Information to Users

Total Page:16

File Type:pdf, Size:1020Kb

Information to Users INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMl films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in reduced form at the back of the book. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9” black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. UMI A Bell & Howell Infonnation Company 300 North Zeeb Road, Ann Arbor MI 48106-1346 USA 313/761-4700 800/521-0600 AN ANTHROPOLOGICAL INVESTIGATION OF THREE INFORMATION TECHNOLOGY FIRMS USING JAMES C. SCOTT'S THEORIES RELATED TO EVERYDAY FORMS OF RESISTANCE TO POWER DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Cynthia Joseph Smith, B.A., M.A. ***** The Ohio State University 1998 Dissertation Committee: Approved by Professor Erika Bourguignon Professor Amy Zaharlick Adviser Department of Anthropology UMI Number: 9911271 Copyright 1998 by Smith, Cynthia Joseph All rights reserved. UMI Microform 9911271 Copyright 1999, by UMI Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. t n v n 300 North Zeeb Road Ann Arbor, MI 48103 Copyright by Cynthia Joseph Smith 1998 ABSTRACT This dissertation investigates the use of James C. Scott's theoretical framework to analyze data collected in three business organizations. Primary concepts from the framework used in this analysis are: the moral economy, hidden and public transcripts, and everyday forms of resistance. The interplay of the moral and material economies of business settings, and the use of figurative communication to enact everyday forms of resistance are explored in detail. Participant-observation methods were used over the course of nearly eight years in the first organization, three years in the second, and over two years in the third. My roles within the organizations included independent researcher, employee and consultant. All organizations studied provide information technology consulting services to business and government. Each represents a different segment of the information technology industry. One is a professional services partnership, another is a large mainframe computer manufacturer, and the third is a development software product company. 11 An overview of anthropological involvement in contemporary business and my use of ethnographic methods in business settings is presented. Brief descriptions of the three organizations in this study are provided. James C. Scott's body of work is discussed extensively. Using the data from my research, the interplay of the moral and material economies in organizations is explored as a means to understand resistance behavior and the informal aspects of organizational time and expense accounting systems. Figurative communication is defined as a broad category including linguistic as well as a wide range of other behaviors used for communicative purposes. Figurative communication is discussed and its use in everyday forms of resistance to power emphasized. The results of this analysis indicate Scott's conceptual framework provides a very robust approach to analyzing ethnographic data gathered in business settings. In combination with sociolinguistic techniques emphasizing the use of figurative communication, the dynamics of power relations can be effectively analyzed and discussed. Additionally, Scott's framework and attention to figurative communication is proposed for use in applied business anthropology as a means to develop practical applications. Ill To Sara and Mitch and with gratitude to Bill IV ACKNOWLEDGMENTS This dissertation is the culmination of a long career in business punctuated by retreats into scholarship which has helped make sense of that experience. I would first like to thank the Department of Anthropology for making me feel welcome every time I turned up on its doorstep in the past twenty-five years. Dr. Richard H. Moore could not have been a better adviser for this effort. His hard work and dedication are an inspiration. He has provided steady and invaluable guidance, yet has allowed me the freedom to pursue my individual interests. I greatly appreciate all the time and effort he has put forth in my behalf, his unfailing support and encouragement, and the great wealth of knowledge and experience he has shared over the years. I am indebted to Dr. Erika Bourguignon not only for all she has taught me in her seminars and her help with this dissertation, but also for being an exemplary role model. She is not only a formidable intellect and indomitable spirit, but is also a consummate professional and a gracious lady. Her skillful interviewing, probing questions, and incisive comments have taught me as much about life as about V anthropology. Probably like many others, I am glad Dr. Bourguignon does not drive. Our excursions here and there have been a real pleasure, and I look forward to "driving Dr. B" for many years to come. Dr. Amy Zaharlick's excellent seminar in linguistics inspired my interest in using sociolinguistics to analyze the extensive data I have collected. Her encouragement and suggestions helped with completing my Master's thesis on the topic of metaphor, and with the further extension of this work into the area of figurative communication reflected in this dissertation. Dr. Zaharlick's command of her specialty and great clarity in teaching are truly impressive and have been immeasurably helpful. I would also like to thank Dr. Ojo Arewa for his help with my Candidacy