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The Neglect of Experiment

Noûs 24 (4):631-634 (1990)

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  1. Bayesian Informal Logic and Fallacy.Kevin Korb - 2004 - Informal Logic 24 (1):41-70.
    Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing.
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  • Computer Simulation and Philosophy of Science.Wendy S. Parker - 2012 - Metascience 21 (1):111-114.
    Computer simulation and philosophy of science Content Type Journal Article Pages 1-4 DOI 10.1007/s11016-011-9567-8 Authors Wendy S. Parker, Department of Philosophy, Ellis Hall 202, Ohio University, Athens, OH 45701, USA Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.
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  • Bayesian Networks and the Problem of Unreliable Instruments.Luc Bovens & Stephan Hartmann - 2000 - Philosophy of Science 69 (1):29-72.
    We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising (...)
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  • On Pain Experience, Multidisciplinary Integration and the Level-Laden Conception of Science.Tudor Baetu - 2017 - Synthese:1-20.
    Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...)
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  • Reconsidering the Carnap-Kuhn Connection.Jonathan Y. Tsou - 2015 - In Kuhn’s Structure of Scientific Revolutions - 50 Years On. Springer Verlag.
    Recently, some philosophers of science (e.g., Gürol Irzik, Michael Friedman) have challenged the ‘received view’ on the relationship between Rudolf Carnap and Thomas Kuhn, suggesting that there is a close affinity (rather than opposition) between their philosophical views. In support of this argument, these authors cite Carnap and Kuhn’s similar views on incommensurability, theory-choice, and scientific revolutions. Against this revisionist view, I argue that the philosophical relationship between Carnap and Kuhn should be regarded as opposed rather than complementary. In particular, (...)
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  • Philosophical Conceptual Analysis as an Experimental Method.Michael T. Stuart - 2015 - In Thomas Gamerschlag, Doris Gerland, Rainer Osswald & Wiebke Petersen (eds.), Meaning, Frames, and Conceptual Representation. Düsseldorf University Press. pp. 267-292.
    Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...)
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  • Experimentation in Cognitive Neuroscience and Cognitive Neurobiology.Jacqueline Anne Sullivan - 2015 - In Jens Clausen Neil Levy (ed.), Handbook on Neuroethics. Springer.
    Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...)
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  • New Science for Old.Bruce Mangan & Stephen Palmer - 1989 - Behavioral and Brain Sciences 12 (3):480-482.
  • Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
  • The Rule of Reproducibility and its Applications in Experiment Appraisal.Xiang Chen - 1994 - Synthese 99 (1):87 - 109.
  • History and Physics.Roger H. Stuewer - 1998 - Science & Education 7 (1):13-30.
  • Vicissitudes of Laboratory Life.Friedel Weinert - 1992 - British Journal for the Philosophy of Science 43 (3):423-429.
  • Bayesian Conditionalization and Probability Kinematics.Colin Howson & Allan Franklin - 1994 - British Journal for the Philosophy of Science 45 (2):451-466.
  • Old and New Problems in Philosophy of Measurement.Eran Tal - 2013 - Philosophy Compass 8 (12):1159-1173.
    The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...)
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  • Popper, Kuhn, Lakatos, and Aim-Oriented Empiricism.Nicholas Maxwell - 2001 - Philosophia 32 (1-4):181-239.
    In this paper I argue that aim-oriented empiricism (AOE), a conception of natural science that I have defended at some length elsewhere[1], is a kind of synthesis of the views of Popper, Kuhn and Lakatos, but is also an improvement over the views of all three. Whereas Popper's falsificationism protects metaphysical assumptions implicitly made by science from criticism, AOE exposes all such assumptions to sustained criticism, and furthermore focuses criticism on those assumptions most likely to need revision if science is (...)
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  • A Pragmatic, Existentialist Approach to the Scientific Realism Debate.Curtis Forbes - 2017 - Synthese 194 (9):3327-3346.
