Aristotle and the Problem of Intentionality1
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On the Several Senses of Being in Aristotle
Franz Brentano ON THE SEVERAL SENSES OF BEING IN ARISTOTLE To OJ) A€'YETaL 7/'OAAaxW~ Aristotle, Metaphysics Z, 1 Edited and Translated ~ Rolf George UNIVERSITY OF CALIFORNIA PRESS Berkeley Los Angeles London 1975 Dedicated in veneration and gratitude to DR. ADOLPH TRENDELENBURG Professor of Philosophy at the University of Berlin My most revered teacher, UNIVERSITY OF CALIFORNIA PRESS the scholar so highly distinguished BERKELEY AND LOS ANGELES in the advancement of our understanding of Aristotle. UNIVERSITY OF CALIFORNIA PRESS, LTD. LONDON, ENGLAND COPYRIGHT © 1975 BY THE REGENTS OF THE UNIVERSITY OF CALIFORNlA ISBN: o-52()'()2346-3 LIBRARY OF CONGRESS CATALOG CARD NUMBER: 72-89796 PRINTED IN THE UNITED STATES OF AMERICA Contents Editor's Preface . .. xi Preface ..................................... xv Introduction ................................. Chapter I. The Fourfold Distinction of Being. .. 3 Being is a homonym. Its several senses fit into the fourfold distinction of accidental being, being in the sense of being true, being of the categories, and potential and actual being. • . 3 Chapter II. Accidental Being . 6 Chapter III. Being in the Sense of Being True . 15 § 1. Of the true and the false . • • . • . .•. 1 5 § 2. Of the true and the false when considered in relation to the concept of being in the sense of being true and of non-being in the sense of being false . • . • . 22 Chapter IV. Potential and Actual Being . .. 27 § 1. The kind of being which is divided into actual and potential is being in the sense in which this name .is applied not only to that which is realized, that which exists, the really-being, but also to the mere real possibility of being. -
Block.What.Psch.States.Not.1972.Pdf
Philosophical Review What Psychological States are Not Author(s): N. J. Block and J. A. Fodor Source: The Philosophical Review, Vol. 81, No. 2 (Apr., 1972), pp. 159-181 Published by: Duke University Press on behalf of Philosophical Review Stable URL: http://www.jstor.org/stable/2183991 Accessed: 08/09/2009 16:04 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=duke. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We work with the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact [email protected]. Duke University Press and Philosophical Review are collaborating with JSTOR to digitize, preserve and extend access to The Philosophical Review. -
Causal Inference with Information Fields
Causal Inference with Information Fields Benjamin Heymann Michel De Lara Criteo AI Lab, Paris, France CERMICS, École des Ponts, Marne-la-Vallée, France [email protected] [email protected] Jean-Philippe Chancelier CERMICS, École des Ponts, Marne-la-Vallée, France [email protected] Abstract Inferring the potential consequences of an unobserved event is a fundamental scientific question. To this end, Pearl’s celebrated do-calculus provides a set of inference rules to derive an interventional probability from an observational one. In this framework, the primitive causal relations are encoded as functional dependencies in a Structural Causal Model (SCM), which maps into a Directed Acyclic Graph (DAG) in the absence of cycles. In this paper, by contrast, we capture causality without reference to graphs or functional dependencies, but with information fields. The three rules of do-calculus reduce to a unique sufficient condition for conditional independence: the topological separation, which presents some theoretical and practical advantages over the d-separation. With this unique rule, we can deal with systems that cannot be represented with DAGs, for instance systems with cycles and/or ‘spurious’ edges. We provide an example that cannot be handled – to the extent of our knowledge – with the tools of the current literature. 1 Introduction As the world shifts toward more and more data-driven decision-making, causal inference is taking more space in applied sciences, statistics and machine learning. This is because it allows for better, more robust decision-making, and provides a way to interpret the data that goes beyond correlation Pearl and Mackenzie [2018]. -
The Alleged Activity of Active Intellect: a Wild Goose Chase Or a Puzzle to Be Solved?1
