Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher‐level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea that (...) higher‐level theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories. *Received July 2009; revised October 2009. †To contact the authors, please write to: Leah Henderson, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 32D‐808, Cambridge, MA 02139; e‐mail: [email protected]. (shrink)

Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘para- digms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher-level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea (...) that higher-level theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories. (shrink)

Hierarchical Bayesian models provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher-level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea that higher-level (...) theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories. (shrink)

The paper illustrates how organic chemists dramatically altered their practices in the middle part of the twentieth century through the adoption of analytical instrumentation - such as ultraviolet and infrared absorption spectroscopy and nuclear magnetic resonance spectroscopy - through which the difficult process of structure determination for small molecules became routine. Changes in practice were manifested in two ways: in the use of these instruments in the development of 'rule-based' theories; and in an increased focus on synthesis, at the expense (...) of chemical analysis. These rule-based theories took the form of generalizations relating structure to chemical and physical properties, as measured by instrumentation. This 'Instrumental Revolution' in organic chemistry was two-fold: encompassing an embrace of new tools that provided unprecedented access to structures, and a new way of thinking about molecules and their reactivity in terms of shape and structure. These practices suggest the possibility of a change in the ontological status of chemical structures, brought about by the regular use of instruments. The career of Robert Burns Woodward (1917-1979) provides the central historical examples for the paper. Woodward was an organic chemist at Harvard from 1937 until the time of his death. In 1965, he won the Nobel Prize in Chemistry. (shrink)

Written between 1855 and 1862, the four novels "Rudin", "A Nest o f the Gentry", "On the Eve" and "Fathers and Sons" are generally recognised as Turgenev's most notable contribution to Russian and world literature. Are they primarily social chronicles, as Turgenev suggested, or are they rather to be seen as celebrations of life, of the beauty of love and youthful idealism? Are they paens to the nobility of the human spirit or ironic comments on human folly? The same questions (...) are addressed in the present study, but the question with which it is principally concerned is that of the novels' essential character. (shrink)

Clambering down slippery rocks to a swimming hole. Ducking the plume of smoke from a barbecue grill. Wishing for a breeze in a too-small dome tent. Scanning the sky for rain from a postage-stamp backyard. It is in these small moments of action—and inaction—that Justin Kimball captures our everyday attempts to relax. Indeed, one might argue that the events depicted are everyday life. Kimball’s compelling photographs depict ordinary people—parents and teens, grandparents and kids—in landscapes of leisure. These are not the (...) exclusive resorts and white sand beaches of the affluent; rather, they are the parks, campgrounds, and fishing piers where most Americans vacation. They are natural landscapes—inviting, green, and sometimes beautiful—but at the same time they are imperfect—muddy, crowded, and partially paved. There is nothing idyllic about these vacation spots; indeed, Kimball’s photographs make clear that daily life can never be fully left behind. The people in his pictures, though momentarily transformed by cascading water or the shade of towering trees, remain enmeshed in ties of family and obligation, shadowed by thoughts of home. It is Kimball’s particular genius to isolate these moments between duty and pleasure. Where We Find Ourselves enables viewers to identify with—and participate in—this bittersweet aspect of American leisure and the ambiguous contemporary relationship between people and nature. (shrink)

This book is about the eminent behavioral scientist B. F. Skinner, the American culture in which he lived and worked, and the behaviorist movement that played a leading role in American psychological and social thought during the twentieth century. From a base of research on laboratory animals in the 1930s, Skinner built a committed and influential following as well as a utopian movement for social reform. His radical ideas attracted much public attention and generated heated controversy. By the mid-1970s, he (...) had become the most widely recognized scientist in America, surpassing even Margaret Mead and Linus Pauling. Yet Skinner himself was an unassuming family man from a modest middle-class background, a machine-shop tinkerer whose tastes ran to English and French literature. Drawing on archival research, interviews, and historical styles appropriate to the evidence, the authors assembled in this volume examine Skinner's remarkable rise to prominence in the wider context of America's intellectual, cultural, and social history. (shrink)