Exam. His questions helped greatly in clarifying my thoughts about business anthropology. I have truly enjoyed the many hours of pleasant and stimulating conversation on a wide range of topics that we have had over the years. I am deeply indebted to Dr. Frank Poirier for not only what he has taught me about physical anthropology, but also for what he has taught me about teaching. It has been a real privilege to be his student and his graduate teaching assistant. As a member of the committee overseeing my VI Master's thesis. Dr. Poirier provided important feedback and insights that have also been useful in completing this dissertation. Dr. William Dancey was also instrumental as a committee member for my Master's thesis on which this dissertation is based. It was Dr. Dancey's introduction to archaeology that put me on the path that made anthropology my major. Not only has Dr. Dancey been an excellent teacher, but he is also a friend with whom I have shared some of life's ups and downs. To Dr. Paul Sciulli I owe a great intellectual debt for the excellent foundation in evolutionary theory he provides through his seminar. Other seminars with him furthered my appreciation for the importance of physical anthropology to a well-rounded education. I have very fond memories of the summer I spent in his lab sorting and measuring bones. I am very grateful to Dr. Kenneth David of Michigan State University who put research before consulting to help me in the early stages of my fieldwork. His great energy and wit were instrumental in getting an important stage in this work completed successfully. It has also been an honor and privilege to know and work with Dr. Leonard Sayles of Columbia University. For more than ten years he has been a mentor, a colleague, and a friend. Not only do I treasure sharing good food and many pleasant hours of conversation with he and his wife, Kathy VIX Ripin, but the opportunity for the three of us to collaborate has also helped me grow as a professional. Many anthropologists actively involved in business anthropology have generously given of their time, advice and support. I wish to thank Drs. John Sherry, Tomoko Hamada, Marietta Baba, Frank Dubinskas, Roger McConochie, Margo Smith, Lorna McDougall, Susan Squires, Helen Schwartzman, Richard Reeves-Ellington, Jo Rainie Rodgers, and Darby Stapp in particular for their assistance, especially during the formative stages of my work. I am also grateful to Dr. Juliana Roth for her hospitality during my stay in Munich and for sharing her experiences during our long and pleasant conversations. Harry Blaine who encouraged my study of anthropology from the beginning and gave me his very fine library of anthropological classics is especially thanked. I thank Anita, Phyllis and Susan for all their cheerful assistance over these many years. They are not only very knowledgeable and ever-ready to help, but they make visits to the Department's office an invariably enjoyable experience. I also wish to thank all the business colleagues who, over the past thirty years, have helped me both personally and professionally. Hundreds of people contributed directly and indirectly to the research I have conducted. V l l l A very special thanks goes to William Yeack, who more than any other, has made this work possible. I have had the privilege of knowing Bill for over fifteen years and have watched him help many individuals, besides myself, realize their aspirations.
Recommended publications
  • The State of the Art in Developing Fuzzy Ontologies: a Survey
    The State of the Art in Developing Fuzzy Ontologies: A Survey Zahra Riahi Samani1, Mehrnoush Shamsfard2, 1Faculty of Computer Science and Engineering, Shahid Beheshti University Email:[email protected] 1Faculty of Computer Science and Engineering, Shahid Beheshti University Email:[email protected] Abstract Conceptual formalism supported by typical ontologies may not be sufficient to represent uncertainty information which is caused due to the lack of clear cut boundaries between concepts of a domain. Fuzzy ontologies are proposed to offer a way to deal with this uncertainty. This paper describes the state of the art in developing fuzzy ontologies. The survey is produced by studying about 35 works on developing fuzzy ontologies from a batch of 100 articles in the field of fuzzy ontologies. 1. Introduction Ontology is an explicit, formal specification of a shared conceptualization in a human understandable, machine- readable format. Ontologies are the knowledge backbone for many intelligent and knowledge based systems [1, 2]. However, in some domains, real world knowledge is imprecise or vague. For example in a search engine one may be interested in ”an extremely speedy, small size, not expensive car”. Classical ontologies based on crisp logic are not capable of handling this kind of knowledge. Fuzzy ontologies were proposed as a combination of fuzzy theory and ontologies to tackle such problems. On the topic of fuzzy ontology, we studied about 100 research articles which can be categorized into four main categories. The first category includes the research works on applying fuzzy ontologies in a specific domain- application to improve the performance of the application such as group decision making systems [3] or visual video content analysis and indexing [4].The ontology development parts of the works in this category were done manually or were not of much concentration.
