Tracing the Development of Models in the Philosophy of Science
01 Jan 1999-pp 23-40
TL;DR: It is shown how an analysis of the functions of models could lead to the consideration of their function not just within science, but also in human cognition, so that models are now sometimes viewed as tools of actual (rather than logically reconstructed) scientific thinking.
Abstract: An overview is provided of how the concept of a scientific model has devel-oped and changed in the philosophy of science in the course of this Century. I identify three shifts of interest in the treatment of the topic of scientific models. First, only from the 1950s did models begin to be considered relevant to the scientific enterprise, motivated by the desire to account for issues such as theory change and creativity in scientific discovery. Second, I examine how philosophers then increasingly concentrated on the analysis of the functions of models, e.g. for explanation or for guiding and suggesting new experiments. Finally, I show how an analysis of the functions of models could lead to the consideration of their function not just within science, but also in human cognition, so that models are now sometimes viewed as tools of actual (rather than logically reconstructed) scientific thinking.
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01 Jan 2005
TL;DR: It is concluded that much more research and development is needed in respect of visualization in science education if its importance is to be recognised and its potential realised.
Abstract: The range of terminology used in the field of ‘visualization’ is reviewed and, in the light of evidence that it plays a central role in the conduct of science, it is argued that it should play a correspondingly important role in science education. As all visualization is of, and produces, models, an epistemology and ontology for models as a class of entities is presented. Models can be placed in the public arena by means of a series of ‘modes and sub-modes of representation’. Visualization is central to learning, especially in the sciences, for students have to learn to navigate within and between the modes of representation. It is therefore argued that students -science students’ especially - must become metacognitive in respect of visualization, that they must show what I term ‘metavisual capability’. Without a metavisual capability, students find great difficulty in being able to undertake these demanding tasks. The development of metavisual capability is discussed in both theory and practice. Finally, some approaches to identifying students’ metavisual status are outlined and evaluated. It is concluded that much more research and development is needed in respect of visualization in science education if its importance is to be recognised and its potential realised.
404 citations
Cites background from "Tracing the Development of Models i..."
...This is not surprising – and is evident in the balance of contributions to this book for the key role of models in the development of chemical knowledge was recognised by the mid-twentieth century (Bailer-Jones, 1999; Francoeur, 1997)....
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...This is not surprising – and is evident in the balance of contributions to this book - for the key role of models in the development of chemical knowledge was recognised by the mid-twentieth century (Bailer-Jones, 1999; Francoeur, 1997)....
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TL;DR: It is argued that a central role for models and modelling would greatly increase the authenticity of the science curriculum and a great deal of detailed research and development will be needed if the potential of this change in emphasis within theScience curriculum is to be realised.
Abstract: It is argued that a central role for models and modelling would greatly increase the authenticity of the science curriculum. The range of ontological states available for the notion of ‘model’ is outlined, together with the modes available for their representation. Issues in the selection of models for and the development of modelling skills within the model-based curriculum are presented. It is suggested that learning within such a curriculum entails: acquiring an acceptable understanding of what a model is and how modelling takes place; having a developed capacity to mentally visualise models; understanding the natures of analogy and of metaphor, processes which are central to models and modelling. The emphases required in teaching for this learning to be supported are discussed. Finally, implications of the model-based curriculum for teacher education are evaluated. It is concluded that a great deal of detailed research and development will be needed if the potential of this change in emphasis within the science curriculum is to be realised.
370 citations
01 Jan 2002
134 citations
TL;DR: In this article, the authors discuss economic innovation as a product of organizational competencies, highlighting the importance of social network and propose a framework for studying the social aspects of economic innovations.
Abstract: Purpose – The importance of innovations in business management is a widely accepted hypothesis. Lately the research on innovation has widened to include consideration of the impact of social networks on the innovation. This paper aims to contribute to research on this approach by suggesting a framework for studying the social aspects of economic innovations.Design/methodology/approach – The paper discusses economic innovation as a product of organizational competencies, highlighting the importance of social network.Findings – This paper has three goals: we clarify the concept of economic innovation, we present the essential questions for studying the economic innovation process, and we present a proposal for an empirical approach and address problems in collecting data about economic innovations.Originality/value – The paper opens a new, socio‐psychological approach to studying the innovation processes. It proposes a holistic approach to the phenomenon by combining these with the material aspects of an or...
76 citations
01 Nov 2005
TL;DR: In this article, a new artefactual approach to models is presented that loosens the epistemic value of models from representation and ascribes it instead to their materially embodied constraints and interactive enablings.
