VictorJuiz/thesis huggingface dataset:
Storying the Social: Opening Interpretations of Deafness, Disability, and Race in Accessibility Training Modules and Videoed Encounters

This dissertation engages stories produced by, within, and for institutions of policing, in particular institutions of police, revealing different possibilities for how we might understand deafness, disability, race, and policing differently. It explores and analyses a set of cultural artefacts: (a) videos of encounters between d/Deaf people and police officers occurring in North America, and (b) accessibility training modules from the AccessForward program developed in 2012 by Curriculum Services Canada. Drawing on the work of the early Dorothy Smith and Thomas King, I develop my method of storying the social. Interpretive disability studies (specifically blindness as perception), Black methodologies (specifically counterstorytelling), and Indigenous epistemologies frame how I proceed, shaping my desire to unfold another approach to interpreting the human and the world of police training. In storying the social, a slow and poetic attention to the videos and modules reveals how linear patterns of storytelling obliterate signs of interpretation, producing problem-characters and watchable-types in relationship to a juridical discourse that authorizes police officers, specifically in Canada and the United States, as necessary enforcers of racial capitalist and settler colonial rule. Approaching our everyday lives as narratively-mediated appears deafness, disability, and race as interpretive scenes always already determined by routine protocols of accessibility training and police officer conduct. Foremost concerned with making and uncovering connections, storying the social is a transformative and abolitionist act of sociological inquiry that, by way of wonder and pause, opens what otherwise remains closed interpretations of deafness, disability and race. This way of proceeding challenges a dominant human imaginary that aspires to manage, define, extract, and dominate. Instead of presenting improved training programs as solutions to police violence, I argue for noticing the relations that we are already part of, such that a world that stories disability as a problem and institutions of police as problem-solvers becomes our object of perception.

Keywords: deafness
disability
narrative
policing
race
storytelling
Advisor: Titchkosky, Tanya
Multifaceted Investigations on Transit Demand Resilience: A Roadmap for Developing Sustainable Urban Transit Policies

The thesis inspects transit's resiliency during an unprecedented disruptive event and conducts longitudinal analysis to identify strategies for transit to resist, recover and adapt to such disturbances. The recent COVID-19 pandemic has disrupted the transit system and its overall functions. Besides, users' vigilant safety concerns and the consequent transit avoidance behavior left the concerned authorities searching for recovery strategies. Therefore, the research aimed to conduct empirical investigations on the COVID impact on users' multidimensional transit preferences at different pandemic phases. The study also intended to fabricate a comprehensive travel demand model to provide data-driven insight into the plausible policies for building a health crisis-resistant transit system.The dissertation presents six empirical investigations, each highlighting different research avenues. For behavioral studies, the emphasis lies in administering and designing multiple surveys, conceptualizing choice experiments, preprocessing collected data, and devising advanced transportation demand modeling techniques. The first study examines the passenger's transit mode choice behavior capturing the user's sensitivity to specific pandemic characteristics and infection-resistant transit safety policies. The second work uses an integrated modeling approach to investigate the interaction between users' in-vehicle safety perception and transit usage during the second pandemic year. It also portrays the efficacy of rapid vaccine rollout in restoring transit demand. Later, the research examines the long-lasting impact of pandemic fear, individuals' vaccination status, and level of service attributes on users' transit route choice behavior. Then, the thesis presents a hypothesized psychometric model utilizing the protection motivation theory. It captures the interplay amongst trip makers' pandemic-induced psychometric factors, altered travel behavior, and future transit usage. Conversely, the fifth work provides insight into the potential of post-pandemic interventions in reinstating the demand. However, the final work developed a multimodal network microsimulation model in an agent-based framework for the Greater Toronto Area using a simulation tool, MATSim, and a wide range of transportation data. The model will be a testbed for evaluating the policies endorsed in former analyses. The empirical findings provide first-hand evidence for transit planners with timely and effective transit policies and service planning to withstand the unexpected pandemic shock and reinstate its regular functionality.