    [Show full text]
  • A Fuzzy Description Logic
    From: AAAI-98 Proceedings. Copyright © 1998, AAAI (www.aaai.org). All rights reserved. A Fuzzy Description Logic Umberto Straccia I.E.I - C.N.R. Via S. Maria, 46 I-56126 Pisa (PI) ITALY [email protected] Abstract is such a concept: we may say that an individual tom is an instance of the concept Tall only to a certain degree Description Logics (DLs, for short) allow reasoning n ∈ [0, 1] depending on tom’s height. about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to Fuzzy logic directly deals with the notion of vague- dealing with crisp, well dened concepts. That is, con- ness and imprecision using fuzzy predicates. Therefore, cepts for which the problem whether an individual is it oers an appealing foundation for a generalisation of an instance of it is a yes/no question. More often than DLs in order to dealing with such vague concepts. not, the concepts encountered in the real world do not The aim of this work is to present a general fuzzy DL, have a precisely dened criteria of membership: we which combines fuzzy logic with DLs. In particular we may say that an individual is an instance of a concept will extend DLs by allowing expressions of the form only to a certain degree, depending on the individual’s hC(a) ni (n ∈ [0, 1]), e.g. hTall(tom) .7i, with intended properties. Concepts of this kind are rather vague than precise. As fuzzy logic directly deals with the notion of meaning “the membership degree of individual a being vagueness and imprecision, it oers an appealing foun- an instance of concept C is at least n”.
    [Show full text]
  • A Unifying Field in Logics: Neutrosophic Logic
    University of New Mexico UNM Digital Repository Faculty and Staff Publications Mathematics 2007 A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS - 6th ed. Florentin Smarandache University of New Mexico, [email protected] Follow this and additional works at: https://digitalrepository.unm.edu/math_fsp Part of the Algebra Commons, Logic and Foundations Commons, Other Applied Mathematics Commons, and the Set Theory Commons Recommended Citation Florentin Smarandache. A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS - 6th ed. USA: InfoLearnQuest, 2007 This Book is brought to you for free and open access by the Mathematics at UNM Digital Repository. It has been accepted for inclusion in Faculty and Staff Publications by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected], [email protected], [email protected]. FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (sixth edition) InfoLearnQuest 2007 FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (sixth edition) This book can be ordered in a paper bound reprint from: Books on Demand ProQuest Information & Learning (University of Microfilm International) 300 N. Zeeb Road P.O. Box 1346, Ann Arbor MI 48106-1346, USA Tel.: 1-800-521-0600 (Customer Service) http://wwwlib.umi.com/bod/basic Copyright 2007 by InfoLearnQuest. Plenty of books can be downloaded from the following E-Library of Science: http://www.gallup.unm.edu/~smarandache/eBooks-otherformats.htm Peer Reviewers: Prof. M. Bencze, College of Brasov, Romania.
    [Show full text]
  • A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability and Statistics
    FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 1 Contents: Preface by C. Le: 3 0. Introduction: 9 1. Neutrosophy - a new branch of philosophy: 15 2. Neutrosophic Logic - a unifying field in logics: 90 3. Neutrosophic Set - a unifying field in sets: 125 4. Neutrosophic Probability - a generalization of classical and imprecise probabilities - and Neutrosophic Statistics: 129 5. Addenda: Definitions derived from Neutrosophics: 133 2 Preface to Neutrosophy and Neutrosophic Logic by C.
