Authors
Aron Vallinder
London School of Economics (PhD)
Abstract
Traditional Bayesianism requires that an agent’s degrees of belief be represented by a real-valued, probabilistic credence function. However, in many cases it seems that our evidence is not rich enough to warrant such precision. In light of this, some have proposed that we instead represent an agent’s degrees of belief as a set of credence functions. This way, we can respect the evidence by requiring that the set, often called the agent’s credal state, includes all credence functions that are in some sense compatible with the evidence. One known problem for this evidentially motivated imprecise view is that in certain cases, our imprecise credence in a particular proposition will remain the same no matter how much evidence we receive. In this article I argue that the problem is much more general than has been appreciated so far, and that it’s difficult to avoid it without compromising the initial evidentialist motivation. _1_ Introduction _2_ Precision and Its Problems _3_ Imprecise Bayesianism and Respecting Ambiguous Evidence _4_ Local Belief Inertia _5_ From Local to Global Belief Inertia _6_ Responding to Global Belief Inertia _7_ Conclusion
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DOI 10.1093/bjps/axx033
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References found in this work BETA

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Citations of this work BETA

Imprecise Probabilities.Seamus Bradley - 2019 - Stanford Encyclopedia of Philosophy.
Updating as Communication.Sarah Moss - 2012 - Philosophy and Phenomenological Research 85 (2):225-248.
Imprecise Probabilities.Anna Mahtani - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 107-130.
Subjunctive Credences and Semantic Humility.Sarah Moss - 2013 - Philosophy and Phenomenological Research 87 (2):251-278.

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