BackgroundSome people with progressive neurological diseases find they need additional support with eating and drinking at mealtimes, and may require artificial nutrition and hydration. Decisions concerning artificial nutrition and hydration at the end of life are ethically complex, particularly if the individual lacks decision-making capacity. Decisions may concern issues of life and death: weighing the potential for increasing morbidity and prolonging suffering, with potentially shortening life. When individuals lack decision-making capacity, the standard processes of obtaining informed consent for medical interventions (...) are disrupted. Increasingly multi-professional groups are being utilised to make difficult ethical decisions within healthcare. This paper reports upon a service evaluation which examined decision-making within a UK hospital Feeding Issues Multi-Professional Team.MethodsA three month observation of a hospital-based multi-professional team concerning feeding issues, and a one year examination of their records. The key research questions are: a) How are decisions made concerning artificial nutrition for individuals at risk of lacking decision-making capacity? b) What are the key decision-making factors that are balanced? c) Who is involved in the decision-making process?ResultsDecision-making was not a singular decision, but rather involved many different steps. Discussions involving relatives and other clinicians, often took place outside of meetings. Topics of discussion varied but the outcome relied upon balancing the information along four interdependent axes: Risks, burdens and benefits; Treatment goals; Normative ethical values; Interested parties.ConclusionsDecision-making was a dynamic ongoing process with many people involved. The multiple points of decision-making, and the number of people involved with the decision-making process, mean the question of ‘who decides’ cannot be fully answered. There is a potential for anonymity of multiple decision-makers to arise. Decisions in real world clinical practice may not fit precisely into a model of decision-making. The findings from this service evaluation illustrate that within multi-professional team decision-making; decisions may contain elements of both substituted and supported decision-making, and may be better represented as existing upon a continuum. (shrink)

Participants in the cognitive phenomenology debate have proceeded by (a) proposing a bifurcation of theoretical options into inflationary and non-inflationary theories, and then (b) providing arguments for/against one of these theories. I suggest that this method has failed to illuminate the commonalities and differences among conscious intentional states of different types, in the absence of a theory of the structure of these states. I propose such a theory. In perception, phenomenal-intentional properties combine with somatosensory properties to form P-I property clusters (...) that serve as phenomenal modes of presentations of particulars. In imagination, somatosensory properties are replaced with phenomenal-intentional properties whose intentional objects are somatosensory properties, thus resulting in imaginative facsimiles of perceptual P-I property clusters. Such structures can then be used as phenomenal prototypes that pick out individuals and kinds. Sets of such prototypes constitute a subject’s conception of individuals and kinds. Combined with a few additional elements, these imaginative P-I property clusters serve as the building-blocks of conscious cognitive states. Different ways of carving up theoretical space classify my theory either as inflationary or as non-inflationary. I conclude that the theory is anti-inflationary in letter but inflationary in spirit. (shrink)

This paper explores, in a rather schematic way, some issues having to do with the conception of causation and explanation implicit in regression analysis. I argue that (a) regression analysis does not yield lawlike generalizations but rather claims about causal connections in particular populations and that (b) regression analyses are not plausibly viewed as part of a neo-Humean program of analyzing causal claims in terms of claims about patterns of statistical association. I also argue that (c) the conception of explanation (...) implicit in regression analysis is deductive and involves the exhibition of a pattern of counterfactual dependence between mean values of the independent and dependent variables. (shrink)

