Gelfert How to Do Science with Models

A Philosophical Primer
1. Auflage 2015
ISBN: 978-3-319-27954-1
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 135 Seiten

Reihe: SpringerBriefs in Philosophy

Taking scientific practice as its starting point, this book charts the complex territory of models used in science. It examines what scientific models are and what their function is. Reliance on models is pervasive in science, and scientists often need to construct models in order to explain or predict anything of interest at all. The diversity of kinds of models one finds in science – ranging from toy models and scale models to theoretical and mathematical models – has attracted attention not only from scientists, but also from philosophers, sociologists, and historians of science. This has given rise to a wide variety of case studies that look at the different uses to which models have been put in specific scientific contexts. By exploring current debates on the use and building of models via cutting-edge examples drawn from physics and biology, the book provides broad insight into the methodology of modelling in the natural sciences. It pairs specific arguments with introductory material relating to the ontology and the function of models, and provides some historical context to the debates as well as a sketch of general positions in the philosophy of scientific models in the process.

Autoren/Hrsg.

Gelfert, Axel

Inhaltsverzeichnis

1;Preface;6
2;Contents;10
3;1 Between Theory and Phenomena: What are Scientific Models?;12
3.1;1.1 Introduction;12
3.2;1.2 Models, Analogies, and Metaphor;16
3.3;1.3 The Syntactic View of Theories;20
3.4;1.4 The Semantic View;23
3.5;1.5 `Folk Ontology' and Models as Fictions;25
3.6;1.6 The Challenge from Scientific Practice;29
3.7;References;33
4;2 Scientific Representation and the Uses of Scientific Models;36
4.1;2.1 Models and Their Functions;36
4.2;2.2 Scientific Representation;37
4.3;2.3 The DDI Account of Model-Based Representation;44
4.4;2.4 Representation and Surrogate Reasoning: Su00E1rez's Inferential Account;46
4.5;2.5 Realism, Instrumentalism, and the Varied Uses of Models;49
4.6;References;52
5;3 Strategies and Trade-Offs in Model-Building;54
5.1;3.1 Strategies of Model-Building;54
5.2;3.2 The Case of Superconductivity: Ginzburg-Landau Approach and the BCS Model;56
5.2.1;3.2.1 Ginzburg and Landau's Phenomenological Approach;57
5.2.2;3.2.2 Bardeen, Cooper, and Schrieffer's Microscopic Model;60
5.2.3;3.2.3 How Phenomenological is the BCS Model?;62
5.3;3.3 The Hubbard Model: Constructing Many-Body Models;64
5.4;3.4 Modeling Dynamic Populations: The Lotka-Volterra Model;69
5.5;3.5 The Question of Trade-Offs: Origins of the Debate;72
5.6;3.6 Trade-Offs as a Demarcation Criterion?;75
5.7;3.7 Models in the Context of Application;78
5.8;References;80
6;4 Exploratory Uses of Scientific Models;82
6.1;4.1 Model-Based Understanding and the Tacit Dimension;82
6.2;4.2 On the Notion of `Exploration';85
6.3;4.3 Exploration and Experimentation;87
6.4;4.4 Exploratory Models;90
6.5;4.5 The Uses and Functions of Exploratory Models;94
6.5.1;4.5.1 Exploratory Models as Starting Points;95
6.5.2;4.5.2 Exploratory Models and Proof-of-Principle Demonstrations;96
6.5.3;4.5.3 Exploratory Models and Potential Explanations;98
6.5.4;4.5.4 Exploring the Suitability of the Target;104
6.6;4.6 Exploratory Modeling: Prospects and Caveats;105
6.7;References;108
7;5 Models as Mediators, Contributors, and Enablers of Scientific Knowledge;111
7.1;5.1 Models as Mediators;111
7.2;5.2 Mature Mathematical Formalisms as a Representational Resource;114
7.3;5.3 Models as Contributors;119
7.4;5.4 Models as Epistemic Tools;123
7.5;5.5 Models as Enablers of Scientific Knowledge;127
7.6;References;137
8;Index;140