This dissertation, Making Sense of Digital Content Moderation from the Margins, examines how content creators who are marginalized by race, sexuality, gender, ethnicity, and disability understand their experiences of content moderation on the social media platform TikTok. Using critical interface and narrative-based inquiry methods with six marginalized content creators on TikTok, I argue that marginalized creators navigate the opaque content moderation infrastructure of TikTok by drawing on their embodied experiences. The key research questions ask how these content creators interpret TikTok's platform policies and processes through their interactions on the app and how these interpretations influence content creation on TikTok and how creators feel about moderation in the absence of platform transparency about how content is moderated. To answer these questions, I conducted narrative-driven interviews with six TikTok creators and analyzed these stories alongside online testimonials in eight Change.org petitions. My analysis revealed that lack of transparency around TikTok's algorithmic curation and moderation contributes to content creators feeling alienated, exploited, frustrated, and unwelcome on the platform and influences content creators to adapt their content to avoid moderation, oftentimes by self-censoring themselves and aspects of their marginalized identities. Over time, the accumulation of content moderation micro-interactions diminishes the ability of marginalized content creators to trust content moderation processes. My analysis also shows how TikTok's user experience design and opaque content moderation practices contribute to an affective platform environment in which creators are compelled to speak out and across creator networks about such gaps in experience and platform policy. I conclude with a discussion of how my findings about content moderation and transparency contribute to conversations in writing-related scholarship, especially as it pertains to writing assessment, technical communication, and algorithmic research methodologies. / Doctor of Philosophy / In recent years, marginalized content creators on TikTok have sounded the alarm about the way that the platform's content moderation and algorithmic recommendation disadvantages marginalized creators. This dissertation, Making Sense of Digital Content Moderation from the Margins, examines how content creators who are marginalized by race, sexuality, gender, ethnicity, and disability understand their experiences of content moderation on the social media platform TikTok. The key research questions ask how these content creators interpret TikTok's platform policies and processes through their interactions on the app and how these interpretations influence content creation on TikTok and how creators feel about moderation in the absence of platform transparency about how content is moderated. To answer these questions, I conducted narrative-driven interviews with six TikTok creators and analyzed these stories alongside online testimonials. My analysis revealed that lack of transparency around TikTok's algorithmic curation and moderation contributes to content creators feeling alienated, exploited, and unwelcome on the platform and influences content creators to adapt their content to avoid moderation, oftentimes by self-censoring themselves and aspects of their marginalized identities. Moreover, I found that TikTok isolates user experiences of biased content moderation which compels creators to speak out and across creator networks about discriminatory experiences of platform policy.

The thoughtful expression of building components provides a conceptual framework through which we can come to an understanding of architecture. Beyond the appreciation of individual elements involved in an assembly, numerous opportunities emerge to form architectural conditions and places. An envelope that oscillates between transparency and opaqueness introduces a modern conception of boundary. The control of natural light can also contribute to a compact space without compromising the desired level of privacy that is expected from a house. / Master of Architecture

In recent years, rapid advancements in computer science, including increased capabilities of machine learning models like Large Language Models (LLMs) and the accessibility of large datasets, have facilitated the widespread adoption of AI technology, such as ChatGPT, underscoring the need to design and evaluate these technologies with ethical considerations for their impact on students and teachers. Specifically, the rise of Automated Essay Scoring (AES) platforms have made it possible to provide real-time feedback and grades for student essays. Despite the increasing development and use of AES platforms, limited research has specifically focused on AI explainability and algorithm transparency and their influence on the usability of these platforms. To address this gap, we conducted a qualitative study on an AI-based essay writing and grading platform, with a primary focus to explore the experiences of students and graders. The study aimed to explore the usability aspects related to explainability and transparency and their implications for computer science education. Participants took part in surveys, semi-structured interviews, and a focus group. The findings reveal important considerations for evaluating AES systems, including the clarity of feedback and explanations, impact and actionability of feedback and explanations, user understanding of the system, trust in AI, major issues and user concerns, system strengths, user interface, and areas of improvement. These proposed key considerations can help guide the development of effective essay feedback and grading tools that prioritize explainability and transparency to improve usability in computer science education. / Master of Science / In recent years, rapid advancements in computer science have facilitated the widespread adoption of AI technology across various educational applications, highlighting the need to design and evaluate these technologies with ethical considerations for their impact on students and teachers. Nowadays, there are Automated Essay Scoring (AES) platforms that can instantly provide feedback and grades for student essays. AES platforms are computer programs that use artificial intelligence to automatically assess and score essays written by students. However, not much research has looked into how these platforms work and how understandable they are for users. Specifically, AI explainability refers to the ability of AES platforms to provide clear and coherent explanations of how they arrive at their assessments. Algorithm transparency, on the other hand, refers to the degree to which the inner workings of these AI algorithms are open and understandable to users. To fill this gap, we conducted a qualitative study on an AI-based essay writing and grading platform, aiming to understand the experiences of students and graders. We wanted to explore how clear and transparent the platform's feedback and explanations were. Participants shared their thoughts through surveys, interviews, and a focus group. The study uncovered important factors to consider when evaluating AES systems. These factors include the clarity of the feedback and explanations provided by the platform, the impact and actionality of the feedback, how well users understand the system, their level of trust in AI, the main issues and concerns they have, the strengths of the system, the user interface's effectiveness, and areas that need improvement. By considering these findings, developers can create better essay feedback and grading tools that are easier to understand and use.

