Theses

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The theses in UWSpace are publicly accessible unless restricted due to publication or patent pending.

This collection includes a subset of theses submitted by graduates of the University of Waterloo as a partial requirement of a degree program at the Master's or PhD level. It includes all electronically submitted theses. (Electronic submission was optional from 1996 through 2006. Electronic submission became the default submission format in October 2006.)

This collection also includes a subset of UW theses that were scanned through the Theses Canada program. (The subset includes UW PhD theses from 1998 - 2002.)

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Gas hydrate formation and dissociation: predictive, thermodynamic, and dynamic models
(University of Waterloo, 2025-06-27) Hosseini, Mostafa
Gas hydrates are a type of crystalline compound consisting of water and small gas molecules. A wide range of applications of gas hydrates in storing natural gas in the form of artificially created solid hydrates, known as solidified natural gas technology, gas separation processes, and seawater desalination technology, has attracted great interest in scientific and practical studies. Gas hydrate formation may also cause deleterious effects, such as blockage of gas pipelines. Therefore, accurate prediction of equilibrium conditions for gas hydrates is of great interest. In this regard, machine learning-based models were proposed to predict methane-hydrate formation temperature for a wide range of brines. A comprehensive database including 987 data samples covering 15 different brines was gathered from the literature. After data cleaning and preparation, three different models, namely multilayer perceptron (MLP), decision tree (DT), and extremely randomized trees (ET), were trained and tested. The ET model achieved the best performance with a root mean squared error (RMSE) of 0.6248 K for the testing dataset. Moreover, in an additional independent testing with MgBr2 samples, ET achieved an RMSE of 0.3520 K, confirming its strong generalization ability. The order of model accuracy was ET greater than MLP greater than DT. Compared to previous studies, the developed models achieved similar or better accuracy while covering a wider range of brine types. The findings of this study can be used as a reliable tool to predict methane-hydrate formation PT curves for pure water, single-salt brines, and multi-salt brines. The research further focuses on improving the prediction of equilibrium conditions in methane hydrate systems by incorporating diverse water-soluble hydrate formers and applying advanced machine learning techniques. Methane hydrates, which naturally form under high pressure and low temperature, can be more efficiently formed or dissociated by altering thermodynamic conditions using these hydrate formers. Accurate prediction of these conditions is crucial for optimizing gas storage and energy applications. Molecular descriptors and operational parameters, such as mole fraction and pressure, were used as input variables to predict equilibrium temperature. Machine learning methods, including Decision Trees (DT), Random Forests (RF), Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP), were employed, using a novel former-based data-splitting approach rather than traditional sample-based methods. The RF model achieved the best results, with R2 = 0.930, RMSE = 1.71, and AARD = 0.48%. Feature selection, preprocessing, and Shapley Additive Explanations (SHAP) provided valuable insights into variable importance. Additional findings from the reduced model revealed that even less influential features significantly impacted distance-based models such as SVM and MLP. Interaction analysis through SHAP dependency plots highlighted the critical interplay between polar surface area and rotatable bonds in hydrate formation conditions. This work advances methane hydrate research by offering a more accurate and interpretable framework for predicting hydrate equilibrium, addressing key gaps in previous studies, and extending its applicability to a broader range of systems. Moreover, the introduction of a former-based data-splitting method improves generalization across different hydrate formers, while the use of SHAP values for model interpretability offers deeper insights into the relationships between molecular descriptors and hydrate equilibrium conditions. This study paves the way for improved selection of hydrate formers in hydrate systems. In addition to the phase equilibrium studies, this research also addresses the behavior of gas hydrates under confinement, focusing on hydrate dissociation in porous media. Understanding the dissociation behavior of gas hydrates in confined porous media is crucial for evaluating their stability and potential applications in energy storage, carbon capture, and climate modeling. Two distinct approaches were developed, namely a thermodynamic activity model and machine learning (ML) models, to predict equilibrium dissociation temperatures of gas hydrates in porous media of varying pore sizes. The activity model accounted for capillary effects and surface interactions and was validated against an unfiltered experimental dataset. For CH4 hydrates, the model achieved an AAD% of 0.17%, and for C3H8 hydrates, an AAD% of 0.62%. Complementary machine learning models (DT, RF, SVM, MLP) were trained using pore diameter, pressure, and gas critical properties as features. Group-based data splitting, with propane data reserved for testing, ensured robust evaluation. Among ML models, the SVM achieved the best predictive performance with an AAD% of 0.52%. SHAP analysis revealed that critical temperature, system pressure, and pore size were dominant predictors. The study also noted that experimental scatter was linked to pore structure variability and procedural differences, with larger pores showing convergence to bulk hydrate behavior. The combined modeling framework effectively captures hydrate behavior across a wide range of confined conditions, offering valuable predictive capability for both industrial and geological hydrate systems. In conclusion, the integration of physics-based and data-driven modeling enables accurate prediction of hydrate dissociation temperatures across a range of porous media. These findings support the development of predictive tools for hydrate systems in both geological and industrial applications. Finally, to complement the thermodynamic and equilibrium predictions, the dynamic transport behavior of hydrate particles in pipelines was investigated through CFD–DEM simulations. The dynamic behavior of hydrate particles suspended in water-dominated horizontal pipe flow using a two-way coupled CFD–DEM framework based on OpenFOAM and LIGGGHTS via CFDEM® coupling was explored. Multiphase flow simulations were conducted across inlet velocities of 0.2, 0.5, and 0.8 m/s and hydrate volume fractions of 2%, 5%, 8%, 15%, and 20%. Pressure drop behavior was quantified by extracting pressure gradients between two axial positions (z = 0.10 m and z = 0.49 m) early in the simulation. Results indicated that pressure drop increases with hydrate volume fraction at all flow velocities, with clustering phenomena becoming more prominent at higher solid loadings. Cross-sectional velocity profiles visualized the early evolution of particle clustering, wall interactions, and domain depletion. Increased flow velocity enhanced particle suspension but reduced domain uniformity over time. Time-resolved analyses of pressure drop, drag force, particle velocity, interparticle forces, and radial migration were conducted to explore flow regime transitions and mechanical resistance. Early clustering near the pipe walls was observed under dense flow conditions, driven by cohesive and frictional forces, leading to partial stratification and localized energy dissipation. The study highlights the importance of considering early-time flow dynamics, where suspension quality and transport resistance are most sensitive to hydrate loading. These findings contribute to a deeper understanding of hydrate slurry transport in multiphase pipeline systems and offer practical guidance for improving flow assurance models and mitigation strategies in subsea energy operations.
