I argue that the issues of foodquality, in the most general sense includingpurity, safety, and ethics, can no longer beresolved through ``normal'' science andregulation. The reliance on reductionistscience as the basis for policy andimplementation has shown itself to beinadequate. I use several borderline examplesbetween drugs and foods, particularly coffeeand sucrose, to show that ``quality'' is now acomplex attribute. For in those cases thesubstance is either a pure drug, or a bad foodwith drug-like properties; both are marketed asif they were foods. (...) An example of theinadequacy of old ways of thinking is obesity,whose causes are as yet outside the purview ofmedicine, while its effects constitute anepidemic disease. The new drug/food syndromeneeds a new sort of science, what we call``post-normal.'' This is inquiry at the contestedinterfaces of science and policy; typically itdeals with issues where facts are uncertain,values in dispute, stakes high, and decisionsurgent. With the perspective of post-normalscience, we can better understand some keyissues. We see that ``safety'' is different from``risk,'' being pragmatic, moral, and recursive.Also, we understand that an appropriatefoundation for regulation and ethics is not somuch ``objectivity'' as ``awareness.'' In an agewhen ``consumers'' are becoming concerned``citizens,'' the relevant science must becomepost-normal. (shrink)

In spite of being a very public intellectual, the philosopher Imre Lakatos (who died in 1974) was little understood. His Hungarian background seemed irrelevant to his career at the London School of Economics as the colleague and then successor to Sir Karl Popper. In Imre Lakatos and The Guises of Reason, John Kadvany demonstrates the overwhelming importance of Lakatos's Hungarian background, and thereby also explains and illuminates Lakatos's philosophy. His study also demonstrates the power of Hegel's thought as the background (...) to any genuinely historical approach to philosophy, even of science and mathematics. He also provides a glimpse of the nightmare world of Stalinist Hungary, as a contribution to an explanation of Lakatos's personal and intellectual style. Kadvany's exposition does much to clarify and explain Lakatos's philosophy, thereby enhancing his reputation and also making his work, much of it still of vital significance, more accessible to a new public. (shrink)

Beyond being the first substantial publication on Fourier, this work contains the text of Fourier's seminal paper of 1807 on the propagation of heat, marking the first time it has ever appeared in print. This paper incorporates many of the mathematical creations on which Fourier's fame rests, including derivation of the diffusion equation, the separation of the treatment of surface phenomena from internal phenomena, the use of boundary values and initial conditions, and the development of "Fourier series" and the so-called (...) "Bessel functions."When submitted to the examiners of the Institut de France, the originality of the paper and the surprising nature of some of its mathematical revelations caused great controversy, and it was denied publication both in 1807 and in later years. Fourier had the support, among the examiners, of Laplace and Monge, but Lagrange was adamantly in opposition, so that Fourier's work did not appear in print until 1822, reworked into book form.Fourier's mathematical discoveries are intimately related to his interest in the solution of physical problems and their experimental verification. The mathematical methods he developed in connection with heat diffusion apply to physical situations far beyond the boundaries of this area. Generally, Fourier may be credited with one of the first major extensions of mathematical physics beyond the applications of Newton's laws of motion and universal gravitation.The opening biographical chapter of this book follows Fourier's career up to the submission of the 1807 paper, and the two closing chapters take up his life and work from that point on. Fourier had strong political motivations and spent much of his life in the public service. These chapters trace his political difficulties, both before and after 1807, when he was the prefect of a department of France and was subjected to the dislocations of Napoleon's ups and downs. These chapters also describe aspects of the turbulent but productive development of French science from the Revolution to 1830.The core of the book presents the paper of 1807 in its original French and with the original notation. Grattan-Guinness has divided the paper into sections by the sequence of the problems taken up, and he introduces and, where necessary, closes each section with commentary relevant to Fourier's later work in these areas. The paper itself (cllows the chronology of Fourier's discoveries, and among the topics treated are, in this order: heat diffusion between disjoint bodies and in continuous bodies; the appearance of partial differential equations; the special solution for the lamina; sine and cosine series for an arbitrary function; reflections on the vibrating string problem; solution for the annulus; the full Fourier series for an arbitrary function; reflections on n-body analysis; solution for the sphere; solution for the cylinder; steady-state diffusion in the rectangular prism; time-dependent diffusion in the cube; and Fourier's experimental work. (shrink)