Keywords: Choice modeling
COVID-19 pandemic
Public Transit
Risk perception
Transportation Resilience
Traveler behavior and values
Advisor: Habib, Khandker Nurul
Control of Magnetic Microrobotic Swarms

Swarms, which stem from the collective behavior among individual elements, are commonly seen in nature. Over the past decade, the generation mechanism of microrobotic swarms has been explored for understanding the guiding principles of living swarms, and the swarms have been functionalized to enable specific applications. Nevertheless, the generation and navigation of microrobotic swarms under gravity and fluidic flow remain challenging, due to the the complexity in controlling agent-agent interactions. This thesis focuses on developing a strategy that enables the swarming of magnetic microparticles against gravity into vertical swarms. By analyzing the interparticle interaction under the influence of gravity and hydrodynamic drag, a unique dual-axis oscillating magnetic field was designed. The necessity of the vertical interparticle interactions, attraction among the intermediate structures, and positional reconfigurability of particles for the generation of the vertical swarms were revealed. The gravity-resisting capability, pattern reconfiguration, adaptive locomotion, and collective behavior of the vertical swarms were demonstrated. Next, this thesis presents the generation and navigation of magnetic nanoparticle swarms in fluidic flow. The interparticle interaction and locomotion mechanism of the magnetic particles in fluidic flow were analyzed and validated in experiments. Based on the findings, an actuation strategy was established to navigate the swarms in fluidic flow. Using the proposed strategy, downstream and upstream navigation of the swarms were realized in a blood flow with a rate of 2 mm/s. Moreover, this thesis focuses on the integrity of swarms in fluidic flow. An analytical model that described the relationships between fluid viscosity, flow rate, branching angle, magnetic field strength, and swarm integrity, was established. Based on the model, dynamic magnetic fields were designed to selectively maintain swarm integrity. Combining the dynamic fields and thrombin-coated magnetic particles, a microrobotic swarm-based strategy was developed to address the low selectivity issue of existing embolization techniques. Experiments in microfluidic channels, ex vivo tissues, and in vivo porcine kidneys validated the efficacy of the proposed strategy for selective embolization. The research deepens the fundamental understanding of swarm generation and behavior under gravity and fluidic flow, and establishes a route for developing the next generation of targeted delivery and embolization approaches.

Keywords: Magnetic swarms
Medical robotics
Microrobotic swarms
Microrobotics
Microswarms
Robotics
Advisor: Sun, Yu
Reexamining Assumptions in Compartmental Models of Heterosexual HIV Transmission applied to Eswatini

Compartmental HIV transmission models help guide global, national, and local epidemic responses via detailed projections, hypothetical scenarios, and mechanistic inference. While such models must make simplifying assumptions due to time and data constraints, prior work has shown that these assumptions can sometimes bias model outputs. In this thesis, I re-examine common assumptions used in compartmental HIV transmission models, and explore their potential influence on key model outputs. I focus on disproportionate risk among female sex workers, within the high-prevalence HIV epidemic of Eswatini. First, I systematically review how differential risk has been captured in prior models exploring HIV treatment scale-up across Sub-Saharan Africa. Among 94 studies, I find that only 2/5 explicitly included sex work, and only 1/4 considered differences in treatment access across risk groups. Next, I design, parameterize, and calibrate a model of heterosexual HIV transmission in Eswatini. The model features 4 partnership types and 8 risk groups, including higher/lower risk female sex workers and their clients. While parameterizing the model, I develop several new adjustments for common sources of bias in sexual behaviour data. I also critically review existing "force of infection equation" approaches, used to model HIV transmission via sexual partnerships within compartmental models, with respect to their implicit assumptions, data needs, strengths, and limitations. Drawing on this review, I develop a new approach - the Effective Partnerships Adjustment - which can overcome some of the key limitations of existing approaches. Comparing the new and existing approaches in the Eswatini model, I show that some existing approaches might be systematically overestimating the impact of prevention in longer partnerships, and underestimating the impact of prevention in shorter partnerships. Finally, I apply the Eswatini model to further explore scenarios with different HIV treatment scale-up across risk groups. I find that the prevention impacts of treatment could be substantially reduced if higher risk groups are "left behind". Taken together, these results suggest that existing compartmental HIV transmission models may underestimate the importance of prioritizing resources to populations at highest risk of HIV acquisition and/or transmission, including female sex workers, even within a high prevalence epidemic such as Eswatini.

Keywords: bias
HIV
mathematical model
population heterogeneity
sex work
Southern Africa
Advisor: Mishra, Sharmistha
Autonomous Low-cost Data Capture and Inference with Incomplete Data for Indoor Construction Environments