This paper examines a recent attempt by Evan Jobe to account for the asymmetric character of many scientific explanations. It is argued that a purported counterexample to Jobe's account, from Clark Glymour, is inconclusive, but that the account faces independent objections. It is also suggested, contrary to Jobe, that the explanatory relation is not always asymmetric. Sometimes a singular sentence C can figure in a DN derivation of another singular sentence E and E can also figure in a DN derivation (...) of C. Yet while we are inclined to regard the first derivation as an explanation of E, we are not inclined to regard the second derivation as an explanation of C. As Sylvain Bromberger pointed out in a now classic article (1966), one can explain the period of a pendulum by reference to its length and yet, although one can give a DN derivation of the length of a pendulum by reference to its period, this derivation does not seem to represent an explanation. Evan Jobe has recently offered an interesting account of such explanatory asymmetries and Clark Glymour has in turn proposed a counterexample which seems to show that Jobe's account is defective. The aim of this paper is two-fold. I shall attempt to show that (a) Glymour's proposed counterexample can be rejected on the grounds that it violates an independently plausible restriction on the role that equalities may play in DN explanation, and that (b) although Glymour's counterexample can be avoided in this way, Jobe's account is defective in several other respects. (shrink)

The Schuster-Blackett (S-B) conjecture, which supposes the relationshipM/J=βG 1/2 /2c between the magnetic dipole moments (M) of celestial objects and their angular momenta (J), where G is the Newtonian constant of gravitation, c the speed of light, and β a dimensionless constant of order unity, is examined in the context of the evolution of pulsar gyromagnetic ratios. It is demonstrated that the evolution of pulsar gyromagnetic ratios is not consistent with the strong form of the S-B conjecture where β is (...) taken to be a constant. The pulsar evidence, which shows evolution withM/J constant for individual short-period pulsars, however, does admit the validity of a weaker form of the S-B conjecture, where β is allowed to take on a range of values. It is also shown that the only conventional explanation of the origin of pulsar magnetic fields that produces evolution where the gyromagnetic ratio remains constant for individual pulsars which generates magnetic fields of sufficient strength, the thermally driven Hall-field-limited battery effect, may not convincingly account for the observed behavior of pulsars. A few of the implications of the S-B conjecture and the pulsar evidence are explored. (shrink)

"In the 12 case studies in this treasure of a book, various authors examine the critical, direction-finding moments in the work of such individuals as Charles Darwin, Jean Piaget, Robert Burns Woodward, William James, Anais Nin, and others." --Virginia Quarterly Review.

The aim of the paper is to present James Woodward's conception of the philosophy of science as it has been developed during last two decades in his essays. Compared with B. van Fraassen, N. Cartwright or W. C. Salmon the views of J. Woodward are not so popular. According to the author, however, they represent an important contribution to the contemporary philosophy of science. In the first two parts of the paper the differences between Woodward's and Hempel's (...) views of scientific explanation are shown. The third part shows Woodward's approach to the problems of the causal analysis and to the philosophical problems of the so called "regression equations". In conclusion the author makes some critical commentaries and remarks on Woodward's views. (shrink)

In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward ([1999]) put forward two independent theses, which they label ‘level invariance’ and ‘manipulability’, and they claim that, given a specific set of assumptions, manipulability implies the causal Markov condition. These claims are interesting and important, and this paper is devoted to commenting on them. With respect to level invariance, I argue that Hausman and Woodward's discussion is confusing because, as I (...) point out, they use different senses of ‘intervention’ and ‘invariance’ without saying so. I shall remark on these various uses and point out that the thesis is true in at least two versions. The second thesis, however, is not true. I argue that in their formulation, the manipulability thesis is patently false and that a modified version does not fare better. Furthermore, I think their proof that manipulability implies the causal Markov condition is not conclusive. In the deterministic case it is valid but vacuous, whereas it is invalid in the probabilistic case. 1 Introduction 2 Intervention, invariance and modularity 3 The causal Markov condition: CM1 and CM2 4 From MOD to the causal Markov condition and back 5 A second argument for CM2 6 The proof of the causal Markov condition for probabilistic causes 7 ‘Cartwright's objection’ defended 8 Metaphysical defenses of the causal Markov condition 9 Conclusion. (shrink)

In a recent paper James Bogen and James Woodward denounce a set of views on confirmation that they collectively brand 'IRS'. The supporters of these views cast confirmation in terms of Inferential Relations between observational and theoretical Sentences. Against 1RS accounts of confirmation, Bogen and Woodward unveil two main objections: (a) inferential relations are not necessary to model confirmation relations since many data are neither in sentential form nor can they be put in such a form and (b) (...) inferential relations are not sufficient to model confirmation relations because the former cannot capture evidentially relevant factors about the detection processes and instruments that generate the data. In this paper I have a two-fold aim: (i) to show that Bogen and Woodward fail to provide compelling grounds for the rejection of IRS models and (ii) to highlight some of the models' neglected merits. (shrink)

