Causes as deviations from actual standards: a perspectival account of causation

Georgina Statham

Research output: ThesisMaster's Thesis

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Abstract

This thesis defends an account of a kind of token causal judgement that is common in everyday discourse, according to which causes are deviations from the normal course of evolution of a system. The account is based on a theory of causation developed by Peter Menzies, which I reinforce with a notion of normal defined by Sarah McGrath. McGrath claims that on the relevant sense of 'normal', events (or states) are normal if they adhere to certain actual standards, which can be descriptive or normative. Combining Menzies' account of causation with McGrath's notion of normal results in an account (which I call the 'Menzies–McGrath model') according to which token causes are deviations from the normal course of evolution of systems that are governed by actual standards. I argue that the Menzies–McGrath model is not consistent with a position that I call the 'natural network model'—a metaphysical picture that underpins most of the accounts of causation that have recently been defended. According to the natural network model, the causal history of the universe consists of a single network of events and two-place causal relations, to which true causal judgements directly refer. I defend an alternative metaphysical picture, according to which the truth values of token causal judgements are relative to the kinds of systems described above. That is, to systems that are open to intervention, and governed by actual standards. Which kind of system is relevant to a particular causal judgement is determined by the purpose of the individual (or group) making the judgement—that is, by what I call a 'purpose-dependent perspective'. The truth values of token causal judgements are thus not completely mind-independent, but perspectival.
Original languageEnglish
QualificationMasters
Publication statusUnpublished - 2013

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