Jones, Nicholaos (2006) Resolving the Bayesian Problem of Idealization. In: UNSPECIFIED.

Preview

PDF Jones_-_Bayesian_Idealization.pdf Download (146kB)

Abstract

In "Bayesian Confirmation of Theories that Incorporate Idealizations", Michael Shaffer argues that, in order to show how idealized hypotheses can be confirmed, Bayesians must develop a coherent proposal for how to assign prior probabilities to counterfactual conditionals. This paper develops a Bayesian reply to Shaffer's challenge that avoids the issue of how to assign prior probabilities to counterfactuals by treating idealized hypotheses as abstract descriptions. The reply allows Bayesians to assign non-zero degrees of confirmation to idealized hypotheses and to capture the intuition that less idealized hypotheses tend to be better confirmed than their more idealized counterparts.

---

Export/Citation:

EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL

Social Networking:

Share |

---

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Creators:	Creators Email ORCID Jones, Nicholaos
Keywords:	abstraction, Bayesian, confirmation, idealization
Subjects:	General Issues > Confirmation/Induction General Issues > Models and Idealization
Depositing User:	Nicholaos Jones
Date Deposited:	18 Dec 2006
Last Modified:	07 Oct 2010 15:14
Item ID:	3101
Subjects:	General Issues > Confirmation/Induction General Issues > Models and Idealization
Date:	2006
URI:	https://philsci-archive.pitt.edu/id/eprint/3101

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item