James Joyce was educated almost exclusively by the Jesuits; this education and these priests make their appearance across Joyce's oeuvre. This dynamic has never been properly explicated or rigorously explored. Using Joyce's religious education and psychoanalytic theories of depression and paranoia, this book opens radical new possibilities for reading Joyce's fiction. It takes readers through some of the canon's most well-read texts and produces bold, fresh new readings. By placing these readings in light of Jesuit religious practice - in particular, (...) the Spiritual Exercises all Jesuit priests and many students undergo - the book shows how Joyce's deepest concerns about truth, literature, and love were shaped by these religious practices and texts. Joyce worked out his answers to these questions in his own texts, largely by forcing his readers to encounter, and perhaps answer, those questions themselves. Reading Joyce is a challenge not only in terms of interpretation but of experience - the confusion, boredom, and even paranoia readers feel when making their way through these texts. (shrink)

Current scientific research almost always requires collaboration among several (if not several hundred) specialized researchers. When scientists co-author a journal article, who deserves credit for discoveries or blame for errors? How should scientific institutions promote fruitful collaborations among scientists? In this book, leading philosophers of science address these critical questions.

This article shares reflections from members of the community of philosophers of education in the United States and Canada who were invited to express their insights in response to the theme ‘Snaps...

Liz JacksonEducation University of Hong KongNel Noddings is known around the world for her contributions to philosophy and philosophy of education. Her work on caring and relational ethics broke ne...

Death in the Clinic fills a gap in contemporary medical education by explicitly addressing the concrete clinical realities about death with which practitioners, patients, and their families continue to wrestle. Visit our website for sample chapters!

Aris Spanos and Deborah Mayo’s error-statistical approach to statistical modeling and inference adopts the reliability of inductive inference as a primary criterion for statistical model and estimator selection (e.g., curve fitting). In this paper, we expand the error-statistical approach’s adoption of reliable inductive inference by scrutinizing the epistemic legitimacy of contemporary techniques leveraged in data science. We argue that data validation and testing potentially provides a direct, measurable method of evaluating evidence for reliable inductive inferences in cases where the (...) error-statistical approach is not easily applied, and conclude with an exploration of core methodological foils to the reliability of inductive inference revealed by this argument. (shrink)

Cortisone, initially known as ‘compound E’ was the medical sensation of the late 1940s and early 1950s. As early as April 1949, only a week after Philip Hench and colleagues first described the potential of ‘compound E’ at a Mayo Clinic seminar, the New York Times reported the drug’s promise as a ‘modern miracle’ in the treatment of rheumatoid arthritis. Given its high profile, it is unsurprising that historians of medicine have been attracted to study the innovation of cortisone. (...) It arrived at the end of a decade of ‘therapeutic revolutions’, kicked off by penicillin transforming the treatment of bacterial infections and ending with hopes of a revolution in the treatment of non-infectious, chronic inflammatory diseases. Despite these studies of cortisone’s introduction, few historians have taken the story forward and considered how cortisone was adopted and adapted into clinical practice. This article tells the longer of how the drug and its derivatives were taken from research laboratories and integrated into clinical practice; what has in recent decades become known as translational medicine. In exploring cortisone’s first decade in Britain, we focus specifically on its role in the treatment of RA. Our approach is always to consider cortisone’s use in the context of other treatments available to clinicians, and at local and national institutional settings. We do not discuss the many other therapeutic uses of cortisone, which ranged for topical applications for skin diseases to the management of cancers, especially childhood leukaemia, nor do we discuss its close analogue ACTH—AdenoCorticoTropic Hormone. We think there are lessons in our study for TM policies today. (shrink)

El libro de Michael Heinrich tiene el doble mérito de presentar una mediación de la obra cumbre de Karl Marx, redactada en un lenguaje claro y accesible, y de proponer, al mismo tiempo, una interpretación densa y erudita del famoso texto. El autor no sólo evita las simplificaciones y los esquematismos, sino que incluso se interna por las complejidades y paradojas del pensamiento marxiano, que han dado origen a discusiones y polémicas nunca saldadas, y nos ofrece siempre una posición (...) argumenta.. (shrink)

Review of the volume "Scientific Collaboration and Collective Knowledge: New Essays", edited by Thomas Boyer-Kassem, Conor Mayo-Wilson, and Michael Weisberg.

