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

Preview

Text Informative Models_v2021.pdf Download (360kB) | 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 that it 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:	Creators Email ORCID Suárez, Mauricio msuarez@filos.ucm.es 0000-0002-2842-3641 Bolinska, Agnes amb273@cam.ac.uk 0000-0002-6133-6734
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:	11 Dec 2023 00:31
Last Modified:	11 Dec 2023 00:31
Item ID:	22830
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/22830

Available Versions of this Item

• Informative Models: Idealization and Abstraction. (deposited 11 Dec 2023 00:31) [Currently Displayed]

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item