Sal Restivo

THE MYTH OF THE KUHNIAN REVOLUTION

The widespread adoption of the rhetoric of normal science, revolutionary science, paradigms, and exemplars by sociologists of science and sociologists in general suggests the strong influence that Thomas S. Kuhns The Structure of Scientific Revolutions (1962, 1970) has had on sociological inquiry. But claims that Kuhns work is antiMertonian, nonnormative, relativistic, an alternative to positivism and logical empiricism, and even compatible with Marxism are all part of the myth of the Kuhnian revolution in the sociology of science.1 The central dogma in the Kuhnian mythology is that Kuhns paradigm is a significant, indeed a radical, alternative to Mertons. Some Mertonians (see Gaston, 1979, pp. 118-119) have been more perceptive about the Kuhnian mythology than have critics of Mertonian sociology of science. Gaston suggests (correctly I think) that Kuhns reception is

Toward a socio-visual theory of information and information technology

In this paper, we report an evolving collaboration between a social theorist and a visual communication theorist-graphic designer. We are exploring the contributions that can be made by integrating our theories and practices to theory, design and practice in information technology. We discuss the nature and current state of our collaboration and a project in which we are developing a Web-based GUI research protocol. The overall objective of our work is to explore the implications of understanding AI, robotics, GUIs, and human-computer interactions in terms of the idea that science and technology are socially constructed. One of our objectives in this paper is to explain what it means to say something is socially constructed. Another is to show why it is important to think about visual communication and graphic design in social and cultural terms.

Theory of Mind, Social Science, and Mathematical Practice

The Very Idea Of “Mathematical Practice” Implies, Beyond The Transparent Social Turn In Philosophy, Pedagogy, And Didactics Of Mathematics, A Theory Of Mind. Theories Of Mind May Be The Informal Folk Theories Of Our Everyday Lives Or The More Formal Theories Of Professional Students Of Mind. My Conjecture Is That Folk Theories Of Mind Are At Present Still More Influential In The Work Of Students Of Mathematics And The Mathematics Classroom Than Are Professional Theories. The Problem Is That Whichever Theory Prevails In Any Given Setting Or Study, Or For Any Given Researcher, It Is More Likely Than Not To Locate The Mind In The Brain And In The Person. So One Question I Want To Pose Is: Which Theory Or Theories Of Mind Are Built Into Our Theories Of And Approaches To Mathematical Practice? If Turning Our Attention To Mathematical Practice As Opposed To Focusing On Questions Of Foundations Is A Turn To The Social, Perhaps We Should Be Alert To The Possibility Of A Social Turn In Our Theories Of Mind.

The Invention of Science

Social and cultural studies of science revolutionized our understanding of science during the last quarter of the 20th century. This achievement has been accomplished in the face of great resistance and at great cost to the critics and theorists of science. In this paper, we explore some of the reasons for the resistance to and costs of analyzing science as a social fact. At the same time, we try to regain some of the momentum science studies achieved in the 1960s and 1970s. Our approach is to consider the consequences of bringing science into the dialogue on orientalism and occidentalism. We discuss the invention of science in terms of the traditions against or in opposition to which it was invented. Science, no matter how we define it, is intertwined with the industrial, and military technologies that grounded European movement into and around the world. Social theory is not only a route to critique and theory in science studies, but also a route for saving science as an intellectual enterprise.

The Sociology of Mathematics

The sociology of mathematics has grown slowly on the periphery of developments in mainstream sociology of knowledge and science. Spengler, Hessen, Wittgenstein, Struik, and Needham were among the small group of important contributors to the sociology of mathematics (most of them Marxists) between 1920 and 1970.1 But their contributions were overshadowed by the development of functional analyses of the social system of science that virtually excluded studies of mathematical activities and knowledge.2 Mannheim explicitly exempted mathematical knowledge from sociological inquiry.3 During the last decade, new directions in the sociology of knowledge and science have helped to stimulate interest in and research on mathematics. The renaissance in radical science studies, the “strong program” in the sociology of knowledge, and ethnographic studies of science have been especially important in breaking down the traditional barriers to sociological studies of mathematics.4 This is a critical development because among all systems of knowledge, mathematics has been the most resistant to sociological analysis and the ultimate arbiter of the limits of the sociology of knowledge.

Mechanizing Proof: Computing, Risk, and Trust, by D. MacKenzie. Cambridge, MA: MIT Press, 2001. xi + 427 pp.

