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During the nineteenth century, children's physical health became a dominant theme in France and Great Britain, two of Europe's pediatric pioneers. This dissertation examines how British and French doctors, legislators, hospital administrators, and social reformers came to see the preservation of children's physical health as an object of national and international concern. Medical knowledge and practice shaped, and was shaped by, nineteenth-century child preservation activities in France and Great Britain, linking medicine, public health, and national public and private efforts to improve the health of nations, especially that of their future members. Children's hospitals played a significant role in this process by promoting child health; preventing and combating childhood diseases; fostering pediatric professionalization and specialization; and diffusing medical-based justifications for child welfare reforms in the second half of the century. This deeply contextualized tale of two hospitals, Great Ormond Street Hospital for Children in London (1852) and Sainte-Eugénie in Paris (1855), traces a crescendo in the interest, provision, and advocacy for children's medical care over time: from foundling homes and dispensaries to specialized hospitals with convalescent branches and large outpatient clinics. As a comparative study of the medicalization of children's bodies between 1820 and 1890, this dissertation also investigates the transnational exchange of medical ideas, institutions, and practices pertaining to child health between France and Great Britain during a period of nation-building. Specialized pediatric institutions in Paris and London built upon and solidified local, national, and international interests in improving and preserving child health. Despite great differences in their hospital systems, French and British children's hospital administrators and doctors looked to one another as partners, models, and competitors. Nineteenth-century French and British concerns for national public health, and child health in particular, had important distinctions and parallels, but medical, institutional, and legislative developments related to these concerns were not isolated activities, but rather, tied to transnational communication, cooperation, and competition.
ContributorsSchreiner, Stephanie (Author) / Fuchs, Rachel G. (Thesis advisor) / Green, Monica (Committee member) / Szuter, Christine (Committee member) / Thompson, Victoria (Committee member) / Arizona State University (Publisher)
Created2014
Description
Solar energy is a disruptive technology within the electricity industry, and rooftop solar is particularly disruptive as it changes the relationship between the industry and its customers as the latter generate their own power, sell power to the grid, and reduce their dependence on the industry as the sole source provider of electric power. Hundreds of thousands of people in the western United States have made the decision to adopt residential rooftop solar photovoltaic technologies (solar PV) for their homes, with some areas of western cities now having 50% or more of homes with solar installed. This dissertation seeks to understand how rooftop solar energy is altering the fabric of urban life, drawing on three distinct lenses and a mixed suite of methods to examine how homeowners, electric utilities, financial lenders, regulators, solar installers, realtors, and professional trade organizations have responded to the opportunities and challenges presented by rooftop solar energy. First, using a novel solar installation data set, it systematically examines the temporal, geographic, and socio-economic dynamics of the adoption of rooftop solar technologies across the Phoenix metropolitan area over the decade of the 2010s. This study examines the broad social, economic, and urban environmental contexts within which solar adoption has occurred and how these have impacted differential rates of solar uptake. Second, using survey and real estate data from the Phoenix metropolitan area, it explores how solar energy has begun to shape important social and market dynamics, illuminating how decision-making in real estate transactions, including by buyers, sellers, agents, lenders, and appraisers is shifting to accommodate houses with installed solar systems. Lastly, the study explores patterns of rooftop solar adoption across major electric utilities and what those can tell us about the extent to which corporate social responsibility and sustainability reporting have affected the practices of investor-owned electric utilities (IOU) within the western US.
ContributorsO'Leary, Jason (Author) / Fisher, Erik (Thesis advisor) / Miller, Clark (Thesis advisor) / Dirks, Gary (Committee member) / Arizona State University (Publisher)
Created2021
Description
Generative Adversarial Networks are designed, in theory, to replicate the distribution of the data they are trained on. With real-world limitations, such as finite network capacity and training set size, they inevitably suffer a yet unavoidable technical failure: mode collapse. GAN-generated data is not nearly as diverse as the real-world data the network is trained on; this work shows that this effect is especially drastic when the training data is highly non-uniform. Specifically, GANs learn to exacerbate the social biases which exist in the training set along sensitive axes such as gender and race. In an age where many datasets are curated from web and social media data (which are almost never balanced), this has dangerous implications for downstream tasks using GAN-generated synthetic data, such as data augmentation for classification. This thesis presents an empirical demonstration of this phenomenon and illustrates its real-world ramifications. It starts by showing that when asked to sample images from an illustrative dataset of engineering faculty headshots from 47 U.S. universities, unfortunately skewed toward white males, a DCGAN’s generator “imagines” faces with light skin colors and masculine features. In addition, this work verifies that the generated distribution diverges more from the real-world distribution when the training data is non-uniform than when it is uniform. This work also shows that a conditional variant of GAN is not immune to exacerbating sensitive social biases. Finally, this work contributes a preliminary case study on Snapchat’s explosively popular GAN-enabled “My Twin” selfie lens, which consistently lightens the skin tone for women of color in an attempt to make faces more feminine. The results and discussion of the study are meant to caution machine learning practitioners who may unsuspectingly increase the biases in their applications.
ContributorsJain, Niharika (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Manikonda, Lydia (Committee member) / Arizona State University (Publisher)
Created2020