Contextual and Individual Factors Associated with the Interpretation and Usage of Prosocial Lies
(University of Waterloo, 2025-06-26) Ong, Shirley
Lying is a complex and multifaceted aspect of human communication, often viewed as a moral or social transgression. Growing up, children are instilled with the message that it is important to be honest. However, not all lies are told for malicious purposes, and there are situations where telling a lie may be socially appropriate and provide beneficial for the recipient. Prosocial lying is defined as a type of lie that is socially beneficial and enhances the quality of social interactions by minimizing harm to others. Within everyday exchanges both children and adults use prosocial lies on a frequent basis. While there may be social benefits to using prosocial lies, overuse or inappropriate use has negative outcomes. Thus, it is important for children to know how and when prosocial lying is more/less appropriate. My doctoral dissertation examines how contextual and individual factors relate to children’s reasoning about prosocial lies. I examined this for both children’s perceptions of lies, namely, how children felt the emotions of both the lie-teller and the lie-listener may be affected by the lie, as well as children’s endorsement of lies (versus truth), that is, how likely they themselves would be to use lies in varying contexts. There were two contextual factors manipulated with my work. First, I examined the listener’s knowledge of the situation, thereby allowing my work to build upon the rich body of work that has examined children’s sensitivity to and use of others’ knowledge to guide their communication. Second, I explored the role of statement content (i.e., whether there was a reference to an opinion or to reality), building on past work that has shown children’s sensitivity to the moral weight of lies based on content. With respect to individual differences, I focused on the role of empathy in relation to perceptions/endorsement of prosocial lies, exploring whether increased sensitivity to others’ emotional states (i.e., empathy) was associated with children’s perception/endorsement of prosocial lying within certain contexts. My central focus was on the performance of school-aged children, a developmental stage chosen as children in this age range would both understand the function of prosocial lies generally and show sensitivity to the content of lies. However, to assist with understanding developmental shifts in performance, I also assessed how adults would respond on similar tasks. Two studies were conducted with different groups of children and adults. Study 1 focused on children’s (8–11 years, N=80) and adults’ (N=192) perceptions of the emotional impact of prosocial lies (and truths) for both lie-tellers (i.e. speakers) and listeners. Participants read/heard a series of eight vignettes describing a negative event wherein a speaker says either a truth/lie (referring to their opinion or reality) to a listener who was/was not aware of the negative event. Before and after the statement was uttered, participants rated the emotions of both characters. Results demonstrated that the statement content did not affect children’s or adults’ perceptions of listener/speaker emotions. Both children and adults perceived that listeners would feel better after hearing a prosocial lie regardless of their knowledge state, suggesting that there may be a social benefit even when a prosocial lie is unlikely to deceive. However, following a lie, when listeners were unaware of the negative event (versus aware), their emotions were rated as more positive, suggesting that participants were tracking the listener’s knowledge state and using this to gauge emotional outcomes. Children with higher empathy showed better accuracy in detecting lies (when told to ignorant listeners) and adults with better empathy perceived knowledgeable listeners as feeling worse following a prosocial lie. Study 2 focused on children’s (8–11 years, N=81) and adults’ (N=218 endorsement of prosocial lies. Participants were asked to imagine themselves in scenarios involving a negative event that another person either knew or did not know about. They then rated how likely they would be to use the truth/lie statements which varied in content (referring to opinion or reality). Results demonstrated that while children endorsed statements similarly for ignorant/knowledgeable listeners, adults endorsed a greater likelihood of using a prosocial lie when the listener was ignorant of the negative event. Both age-groups indicated higher likelihood of telling a prosocial lie about an opinion versus reality. Empathy was not associated with children’s responses but was associated with adults’ communicative choices. Across the two studies, findings provide insight into how children (and adults) incorporate information about listener knowledge and statement content into their appreciation of prosocial lies. Findings also highlight the differing role of empathy throughout development within the context of these studies. My results have theoretical implications for children’s communicative development and practical considerations for prosocial lying in general.
Mathematical modeling of whole-body electrolyte homeostasis
(University of Waterloo, 2025-06-24) Stadt, Melissa
Electrolyte balance is crucial for many physiological processes, including cellular signaling, muscle contractions, membrane potentials, hormonal secretion, and bone structure. Disruptions to electrolyte balance, arising from disease, diet, or drugs can have severe health consequences, such as muscle weakness, bone fragility, and life-threatening cardiac arrythmias. Therefore, a comprehensive understanding of these regulatory systems and how they may be disrupted is important for developing effective preventative and therapeutic strategies. Mathematical modeling provides a powerful tool for investigating these systems through simulations and analysis. In this thesis, we present the development and analysis of mathematical models focused on the regulation of key electrolytes, potassium and calcium. For potassium homeostasis, we first developed a detailed, whole-body model incorporating known regulatory mechanisms. We conducted model simulations to quantify the individual contributions of these regulatory mechanisms on long-term potassium balance and responses to a meal. Additionally, we conducted sensitivity analyses to understand how parameter variations impact potassium levels in the extracellular and intracellular fluid. Furthermore, we integrated recent experimental data on renal adaptations to high potassium intake to analyze these findings from a whole-body perspective. For calcium homeostasis, we developed mathematical models representing a male, female, late pregnant, and lactating rat to quantify sex-specific differences and maternal adaptations in calcium regulation. These models synthesized literature data to identify key mechanisms that enable females to meet the high calcium demands of pregnancy and lactation. Finally, we developed an integrated model that represents the renin-angiotensin system, calcium regulation, and bone remodeling to investigate the impact of estrogen deficiency in post-menopausal women and common antihypertensive treatments on bone density and calcium regulation. The research provided in this thesis contributes frameworks for understanding electrolyte homeostasis and predicting the impacts of physiological changes and pharmacological interventions on electrolyte and bone homeostasis.
Role of Social Capital and Relational Well-being in Shaping the Community Level Responses to Tropical Cyclones among the Small-Scale Fisheries Communities in Chilika Lagoon, India
(University of Waterloo, 2025-06-24) PRAKASH SHERLY, GREESHMA
Small scale fisheries (SSFs) are more vulnerable to calamities brought on by natural hazards, changing climatic conditions, and climate change due to their proximity to the seashore. Dealing with these challenges is an added burden to already existing vulnerabilities, injustice and marginalization faced by them. The Indian subcontinent with a vast coastline extending up to 7516 kms (about 4670.23 mi), is vulnerable to world’s 10% tropical cyclones, especially in the places adjacent to Bay of Bengal (BoB). Asia’s largest and world’s second largest brackish water lagoon, adjacent to BoB - Chilika lagoon, situated in Odisha state of India is extremely prone to catastrophic events, causing around 5-6 cyclones hitting the coast annually. SSFs who depend on the lagoon for their livelihood are on the forefront suffering from the repercussions of cyclonic activities. While resilience against events like cyclones is usually analyzed in terms of economic and infrastructure aspects, there is a lack of focus on the intrinsic material aspects contributing to community resilience in the face of climate related disasters. This research fills this gap by analyzing the community resilience of SSF’s in Chilika Lagoon through the lens of social capital and relational well-being. Social capital measures the different links or connections a community has within and outside of their network that helps them build effective response strategies through collective action at the time of crisis. Communities with high social capital can bring community members together for better preparedness, emergency support, response, and recovery efforts. Nevertheless, it is not the existence of all these linkages that matters, but the quality and balance of all these ties are imperative. For instance, the effectiveness of these could be hindered in a community level resilience if it lacks the ability to address the power imbalance, social inequality, and trust. Thus, relational well-being measures the quality of various networks through characteristics such as trust, reciprocity, support, and network dynamics which create a sense of motivation to work collectively. The study employs a qualitative case study approach and multiple data collection tools such as semi-structured interviews, non-participant observations, and focus group discussions. The key findings present the various challenges faced by the communities in various systems like social, economic, environmental and physical and their interconnectedness, role of social capital and relational well-being in the various community level response to deal with the crises, the lack thereof due to power imbalance, social inequality, caste system and political power and finally providing recommendations to ensure tailored context specific approaches to enhance the community resilience against disasters like tropical cyclone in the future.