A crisis looms over the scientific enterprise. Not a day passes without news of retractions, failed replications, fraudulent peer reviews, or misinformed science-based policies. The social implications are enormous, yet this crisis has remained largely uncharted-until now. In Science on the Verge, luminaries in the field of post-normal science and scientific governance focus attention on worrying fault-lines in the use of science for policymaking, and the dramatic crisis within science itself. This provocative new volume in The Rightful Place of Science (...) also explores the concepts that need to be unlearned, and the skills that must be relearned and enhanced, if we are to restore the legitimacy and integrity of science. (shrink)

Les décisions politiques sur les risques environnementaux complexes font fréquemment intervenir des éléments scientifiques contestés. Il n’y a généralement pas de « faits » qui conduisent à une politique correcte unique. Les éléments de preuve qui sont intégrés dans les avis scientifiques destinés à une décision politique nécessitent une évaluation de leur qualité. En 2003, l’Agence néerlandaise d’évaluation environnementale a adopté une méthode standardisée, désignée sous le nom de « guide », dans le cadre de laquelle les principaux aspects de (...) la production et de l’utilisation des connaissances sont présentés grâce à une liste de contrôle visant à l’évaluation et à la communication des incertitudes. Dans cet article, nous présentons des résultats de l’application de ce guide à la controverse sur les risques des particules en suspension. La délibération active sur l’incertitude dans un contexte d’expertise entraîne un processus d’apprentissage commun entre les experts et les décideurs politiques, ce qui conduit à une meilleure prise de conscience du phénomène d’incertitude et de ses implications politiques.Policy decisions on complex environmental risks often involve disputed science. Typically, there are no “ facts” to support a single unequivocally correct policy. The evidence provided in scientific studies for policy-making decisions requires high-quality assessment. In 2003, the Netherlands Environmental Assessment Agency adopted a standardized method, referred to as “guidelines”, whereby key quality aspects of knowledge production and use are presented in the form of a checklist for uncertainty assessments and communication. In this article, we present the outcomes of applying the guidelines in controversies on the risks of ambient particulate matter. In the policy–advisory context, active deliberation on uncertainty produces a common learning process for advisors and policy makers, which leads to a deeper understanding and increased awareness of the phenomenon of uncertainty and its policy implications. (shrink)

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum (...) entanglement', allows cognitive phenomena to be modeled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light. Introducing the basic principles in an easy-to-follow way, this book does not assume a physics background or a quantum brain and comes complete with a tutorial and fully worked-out applications in important areas of cognition and decision. (shrink)

Understanding cognitive processes with a formal framework necessitates some limited, internal prescriptive normativism. This is because it is not possible to endorse the psychological relevance of some axioms in a formal framework, but reject that of others. The empirical challenge then becomes identifying the remit of different formal frameworks, an objective consistent with the descriptivism Elqayam & Evans (E&E) advocate.

Our study provides a review of argument-based scientific literature to address conscientious objections to end-of-life procedures. We also proposed a taxonomy based on this study that might facilitate clarification of this discussion at a basic level. The three clusters of our taxonomy include (1) nonconventional compatibilists that claim that conscientious objection against morally repugnant social conventions is compatible with professional obligation, (2) conventional compatibilists that suggest that conscientious objection against social convention is permissible under certain terms of compromise, and (3) (...) conventional incompatibilists that aver that conscientious objection is incompatible with the privileges and obligations of a health care provider. We conclude with three moments of reflective pause. The first pause reflects on the question of the health of a society's pluralism. The second pause results in suggested practice guidelines for conscientious objection to facilitate cooperation. The final pause reveals the need for further research to uncover a global perspective. (shrink)

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the (...) fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality. (shrink)

Quantum cognition is an emerging field that uses mathematical principles of quantum theory to help formalize and understand cognitive systems and processes. The topic on the potential of using quantum theory to build models of cognition (Volume 5, issue 4) introduces and synthesizes its new development through an introduction and six core articles. The current issue presents 14 commentaries on the core articles. Five key issues surface, some of which are interestingly controversial and debatable as expected for a new emerging (...) field. (shrink)

Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability (...) theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. (shrink)

Question order effects are commonly observed in self-report measures of judgment and attitude. This article develops a quantum question order model (the QQ model) to account for four types of question order effects observed in literature. First, the postulates of the QQ model are presented. Second, an a priori, parameter-free, and precise prediction, called the QQ equality, is derived from these mathematical principles, and six empirical data sets are used to test the prediction. Third, a new index is derived from (...) the model to measure similarity between questions. Fourth, we show that in contrast to the QQ model, Bayesian and Markov models do not generally satisfy the QQ equality and thus cannot account for the reported empirical data that support this equality. Finally, we describe the conditions under which order effects are predicted to occur, and we review a broader range of findings that are encompassed by these very same quantum principles. We conclude that quantum probability theory, initially invented to explain order effects on measurements in physics, appears to be a powerful natural explanation for order effects of self-report measures in social and behavioral sciences, too. (shrink)

