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dc.contributor.authorOsimani, Barbara
dc.date.accessioned2021-08-04T10:11:41Z
dc.date.available2021-08-04T10:11:41Z
dc.date.issued2020
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/50312
dc.description.abstractIn this paper I analyse the dissent around evidence standards in medicine and pharmacology as a result of distinct ways to address epistemic losses in our game with nature and the scientific ecosystem: an “elitist” and a “pluralist” approach. The former is focused on reliability as minimisation of random and systematic error, and is grounded on a categorical approach to causal assessment, whereas the latter is more focused on the high context-sensitivity of causation in medicine and in the soft sciences in general, and favours probabilistic approaches to scientific inference, as better equipped for defeasibility of causal inference in such domains. I then present a system for probabilistic causal assessment from heterogenous evidence that makes justice of concerns from both positions, while also incorporating “higher order evidence” (evidence/information about the evidence itself) in hypothesis confirmation.en_US
dc.languageEnglishen_US
dc.subject.classificationbic Book Industry Communication::M Medicine::MM Other branches of medicine::MMG Pharmacologyen_US
dc.subject.otherUncertainty Management in Pharmacology, Causality,Medical Epistemology, evidence standards, random error, systematic error, extrapolation, relevance, biasen_US
dc.titleChapter 15 Epistemic Gains and Epistemic Gamesen_US
dc.title.alternativeReliability and Higher Order Evidence in Medicine and Pharmacologyen_US
dc.typechapter
oapen.identifier.doi10.1007/978-3-030-29179-2_15en_US
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5en_US
oapen.relation.isPartOfBook6dde7ba1-8654-4ccc-9249-6bef6c837290en_US
oapen.relation.isFundedBy178e65b9-dd53-4922-b85c-0aaa74fce079en_US
oapen.relation.isbn9783030291785en_US
oapen.collectionEuropean Research Council (ERC)en_US
oapen.pages28en_US
oapen.grant.number639276
oapen.grant.projectPhilPharm


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