Teenage Feminists: High School Students and the Women's Movement in Ontario, 1968-1980
(University of Waterloo, 2025-06-24) Blair, Megan
This thesis examines the involvement of teenage girls in the upsurge of feminist activism between 1968 and 1980. Young women across Ontario engaged in feminism in a variety of ways; some joined high school women’s liberation groups in their communities or started their own feminist groups in their schools, while others reflected a more intimate and subtle feminism, challenging gender discrimination in their everyday lives. Using an age-focused analysis, this thesis argues that teenage girls partook in everyday feminism. Everyday feminism entails the recognition of discrimination and inequalities in intimate, everyday spaces, and the words, actions, and thoughts that challenged these inequalities. By broadening the definition of feminism beyond adult-oriented women’s groups and issues, this thesis captures the feminist actions of young women. Spaces and issues that mattered to young women such as school, sports, sex education, and fashion were all ways that teenage girls negotiated with discrimination and feminism. While young women sometimes collaborated with adults, at other times their efforts were more individualized, spontaneous, or collaborative with their peers. This thesis contributes to a more complex and varied history of feminism in Canada by taking seriously the issues that mattered to young women and recognizing the reality of their involvement in feminist action.
Developing an Agent-Based Model (ABM) to Explore the Geographic Redistribution of Snowmobilers During a Record Warm Winter
(University of Waterloo, 2025-06-20) Rubiano, Mave
Canada's snowmobile industry is the second largest market in the world, with Ontario generating over $3 billion in economic activity and supporting over 10,000 full time jobs. Inter-annual climate variability and record warm winters have underscored the vulnerability of the industry, which is predicated on natural snowfall and low temperatures to support over 100,000 riders across the 33,000 kilometers network of trails. However, critical regional and methodological gaps limit our understanding of the vulnerability of snowmobiling to both current conditions and projected climate change, with no available research that empirically explores the dynamic relationship between supply- and demand-side responses to marginal climatic conditions. The presented research develops an agent-based model (ABM) to simulate how trail availability influences the spatial redistribution of snowmobilers across Ontario. Using the record warm 2023/2024 winter season as a climate analogue, the ABM was informed by a geospatial analysis of trail network availability (i.e., supply-side vulnerability) and the results from an online survey of snowmobilers' (n=161) (i.e., demand-side vulnerability). Results from the geospatial analysis revealed significant trail closures across the province, with 14 districts having ≤5% trail availability in December followed by an early end to the season (≤1% of trails available in March). Survey findings revealed that 90.4% reducing riding frequency in response to trail closures, but strong willingness to travel (e.g., 61.5% travelled to alternative trails outside their preferred district due to closures, averaging 239.8km for day trips and 861.1km for overnight trips). The ABM simulated the movement of 1,000 snowmobiler agents across the 16 districts, resulting in significant redistribution patterns that underscore differential climate risks, such that some districts gained market share (e.g., Districts 1 and 3) while others incurred substantial losses (e.g., Districts 11 and 6). Collectively, the results suggest the future of snowmobiling in Ontario may involve substantial geographical shifts rather than outright market collapse, with important implications for tourism planning and rural economic development in a warming world.
Simulated spin qubits in silicon quantum dots and enhancement of InGaAs photodetectors
(University of Waterloo, 2025-06-20) Merino, Zach
Semiconductor quantum dot spin qubits are a leading candidate for scalable, fault- tolerant quantum computing. Their advantages include nanoscopic device size, compat- ibility with foundry fabrication processes, and long coherence times relative to gate du- rations. The fabrication and control of a quantum processing unit composed of tens of thousands to millions of physical qubits pose many engineering challenges. These chal- lenges fall broadly into two categories: device design, such as optimizing the geometry for high-quality qubit formation, and qubit control, which involves the precise manipulation of spin or charge states in qubits that are capacitively coupled to numerous neighboring electrodes. In this thesis, we develop a simulation tool that accelerates device design iter- ation prior to fabrication by providing a priori knowledge of the quantum dot electrostatic potential landscape as a function of external electrode voltages. This enables effective spin and Hubbard Hamiltonian parameters to be computed before experimental charac- terization, facilitating early-stage control method development and device performance prediction. The tool, implemented as the Python-based QuDiPy package, integrates three- dimensional finite-element Poisson solutions with modules for electrostatic reconstruction, Hamiltonian parameter extraction, and control pulse optimization. Unlike previous dis- jointed toolchains, QuDiPy offers a unified workflow for full-stack qubit control simulations, including automated voltage-to-Hamiltonian mapping for exploring high-dimensional gate voltage spaces and mitigating crosstalk in dense qubit arrays. The simulator is designed to be memory- and CPU-efficient to enable computationally efficient simulation of linear quantum dot arrays consisting of several qubits. Simulation of small quantum dot arrays serves as a design tool for control protocols within multi-node quantum processors. Sim- ulation of spin qubit dynamics in many-qubit nodes connected in a network enables the study of required voltage ranges for maintaining stable charge configurations in the device. It also supports the design of experimental input pulses to generate maximally entangled Greenberger–Horne–Zeilinger (GHZ) states between nodes, a key step for implementing surface code error correction protocols. Spin qubit control requires a precise understanding of the impact of experimental con- trols, such as electrode voltages or radio-frequency magnetic field amplitude and phase, on effective parameters such as electronic g-factor, exchange energy, chemical potential, etc. A mapping between experimental and effective parameters is created by performing effective parameter calculations on two-dimensional cross-sections of the electrostatic po- tential landscape obtained from a 3-dimensional Poisson solver nextnano++, a commercially available, 3D Poisson solver chosen for its robustness, flexibility in defining quantum device geometries, and proven accuracy in modeling semiconductor heterostructures at cryogenic temperatures. First, a 2D cross-section of the electrostatic potential landscape is taken along the growth direction of the quantum dot device, near the heterojunction where qubit formation occurs. This region is selected because it captures the horizontal confinement profile most relevant to charge localization and wavefunction shape. The cross-section is extracted for all simulated voltage configurations applied to the gate electrodes. Second, the single-particle ground state or first excited state wavefunctions are determined using a non-uniform grid Schrödinger solver for all voltage configurations and for each isolated quantum dot or nearest-neighbor quantum dot pair. The non-uniform grid provides higher spatial resolution near confinement potential minima, enabling more accurate modeling of localized wavefunctions where precision is most critical. The mapping between input voltage and single-particle wavefunctions is leveraged, along with numerical integration routines, to calculate the desired effective parameters as a function of voltage. The chemi- cal potential, tunnel coupling, and onsite and interdot Coulomb parameters are computed for each voltage configuration. This enables exact diagonalization of the Hubbard Hamil- tonian at every point in