Aristotelianism in the Philosophy of Mathematics James Franklin
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What Is That Thing Called Philosophy of Technology? - R
HISTORY AND PHILOSOPHY OF SCIENCE AND TECHNOLOGY – Vol. IV - What Is That Thing Called Philosophy of Technology? - R. J. Gómez WHAT IS THAT THING CALLED PHILOSOPHY OF TECHNOLOGY? R. J. Gómez Department of Philosophy. California State University (LA). USA Keywords: Adorno, Aristotle, Bunge, Ellul, Feenberg, Habermas, Heidegger, Horkheimer, Jonas, Latour, Marcuse, Mumford, Naess, Shrader-Frechette, artifact, assessment, determinism, ecosophy, ends, enlightenment, efficiency, epistemology, enframing, ideology, life-form, megamachine, metaphysics, method, naturalistic, fallacy, new, ethics, progress, rationality, rule, science, techno-philosophy Contents 1. Introduction 2. Locating technology with respect to science 2.1. Structure and Content 2.2. Method 2.3. Aim 2.4. Pattern of Change 3. Locating philosophy of technology 4. Early philosophies of technology 4.1. Aristotelianism 4.2. Technological Pessimism 4.3. Technological Optimism 4.4. Heidegger’s Existentialism and the Essence of Technology 4.5. Mumford’s Megamachinism 4.6. Neomarxism 4.6.1. Adorno-Horkheimer 4.6.2. Marcuse 4.6.3. Habermas 5. Recent philosophies of technology 5.1. L. Winner 5.2. A. Feenberg 5.3. EcosophyUNESCO – EOLSS 6. Technology and values 6.1. Shrader-Frechette Claims 6.2. H Jonas 7. Conclusions SAMPLE CHAPTERS Glossary Bibliography Biographical Sketch Summary A philosophy of technology is mainly a critical reflection on technology from the point of view of the main chapters of philosophy, e.g., metaphysics, epistemology and ethics. Technology has had a fast development since the middle of the 20th century , especially ©Encyclopedia of Life Support Systems (EOLSS) HISTORY AND PHILOSOPHY OF SCIENCE AND TECHNOLOGY – Vol. IV - What Is That Thing Called Philosophy of Technology? - R. -
Variables in Mathematics Education
Variables in Mathematics Education Susanna S. Epp DePaul University, Department of Mathematical Sciences, Chicago, IL 60614, USA http://www.springer.com/lncs Abstract. This paper suggests that consistently referring to variables as placeholders is an effective countermeasure for addressing a number of the difficulties students’ encounter in learning mathematics. The sug- gestion is supported by examples discussing ways in which variables are used to express unknown quantities, define functions and express other universal statements, and serve as generic elements in mathematical dis- course. In addition, making greater use of the term “dummy variable” and phrasing statements both with and without variables may help stu- dents avoid mistakes that result from misinterpreting the scope of a bound variable. Keywords: variable, bound variable, mathematics education, placeholder. 1 Introduction Variables are of critical importance in mathematics. For instance, Felix Klein wrote in 1908 that “one may well declare that real mathematics begins with operations with letters,”[3] and Alfred Tarski wrote in 1941 that “the invention of variables constitutes a turning point in the history of mathematics.”[5] In 1911, A. N. Whitehead expressly linked the concepts of variables and quantification to their expressions in informal English when he wrote: “The ideas of ‘any’ and ‘some’ are introduced to algebra by the use of letters. it was not till within the last few years that it has been realized how fundamental any and some are to the very nature of mathematics.”[6] There is a question, however, about how to describe the use of variables in mathematics instruction and even what word to use for them. -
Kind of Quantity’
NIST Technical Note 2034 Defning ‘kind of quantity’ David Flater This publication is available free of charge from: https://doi.org/10.6028/NIST.TN.2034 NIST Technical Note 2034 Defning ‘kind of quantity’ David Flater Software and Systems Division Information Technology Laboratory This publication is available free of charge from: https://doi.org/10.6028/NIST.TN.2034 February 2019 U.S. Department of Commerce Wilbur L. Ross, Jr., Secretary National Institute of Standards and Technology Walter Copan, NIST Director and Undersecretary of Commerce for Standards and Technology Certain commercial entities, equipment, or materials may be identifed in this document in order to describe an experimental procedure or concept adequately. Such identifcation is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose. National Institute of Standards and Technology Technical Note 2034 Natl. Inst. Stand. Technol. Tech. Note 2034, 7 pages (February 2019) CODEN: NTNOEF This publication is available free of charge from: https://doi.org/10.6028/NIST.TN.2034 NIST Technical Note 2034 1 Defning ‘kind of quantity’ David Flater 2019-02-06 This publication is available free of charge from: https://doi.org/10.6028/NIST.TN.2034 Abstract The defnition of ‘kind of quantity’ given in the International Vocabulary of Metrology (VIM), 3rd edition, does not cover the historical meaning of the term as it is most commonly used in metrology. Most of its historical meaning has been merged into ‘quantity,’ which is polysemic across two layers of abstraction. -
