Electronic Theses and Dissertations (ETD)
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All theses from 2011 to the present are in this collection, as well as some from 2010 and earlier years.
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Item Balancing energy and ecosystems: Exploring the spatiality of renewable energy development for a low-carbon future(2025) Willard-Stepan, Maya; Hoicka, Christina; Bone, ChristopherFossil fuel energy production, as one of the most significant drivers of climate change, is causing extreme social and environmental harm worldwide. These circumstances necessitate a transition to low-carbon energy sources. A key factor in the expansion of low-carbon energy systems is the potential impact this development may have on other benefits provided by the environment, such as food or materials, commonly referred to as ecosystem services. There is currently limited knowledge beyond the regional scope of how energy development is impacting these services; an important consideration, as local studies cannot consider the full spectrum of global environmental impacts. The research outlined in this thesis uses an exploratory methodology to examine the spectrum of environments in which renewable energy projects are constructed in, and which ecosystem services are most likely to be impacted by the expansion of renewable energy globally, both for single-technology and clustered renewable energy power plants. First, in Chapter 3, I analyse the land cover and associated ecosystem services surrounding global power plants. In Chapter 4, I reproduce this analysis on a growing global dataset of renewable energy projects that utilize multiple types of resources, known as clusters. These results are compared with those discussed in Chapter 3 to assess how the configuration of energy systems influence the land they are constructed on. I find that hydropower and wind power show the highest occurrence in ecosystem service rich environments, creating the largest risk of ecosystem service loss from renewable energy production, while clustered energy systems are placed in areas which decrease the risk of ecological trade-offs. As renewable energy continues to develop, incorporating other land considerations will be critical in ensuring the energy transition minimizes harm to the natural environment for which we all rely on.Item Unsettled futures: Pathways for Indigenous solidarity on Haida Gwaii(2025) Weder, Julia; Rowe, James K.Haida scholars and community leaders have made it clear that non-Haida people can (and should) contribute to the collective protection, well-being, and resilience of Haida Gwaii. There is a lack of clarity among many settlers, however, around their agency in the anti-colonial movement and methods for addressing settler colonial logics in the community. To address this gap, I reviewed literature on settler colonialism and non-Indigenous agency in collective social liberation, and conducted 13 interviews with Haida and non-Haida community members. I explored three research questions. (1) What approaches, practices, and tools have been successfully used by other communities and social practitioners/organizations to support settler (un)learning and transformation? I found that helping people foster deeper relationships with land and ancestry, exploring shared place-based histories, engaging in reading, discussion, and embodiment-based courses, and using art as a tool for knowledge-sharing are examples of effective social/educational tools. (2) What past or current spaces/movements on Haida Gwaii have fostered dialogue around settler responsibilities and conceptions of Haida sovereignty? A key finding was that Haida Gwaii has a rich history of alliances between Haida and settler peoples – in support of Haida title and resurgence, to protect Haida Gwaii’s lands and waters, and in resistance to corporate industrial invasion – which have been powerful sites of personal transformation and solidarity-building. (3) What approaches, practices, and tools might be effective for settlers in Daajing Giids with various perspectives to critically interrogate and transform mindsets around settler identity and Haida sovereignty? How can passive allies or more neutral residents be brought more into the fold of anti-colonial action? I found that among local community organizers, a politics based on relationships and shared interests (such as a connection to place and the health of the community’s air, water, and food sources) was favoured over a politics of identity, shame, and deference; the latter of which risks homogenizing or unnecessarily burdening the Haida community. Neutral or passive allies could be engaged by creating opportunities for in-person relationship-building and supporting residents in witnessing Haida business at potlatches and other political/cultural events. Ultimately, I saw great interest among participants to strengthen networks and practices of mutual aid, support one another in subverting settler colonial habits and structures, and continue to build popular social power that aligns with the interests of the Haida Nation.Item The emergence of novel disturbance in Jasper National Park – evaluating the causes and implications of 100 years of landscape change using repeat photography(2025) Tricker, James; Higgs, EricRecurring disturbance has a strong influence on the bounds of ecosystem variability. The concept historical range of variability (HRV) describes these bounds, providing a sense of the range of ecosystem characteristics exhibited in response to disturbance and recovery over time and space. Altered and novel disturbances can drive changes in ecosystem composition and configuration that depart from the HRV and lead to regimes shifts. In Jasper National Park, a systematic set of historical and repeated oblique photographs depict montane landcover in the aftermath of extensive fires in 1915 and a mountain pine beetle (MPB) outbreak in 2020/22. However, the MPB disturbance is historically unprecedented, and raises important questions about whether the characteristics of this event are within the HRV of the montane ecosystems. The focus of this dissertation is to apply a new workflow for deriving landcover maps from oblique photographs to evaluate the landcover changes that have occurred in the park’s montane ecoregion over the last 105 years. The workflow comprises a deep learning algorithm that