voltage space and identifies the regions of charge stability for a multiqubit quantum dot device. This step is essential for establishing control over the quantum processor. The second part of this thesis investigates optoelectronic device enhancement using localized surface plasmons in nanocrystals. Fast and accurate detection of light in the near-infrared (NIR) spectral range plays a crucial role in alleviating speed and capacity bottlenecks in optical communications and in enhancing the control and safety of au- tonomous vehicles through NIR imaging systems. Several technological platforms are cur- rently under investigation to improve NIR photodetection, aiming to surpass the perfor- mance of established III–V semiconductor p-i-n (PIN) junction technology. These plat- forms include in situ-grown inorganic nanocrystals (NCs) and nanowire arrays, as well as hybrid organic–inorganic materials such as graphene-perovskite heterostructures. How- ever, challenges remain in NC and nanowire growth, large-area fabrication of high-quality 2D materials, and the fabrication of devices for practical applications. Here, we ex- plore the potential for tailored semiconductor NCs to enhance the responsivity of planar metal–semiconductor–metal (MSM) photodetectors. MSM technology offers ease of fabri- cation and fast response times compared to PIN detectors. We observe enhancement of the optical-to-electric conversion efficiency by up to a factor of ∼2.5 through the application of plasmonically-active semiconductor nanorods and NCs. We present a protocol for syn- thesizing and rapidly testing the performance of non-stoichiometric tungsten oxide (WO) nanorods and cesium-doped tungsten oxide (CsyWO) hexagonal nanoprisms prepared in colloidal suspensions and drop-cast onto photodetector surfaces. The results demonstrate the potential for a cost-effective and scalable method exploiting tailored NCs to improve the performance of NIR optoelectronic devices.
The development of the sunk cost bias
(University of Waterloo, 2025-06-20) Sehl, Claudia G.
The sunk cost bias is when people overvalue objects or projects because they have already invested time, money, or effort into them. Most sunk cost research over the past 50 years investigated the bias in adults, exploring the conditions in which people expect themselves and others to be biased by sunk costs. However, very little work has examined the developmental origins of the bias, despite much evidence that young children reason about costs for a host of predictions and inferences about others. Across three papers, this dissertation examines children’s (N = 990) and adults’ (N = 934) sunk cost predictions. Chapter Two first explored whether children predict others’ actions are biased by sunk costs. After seeing agents collect two identical objects but being able to keep only one, adults expected agents will be biased by sunk costs and choose high-cost objects. However, 5- to 6-year-olds chose between high- and low-cost objects equally. Across four experiments, children consistently failed to anticipate that sunk costs biased others’ choices, their own hypothetical choices, or their choices in interpersonal contexts where costs are sunk by others. Children were not insensitive to costs, though, as children predicted agents would collect low-cost objects in the future. Together, the findings from this chapter show that children do not anticipate sunk cost bias across various scenarios. Chapter 3 tested between two accounts for why children overlook sunk costs when predicting actions. On one account, children do not see sunk costs as causing future outcomes, while on another, they can recognize this causal link but do not see actions as avoiding losses. In three experiments, 5-7-year-olds again did not expect sunk costs to bias others’ actions, as they responded at chance when predicting which objects agents would keep. However, children reasoned about sunk costs to predict emotion, anticipating that agents would feel sadder about high-cost objects. Together, the findings of this chapter support the view that children see sunk costs as causally relevant but do not expect actions to compensate for losses. Chapter Four examined whether children can be prompted to anticipate the sunk cost bias. Before predicting which objects agents would keep, children were asked about effort, waste, or negative emotion. In three experiments, children around age 6 predicted the sunk cost bias when prompted with effort and around age 7 when prompted with waste. Prompting children with waste did not always lead to sunk cost predictions, though, and children only showed some sensitivity to predicting the bias with negative emotion. Overall, this dissertation shows that children do not spontaneously predict the sunk cost bias. Yet, children are not entirely unable to reason about sunk costs, as they can recognize how sunk costs relate to waste, effort, and negative emotion, and predict the bias when prompted. This work deepens our understanding of children’s cost-based reasoning and the developmental trajectory of the sunk cost bias. This work also contributes to theories of the bias and raises questions about the role of experience and theory of mind in the emergence of sunk cost predictions.
Protecting Environmental and Cultural Water Through Collaborative Goverrnance and Impact Assessment: International, Canadian, and Saskatchewan Examples
(University of Waterloo, 2025-06-20) Bergbusch, Nathanael
Human activities and climate change threaten freshwater resources and Indigenous rights. Developments (e.g., irrigation, dams, mines) cumulatively pollute and alter the hydrology of fresh water, affecting ecosystems (environmental flow/water) and Treaty and Inherent Rights (cultural flow/water). However, development assessment and management may not guarantee the protection or connectivity of water downstream. Regional sustainability-based guidance is needed through collaboration between Crown and Indigenous governments. Through interviews, workshops, ecohydrology, and policy analysis, this dissertation investigates strategies for collaborative governance and impact assessment to protect water for the environment, human uses, and Indigenous rights at three scales: globally, nationally (Canada), and regionally (Saskatchewan’s Treaty Four). Treaty Four studies were co-created with File Hills Qu’Appelle Tribal Council’s Lands, Resources, Environment, and Stewardship Department (Ch. 2) and informed the design of global and Canadian studies. I systematically reviewed international English-language papers on the collaborative governance of environmental and cultural water to inform practice in Canada (Ch. 3). In Chapter 4, I investigated the uptake of environmental and cultural flows in Canadian legislation and assessment and suggested steps for their protection. Moving to Treaty Four, I examined barriers to water regulation (Ch. 5), developed flow-based sustainability criteria for the Qu’Appelle and South Saskatchewan sub-basins (Ch. 6), tested these criteria (Ch. 7), and proposed regional response options (Ch. 8) for the Lake Diefenbaker Irrigation Expansion and Agricultural Water Stewardship Policy (that promotes continued wetland drainage). Overall, dissertation findings established that, worldwide, communities need to have a greater role in environmental and cultural water policy, planning, and impact assessment (Ch. 3). In Canada, experts detailed a need for water councils to set needs-based rules for environmental and cultural flows maintenance ahead of development (Ch. 4). In Saskatchewan, water protection is challenged because of abstraction and drainage not triggering assessments, impact and project splitting, a lack of regulation, weak effort to meet the duty to consult, and the absence of regional approaches for identifying and managing cumulative effects of abstraction and drainage initiatives (Ch. 5). Collaborative regional governance (Ch. 8) was identified as needed to support progress towards sustainability through restoration of water and land, equity, respect for Treaties, transparency, climate uncertainty, and procedural justice (Ch. 6, Ch. 7). Together, these studies demonstrate the opportunity for more collaborative regional governance and impact assessment of environmental and cultural water in Canada and inform recommendations for future management and study, provided in Chapter 9.