A medical student's ability to present a case history is a critical skill that is difficult to teach. Case histories presented without theatrical engagement may fail to catch the attention of their intended recipients. More engaging presentations incorporate ‘stage presence’, eye contact, vocal inflection, interesting detail and succinct, well organised performances. They convey stories effectively without wasting time. To address the didactic challenge for instructing future doctors in how to ‘act’, the Mayo Medical School and The Mayo Clinic (...) Center for Humanities in Medicine partnered with the Guthrie Theater to pilot the programme ‘Telling the Patient's Story’. Guthrie teaching artists taught storytelling skills to medical students through improvisation, writing, movement and acting exercises. Mayo Clinic doctors participated and provided students with feedback on presentations and stories from their own experiences in patient care. The course's primary objective was to build students' confidence and expertise in storytelling. These skills were then applied to presenting cases and communicating with patients in a fresher, more engaging way. This paper outlines the instructional activities as aligned with course objectives. Progress was tracked by comparing pre-course and post-course surveys from the seven participating students. All agreed that the theatrical techniques were effective teaching methods. Moreover, this project can serve as an innovative model for how arts and humanities professionals can be incorporated for teaching and professional development initiatives at all levels of medical education. (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)

In this, the first book devoted to Peter Achinstein's influential work in philosophy of science, twenty distinguished philosophers, including four Lakatos award winners, address various aspects of Achinstein's influential views on the nature of scientific evidence, scientific explanation, and scientific realism. It includes short essays by Steve Gimbel and Jeff Maynes, Nancy Cartwright, Jordi Cat, Victor DiFate, Jerry Doppelt, Adam Goldstein, Philip Kitcher, Fred Kronz, Deborah Mayo, Greg Morgan, Helen Longino, John Norton, Michael Ruse, Bas van Fraassen, Stathis (...) Psillos, Larry Laudan, Richard Richards, Kent Staley, and Jim Woodward with replies to each contributor from Peter Achinstein. Readers will come away with an understanding of the current debate in multiple areas of philosophy of science and how various contemporary issues are connected. (shrink)

An innovative, multifaceted approach to scientific experiments as designed by and shaped through interaction with the modeling process The role of scientific modeling in mediation between theories and phenomena is a critical topic within the philosophy of science, touching on issues from climate modeling to synthetic models in biology, high energy particle physics, and cognitive sciences. Offering a radically new conception of the role of data in the scientific modeling process as well as a new awareness of the problematic aspects (...) of data, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Contributors address such issues as the construction of models in conjunction with scientific experimentation; the status of measurement and the function of experiment in the identification of relevant parameters; how the phenomena under study are reconceived when accounted for by a model; and the interplay between experimenting, modeling, and simulation when results do not mesh. Highlighting the mediating role of models and the model-dependence of data measurement, this volume proposes a normative and conceptual innovation in scientific modeling--that the phenomena to be investigated and modeled must not be precisely identified at the start but specified during the course of the interactions arising between experimental and modeling activities. Contributors: Nancy D. Cartwright, U of California, San Diego; Anthony Chemero, U of Cincinnati; Ronald N. Giere, U of Minnesota; Jenann Ismael, U of Arizona; Tarja Knuuttila, U of South Carolina; Andrea Loettgers, U of Bern, Switzerland; Deborah Mayo, Virginia Tech; Joseph Rouse, Wesleyan U; Paul Teller, U of California, Davis; Michael Weisberg, U of Pennsylvania; Eric Winsberg, U of South Florida. (shrink)

