Classifications are useful and efficient. We group things into kinds to facilitate the acquisition and transmission of important, often tacit, information about a particular entity qua member of some kind. Whilst it is universally acknowledged that classifications are useful, some scientific classifications (e.g. chemical elements) are held to higher epistemic standards than folk classifications (e.g. bugs). Scientific classifications in terms of 'natural kinds' are considered to be more reliable and successful because they are highly projectible and support law-like and inductive generalisations. What counts as a natural kind is, however, controversial: according to essentialists (e.g. Putnam, Kripke, Ellis) natural kinds are mind-independent and possess essential characteristics; according to promiscuous realists (e.g. Dupre ) there are 'countless legitimate, objectively grounded ways of classifying objects in the world'; and according to scientific realists (e.g. Boyd, Psillos) natural kinds are grounded in the 'causal structure of the world'. More specifically, realism about kinds can be understood as a commitment to the existence of natural divisions (kinds) in the world that we come to know as a result of mature scientific investigation into the nature of such kinds. Realism about natural kinds is supported and articulated in terms of three main arguments, metaphysical, semantical, and epistemological. In the first part of my thesis I offer a sustained and systematic investigation of these three main arguments, with their respective promises and prospects for the viability of realism about kinds and I find them wanting, whilst in the second part of the thesis I pursue an unexplored line of inquiry regarding natural kinds and propose a mild realism about natural kinds via the ontology of real patterns.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:756704 |
Date | January 2018 |
Creators | Creţu, Ana-Maria |
Contributors | Richmond, Alasdair ; Massimi, Michela |
Publisher | University of Edinburgh |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/1842/31423 |
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