    It has become apparent that the debate between scientific realists and constructive empiricists has come to a stalemate. Neither view can reasonably claim to be the most rational philosophy of science, exclusively capable of making sense of all scientific activities. On one prominent analysis of the situation, whether we accept a realist or an anti-realist account of science actually seems to depend on which values we antecedently accept, rather than our commitment to “rationality” per se. Accordingly, several philosophers have attempted (...)
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  • Hacking’s Experimental Realism.David B. Resnik - 1994 - Canadian Journal of Philosophy 24 (3):395-411.
  • How Did Kettlewell’s Experiment End?David Rudge - unknown
    The past quarter century has seen an enormous growth of interest among scholars of science and technology in both particular experimental episodes and the process of experimentation. Among the most influential accounts have been those developed by Allan Franklin (1986, 1990), Deborah Mayo (1996) and Peter Galison (1987), each of which was developed primarily with reference to examples drawn from the history of physics. One useful way to access the generality of an account of experiment is to see how it (...)
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  • Prospective Realism.Harold I. Brown - 1990 - Studies in History and Philosophy of Science Part A 21 (2):211.
  • The Discovery of the Zeeman Effect: A Case Study of the Interplay Between Theory and Experiment.Theodore Arabatzis - 1991 - Studies in History and Philosophy of Science Part A 23 (3):365-388.
  • Habits of Mind, Scholarship and Decision Making in Science and Religion.Colin F. Gauld - 2005 - Science & Education 14 (3-5):291-308.
  • Generative Role of Experiments in Physics and in Teaching Physics: A Suggestion for Epistemological Reconstruction.Ismo T. Koponen & Terhi Mäntylä - 2006 - Science & Education 15 (1):31-54.
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  • Lawson’s Shoehorn, Reprise.Douglas Allchin - 2006 - Science & Education 15 (1):113-120.
  • Franklin, Holmes, and the Epistemology of Computer Simulation.Wendy S. Parker - 2008 - International Studies in the Philosophy of Science 22 (2):165 – 183.
    Allan Franklin has identified a number of strategies that scientists use to build confidence in experimental results. This paper shows that Franklin's strategies have direct analogues in the context of computer simulation and then suggests that one of his strategies—the so-called 'Sherlock Holmes' strategy—deserves a privileged place within the epistemologies of experiment and simulation. In particular, it is argued that while the successful application of even several of Franklin's other strategies (or their analogues in simulation) may not be sufficient for (...)
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  • Two Styles of Reasoning in Scientific Practices: Experimental and Mathematical Traditions.Mieke Boon - 2011 - International Studies in the Philosophy of Science 25 (3):255 - 278.
    This article outlines a philosophy of science in practice that focuses on the engineering sciences. A methodological issue is that these practices seem to be divided by two different styles of scientific reasoning, namely, causal-mechanistic and mathematical reasoning. These styles are philosophically characterized by what Kuhn called ?disciplinary matrices?. Due to distinct metaphysical background pictures and/or distinct ideas of what counts as intelligible, they entail distinct ideas of the character of phenomena and what counts as a scientific explanation. It is (...)
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  • Studying Justificatory Practice: An Attempt to Integrate the History and Philosophy of Science.Jutta Schickore - 2009 - International Studies in the Philosophy of Science 23 (1):85-107.
    In recent years there has been a revival of the debate about the relation between history and philosophy of science. This article seeks to contribute to the discussion by approaching the issue from a new angle. To rethink the relation between the two domains of study, I apply an important insight about scientific practice to the practice of integrating the history and philosophy of science: the insight that the scientific paper does not give a faithful account of the actual research (...)
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  • The Phenomena of Homology.Paul Edmund Griffiths - 2007 - Biology and Philosophy 22 (5):643-658.
    Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...)
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  • Coherence: Beyond Constraint Satisfaction.Gareth Gabrys & Alan Lesgold - 1989 - Behavioral and Brain Sciences 12 (3):475-475.
  • What's in a Link?Jerome A. Feldman - 1989 - Behavioral and Brain Sciences 12 (3):474-475.
  • Thagard's Principle 7 and Simpson's Paradox.Robyn M. Dawes - 1989 - Behavioral and Brain Sciences 12 (3):472-473.