Part I: WHAT IS ETHICS? Plato: Socratic Morality: Crito. Suggestions for Further Reading. Part II: ETHICAL RELATIVISM VERSUS ETHICAL OBJECTIVISM. Herodotus: Custom is King. Thomas Aquinas: Objectivism: Natural Law. Ruth Benedict: A Defense of Ethical Relativism. Louis Pojman: A Critique of Ethical Relativism. Gilbert Harman: Moral Relativism Defended. Alan Gewirth: The Objective Status of Human Rights. Suggestions for Further Reading. Part III: MORALITY, SELF-INTEREST AND FUTURE SELVES. Plato: Why Be Moral? Richard Taylor: On the Socratic Dilemma. David Gauthier: Morality and (...) Advantage. Gregory Kavka: A Reconciliation Project. Derek Parfit: Later Selves and Moral Principles. Bernard Williams: Persons, Character, and Morality. Suggestions for Further Reading. Part IV: VALUE. Jeremy Bentham: Classical Hedonism. Robert Nozick: The Experience Machine. Richard Taylor: Value and the Origin of Right and Wrong. Friedrich Nietzsche: The Transvaluation of Values. Derek Parfit: What Makes Someone’s Life Go Best? Thomas Nagel: Value: The View from Nowhere. Suggestions for Further Reading. Part V: UTILITARIANISM AND CONSEQUENTIALISM. John Stuart Mill: Utilitarianism. J.J.C. Smart: Extreme and Restricted Utilitarianism. Kai Nielsen: Against Moral Conservatism. Bernard Williams: Against Utilitarianism. John Hospers: Rule-Utilitarianism. Robert Nozick: Side Constraints. Peter Singer: Famine, Affluence and Morality. Suggestions for Further Reading. Part VI: KANTIAN AND DEONTOLOGICAL SYSTEMS. Immanuel Kant: Foundation for the Metaphysic of Morals. W. D. Ross: What Makes Right Acts Right? Onora O’Neill: Kantian Formula of the End in Itself and World Hunger. Thomas Nagel: Moral Luck. Philippa Foot: Morality as a System of Hypothetical Imperatives. Judith Jarvis Thomson: Killing, Letting Die, and the Trolley Problem. Suggestions for Further Reading. Part VII: CONTRACTARIAN ETHICAL SYSTEMS. Thomas Hobbes: The Leviathan. David Gauthier: Why Contractarianism? John Rawls: Contractualism: Justice as Fairness. T.M. Scanlon: Contractualism and Utilitarianism. Suggestions for Further Reading. Part VIII: VIRTUE-BASED ETHICAL SYSTEMS. Aristotle: The Ethics of Virtue. Bernard Mayo: Virtue and the Moral Life. William Frankena: A Critique of Virtue-Based Ethics. Walter Schaller: Are Virtues No More than Dispositions to Obey Moral Rules? Alasdair MacIntyre: The Nature of the Virtues. Susan Wolf: Moral Saints. Louis P. Pojman: In Defense of Moral Saints. Suggestions for Further Reading. Part IX: THE FACT/VALUE PROBLEM: METAETHICS IN THE TWENTIETH CENTURY. David Hume: On Reason and the Emotions: The Fact/Value Distinction. G. E. Moore: Non-Naturalism. A. J. Ayer: Emotivism. R. M. Hare: Prescriptivism: The Structure of Ethics and Morals. Geoffrey Warnock: The Object of Morality. Suggestions for Further Reading. Part X: MORAL REALISM AND THE CHALLENGE OF SKEPTICISM. J.L. Mackie: The Subjectivity of Values. Jonathan Harrison: A Critique of Mackie’s Error Theory. Gilbert Harman: Moral Nihilism. Nicholas Sturgeon: Moral Explanations. Bernard Williams: Ethics and the Limits of Philosophy. Bruce Russell: Two Forms of Ethical Skepticism. Michael Smith: A Defense of Moral Realism. Suggestions for Further Reading. Part XI: RELIGION AND ETHICS. Plato: Morality and Religion. Immanuel Kant: God and Immortality as Necessary Postulates of Morality. George Mavrodes: Religious and the Queerness of Morality. Kai Nielson: Ethics Without God. Suggestions for Further Reading. Part XII: CONTEMPORARY CHALLENGES TO CLASSICAL ETHICAL THEORY. Part A. Sociobiology and the Question of Moral Responsibility. Charles Darwin: Ethics and the Descent of Man. E.O.Wilson: Sociobiology and Ethics. Michael Ruse: Evolution and Ethics: The Sociobiological Approach. Elliot Sober: Prospects for an Evolutionary Ethics. J.L. Mackie: The Law of the Jungle, Evolution and Morality. Suggestions for Further Readingon Sociobiology. Part B. The Challenge of Determinism to Moral Responsibility and Desert. Galen Strawson: The Impossibility of Moral Responsibility. Louis Pojman: Free Will, Determinism, and Moral Responsibility:A Response to Galen Strawson. Richard Taylor: A Libertarian Defense of Free Will and Responsibility. Suggestions for Further Reading on Moral Responsibility. Glossary of Ethical Terms. (shrink)

This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.

