Results for 'Models'

962 found
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  1. Concepts of chaos-the analysis of self-similarity and the relevance of the ethical dimension-a comment on Baker, Gregory, L. a'dualistic model of ultimate reality and meaning-self-similarity in chaotic dynamics and and swedenborg'.Sm Modell - 1994 - Ultimate Reality and Meaning 17 (4):310-315.
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  2. Professor, Water Science and Civil Engineering University of California Davis, California.A. Mathematical Model - 1968 - In Peter Koestenbaum (ed.), Proceedings. [San Jose? Calif.,: [San Jose? Calif.. pp. 31.
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  3. Katsuhiko Sekine.Problème de Cauchy Dans le Modèle & En Métrique de LeeIndéfinie - 1968 - In Jean-Louis Destouches & Evert Willem Beth (eds.), Logic and foundations of science. Dordrecht,: D. Reidel.
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  4. A. lansner1.Neuron Model - 1986 - In G. Palm & A. Aertsen (eds.), Brain Theory. Springer. pp. 249.
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  5. Models, analogies, and theories.Peter Achinstein - 1964 - Philosophy of Science 31 (4):328-350.
    Recent accounts of scientific method suggest that a model, or analogy, for an axiomatized theory is another theory, or postulate set, with an identical calculus. The present paper examines five central theses underlying this position. In the light of examples from physical science it seems necessary to distinguish between models and analogies and to recognize the need for important revisions in the position under study, especially in claims involving an emphasis on logical structure and similarity in form between theory (...)
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  6. Hubert L. Dreyfus and Stuart E. Dreyfus.Model Of Rationality - 1978 - In A. Hooker, J. J. Leach & E. F. McClennen (eds.), Foundations and Applications of Decision Theory: Vol.II: Epistemic and Social Applications. D. Reidel. pp. 115.
  7.  58
    Imagination and the Meaningful Brain.Arnold H. Modell - 2003 - Bradford Book/MIT Press.
    " In Imagination and the Meaningful Brain, psychoanalyst Arnold Modell claims that subjective human experience must be included in any scientific...
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  8. Reflections on DNA: The contribution of genetics to an energy-based model of ultimate reality and meaning.Stephen M. Modell - 2002 - Ultimate Reality and Meaning 25 (4):274-294.
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  9.  94
    Genetic and reproductive technologies in the light of religious dialogue.Stephen M. Modell - 2007 - Zygon 42 (1):163-182.
    Abstract.Since the gene splicing debates of the 1980s, the public has been exposed to an ongoing sequence of genetic and reproductive technologies. Many issue areas have outcomes that lose track of people's inner values or engender opposing religious viewpoints defying final resolution. This essay relocates the discussion of what is an acceptable application from the individual to the societal level, examining technologies that stand to address large numbers of people and thus call for policy resolution, rather than individual fiat, in (...)
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  10.  7
    Philosophical-Scientific Musings on the Ultimate Nature of Synchronistic Events and Their Meaning.Stephen M. Modell - 2021 - Ultimate Reality and Meaning 38 (1-2):50-72.
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  11.  88
    Aristotelian Influence in the Formation of Medical Theory.Stephen M. Modell - 2010 - The European Legacy 15 (4):409-424.
    Aristotle is oftentimes viewed through a strictly philosophical lens as heir to Plato and has having introduced logical rigor where an emphasis on the theory of Forms formerly prevailed. It must be appreciated that Aristotle was the son of a physician, and that his inculcation of the thought of other Greek philosophers addressing health and the natural elements led to an extremely broad set of biologically- and medically-related writings. As this article proposes, Aristotle deepened the fourfold theory of the elements (...)
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  12.  56
    Approaching Religious Guidelines for Chimera Policymaking.Stephen M. Modell - 2007 - Zygon 42 (3):629-642.
  13.  21
    Frieden und Krieg. Zur Hegel-Auslegung Emmanuel Lévinas.Anselm Model - 2007 - Hegel-Jahrbuch 2007 (1).
