Suárez, Mauricio and Bolinska, Agnes (2021) Informative Models: Idealization and Abstraction. [Preprint]
This is the latest version of this item.
|
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: |
Available Versions of this Item
-
Informative Models: Idealization and Abstraction. (deposited 27 Oct 2023 01:03)
- Informative Models: Idealization and Abstraction. (deposited 30 Oct 2023 02:10) [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 |