In the latter half of the twentieth century, philosophers of science have argued (implicitly and explicitly) that epistemically rational individuals might compose epistemically irrational groups and that, conversely, epistemically rational groups might be composed of epistemically irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they together imply that methodological prescriptions for scientific communities and those for individual scientists might be logically independent of one another. We develop a formal model of scientific inquiry, define four (...) criteria for individual and group epistemic rationality, and then prove that the four definitions diverge, in the sense that individuals will be judged rational when groups are not and vice versa. We conclude by explaining implications of the inconsistency thesis for (i) descriptive history and sociology of science and (ii) normative prescriptions for scientific communities. (shrink)

Jim Joyce argues for two amendments to probabilism. The first is the doctrine that credences are rational, or not, in virtue of their accuracy or “closeness to the truth” (1998). The second is a shift from a numerically precise model of belief to an imprecise model represented by a set of probability functions (2010). We argue that both amendments cannot be satisfied simultaneously. To do so, we employ a (slightly-generalized) impossibility theorem of Seidenfeld, Schervish, and Kadane (2012), who show that (...) there is no strictly proper scoring rule for imprecise probabilities. -/- The question then is what should give way. Joyce, who is well aware of this no-go result, thinks that a quantifiability constraint on epistemic accuracy should be relaxed to accommodate imprecision. We argue instead that another Joycean assumption — called strict immodesty— should be rejected, and we prove a representation theorem that characterizes all “mildly” immodest measures of inaccuracy. (shrink)

Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error probabilities (...) is to ensure that only statistical hypotheses that have passed severe or probative tests are inferred from the data. The severity criterion supplies a meta-statistical principle for evaluating proposed statistical inferences, avoiding classic fallacies from tests that are overly sensitive, as well as those not sensitive enough to particular errors and discrepancies. Introduction and overview 1.1 Behavioristic and inferential rationales for Neyman–Pearson (N–P) tests 1.2 Severity rationale: induction as severe testing 1.3 Severity as a meta-statistical concept: three required restrictions on the N–P paradigm Error statistical tests from the severity perspective 2.1 N–P test T(): type I, II error probabilities and power 2.2 Specifying test T() using p-values Neyman's post-data use of power 3.1 Neyman: does failure to reject H warrant confirming H? Severe testing as a basic concept for an adequate post-data inference 4.1 The severity interpretation of acceptance (SIA) for test T() 4.2 The fallacy of acceptance (i.e., an insignificant difference): Ms Rosy 4.3 Severity and power Fallacy of rejection: statistical vs. substantive significance 5.1 Taking a rejection of H0 as evidence for a substantive claim or theory 5.2 A statistically significant difference from H0 may fail to indicate a substantively important magnitude 5.3 Principle for the severity interpretation of a rejection (SIR) 5.4 Comparing significant results with different sample sizes in T(): large n problem 5.5 General testing rules for T(), using the severe testing concept The severe testing concept and confidence intervals 6.1 Dualities between one and two-sided intervals and tests 6.2 Avoiding shortcomings of confidence intervals Beyond the N–P paradigm: pure significance, and misspecification tests Concluding comments: have we shown severity to be a basic concept in a N–P philosophy of induction? (shrink)

While many philosophers of science have accorded special evidential significance to tests whose results are "novel facts", there continues to be disagreement over both the definition of novelty and why it should matter. The view of novelty favored by Giere, Lakatos, Worrall and many others is that of use-novelty: An accordance between evidence e and hypothesis h provides a genuine test of h only if e is not used in h's construction. I argue that what lies behind the intuition that (...) novelty matters is the deeper intuition that severe tests matter. I set out a criterion of severity akin to the notion of a test's power in Neyman-Pearson statistics. I argue that tests which are use-novel may fail to be severe, and tests that are severe may fail to be use-novel. I discuss the 1919 eclipse data as a severe test of Einstein's law of gravity. (shrink)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

The key problem in the controversy over group selection is that of defining a criterion of group selection that identifies a distinct causal process that is irreducible to the causal process of individual selection. We aim to clarify this problem and to formulate an adequate model of irreducible group selection. We distinguish two types of group selection models, labeling them type I and type II models. Type I models are invoked to explain differences among groups in their respective rates of (...) production of contained individuals. Type II models are invoked to explain differences among groups in their respective rates of production of distinct new groups. Taking Elliott Sober's model as an exemplar, we argue that although type I models have some biological importance--they force biologists to consider the role of group properties in influencing the fitness of organisms--they fail to identify a distinct group-level causal selection process. Type II models if properly framed, however, do identify a group-level causal selection process that is not reducible to individual selection. We propose such a type II model and apply it to some of the major candidates for group selection. (shrink)

Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners (...) are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing. (shrink)

The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle 'practical' problems of model validation, and conversely, (...) a methodology of statistical model validation can shed light on a number of issues of interest to philosophers of science. (shrink)

Bernard Mayo; VIII—Belief and Constraint, Proceedings of the Aristotelian Society, Volume 64, Issue 1, 1 June 1964, Pages 139–156, https://doi.org/10.1093/arist.