automates the classification of landcover evident in grayscale and color oblique photographs and a georeferencing tool that incorporates these data into a GIS. I report on the accuracy of the data produced by the workflow (Chapter 2) and quantify the changes in composition and configuration of broad landcover types after the two disturbance events for a study area in the montane ecoregion (Chapter 3). A scenario planning exercise is then undertaken to evaluate the uncertainty surrounding the implications of these changes and the potential for future novel disturbance events (Chapter 4). Georeferencing accuracy using root-mean-square error for a subset of 7 images was 4.6 m and overall classification accuracy for the landcover map produced from oblique photographs using the new workflow was 68%. The change analysis in the montane ecoregion indicated that the MPB outbreak has returned a version of heterogeneity evident in 1915 to the landscape by reducing the dominance of mature conifer (both in composition and configuration) across the landscape. Four scenarios then describe alternative futures in the park based on different levels and combinations of ecological novelty and management intervention. The value of this research is to validate the development of a new workflow for analyzing historical and repeat photographs, increase the temporal depth of ecological monitoring in the park, and allow managers and restoration practitioners to develop a better understanding of how and where novel disturbance is altering ecological processes and could reoccur in the future.Item Investigating the function of eosinophils in mucosal immunity(2025) FitzPatrick, Rachael D.; Reynolds, Lisa A.Eosinophils are a highly abundant immune cell type in the gastrointestinal (GI) tract at steady-state, where they have recently been reported to contribute to tissue homeostasis in response to nutrient and bacterial microbiota-derived signals. Eosinophils are also elevated in the GI tract of some individuals with inflammatory bowel disease (IBD) who are also more susceptible to enteric bacterial infections. Further, therapies to treat hypereosinophilic syndromes have been designed to deplete eosinophils from the human body rendering some people completely devoid of this cell type. Together, these observations emphasize the need to gain a deeper understanding of the role of eosinophils in the GI mucosa. In this thesis, I examine the function of eosinophils under three different contexts within the murine intestinal tract: 1) steady-state secretory immunoglobulin A (sIgA) production, 2) enteric bacterial infection, and 3) the development of oral tolerance. We find that contrary to previous reports, eosinophils are not essential for the maintenance of sIgA in the GI tract at steady-state. Instead, our findings emphasize the importance of optimally controlling rearing and housing conditions throughout life between mice of different genotypes when their phenotypes are being assessed. Further, we determine that eosinophils are responsive to an enteric infection with the bacterial pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) but not essential for controlling S. Typhimurium colonization within the GI tract. Finally, we established a mouse model to investigate the contribution of eosinophils to oral tolerance development in early life. Using this model, we uncover immune responses to dietary antigens unique to the early life period and determine that eosinophils are not an essential cell type contributing to oral tolerance in early life. Collectively, these results contribute to our understanding of eosinophils within the GI mucosa, which ultimately will help inform treatment strategies for people living with elevated or depleted levels of eosinophils. Further, our findings lay the groundwork for future well-controlled and robust studies of eosinophils as well as oral tolerance development during the early life period.Item Bandwidth tomography(2025) An, Jianwei; Wu, KuiBandwidth tomography—inferring the bandwidth of internal network links from end-to-end path bandwidth measurements—is a long-standing open problem in network tomography. The core challenge arises from the fact that no existing mathematical framework directly addresses the inverse problem formulated as a set of min-equations. To systematically tackle this challenge, we design a polynomial-time algorithm that accurately determines the bandwidth of all identifiable links and derives the tightest possible error bounds for unidentifiable links based on a given set of measurement paths. Furthermore, when additional information on link correlations is available, we leverage the extra information to refine our error bounds. Specifically, we explore two key types of link correlations: fairness constraints and total capacity constraints among a node's adjacent links. We provide theoretical guarantees on how these correlations enhance the precision of bandwidth tomography and develop algorithms to address two fundamental challenges in refining these bounds: (i) the impact of synchronous vs. asynchronous updates and (ii) the cascading effects during bound updates. Having developed algorithms to derive the tightest possible performance bounds for a given set of measurement paths, we then tackle the next major challenge: constructing optimal measurement paths that minimize the global error bounds for unidentifiable links. We prove the hardness of this problem and, in response, propose a reinforcement learning (RL) approach for measurement path construction. Our solution leverages domain-specific knowledge in bandwidth tomography and integrates both offline training and online prediction to build suitable measurement paths. We evaluate our proposed methods using real-world ISP topologies and simulated networks. Experimental results show that compared to existing path construction methods—Random and Diversity Preferred—our RL-based approach significantly reduces the average error bound of inferred link bandwidths. In addition, our performance bound computation algorithms improve the state-of-the-art techniques by substantially tightening the performance bounds in bandwidth tomography.Item Three ethical dimensions of AI: Fairness in social recommenders, bias detection in LLMs, and privacy in NLP(2025) Potka, Shera; Thomo, AlexThis thesis investigates three foundational challenges in the development of responsible Artificial