Guide for the Use of the International System of Units (SI)
Guide for the Use of the International System of Units (SI) m kg s cd SI mol K A NIST Special Publication 811 2008 Edition Ambler Thompson and Barry N. Taylor NIST Special Publication 811 2008 Edition Guide for the Use of the International System of Units (SI) Ambler Thompson Technology Services and Barry N. Taylor Physics Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899 (Supersedes NIST Special Publication 811, 1995 Edition, April 1995) March 2008 U.S. Department of Commerce Carlos M. Gutierrez, Secretary National Institute of Standards and Technology James M. Turner, Acting Director National Institute of Standards and Technology Special Publication 811, 2008 Edition (Supersedes NIST Special Publication 811, April 1995 Edition) Natl. Inst. Stand. Technol. Spec. Publ. 811, 2008 Ed., 85 pages (March 2008; 2nd printing November 2008) CODEN: NSPUE3 Note on 2nd printing: This 2nd printing dated November 2008 of NIST SP811 corrects a number of minor typographical errors present in the 1st printing dated March 2008. Guide for the Use of the International System of Units (SI) Preface The International System of Units, universally abbreviated SI (from the French Le Système International d’Unités), is the modern metric system of measurement. Long the dominant measurement system used in science, the SI is becoming the dominant measurement system used in international commerce. The Omnibus Trade and Competitiveness Act of August 1988 [Public Law (PL) 100-418] changed the name of the National Bureau of Standards (NBS) to the National Institute of Standards and Technology (NIST) and gave to NIST the added task of helping U.S. -
Scalars and Vectors
1 CHAPTER ONE VECTOR GEOMETRY 1.1 INTRODUCTION In this chapter vectors are first introduced as geometric objects, namely as directed line segments, or arrows. The operations of addition, subtraction, and multiplication by a scalar (real number) are defined for these directed line segments. Two and three dimensional Rectangular Cartesian coordinate systems are then introduced and used to give an algebraic representation for the directed line segments (or vectors). Two new operations on vectors called the dot product and the cross product are introduced. Some familiar theorems from Euclidean geometry are proved using vector methods. 1.2 SCALARS AND VECTORS Some physical quantities such as length, area, volume and mass can be completely described by a single real number. Because these quantities are describable by giving only a magnitude, they are called scalars. [The word scalar means representable by position on a line; having only magnitude.] On the other hand physical quantities such as displacement, velocity, force and acceleration require both a magnitude and a direction to completely describe them. Such quantities are called vectors. If you say that a car is traveling at 90 km/hr, you are using a scalar quantity, namely the number 90 with no direction attached, to describe the speed of the car. On the other hand, if you say that the car is traveling due north at 90 km/hr, your description of the car©s velocity is a vector quantity since it includes both magnitude and direction. To distinguish between scalars and vectors we will denote scalars by lower case italic type such as a, b, c etc. -
Outline of Mathematics
Outline of mathematics The following outline is provided as an overview of and 1.2.2 Reference databases topical guide to mathematics: • Mathematical Reviews – journal and online database Mathematics is a field of study that investigates topics published by the American Mathematical Society such as number, space, structure, and change. For more (AMS) that contains brief synopses (and occasion- on the relationship between mathematics and science, re- ally evaluations) of many articles in mathematics, fer to the article on science. statistics and theoretical computer science. • Zentralblatt MATH – service providing reviews and 1 Nature of mathematics abstracts for articles in pure and applied mathemat- ics, published by Springer Science+Business Media. • Definitions of mathematics – Mathematics has no It is a major international reviewing service which generally accepted definition. Different schools of covers the entire field of mathematics. It uses the thought, particularly in philosophy, have put forth Mathematics Subject Classification codes for orga- radically different definitions, all of which are con- nizing their reviews by topic. troversial. • Philosophy of mathematics – its aim is to provide an account of the nature and methodology of math- 2 Subjects ematics and to understand the place of mathematics in people’s lives. 2.1 Quantity Quantity – 1.1 Mathematics is • an academic discipline – branch of knowledge that • Arithmetic – is taught at all levels of education and researched • Natural numbers – typically at the college or university level. Disci- plines are defined (in part), and recognized by the • Integers – academic journals in which research is published, and the learned societies and academic departments • Rational numbers – or faculties to which their practitioners belong. -
