Models as Mediators: Perspectives on Natural and Social Science

Last updated
Models as Mediators: Perspectives on Natural and Social Science
Editors Mary S. Morgan
Margaret Morrison
LanguageEnglish
Subjects Sociology of quantification
Philosophy of Science
Economics
Publisher Cambridge University Press
Publication date
1999
Pages401
ISBN 978-0521650977

Models as Mediators: Perspectives on Natural and Social Science [1] is a multi-author book edited by Mary S. Morgan and Margaret Morrison and published in 1999 by Cambridge University Press.

Contents

Synopsis

The volume looks at the working of models in the social and natural sciences, with a focus in economics and physics. [2] The book illustrate the concept of models as mediating between theory and the world and yet independent from both. [2] It offers a historical and philosophical discussion of what models are and of what models do, with detailed examples written by the same editors and scholars such as Ursula Klein, Marcel Boumans, R.I.G. Hughes, Mauricio Suárez, Geert Reuten, Nancy Cartwright, Adrienne van den Boogard and Stephan Hartmann.

Content

Models and theories are related, so that an evolution in the perception of what a scientific theory is also chances the perception of what models are. [2] The concept of scientific theory has moved from the 'received view' - whereby a theory can be seen as an axiomatic system to be dealt with in the context of the discipline of logic, to a new conception of theory as framed in therms of semantics, whereby models acquire a new prominence as 'fundamental unit of scientific theorizing, theories themselves being families of models'. [2] Most of the examples in the book are quite articulated and pertinent to either physics or economics, with one, offered by historian of science Ursula Klein, in Chemistry.

The introduction written by Margaret Morrison and Mary S. Morgan discusses the syntactic versus semantic view of theories and how these consider models. The second chapter by the same authors entitled 'Models as mediating instruments' — a key chapter in the economy of the volume, [2] introduces the unifying theme of the work: the concept of models as mediators between theory and world. Models may represent 'some aspect of our theories about the world'. [1] {rp|11}. While they may act as mediators between theory and world, they are situated outside the theory-world axis'. [1] {rp|11}

We believe there is a significant connection between the autonomy of models and their ability to function as instruments. It is precisely because models are partially independent of both theories and the world that they have this autonomous component and so can be used as instrument of exploration in both domains. [1] : 10 

The chapter also details what has been called a 'functionalist' [2] articulation of the difference between models and theory, namely in four functions served by models: the first is how they are constructed deriving elements from one or more theories, other models, and the world. The second function is the use of models as instruments for the exploration and development of theory and or for the design of better experiments. The third is their use to 'represent' beyond what a theory alone can offer. The fourth function is the capacity of the model to enhance learning - though this function is also present in the preceding three steps. [1] : 10–37  Morrison and Morgan emphasize that models can thus be regarded as 'technologies for investigation' — one learns by manipulating and playing with them. [3] Models 

have the quality of a technology — the power of the model only becomes apparent in the context of its use. [1] : 12 

Chapter 3 by Margaret Morrison, entitled 'Models as autonomous agents', elaborates on the autonomy of models with example from physics. Chapter 4 'Built in justification' is from Marcel Boumans. Using examples from economics Boumans shows that models 'integrate a broader range of ingredients than only theory and data': these are theoretical notions, mathematical concepts and techniques, stylized facts, empirical data, policy views, analogies, metaphors. [1] : 93  [3]

Chapter 5 from R.I.G. Hughes, discusses how the development of computers and simulation changed the relation between models and theory. It was the use of computer simulation that permitted the Ising model to be accepted. In Chapter 6 by Ursula Klein chemical formulae as developed by Jöns Jacob Berzelius in 1813 are presented as 'paper tools' permitting representation and the construction of models. In Chapter 6 Mauricio Suárez discusses how an essential feature of models as mediators is to possibly replace the phenomenon itself in becoming the focus of scientific research, and illustrate this feature with an example from superconductivity in physics.

Chapter 8 from Geert Reuten, 'Knife edge caricature modelling: the case of Marx's reproduction schema' is a 'detailed historical reconstruction' or exegesis of Marxian economics, with little general theory of models. [2] Chapter 9 from Nancy Cartwright 'Models and the limit of theory: quantum Hamiltonians and the BCS model of superconductivity' distinguishes what she call representative models that are accurate to the phenomena from more theory-internal models, models that bridge element of the theory with one another, and that are named interpretative models, especially in fields such as quantum mechanics, quantum electrodynamics, classical mechanics and classical electromagnetic theory. [1] : 242–243  For example, an abstract concept such as force 'can only exist in particular mechanical models'. [1] : 257 

Adrienne van den Boogard notes that 'the model is also a social and political device', [1] : 283  and shows how institutions can be 'influenced (but were also conditioned by) the usage of different models and statistical techniques.' [2] van den Boogard provides an illustration based on economic models and index numbers developed in the Netherlands. In discussing for example unemployment statistics:

Even the most simple-looking figure, i.e. absolute numbers, reflect an institutional structure, embody work of people (filling questionnaires) as consequence of which the actual figures represent a specific group of unemployed, namely those who found their job via the official employment offices.