Multi-scale Modelling of Neurosteroid-mediated Seizure Trajectories in Childhood Absence Epilepsy
(University of Waterloo, 2025-06-20) Ahmed, Maliha
Childhood absence epilepsy (CAE) is a pediatric generalized epilepsy disorder characterized by brief episodes of impaired consciousness and distinctive 2.5--5 Hz spike-wave discharges (SWDs) on electroencephalography. With a well-established genetic aetiology, this condition tends to resolve spontaneously during adolescence in most cases. While several mechanisms have been proposed for remission, understanding remains insufficient to guide early intervention practices. In this thesis, we first utilize a conductance-based thalamocortical network model that exhibits characteristic SWDs, to demonstrate that allopregnanolone---a progesterone metabolite known to enhance GABAa receptor-mediated inhibition---has an ameliorating effect on SWDs. To investigate the divergence between this finding and clinical observations, we developed an enhanced thalamocortical model that incorporates a layered cortical structure to explore regional cortical heterogeneity and frontocortical connectivity as potential resistance factors to ALLO-mediated recovery. Our results suggest that non-resolving CAE may be due not only to increased frontocortical connectivity but also to the composition of cell types within the network. Specifically, a higher proportion of bursting-type cells may prevent the therapeutic effects of allopregnanolone. We extended our investigation to examine whether these findings apply to CAE caused by different genetic mechanisms, particularly mutations in sodium channel genes by modelling their effects at the individual neuron level. Furthermore, we examined the degree to which these alterations lead to network-level pathological activity, as well as the influence of ALLO on these genetically distinct networks. Our results demonstrate that ALLO facilitates recovery from SWDs regardless of the underlying mutation type. However, enhanced frontocortical connectivity prevents recovery in some mutation types, particularly when mutation effects are severe. Altogether, the multi-scale computational framework developed in this thesis demonstrates that CAE remission is determined by complex interactions between hormonal influences, genetic factors, and network connectivity patterns. The results suggest that certain genetic mutations may predispose individuals toward either remission or non-remission, which can be further modulated by connectivity profiles. In particular, enhanced frontocortical connectivity appears to be a significant factor in resistance to hormone-mediated remission. Additionally, this thesis develops techniques for analyzing transitions between distinct dynamical states in neural systems, incorporates genetic and hormonal factors into conductance-based models, and provides a computational framework to identify key parameters governing epileptic activity. These approaches not only advance our understanding of CAE specifically, but offer generalizable insights into the mathematical modelling of neurological conditions characterized by spontaneous shifts in brain dynamics.
Phase Model Analysis of the Effect of Acetylcholine on the Neural Synchrony in Hippocampal Networks
(University of Waterloo, 2025-06-20) Manoj, Megha
Neural assemblies—transiently coordinated groups of neurons—are observed in the hippocampus and are thought to underlie the encoding and consolidation of episodic memories. Acetylcholine (ACh), a key neuromodulator, plays a critical role in learning and memory and has been implicated in neurodegenerative disorders involving hippocampal dysfunction. A well-supported hypothesis suggests that high levels of ACh during active exploration and rapid eye movement (REM) sleep promote memory encoding, while low levels during quiet waking and slow-wave sleep (SWS) support memory consolidation. In this study, we examine the bidirectional role of ACh in modulating neural assembly formation through its effect on neural synchrony in the CA3 region of the hippocampus. We construct a computational model of a network of excitatory pyramidal neurons, each equipped with a slow, voltage-dependent, non-inactivating potassium current (M-current), which is downregulated in the presence of ACh. Neural assemblies are modelled mathematically as cluster solutions—special types of phase-locked states. Using a phase model reduction of a pair of weakly coupled neurons, we analyze the existence and stability of cluster solutions that may emerge in larger networks equipped with all-to-all globally homogeneous, symmetric distance-dependent and nearest-neighbours coupling architectures. Our results suggest that ACh shapes assembly formation by modulating network dynamics in CA3. Under low ACh conditions, the network tends to fully synchronize, whereas high ACh levels enable the emergence of multiple stable cluster states, allowing for distinct patterns of activity associated with memory encoding. These findings propose a mechanism by which ACh regulates transitions in hippocampal network states, supporting distinct stages of memory formation.
Evaluation of Information Access Systems in the Generative Era
(University of Waterloo, 2025-06-20) arabzadehghahyazi, negar
The rapid advancement of information access technologies, including neural retrieval models and generative information-seeking systems, has outpaced traditional evaluation methodologies, exposing fundamental gaps in assessing their effectiveness. Existing evaluation frameworks struggle to adapt, particularly in the presence of sparse relevance labels, limiting their ability to fairly and comprehensively compare retrieval and generation-based systems. The emergence of large language models (LLMs) further complicates evaluation, as they challenge conventional assessment paradigms while offering new opportunities for automated evaluation. To address these issues, it is crucial to first identify flaws in current evaluation methodologies and then develop more robust, efficient, and adaptable assessment strategies. This thesis begins by demonstrating that evaluation based on sparse labeling introduces substantial biases and inconsistencies in system rankings, often failing to recognize genuine improvements in retrieval effectiveness. We show that in traditional IR benchmarks,stronger models may retrieve highly relevant but unjudged documents, leading to underestimation of their performance. To mitigate this, we propose an alternative evaluation approach based on distribution of retrieved results and labeled data using Fréchet Distance. This method not only improves robustness in the presence of sparse labels but also facilitates direct comparison between retrieval-based and generative models on a common evaluation scale. We then investigate how LLMs can be leveraged to evaluate IR systems, distinguishing between their use for evaluating retrieval-based methods and generative IR systems. A key focus of this work is the role of LLMs in automated relevance judgments. We systematically compare different LLM-based relevance assessment methodologies, highlighting the lack of standardization in evaluating these approaches. To address this gap, we propose a structured framework that evaluates relevance judgment methods based on their alignment with human labels and their impact on system rankings. Furthermore, we examine the effect of prompt formulation on LLM-based evaluation, demonstrating how prompt variations can significantly influence the consistency and reliability of assessment outcomes. Finally, we extend our study beyond retrieval-based evaluation to assessing generated content across multiple applications. We explore retrieval-assisted methods for evaluating generative textual content, IR-inspired approaches for assessing text-to-image generation models, and a broader framework for evaluating LLM-powered applications. These contributions lay the foundation for a new generation of evaluation methodologies that keep pace with evolving information access technologies, ensuring that improvements in retrieval and generative AI systems can be accurately and meaningfully assessed.