This thesis began with an interest in apartment housing typology. I am familiar with this typology, yet it remains mysterious. The topic was never touched on in five years of architectural education or the time spent working in firms. I felt the need to study this typology. It is through the repetition of working with the realization that the hand and mind are one; I understand what I am working toward and the hand informs the mind of what it is doing. The notion of centralization, transparency, spatial ambiguity, symmetry, dematerialization, are used as a method to organize space and architectural elements. Spatial orders and conditions are examined through the use of idealized color. This work is the result of a year long study of the above architectural vocabulary. It is my hope that through this study, I can begin to establish a point of view. This thesis is a cross section of a thought. / Master of Architecture

Economic theory and empirical research suggests product market competition can result in both positive and negative capital market effects. Specifically, research suggests competition reduces agency costs, but also reduces profitability. I examine the relation between product market competition and firm value in an international setting, focusing on how the relation varies with firm- and country-specific characteristics. I document lower values for firms in more competitive industries. However, the negative relation between competition and firm value is less pronounced for firms with higher firm-level liquidation risk, stronger country-level investor protection mechanisms, and higher firm-level transparency. These findings are consistent with an agency cost benefit resulting from product market competition. / Ph. D.

The intention of this dissertation is to understand how federal advisory boards are operationalizing Congressional intent of transparency, financial efficiency and balanced board membership. When Congress passed the Federal Advisory Commission Act (FACA) in 1972, these three values were intended to help add legitimacy to the operation advisory boards. Advisory boards have been in use on the federal level since the first term of President George Washington, and they provide valuable expertise on a wide variety of subjects for the government. Currently, over 1,000 advisory boards are operating across the federal government with nearly 25,000 people participating. Collectively, annual operations of these boards approaches a half billion dollars. In the years leading up to the passage of FACA, Congressional hearings revealed deficiencies across federal departments with transparency of advisory board operations, spending practices, and appointment processes which threatened the legitimacy of their use. The FACA law was intended to bring legitimacy back to boards' operation by requiring more transparency, financial efficiency and balance in viewpoints on board appointments. With the law more than 40 years old, this dissertation explores how advisory boards today are operating is relation to the values Congress laid out in legislation. A quantitative exploration was conducted to assess the fidelity to the Congressional values by using publicly available data points. A sample of the 1,000 operating advisory boards was used to conduct the research. Using the results of the quantitative exploration, six case studies were selected for additional examination. Three cases were selected by a systematic method based on the quantitative data, and three additional cases were selected by the unique results from the data. A dozen policy changes were suggested as a result of the quantitative and qualitative examinations to better align present day operation of advisory boards with the Congressional intent. This study may be useful to policymakers who have oversight on advisory board operations. / Doctor of Philosophy / American citizens provide input to the federal government in several ways. Voting for President and Members of Congress is the most visible way. However, serving on one of the approximately one thousand existing federal advisory boards is another way. These are boards and commissions made up of citizens who have expertise in various subjects for which the government needs ideas to help fix problems affecting our country. The focus of these boards ranges greatly. For example, some boards focus on highly specialized medical issues, and others focus on how citizens use the land around national forests. In 1972, Congress passed a law that set some basic guidelines on how these boards should operate. Congress said that boards need to be transparent in how they work so the public can monitor them easily. Congress also noted that the boards need to use the tax money given to them to operate efficiently and try to save money whenever they can. Finally, Congress wanted boards to have people with different points of views represented, so recommendations are not one-sided. Now that the law is over 40 years old, this dissertation examines how closely advisory boards today are following those guidelines Congress wrote in 1972. This dissertation suggests some ways to measure how close they are following the directions, and it looks in-depth to several of them to see how they operate. Finally, the dissertation gives some new suggestions on how all boards can operate to better reflect the ideas Congress wanted.