Intelligence (AI): fairness in social recommender systems, demographic bias in large language models (LLMs), and privacy-preserving techniques for Natural Language Processing (NLP). Though these problems differ in technical scope and application domain, they share a common thread: vector-based representations—embeddings of users, words, and tokens—fundamentally shape how AI systems behave, make decisions, and affect people. Across these three dimensions, this work introduces new methods for measuring, interpreting, and mitigating risk, offering solutions grounded in both empirical analysis and practical utility.The first part of the thesis (Chapter 2) examines fairness in algorithmic link recommendation, with a focus on how structural minority communities—groups defined by network topology rather than identity—are represented in evolving social graphs. Standard recommenders tend to amplify popular users, reinforcing visibility gaps over time. We propose MinWalk, a fairness-aware algorithm that improves minority visibility while maintaining network stability. Simulations on real-world networks show that fairness- and diversity- aware algorithms vary widely in long-term impact, and that MinWalk offers a balanced, effective solution. This work underscores the importance of evaluating fairness dynami- cally and provides tools for designing more inclusive recommendation systems. The second part (Chapters 3 and 4) turns to demographic bias in LLM behavior. We analyze gender and race associations in contextual embeddings from five leading models developed by OpenAI, Google, Microsoft, Cohere, and BGE. Using the SC-WEAT metric and clustering techniques, we show that stereotypical associations persist and are amplified in modern embeddings. We also examine how these biases appear in real-world applications, focusing on consumer product recommendations. Using prompt engineering and computational linguistics methods—including Marked Words, SVM classification, and distributional divergence—we find that LLMs generate demographically skewed suggestions that reinforce social stereotypes. These findings highlight the risks of bias in LLM outputs and offer concrete tools for auditing fairness in generative systems. The final part (Chapter 5) addresses privacy in NLP, where the challenge lies in re- moving sensitive information from text without damaging meaning or fluency. Existing approaches either prioritize privacy but degrade text quality, or preserve fluency at the cost of weaker guarantees. To address this, we propose CluSanT, a flexible framework that uses token clustering and controlled replacement mechanisms to balance privacy and utility. Unlike prior methods, CluSanT retains strong privacy protection while producing more natural, semantically faithful text. We evaluate it using a range of metrics—including coherence, grammar, and semantic similarity—showing that it consistently improves over baselines on a legal benchmark dataset. Our results demonstrate that text sanitization can be both effective and intelligible to human readers. Taken together, this thesis presents a unified perspective on ethical AI through the lens of embeddings. In social networks, language generation, and privacy-preserving NLP, vector representations are not neutral—they encode power dynamics, preferences, and access. By examining how these embeddings influence visibility, bias, and confidentiality, this work contributes both practical algorithms and conceptual frameworks for designing fair, inclusive, and trustworthy AI systems.Item Impacts of heatwaves and hypoxia on gene expression in the pacific oyster and the development of monitoring and mitigation tools for summer mortality(2025) Bickell, Andrew; Pearce, Christopher Michael; Bates, AmandaMarine heatwaves and coastal hypoxic events are increasing in frequency and intensity under anthropogenic climate change, resulting in widespread mass mortalities of the Pacific oyster (Crassostrea gigas). Those mortality events threaten the economic stability of global aquaculture, yet strategies to monitor oyster health and mitigate losses during periods of environmental stress are largely limited. Changes in gene expression of C. gigas in response to laboratory-simulated heatwaves and hypoxic events were assessed to identify candidate monitoring genes and explore artificial aeration as a potential mortality mitigation strategy. Two laboratory experiments were performed, exposing farmed C. gigas to simulated 10-day heatwave and hypoxic conditions similar to a 2021 marine heatwave that triggered farmed oyster mortality in Baynes Sound, British Columbia, Canada. Gill tissues were periodically sampled during the experiments and total RNA was extracted to explore patterns of gene expression via RNAseq and qPCR. Five candidate genes were consistently differentially expressed in both experiments— death-associated inhibitor of apoptosis 2 (A2I), high mobility group protein DSP1 (DSP1), high mobility group box 1 (HMGB1), heat shock protein 90 (HSP90), and peptidyl-prolyl cis-trans isomerase (PPCTI)—demonstrating potential for monitoring summer mortality. No significant differences in expression of the general stress marker genes heat shock protein 70 (HSP70) and heat shock protein 20 (HSP20) were detected, suggesting that genes related to immune function and regulation of transcription may be more appropriate for monitoring summer mortality. In addition, the presence of artificial aeration resulted in significantly lower HSP90 relative expression, suggesting some potential utility in stress mitigation during heatwaves. The present work provides insights into the role of heatwaves and hypoxia in Pacific oyster summer mortality and will inform effective monitoring and mitigation practices to support the adaptation of shellfish aquaculture to the growing impacts of climate change.Item A deeper look: The development of global peat depth datasets and subsequent carbon stock estimates(2025) Skye, Jade Erin; Melton, Joe; Goldblatt, ColinPeatlands are important carbon stores which are being destabilised by anthropogenic activity and are sensitive to climate change. To faithfully assess the carbon stored in peatlands and to model their responses to future climate scenarios, it is essential to have accurate information on peat depth. Presently, however, observations of peat depth are insufficient for conducting these tasks at the global scale. Thus, the