Re-presenting Scientific Representation Roman Frigg London School of Economics Thesis submitted to the University of London for the completion of the degree of a Doctor of Philosophy September 2003 UMI Number: U185091 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Dissertation Publishing UMI U185091 Published by ProQuest LLC 2014. Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 S poirncALOP 1(0 AND Th£S£S F SIS'? I O I Abstract It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? Surprisingly, this issue has hardly been recognised, much less seriously discussed. In the first part, I introduce the problem of scientific representation and argue for its importance. In the second part, I provide a critique of the current orthodoxy, the semantic view of theories. Though writers in this tradition do not explicitly address the issue of scientific representation, the semantic view implies that a model represents by being isomorphic or, in another version, similar to its target. I argue that this view faces insurmountable problems because both isomorphism and similarity are notions too weak to endow a model with representational power. In the third part, I develop a theory of representation that overcomes the shortcomings of the semantic view. The leading idea consists in taking representation to be explained in terms of three relations: denotation, display and designation. A model denotes its target system in roughly the same way in which a name denotes its bearer. At the same time it displays certain aspects, that is, it possesses these aspects and a user of the model thematises them. Finally, an aspect of the model designates an aspect of the target if the former stands for the latter and a specification of how exactly the two relate is provided. 2 For Mum and Dad Contents Part I - Scientific Representation as a Philosophical Problem 1. Models and the Three Conundrums of Scientific Representation ........... 8 1. Models Matter - A Brief Survey ................................................................. 8 2. Description versus Representation .......................................................... 10 3. The Three Conundrums of Scientific Representation ............................. 13 4. Taking Stock........................................................................................... 17 5. Why Bother? ........................................................................................... 19 6. Aims and Plan ......................................................................................... 20 Part II - Why Current Accounts are Blind Alleys 2. Strictures on Structures ...............................................................................23 1. The Structuralist Conception of Models ....................................................23 2. Structuralism and the Enigma of Representation .......................................29 (a) Isomorphism has the wrong formal properties .................................... 30 (b) Isomorphism is not sufficient for representation..................................32 (c) Multiple realisability ............................................................................ 32 (d) Identity conditions for models.............................................................. 36 Where does representational power come from?..................................... 36 3. Structuralism and the Problem of Quomodity............................................40 4. Amended Versions: Why They Do Not Fare Better ..................................42 3. Further Strictures on Structures .................................................................45 1. Introduction ................................................................................................45 2. Why One Cannot Have Structures All the Way Down..............................46 The argument: structures are not the whole story ................................... 46 Specific and unspecific structures............................................................. 46 Different notions of abstraction............................................................... 49 Abstract Concepts .................................................................................... 50 The abstractness of structure ................................................................... 53 Conclusion............................................................................................... 56 Possible responses................................................................................... 57 A qualification: a hierarchy of structures - but not all the way down ! ... 60 3. The Chimera of the One and Only Structure of Reality ........................... 61 There is not such thing as the one and only structure o f a target system . 61 Newman's theorem .................................................................................. 63 A starting point: objects o f everyday experience..................................... 64 4 A continuation: the methane molecule .......................................................64 Another continuation: the solar system ..................................................... 67 Logistic growth in ecological models ........................................................67 A final remark ......................................................................................... 68 4. Counter: This Is Nonsense - All We Need Is a Data M odel ......................69 5. Conclusion: Structures and Descriptions Go in Tandem ........................... 75 4. Putting Similarity into Perspective ........................................................... 79 1. Models and Similarity 79 • 2. Similarity and the Enigma of Representation .......................................... 80 3. Similarity and the Problem of Quomodity ............................................... 81 Part III - Re-Presenting Scientific Representation 5. What Are Models? ..................................................................................... 86 1. Introduction ............................................................................................. 86 2. Models as Imagined Objects .................................................................... 87 3. The Descriptivist Objection ..................................................................... 90 4. A Faster Route to Imagined Models ........................................................ 96 5. Other Kinds of Models .............................................................................. 98 Material Models ........................................................................................ 99 Equations ............................................................................................... 100 Summary ............................................................................................... 101 5. A Brief Remark on Models and Similarity .......................................... 102 6. On Scientific Aboutness........................................................................... 103 1. Introduction ............................................................................................ 103 2. ‘Naturalness* and the Acquisition of Knowledge .................................. 104 3. The Intentional Character of Scientific Representation ......................... 108 7. Facing the Enigma of Representation ..................................................... 119 1. Introduction ........................................................................................... 119 2. Scientific Representation - The Elements ............................................ 119 Heuristic considerations and the overall picture .................................. 120 T-Denotation......................................................................................... 125 Display ................................................................................................... 128 Designation............................................................................................ 133 Interlude: representation and intentionality ......................................... 135 Learning from models - a two stage approach ..................................... 136 A first simple example: samples ............................................................ 138 A second simple example: measuring air resistance in the wind tunnel 139 A third example: cell differentiation..................................................... 140 3. Linking ................................................................................................... 141 Linking, methodological naturalism, and the problem of quomodity ... 141 Identity and Sampling........................................................................... 144 Idealisation: