Publication
Title
Plausibility versus richness in mechanistic models
Author
Abstract
In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Cravers continuum of how-possibly, to how-plausibly, to how-actually models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanisms activities, not its entities. This point is illustrated with two examples of functional models.
Language
English
Source (journal)
Philosophical psychology. - Abington
Publication
Abington : 2013
ISSN
0951-5089
Volume/pages
26:1(2013), p. 139-152
ISI
000312533500008
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 12.04.2016
Last edited 23.06.2017