goal of my thesis is to accurately generate a global distribution of peatland depth and use that distribution to estimate how much carbon is stored within them. The first step was to create Peat-DBase, the largest database of harmonised peat depth measurements at the global scale. Peat-DBase was then used as the basis of training and testing data for PeatDepth-ML, a machine learning-based modelling framework designed to predict peat depths globally. I created PeatDepth-ML by adapting an existing modelling framework that was designed to predict peatland spatial extents by including new datasets of environmental variables that may drive or indicate peat formation, updating the cross-validation procedures used for model testing, and adding a custom scoring metric to the model to assist in predicting deeper peat depths. I then used PeatDepth-ML to produce a spatially continuous global map of peatland depths. Inspection of Peat-DBase revealed regional data gaps, such as in the Tropics, and potential sampling biases in peat depth measurements, e.g. the collecting of a single peat core to represent the depth of an entire peatland wherein depth could be varying significantly or the presence of multiple peat cores with highly varying depths over small spatial scales. The impact of Peat-DBases's regional biases on PeatDepth-ML's predictions was assessed by calculating a metric describing the predictions area of applicability. To test the sensitivity of PeatDepth-ML to some aspects of sampling bias, a bootstrapping method was developed to create multiple training datasets from Peat-DBase. Running PeatDepth-ML on the bootstrapped datasets showed that model behaviour could vary significantly in response to changes in the training data, particularly at the regional scale. When compared to other estimates in the literature, PeatDepth-ML achieved a similar or improved level of performance and is of better overall quality because of its global reach and continuous representation of peat and non-peat regions without the use of an independent peatland extent map. However, PeatDepth-ML demonstrated a tendency to predict towards the mean peat depth of its training data, which was relatively shallow possibly due to the inclusion of non-peat data, which was included to allow the model to predict over all regions. Performing simple carbon stock calculations using PeatDepth-ML’s results produced estimates that are in line with those previously published. Collectively, Peat-DBase and PeatDepth-ML are cohesive global datasets of peat depth that can aid future peatland research and policy endeavors.Item Single mutation effects on protein secondary structure(2025) Perez Martell, Raul Ivan; Stege, Ulrike; Jabbari, HosnaHuman diversity often manifests through single nucleotide polymorphisms (SNPs). Among these polymorphisms, SNPs that alter amino acids can modify a protein's three-dimensional structure. Such single amino acid mutations can impact the protein's function and potentially elicit diseases or affect drug interactions. Thus, understanding protein single point mutations is crucial for precision medicine, as it helps tailor treatments based on individual genetic variations. Protein tertiary structure prediction models like AlphaFold2 have revolutionized the field with unprecedented accuracy, yet predicting structural changes arising from single amino acid mutations remains a challenge. The complexity introduced by these mutations calls for models that can incorporate mutational information into their predictions. As atomic locations can be susceptible to any number of changes that might or might not affect function, we focus on the secondary structure to provide concrete results on possible protein structural deformation that may occur from single amino acid mutations. We assess state-of-the-art structure prediction methods regarding backbone deformations caused by single amino acid mutations. We categorize these deformations as local, distant, or global based on the proximity of structural changes to the mutation site. Our analysis utilizes a diverse dataset from the Protein Data Bank, comprising over 500 protein clusters with experimentally determined structures and documented mutations. Our findings indicate that single amino acid mutations can significantly affect the accuracy of structure prediction methods. These mutations often lead to predicted structural changes even when the actual secondary structures remain unchanged, suggesting that current methods overestimate the impact of single amino acid mutations. This issue is particularly evident in advanced prediction algorithms, which struggle to accurately model proteins with stable mutations. We also found that the addition of low-performing prediction methods during structural analysis can positively impact the results on some proteins, particularly those with low levels of homology. Furthermore, proteins that form complexes or bind ligands—such as membrane and transport proteins—are inaccurately predicted due to the absence of extra-molecular interaction data in the models, highlighting how single amino acid mutations can complicate accurate structure prediction. Due to these findings, we propose a novel refinement strategy for protein secondary structure prediction that leverages single amino acid mutational data. As part of this strategy, we introduce Mut2Dens, a model that not only yields more consistent predictions for mutational data but also maintains robust predictive performance on non-mutational datasets. These refined models take multiple predicted secondary structures and generate a mutation-aware secondary structure. In particular, Mut2Dens employs the extremely randomized trees algorithm to avoid overfitting and make effective use of the limited mutational data available from experimentally determined three-dimensional structures. By combining predictions from highly accurate structure prediction models, we create an ensemble that integrates their strengths while enhancing mutational capabilities. This refinement strategy also improves the non-mutational performance of state-of-the-art methods by addressing their most inaccurate and least confident predictions. Moreover, our refinement strategy reduces improbable outcomes in mutated protein structures—such as transforming π-helices into β-sheets—that can still occur in current prediction models. Finally, by using interpretable machine learning