    [Show full text]
  • Integrating Fuzzy Logic in Ontologies
    INTEGRATING FUZZY LOGIC IN ONTOLOGIES Silvia Calegari and Davide Ciucci Dipartimento di Informatica, Sistemistica e Comunicazione, Universita` degli Studi di Milano Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy Keywords: Concept modifiers, fuzzy logics, fuzzy ontologies, membership modifiers, KAON, ontology editor. Abstract: Ontologies have proved to be very useful in sharing concepts across applications in an unambiguous way. Nowadays, in ontology-based applications information is often vague and imprecise. This is a well-known problem especially for semantics-based applications, such as e-commerce, knowledge management, web por- tals, etc. In computer-aided reasoning, the predominant paradigm to manage vague knowledge is fuzzy set theory. This paper presents an enrichment of classical computational ontologies with fuzzy logic to create fuzzy ontologies. So, it is a step towards facing the nuances of natural languages with ontologies. Our pro- posal is developed in the KAON ontology editor, that allows to handle ontology concepts in an high-level environment. 1 INTRODUCTION A possible solution to handle uncertain data and, hence, to tackle these problems, is to incorporate fuzzy logic into ontologies. The aim of fuzzy set An ontology is a formal conceptualization of a partic- theory (Klir and Yuan, 1995) introduced by L. A. ular domain of interest shared among heterogeneous Zadeh (Zadeh, 1965) is to describe vague concepts applications. It consists of entities, attributes, rela- through a generalized notion of set, according to tionships and axioms to provide a common under- which an object may belong to a certain degree (typ- standing of the real world (Lammari and Mtais, 2004; ically a real number from the interval [0,1]) to a set.
    [Show full text]
  • Fuzzy Types: a Framework for Handling Uncertainty About Types of Objects Tru H
    CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector International Journal of Approximate Reasoning 25 (2000) 217±253 www.elsevier.com/locate/ijar Fuzzy types: a framework for handling uncertainty about types of objects Tru H. Cao a,*, Peter N. Creasy b a Department of Engineering Mathematics, Arti®cial Intelligence Group, University of Bristol, Bristol BS8 1TR, UK b Department of Computer Science and Electrical Engineering, University of Queensland, Qld 4072, Australia Received 1 November 1999; received in revised form 1 June 2000; accepted 1 July 2000 Abstract Like other kinds of information, types of objects in the real world are often found to be ®lled with uncertainty and/or partial truth. It may be due to either the vague nature of a type itself or to incomplete information in the process determining it even if the type is crisp, i.e., clearly de®ned. This paper proposes a framework to deal with uncertainty and/or partial truth in automated reasoning systems with taxonomic information, and in particular type hierarchies. A fuzzy type is formulated as a pair combining a basic type and a fuzzy truth-value, where a basic type can be crisp or vague (in the intuitive sense). A structure for a class of fuzzy truth-value lattices is proposed for this con- struction. The fuzzy subtype relation satisfying intuition is de®ned as a partial order between two fuzzy types. As an object may belong to more than one (fuzzy) type, conjunctive fuzzy types are introduced and their lattice properties are studied.
    [Show full text]
  • PREPRINT Intelligence, Science and the Ignorance Hypothesis David R
    PREPRINT Intelligence, Science and the Ignorance Hypothesis David R. Mandel Defence Research and Development Canada Intelligence organizations perform many functions. For example, they conduct covert operations that would be too politically sensitive for militaries to undertake as explicit missions. They also collect vast amounts of data that are inaccessible to others, except perhaps other intelligence organizations. However, the principal purpose of information collection is to produce substantive intelligence that can inform policymakers, commanders and other decision-makers who guard their nation’s interests and security. The fundamental premise of intelligence is that it serves to improve the planning and decision-making of these elite decision-makers by elevating the debate about policy options (Kent, 1955). If this were not so, the multi-billion dollar annual budgets would not be justified. If the premise is justified, then clearly the intellectual rigor and accuracy with which intelligence assessments are produce is of paramount importance. How do intelligence organizations ensure that the intelligence assessments they have produced are as accurate and sound as they can be? In this chapter, I will propose that the short answer is “not very well at all.” Methods and policies for ensuring analytic rigor have surely been implemented over the past several decades, but what has been endemic to these efforts is a rather pre-scientific, if not a fully anti-scientific, attitude towards their development and testing. After reviewing some examples of intelligence practices intended to ensure analytic rigor, I advance what I call the ignorance hypothesis to explain the absence of scientific attempts to discern what practices work from those that do not work so that intelligence organizations can effectively learn and adapt to the challenges of the modern world.