The alleged activity of active intellect: A wild goose chase or a puzzle to be solved?1 Sonia Kamińska Summary Trying to describe the activity of Aristotle’s active intellect, we will sooner or later realize that we cannot find its right description, because Aristotle did not provide for one. He left us with many ir- reconcilable statements and questions with no answers. In the fa- | LIV • 2014 w Nauce Zagadnienia Filozoficzne mous text Aristotle’s Two Intellects: a Modest Proposal Victor Cas- ton claims that Aristotle did not describe the activity, because there simply is no such activity and we should therefore identify nous poietikos with God, because God too does nothing. Trying to find this lacking description is like going on a wild goose chase – Caston argues. In my text I will show that his solution, albeit tempting, is in fact a kind of “dissolution” and that a wild goose chase, although for many doomed to failure, can be fruitful. I will do so by present- ing three groups or clusters of views on active intellect which – I believe – are philosophically significant. Caston’s proposal will be 1 �����������������������������������������������������������������This publication was supported by Copernicus Center for Interdis- ciplinary Studies under grant "The Limits of Scientific Explanation" founded by the John Templeton Foundation. 79 Sonia Kamińska one of them, but not the privileged one. These three types of inter- pretations will hopefully provide us with an imagery that will help us somewhat come to terms with Aristotle’s succinctness. Keywords nous, nous poietikos, nous pathetikos, soul, intellect, God, Deity, actuality, potentiality, philosophy of mind, Aristotle, Thomas Aqui- nas, Franz Brentano, Victor Caston 1. -
A Difference-Making Account of Causation1
A difference-making account of causation1 Wolfgang Pietsch2, Munich Center for Technology in Society, Technische Universität München, Arcisstr. 21, 80333 München, Germany A difference-making account of causality is proposed that is based on a counterfactual definition, but differs from traditional counterfactual approaches to causation in a number of crucial respects: (i) it introduces a notion of causal irrelevance; (ii) it evaluates the truth-value of counterfactual statements in terms of difference-making; (iii) it renders causal statements background-dependent. On the basis of the fundamental notions ‘causal relevance’ and ‘causal irrelevance’, further causal concepts are defined including causal factors, alternative causes, and importantly inus-conditions. Problems and advantages of the proposed account are discussed. Finally, it is shown how the account can shed new light on three classic problems in epistemology, the problem of induction, the logic of analogy, and the framing of eliminative induction. 1. Introduction ......................................................................................................................................................... 2 2. The difference-making account ........................................................................................................................... 3 2a. Causal relevance and causal irrelevance ....................................................................................................... 4 2b. A difference-making account of causal counterfactuals -
Chapter 7 Mental Representation Mental Representation
Chapter 7 Mental Representation Mental Representation Mental representation is a systematic correspondence between some element of a target domain and some element of a modeling (or representation) domain. A representation, whether it be mental or any other, is a system of symbols. The system of symbols is isomorphic to another system (the represented system) so that conclusions drawn through the processing of the symbols in the representing system constitute valid inferences about the represented system. Isomorphic means `having the same form.' The following figure is a typical example of how we represent information mentally in our minds. Figure 8.12 A hierarchical network representation of concepts. Source: Collins and Quillian (1969) The cognitive psychologists have always agreed on the fact that human information processing depends on the mental representation of information; but there is a great disagreement with regard to the nature of this mental representation of information. Symbols are the representations that are amodal. They bear no necessary resemblance to the concept or percept they represent. The systematic correspondence between the two domains may be a matter of convention (only). For example, in algebra, we denote the different variables as x, y, z, and so on, but neither of these symbols have a direct resemblance to what they represent. Similarly, while solving a geometrical problem involving geometrical shapes, we might assign symbols such as A, B, or C to such geometrical shapes, even though these symbols do not have a direct resemblance to the shapes. Images are another way how the information can be represented in our minds. Images are basically representations that resemble what they represent in some non-arbitrary way. -
Benjamin Miller.Master CV.Updated 10232020 Copy