Transitioning from Vulnerability to Viability: Fisher community responses to illegal gold mining impacts on small-scale fisheries along the Ankobra river, Ghana
(University of Waterloo, 2025-06-20) Agyapong, Prince
Small-scale fisheries in Ghana’s Ankobra River basin are increasingly threatened by the expansion of illegal and small-scale gold mining (ASGM), resulting in environmental degradation, declining fish stocks, and reduced livelihood resilience. This thesis investigates the socio-ecological impacts of ASGM on fishing communities in Ajomoro Eshiem, Eziome, and Sanwoma, using a convergent mixed-methods approach grounded in the Social-Ecological Systems (SES) frameworks. The research aims to (a) Explore the nature of ASGM activities and the key characteristics of the small-scale fishery industry in the Ankobra basin, (b) Assess the socio-economic and ecological well-being of small-scale fisheries due to the impact of ASGM on livelihoods, (c) Investigate the adaptive strategies adopted by fishing communities in response to ASGM-related disruptions. Quantitative survey data, along with qualitative interviews and focus groups, were integrated to provide a comprehensive understanding of household expenditures, changes in fish catch, access to support services, compensation mechanisms, and the inclusion of women and marginalized groups in decision-making. Findings reveal that ASGM has led to substantial declines in fish catch, increased household expenditures to mitigate health and environmental impacts, and widespread dissatisfaction with compensation and support services. Women and marginalized groups remain largely excluded from local governance processes, further weakening community resilience. While some fishers employ livelihood diversification and collective action to cope, these strategies are constrained by limited institutional support and infrastructural deficits. This research highlights the urgent need for inclusive governance, targeted capacity building, and sustainable alternative livelihood programs to enhance resilience and ensure the long-term viability of fisheries-dependent communities. It contributes to the understanding of how mixed-methods and socio-ecological systems based analysis can inform policy and practice in mining-impacted regions. Further studies can support viable transition pathways for affected communities. Keywords: small-scale fisheries, illegal gold mining, livelihood resilience, social-ecological systems, adaptive capacity
100 mile fibre: The organization and governance of fibresheds in Southern Ontario and Northern Ohio
(University of Waterloo, 2025-06-19) deGroot, Amaryah
Textile overconsumption, propelled by a fashion industry that is global in scale and overly reliant on non-renewable feedstocks, has led to new models of fibre production. One model is the fibreshed, a regional-based fibre system that proposes circularity, local scale and suitability, and accessible mechanisms of governance. While fashion and design scholars have studied fibresheds, more research is needed to develop a theoretical understanding of them, their structures of governance and their contributions to sustainable fashion. To address these gaps, a case study was conducted on two fibreshed networks in North America. This research examined how the model is being delivered and the factors influencing its implementation, in particular, how regional fibre production is structured, managed and supported in two regions – Southern Ontario and Northern Ohio – areas which include the organizations of Upper Canada Fibreshed in Ontario and Rust Belt Fibershed in Ohio. Informed by existing scholarship in fashion, sustainable fashion and governance, and by theories on place and regions, this exploratory work involved interviews with key informants and a review of primary documents to draw an empirical understanding of the organization and governance of fibresheds. More specifically, it applied Benedum and Becker’s (2021) network governance framework to assess how fibreshed players organize, coordinate stakeholders and carry out their objectives of social accountability and regional development. By integrating sustainable fashion concepts with regional theories from geography and design, the results of this research emphasize the social-spatial dimensions of fibresheds. They also inform the study of other regional-based supply networks by reinforcing the impact of heterogeneity on network capacity and the need for producer involvement in decision-making. Such an analysis provides a critical foundation for progress toward the governance of sustainable fashion which values the players and leads to more meaningful engagement with sustainable consumption.
Trustworthy Machine Learning with Data in the Wild
(University of Waterloo, 2025-06-19) Lu, Yiwei
Recent advances in machine learning (ML) have been largely fueled by models trained on extensive internet-collected datasets. While this approach has yielded remarkable capabilities, it introduces critical vulnerabilities: training data can be untrustworthy, containing harmful content or becoming susceptible to data poisoning attacks. In such scenarios, model behavior can be maliciously altered, resulting in reduced test performance for classification models or the replication of copyrighted materials for generative models. This thesis examines the influence of untrusted training data on machine learning training dynamics through two crucial perspectives: the ML developer's lens, focusing on model integrity, and the data owner's viewpoint, addressing privacy and copyright concerns. Specifically, this thesis analyzes the impact of data in the wild from both theoretical and empirical perspectives. The first part formulates data poisoning attacks (specifically, accuracy degradation attacks) as bi-level optimization problems, also known as Stackelberg games. It provides a viable algorithm to poison modern machine learning models, particularly neural networks, which demonstrate significantly greater robustness to such attacks compared to traditional linear models. The second part investigates this robustness distinction and develops a principled theoretical framework for understanding the effectiveness boundaries of data poisoning attacks across various scenarios. Given some clean training data, a target model, and malicious parameter objectives, this theoretical tool determines the minimum amount of poisoned data required to achieve these parameters, thereby quantifying the fundamental limits of data poisoning attacks. Building upon the understanding of data poisoning attacks in supervised settings (i.e., classification tasks), this thesis further examines their threats in two realistic machine learning pipelines. The third part presents the first comprehensive analysis of data poisoning attacks against pre-trained feature extractors—components frequently utilized for various downstream ML tasks, such as adapting large models to medical data. This analysis reveals that drastic domain shifts can significantly increase ML models' vulnerability to data poisoning attacks, necessitating more robust countermeasures. The final section examines the role of harmful data in generative models, specifically focusing on advanced latent diffusion models for text-to-image generation tasks. Copyright infringement concerns arise when such models produce outputs substantially similar to copyrighted training data. This section introduces a novel scenario termed "disguised copyright infringement" incurred by targeted data poisoning attacks, providing a thorough description of potential attack vectors and corresponding defensive strategies.