Donald MacKenzie, a sociologist at the University of Edinburgh, is one of the founders of the sociology of scientific knowledge and mathematics. One of the central questions in this field (more broadly, social studies of science and technology), as we know it from its beginnings in the late 1960s, is: How do we know the properties of the natural, cultural, and artifactual worlds we live in? MacKenzie addresses one aspect of that general question in this book: How do we assess the dependability of the computers we depend on across virtually all aspects of our lives? This resolves itself into questions about risk, trust, and proof. More generally, MacKenzie gives us an historical sociology of machine proof. The book is marked by a technically sophisticated history of machine proofs that gives priority to historical details interrupted by episodes of sociological inquiry and insight. The bulk of MacKenzie’s sociological theory comes in the last chapter. His sociological eye, however, is obvious on almost every page. He gives only a bare account of the methodology that grounds this history. Interviews were conducted with many of the leading figures in the story MacKenzie tells, but it is not clear how many people were interviewed. Several coworkers carried out the interviews. The final product, in any case, is by any standard an outstanding and relatively rare example of historical sociology of technology and mathematics. Its quality is such that someone not familiar with the methodological, theoretical, and substantive achievements of sociology or with MacKenzie’s earlier work might, like the computer scientist author of the blurb on the back of the book’s jacket, find the results “utterly beyond me” and “thoroughly amazing.” MacKenzie begins his story by examining the emergence in the 1960s of questions about computer dependability. This takes his discussion into the realm of testing procedures for determining the properties of computer systems. The focus here is on deductive knowledge. The concern with dependability put computer scientists up against Hume’s classic concern with how we know a claimed proof is correct. The possibility of erroneous proofs in modern science points to the difference between “subjective conviction” and automated machine proofs. In Chapter 3, MacKenzie returns us to that “iconic moment” in 1956 when Simon and Newell introduced their “thinking machine.” Then Alan Robinson’s invention of resolution, an automated deduction technique, suggested the possibility that there might be “machine-oriented” as opposed to “human-oriented” forms of inference. At this point in the book, it is already clear that we are involved in conflicts and criticisms that cut across the fields of computer science, science, mathematics, and artificial intelligence. In Chapter 4, MacKenzie discusses the 1976 proof of the four-color conjecture by Haken and Appel. Their use of a computer raised the issue of whether such an unsurveyable proof was a proof at all. Any reader who began this book with the idea that a proof is a proof is a proof is by this point able to understand the significance of Sidney Harris’s famous cartoon in which two mathematicians are in front of a blackboard filled with mathematical symbols. One of the mathematicians has his fist raised and is saying, “You want proof, I’ll show you proof!” From the 1960s onward, computer security began to trouble defense department officials (especially in the United States at the Defense Advanced Projects Research Agency, and among members of the highly secretive National Security Agency). DARPA and NSA provided much of the funding that led to the first serious computer systems proofs. The everyday concerns about trust and risk that are a part of any community became almost pathological concerns within the arenas of national security, and these concerns influenced the development and assessments of computer systems proofs.

50.00. ISBN 0-262-13393-8.

Chapter 1 Introduction: Sociology, Humanist and Scientific Chapter 2 Sociology and Choice Chapter 3 The Social Construction of Life-Cycle Crises Chapter 4 Overcoming Cultural Impediments to Human Survival Chapter 5 A Humanistic Perspective on Science and Society Chapter 6 Toward a Grounded Theory of Humanist Organization Chapter 7 Community and Social Justice: Pedagogical Reflections on Justice as Fairness Chapter 8 Inequality Chapter 9 Humanist Issues in Participant Observation Research Chapter 10 The Myth of the Normal Curve: A Theoretical Critique and Examination of its Role in Teaching and Research

Readings in Humanist Sociology: Social Criticism and Social Change

Perennial issues in the sociology of science, such as &dquo;relativism,&dquo; &dquo;objectivity,&dquo; and &dquo;scientific progress,&dquo; are today being discussed and debated in a post-Mertonian atmosphere of laboratory studies, meta-analyses of science, and scientific knowledge. This essay, a brief introduction to the new debates, looks first at some basic ideas about the Mertonian paradigm, the &dquo;myth&dquo; of the Kuhnian revolution, Marxist and conflict sociologies of science, and, then, at the &dquo;laboratory life&dquo; studies. In the second part, I focus on a central question about the relationship between science and the sociology of science: What is the epistemological relevance of the sociology of science?1 There are three major perspectives on this problem: the &dquo;strong&dquo; program, evolutionary epistemology (or the &dquo;moderate&dquo; program), and meta-inquiry (or the &dquo;weak&dquo; program).z Parties to the Debate

Commentary: Some Perspectives in Contemporary Sociology of Science.

My objective in this chapter is to review some of the general ideas that have come from studies in the sociology of mathematics. Mathematicians, philosophers, and scientists traditionally assumed that the secret of mathematical power ultimately rested on formal relations between meaningless symbols. This represented a late nineteenth-/early twentieth-century transformation of mathematics from a general Platonist transcendental phenomenon to a professional utilitarian Platonism, a game for mathematicians. Sociologists of mathematics have, however, shown that technical talk about mathematics cannot by itself provide a complete understanding of mathematics. Relying on technical talk obscures the social dimensions of mathematics and the social dimensions of technical talk itself. Indeed, technical talk is social talk; there are no forms of talk that transcend society, culture, and history.

The Social Construction of Mathematics

Discipline & Experience: The Mathematical Way in the Scientific Revolution, by Peter Dear, Chicago: University of Chicago Press, 1995, 290 pp.,