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  14.  23
    Female sexuality, mockery, and a challenge to fate: A reinterpretation of South Nayar talikettukalyanam.Judith Modell - 1984 - Semiotica 50 (3-4).
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  15. Naturalizing relational psychoanalytic theory.Arnold Modell - 2009 - In Roger Frie & Donna M. Orange (eds.), Beyond Postmodernism: New Dimensions in Theory and Practice. Routledge.
  16. Energy, information, and emergence in the context of ultimate reality and meaning.Alexander A. Berezin, Stephen M. Modell, Louise Sundarajan & Siti Salamah Pope - 2002 - Ultimate Reality and Meaning 25 (4):256-273.
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  17.  72
    Connectionist Models and Their Properties.J. A. Feldman & D. H. Ballard - 1982 - Cognitive Science 6 (3):205-254.
    Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence (...)
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  18.  31
    Evaluating models of consent in changing health research environments.Svenja Wiertz & Joachim Boldt - 2022 - Medicine, Health Care and Philosophy 25 (2):269-280.
    While Specific Informed Consent has been the established standard for obtaining consent for medical research for many years, it does not appear suitable for large-scale biobank and health data research. Thus, alternative forms of consent have been suggested, based on a variety of ethical background assumptions. This article identifies five main ethical perspectives at stake. Even though Tiered Consent, Dynamic Consent and Meta Consent are designed to the demands of the self-determination perspective as well as the perspective of research as (...)
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  19. (1 other version)Models and fiction.Roman Frigg - 2007 - Synthese 172 (2):251-268.
    Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on (...)
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  20. Models of the Self.Galen Strawson - 2002 - Thorverton UK: Imprint Academic.
     
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  21.  33
    Formal Models at the Core.Emmanuel Chemla, Isabelle Charnavel, Isabelle Dautriche, David Embick, Fred Lerdahl, Pritty Patel-Grosz, David Poeppel & Philippe Schlenker - 2023 - Cognitive Science 47 (3):e13267.
    The grammatical paradigm used to be a model for entire areas of cognitive science. Its primary tenet was that theories are axiomatic-like systems. A secondary tenet was that their predictions should be tested quickly and in great detail with introspective judgments. While the grammatical paradigm now often seems passé, we argue that in fact it continues to be as efficient as ever. Formal models are essential because they are explicit, highly predictive, and typically modular. They make numerous critical predictions, (...)
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  22. Etiological models in psychiatry : reductive and nonreductive approaches.Kenneth F. Schaffner - 2008 - In Kenneth S. Kendler & Josef Parnas (eds.), Philosophical Issues in Psychiatry: Explanation, Phenomenology, and Nosology. Baltimore: Johns Hopkins University Press.
  23. Models for Modalities.Jaakko Hintikka - 1971 - Studia Logica 28:161-163.
     
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  24.  78
    Models of data.Patrick Suppes - 2009 - In Ernest Nagel, Patrick Suppes & Alfred Tarski (eds.), Provability, Computability and Reflection. Stanford, CA, USA: Elsevier.
  25. Models and fictions in science.Peter Godfrey-Smith - 2009 - Philosophical Studies 143 (1):101 - 116.
    Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.
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  26. When scientific models represent.Daniela M. Bailer-Jones - 2003 - International Studies in the Philosophy of Science 17 (1):59 – 74.
    Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit (...)
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  27. Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  28.  20
    Saturated models of first-order many-valued logics.Guillermo Badia & Carles Noguera - 2022 - Logic Journal of the IGPL 30 (1):1-20.
    This paper is devoted to the problem of existence of saturated models for first-order many-valued logics. We consider a general notion of type as pairs of sets of formulas in one free variable that express properties that an element of a model should, respectively, satisfy and falsify. By means of an elementary chains construction, we prove that each model can be elementarily extended to a $\kappa $-saturated model, i.e. a model where as many types as possible are realized. In (...)