Construction projects require effective control mechanisms to ensure alignment between the intended design and the as-built reality. This process entails a cyclic comparison between the two, often involving the capture, pre-processing, and analysis of data to extract valuable information. This information is then modeled and documented, serving as a basis for informed decision-making and subsequent actions. This dissertation addresses two main challenges related to on-site construction data (i.e., 2D images and 3D point clouds): autonomous data capture in indoor construction environments and inference with incomplete data. Indoor construction environments are characterized by clutter and their dynamic nature, making frequent data capture a highly challenging task. Furthermore, even with an ideal data capture solution, on-site data are often plagued by noise and occlusion, resulting in incomplete data. In the first part, it proposes a tag-based visual-inertial localization method to facilitate low-cost autonomous image collection in indoor construction environments. The proposed on-manifold formulation allows for modeling manual tag installation errors to enhance localization robustness. It also enables 4D planning of tag size, number, and location to reliably support localization throughout the project while minimizing tag installation costs. Experimental validation in simulation and laboratory settings demonstrates the feasibility of autonomous indoor data collection using low-cost unmanned aerial vehicles (UAVs) instead of expensive robots. The second part of this dissertation presents a novel method that effectively addresses inference challenges posed by high levels of noise and occlusions in on-site 3D point cloud data through the exploitation of semantic relationships between building elements. This part introduces the BIM-Graph Neural Network (BIM-GNN), a novel approach to element-wise quality assessments that leverages semantics in as-designed Building Information Models (ad-BIMs) and the expressiveness power of GNNs. The contributions of this research are fourfold. In the first part, it (1) proposes an on-manifold formulation for tag-based visual-inertial localization of low-cost UAVs for indoor construction environments; (2) demonstrates the utility of the proposed formulation in modeling uncertainties in the determination of the pose of the tags on site, resulting in enhanced localization robustness; (3) presents a 4D perception-aware genetic algorithm-based tag placement planner (PGA-TaPP) to determine the optimal tag configuration using 4D-BIM, considering the project progress, safety requirements, and UAV's localizability. The second part of the dissertation (4) introduces BIM-GNN, a semantic-aware approach to element-wise quality assessment that leverages semantics in ad-BIM to infer the status of partially observed and unobserved elements.

Keywords: Autonomous UAVs
BIM
Data Capture
GNN
Robotics
Semantics
Advisor: McCabe, Brenda Y
Schoellig, Angela P
The Role of Information Seeking and Use in Management Accounting: Exploring the Process of Creating a Budget for Complex Projects.

This research study investigates the relatively unexplored topic of the ‘process’ of creating a budget. In this study, the focus is on preparing the budget for use, as opposed to using the budget as a tool once it has been prepared. This study on the budget creation process, a topic in management accounting studies, draws upon research from the information science domain. Understanding the process of creating a budget, i.e., how information is located, evaluated, and used, can be significant as the quality of the budget as a product (the output from the process) can have a downstream effect on the decisions for which the budget may be an input. This study applies both information science and management accounting literature to help improve our understanding of the budgeting process. A preliminary conceptual framework, informed by the review of literature in both management accounting (budgeting) and information science (information needs, seeking, and use), was designed to be used as a guiding star/map. The preliminary conceptual framework evolved through interviews with 22 industry professionals. A semi-structured interview approach was utilized in an individual 1:1 interview setting. This empirical method allowed the participant to tell their story, while ensuring that prompts and a few prepared structured questions were provided to help guide the conversation. Six main themes (task readiness and organization, information needs, sources of information gathered, information seeking, information use, influence of experience) surfaced from the analysis of the participant interview data. The research contribution from this study is a Conceptual Framework for Budgeting Process that can be used while working through the process of creating a budget. The conceptual framework produced from this study is a unique offering of a roadmap to understand the “role of information seeking and use in management accounting” during the process of creating a budget. The outcomes of this research study also contribute by adding an important critical thinking element to the management accounting literature. This research study also suggests further possibilities for research linking information behavior to other management accounting topics or other accounting disciplines, e.g., auditing and assurance, financial accounting, that can be explored.

Keywords: Budgeting Process
Capital Budgeting
Information Behaviour
Information Seeking and Use
Management Accounting
Thematic Analysis
Advisor: Wensley, Anthony
Dialogue for Change: Extending the Impacts of Teaching for Critically Reflective Practice

Critical reflection has long been theorized as a path toward addressing inequitable practices. However, a gap is emerging in health professions education and practice between what theory espouses and what research supports. While empirical studies have highlighted opportunities for critical reflection, the effects of teaching for critical reflection on learners’ actions, and the potential for those actions to contribute to social change, remain underexplored. This dissertation draws on theories and knowledge of critically reflective practice, dialogue, and critical disability studies to extend the chain of impact from education to action to potential social change. In this dissertation, I investigate the impacts of teaching for critically reflective practice in the context of school-based healthcare for children with disabilities and chronic health conditions. My dissertation leverages clinical letters to explore the chain of impact. I designed the studies in this dissertation to achieve three overarching research aims: 1) to investigate the effects of teaching for critically reflective practice on shifts in learners’ action and possibilities for social change, 2) to examine the role of Bakhtin-informed dialogue as a critical pedagogical approach, and 3) to explore the relationships between collaborative learning and collaborative practice. The results from my first study demonstrate the pedagogical potential of Bakhtin-informed dialogue in preparing health professions learners for critically reflective practice. The findings from my second study illuminate the ways critically reflective practice reconstructs and renegotiates the meaning of disability. The findings from my third study reveal a cascade of potential outcomes of critically reflective practice related to inter-sector communication, collaboration, and advocacy. Collectively, the manuscripts presented in this dissertation demonstrate how teaching for critically reflective practice through dialogic education supports learners in enacting informed social action and creates possibilities for changes in the way collaborative practice unfolds. My dissertation offers directions for designing education to prepare health professionals who embody a curiosity to question why things are the way they are, a view toward imagining how things could be different, and a commitment to taking informed steps to realize those visions.

