While every health care system stakeholder would seem to be concerned with obtaining the greatest value from a given technology, there is often a disconnect in the perception of value between a technology’s promoters and those responsible for the ultimate decision as to whether or not to pay for it. Adopting an empirical ethics approach, this paper examines how five Canadian medical device manufacturers, via their websites, frame the corporate “value proposition” of their innovation and seek to respond to what (...) they consider the key expectations of their customers. Our analysis shows that the manufacturers’ framing strategies combine claims that relate to valuable socio-technical goals and features such as prevention, efficiency, sense of security, real-time feedback, ease of use and flexibility, all elements that likely resonate with a large spectrum of health care system stakeholders. The websites do not describe, however, how the innovations may impact health care delivery and tend to obfuscate the decisional trade-offs these innovations represent from a health care system perspective. Such framing strategies, we argue, tend to bolster physicians’ and patients’ expectations and provide a large set of stakeholders with powerful rhetorical tools that may influence the health policy arena. Because these strategies are difficult to counter given the paucity of evidence and its limited use in policymaking, establishing sound collective health care priorities will require solid critiques of how certain kinds of medical devices may provide a better (i.e., more valuable) response to health care needs when compared to others. (shrink)

Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

Mayo (1987) sought to discredit Urbach's (1985) arguments against randomization as a universal requirement in clinical and agricultural trials. The present reply rebuts Mayo's criticisms.

In clinical and agricultural trials, there is the danger that an experimental outcome appears to arise from the causal process or treatment one is interested in when, in reality, it was produced by some extraneous variation in the experimental conditions. The remedy prescribed by classical statisticians involves the procedure of randomization, whose effectiveness and appropriateness is criticized. An alternative, Bayesian analysis of experimental design, is shown, on the other hand, to provide a coherent and intuitively satisfactory solution to the problem.

Bacon's scientific method is commonly thought to proceed mechanically to its infallible end. In this book however, Urbach presents Bacon's philosophy in an alternative light which acquits him of several errors. Urbach describes Bacon as an experimental scientist and examines the criticisms made against him, one of which was that he did not understand the roles of mathematics and science. Bacon was not a traditional metaphysician and was alarmed at the lack of progress in science since ancient times, (...) especially the lack of practical results. He attempted to open up a middle path between practical experience and unsupported theorizing. The author intends to clarify rather than defend Bacon's work. (shrink)

The Drosophila embryo provides a useful model system to study the mechanisms that lead to pattern and cell diversity in the central nervous system (CNS). The Drosophila CNS, which encompasses the brain and the ventral nerve cord, develops from a bilaterally symmetrical neuroectoderm, which gives rise to neural stem cells, called neuroblasts. The structure of the embryonic ventral nerve cord is relatively simple, consisting of a sequence of repeated segmental units (neuromeres), and the mechanisms controlling the formation and specification of (...) the neuroblasts that form these neuromeres are quite well understood. Owing to the much higher complexity and hidden segmental organization of the brain, our understanding of its development is still rudimentary. Recent investigations on the expression and function of proneural genes, segmentation genes, dorsoventral‐patterning genes and a number of other genes have provided new insight into the principles of neuroblast formation and patterning during embryonic development of the fly brain. Comparisons with the same processes in the trunk help us to understand what makes the brain different from the ventral nerve cord. Several parallels in early brain patterning between the fly and the vertebrate systems have become evident. BioEssays 26:739–751, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