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  • Assimilating Evidence: The Key to Revision?Michelene T. H. Chi - 1989 - Behavioral and Brain Sciences 12 (3):470-471.
  • Explanatory Coherence as a Psychological Theory.P. C.-H. Cheng & M. Keane - 1989 - Behavioral and Brain Sciences 12 (3):469-470.
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  • When Weak Explanations Prevail.Carl Bereiter & Marlene Scardamalia - 1989 - Behavioral and Brain Sciences 12 (3):468-469.
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  • Psychology, or Sociology of Science?N. E. Wetherick - 1989 - Behavioral and Brain Sciences 12 (3):489-489.
  • Measuring the Plausibility of Explanatory Hypotheses.James A. Reggia - 1989 - Behavioral and Brain Sciences 12 (3):486-487.
  • Explanatory Coherence in Understanding Persons, Interactions, and Relationships.Stephen J. Read & Lynn C. Miller - 1989 - Behavioral and Brain Sciences 12 (3):485-486.
  • Probability and Normativity.David Papineau - 1989 - Behavioral and Brain Sciences 12 (3):484-485.
  • Explanatory Coherence in Neural Networks?Daniel S. Levine - 1989 - Behavioral and Brain Sciences 12 (3):479-479.
  • Inference to the Best Explanation is Basic.John R. Josephson - 1989 - Behavioral and Brain Sciences 12 (3):477-478.
  • Are Explanatory Coherence and a Connectionist Model Necessary?Jerry R. Hobbs - 1989 - Behavioral and Brain Sciences 12 (3):476-477.
  • What Does Explanatory Coherence Explain?Ronald N. Giere - 1989 - Behavioral and Brain Sciences 12 (3):475-476.
  • Epistemologically Authentic Inquiry in Schools: A Theoretical Framework for Evaluating Inquiry Tasks.Clark A. Chinn & Betina A. Malhotra - 2002 - Science Education 86 (2):175-218.
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  • A Visible Hand in the Marketplace of Ideas: Precision Measurement as Arbitage.Philip Mirowski - 1994 - Science in Context 7 (3):563-589.
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  • Calibration of Laboratory Models in Population Genetics.Robert Skipper - 2004 - Perspectives on Science 12 (4):369-393.
    : This paper explores the calibration of laboratory models in population genetics as an experimental strategy for justifying experimental results and claims based upon them following Franklin (1986, 1990) and Rudge (1996, 1998). The analysis provided undermines Coyne et al.'s (1997) critique of Wade and Goodnight's (1991) experimental study of Wright's (1931, 1932) Shifting Balance Theory. The essay concludes by further demonstrating how this analysis bears on Diamond's (1986) claims regarding the weakness of laboratory experiments as evidence, and further how (...)
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  • Sanctioning Models: The Epistemology of Simulation.Eric Winsberg - 1999 - Science in Context 12 (2):275-292.
  • Going Outside the Model: Robustness Analysis and Experimental Science.Michael Trevor Bycroft - 2009 - Spontaneous Generations 3 (1):123-141.
    In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper de?nition and (...)
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  • Two Ways to Rule Out Error: Severity and Security.Kent Staley - unknown
    I contrast two modes of error-elimination relevant to evaluating evidence in accounts that emphasize frequentist reliability. The contrast corresponds to that between the use of of a reliable inference procedure and the critical scrutiny of a procedure with regard to its reliability, in light of what is and is not known about the setting in which the procedure is used. I propose a notion of security as a category of evidential assessment for the latter. In statistical settings, robustness theory and (...)
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  • Modeling and Experimenting.Isabelle Peschard - 2009 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge.
    Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is conceptual (...)
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  • Is There a Bayesian Justification of Hypothetico‐Deductive Inference?Samir Okasha & Karim Thébault - forthcoming - Noûs.
    Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico-deductive inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen, we analyze a problem for the putative Bayesian justification of H-D inference in the case where what we learn from observation is logically stronger than what our theory implies. Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient (...)
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  • Re-Thinking Reproducibility as a Criterion for Research Quality.Sabina Leonelli - unknown
    A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a "crisis of reproducibility" to the rise of fraudulent, careless and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit (...)
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