%0 Journal Article %J PHILOSOPHICAL PSYCHOLOGY %D 2013 %T Plausibility versus richness in mechanistic models %A Gervais, Raoul %A Weber, Erik %X

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 Craver's 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 mechanism's activities, not its entities. This point is illustrated with two examples of functional models.

%B PHILOSOPHICAL PSYCHOLOGY %V 26 %P 139–152 %G eng %R http://dx.doi.org/10.1080/09515089.2011.633693