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Quitting CertaintiesA Bayesian Framework Modeling Degrees of Belief$
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Michael G. Titelbaum

Print publication date: 2012

Print ISBN-13: 9780199658305

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199658305.001.0001

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Applying CLF models to stories

Applying CLF models to stories

Chapter:
(p.55) 4 Applying CLF models to stories
Source:
Quitting Certainties
Author(s):

Michael G. Titelbaum

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199658305.003.0004

This chapter focuses on what exactly models in the Certainty-Loss Framework (CLF) say about agents’ degrees of belief. Developing the standard interpretation of CLF given in the previous chapter, it lays down explicit bridge principles relating CLF’s formal models to norms. Under this intepretation, CLF models indicate necessary but not sufficient evaluative requirements for rational consistency. The chapter considers objections to these evaluative requirements and exactly how idealized the notion of rationality involved needs to be. Finally, the chapter provides a model theory for CLF’s derivation system and considers alternative interpretations for the framework, such as interpretations on which CLF models represent imprecise probabilities (also known as “ranged” degrees of belief).

Keywords:   rationality, normativity, bridge principles, imprecise probabilities, idealization, Certainty-Loss Framework

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