Ethics 15 (1):73-86.
    Commercialization of genetically modified organisms (GMOs) have sparked profound controversies concerning adequate approaches to risk regulation. Scientific uncertainty and ambiguity, omitted research areas, and lack of basic knowledge crucial to risk assessmentshave become apparent. The objective of this article is to discuss the policy and practical implementation of the Precautionary Principle. A major conclusion is that the void in scientific understanding concerning risks posed by secondary effects and the complexity ofcause-effect relations warrant further research. Initiatives to approach the acceptance (...)
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  39.  45
    Boudewijn de Bruin (2008). Common Knowledge of Payoff Uncertainty in Games. Synthese 163 (1):79-97.
    Using epistemic logic, we provide a non-probabilistic way to formalise payoff uncertainty, that is, statements such as ‘player i has approximate knowledge about the utility functions of player j.’ We show that on the basis of this formalisation common knowledge of payoff uncertainty and rationality (in the sense of excluding weakly dominated strategies, due to Dekel and Fudenberg (1990)) characterises a new solution concept we have called ‘mixed iterated strict weak dominance.’.
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  40.  37
    Steven J. Brams & D. Marc Kilgour (1998). Backward Induction Is Not Robust: The Parity Problem and the Uncertainty Problem. [REVIEW] Theory and Decision 45 (3):263-289.
    A cornerstone of game theory is backward induction, whereby players reason backward from the end of a game in extensive form to the beginning in order to determine what choices are rational at each stage of play. Truels, or three-person duels, are used to illustrate how the outcome can depend on (1) the evenness/oddness of the number of rounds (the parity problem) and (2) uncertainty about the endpoint of the game (the uncertainty problem). Since there is no known (...)
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  41.  3
    Wendy S. Parker & James S. Risbey (2015). False Precision, Surprise and Improved Uncertainty Assessment. Philosophical Transactions of the Royal Society A 373 (2055):20140453.
    An uncertainty report describes the extent of an agent’s uncertainty about some matter. We identify two basic requirements for uncertainty reports, which we call faithfulness and completeness. We then discuss two pitfalls of uncertainty assessment that often result in reports that fail to meet these requirements. The first involves adopting a one-size-fits-all approach to the representation of uncertainty, while the second involves failing to take account of the risk of surprises. In connection with the latter, (...)
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  42.  8
    Louise Cummings (2009). Emerging Infectious Diseases: Coping with Uncertainty. [REVIEW] Argumentation 23 (2):171-188.
    The world’s scientific community must be in a state of constant readiness to address the threat posed by newly emerging infectious diseases. Whether the disease in question is SARS in humans or BSE in animals, scientists must be able to put into action various disease containment measures when everything from the causative pathogen to route(s) of transmission is essentially uncertain. A robust epistemic framework, which will inform decision-making, is required under such conditions of uncertainty. I will argue that this (...)
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  43.  30
    F. Ben Abdelaziz, P. Lang & R. Nadeau (1999). Dominance and Efficiency in Multicriteria Decision Under Uncertainty. Theory and Decision 47 (3):191-211.
    This paper proposes several concepts of efficient solutions for multicriteria decision problems under uncertainty. We show how alternative notions of efficiency may be grounded on different decision ‘contexts’, depending on what is known about the Decision Maker's (DM) preference structure and probabilistic anticipations. We define efficient sets arising naturally from polar decision contexts. We investigate these sets from the points of view of their relative inclusions and point out some particular subsets which may be especially relevant to some decision (...)
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  44.  53
    Alessandro Giordani & Luca Mari (2012). Measurement, Models, and Uncertainty. IEEE Transactions on Instrumentation and Measurement 61 (8):2144 - 2152.