Investigating Changes in Mercury Concentrations in Small-Bodied Fishes Following Mine-Related Flooding in the Canadian Arctic
(University of Waterloo, 2025-06-19) Soogrim, Noel
Mercury (Hg) is a globally distributed contaminant that, in its methylated form (methyl mercury (MeHg)), is a potent neurotoxin that bioaccumulates and biomagnifies in aquatic food webs. At high enough exposures, Hg can pose risks to wildlife and human health. While Hg concentrations in aquatic ecosystems have been relatively well-studied in boreal systems, less research has been conducted in Arctic freshwater ecosystems, particularly in Barrenland tundra lakes that are increasingly affected by industrial activity and climate-driven change. This thesis examined the effects of a mine-related flooding event at the Amaruq project site in Nunavut, Canada, on aqueous and biological concentrations of Hg in a series of shallow Arctic lakes. Concentrations of total mercury (THg) and methyl mercury (MeHg) in water, indicators of organic matter (OM) quantity and quality in water, including concentrations of dissolved organic carbon (DOC), humification index (HIX), and specific ultraviolet absorbance (at 254 nm; SUVA) and concentrations of Hg in the tissues of Slimy Sculpin (Cottus cognatus) and Ninespine Stickleback (Pungitius pungitius), were compared: 1) before and after flooding in impacted lakes; and, 2) between flooded and reference lakes in the post-flood years. A series of potential covariates of fish Hg concentrations, including fish age, condition, C: N, δ13C, and δ15N, were also compared between pre- and post-flood years and between flooded and reference lakes. Aqueous concentrations of THg and MeHg were significantly higher in flooded lakes compared to reference lakes (THg filtered: p = 0.01; MeHg filtered: p < 0.001) in post-flood years. In flooded lakes, concentrations of THg and MeHg were significantly higher in post-flood years compared to pre-flood years (p < 0.05) whereas there were no significant differences among years in reference lakes (p > 0.28). Concentrations of DOC were significantly higher in flooded lakes than in reference lakes in post-flood years (p < 0.001), suggesting increased terrestrial OM inputs. Higher MeHg concentrations and higher % MeHg in water in flooded lakes relative to reference lakes in post-flood years may indicate that terrestrial OM inputs increased net Hg methylation rates, but there was no difference in % MeHg between pre- and post-flood years in the flooded lakes (p < 0.05). Evidence for enhanced methylation post-flood is thus mixed, and more research is necessary. Fish tissue Hg concentrations were significantly higher in flooded lakes than in reference lakes in the post-flood years for both Slimy Sculpin (p < 0.001 in 2020 and 2021) and Ninespine Stickleback (p = 0.002 in 2021). Within flooded lakes, tissue Hg concentrations in both species were significantly higher in the post-flood years relative to pre-flood years (Slimy Sculpin: F₃,₂₆₁.₇₁ = 14.53, p < 0.001; Ninespine Stickleback: F₃,₁₁.₀₆ = 33.96, p < 0.001). Flooding-induced increases in fish Hg concentrations appeared to be most closely related to concomitant decreases in δ¹³C; δ¹³C ratios were significantly more depleted in post-flood years (Slimy Sculpin: F₃,₃₁₅.₂₈ = 20.11, p < 0.0001; Ninespine Stickleback: F₃,₃₆₇.₃₃ = 5.38, p = 0.001) compared to pre-flood years, and were negatively correlated with fish Hg concentrations (Slimy Sculpin: r = -0.72; Ninespine Stickleback: r = -0.63). These results suggest a shift in basal carbon sources, likely reflecting increased reliance on terrestrially derived, allochthonous OM. The strong correlation between δ¹³C and Hg concentrations indicates that OM dynamics played a central role in driving Hg bioaccumulation in the food web. Other potential covariates of fish Hg concentrations, including relative condition, C:N ratio, and length-at-age, explained less variation in Hg concentrations and/or did not appear to be affected by flooding, although weak negative correlations between Hg concentrations and condition were observed. While the general patterns observed in this study align with findings from boreal systems subjected to flooding, it is possible that Arctic lakes are uniquely vulnerable to flooding-induced Hg mobilization and increases in fish Hg concentrations due to their low productivity and catchments with permafrost. These characteristics may increase the release of OM and Hg during flooding and increase bioaccumulation of newly released Hg. Despite limitations in sampling design and data availability, results of this study provide the first empirical evidence linking industrial flooding to increases in Hg concentrations in Arctic lakes. Results underscore the need for long-term contaminant monitoring in remote tundra regions where climate warming, industrial development, and permafrost degradation are expected to intensify. Given the cultural importance of fish for northern communities, understanding how environmental disturbances affect Hg bioaccumulation is critical for protecting both ecosystem and human health in the Arctic.
I Saw You in the Archive
(University of Waterloo, 2025-06-19) Smith, Paige
I Saw You in the Archive is a multidisciplinary exhibition that reveals the history of eugenic practices in Kitchener-Waterloo in the mid 20th century. The exhibition questions how the framing of history impacts our personal understandings of each other’s identities. Mixing visuals associated with institutional archives and rubber factories, the artworks examine the former Kaufman Rubber Company and its owner A. R. Kaufman’s attempts to contain certain types of people, particularly those deemed ‘feeble-minded’. The exhibition embodies my experience parsing through this complicated history as a queer and neurodiverse woman—digging through a cacophony of propaganda pamphlets, shoe sale reports, instruction manuals for birth control use, blueprints of the factory, and photography of the workers. Seen through video documentation, I reintroduce remnants from the archive to the contemporary condominium that was formerly the rubber factory, connecting past rhetoric to today’s circumstances. The complicated layers of eugenics, birth control access, disability rights, and feminism seep into each other and spill into the gallery. Through use of performance and site-specific interventions, I challenge the internal shame many who have been othered experience and resist systems of containment that aim to erase our identities.
Boredom as a Motivator of Pain Infliction in Psychopathy
(University of Waterloo, 2025-06-18) Lee, Jessica
Maladaptive behaviours have been associated with both psychopathy and boredom proneness—however, there remains limited evidence of how they interact to influence these behaviours. Given that psychopathy has been linked to boredom susceptibility, it is possible that boredom contributes to harmful behaviours in psychopathy. This thesis addressed this gap by investigating the interplay between boredom proneness, psychopathy, and the inclination to inflict pain on others. Chapter 1 described the current literature on how boredom and psychopathy influence maladaptive behaviours and highlighted limitations in the extant literature. The following chapters were comprised of four studies: the first study (Chapter 2) explored how individuals with different levels of psychopathy and boredom represented emotions in their bodies, to determine whether the traits of boredom proneness and psychopathy were associated with distinct embodied representations of affect. This was deemed important given the role both state and trait boredom would play in subsequent experimental chapters. Results showed that the embodied experience of boredom did not substantially differ as a function of psychopathy or boredom proneness. The second study (Chapter 3) examined whether boredom (both trait and state) and psychopathy traits exacerbated the tendency to inflict physical pain through an online game scenario. Results showed that state boredom diminished aggression strength in those with higher levels of psychopathy, particularly primary psychopathy. The final two studies (Chapter 4) investigated the likelihood of inflicting social pain using novel scenarios in which participants could choose to inflict social pain on a fictional person. In both Study 4A and 4B, trait boredom proneness did not emerge as a significant moderator between psychopathy and choosing socially painful options. However, when forced to consider the likelihood of choosing each option, boredom proneness did act as a significant positive moderator between psychopathy (and primary psychopathy) and social pain infliction. Chapter 5 concluded with a summary of the research findings and explored possible explanations for the discrepancies observed in the results, addressed the limitations of the current studies, and suggested avenues for future research.