algorithms, we can reveal the underlying biological knowledge from the refinement model. The insights gained from Mut2Dens can be corroborated with known mutational outcomes, helping users pinpoint discrepancies across structure prediction models and make more informed decisions regarding the predicted structures.Item Development of a performance measurement framework for the leadership fund(2025) Matthewman, Spencer; Castle, DavidAnnounced in Budget 2016 as part of the Pan Canadian Framework on Clean Growth and Climate Change, the Low Carbon Economy Fund aimed to advance Canada towards meeting its Paris targets by providing financial support for GHG reducing and clean growth projects. The client, Environment and Climate Change Canada’s Methodology and Evaluation Division, requested the development of a performance measurement framework for the Low Carbon Economy Leadership Fund (i.e., the Leadership Fund) to summarize key findings and general themes and support its recapitalization. The study employs a gap analysis to develop key performance indicators by assessing current performance mechanisms, defining a desired state based on available program data, and addressing the gaps between those states. Methods include a review of funding agreement and internal progress reports for each portfolio component across the three implementation stages. All components are classified by geographic region, component type, and economic sector to support the thematic analysis, with individual inclusion and exclusion criteria. A database is developed to support the analysis of data and key visualizations. While findings show the Fund is 39% less cost-effective from the original funding agreement execution to current data, the results narrative highlight key trends in average emissions reductions, cost-effectiveness, and project survivability across sectors, regions, and funding mechanisms. These trends underscore important successes and lessons learned across the portfolio and provide opportunities for improvement in the Fund’s recapitalization.Item "Care is connection": How place shapes experiences of care for precariously housed adults nearing end-of-life(2025) Stewart, Alexandra; Stajduhar, Kelli I.; Cloutier, Denise S.As the social determinants of health literature highlight, housing is more than a physical space; it is a critical foundation for social connectivity and healthcare access. Stable housing supports the development of community connections, which are linked to enhanced well-being and a better quality of life. Furthermore, these connections fulfill a vital function in the context of end-of-life care. Conversely, for adults who are precariously housed, inadequate housing may disrupt the ability to engage with their communities, resulting in social isolation and adverse end-of-life care experiences. As such, housing stability plays a vital role in facilitating or limiting social connections. Drawing on observational fieldnotes and qualitative interviews, this study examined the role of ‘place’ in shaping experiences of care for unstably housed adults nearing end-of-life guided by a geographic and health equity lens. The findings reveal that social connection and supportive relationships were seen as central to participants’ sense of home and experiences of care. Meanwhile, displacement and frequent transitions illustrate how disrupted connections can impact quality of life and restrict access to social support at end-of-life. In conclusion, this study underscores the significance of social connection, community support and sense of place in fostering more equitable end-of-life care experiences for precariously housed adults.Item Toward an extensible quantum platform-agnostic combinatorial optimization library(2025) Ossorio Trochez, Jose; Muller, Hausi A.; Villegas, Norha M.Combinatorial optimization (CO) problems are computationally challenging as evidenced in various industry and research domains. With recent advances in quantum computing hardware and algorithms, such problems represent an excellent case study for these technologies. Nevertheless, current software tools for CO lack platform-agnostic abstractions to enable researchers and practitioners to utilize quantum resources effectively. This thesis aims to validate and extend the QPLEX Python library, a platform-agnostic CO package built on DOcplex which integrates execution across multiple quantum providers using various algorithms. We focus on two key software quality attributes: completeness, examining the quantum providers QPLEX supports to look for features that could be added to our library, enhancing its capabilities for handling CO problems; and extensibility, making the library more adaptable for future expansions. We first compile a high-level workflow for solving CO problems to ensure that our elicited software requirements align with the actual process practitioners follow when solving these problems. Subsequently, we evaluate QPLEX through a comprehensive analysis of its completeness by comparing features against alternative solutions including platform-specific SDKs, and its extensibility by examining how easily new features can be integrated without disrupting existing functionality. Based on the identified functional and non-functional requirements, we design and implement several extensions to QPLEX, including support for Qiskit Runtime Sessions, integration with D-Wave's quantum solvers and implementation of the QAOAnsatz algorithm. Furthermore, we enhance the extensibility of the library through comprehensive documentation, automated testing, and CI/CD pipelines to ensure smooth integration of future open-source contributions. Validation results demonstrate that these enhancements successfully extend QPLEX's capabilities for solving CO problems using quantum resources, providing a more comprehensive suite of features for quantum-based CO while establishing robust foundations for future development. This work contributes to the evolving field of quantum software engineering by advancing an abstraction layer that shields practitioners from low-level quantum details, allowing them to focus on problem formulation. As quantum hardware and algorithms continue to advance, such platform-agnostic libraries will play a crucial role in broadening quantum computing adoption, enabling domain experts to leverage quantum resources without requiring deep quantum computing knowledge.Item