Benjamin Miller CONTACT Department of Political Science Phone: + .. INFORMATION David Kinley Hall, MC- Email: [email protected] W. Gregory Drive Site: pol.illinois.edu/people/bm Urbana, IL ACADEMIC UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN APPOINTMENTS Assistant Professor, Department of Political Science -present Assistant Professor, Department of Philosophy () -present Assistant Professor, Department of Classics () -present Assistant Professor, European Union Center () -present Unit for Criticism & Interpretive Theory () -present Visiting Assistant Professor, Department of Political Science - CARLOS III JUAN MARCH INSTITUTE (Madrid, Spain) Visiting Research Scholar, Research and Postgraduate Centre in Social - Sciences NOTRE DAME DE NAMUR UNIVERSITY (Belmont, California) Lecturer, Department of Philosophy & Religion Studies - EDUCATION STANFORD UNIVERSITY Ph.D., Philosophy Areas of Specialization: Ancient Greek, Ethics & Political Philosophy Committee: Chris Bobonich, Alan Code, Josiah Ober, Eamonn Callan M.A., Graduate College of Education UNIVERSITY OF AUCKLAND M.A., Philosophy (first class honours) NORTHEASTERN UNIVERSITY B.S., Philosophy (magna cum laude) B.S., Psychology (magna cum laude) PUBLICATIONS . Miller, B. (forthcoming). Virtue, Knowledge, and Political Instability in Aristotle’s Politics: Lessons from the Eudemian Ethics. Polis. Miller, B. (). What Open-Mindedness Requires from Us. Educational Theory, (). Miller, B. (). Aristotle on citizenship and education: the central role of political participation. In A. Peterson, -
Magic, Semantics, and Putnam's Vat Brains
Published in Studies in History and Philosophy of Science (««) t: [email protected] ;–tE. doi:10.1016/j.shpsc.2004.03.007 Magic, semantics, and Putnam’s vat brains Mark Sprevak Christina McLeish University of Edinburgh University of Cambridge Ït March «« In this paper we oòer an exegesis of Hilary Putnam’s classic argument against the brain-in-a-vat hypothesis oòered in his Reason, Truth and History (ÏÊÏ). In it, Putnam argues that we cannot be brains in a vat because the semantics of the situation make it incoherent for anyone to wonder whether they are a brain a vat.Putnam’s argument is that in order for ‘I am a brain in a vat’ to be true, the person uttering it would have to be able to refer successfully to those things: the vat, and the envatted brain. Putnam thinks that reference can’t be secured without relevant kinds of causal relations, which, if envatted, the brain would lack, and so, it fails to be able to meaningfully utter ‘I am a brain in a vat’. We consider the implications of Putnam’s arguments for the traditional sceptic. In conclusion, we discuss the role of Putnam’s arguments against the brain in a vat hypothesis in his larger defense of his own internal realism against metaphysical realism. Ï Introduction Consider the possibility, familiar to us in many guises, that instead of being a living breathing human, you are a brain in a vat. Almost everything that you believe about the external world is false. Your body, your friends, your family, your home—none of these things exist. -
Malcolm Cameron Wilson
1 MALCOLM CAMERON WILSON Department of Classics University of Oregon Eugene, OR, 97403 541-346-4155 Academic Positions 2000- Associate Professor, Department of Classics, University of Oregon 1994-2000. Assistant Professor, Department of Classics, University of Oregon 1990-1994. Adjunct Assistant Professor, Dept. of Classics, University of Oregon Education 1993. Ph.D. (Classics) University of California, Berkeley 1986. M.A. (Classics) University of Toronto, Toronto, Canada 1985. B.A. Hon. (Classics) University of Western Ontario, London, Canada Dissertation: “Aristotle's Theory of Analogy, Focality and Cumulation” (directed by A.A. Long, with John Ferrari and Alan Code) Areas of Specialization: Greek Philosophy, Aristotle, Greek Intellectual History Research: Books Structure and Method in Aristotle’s Meteorologica: A More Disorderly Nature (in production: Cambridge University Press 2013) 2000. Aristotle's Theory of the Unity of Science. University of Toronto Press. Articles and Book Chapters Forthcoming: "The Terrestrial Waters: Aristotle and Olympiodorus" in Topoi Berlin Conference E-proceedings. 2009. “A Somewhat Disorderly Nature: Unity in Aristotle’s Meteorologica” 42.1 Apeiron 42.1 pp.65-88. (peer-reviewed) 2008. “Hippocrates of Chios’ Theory of Comets” Journal for the History of Astronomy 39.2, pp. 141-60. (peer-reviewed) 2 Major article for ‘Aristotle’ for Biographical Encyclopedia of the Ancient Natural Scientists edd. Paul Keyser and Georgia Irby-Massey (Routledge). 2006 w/ Demetra George, “Anonymi de Decubitu: Contexts of Rationality,” Greeks and the Ir/rational, Museion Series III.6. pp. 439-52. (peer-reviewed). 2005. “Autonomy and the Mistress Discipline in European Thought,” in edd. G. Sheridan and E. Gould, Engaging Europe. pp.173-89 Rowman and Littlefield. -
A Visual Analytics Approach for Exploratory Causal Analysis: Exploration, Validation, and Applications