    [Show full text]
  • What Is a Fuzzy Concept Lattice? *
    ? WhatWhat is is a a fuzzy fuzzy concept concept lattice? lattice? ? Radim Bˇelohl´avek and Vil´em Vychodil Radim Bˇelohl´avek and Vil´em Vychodil Department of Computer Science, Palacky University, Olomouc DepartmentTomkova of Computer 40, CZ-779 Science, 00 Olomouc, Palack´yUniversity, Czech Republic Olomouc Tomkova{radim.belohlavek, 40, CZ-779 00 vilem.vychodil Olomouc, Czech}@upol.cz Republic {radim.belohlavek, vilem.vychodil}@upol.cz Abstract. The paper is an overview of several approaches to the notion of a concept lattice from the point of view of fuzzy logic. The main aim is to clarify relationships between the various approaches. Keywords: formal concept analysis, fuzzy logic, fuzzy attribute 1 Introduction Formal concept analysis (FCA) deals with a particular kind of analysis of data which, in the basic setting, has the form of a table with rows corresponding to objects, columns corresponding to attributes, and table entries containing 1’s and 0’s depending on whether an object has or does not have an attribute (we assume basic familiarity with FCA and refer to [24] for information). The basic setting is well-suited for attributes which are crisp, i.e. each object of the domain of applicability of the attribute either has (1) or does not have (0) the attribute. Many attributes are fuzzy rather than crisp. That is to say, it is a matter of degree to which an object has a (fuzzy) attribute. For instance, when asking whether a man with a height of 182 cm is tall, one probably gets an answer like “not completely tall but almost tall” or “to a high degree tall”, etc.
    [Show full text]
  • Modeling Fuzzy Rules with Description Logics
    Wright State University CORE Scholar Computer Science and Engineering Faculty Publications Computer Science & Engineering 11-1-2005 Modeling Fuzzy Rules with Description Logics Sudhir Agarwal Pascal Hitzler [email protected] Follow this and additional works at: https://corescholar.libraries.wright.edu/cse Part of the Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, and the Science and Technology Studies Commons Repository Citation Agarwal, S., & Hitzler, P. (2005). Modeling Fuzzy Rules with Description Logics. CEUR Workshop Proceedings, 188, 5. https://corescholar.libraries.wright.edu/cse/75 This Conference Proceeding is brought to you for free and open access by Wright State University’s CORE Scholar. It has been accepted for inclusion in Computer Science and Engineering Faculty Publications by an authorized administrator of CORE Scholar. For more information, please contact [email protected]. Modeling Fuzzy Rules with Description Logics Sudhir Agarwal and Pascal Hitzler Institute of Applied Informatics and Formal Description Methods (AIFB), University of Karlsruhe (TH), Germany. {agarwal,hitzler}@aifb.uni-karlsruhe.de Abstract. In real application scenarios, input data and knowledge is often vague. Likewise, it is often the case that exact reasoning over data is impossible due to complex dependencies between input data and tar- get outputs. For practical applications, however, good approximations often suffice, and efficient calculation of an approximate answer is often preferable over complex processing which may take a long time to come up with an exact answer. Fuzzy logic supports both features by provid- ing fuzzy membership functions and fuzzy IF-THEN rule bases.
    [Show full text]
  • Dariusz Piętka ( Cardinal Stefan Wyszy Ń Ski University in Warsaw ) 
    ORGANON 47:2015 Dariusz Piętka ( Cardinal Stefan Wyszy ń ski University in Warsaw ) THE CONCEPT OF INTUITION AND ITS ROLE IN PLATO AND ARISTOTLE Abstract . The subject of the article is intuition and its role in philosophical cognition in Plato and Aristotle. The mai n problem concerns the rationality of intuitive knowledge. Plato is the heir of the Parmenidean doctrinal tradition of being and cognition. According to him, intuition is the immediate perceiving of ideas. This may be supernatural intuition or rational int uition. The first is perceiving ideas seen before birth, the second is recollection of knowledge or cognition of ideas in the mind. The aim of intuitive knowledge is the definition of the essence. Plotinus is the successor to Plato’s theory of supernatura l intuition. Aristotle used intuition to formulate the first principles of science or to define the goals of activity. Each type is characterised by common features, such as directness, comprehensiveness of cognition and obviousness. There are differences between the types of intuition. First of all, they concern whether the object is natural or supernatural, its intersubjectivity, and the sources of intuitive cognition. In the case of intersubjectivity, Aristotle introduced a confirmation procedure concer ning some of principles known intuitively. The idea of confirmation is forced by accusations against, for example, the principle of non – contradiction, which made Aristotle present a certain extra – intuitive way for it to be substantiated. Key – words: Intuit ion, nous , Plato, Aristotle, ancient theory of knowledge. Introduction Science, or more generally knowledge, is an organised set of propositions. Their arrangement, broadly speaking, is that particular propositions from the set are justified by proposit ions formerly accepted which are substantiated by Addr ess for correspondence: Instytu t Filozofii UKSW, W óy cickiego 1/3, 01 – 938 Warszawa , Pol and.