For Stephan Hartmann empirical adequacy and logical consistency are not the only criteria of models acceptance. [1] : 326  The story told by a model matters to its acceptability, and thus to its function and quality. The argument is developed in the final chapter of the volume entitled 'Models and stories in hadron physics'.

Reception

One review notes that while the title appears to promise a unified theory of models the chapters point instead to a universe of possible ways to characterize the nature and use of models. [2] Acting as mediators, models are partly independent from both theory and world, and this independence, that ensures the versatility of 'models as autonomous agents', [1] : 10  is also the reason why they resist an attempt to a unified 'theory of models'. [2] 

But the individual chapters make clear why Models as Mediators cannot possibly offer such a theory: the models dealt with in the book are so diverse and disparate that they cannot really be covered by a general description. [2]

The 'functionalist' — rather than philosophical approach of the work, i.e. more about what a model does than what a model is, leaves several questions unanswered (or answered in different ways in different chapters). [2] Furthermore, the examples are quite technical and detailed, not easy to read for the non initiated. [2] Important epistemological questions left open concerns for example why individual models are constructed with the particular degrees of independence from theory and experiment. [4] Being focused on models in physics, chemistry and economics, the book leaves out biological models. [3]

The book lays the basis for a research programme for studying models from the point of view of scientific practice providing 'a potential bridge between philosophical theorising and the more practice-oriented approach of STS'. [5]

See also

Related Research Articles

A mathematical model is an abstract description of a concrete system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in applied mathematics and in the natural sciences and engineering disciplines, as well as in non-physical systems such as the social sciences. It can also be taught as a subject in its own right.

The following outline is provided as an overview of and topical guide to physics:

A paradigm shift is a fundamental change in the basic concepts and experimental practices of a scientific discipline. It is a concept in the philosophy of science that was introduced and brought into the common lexicon by the American physicist and philosopher Thomas Kuhn. Even though Kuhn restricted the use of the term to the natural sciences, the concept of a paradigm shift has also been used in numerous non-scientific contexts to describe a profound change in a fundamental model or perception of events.

<span class="mw-page-title-main">Determinism</span> Philosophical view that events are determined by prior events

Determinism is the philosophical view that all events in the universe, including human decisions and actions, are causally inevitable.

An interpretation of quantum mechanics is an attempt to explain how the mathematical theory of quantum mechanics might correspond to experienced reality. Although quantum mechanics has held up to rigorous and extremely precise tests in an extraordinarily broad range of experiments, there exist a number of contending schools of thought over their interpretation. These views on interpretation differ on such fundamental questions as whether quantum mechanics is deterministic or stochastic, local or non-local, which elements of quantum mechanics can be considered real, and what the nature of measurement is, among other matters.

<span class="mw-page-title-main">Uncertainty</span> Situations involving imperfect or unknown information

Uncertainty or Incertitude refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable or stochastic environments, as well as due to ignorance, indolence, or both. It arises in any number of fields, including insurance, philosophy, physics, statistics, economics, finance, medicine, psychology, sociology, engineering, metrology, meteorology, ecology and information science.

Scientific realism is the view that the universe described by science is real regardless of how it may be interpreted. A believer of scientific realism takes the universe as described by science to be true, because of their assertion that science can be used to find the truth about both the physical and metaphysical in the Universe.

Econophysics is a non-orthodox interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics, usually those including uncertainty or stochastic processes and nonlinear dynamics. Some of its application to the study of financial markets has also been termed statistical finance referring to its roots in statistical physics. Econophysics is closely related to social physics.

<span class="mw-page-title-main">Operationalization</span> Part of the process of research design

In research design, especially in psychology, social sciences, life sciences and physics, operationalization or operationalisation is a process of defining the measurement of a phenomenon which is not directly measurable, though its existence is inferred from other phenomena. Operationalization thus defines a fuzzy concept so as to make it clearly distinguishable, measurable, and understandable by empirical observation. In a broader sense, it defines the extension of a concept—describing what is and is not an instance of that concept. For example, in medicine, the phenomenon of health might be operationalized by one or more indicators like body mass index or tobacco smoking. As another example, in visual processing the presence of a certain object in the environment could be inferred by measuring specific features of the light it reflects. In these examples, the phenomena are difficult to directly observe and measure because they are general/abstract or they are latent. Operationalization helps infer the existence, and some elements of the extension, of the phenomena of interest by means of some observable and measurable effects they have.