Keywords: Critical reflection
Critically reflective practice
Dialogic education
Dialogue
Disability
Health professions education
Advisor: Ng, Stella
Woods, Nikki
Learning to Drive with Neural Motion Planner

Building autonomous driving vehicles is exciting. It is going to transform the future of mobility with increased safety, efficiency and less environmental burden. However, driving autonomously everywhere under every condition is challenging, as it requires the AI system to generalize well to unseen environments and behave robustly in various conditions. Motivated by the success of data-driven approaches, many recent works focus on building end-to-end neural networks to learn a direct mapping from sensor inputs to control signals. However, it loses key inductive biases of driving and has difficulty to generalize. To overcome these challenges, popular techniques in the industry build the driving system by stacking several modules in a feed-forward pipeline, mimicking how human intelligence would solve the task. However, such a system heavily relies on manually crafted heuristics and representations, resulting in suboptimal performance and cannot cope with real-world complexities. In this thesis, I present our work in the direction of a new paradigm, Neural Motion Planner, which can be learned holistically from data while retaining key inductive biases of how humans learn to drive, and thus enjoys the benefits of both worlds. The first technical part of the thesis describes how we formulate driving as a task that can be learned and introduces our first attempt to bridge observations with actions. Next, we explore better world modeling for expressiveness, generalization and learning efficiency. In particular, we propose a perceptive model of the world for understanding the environment and a predictive model of the world for forecasting distributions of multi-modal futures. Finally, we study closed-loop training techniques for mitigating the distribution shift between training and deployment. Discussions about promising future directions are presented at the end of each technical chapter as well as at the end of the thesis.

Keywords: Artificial Intelligence
Autonomous Driving
Deep Learning
Advisor: Urtasun, Raquel
Decolonizing Global Health Partnerships: Exploring International Partnerships in Health Professions Education Through a Postcolonial Lens

The education of health care professionals plays an important role in addressing global population health disparities and strengthening health systems. One avenue to address the global shortage of health professions is to invest in health professions education globally through international academic collaborations, particularly partnerships between high-income countries (HICs) and low- or middle-income countries (LMICs). While global health partnerships have intensified in the first two decades of the 21st century, only a fraction are described in published literature. Additionally, published accounts of partnerships seldom take into account the perspective and experiences of the LMIC partner. Furthermore, partnerships are rarely examined from a perspective that acknowledges unequal relations resulting from historical colonial ruling and neocolonial globalization.The purpose of this study was to problematize HIC and LMIC international partnerships in health professions education through a postcolonial theory lens. The aims of this study were: 1) To explore moments of success and challenges experienced by partners during the everyday processes that shape the partnership; and, 2) To explore these partnerships taking into account power imbalances and unequal relations resulting from historic colonial ruling and neocolonial globalization. The postcolonial theory concepts of neocolonialism, globalization, global citizenship, and knowledge and power were operationalized using critical qualitative methodology. Ninteen participants (ten from HIC and nine from LMIC) from 13 different partnerships were interviewed using a semi-structured approach using video-conferencing. Data were analysed using inductive, deductive and abductive reasoning. This study offers an augmented view of partnerships summarized by three key findings. First, partnerships are greatly reliant on human relationships which are enacted by highly committed partners that embody an anticolonial ethos. Secondly, a deeper appreciation of the partnership process is required in order to value alternative outcomes, celebrate achievements, and reinvigorate partners. Third, in order to decolonize global partnerships in health professions education between HICs and LMICs, a deep understanding of power dynamics and neocolonial relations is needed. Valuing people, appreciating processes and contextual factors, and acknowledging power relations as well as an engagement with complexity are required for current and future partnerships to contribute to social justice and decolonization.

Keywords: decolonization
global health
medicine
nursing
partnership
post-colonial theory
Advisor: Gastaldo, Denise