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

本论文的研究项目是对南极臭氧“空洞”的发现进行历史和哲学上的调查，旨在建立科学模型，而不是理论，是科学的流行基础。研究人员打算通过对主要参与者进行口述历史访谈，为南极臭氧“空洞”的发现编写一份全面、客观的历史报告。这个项目与论文的另外两个部分有关。它将提供一个具体的背景，重新评估，提炼，也许挑战来自其他两个部分的一些发现，以及揭示理论的认知模型依赖和建模的认知自治。论文的另外两个部分，不直接支持这个项目侧重于非启发式的，基于模型的科学知识的认识论分析。正在发展和辩护的主张和发现挑战了许多关于理论和科学建模的公认和有影响力的哲学立场。第一部分考察了在阐明抽象理论、结构和物理系统之间的联系时使用量纲分析。这些联系是通过量纲分析将模型拟合到数据中来建立的。这种拟合既不是启发式的，也不是类比式的；因此，证明模型可以在理论知识的生产中非启发式地发挥作用。第二部分系统地论证了在当代遥感环境和更传统的受控实验室实验中，模型和建模对于数据的性质和收集都是内在的。这些问题将通过大气模拟的详细分析来处理，这是围绕全球变暖的争议的核心。已经产生了重要的结果，包括：(i)许多实验工作和计算机模拟的中心问题是区分数据中的真实效果和由与感兴趣的现象无关的效果产生的伪影。科学建模往往是作出这些决定的唯一有效手段。（iii）建模和实验设计之间的认知连续性是这样的，如果对建模的怀疑攻击是正确的，那么所有传统的科学实验实践和观察都同样无法产生关于世界的可靠知识主张。（iv）科学建模通常是非启发式的和认知创造性的。

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.