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  29.  48
    Scientific Problems: Three Empiricist Models.Thomas Nickles - 1980 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1980:3 - 19.
    One component of a viable account of scientific inquiry is a defensible conception of scientific problems. This paper specifies some logical and conceptual requirements that an acceptable account of scientific problems must meet as well as indicating some features that a study of scientific inquiry indicates scientific problems have. On the basis of these requirements and features, three standard empiricist models of problems are examined and found wanting. Finally a constraint inclusion-model of scientific problems is proposed.
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  30.  32
    Information Models in Physics.G. B. Zhdanov - 1964 - Russian Studies in Philosophy 3 (3):54-57.
    In the article "The Epistemological Nature of Information Modeling" [Gnoseologicheskaia priroda informatsionnogo modelirovaniia], Voprosy filosofii, 1963, No. 10, Academician V. M. Glushkov examines two important methodological aspects of the modeling of natural objects and phenomena in the contemporary natural sciences. The first consists of the informational nature of the models created, and the second of their dynamism. The dynamic nature of today's models in the natural sciences means that it is not so much the material structure of the (...)
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  31. Models, Representation, and Mediation.Tarja Knuuttila - 2005 - Philosophy of Science 72 (5):1260-1271.
    Representation has been one of the main themes in the recent discussion of models. Several authors have argued for a pragmatic approach to representation that takes users and their interpretations into account. It appears to me, however, that this emphasis on representation places excessive limitations on our view of models and their epistemic value. Models should rather be thought of as epistemic artifacts through which we gain knowledge in diverse ways. Approaching models this way stresses their (...)
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  32. The genetic recombination of science and religion.Stephen M. Modell - 2010 - Zygon 45 (2):462-468.
    The estrangement between genetic scientists and theologians originating in the 1960s is reflected in novel combinations of human thought (subject) and genes (investigational object), paralleling each other through the universal process known in chaos theory as self-similarity. The clash and recombination of genes and knowledge captures what Philip Hefner refers to as irony, one of four voices he suggests transmit the knowledge and arguments of the religion-and-science debate. When viewed along a tangent connecting irony to leadership, journal dissemination, and the (...)
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  33. Which Models of Scientific Explanation Are (In)Compatible with Inference to the Best Explanation?Yunus Prasetya - 2024 - British Journal for the Philosophy of Science 75 (1):209-232.
    In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s erotetic (...)
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  34. Definitions of trauma.Dissociated Trauma Model - 2002 - In Kelly Oliver & Steve Edwin (eds.), Between the psyche and the social: psychoanalytic social theory. Lanham, Md.: Rowman & Littlefield.
     
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  35. The Search for Deeper Meaning in the Life Sciences.Stephen M. Modell - 2008 - Ultimate Reality and Meaning 31 (2-3):160-182.
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  36. Models, Mechanisms, and Coherence.Matteo Colombo, Stephan Hartmann & Robert van Iersel - 2015 - British Journal for the Philosophy of Science 66 (1):181-212.
    Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...)
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  37. Models of language learning and their implications for social constructionist analyses of scientific belief.Donald T. Campbell - 1989 - In Steve Fuller (ed.), The Cognitive turn: sociological and psychological perspectives on science. Boston: Kluwer Academic Publishers.
  38. Probabilistic models of cognition: Conceptual foundations.Nick Chater & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):287-291.
    Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, (...)
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  39. Models and Explanation.Alisa Bokulich - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 103-118.
    Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...)
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  40. Hagiographic models of worship of images and angels.Glenn Peers - 1997 - Byzantion 67 (2):407-420.
    L'assimilation des images à une attitude chrétienne correcte fut le résultat d'un long débat sur la nature du culte chrétien. Les icones n'excluaient pas d'autres approches comme la vertu chrétienne , mais elles faisaient désormais partie inextricablement d'une éthique chrétienne complète. Les hagiographies de Théodore Stoudite, de Photios, de Nicéphore ont contribué à la diffusion du culte des images comme une pratique chrétienne acceptable. L'exemple miraculeux de Michel au sanctuaire d'Eusèbe intervient également dans la mise en place d'un consensus.
