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Nature and the Greeks

Cambridge [Eng.]: University Press. Edited by Erwin Schrödinger (1951)

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  1. Erwin Schrödinger’s Poetry.Tzveta Sofronieva - 2014 - Science & Education 23 (3):655-672.
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  • Explanation and the Nature of Scientific Knowledge.Kevin McCain - 2015 - Science & Education 24 (7-8):827-854.
    Explaining phenomena is a primary goal of science. Consequently, it is unsurprising that gaining a proper understanding of the nature of explanation is an important goal of science education. In order to properly understand explanation, however, it is not enough to simply consider theories of the nature of explanation. Properly understanding explanation requires grasping the relation between explanation and understanding, as well as how explanations can lead to scientific knowledge. This article examines the nature of explanation, its relation to understanding, (...)
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  • The strategy of optimality revisited.Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):237-245.
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  • Optimal confusion.Stephanie Stolarz-Fantino & Edmund Fantino - 1991 - Behavioral and Brain Sciences 14 (2):234-234.
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  • Optimality as a prescriptive tool.Alexander H. G. Rinnooy Kan - 1991 - Behavioral and Brain Sciences 14 (2):230-231.
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  • Rational agents, real people and the quest for optimality.Eldar Shafir - 1991 - Behavioral and Brain Sciences 14 (2):232-232.
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  • Extremum descriptions, process laws and minimality heuristics.Elliott Sober - 1991 - Behavioral and Brain Sciences 14 (2):232-233.
    The examples and concepts that Shoemaker cites are rather heterogeneous. Some distinctions need to be drawn. An optimality thesis involves not just an ordering of options, but a value judgment about them. So let us begin by distinguishing minimality from optimality. And the concept of minimality can play a variety of roles, among which I distinguish between extremum descriptions, statements hypothesizing an optimizing process, and methodological recommendations. Finally, I consider how the three categories relate to Shoemaker’s question that “Who is (...)
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  • Avoid the push-pull dilemma in explanation.Kenneth M. Steele - 1991 - Behavioral and Brain Sciences 14 (2):233-234.
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  • The infinite regress of optimization.Philippe Mongin - 1991 - Behavioral and Brain Sciences 14 (2):229-230.
    A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.
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  • Vaulting optimality.Peter Dayan & Jon Oberlander - 1991 - Behavioral and Brain Sciences 14 (2):221-222.
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  • Optimality and human memory.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (2):215-216.
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  • Where Epistemology and Religion Meet What do(es) the god(s) look like?Maria Michela Sassi - 2013 - Rhizomata 1 (2):283-307.
    The focus of this essay is on Xenophanes’ criticism of anthropomorphic representation of the gods, famously sounding like a declaration of war against a constituent part of the Greek religion, and adopting terms and a tone that are unequalled amongst “pre-Socratic” authors for their directness and explicitness. While the main features of Xenophanes’ polemic are well known thanks to some of the most studied fragments of the pre-Socratic tradition, a different line of enquiry from the usual one is attempted by (...)
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  • Founding Quantum Theory on the Basis of Consciousness.Efstratios Manousakis - 2006 - Foundations of Physics 36 (6):795-838.
    In the present work, quantum theory is founded on the framework of consciousness, in contrast to earlier suggestions that consciousness might be understood starting from quantum theory. The notion of streams of consciousness, usually restricted to conscious beings, is extended to the notion of a Universal/Global stream of conscious flow of ordered events. The streams of conscious events which we experience constitute sub-streams of the Universal stream. Our postulated ontological character of consciousness also consists of an operator which acts on (...)
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  • The problem of other minds: A debate between schrödinger and Carnap. [REVIEW]Michel Bitbol - 2004 - Phenomenology and the Cognitive Sciences 3 (1):115-123.
    This paper reviews the debate between Carnap and Schrödinger about Hypothesis P (It is not only I who have perceptions and thoughts; other human beings have them too)–a hypothesis that underlies the possibility of doing science. For Schrödinger this hypothesis is not scientifically testable; for Carnap it is. But Schrödinger and Carnap concede too much to each other and miss an alternative understanding: science does not depend on an explicit hypothesis concerning what other human beings see and think; it is (...)
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  • Guidelines for authors.[author unknown] - 2018 - Scientia et Fides 6 (1):339-344.
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  • The quest for plausibility: A negative heuristic for science?R. W. Byrne - 1991 - Behavioral and Brain Sciences 14 (2):217-218.
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  • Merleau-Ponty’s Phenomenology as a Hermeneutic Framework for Quantum Mechanics.Leonardo Colletti & Pablo Pellegrini - 2020 - Axiomathes 30 (1):49-68.
    We propose a synthetic description of Merleau-Ponty’s phenomenology with the aim of providing physicists and philosophers with an alternative linguistic and conceptual framework to address the logical and ontological problematics emerged in quantum mechanics. Phenomenology’s cognitive devices such as the dynamical relationship between object and horizon, the presumptive synthesis and the constitution of an ontology based on the indivisibility of object and subject, not only show hermeneutic efficacy when applied to the study of human perception, but may prove to be (...)
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  • The Universe as a Computer Game, from Virtual to Actual Reality.Alfred Driessen - 2018 - Scientia et Fides 6 (1):31-52.
    From the very beginning of ancient Greek philosophy up to the present day a puzzling correlation is found between rationality and reality. In this study this relation is examined with emphasis on the philosophical tradition of Aristotle and Aquinas. A comparison is made with the virtual reality created by computers and actual reality of our universe. The view expressed in the scientific neopositivism of Jordan and Mach is found to be an adequate approach to avoid contradictions in the interpretation of (...)