    [Show full text]
  • Patent Verdicts: Improving the Quality of Appellate Review by Incorporating Fuzzy Logic in Jury Verdicts Michael T
    Hastings Law Journal Volume 59 | Issue 5 Article 11 1-2008 The yM th of "Lucky" Patent Verdicts: Improving the Quality of Appellate Review by Incorporating Fuzzy Logic in Jury Verdicts Michael T. Nguyen Follow this and additional works at: https://repository.uchastings.edu/hastings_law_journal Part of the Law Commons Recommended Citation Michael T. Nguyen, The Myth of "Lucky" Patent Verdicts: Improving the Quality of Appellate Review by Incorporating Fuzzy Logic in Jury Verdicts, 59 Hastings L.J. 1257 (2008). Available at: https://repository.uchastings.edu/hastings_law_journal/vol59/iss5/11 This Note is brought to you for free and open access by the Law Journals at UC Hastings Scholarship Repository. It has been accepted for inclusion in Hastings Law Journal by an authorized editor of UC Hastings Scholarship Repository. For more information, please contact [email protected]. The Myth of "Lucky" Patent Verdicts: Improving the Quality of Appellate Review by Incorporating Fuzzy Logic in Jury Verdicts MICHAEL T. NGUYEN* Everything is vague to a degree you do not realize till you have tried to make it precise. - Bertrand Russell INTRODUCTION Patent jury verdicts resemble lottery jackpot winnings in a multitude of ways.' For many years, commentators have lamented the unpredictable nature of patent jury verdicts.' The damages awards of these patent verdicts, like lottery jackpots, are measured in the millions of dollars. For example, in a recent patent case, Verizon v. Vonage, the jury awarded Verizon $58 million in damages.4 For better or for worse, * J.D., University of California, Hastings College of the Law, 2008; B.A., Southwestern University, 2003.
    [Show full text]
  • A Context Model for Fuzzy Concept Analysis Based Upon Modal Logic V.N
    Information Sciences 160 (2004) 111–129 www.elsevier.com/locate/ins A context model for fuzzy concept analysis based upon modal logic V.N. Huynh a,*,1, Y. Nakamori a, T.B. Ho a, G. Resconi b a School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Tatsunokuchi, Ishikawa 923-1292, Japan b Catholic University, Trieste 17, 25128 Brescia, Italy Received 23 November 2002; received in revised form 20 June 2003; accepted 4 August 2003 Abstract In this paper we present interesting relationships between the context model, modal logic and fuzzy concept analysis. It has been shown that the context model proposed by Gebhardt and Kruse [Int. J. Approx. Reason. 9 (1993) 283] can be semantically ex- tended and considered as a data model for fuzzy concept analysis within the framework of the meta-theory developed by Resconi et al. in 1990s. Consequently, the context model provides a practical framework for constructing membership functions of fuzzy concepts and gives the basis for a theoretical justification of suitably use of well-known t-norm based connectives such as min–max and product–sum rules in applications. Furthermore, an interpretation of mass assignments of fuzzy concepts within the con- text model is also established. Ó 2003 Elsevier Inc. All rights reserved. Keywords: Context model; Modal logic; Fuzzy concept; Membership function 1. Introduction While the real world consists of a very large number of instances of events and continuous numeric values, people only represent and process their * Corresponding author. E-mail addresses: [email protected], [email protected] (V.N.
    [Show full text]