Reasoning Canada’s rights in immigration matters, 1867-1977: The conceptual labour of state sovereignty(2025) Lu, Wenjuan; Marks, Lynne Sorrel; Lepp, Annalee E.This dissertation investigates how parliamentarians reasoned Canada’s rights in immigration matters, including admission, exclusion, and deportation. I look at parliamentary debates over immigration from 1867 to 1977, with an eye to discerning the patterns of lawmakers’ thinking on the “right” question. My finding is that they developed multiple lines of reasoning over the decades. Critics and defenders shared some metalogics, including assumptions about Canada’s territorial ownership and its power over Indigenous peoples, international law, imperial policy and interest, and governing principle. In addition, critics mobilized citizenship right, and defenders reasoned with autonomy, the British North America Act, and sovereignty. Furthermore, to understand the historical significance of the “right” debates, I examine them in relation to Canada’s construction of its state sovereignty. Using an integrated analytical framework, I study how legislators’ modes of thinking intersected with Canada’s sovereignty project vis-à-vis Britain, the international society of sovereign states, and Indigenous nations. The integrated framework illuminates the ripple effects of lawmakers’ lines of reasoning and the cross-pollination of ideas amongst the three strands of Canada’s sovereignty enterprise. My argument is that in reasoning the “right” question, parliamentarians performed sustained conceptual labour that moved forward Canada’s braided sovereignty project.Item Developing an impedimetric glucose sensor using multi-layer molecularly imprinting technique(2025) Abbaspour, Koorosh; Hoorfar, MinaA sensitive and cost-effective measurement of glucose has always been a priority in clinical and quality control arena. In this article, molecularly imprinted and non-imprinted polymer (MIP & NIP) based on conducting polymers and functionalized composites was suggested to achieve repeatable and stable determination of glucose in POC analyses. Glucose was introduced into the imprinted layer composed of polypyrrole (PPy) along with (APBA), which was formed on the carboxylayed multiwalled carbon nanotubes (COO-MWCNT) as the step to immobilize glucose. Further polymerization of an imprinting layer for glucose, in a basic medium, was performed to cage the glucose molecule. A layer-by-layer analysis of the sensor was performed with electrochemical and surface analyzing methods. Also, both NIP and MIP were characterized before and after the glucose removal by phosphate buffer. The glucose rebinding to form glucoboronate ester in sensor was tested using impedance technique and a linear range between 1 µM and 20 µM with the detection limit of 6 µM was achieved. The reusability and stability of the imprinted sensor were determined to be 10 times and 96% of the beginning current was maintained after 15 days. In overall, such a sensor demonstrates promising future for developing cheap, reusable and non-invasive glucose sensors.Item Anaesthetic modernism(2025) Tunnicliffe, Kevin; Ross, StephenAnglophone literary modernism has often been discussed in terms of its various attempts to shock its readership back to their senses, to reinvigorate a culture too used to convention. The notorious and persistent sentiments forwarded by Ezra Pound and Wyndham Lewis—to blast such a stagnant culture into a frenzy of radical creativity by embracing progress and cutting away stale traditions—are both familiar and useful touchstones. However, against the view of modernism as a strong, bombastic attempt to shock people back to their senses, my dissertation draws attention to a contrary understanding of anglophone literary modernism and defines it in terms of its pervasive anaesthetics: a mode of formal experimentation that takes anaesthesia and insensitivity as its key aesthetic elements. Anaesthetic modernism pertains to the multitude of experiences of insensitivity, numbness, and disembodiment that also made up a significant strain of modernist creation. Anaesthetic modernism connects the formal, stylistic, and thematic with the sensory, affective, and bodily, thus embracing aesthetics on broad terms and emphasizing the connections among content, form, and feeling in art. In this dissertation, I examine major works by Virginia Woolf, Malcolm Lowry, and Mulk Raj Anand that all represent anaesthetization, but do so in very different ways, ranging from how age, social expectations, and even language cut us off from direct sensory experiences, to self-medicating with alcohol and coping with the existential fallout of being suspended between cultures, to the defining limitations one’s social status can enact on one’s sensorium and identity. I weave literary criticism and close reading together with biological definitions of insensitivity and the embodied cognition model of consciousness in hopes of expanding the terrain of anglophone literary modernist studies.Item Population ecology of mountain goats in relation to climate, weather and snow avalanches(2025) White, Kevin Scott; Darimont, Chris T.Weather and climate exert profound influences on wildlife populations. In mountain environments climate is changing rapidly, compared with surrounding lowland areas, highlighting the importance of understanding the population ecology of species inhabiting these sensitive and biodiverse systems. My dissertation research focused on how weather and climate, and related phenomena (i.e. snow avalanches), influence the population ecology of mountain goats – a sentinel species on mountain environments. I used long-term field data collected from individually marked animals (421 individuals over 17 years across 4 study areas in coastal Alaska) combined with remote-sensing environmental data to assess a suite of research questions. First, however, I synthesized existing information about how mountain goats are influenced by weather and climate in order to comprehensively understand the state of our knowledge and identify knowledge gaps (Chapter 2). Next, I examined how climate and life-history trade-offs shape mountain goat reproductive demography (Chapter 3). These analyses revealed age-specific patterns in reproductive performance were negatively influenced by previous parturition success, late-winter snow depth and summer temperature. Highlighting the importance of