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  • Esencia y causas en y a través de los movimientos naturales. Desde Aristóteles y en diálogo con Alicia Juarrero.Miguel Martí Sánchez - 2014 - Scientia et Fides 2 (2):67-92.
    Essence and causes in and through the movements in Nature. From Aristotle and in dialogue with Alicia Juarrero: According to Aristotle there is an intrinsic relation between ordinary language, logic and ontology, which is a key element for the knowledge of reality. Such a relation is applied by the Stagirite in the sphere of nature as support for the analysis made by the incipient natural sciences of his time. Thus, Aristotle provided a unitary conception of nature and the sciences which (...)
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  • Overturning Dilthey's view on natural sciences.Leonardo Colleti - 2014 - Epistemologia 37 (2):202-216.
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  • Commentary on Long.Stanley Rosen - 1996 - Proceedings of the Boston Area Colloquium of Ancient Philosophy 12 (1):152-162.
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  • Is economics still immersed in the old concepts of the Enlightenment era?Andrzej P. Wierzbicki - 1991 - Behavioral and Brain Sciences 14 (2):236-237.
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  • The human being as a bumbling optimalist: A psychologist's viewpoint.Masanao Toda - 1991 - Behavioral and Brain Sciences 14 (2):235-235.
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  • Should the quest for optimality worry us?Nils-Eric Sahlin - 1991 - Behavioral and Brain Sciences 14 (2):231-231.
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  • Don't just sit there, optimise something.J. H. P. Paelinck - 1991 - Behavioral and Brain Sciences 14 (2):230-230.
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  • Complexity and optimality.Dauglas A. Miller & Steven W. Zucker - 1991 - Behavioral and Brain Sciences 14 (2):227-228.
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  • Two dynamic criteria for validating claims of optimality.Geoffrey F. Miller - 1991 - Behavioral and Brain Sciences 14 (2):228-229.
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  • The example of psychology: Optimism, not optimality.Daniel S. Levine - 1991 - Behavioral and Brain Sciences 14 (2):225-226.
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  • Straining the word “optimal”.James E. Mazur - 1991 - Behavioral and Brain Sciences 14 (2):227-227.
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  • Natural science, social science and optimality.Oleg Larichev - 1991 - Behavioral and Brain Sciences 14 (2):224-225.
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  • Why optimality is not worth arguing about.Stephen E. G. Lea - 1991 - Behavioral and Brain Sciences 14 (2):225-225.
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  • Optimality and constraint.David A. Helweg & Herbert L. Roitblat - 1991 - Behavioral and Brain Sciences 14 (2):222-223.
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  • Types of optimality: Who is the steersman?Michael E. Hyland - 1991 - Behavioral and Brain Sciences 14 (2):223-224.
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  • Natural selection doesn't have goals, but it's the reason organisms do.Martin Daly - 1991 - Behavioral and Brain Sciences 14 (2):219-220.
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  • Organisms, scientists and optimality.Michael Davison - 1991 - Behavioral and Brain Sciences 14 (2):220-221.
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  • Criteria for optimality.Michel Cabanac - 1991 - Behavioral and Brain Sciences 14 (2):218-218.
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  • Some optimality principles in evolution.James F. Crow - 1991 - Behavioral and Brain Sciences 14 (2):218-219.
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  • Optimality as a mathematical rhetoric for zeroes.Fred L. Bookstein - 1991 - Behavioral and Brain Sciences 14 (2):216-217.
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  • Optimality as an evaluative standard in the study of decision-making.Jonathan Baron - 1991 - Behavioral and Brain Sciences 14 (2):216-216.
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  • The quest for optimality: A positive heuristic of science?Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):205-215.
    This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples;optimalityis used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the extreme flexibility of (...)
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  • Signs, chaos, life.Floyd Merrell - 2002 - Semiotica 2002 (138).
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  • Defending Realism: Reflections on Karl Rogers's Metaphysics of Experimental Physics.John Spencer - 2007 - Journal of Critical Realism 6 (1):126-147.
    The main goal of this paper is to argue against Karl Rogers's attacks on realism in physics. Rogers argues that electrons do not exist independently of the relevant socio-technological process, but I show that such an assumption would make our best scientific theories incomprehensible. While the paper supports Rogers's attempts to refute positivism, it demonstrates that his own position is positivistic, and it corrects his overemphasis on the roles of technology and the experimenter. Rogers assumes that the founders of modern (...)
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  • Natural Food and the Pastoral: A Sentimental Notion? [REVIEW]Donald B. Thompson - 2011 - Journal of Agricultural and Environmental Ethics 24 (2):165-194.
    The term natural is effective in the marketing of a wide variety of foods. This ambiguous term carries important meaning in Western culture. To challenge an uncritical understanding of natural with respect to food and to explore the ambiguity of the term, the development of Western ideas of nature is first discussed. Personification and hypostasization of nature are given special emphasis. Leo Marx’s idea of the pastoral design in literature is then used to explore the meaning of natural as applied (...)
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  • The origins and governance of complex social systems.Robert Artigiani - 2004 - World Futures 60 (8):593 – 616.
    The new science of Complexity explains that limited knowledge prevents societies from predicting and controlling their developments. But Complexity further suggests that nature uses the limits of knowledge to evolve, which turns an apparent obstacle into an opportunity to reevaluate governmental institutions. As in nature, the limits of knowledge lead social systems to evolve by individuating, liberating, and empowering their members. Societies individuate and liberate their members to probe environments and exploit opportunities. Societies empower individuals to globalize their findings which (...)
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