PhilSci Archive

Justifying the Norms of Inductive Inference

Vassend, Olav Benjamin (2019) Justifying the Norms of Inductive Inference. British Journal for the Philosophy of Science. ISSN 1464-3537

This is the latest version of this item.

[img]
Preview
Text
Justifying the norms of inductive inference BJPS final version.pdf

Download (132kB) | Preview

Abstract

Bayesian inference is limited in scope because it cannot be applied in idealized contexts where none of the hypotheses under consideration is true and because it is committed to always using the likelihood as a measure of evidential favoring, even when that is inappropriate. The purpose of this paper is to study inductive inference in a very general setting where finding the truth is not necessarily the goal and where the measure of evidential favoring is not necessarily the likelihood. I use an accuracy argument to argue for probabilism and I develop a new kind of argument to argue for two general updating rules, both of which are reasonable in different contexts. One of the updating rules has standard Bayesian updating, Bissiri et al.'s (2016) general Bayesian updating, and Vassend's (2019b) quasi-Bayesian updating as special cases. The other updating rule is novel.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Vassend, Olav Benjaminvassend@ntu.edu.sg0000-0002-5964-8835
Keywords: Inductive inference Bayesian inference Bayesianism Statistical inference Philosophy of statistics General philosophy of science Conditionalization
Subjects: General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Depositing User: Olav Vassend
Date Deposited: 24 Dec 2021 02:57
Last Modified: 24 Dec 2021 02:57
Item ID: 16910
Journal or Publication Title: British Journal for the Philosophy of Science
Official URL: https://www.journals.uchicago.edu/doi/abs/10.1093/...
DOI or Unique Handle: https://doi.org/10.1093/bjps/axz041
Subjects: General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Date: 1 October 2019
ISSN: 1464-3537
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/16910

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item