“You don’t expect a man to make good policies that affect women’s health”: Exploring barriers and opportunities to gender transformative policymaking and programming in Ghana’s health and WaSH sectors.
(University of Waterloo, 2025-06-18) Meho-Akakpo, Pascal
Gender inequality is a prevailing global issue, particularly in Sub-Saharan Africa (SSA), a region highly influenced by patriarchal structures. Gender, a socially constructed concept that encompasses the roles, behaviors, customs, norms, and characteristics identified with men and women, significantly influences life choices, including those associated with health and wellbeing. In an attempt to perform socially ascribed gender roles in SSA relating to Water Sanitation and Hygiene (WaSH), women's health and wellbeing are substantially, typically adversely, impacted. Despite efforts by policymakers and other stakeholders to address gender inequalities in health and WaSH these issues persist. These efforts have been criticized for either lacking a gender focus and/or not deliberately addressing the root causes of gender inequalities or often only focusing on infrastructure access. There have been calls to adopt the Gender Integration Framework (GIF)1 to assess how gender policies address gender norms and inequalities from policy formulation to implementation, and the impacts of these policies in transforming harmful gender norms. Ghana has made progress in formulating gender-related policies and programs in both the health and WaSH sectors; however, gender inequalities persist, especially in rural communities. While research has begun to examine gender-transformative policymaking in the health and WaSH sectors, there has been a limited focus on the perspectives of stakeholders to ascertain their level of awareness of gender-transformation and the opportunities in adopting gender-transformative approaches to address these challenges on the ground. Through a qualitative case-study research design, the thesis begins to fill this gap by exploring stakeholders' knowledge and perspectives about gender transformation as well as identifying barriers and opportunities to gender transformative policymaking and programming in Ghana's health and WaSH sectors. Specifically, the research addressed the following objectives: (1) To explore stakeholders' knowledge and perspectives of gender transformative policymaking and programming in Ghana; (2) To identify barriers to gender transformative policymaking and programming across Ghana's health WaSH sectors. (3) To explore the opportunities within existing government policies to break down barriers to women's empowerment in WaSH. Semi-structured interviews with stakeholders (n=30) in three districts in the Upper West Region of Ghana were conducted from July to August 2024. Participants were purposely sampled from government agencies (n=11), civil service organizations (n=7), and community leaders (n=12). Interviews were digitally recorded and transcribed verbatim for subsequent thematic analysis. The results revealed a significant awareness among stakeholders regarding gender-transformative policymaking and programming in Ghana's health and WaSH sectors. This awareness is attributed to their educational status and/or experience in gender-related fields. Despite the awareness, the findings showed a lack of consensus on what gender transformation entails, as stakeholders approach gender-transformative policymaking and programming based on their institutional goals and visions. Participants also revealed institutional and community-level barriers impeding the full potential of gender transformative policies and programs; these included, at the community level: socio-cultural, financial, logistics, monitoring and evaluation, and corruption. Institutional barriers included: bureaucracy, political commitment, women’s representation, and consultation. The National Health Insurance Scheme, Community-based Health and Planning Services, Community Water and Sanitation Program, and Mother-to-Mother Support Initiative were identified as existing gender-transformative policies and programs with significant potential to transform harmful gender norms and empower women. The results of this thesis research contribute to the broader discussion on gender-transformative policies and programming and their potential to address gender inequalities in health and WaSH. They also contribute to the evidence of the shortfalls of the identified gender-transformative policies and programs, which can inform policy and practice review. Future research that can build on these results includes women empowerment in WaSH, gender norms and gender-based violence, among others.
Promoting positive mental health among individuals with eating disorders: Investigating the role of self-compassion
(University of Waterloo, 2025-06-18) Katan, Aleece
There is a call in the eating disorders field to identify factors that not only reduce eating pathology, but that also promote positive mental health and well-being in individuals with eating disorders. Yet, little is known about factors that might accomplish both of these goals. Self-compassion refers to the desire to respond to one’s own distress in a mindful, caring, and understanding manner, coupled with the motivation to prevent and alleviate it. Self-compassion has been found to be associated with reduced eating pathology in people with eating disorders, but no research has examined whether it might also give rise to more positive mental health in this population. However, theoretical and empirical research conducted in diverse non-clinical samples suggests that treating oneself in a self-compassionate manner, both on a given day or in general, can promote markers of positive mental health and well-being. Three longitudinal studies spanning different contexts, durations, and eating disorder populations sought to test the overarching hypotheses that treating oneself with more self-compassion than others or than one’s typical level, such as on a given day or following brief periods of time, would be associated with increased markers of positive mental health (i.e., positive affect, social safeness, and adaptive coping behaviours) in individuals with eating disorders. Study 1 utilized a two-week daily diary design to explore whether daily and trait (i.e., average) levels of self-compassion promoted positive affect and social safeness (i.e., a sense of social connection and belonging) in a community sample of women with typical and atypical anorexia nervosa who were not seeking treatment for their eating disorder. Multilevel modelling revealed that, consistent with hypotheses, higher levels of self-compassion on a given day, than the previous day, and on average over the study period, were associated with greater positive affect and social safeness. In Study 2, a two-week daily diary investigated whether daily and trait levels of self-compassion predicted adaptive coping behaviours in a community sample of women with symptoms of bulimia nervosa. In line with my hypotheses and the findings from Study 1, multilevel modelling revealed that natural upward fluctuations in self-compassion levels from day to day, and trait or average self-compassion levels over the study period, were generally associated with the use of more adaptive coping strategies. Study 3 examined the links between self-compassion and social safeness over a 12-week period in a transdiagnostic sample of individuals receiving inpatient or day hospital treatment for their eating disorder. Multilevel modelling revealed that, as hypothesized, periods of increased self-compassion were associated with a greater subsequent sense of social safeness. Further, consistent with my hypothesis, higher average levels of self-compassion over the course of the 12 weeks of eating disorder treatment were associated with more social safeness. In sum, the current findings largely lend support for my overarching hypothesis: that one’s ability to treat themselves with more self-compassion than is typical for them, including on a given day or over a brief period of time, or than other people, is associated with improved positive mental health. Importantly, the current findings highlight the potential clinical benefits of incorporating self-compassion practices into both eating disorder treatments and the daily lives of individuals with eating disorders. This way of compassionate self-relating, which can be learned, may have a significant, multifaceted impact. Self-compassion interventions have already been shown to help reduce harmful eating behaviors in previous research; however, the current findings suggest that these practices might also enhance markers of positive mental health in eating disorder samples. Therefore, directly targeting self-compassion could provide an effective way to achieve the shared goals of both clinicians and individuals with eating disorders: reducing symptoms of the disorder and enhancing overall quality of life.

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