Euclidean Spaces and Vectors
EUCLIDEAN SPACES AND VECTORS PAUL L. BAILEY 1. Introduction Our ultimate goal is to apply the techniques of calculus to higher dimensions. We begin by discussing what mathematical concepts describe these higher dimensions. Around 300 B.C. in ancient Greece, Euclid set down the fundamental laws of synthetic geometry. Geometric figures such as triangles and circles resided on an abstract notion of plane, which stretched indefinitely in two dimensions; the Greeks also analysed solids such as regular tetrahedra, which resided in space which stretched indefinitely in three dimensions. The ancient Greeks had very little algebra, so their mathematics was performed using pictures; no coordinate system which gave positions to points was used as an aid in their calculations. We shall refer to the uncoordinatized spaces of synthetic geometry as affine spaces. The word affine is used in mathematics to indicate lack of a specific preferred origin. The notion of coordinate system arose in the analytic geometry of Fermat and Descartes after the European Renaissance (circa 1630). This technique connected the algebra which was florishing at the time to the ancient Greek geometric notions. We refer to coordinatized lines, planes, and spaces as cartesian spaces; these are composed of ordered n-tuples of real numbers. Since affine spaces and cartesian spaces have essentially the same geometric properties, we refer to either of these types of spaces as euclidean spaces. Just as coordinatizing affine space yields a powerful technique in the under- standing of geometric objects, so geometric intuition and the theorems of synthetic geometry aid in the analysis of sets of n-tuples of real numbers. -
Basics of Euclidean Geometry
This is page 162 Printer: Opaque this 6 Basics of Euclidean Geometry Rien n'est beau que le vrai. |Hermann Minkowski 6.1 Inner Products, Euclidean Spaces In a±ne geometry it is possible to deal with ratios of vectors and barycen- ters of points, but there is no way to express the notion of length of a line segment or to talk about orthogonality of vectors. A Euclidean structure allows us to deal with metric notions such as orthogonality and length (or distance). This chapter and the next two cover the bare bones of Euclidean ge- ometry. One of our main goals is to give the basic properties of the transformations that preserve the Euclidean structure, rotations and re- ections, since they play an important role in practice. As a±ne geometry is the study of properties invariant under bijective a±ne maps and projec- tive geometry is the study of properties invariant under bijective projective maps, Euclidean geometry is the study of properties invariant under certain a±ne maps called rigid motions. Rigid motions are the maps that preserve the distance between points. Such maps are, in fact, a±ne and bijective (at least in the ¯nite{dimensional case; see Lemma 7.4.3). They form a group Is(n) of a±ne maps whose corresponding linear maps form the group O(n) of orthogonal transformations. The subgroup SE(n) of Is(n) corresponds to the orientation{preserving rigid motions, and there is a corresponding 6.1. Inner Products, Euclidean Spaces 163 subgroup SO(n) of O(n), the group of rotations. -
Investigations of Worth: Towards a Phenomenology of Values Dale Hobbs Jr
Marquette University e-Publications@Marquette Dissertations (2009 -) Dissertations, Theses, and Professional Projects Investigations of Worth: Towards a Phenomenology of Values Dale Hobbs Jr. Marquette University Recommended Citation Hobbs, Dale Jr., "Investigations of Worth: Towards a Phenomenology of Values" (2017). Dissertations (2009 -). 740. http://epublications.marquette.edu/dissertations_mu/740 INVESTIGATIONS OF WORTH: TOWARDS A PHENOMENOLOGY OF VALUES by Dale (D.J.) Hobbs A Dissertation submitted to the Faculty of the Graduate School, Marquette University, in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Milwaukee, WI August 2017 ABSTRACT INVESTIGATIONS OF WORTH: TOWARDS A PHENOMENOLOGY OF VALUES Dale (D.J.) Hobbs Marquette University, 2017 The purpose of this dissertation is to provide a clear and compelling account of the existence and nature of values within a phenomenological context. Values such as beauty or virtue are certainly a major part of our experiential lives. After all, what would life be worth if we could never describe a painting as beautiful, for example, or a beverage as delicious? Nevertheless, understanding what these values are on their own terms has historically been a rather difficult task. Certainly, they are not ordinary objects that could be seen or heard, touched or tasted, like the physical objects to which they seem to be connected in some mysterious way. In this dissertation, I argue that a phenomenological approach enables us to give a solid account of the role that values play in experience. Working in dialogue with Husserl and other phenomenologists and related thinkers (especially Max Scheler and Nicolai Hartmann), as well as with recent commentary, I develop my own account of values as lying on the phenomenological “horizons” of experience. -