Daniel Hausman and James Woodward claim to prove that the causal Markov condition, so important to Bayes-nets methods for causal inference, is the ‘flip side’ of an important metaphysical fact about causation—that causes can be used to manipulate their effects. This paper disagrees. First, the premise of their proof does not demand that causes can be used to manipulate their effects but rather that if a relation passes a certain specific kind of test, it is causal. Second, the proof (...) is invalid. Third, the kind of testability they require can easily be had without the causal Markov condition. (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)

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining of a capacity with its exercise. But Hume argued that no distinction can be made between the obtaining of a power and its exercise. (shrink)

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining (or triggering) of a capacity with its exercise. But Hume argued (mistakenly I suggest) that no distinction can be made between the obtaining of a power and its exercise. (shrink)

I argue that the Causal Markov Condition (CMC) is in principle applicable to the Einstein–Podolsky–Rosen (EPR) correlations. This is in line with my defence in the past of the applicability of the Principle of Common Cause to quantum mechanics. I first review a contrary claim by Dan Hausman and Jim Woodward, who endeavour to preserve the CMC against a possible counterexample by asserting that the conditions for the application of the CMC are not met in the EPR experiment. In (...) their view the CMC is inapplicable to the EPR correlations—i.e. it neither obtains nor fails. The view is grounded upon the non-separability of the quantum state, and the consequent unavailability of interventions. I urge that whether interventions are available in EPR—and why—is a complex and contextual question that does not have a unique or uniform answer. Instead, I argue that different combinations of causal hypotheses under test and interpretations of quantum mechanics yield different answers to the question. (shrink)

The key idea of the interventionist account of causation is that a variable A causes a variable B if and only if B would change if A were manipulated in the appropriate way. This paper raises two problems for Woodward's (2003) version of interventionism. The first is that the conditions it imposes are not sufficient for causation, because these conditions are also satisfied by non-causal relations of nomological dependence expressed in association laws. Such laws ground a relation of mutual (...) manipulability that is incompatible with the asymmetry of causation. Several ways of defending the interventionist account are examined and found unsatisfying. The second problem is that it often seems to be impossible, in a model that contains variables linked by an association law, to satisfy the conditions imposed on interventions on such variables. Various ways to solve this second problem, most importantly the analysis of manipulability in terms of difference making, are examined. Given that none solves the problem, I conclude that the interventionist conditions are neither sufficient nor necessary for causation. It is suggested that they provide an analysis of nomological dependence, which may be supplemented with the notion of a causal process to yield an analysis of causation. (shrink)

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining (or triggering) of a capacity with its exercise. But Hume argued (mistakenly I suggest) that no distinction can be made between the obtaining of a power and its exercise. (shrink)

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining (or triggering) of a capacity with its exercise. But Hume argued (mistakenly I suggest) that no distinction can be made between the obtaining of a power and its exercise. (shrink)

Intention was seen traditionally as a philosophical concept, before being debated more recently from psychological and social perspectives. Today the cognitive sciences approach intention empirically, at the level of its underlying mechanisms. This naturalization of intention makes it more concrete and graspable by empirical sciences. This volume offers an interdisciplinary integration of current research on intentional processes naturalized through action, drawing on the theoretical and empirical approaches of cognitive neuroscience, psychology, philosophy, and sociology. Each chapter integrates several disciplinary perspectives. Taken (...) together, the chapters show that the reunification of the different dimensions of intentional processes may constitute an adequate basis for a general model of intentional processes and their links to action. This can be applied at various levels, from neuronal activity to self-constitution, from the expression of intentional actions at the individual level to their expression in social contexts, and to the recognition of intention in actions executed by others.ContributorsColin Allen, Mireille Bonnard, Vittorio Gallese, Jozina B. de Graaf, Franck Grammont, Patrick Haggard, Marco Iacoboni, Dorothée Legrand, Pierre Livet, Albert Ogien, Jean Pailhous, Jean-Luc Petit, Jean-Michel Roy, Jessica A. Sommerville, Manos Tsakiris, Amanda L. Woodward. (shrink)