A Visual Analytics Approach for Exploratory Causal Analysis: Exploration, Validation, and Applications Xiao Xie, Fan Du, and Yingcai Wu Fig. 1. The user interface of Causality Explorer demonstrated with a real-world audiology dataset that consists of 200 rows and 24 dimensions [18]. (a) A scalable causal graph layout that can handle high-dimensional data. (b) Histograms of all dimensions for comparative analyses of the distributions. (c) Clicking on a histogram will display the detailed data in the table view. (b) and (c) are coordinated to support what-if analyses. In the causal graph, each node is represented by a pie chart (d) and the causal direction (e) is from the upper node (cause) to the lower node (result). The thickness of a link encodes the uncertainty (f). Nodes without descendants are placed on the left side of each layer to improve readability (g). Users can double-click on a node to show its causality subgraph (h). Abstract—Using causal relations to guide decision making has become an essential analytical task across various domains, from marketing and medicine to education and social science. While powerful statistical models have been developed for inferring causal relations from data, domain practitioners still lack effective visual interface for interpreting the causal relations and applying them in their decision-making process. Through interview studies with domain experts, we characterize their current decision-making workflows, challenges, and needs. Through an iterative design process, we developed a visualization tool that allows analysts to explore, validate, arXiv:2009.02458v1 [cs.HC] 5 Sep 2020 and apply causal relations in real-world decision-making scenarios. -
MID-TWENTIETH CENTURY NEO-THOMIST APPROACHES to MODERN PSYCHOLOGY Dissertation Submitted to the College of Arts and Sciences Of
MID-TWENTIETH CENTURY NEO-THOMIST APPROACHES TO MODERN PSYCHOLOGY Dissertation Submitted to The College of Arts and Sciences of the UNIVERSITY OF DAYTON In Partial Fulfillment of the Requirements for The Degree of Doctor of Philosophy in Theology By Matthew Glen Minix UNIVERSITY OF DAYTON Dayton, Ohio December 2016 MID-TWENTIETH CENTURY NEO-THOMIST APPROACHES TO MODERN PSYCHOLOGY Name: Minix, Matthew G. APPROVED BY: _____________________________________ Sandra A. Yocum, Ph.D. Dissertation Director _____________________________________ William L. Portier, Ph.D. Dissertation Reader. _____________________________________ Anthony Burke Smith, Ph.D. Dissertation Reader _____________________________________ John A. Inglis, Ph.D. Dissertation Reader _____________________________________ Jack J. Bauer, Ph.D. _____________________________________ Daniel Speed Thompson, Ph.D. Chair, Department of Religious Studies ii © Copyright by Matthew Glen Minix All rights reserved 2016 iii ABSTRACT MID-TWENTIETH CENTURY NEO-THOMIST APPROACHES TO MODERN PSYCHOLOGY Name: Minix, Matthew Glen University of Dayton Advisor: Dr. Sandra A. Yocum This dissertation considers a spectrum of five distinct approaches that mid-twentieth century neo-Thomist Catholic thinkers utilized when engaging with the tradition of modern scientific psychology: a critical approach, a reformulation approach, a synthetic approach, a particular [Jungian] approach, and a personalist approach. This work argues that mid-twentieth century neo-Thomists were essentially united in their concerns about the metaphysical principles of many modern psychologists as well as in their worries that these same modern psychologists had a tendency to overlook the transcendent dimension of human existence. This work shows that the first four neo-Thomist thinkers failed to bring the traditions of neo-Thomism and modern psychology together to the extent that they suggested purely theoretical ways of reconciling them. -
Automating Path Analysis for Building Causal Models from Data
From: AAAI Technical Report WS-93-02. Compilation copyright © 1993, AAAI (www.aaai.org). All rights reserved. AutomatingPath Analysis for Building Causal Models from Data: First Results and Open Problems Paul R. Cohen Lisa BaUesteros AdamCarlson Robert St.Amant Experimental KnowledgeSystems Laboratory Department of Computer Science University of Massachusetts, Amherst [email protected]@cs.umass.edu [email protected] [email protected] Abstract mathematical basis than path analysis; they rely on evidence of nonindependence, a weaker criterion than Path analysis is a generalization of multiple linear regres- path analysis, which relies on evidence of correlation. sion that builds modelswith causal interpretations. It is Thosealgorithms will be discussed in a later section. an exploratory or discovery procedure for finding causal structure in correlational data. Recently, we have applied Wedeveloped the path analysis algorithm to help us path analysis to the problem of building models of AI discover causal explanations of how a complex AI programs, which are generally complex and poorly planning system works. The system, called Phoenix understood. For example, we built by hand a path- [Cohenet al., 89], simulates forest fires and the activities analytic causal model of the behavior of the Phoenix of agents such as bulldozers and helicopters. One agent, planner. Path analysis has a huge search space, however. called the fireboss, plans howthe others, whichare semi- If one measures N parameters of a system, then one can autonomous,should fight the fire; but things inevitably go build O(2N2) causal mbdels relating these parameters. wrong,winds shift, plans fail, bulldozers run out of gas, For this reason, we have developed an algorithm that and the fireboss soon has a crisis on its hands.