    Against the tradition, which has considered measurement able to produce pure data on physical systems, the unavoidable role played by the modeling activity in measurement is increasingly acknowledged, particularly with respect to the evaluation of measurement uncertainty. This paper characterizes measurement as a knowledge-based process and proposes a framework to understand the function of models in measurement and to systematically analyze their influence in the production of measurement results and their interpretation. To this aim, a general model of measurement (...)
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  45.  8
    Anna Paldam Folker & Peter Sandøe (2008). Leaping “Out of the Doubt”—Nutrition Advice: Values at Stake in Communicating Scientific Uncertainty to the Public. Health Care Analysis 16 (2):176-191.
    This article deals with scientific advice to the public where the relevant science is subject to public attention and uncertainty of knowledge. It focuses on a tension in the management and presentation of scientific uncertainty between the uncertain nature of science and the expectation that scientific advisers will provide clear public guidance. In the first part of the paper the tension is illustrated by the presentation of results from a recent interview study with nutrition scientists in Denmark. According (...)
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  46.  6
    H. Fakhri & M. Sayyah-Fard (2016). An Uncertainty Relation for the Orbital Angular Momentum Operator. Foundations of Physics 46 (8):1062-1073.
    A common reducible representation space of the Lie algebras su and su is equipped with two different types of scalar products. The representation bases are labeled by the azimuthal and magnetic quantum numbers. The generators of su are the x-, y- and z-components of the orbital angular momentum operator. The representation of each of these Lie algebras is unitary with respect to only one of the scalar products. To each positive magnetic quantum number a family of the su-Barut–Girardello coherent states (...)
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  47.  12
    Franz Baader, Hans-Jürgen Bürckert, Bernhard Nebel, Werner Nutt & Gert Smolka (1993). On the Expressivity of Feature Logics with Negation, Functional Uncertainty, and Sort Equations. Journal of Logic, Language and Information 2 (1):1-18.
    Feature logics are the logical basis for so-called unification grammars studied in computational linguistics. We investigate the expressivity of feature terms with negation and the functional uncertainty construct needed for the description of long-distance dependencies and obtain the following results: satisfiability of feature terms is undecidable, sort equations can be internalized, consistency of sort equations is decidable if there is at least one atom, and consistency of sort equations is undecidable if there is no atom.
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  48.  41
    William L. Ascher (2004). Scientific Information and Uncertainty: Challenges for the Use of Science in Policymaking. Science and Engineering Ethics 10 (3):437-455.
    Science can reinforce the healthy aspects of the politics of the policy process, to identify and further the public interest by discrediting policy options serving only special interests and helping to select among “science-confident” and “hedging” options. To do so, scientists must learn how to manage and communicate the degree of uncertainty in scientific understanding and prediction, lest uncertainty be manipulated to discredit science or to justify inaction. For natural resource and environmental policy, the institutional interests of government (...)
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  49.  5
    Jeff Davis & Daniel Werre (2008). A Longitudinal Study of the Effects of Uncertainty on Reproductive Behaviors. Human Nature 19 (4):426-452.
    Uncertainty exerts powerful influences on life history decisions. This has been demonstrated in experiments on nonhumans and in mathematical models. Studies of human populations are suggestive of the effects of uncertainty, but they rely on measures of environmental stress. In this paper, we derive a new measure of uncertainty, upsilon (υ), for use in non-experimental studies. We estimate its association with reproductive behaviors in a longitudinal panel sample of adolescents in the United States. Results show upsilon’s internal (...)
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  50.  45
    Lisa Warenski (2012). Relative Uncertainty in Term Loan Projection Models: What Lenders Could Tell Risk Managers. Journal of Experimental and Artificial Intelligence 24 (4):501-511.
    This article examines the epistemology of risk assessment in the context of financial modelling for the purposes of making loan underwriting decisions. A financing request for a company in the paper and pulp industry is considered in some detail. The paper and pulp industry was chosen because it is subject to some specific risks that have been identified and studied by bankers, investors and managers of paper and pulp companies and certain features of the industry enable analysts to quantify the (...)
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