published_or_final_version / Philosophy / Master / Master of Philosophy

Thesis--School of Advanced Airpower Studies, 1995. / Shipping list no.: 1998-0921-M. "August 1997." Also available via Internet from the Air University Press web site. Address as of 11/3/03: http://aupress.au.af.mil/SAAS%5FTheses/Pellegrini/pellegrini.pdf; current access is available via PURL.

M.A. / A pressing problem in contemporary political philosophy is how to accommodate difference justly in culturally diverse societies. A philosopher of science, Paul Feyerabend, has provided an unusual perspective on diversity. He argues that science and its philosophy provide the greatest threat to diversity. The aim of this thesis is to analyse and critically evaluate Paul Feyerabend's attempt to transform science, politics and philosophy to accommodate diversity better. This aim will be accomplished through a literature study of Feyerabend’s relevant texts, political philosophy on diversity, and the most significant philosophies of science. Feyerabend claims that scientific method, science’s dominant role in society, and philosophy, suppress freedom and marginalise diversity. Firstly, he argues that scientific method interferes with the freedom of scientists and the complexity of scientific practice. Secondly, he maintains that science’s dominance in society stifles non-scientific alternatives and the autonomy of citizens to choose between science and these alternatives. Thirdly, he argues that philosophy necessarily suppresses difference by associating knowledge with simple abstract theories, instead of the pluralism of the concrete world. Feyerabend’s political solution to accommodating diversity is to eradicate science’s dominance in society. He aspires to construct a free society that will regard science as equal to all other traditions, and that will increase the autonomy and freedom of both citizens and scientists by eliminating the principles and ideologies imposed on them by scientific and rationalist intellectuals. This dissertation will argue that Feyerabend has contributed to accommodating diversity better by identifying that science can interfere with difference. However, this thesis claims that, overall, Feyerabend is unsuccessful in his contribution to the politics of difference. In fact, his primary failure lies in his lack of sensitivity towards complexity and diversity. I will ii argue, firstly, that Feyerabend’s free society fails to accommodate diversity successfully. Secondly, I will argue that Feyerabend’s condemnation of philosophy is flawed: instead of necessarily suppressing diversity, philosophy can be successfully used to express difference. The conclusion of this thesis, thus, is that although Feyerabend contributes to our understanding of how to accommodate diversity better, his attempts to transform science, politics and philosophy are unsuccessful. / Prof. H.P.P. Lötter

While undeniably one of the central explanatory concepts in biology, fitness is deployed in an ambiguous or even inconsistent manner by evolutionary biologists as well as philosophers. This sort of foundational confusion is a plea for conceptual clarity and has, thereby, presented a wonderful opportunity for philosophers of science to ply their trade. After engaging with the topic, however, several influential philosophers of science (e.g., Mohan Matthen, Dennis Walsh, and Andre Ariew) and biologists (Richard Lewontin and Massimo Pigliucci) have reached the conclusion that biological fitness is not in fact the cause of natural selection but instead a mere statistical artifact or redescription of systematic transgenerational change. It is, as they see matters, a label best reserved for abstract trait types rather than the organisms that bear such traits. This poses a serious challenge to the working intuitions of most biologists and many philosophers of biology. Moreover, it is but one of many challenges to the explanatory and ontological primacy of natural selection in recent memory. For at least three decades, some practitioners in the burgeoning subdiscipline of evolutionary developmental biology have been outspoken in insisting that the tools of population biology are insufficient for describing or explaining observations of adaptive evolutionary change both past and present. In this dissertation, I examine these recent challenges to orthodox conceptions of fitness and natural selection, as well as the rejoinders given in defense. Ultimately, I defend a conception of fitness as a probabilistic dispositional property (i.e., a propensity) of token organisms that causes natural selection. / A Dissertation submitted to the Department of Philosophy in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2017. / November 15, 2017. / biological fitness, causation, evo-devo, natural selection, propensity / Includes bibliographical references. / Michael Ruse, Professor Directing Dissertation; Joseph Travis, University Representative; Michael Bishop, Committee Member; James Justus, Committee Member.

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature of complex systems in general. Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework.

In "A Critique of Two Objective Probability Theories," I examine two extensionalist approaches to the analysis of objective probability, arguing ultimately that neither can succeed as analyses of objective probability. Beginning with extensional frequency analyses, I first examine the limiting frequency interpretation of Reichenbach and Salmon, arguing that it is unacceptable as it (1) fails to handle the single case--providing no basis for assigning a value other than 0 or 1; and (2) fails to provide a unique value for the probability as a limit of an infinite sequence--the problem of randomness. I further argue that references to "natural sequences" as a means of avoiding these problems must fail due to an interesting difficulty derived from special relativity. Turning next to Kyburg's finite frequency interpretation, I claim that while it incorporates certain gains within the extensional approach, it still succumbs to variations of the same problems inherent in the Reichenbach/Salmon interpretation. Kyburg's proposal, furthermore, is too narrow, not sufficiently encompassing the concept of objective probability desired. I conclude with an argument to the effect that no extensional frequency interpretation is able to provide an acceptable analysis of scientific conceptions of chance. I next consider a "propensity" interpretation provided by Mellor, which purports to provide an extensionalist analysis of objective chance on the basis of partial beliefs--i.e., a personalist framework. I argue that this approach fails because the dispositional (propensity) basis is an ad hoc addendum to what turns out to be merely a personalist theory. I then consider various alterations of Mellor's approach, with the conclusion that no such personalist-based approach is viable as an analysis of objective probability. I also examine Mellor's notion of dispositions, arguing that it is too deterministic, and that it must be replaced by a statistical notion better adapted to probability. Finally, these several considerations are taken both as a motivation for intensional frequency and propensity approaches, and as identifying certain pitfalls that any approach must guard against. In view of these findings, a rough outline of what would constitute an acceptable intensional frequency or propensity interpretation is indicated.

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