Abstract: This study seeks to situate the philosophical discussion on models and scientific representation within the larger context of questioning representation that is taking place in other fields, especially in science and technology studies. It addresses four related questions: (i) What kinds of different reactions there have been to the puzzle of representation? (ii) From where do the seeming epistemological difficulties concerning representation stem? (iii) How can representation be approached in a non-representationalist way? (iv) What kinds of things are models, and how do they give us knowledge? A new artefactual approach to models is advanced that loosens the epistemic value of models from representation and ascribes it instead to their materially embodied constraints and interactive enablings. The thesis draws four additional major conclusions: (1) Our understanding of modelling should not be reduced to models representing some external target systems. Apart from being representative things models are typically also productive things whose workability and experimentability is crucial for their epistemic value. (2) Representation should be approached both from the use and production points of view. (3) From the use point of view representation appears as a two-fold phenomenon that is based both on the medium-specific affordances of the material sign-vehicle and on the intentional process of relating the sign-vehicle to the represented. (4) From the production point of view a major portion of the work of representation that is taking place in sciences concentrates on what is already represented and modelled somehow. Looking at representation from this angle stresses the methods, ingredients and various representative devices that are needed in producing models. The study consists of a contextualising introductory essay and six original research papers. The first two articles deal with more general issues concerning representation. The next four articles study representation in the context of modelling. Common to all of them is the idea that models can be seen as epistemic artefacts. The articles refer to this idea in discussing the interrelated questions of representation, modelling, and cognition.
73 citations
References
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Book•
01 Jan 1962
TL;DR: The Structure of Scientific Revolutions as discussed by the authors is a seminal work in the history of science and philosophy of science, and it has been widely cited as a major source of inspiration for the present generation of scientists.
Abstract: A good book may have the power to change the way we see the world, but a great book actually becomes part of our daily consciousness, pervading our thinking to the point that we take it for granted, and we forget how provocative and challenging its ideas once were-and still are. "The Structure of Scientific Revolutions" is that kind of book. When it was first published in 1962, it was a landmark event in the history and philosophy of science. And fifty years later, it still has many lessons to teach. With "The Structure of Scientific Revolutions", Kuhn challenged long-standing linear notions of scientific progress, arguing that transformative ideas don't arise from the day-to-day, gradual process of experimentation and data accumulation, but that revolutions in science, those breakthrough moments that disrupt accepted thinking and offer unanticipated ideas, occur outside of "normal science," as he called it. Though Kuhn was writing when physics ruled the sciences, his ideas on how scientific revolutions bring order to the anomalies that amass over time in research experiments are still instructive in our biotech age. This new edition of Kuhn's essential work in the history of science includes an insightful introductory essay by Ian Hacking that clarifies terms popularized by Kuhn, including paradigm and incommensurability, and applies Kuhn's ideas to the science of today. Usefully keyed to the separate sections of the book, Hacking's essay provides important background information as well as a contemporary context. Newly designed, with an expanded index, this edition will be eagerly welcomed by the next generation of readers seeking to understand the history of our perspectives on science.
36,808 citations
01 Jan 1974
TL;DR: The structure of scientific revolutions (1962) / Thomas Samuel Kuhn (1922-1996) is a book about the history of science and its discontents.
Abstract: A good book may have the power to change the way we see the world, but a great book actually becomes part of our daily consciousness, pervading our thinking to the point that we take it for granted, and we forget how provocative and challenging its ideas once were-and still are. "The Structure of Scientific Revolutions" is that kind of book. When it was first published in 1962, it was a landmark event in the history and philosophy of science. And fifty years later, it still has many lessons to teach. With "The Structure of Scientific Revolutions", Kuhn challenged long-standing linear notions of scientific progress, arguing that transformative ideas don't arise from the day-to-day, gradual process of experimentation and data accumulation, but that revolutions in science, those breakthrough moments that disrupt accepted thinking and offer unanticipated ideas, occur outside of "normal science," as he called it. Though Kuhn was writing when physics ruled the sciences, his ideas on how scientific revolutions bring order to the anomalies that amass over time in research experiments are still instructive in our biotech age. This new edition of Kuhn's essential work in the history of science includes an insightful introductory essay by Ian Hacking that clarifies terms popularized by Kuhn, including paradigm and incommensurability, and applies Kuhn's ideas to the science of today. Usefully keyed to the separate sections of the book, Hacking's essay provides important background information as well as a contemporary context. Newly designed, with an expanded index, this edition will be eagerly welcomed by the next generation of readers seeking to understand the history of our perspectives on science.
11,039 citations
TL;DR: In this paper, the interpretation rules of OS implicit rules for mapping knowledge about a base domain into a torget domain are defined by the existence of higher-order relations, which depend only on syntactic properties of the knowledge representation, and not on specific content of the domoins.
4,667 citations
"Tracing the Development of Models i..." refers background in this paper
...…this context, it is interesting to observe that, more recently, analogy, which is viewed as central for explanation, has become a closely investigated, crucial candidate for patterns of human reasoning in cognitive science (Gentner, 1982,1983; Gentner and Markman, 1997; Holyoak and Thagard, 1997)....
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...The argument that models, as analogies or as metaphors, bridge the gap from the unfamiliar to the familiar has also remained prominent until more recent days, e.g. in Hesse (1966), Harre (1988), Gentner (1982,1983)....
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Book•
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01 Jan 1980
TL;DR: In this book van Fraassen develops an alternative to scientific realism by constructing and evaluating three mutually reinforcing theories.
Abstract: In this book van Fraassen develops an alternative to scientific realism by constructing and evaluating three mutually reinforcing theories.
3,468 citations
"Tracing the Development of Models i..." refers background in this paper
...Mathematical model-theory, for instance, proved to be an attractive candidate to provide a formalized account of what scientific models are (proposed, e.g., in varying forms by Suppes, 1961; van Fraassen, 1980; Giere, 1988)....
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