We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the social context (if any) (...) in which such strategies are to be employed. (shrink)

In this article, Cris Mayo examines the relationship among anti-LGBTQ policies, gay marriage, and sexuality education. Her concern is that because gay marriage is insufficiently different from heterosexual marriage, adding it as an issue to curriculum or broader culture debate elides rather than addresses sexual difference. In other words, marriage may be an assimilative aspiration that closes down discussions of what sexuality is and can mean, that sidesteps other related social issues such as health care for all, and that (...) reinforces sexuality and gender identity as privatized, not political, concerns. Mayo examines different strands of LGBTQ history that complicate the meanings of sexuality and that critique a variety of antigay or heterosexist policies for their exclusions. She concludes by suggesting that the possibilities of sexuality are not served by advocacy for one gay relationship formation and calling for a sexuality education that is instead directed at sexual diversity. (shrink)

In seeking general accounts of evidence, confirmation, or inference, philosophers have looked to logical relationships between evidence and hypotheses. Such logics of evidential relationship, whether hypothetico-deductive, Bayesian, or instantiationist fail to capture or be relevant to scientific practice. They require information that scientists do not generally have (e.g., an exhaustive set of hypotheses), while lacking slots within which to include considerations to which scientists regularly appeal (e.g., error probabilities). Building on my co-symposiasts contributions, I suggest some directions in which a (...) new and more adequate philosophy of evidence can move. (shrink)

Epistemic decision theory (EDT) employs the mathematical tools of rational choice theory to justify epistemic norms, including probabilism, conditionalization, and the Principal Principle, among others. Practitioners of EDT endorse two theses: (1) epistemic value is distinct from subjective preference, and (2) belief and epistemic value can be numerically quantified. We argue the first thesis, which we call epistemic puritanism, undermines the second.

A dynamical system is called chaotic if small changes to its initial conditions can create large changes in its behavior. By analogy, we call a dynamical system structurally chaotic if small changes to the equations describing the evolution of the system produce large changes in its behavior. Although there are many definitions of “chaos,” there are few mathematically precise candidate definitions of “structural chaos.” I propose a definition, and I explain two new theorems that show that a set of models (...) is structurally chaotic if it contains a chaotic function. I conclude by discussing the relationship between structural chaos and structural stability. (shrink)

Bernard Mayo, who died in 2000, was Professor of Moral Philosophy at the University of St Andrews from 1967–1983. He chose his 19th century predecessor J F Ferrier as the subject of his inaugural lecture delivered on 26th November 1969. Copies of the lecture were printed and distributed, but it was never published. Mayo's choice of subject for his inaugural shows remarkable and at the time highly unusual insight into the value Ferrier's philosophical writings, and rising current interest (...) in Ferrier warrants its publication now, in a lightly edited version that has eliminated references to the specific occasion on which it was delivered. Mayo explores Ferrier's version of the contrast between the human and the natural as a means of illuminating the 20th century debate between realists and relativists in moral philosophy. (shrink)

Paulo Freire : the educator, his oeuvre, and changing contexts -- Holistic interpretations of Freire's work : a critical review -- Critical literacy, praxis, and emancipatory politics -- "Remaining on the same side of the river" : neo-liberalism, party movements, and the struggle for greater coherence -- Reinventing Freire in a Southern context : the Mediterranean -- Engaging with practice : a Freirean reflection on different pedagogical sites.

I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or "blamed" when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing auxiliary (...) hypotheses from that of appraising a primary hypothesis. By discriminating patterns of error, this approach can at least block, if not also severely test, attempted explanations of an anomaly. I illustrate how this approach directs progress with Duhemian problems and explains how scientists actually grapple with them. (shrink)

Several current debates in the epistemology of testimony are implicitly motivated by concerns about the reliability of rules for changing one’s beliefs in light of others’ claims. Call such rules testimonial norms (tns). To date, epistemologists have neither (i) characterized those features of communities that influence the reliability of tns, nor (ii) evaluated the reliability of tns as those features vary. These are the aims of this paper. I focus on scientific communities, where the transmission of highly specialized information is (...) both ubiquitous and critically important. Employing a formal model of scientific inquiry, I argue that miscommunication and the “communicative structure” of science strongly influence the reliability of tns, where reliability is made precise in three ways. (shrink)

