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A probabilistic analysis of causation

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GLYNN, Luke, 2010. A probabilistic analysis of causation. In: The British Journal for the Philosophy of Science. 62(2), pp. 343-392. ISSN 0007-0882. Available under: doi: 10.1093/bjps/axq015

@article{Glynn2010proba-14231, title={A probabilistic analysis of causation}, year={2010}, doi={10.1093/bjps/axq015}, number={2}, volume={62}, issn={0007-0882}, journal={The British Journal for the Philosophy of Science}, pages={343--392}, author={Glynn, Luke} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:bibliographicCitation>First publ. in: The British Journal for the Philosphy of Science ; 62 (2011), 2. - pp. 343-392</dcterms:bibliographicCitation> <dcterms:hasPart rdf:resource=""/> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:available rdf:datatype="">2013-05-31T22:25:04Z</dcterms:available> <dc:creator>Glynn, Luke</dc:creator> <dc:rights>terms-of-use</dc:rights> <dcterms:isPartOf rdf:resource=""/> <dcterms:title>A probabilistic analysis of causation</dcterms:title> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:language>eng</dc:language> <dc:contributor>Glynn, Luke</dc:contributor> <dcterms:issued>2010</dcterms:issued> <dc:date rdf:datatype="">2011-10-19T07:07:50Z</dc:date> <dcterms:rights rdf:resource=""/> <bibo:uri rdf:resource=""/> <dspace:hasBitstream rdf:resource=""/> <dcterms:abstract xml:lang="eng">The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that an examination of the structure of these problem cases suggests a different treatment, one which avoids the costs of extant probabilistic analyses.</dcterms:abstract> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> </rdf:Description> </rdf:RDF>

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