The site chosen for this thesis project is located in downtown Blacksburg, Virginia. It consists of a 30'­x110' infill lot and an alley running parallel to it. An initial desire to blur the boundary between the alley and the proposed building led to a study of the potential of parallel planes overlapped along the shared border. Representation of these planes in two dimensions allowed almost simultaneous perceptions of multiple spatial and geometrical configurations among them. The architectural consequences of this phenomenon became the main subject of inquiry. Exploration through silkscreen prints and model studies culminated in the design of an outdoor art gallery. / Master of Architecture

Skin cancer is one of the most common cancers worldwide, and its incidence has been rising over the years. Early diagnosis substantially contributes to enhancing patient outcomes and increasing survival rates. However, due to a lack of dermatologists, especially in rural areas, cancer cases may go undiagnosed or inaccurately diagnosed. Subsequently, the burden of early diagnosis falls on non-specialists, such as primary healthcare providers, who are typically not trained to deal with complex dermatological conditions. Given the increasing prevalence of skin cancer and the chronic shortage of dermatological expertise, there is a critical need to develop computer-aided skin cancer decision support systems that offer an accurate early diagnosis. These applications are crucial to ensuring that patients receive timely treatment and that their chances of survival are significantly increased. The recent advances in artificial intelligence (AI) have given rise to a new era of skin cancer diagnosis models that perform on par with dermatologists. Nevertheless, the current AI diagnostic applications are subject to critical limitations. These include the lack of racial data diversity that results in the development of inequitable diagnostic models. Additionally, the black-box nature of AI models poses interpretability challenges that diminish human understandability and trust thus limiting their application in a clinical workflow. Furthermore, the paucity of applications dedicated to disease management prediction, primarily caused by the dearth of labeled data for the purpose of managing skin cancers, presents a significant hurdle in advancing AI in treatment prediction. This thesis aims to harness the power of AI to overcome these limitations, thereby achieving equitable, interpretable skin cancer diagnosis, and enhanced disease management. To accomplish these objectives, this work comprised five phases. In Phase 1, a comprehensive and analytical review employing text mining techniques was conducted to study AI methods and applications in skin cancer diagnosis and treatment. This analysis sought to gain a deep understanding of the explored capabilities and challenges of AI within these fields. Phases 2 and 3 were dedicated to resolving the data diversity issue. Phase 2 focused on the development of an integrated tool that encompassed segmentation, pixel clustering and classification to quantitively assess representation disparities of dark skin tones in dermatological resources. Phase 3 was centred around augmenting the training data with the underrepresented skin tones and developing an inclusive malignancy detection model employing deep neural networks. Phase 4 focused on developing interpretable diagnosis models that capitalize on the incorporation of human knowledge into model design and training to create transparent diagnosis models. Finally, Phase 5 delved into disease management, where a comparison between human-centred and machine-centred approaches was conducted. The two approaches aimed to accurately predict skin cancer management options while overcoming the challenges posed by data size limitations. / Thesis / Doctor of Philosophy (PhD)

Yes / The purpose of this paper is to provide response around three commentaries: Lowe’s view on key mechanisms through which greater transparency could influence consumer product evaluations (Lowe, 2015); Kuah and Weerakkody’s critical assessment on whether cost transparency is good for consumers (Kuah and Weerakkody, 2015); and Singh’s perspective on what is behind the price tag and why companies should embrace cost transparency (Singh, 2015). Design/methodology/approach – This is a response to the aforementioned commentaries, from the authors of “Should Consumers Request Cost Transparency?”. Findings – The authors call for empirical studies to shed light on issues, including, but not limited to, drivers and challenges/barriers of making unit cost available; appropriateness of unit cost information for different category of products; information overload caused by cost transparency; effect of availability of unit cost on the consumer decision-making; empowerment of consumers through unit cost information; impact of cost transparency on realisation of fairness, differentiation, competitive advantage and sustainability for businesses; and impact of cost transparency on market dynamics and consumer behaviour. Originality/value – Given its potential impact on both theory and practice, the arguments presented for and against provisioning of unit cost information to consumers is an issue worthy of further debate and empirical investigation.

This project investigates transparency and movement as the main measured elements that define space. These elements seek to articulate distinct and memorable places throughout the building, acknowledging its unique setting along the Potomac River in Old Town Alexandria, Virginia. Architecture and nature as opposite elements combine here to define a building in which water, light and views become the main architectural agents set in dialog with the natural surroundings. An existing boardwalk along the levee transforms into a transparent enclosed space that connects both city and water on opposite sides. Programmatically a series platforms, walls and volumes are inhabited by a cultural center. The cultural center contributes to the artistic spirit and identity of the city by concentrating various artistic representations. / Master of Architecture