We rely on science and other organized forms of inquiry to answer cardinal questions on issues varying from global warming and public health to the political economy. In my thesis, which is in the intersection of philosophy of science, social epistemology, and science and technology studies, I develop a social theory of knowledge that can help us tell when our beliefs and theories on such matters amount to knowledge, as opposed to mere opinion, speculation, or educated guess. The first two chapters discuss relevant shortcomings of mainstream analytic epistemology and the sociology of knowledge, respectively. Mainstream epistemology regards individuals, rather than communities, as the bearers of knowledge or justified belief. In Chapter 1, I argue that typically, only an epistemic community can collectively possess sufficient justification required for knowledge. In Chapter 2, I present a case study in computer science that militates against the sociological understating of knowledge as mere interest-based agreement. I argue that social interests alone cannot explain the unfolding of the events in this case. Rather, we must assume that knowledge is irreducible to social dynamics and interests. In Chapter 3, I begin my positive analysis of the social conditions for knowledge. I explore the question of when a consensus is knowledge based. I argue that a consensus is knowledge based when knowledge is the best explanation of the consensus. I identify three conditions – social diversity, apparent consilience of evidence, and meta agreement, for knowledge being the best explanation of a consensus. In Chapter 4, I illustrate my argument by analyzing the recent controversy about the safety of the drug Bendectin. I argue that the consensus in this case was not knowledge based, and hence the deference to consensus to resolve this dispute was unjustified. In chapter 5, I develop a new theory of the logical relations between evidence and social values. I identify three roles social values play in evidential reasoning and justification: They influence the trust we extend to testimony, the threshold values we require for accepting evidence, and the process of combining different sorts of evidence.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/27595 |
| Date | 13 June 2011 |
| Creators | Miller, Boaz |
| Contributors | Chakravartty, Anjan |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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