Dissertation Research: Data, Theories, and Scientific Modeling: Discovery of the Antarctic Ozone 'Hole'

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This dissertation research project is an historical and philosophical investigation of the discovery of the Antarctic ozone "hole', that seeks to establish the claim that ~Scientific models, not theories, are epidemically foundational in science. The researcher intends to produce a comprehensive and objective history of the discovery of the Antarctic ozone "hole" by conducting oral history interviews with the key participants. This project relates to two other sections of the dissertation. It will provide a concrete context for reassessing, refining, and perhaps challenging some of the findings from the two other sections, as well as reveal the epistemic model dependency of theories and epistemic autonomy of modeling. The two other sections of the dissertation, not directly supported by this project focus on an epistemological analysis of non-heuristic, model-based scientific knowledge. The claims and findings being developed and defended challenge many accepted and influential philosophical positions regarding theories and scientific modeling. The first part examines the use of dimensional analysis in articulating the connections between abstract theories structure and physical systems. These connections are established by fitting models to data via dimensional analysis. This fitting is neither heuristic nor analogical; thus, demonstrating that models can function non-heuristically in the production of theoretical knowledge. The second part systematically demonstrates that models and modeling are intrinsic to the nature and collection of data both in contemporary remote-sensing contexts and in more traditional controlled laboratory experimentation. These issues are treated through a detailed analysis of atmospheric modeling central to controversies surrounding global warming. Important results have already been generated, including: (i) The central issue of much experimental work and computer simulation is differentiating real effects in data form artifacts produced by effect irrelevant to phenomena of interest. (ii) Scientific modeling often provides the only effective means for making these determinations. (iii) The epistemic continuities between modeling and experimental design are such that if skeptical attacks on modeling were correct, then all traditional scientific experimental practice and observation would be equally incapable of yielding reliable knowledge claims about the world. (iv) Scientific modeling is typically nonheuristic and epistemically creative.