Thesis (M.S.)--University of Idaho, 2005. / Abstract. "December 2005." Includes bibliographical references (leaves 33-34). BMP Handbook available online. Accessed 09/08/2006 at http://www.webs1.uidaho.edu/idahot2/BMP%20working%20drafts/BMP_Handbook_HR.pdf

This dissertation examines contemporary American novelists whose depictions of how humans relate to the natural world challenge dominant Western cultural assumptions about human autonomy. My analysis centers on Marilynne Robinson, Louise Erdrich, and Richard Powers. Scholarship has largely understood these writers to be undertaking human-centered, social projects related to gender, ethnicity, and technology. However, in my reading, their works demonstrate how the formal elements of fiction—character and plot development, narrative voice and perspective, and recurring imagery—can be used to develop what I call a coextensive vision of the environment, one which shifts emphasis from the autonomous human self to a perception of how embodied individuals are embedded in larger networks and interchanges. In developing this claim, I suggest the environmental potential of the novel, a genre that has received short shrift in ecocriticism. Chapter One considers the novels of Marilynne Robinson, focusing on Housekeeping. Robinson’s nature imagery is highly metaphorical, but I argue that her writing also works on what we might call a material register: it persistently gestures toward an external world that resists enclosure through language, a natural world with which the human body is entangled. Accordingly, I argue, Robinson’s work develops an ecological vision wherein humans are coextensive with the environment. Chapter Two centers on Louise Erdrich’s boundary imagery. I first explore the recurrence of imagery of harmful divisions across Erdrich’s whole body of work. This is, I contend, a pattern that Erdrich uses to critique radical individualism. I further argue that Erdrich draws on the traditional trickster of Anishinaabe storytelling to reinvigorate coextensive connections through pleasure and humor, generating a tribal kincentric ecology emphasizing reciprocity between interrelated beings. Chapter Three closes the project by reading Richard Powers, whose work offers a more frightening vision of what it means to be inseparable from nature compared with Robinson and Erdrich: in Gain, the primary link between humans and environment involves shared toxicity. I explore how Powers’s preferred two-stranded narrative structure develops the reader’s ecological awareness. However, I propose, Gain ultimately problematizes the ethical promise of interconnection, suggesting that knowledge of coextension spurs negative affect and disengagement. / 2020-02-14T00:00:00Z

Based on the premises of "Equity Theory" (Adams, 1963), this study evaluated the Virginia Community College System compensation rates and compared the salaries of similarly ranked and similarly qualified male and female faculty members. A quantitative analysis was conducted of the reported salaries of all full-time instructional faculty members in the Virginia Community College System in the Fall of 2006. The specific areas examined included salary, rank, highest degree earned, and full- or parttime employment status. Using the tenets of Equity Theory as a foundation, this study evaluated any differences in the compensation and rank between male and female faculty members to determine the "fairness" of salary policies. The population of this study included all instructional faculty members employed during academic year 2006-2007 in the 23 community colleges in the state of Virginia. Results of this analysis indicated that there were differences based on gender in the mean salaries of faculty members of the Virginia Community College System at the professor faculty rank for VCCS faculty members outside of Northern Virginia Community College and at the associate professor rank at Northern Virginia Community College. Findings of this study further indicated that faculty members in the Virginia Community College system overall were slightly more likely to be female, hold master's degrees, and hold assistant professor rank. Findings indicated that both males and females were equally likely to be employed as part-time faculty members in the Virginia Community College System and that both education and experience contributed significantly to salary in the Virginia Community College System.

L’essentiel de ce texte est une réflexion sur mon travail de création et les concepts théoriques qui le construisent. J’aborde plusieurs thèmes dont en particulier le paysage autour duquel je développe une réflexion sur l’habitation. Ma recherche est au confluent de ces deux éléments qui concernent les relations entre le paysage, l’habitation et l’appartenance. À travers ce projet de recherche-création, j’explore différentes facettes du paysage et je m’approprie ce concept à travers une quête identitaire puisque j’utilise ma ville natale, Lebel-sur-Quévillon, pour mener ma recherche. Les concepts mentionnés seront développés en relation avec les oeuvres produites tout au long de mon projet de recherche-création.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

This thesis aims to develop a new methodological concept better to understand art and curating in a post-human setting. Departing from a post-humanist ontology, my initial idea was to analyse contemporary artworks dealing with food and trace and substantiate a figuration of the gut/intestinal system (connected to post-human notions as the ideas of trans- corporeality, vibrant matter, etc.) and how it could create a productive reading of these works. During my research on food-related art projects, I realised that the gut-figuration has broader implications and could function as a tool to understand the contemporary art world and curating at large, through a post-human lens. Accordingly, I suggest my thesis to be a contribution to what I would like to name an “intestinal turn”, a contemporary post-humanist, trans-corporeal understanding of art that could change how art is perceived and how the subjectivity of the artist, and curatorial work, could be understood today.