After some general remarks about the interrelation between philosophical and statistical thinking, the discussion centres largely on significance tests. These are defined as the calculation of p-values rather than as formal procedures for ‘acceptance‘ and ‘rejection‘. A number of types of null hypothesis are described and a principle for evidential interpretation set out governing the implications of p- values in the specific circumstances of each application, as contrasted with a long-run interpretation. A number of more complicated situ- ations are discussed (...) in which modification of the simple p-value may be essential. (shrink)

Suicide has been condemned in our culture in one way or another since Augustine offered theological arguments against it in the sixth century. More recently, theological condemnation has given way to the view that suicidal behavior must always be symptomatic of emotional disturbance and mental illness. However, suicide has not always been viewed so negatively. In other times and cultures, it has been held that circumstances might befall a person in which suicide would be a perfectly rational course of action, (...) in the same sense that any other course of action could be rational: that it could be sensible, i.e., defensible by good reasons, or that it could be in keeping with the agent's fundamental interests. Indiscriminate use of modern life-sustaining technologies has renewed interest in the possibility of rational suicide. Today proponents of rational suicide tend to equate the rationality of suicide with the competence of the decision to commit suicide. (shrink)

A common intuition about evidence is that if data x have been used to construct a hypothesis H, then x should not be used again in support of H. It is no surprise that x fits H, if H was deliberately constructed to accord with x. The question of when and why we should avoid such “double-counting” continues to be debated in philosophy and statistics. It arises as a prohibition against data mining, hunting for significance, tuning on the signal, and (...) ad hoc hypotheses, and as a preference for predesignated hypotheses and “surprising” predictions. I have argued that it is the severity or probativeness of the test—or lack of it—that should determine whether a double-use of data is admissible. I examine a number of surprising ambiguities and unexpected facts that continue to bedevil this debate. (shrink)

Books on Paulo Freire continue to be published in abundance. It is often very difficult to separate the wheat from the chaff. Following on a great book on the subject by Walter Kohan, this book has...

An important theme to have emerged from the new experimentalist movement is that much of actual scientific practice deals not with appraising full-blown theories but with the manifold local tasks required to arrive at data, distinguish fact from artifact, and estimate backgrounds. Still, no program for working out a philosophy of experiment based on this recognition has been demarcated. I suggest why the new experimentalism has come up short, and propose a remedy appealing to the practice of standard error statistics. (...) I illustrate a portion of my proposal using Galison's experimental narrative on neutral currents. (shrink)

The issues of double-counting, use-constructing, and selection effects have long been the subject of debate in the philosophical as well as statistical literature. I have argued that it is the severity, stringency, or probativeness of the test—or lack of it—that should determine if a double-use of data is admissible. Hitchcock and Sober ([2004]) question whether this ‘severity criterion' can perform its intended job. I argue that their criticisms stem from a flawed interpretation of the severity criterion. Taking their criticism as (...) a springboard, I elucidate some of the central examples that have long been controversial, and clarify how the severity criterion is properly applied to them. Severity and Use-Constructing: Four Points (and Some Clarificatory Notes) 1.1 Point 1: Getting beyond ‘all or nothing’ standpoints 1.2 Point 2: The rationale for prohibiting double-counting is the requirement that tests be severe 1.3 Point 3: Evaluate severity of a test T by its associated construction rule R 1.4 Point 4: The ease of passing vs. ease of erroneous passing: Statistical vs. ‘Definitional’ probability The False Dilemma: Hitchcock and Sober 2.1 Marsha measures her desk reliably 2.2 A false dilemma Canonical Errors of Inference 3.1 How construction rules may alter the error-probing performance of tests 3.2 Rules for accounting for anomalies 3.3 Hunting for statistically significant differences Concluding Remarks. (shrink)

It is common to assume that the problem of induction arises only because of small sample sizes or unreliable data. In this paper, I argue that the piecemeal collection of data can also lead to underdetermination of theories by evidence, even if arbitrarily large amounts of completely reliable experimental and observational data are collected. Specifically, I focus on the construction of causal theories from the results of many studies (perhaps hundreds), including randomized controlled trials and observational studies, where the studies (...) focus on overlapping, but not identical, sets of variables. Two theorems reveal that, for any collection of variables V, there exist fundamentally different causal theories over V that cannot be distinguished unless all variables are simultaneously measured. Underdetermination can result from piecemeal measurement, regardless of the quantity and quality of the data. Moreover, I generalize these results to show that, a priori, it is impossible to choose a series of small (in terms of number of variables) observational studies that will be most informative with respect to the causal theory describing the variables under investigation. This final result suggests that scientific institutions may need to play a larger role in coordinating differing research programs during inquiry. (shrink)