Vague Credence.
It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one's lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which a...
| Published in: | Synthese Vol. 194; no. 10; pp. 3931 - 3955 |
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| Format: | Article |
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Springer Nature
Oct2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=126748637&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 126748637 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Oct2017 vid: 194 iid: 10 pid: 237 pub: Springer Nature artinfo: ui: 126748637 10.1007/s11229-015-0782-5 ppf: 3931 ppct: 24 formats: fmt: @attributes: type: P size: 526KB tig: atl: Vague Credence. aug: au: Lyon, Aidan su: Probability theory Mathematics Statistical decision making Vagueness (Philosophy) Vagueness doctrine (Constitutional law) sug: subj: Probability theory Mathematics Statistical decision making Vagueness (Philosophy) Vagueness doctrine (Constitutional law) keyword: Aggregation Credence Degree of belief Imprecise Indeterminate Subjective probability Vagueness ab: It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one's lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which are often (if not always) vague to some degree. I show that by combining the two models into one model, and understanding that model as a model of vague credence, a natural interpretation arises that suggests a hypothesis concerning how we can improve the accuracy of aggregate credences. I present empirical results in support of this hypothesis. I also discuss how this modeling interpretation of imprecise probabilities bears upon a philosophical objection that has been raised against them, the so-called inductive learning problem. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2017. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2017 holdings: @attributes: islocal: N |
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