intrinsic and extrinsic factors on reproduction, these results also filled an important data gap by enabling parameterization and implementation of mountain goat population modeling simulations used to evaluate relative strength of winter vs summer effects and later analyses (described below). The remainder of my research focused on examining the extent that snow avalanches represent a climate-linked driver of mountain goat populations. In Chapter 4, principal findings revealed that avalanches comprise a major source of mortality (36% of all mortalities, on average) and can remove up to 22% of a population annually. Given the low realized population growth rate previously reported for mountain goats (i.e. 1-4%), such impacts may exert significant demographic consequences. To quantify such impacts, I next developed and implemented a population modeling approach to explicitly examine and quantify how avalanches, across a range of scenarios, influence population growth and dynamics, including recovery times (Chapter 5). Ultimately, I determined that mountain goats can sustain modest population growth (1.5%) during average avalanche conditions, but during severe years (i.e. when 23% of a population dies from avalanches) populations can experience significant declines (15%) that require extended periods (11 years, or 1.5 mountain goat generations) for recovery to baseline levels. Overall, my research contributes several dimensions of new knowledge about how weather and climate-linked factors influence mountain goats populations, and offer important insights about the functionality of mountain ecosystems in the face of changing climate conditions.Item Production of verbal morphology in heritage speakers of Tamil(2025) Srikanth, Shankhalika; Bird, SonyaThis study investigates the differences in the verbal morphology of heritage Tamil speakers and L1 Tamil speakers with the ultimate goal of providing applicable pedagogical insights for heritage Tamil teachers and learners. This work is centred within my community of heritage Tamil speakers. Tamil is a Dravidian language that is dominant primarily in South Asia. Tamil heritage speakers, like heritage speakers of other languages, often face issues of social stigma, shame, and feelings of exclusion when speaking their heritage language, in addition to linguistic barriers because of the lack of pedagogical materials and research on heritage Tamil acquisition. Nevertheless, many adult Tamil heritage speakers have a strong motivation to learn their heritage language. The long-term goal of my research is to identify and implement strategies to support heritage Tamil learners who want to (further) develop their oral proficiency in the language, as well as to raise awareness for heritage Tamil being a legitimate variety of Tamil in its own right. For the purposes of this thesis, I limited my scope to verbal morphology, and the question I investigated was how heritage Tamil speakers and fluent L1 Tamil speakers differ in their production of verbal morphology. I used a combination of games and stories to elicit verb forms with a range of tense and person-number-gender (PNG) affixes, making sure to use methods that could be reapplied in the classroom as teaching tools. The heritage speakers I worked with used a combination of target-like forms as well as different strategies of overgeneralization, notably overmarking, to simplify irregular morphological paradigms that are present in L1 tense and PNG morphology. The findings from this study demonstrate that heritage Tamil speakers have a deep awareness of Tamil’s complex verbal morphology, while also highlighting clear points of divergence between L1 Tamil and heritage Tamil grammars that parallel those seen in other heritage languages cross-linguistically and which can be useful for heritage language teachers in determining what types of forms to focus on in the classroom.Item The efficacy of explicit instruction of discourse connectives on Chinese EFL learners’ argumentative writing performance across different writing proficiency levels(2025) Yuan, Qin; Huang, Li-ShihArgumentative writing involves cognitively sophisticated thinking and reasoning skills (Taylor et al., 2019). Using connectives to indicate the logical reasoning process is one of the challenging aspects of learning writing for English learners (Snow & Uccelli, 2009). Discourse connectives (DCs) are important for discourse coherence and “such coherence is often marked by using discourse connectives” (Zufferey et al., 2015, p. 390). Regarding the use of DCs in IELTS argumentative writing, many Chinese undergraduate English learners in China with different proficiency levels do not perform well (Yao, 2014). What is more, according to the researcher’s teaching experience in English writing classes, many Chinese students could not properly employ DCs in their argumentative writing. Therefore, due to these reasons, more empirical studies are needed in order to investigate the effects of explicit instruction of DCs on Chinese undergraduate EFL learners’ argumentative writing performance across different writing proficiency levels. Using qualitative and quantitative research methods, this study investigated the efficacy of explicit instruction about DCs involving 96 undergraduate Chinese EFL learners across different proficiency levels (i.e., elementary proficiency level, n = 30; intermediate proficiency level, n = 32; upper intermediate proficiency level, n = 34) in their English argumentative writings. Conducted through a four-week treatment, the study used a pre- and post-test design to measure participants’ use of DCs and their writing abilities. Further, participants’ post-treatment survey provided qualitative data about participants’ use of DCs during the treatment. Through both qualitative data (i.e., content analysis) and quantitative (i.e., descriptive statistics, paired-sample t-test, and Pearson’s correlation), the results showed that the participants had stronger awareness and use of DCs and writing performance after the treatment. In the total frequency and appropriateness of using DCs, there were statistically significant differences between pre- and post-treatment writing tests across Elementary Group (EG), Intermediate Group (IG), and Upper Intermediate Group (UIG). As for the frequency and appropriateness of using three types of DCs, there were statistically significant differences on Type