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  41. Models of Distance Education for Composition: The Role of Interactive Video Conferencing.Dawn Rodrigues - 1998 - Kairos (Université de Toulouse-Le Mirail. Faculté de philosophie) 3 (2).
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  42.  1
    (1 other version)Models in science.Edward N. Zalta - 2012 - In Ed Zalta (ed.), Stanford Encyclopedia of Philosophy. Stanford, CA: Stanford Encyclopedia of Philosophy.
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  43.  29
    Computational models of semantic memory.T. Rogers - 2008 - In Ron Sun (ed.), The Cambridge handbook of computational psychology. New York: Cambridge University Press. pp. 226--266.
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  44.  60
    Models of Competence in Solving Physics Problems.Jill H. Larkin, John McDermott, Dorothea P. Simon & Herbert A. Simon - 1980 - Cognitive Science 4 (4):317-345.
    We describe a set of two computer‐implemented models that solve physics problems in ways characteristic of more and less competent human solvers. The main features accounting for different competences are differences in strategy for selecting physics principles, and differences in the degree of automation in the process of applying a single principle. The models provide a good account of the order in which principles are applied by human solvers working problems in kinematics and dynamics. They also are sufficiently (...)
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  45.  80
    Models as Felicitous Falsehoods.Catherine Elgin - 2022 - Principia: An International Journal of Epistemology 26 (1):7-23.
    I argue that models enable us to understand reality in ways that we would be unable to do if we restricted ourselves to the unvarnished truth. The point is not just that the features that a model skirts can permissibly be neglected. They ought to be neglected. Too much information occludes patterns that figure in an understanding of the phenomena. The regularities a model reveals are real and informative. But many of them show up only under idealizing assumptions.
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  46.  43
    Exploring Models for an International Legal Agreement on the Global Antimicrobial Commons: Lessons from Climate Agreements.Susan Rogers Van Katwyk, Alberto Giubilini, Claas Kirchhelle, Isaac Weldon, Mark Harrison, Angela McLean, Julian Savulescu & Steven J. Hoffman - 2023 - Health Care Analysis 31 (1):25-46.
    An international legal agreement governing the global antimicrobial commons would represent the strongest commitment mechanism for achieving collective action on antimicrobial resistance (AMR). Since AMR has important similarities to climate change—both are common pool resource challenges that require massive, long-term political commitments—the first article in this special issue draws lessons from various climate agreements that could be applicable for developing a grand bargain on AMR. We consider the similarities and differences between the Paris Climate Agreement and current governance structures for (...)
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  47.  38
    Models of Brain Function.Rodney M. J. Cotterill (ed.) - 1989 - Cambridge University Press.
    This is an exciting time for brain science. Recent progress has been such that it now seems realistic to look toward an explanation of mind in terms of the brain's anatomy and physiology. Models based on artificially symmetrical arrays of idealized neurons are now being superseded by ones which properly take into account the brain's actual circuitry. This book presents a comprehensive overview of the current state of brain modeling, containing contributions from many leading researchers in this field. It (...)
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  48. Models of Success Versus the Success of Models: Reliability without Truth.Eric Winsberg - 2006 - Synthese 152 (1):1-19.
    In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model (...)
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  49. Models of God and Alternative Ultimate Realities.Jeanine Diller & Asa Kasher (eds.) - 2013 - Springer.
    James E. Taylor As the title of this book makes clear, the essays contained in it are unified by their focus on models of God and alternative ultimate realities. But what is ultimate reality, what does 'God' mean, and what would count as a model ...
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  50. Sanctioning Models: The Epistemology of Simulation.Eric Winsberg - 1999 - Science in Context 12 (2):275-292.
    The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the (...)
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