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dc.contributor.advisorRobert Stalnaker.en_US
dc.contributor.authorHenderson, Leahen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Linguistics and Philosophy.en_US
dc.date.accessioned2011-04-25T15:54:24Z
dc.date.available2011-04-25T15:54:24Z
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/62410
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2010.en_US
dc.description"September 2010." Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 127-133).en_US
dc.description.abstractThis thesis consists of three papers on the nature of scientific theories and inference. In many cases, scientific theories can be regarded as organized into hierarchies, with higher levels sometimes called 'paradigms', and lower levels encoding more specific or concrete hypotheses. The first chapter uses hierarchical Bayesian models to show that the assessment of higher level theories may proceed by the same Bayesian principles as the assessment of more specific hypotheses. It thus shows how the evaluation of higher level theories can be evidence-driven, despite claims to the contrary by authors such as Kuhn. The chapter also discusses how hierarchical Bayesian models may help to resolve certain issues for Bayesian philosophy of science, particularly how to model the introduction of new theories. The second chapter discusses the relationship between Inference to the Best Explanation (IBE) and Bayesianism. Van Fraassen has raised the concern that the explanatory considerations in IBE go beyond the Bayesian formalism, making IBE incompatible with Bayesianism. The response so far has been that the explanatory considerations can be accommodated within the Bayesian formalism by stipulating that they should constrain the assignment of the probabilities. I suggest a third alternative, which is that the extra explanatory considerations have their origins in the relationship between higher and lower level theories and can be modeled in Bayesian terms without directly constraining the probabilities. The third chapter discusses an aspect of the debate over scientific realism. The No Miracles argument and the Pessimistic Induction are often seen as the primary arguments for and against scientific realism. Yet recently it has been alleged that both of these arguments commit the base-rate fallacy. I argue that both arguments can be formulated in a non-fallacious manner, so neither should be dismissed on the grounds of faulty form alone.en_US
dc.description.statementofresponsibilityby Leah Henderson.en_US
dc.format.extent133 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectLinguistics and Philosophy.en_US
dc.titleFramework theories in scienceen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Linguistics and Philosophy.en_US
dc.identifier.oclc710978844en_US


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