In quantum mechanics, the measurement problem is the problem of definite outcomes: quantum systems have superpositions but quantum measurements only give one definite result.

Holism in science, holistic science, or methodological holism is an approach to research that emphasizes the study of complex systems. Systems are approached as coherent wholes whose component parts are best understood in context and in relation to both each other and to the whole. Holism typically stands in contrast with reductionism, which describes systems by dividing them into smaller components in order to understand them through their elemental properties.

<span class="mw-page-title-main">Scientific modelling</span> Scientific activity that produces models

Scientific modelling is an activity that produces models representing empirical objects, phenomena, and physical processes, to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate. It requires selecting and identifying relevant aspects of a situation in the real world and then developing a model to replicate a system with those features. Different types of models may be used for different purposes, such as conceptual models to better understand, operational models to operationalize, mathematical models to quantify, computational models to simulate, and graphical models to visualize the subject.

<span class="mw-page-title-main">Theoretical physics</span> Branch of physics

Theoretical physics is a branch of physics that employs mathematical models and abstractions of physical objects and systems to rationalize, explain, and predict natural phenomena. This is in contrast to experimental physics, which uses experimental tools to probe these phenomena.

<span class="mw-page-title-main">Branches of physics</span> Overview of the branches of physics

Physics is a scientific discipline that seeks to construct and experimentally test theories of the physical universe. These theories vary in their scope and can be organized into several distinct branches, which are outlined in this article.

In the philosophy of science, structuralism asserts that all aspects of reality are best understood in terms of empirical scientific constructs of entities and their relations, rather than in terms of concrete entities in themselves.

Roman Frigg is a Swiss philosopher and professor at the Department of Philosophy, Logic and Scientific Method at the London School of Economics, where he also directs its Centre for Philosophy of Natural and Social Science. He is also visiting professor at the Munich Centre for Mathematical Philosophy at Ludwig Maximilian University. In 2016 he was awarded the Friedrich Wilhelm Bessel Research Award.

Quantum social science is an emerging field of interdisciplinary research which draws parallels between quantum physics and the social sciences. Although there is no settled consensus on a single approach, a unifying theme is that, while the social sciences have long modelled themselves on mechanistic science, they can learn much from quantum ideas such as complementarity and entanglement. Some authors are motivated by quantum mind theories that the brain, and therefore human interactions, are literally based on quantum processes, while others are more interested in taking advantage of the quantum toolkit to simulate social behaviours which elude classical treatment. Quantum ideas have been particularly influential in psychology but are starting to affect other areas such as international relations and diplomacy in what one 2018 paper called a "quantum turn in the social sciences".

The sociologyof quantification is the investigation of quantification as a sociological phenomenon in its own right.

Margaret C. "Margie" Morrison was a Canadian philosopher. She worked in the philosophy of science. She was elected to the Leopoldina in 2004, the Royal Society of Canada in 2015, the Académie Internationale de Philosophie des Sciences in 2016, and received a Guggenheim Fellowship in 2017.

Emmanuel Haven is an academic, author and researcher. He previously held a personal Chair at the University of Leicester (UK) and is currently full professor and the Dr. Alex Faseruk Chair in Financial Management at the Faculty of Business Administration, Memorial University.

References

  1. 1 2 3 4 5 6 7 8 9 10 11 12 Morgan, M. S., Morrison, M., eds. (28 November 1999). Models as Mediators: Perspectives on Natural and Social Science. Cambridge University Press. ISBN   978-0-521-65097-7.
  2. 1 2 3 4 5 6 7 8 9 10 11 12 13 Guala, F., Psillos, S. (October 2001). "Models as Mediators. Perspectives on Natural and Social Science, Mary S. Morgan and Margaret Morrison (eds.). Cambridge University Press, 1999, xi + 401 pages". Economics & Philosophy. 17 (2). Cambridge University Press: 275–294. doi:10.1017/S0266267101230272. ISSN   1474-0028.
  3. 1 2 3 Petersen, A. C. (1 October 2000). "Models as Technological Artefacts". Social Studies of Science. 30 (5). SAGE Publications Ltd: 793–799. doi:10.1177/030631200030005006. ISSN   0306-3127.
  4. ↑ McCoy, C. D., Massimi, M. (1 January 2018). "Simplified models: a different perspective on models as mediators". European Journal for Philosophy of Science. 8 (1): 99–123. doi:10.1007/s13194-017-0178-0. hdl: 20.500.11820/ee6c3398-2777-40d9-bc89-a5d1d9c927cf . ISSN   1879-4920.
  5. ↑ Knuuttila, T. (2005), Models as epistemic artefacts: Toward a non-representationalist account of scientific representation (PDF)
  6. ↑ Frigg, R., Hartmann, S. (27 February 2006). "Models in Science". Stanford Enciclopedia of Philosophy. Retrieved 28 January 2024.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.