Introduction
Copyrighted Material • Introduction I Although the term pragmatism is frequently used to characterize some or other highly specific thesis or program, pragmatism is not and never was a school of thought unified around a distinctive doctrine. In fact, the first pragmatists— Charles Peirce, William James, and John Dewey—were divided over what, precisely, pragmatism is. Peirce first proposed the “pragmatic maxim” as a tool for dispensing with metaphysical nonsense; for him, pragmatism was strictly a “method of ascer- taining the meanings of hard words and abstract concepts” (CP5.464).1 The core of this method is the idea that, To develop [a thought’s] meaning, we have simply to determine what habits it produces, for what a thing means is simply what habits it involves. (CP5.400) Hence the pragmatic maxim: Consider what effects, that might conceivably have practical bearings, we conceive the object of our conception to have. Then our conception of these effects is the whole of our conception of the object. (CP5.402) For Peirce, pragmatism was a way to clear away philosophical error and start upon the path of properly conducted philosophy. Peirce thought that by analyzing words and statements in terms of “what is tangible and conceivably practical” (CP5.400), one could “dismiss make-believes” (CP5.416) and free philosophy of “senseless jar- gon” (CP5.401). Although pragmatism is the beginning of Peirce’s philosophy, it is not the whole of Peirce’s philosophy. As is well known, Peirce went on to develop original (some might say idiosyncratic) views concerning topics ranging from philosophy of mathematics, logic, and science to phenomenology, semiotics, and aesthetics. -
Chapter 1 Euclidean Space
Euclidean space 1 Chapter 1 Euclidean space A. The basic vector space We shall denote by R the ¯eld of real numbers. Then we shall use the Cartesian product Rn = R £ R £ ::: £ R of ordered n-tuples of real numbers (n factors). Typical notation for x 2 Rn will be x = (x1; x2; : : : ; xn): Here x is called a point or a vector, and x1, x2; : : : ; xn are called the coordinates of x. The natural number n is called the dimension of the space. Often when speaking about Rn and its vectors, real numbers are called scalars. Special notations: R1 x 2 R x = (x1; x2) or p = (x; y) 3 R x = (x1; x2; x3) or p = (x; y; z): We like to draw pictures when n = 1, 2, 3; e.g. the point (¡1; 3; 2) might be depicted as 2 Chapter 1 We de¯ne algebraic operations as follows: for x, y 2 Rn and a 2 R, x + y = (x1 + y1; x2 + y2; : : : ; xn + yn); ax = (ax1; ax2; : : : ; axn); ¡x = (¡1)x = (¡x1; ¡x2;:::; ¡xn); x ¡ y = x + (¡y) = (x1 ¡ y1; x2 ¡ y2; : : : ; xn ¡ yn): We also de¯ne the origin (a/k/a the point zero) 0 = (0; 0;:::; 0): (Notice that 0 on the left side is a vector, though we use the same notation as for the scalar 0.) Then we have the easy facts: x + y = y + x; (x + y) + z = x + (y + z); 0 + x = x; in other words all the x ¡ x = 0; \usual" algebraic rules 1x = x; are valid if they make (ab)x = a(bx); sense a(x + y) = ax + ay; (a + b)x = ax + bx; 0x = 0; a0 = 0: Schematic pictures can be very helpful. -
Common Core State Standards for MATHEMATICS
Common Core State StandardS for mathematics Common Core State StandardS for MATHEMATICS table of Contents Introduction 3 Standards for mathematical Practice 6 Standards for mathematical Content Kindergarten 9 Grade 1 13 Grade 2 17 Grade 3 21 Grade 4 27 Grade 5 33 Grade 6 39 Grade 7 46 Grade 8 52 High School — Introduction High School — Number and Quantity 58 High School — Algebra 62 High School — Functions 67 High School — Modeling 72 High School — Geometry 74 High School — Statistics and Probability 79 Glossary 85 Sample of Works Consulted 91 Common Core State StandardS for MATHEMATICS Introduction Toward greater focus and coherence Mathematics experiences in early childhood settings should concentrate on (1) number (which includes whole number, operations, and relations) and (2) geometry, spatial relations, and measurement, with more mathematics learning time devoted to number than to other topics. Mathematical process goals should be integrated in these content areas. — Mathematics Learning in Early Childhood, National Research Council, 2009 The composite standards [of Hong Kong, Korea and Singapore] have a number of features that can inform an international benchmarking process for the development of K–6 mathematics standards in the U.S. First, the composite standards concentrate the early learning of mathematics on the number, measurement, and geometry strands with less emphasis on data analysis and little exposure to algebra. The Hong Kong standards for grades 1–3 devote approximately half the targeted time to numbers and almost all the time remaining to geometry and measurement. — Ginsburg, Leinwand and Decker, 2009 Because the mathematics concepts in [U.S.] textbooks are often weak, the presentation becomes more mechanical than is ideal.