Thesis (doctoral)--Freie Universität Berlin, 2005. / Includes bibliographical references (p. [260]-263).

Gregory Bateson's research spanned many fields. The critical literature on him is mostly limited to assessments of his work within anthropology, psychology, and ethology. This study assesses Bateson's contribution to the methodology of the behavioral sciences generally. It proceeds by applying his methods to the ancient question, "Why does man pursue virtue?" and to its modern rephrasing in terms of excellence or achievement. Bateson himself only touched on this question without answering it. To evaluate Bateson's methodological approach against other approaches in the behavioral sciences, this study examines how other thinkers have explained achievement, using Bateson's tools and methods to critique or restate their conclusions. Major positions examined include those of Plato, Aristotle, Descartes, Spinoza, Nietzsche, Freud, Skinner, and McClelland. The principle conclusion drawn from this study is that Bateson's approach accounts for earlier explanations of achieving behavior within a broader framework suggesting new insights with more practical applications. Its success in explaining achievement argues for its general significance within the behavioral sciences. The approach involves a fundamental rethinking of what Aristotle called "formal causation." Cybernetics, information theory, organization theory and the other new mathematical theories comprising the cognitive sciences all purport to explain as well as describe our world. Bateson's work helps explain how this is possible. Bateson's essential contribution is his contextual theory of learning, which directly challenges the associational theory of learning that underlies most modern empirical research in the behavioral sciences. Bateson explains phenomena as diverse as character development and creativity, mammalian play and certain forms of schizophrenia in terms of hierarchies of context and the conflicts between them. And he does so within the generally accepted parameters of evolutionary theory that informs our modern understanding of biology and behavioral science. It is a major achievement and, as a first attempt to comprehend the foundations of a cognitive science still in its fledgling stages, will likely be appreciated more as time goes on.

In my thesis, I argue that the philosophical and psychological study of concept-learning mechanisms has failed to take the diversity of learning mechanisms into account, and that consequently researchers should embrace a new way of thinking about concept learning: `concept learning' as a class of psychological mechanisms is not a natural kind lending itself to unified study and should be eliminated. To arrive at this, I discuss several concept-learning models that attempt to overcome Jerry Fodor's challenge and base my judgement on the plurality of feasible concept-learning mechanisms and on criteria for theoretical notions from the philosophy of science. Chapter 1 serves as an introduction to the topic `concept learning' and highlights its importance as a research topic in the study of the mind. I argue that a mechanistic understanding of the shape of concept learning is best suited to explain the phenomena, in line with the recent resurgence of mechanism-based explanation in the philosophy of mind. As the main challenge to the idea that concepts can be learnt, I proceed to set up Fodor's challenge for concept learning in Chapter 2. This challenge is the idea that concepts cannot be learnt given the logically possible mechanisms of concept learning. I lay out the argumentative structure and background assumptions that support Fodor's argument, and propose to scrutinise his empirically based premise most closely in my thesis: this empirically based premise is that the only possible mechanism of concept learning is the process of forming and testing hypotheses. As replies to Fodor's challenge, I discuss Perceptual Learning (R. Goldstone), Perceptual Meaning Analysis (J. Mandler), Quinean Bootstrapping (S. Carey), pattern-governed learning (W. Sellars), joint-attentional learning (M. Tomasello), and the Syndrome-Based Sustaining Mechanism Model (E. Margolis and S. Laurence). I argue that almost every mechanism I discuss has some leverage against Fodors argument, suggesting that there may be a wide variety of non-hypothesis-based concept-learning mechanisms. The final chapter of my thesis, Chapter 7, takes a step back and reviews the fate of the notion of concept learning in light of the diverse set of learning mechanisms brought up in my thesis. My first and main worry is that it is questionable whether the previously discussed mechanisms of concept learning share many scientifically relevant properties that would justify seeing them as instances of the natural kind 'concept learning mechanism'. I argue that the substantiation of this worry would necessitate the elimination of 'concept learning' and 'concept-learning mechanism' as terms of the cognitive sciences. The chapter lays out the argumentative structure on which Concept Learning Eliminativism (CLE) rests, along with a discussion of questions about natural kinds and pragmatics in theory construction. This is inspired by Edouard Machery's argument for the elimination of 'concept', but independent of Machery's own project. With this in place, I go on to give a conclusive argument that supports CLE, based on the claims that 'concept learning' is not a natural kind and that there are pragmatic advantages to eliminating 'concept learning'. In this final chapter, I also raise pragmatic considerations that support the argument for CLE, and propose new research directions that could pro t from the eliminativist position.

Thesis (M.S.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on November 9, 2007) Includes bibliographical references.

Thesis (M. A.) (Hons.) -- University of Western Sydney, 2002. / A dissertation submitted in partial fulfillmemt of the degree of Master of Arts, UWS Nepean, School of Contemporary Arts : Dance, July 2002. Bibliography : leaves 81-84.

Thesis (Ph. D.)--University of California, Santa Cruz, 1992. / Typescript. Includes bibliographical references (leaves 269-278).

Thesis (doctoral)--Freie Universität Berlin, 2005. / Includes bibliographical references (p. [260]-263).

The thesis introduces the Archetypal Market Hypothesis (AMH). Based on complex psychology and supported by insights from other (mind) sciences it describes the unconscious nature of investing and how it shapes price patterns. Specifically, it emphasises the central role of numerical archetypes in price discovery. Its ontological premise is the market’s mind, a complex adaptive system in the form of collective consciousness which originates from the collective unconscious. This premise suggests that investing involves more than cognition and reaches beyond rationality and logic. Among others, the thesis clarifies the affective impact of price discovery: it is not only what we can do with prices, but also what they can do with us. Numbers receive their affective powers from the numerical archetypes. They preconsciously create order in the mind by facilitating the dynamics of symbolic mapping as the mind attempts to make sense of what it senses, bridging the imaginative with the real. This autonomous and often dominating impact of the numerical archetypes manifests itself: • in individual consciousness via numerical intuition, and • in crowd consciousness via participation mystique which underlies intersubjectivity. The thesis will argue that both are supported cerebrally. The collective intersubjective nature of the market’s mind and its symbolic expression via prices make it an exemplary phenomenon to be researched because the archetypal dynamics are strongest in such spheres. The PhD’s goal, as part of the AMH proposition, is twofold. First, to formalise theoretically the concept of the market’s mind, in particular the collective experience of market states, generally known as market moods, and how these shift as a result of herd instinct. Second, to propose a framework for further empirical research to show that representing market data in a non-traditional way, based on Jung’s active imagination and similar techniques, can improve investors’ understanding of those states. If successful, the method (including bespoke software) can complement analytical investment research methods currently used by investors.

No description available.

Thesis (Ph.D.)--Texas Christian University, 2008. / Title from dissertation title page (viewed May 12, 2008). Includes abstract. Includes bibliographical references.