It is a hallmark of a good model to make accurate a priori predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to evaluate the (...) models at the individual level of analysis. The first method used a post hoc fit criterion, the second method used a generalization criterion for short‐term predictions, and the third method again used a generalization criterion for long‐term predictions. The results suggest that the models with the prospect utility function can make generalizable predictions to new conditions, and different learning models are needed for making short‐versus long‐term predictions on simple gambling tasks. (shrink)

Order of information plays a crucial role in the process of updating beliefs across time. In fact, the presence of order effects makes a classical or Bayesian approach to inference difficult. As a result, the existing models of inference, such as the belief-adjustment model, merely provide an ad hoc explanation for these effects. We postulate a quantum inference model for order effects based on the axiomatic principles of quantum probability theory. The quantum inference model explains order effects by transforming a (...) state vector with different sequences of operators for different orderings of information. We demonstrate this process by fitting the quantum model to data collected in a medical diagnostic task and a jury decision-making task. To further test the quantum inference model, a new jury decision-making experiment is developed. Using the results of this experiment, we compare the quantum inference model with two versions of the belief-adjustment model, the adding model and the averaging model. We show that both the quantum model and the adding model provide good fits to the data. To distinguish the quantum model from the adding model, we develop a new experiment involving extreme evidence. The results from this new experiment suggest that the adding model faces limitations when accounting for tasks involving extreme evidence, whereas the quantum inference model does not. Ultimately, we argue that the quantum model provides a more coherent account for order effects that was not possible before. (shrink)

Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were shown six faces varying in width, first asked to categorize the faces, and then decide a course of action for each face. Each experiment was designed to include three groups, and for each (...) group, we manipulated the probabilistic contingencies between stimulus, category assignments, and decision consequences. For each group, each participant received three different sequences of category response, category feedback, decision response, and decision feedback. We found that participants were only partially responsive in the appropriate directions to the contingencies assigned to each group. Comparisons of results from different sequences provided evidence for empirical interference effects of categorization on decisions. The empirical interference effect is defined as the difference between the probability of taking a hostile action in decision-alone conditions and the total probability of taking a hostile action in categorization-decision conditions. To test competing accounts for multiple empirical results, including two-stage choice probabilities and empirical interference effects, we compared a quantum cognition model versus a two-stage exemplar categorization model at both aggregate and individual levels. Using a Bayesian information criterion, we found that the quantum model provided an overall better model fit than the exemplar model. Although both models predicted empirical interference effects, the exemplar model was able to generate probabilistic deviation by incorporating category information of the first stage into the feature representation of the subsequent decision stage, while the quantum model produced interference effect by superposition, measurement, and quantum entanglement. (shrink)

The attempt to employ quantum principles for modeling cognition has enabled the introduction of several new concepts in psychology, such as the uncertainty principle, incompatibility, entanglement, and superposition. For many commentators, this is an exciting opportunity to question existing formal frameworks (notably classical probability theory) and explore what is to be gained by employing these novel conceptual tools. This is not to say that major empirical challenges are not there. For example, can we definitely prove the necessity for quantum, as (...) opposed to classical, models? Can the distinction between compatibility and incompatibility inform our understanding of differences between human and nonhuman cognition? Are quantum models less constrained than classical ones? Does incompatibility arise as a limitation, to avoid the requirements from the principle of unicity, or is it an inherent (or essential?) characteristic of intelligent thought? For everyday judgments, do quantum principles allow more accurate prediction than classical ones? Some questions can be confidently addressed within existing quantum models. A definitive resolution of others will have to anticipate further work. What is clear is that the consideration of quantum cognitive models has enabled a new focus on a range of debates about fundamental aspects of cognition. (shrink)

The study of decision making has traditionally been dominated by axiomatic utility theories. More recently, an alternative approach, which focuses on the micro-mechanisms of the underlying deliberation process, has been shown to account for several "paradoxes" in human choice behavior for which simple utility-based approaches cannot. Decision field theory (DFT) is a cognitive-dynamical model of decision making and preferential choice, built on the fundamental principle that decisions are based on the accumulation of subjective evaluations of choice alternatives until a threshold (...) criterion is met. This article extends the basic DFT framework to the domain of dynamic decision making. DFT-Dynamic is proposed as a new alternative to normative backward induction. Through its attention to the processes underlying planning and deliberation DFT-D provides simple, emergent explanations for violations of choice principles traditionally taken as evidence of irrationality. A recent multistage decision making study is used to showcase the model's efficacy for developing cognitive models of individual strategies. (shrink)