Contents Preface General Introduction 1 | Science and Pseudoscience Introduction Karl Popper, Science: Conjectures and Refutations Thomas S. Kuhn, Logic of Discovery or Psychology of Research? Imre Lakatos, Science and Pseudoscience Paul R. Thagard, Why Astrology Is a Pseudoscience Michael Ruse, Creation-Science Is Not Science Larry Laudan, Commentary: Science at the Bar---Causes for Concern Commentary 2 | Rationality, Objectivity, and Values in Science Introduction Thomas S. Kuhn, The Nature and Necessity of Scientific Revolutions Thomas S. Kuhn, Objectivity, Value Judgment, and (...) Theory Choice Ernan McMullin, Rationality and Paradigm Change in Science Larry Laudan, Kuhn’s Critique of Methodology Helen E. Longino, Values and Objectivity Kathleen Okruhlik, Gender and the Biological Sciences Commentary 3 | The Duhem-Quine Thesis and Underdetermination Introduction Pierre Duhem, Physical Theory and Experiment W. V. Quine, Two Dogmas of Empiricism Donald Gillies, The Duhem Thesis and the Quine Thesis Larry Laudan, Demystifying Underdetermination *Colin Howson and Peter Urbach, The Duhem Problem Commentary 4 | Induction, Prediction, and Evidence Introduction Peter Lipton, Induction Karl Popper, The Problem of Induction Wesley C. Salmon, Rational Prediction Carl G. Hempel, Criteria of Confirmation and Acceptability Peter Achinstein, Explanation v. Prediction: Which Carries More Weight? *Nelson Goodman, The New Riddle of Induction Commentary 5 | Confirmation and Relevance: Bayesian Approaches Introduction Wesley C. Salmon, Rationality and Objectivity in Science *Deborah G. Mayo, A Critique of Salmon’s Bayesian Way *Alan Chalmers, The Bayesian Approach Paul Horwich, Therapeutic Bayesianism Commentary 6 | Models of Explanation Introduction Rudolf Carnap, The Value of Laws: Explanation and Prediction Carl G. Hempel, Two Basic Types of Scientific Explanation Carl G. Hempel, The Thesis of Structural Identity Carl G. Hempel, Inductive-Statistical Explanation Peter Railton, A Deductive-Nomological Model of Probabilistic Explanation *Philip Kitcher, Explanatory Unification *James Woodward, The Manipulability Conception of Causal Explanation Commentary 7 | Laws of Nature Introduction A. J. Ayer, What Is a Law of Nature? Fred I. Dretske, Laws of Nature D. H. Mellor, Necessities and Universals in Natural Laws Nancy Cartwright, Do the Laws of Physics State the Facts? Commentary 8 | Intertheoretic Reduction Introduction Ernest Nagel, Issues in the Logic of Reductive Explanations Paul K. Feyerabend, How to Be a Good Empiricist *Jerry A. Fodor, Special Sciences Philip Kitcher, 1953 and All That: A Tale of Two Sciences Commentary 9 | Empiricism and Scientific Realism Introduction Grover Maxwell, The Ontological Status of Theoretical Entities Bas C. van Fraassen, Arguments Concerning Scientific Realism Alan Musgrave, Realism versus Constructive Empiricism Larry Laudan, A Confutation of Convergent Realism *Juha T. Saatsi, On the Pessimistic Induction and Two Fallacies Ian Hacking, Experimentation and Scientific Realism David B. Resnik, Hacking’s Experimental Realism *Martin Carrier, What Is Right with the Miracle Argument Arthur Fine, The Natural Ontological Attitude Alan Musgrave, NOA’s Ark---Fine for Realism Commentary Glossary Bibliography Name Index Subject Index. (shrink)

Urbach (1985) has concluded that the use of randomization in the design of clinical and agricultural trials is both inappropriate and ineffective. It is argued here that it is appropriate, as it eliminates the dependence of inference on the unknown precise physical model that underlies a set of observations, and effective, in that it is relatively simple to apply in practice compared with any competing method. Furthermore, it has been proven in practice.

Peter Urbach; X*—Random Sampling and the Principles of Estimation, Proceedings of the Aristotelian Society, Volume 89, Issue 1, 1 June 1989, Pages 143–164, http.

Peter Urbach; X*—Random Sampling and the Principles of Estimation, Proceedings of the Aristotelian Society, Volume 89, Issue 1, 1 June 1989, Pages 143–164, http.

The EEG and MEG studies cited in the target article found reduced gamma band power following pseudowords in comparison with words. Pulvermüller interprets this power difference in terms of reverberating lexical cell assemblies. An alternative interpretation in terms of latency jitter in the gamma band following pseudowords is proposed that does not appeal to lexical cell assemblies.