The aim of this series is to bring together important recent writings in major areas of philosophical inquiry, selected from a variety of sources, mostly periodicals, which may not be conveniently available to the university student or the general reader. The editor of each volume contributes an introductory essay on the items chosen and on the questions with which they deal. A selective bibliography is appended as a guide to further reading. This volume presents a selection of the most important (...) recent writings on the nature of explanation. It covers a broad range of topics from the philosophy of science to the central philosophical terrain of the theory of knowledge. The distinguished contributors include Peter Achinstein, Wesley C. Salmon, Carl G. Hempel, Philip Kitcher, Bas C. van Fraassen, Jaegwon Kim, B. Brody, Timothy McCarthy, Peter Railton, David Lewis, Peter Lipton, James Woodward, and Robert J. Matthews. (shrink)

This paper compares the relative merits of two alternatives to traditional accounts of causal explanation: Jim Woodward's counterfactual invariance account, and the Mechanistic account of Machamer, Darden, and Craver. Mechanism wins (a) because we have good causal explanations for chaotic effects whose production does not exhibit the counterfactual regularities Woodward requires, and (b)because arguments suggested by Belnap's and Green's discussion of prediction (in'Facing the Future' chpt 6)show that the relevant counterfactuals about ideal interventions on non-deterministic and deterministic systems (...) lack truth value. (shrink)

The COVID-19 pandemic shocked the global economy, with numerous companies suffering losses and shutting down. However, some companies proved to be resilient, being able to sustain their economic performance despite the pandemic. The study aims to explain the sustainable economic performance of companies during the COVID-19 pandemic. The relationships between empowering leadership, innovative work behavior, organizational readiness to change, and sustainable economic performance were assessed. The data were collected via an online questionnaire from January 2021 to March 2021, during the (...) height of the COVID-19 pandemic in Russia. The respondents were Russian companies’ employees holding management positions, competent to objectively assess organizational circumstances during the COVID-19 pandemic. A sample of 337 was used in the analysis. Confirmatory factor analysis (CFA) with maximum likelihood estimation was conducted using SPSS AMOS. The structural model was tested with standardized parameter estimates, standard errors, and p-values calculated. The findings of the study suggest that innovative work behavior and organizational readiness to learn have a direct influence on sustainable economic performance. The findings also suggest that empowering leadership impacts innovative work behavior but not sustainable economic performance. The mediation analysis indicates that innovative work behavior is a mediator between empowering leadership and sustainable economic performance, whereas organizational readiness to learn is not a moderator. The study adds to the leadership and sustainability body of knowledge and contributes to the research on the COVID-19 pandemic in the organizational context. (shrink)

The last two decades have seen a rising interest in (a) the notion of a scientific phenomenon as distinct from theories and data, and (b) the intricacies of experimentally producing and stabilizing phenomena. This paper develops an analysis of the stabilization of phenomena that integrates two aspects that have largely been treated separately in the literature: one concerns the skills required for empirical work; the other concerns the strategies by which claims about phenomena are validated. I argue that in order (...) to make sense of the process of stabilization, we need to distinguish between two types of phenomena: phenomena as patterns in the data ( surface regularities ) and phenomena as underlying (or hidden ) regularities. I show that the epistemic relationships that data bear to each of these types of phenomena are different: Data patterns are instantiated by individual data, whereas underlying regularities are indicated by individual data, insofar as they instantiate a data pattern. Drawing on an example from memory research, I argue that neither of these two kinds of phenomenon can be stabilized in isolation. I conclude that what is stabilized when phenomena are stabilized is the fit between surface regularities and hidden regularities. (shrink)