I DCs (e.g., in addition, finally, and similarly) and Type III DCs (e.g., because and to conclude) in EG, IG, and UIG. In Type II DCs (e.g., nevertheless, although, or, in fact, and on the other hand), there was a statistically significant difference in IG. However, there were no statistically significant differences in EG and UIG. As to their writing performance, participants in EG and IG made significant improvements but not in UIG after the treatment. Correlational analyses showed that there were significant correlations between the total appropriate use of DCs and participants’ writing scores in EG and UIG, but not in IG after the treatment. The analysis of the qualitative data revealed that explicit instruction of DCs could facilitate EG, IG, and UIG participants to overcome their challenges on using DCs in argumentative writing.Item Situating cultural heritage management: How the ȾEL¸IȽĆE / c̓əl̓íɫč Village in Cordova Bay informs the pasts, presents, and futures of BC Archaeology(2025) Tarling, Gemma; Thom, BrianThis thesis provides a synthesis of the history of the archaeological management of the Coast Salish village, ȾEL¸IȽĆE / c̓əl̓íɫč, in Cordova Bay on Vancouver Island. Rather than being recorded as a single landscape-level archaeological site encompassing most of the Cordova Bay community in the present-day District of Saanich the village has been recorded in the provincial archaeological record as 20 distinct sites. In this schema, no direct connections have been made to recognize that these separately recorded sites are representative of activities occurring across one larger archaeological village. To explain this phenomenon, I analyse archaeological work that has happened in the Cordova Bay area and tie it to relevant shifts in how heritage management is governed both locally and provincially (District of Saanich and W̱SÁNEĆ Leadership Council, 2021; McLellan & McDowell, 2024; Scambler, 2023a; Scambler, 2023b). In my findings, I outline how the Cordova Bay case study reveals that cultural heritage of Indigenous communities is not well represented in provincial heritage legislation. In accordance with Article 31 of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), Indigenous peoples have the right to protect and govern tangible heritage, which includes archaeological sites and landscapes. British Columbia has committed to upholding UNDRIP based on the 2019 adoption of the Declaration on the Rights of Indigenous Peoples Act (DRIPA) (British Columbia, 2019). However, irreparable destruction through activities governed by British Columbia through the Heritage Conservation Act (HCA) happen on the ground to material histories in the present day (Mason, 2003; United Nations, 2007, p. 13-14). This thesis explores ways to bridge the gap between these disparate policy intentions and grounded realities through examining the role of the archaeologist and the need for Indigenous legal orders in governance and protection of archaeological sites.Item On switched control systems and model predictive control under uncertainty: Theory and applications(2025) Shang, Xinxin; Yang, ShiHybrid systems are a widely applied class of dynamic systems, leveraging both continuous and discrete variables to characterize practical physical processes, including discrete variables like switches and logic, as well as continuous variables like position and velocity. As a powerful tool to model a variety of control systems, it has been widely applied in control system design and utilized in a large number of practical applications, such as aerospace, industrial electronics, and biomedical engineering. Since the seminal work published in Automatica in 1999 by Prof. Bemporad (Professor of Control Systems, IMT School for Advanced Studies Lucca, Italy), more and more control scientists and engineers have been increasingly devoted to studying the fundamental theories and applications of hybrid systems. Along with this historical research road, this dissertation focuses on: • Theories: Stability and stabilization (Chapter 3), robustness (Chapter 4), data-driven model predictive control (MPC) (Chapter 5) • Applications: Path planning and obstacle avoidance (Chapter 6), mobile communication networks, and hydrogen refueling station optimization (Chapter 7) In the following, a brief introduction will be given. In Chapter 1, a brief introduction to a class of hybrid systems is provided, including their stability and stabilization methods, as well as a typical case, i.e., switched systems. Moreover, a comprehensive review of MPC variants designed for handling uncertain hybrid systems is also presented. In Chapter 2, preliminary concepts and notations are introduced, providing the foundational understanding required for the subsequent chapters. In Chapter 3, an asynchronous stabilization of discrete-time switched linear systems under dwell-time constraints is presented. This research investigates the stability and control of systems that switch between different modes in an asynchronous manner, and a novel convex stability criterion is developed, facilitating efficient control design. Following that, in Chapter 4, from a more practical perspective for stabilizing switched systems, a new control strategy is provided to minimize the error between nominal and disturbed states by employing ellipsoidal techniques and demonstrates how system stability can be maintained despite disturbances. In Chapter 5, a lightweight data-driven approach is developed to construct a novel data-driven MPC framework to control an unknown linear system. The proposed theories ensure two of the most critical properties in MPC frameworks: system stability and recursive feasibility, even under significant uncertainties. Then, Chapter 6 is devoted to the scenario-based MPC for path planning and obstacle avoidance with chance constraints. This work provides solutions for dealing with uncertainties in real-time decision-making under safety-critical conditions. In Chapter 7, a representative application is presented, demonstrating how the fundamental theories developed in previous chapters can address practical requirements. The application involves modeling the hydrogen refueling processes as hybrid systems and leveraging MPC to optimize energy costs while satisfying safety constraints (e.g., temperature and pressure). Finally, the conclusion and future works of the dissertation are presented in Chapter 8.