PhilSci Archive

Informative Models: Idealization and Abstraction

Suárez, Mauricio and Bolinska, Agnes (2021) Informative Models: Idealization and Abstraction. [Preprint]

This is the latest version of this item.

[img]
Preview
Text
Informative Models_v2021.pdf

Download (368kB) | Preview

Abstract

Mauricio Suárez and Agnes Bolinska apply the tools of communication theory to scientific modelling in order to characterize the informational content of a scientific model. They argue that when represented as a communication channel, a model source conveys information about its target, and that such representations are therefore appropriate whenever modelling is employed for informational gain. They then extract two consequences. First, the introduction of idealizations is akin in informational terms to the introduction of noise in a signal; for in an idealization we introduce ‘extraneous’ elements into the model that have no correlate in the target. Second, abstraction in a model is informationally equivalent to equivocation in the signal; for in an abstraction we ‘neglect’ in the model certain features that obtain in the target. They then conclude becomes possible in principle to quantify idealization and abstraction in informative models, although precise absolute quantification will be difficult to achieve in practice.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Suárez, Mauriciomsuarez@filos.ucm.es0000-0002-2842-3641
Bolinska, Agnesamb273@cam.ac.uk0000-0002-6133-6734
Additional Information: Appeared as Chapter 3 in A. Cassini and J. Redmond, eds. (2021), Idealizations in Science: Artifactual and Fictional Approaches, Springer, pp. 71-85.
Keywords: Information – Idealization – Abstraction - Content
Subjects: General Issues > History of Philosophy of Science
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Depositing User: Prof Mauricio Suárez
Date Deposited: 30 Oct 2023 02:10
Last Modified: 30 Oct 2023 02:10
Item ID: 22720
Official URL: https://link.springer.com/chapter/10.1007/978-3-03...
DOI or Unique Handle: 10.1007/978-3-030-65802-1_3
Subjects: General Issues > History of Philosophy of Science
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
Date: 28 May 2021
URI: https://philsci-archive.pitt.edu/id/eprint/22720

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item