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Recent Submissions

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    Investigating Sport Spectators’ Pro-Environmental Behaviours: A Case of the Canadian Open Tennis Tournament
    (University of Waterloo, 2026-02-20) Gunton, Kari
    The sports sector is gaining increased attention on its reciprocal relationship with environmental challenges. While sporting events contribute significant environmental harm, they can also inspire sustainable action across mass audiences. Pro-environmental engagement among spectators of international tennis events remains an unexamined are, creating challenges to achieving positive environmental outcomes of these events. With the overarching goal of improving tennis tournaments’ spectator-focused pro-environmental strategies, the present study applied a Community-Based Social Marketing (CBSM) framework to guide an understanding of tennis spectators’ motivations and barriers to performing pro-environmental behaviours (PEBs). To understand tennis spectators’ PEB engagement, this research incorporated sort-and-weigh waste audits at the 2024 Toronto Canadian Open tennis tournament, while distributing in-person spectator surveys (N = 769). The survey included questions focused on PEB engagement, perceived motivations and barriers to performing the target PEBs. As well as questions on demographics and environmental protection values, which were used to assess whether there were differences in the reported factors influencing PEB engagement. Results revealed varying levels of engagement across behaviours. Less than a third of spectators reported use of the central waste sorting station (24.2%) and public transit (30.1%), while more than half reported use or intended use of the water refill stations (68.2%), while the waste audits revealed that landfill waste streams mostly (69.8%) consisted of recyclable and compostable materials. The results showed that commonly reported factors influencing tennis spectator PEB engagement included convenience, environmental protection, cost savings, and knowledge or awareness. In addition, chi-square and Mann-Whitney U analyses revealed significant differences in the importance of PEB predictors across demographics, environmental values, and prior PEB engagement with the target PEBs. The findings on predictors to tennis spectators’ PEBs shares similar trends to findings from other contexts, however this research also includes novel findings that add important insight into the CBSM framework. Specifically, the results show distinct differences between subgroups of spectators’ perception of important motivators and barriers to pro-environmental engagement. This adds important insight into the CBSM framework by highlighting the potential importance of incorporating segmentation into future campaigns. The findings can also be applied to build strategies for promoting PEB among tennis spectators.
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    Semantic Ink: Intent-Based Graphics Authoring through Annotation-Driven Generative User Interfaces and Reusable Tools
    (University of Waterloo, 2026-02-20) Li, Cara
    Designers face increasing challenges when translating high-level creative intent into precise graphics operations. Traditional authoring tools expose low-level primitives that require complex sequences of tool invocations, imposing steep learning curves on users. While AI-assisted systems can interpret high-level intent, existing tools primarily support single-shot generation or style transfer, lacking scaffolding for iterative refinement and semantic-level reuse. We present Semantic Ink, an intent-based interactive graphics authoring system that combines freehand annotation with generative UI. Users express intent through annotations directly on the canvas, and the system responds by generating structured parameter spaces as interactive controls, for progressive refinement without prompt iteration. Successful edits can be extracted as custom tools for semantic-level reuse. Informed by a formative study with five designers, we contribute a two-dimensional taxonomy crossing five intent types (add, transform, style, remove, scene) with four controllable parameter types (variation, magnitude, spatialization, surface) to enable multimodal LLMs to parse ambiguous annotations into editable parameter spaces. A user study with six experts demonstrates that Semantic Ink improves editing efficiency, reduces cognitive load from mode-switching, and enhances personalization through tool reuse.
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    Iterated Function Systems and the Local Dimension of Measures
    (University of Waterloo, 2026-02-20) Prandi, Joaquin Gabriel
    Given an iterated function system $\mathcal{S}$ in $\mathbb{R}^d$, with full support and such that the rotation in it fixes the hypercube $[−1/2, 1/2]^d$, then S satisfies the weak separation condition if and only if it satisfies the generalized finite-type condition. With this in mind, we extend the notion of net intervals from $\mathbb{R}$ to $\mathbb{R}^d$. We also use net intervals to calculate the local dimension of a self-similar measure with the finite-type condition and full support. We study the local dimension of the convolution of two measures. We give conditions for bounding the local dimension of the convolution on the basis of the local dimension of one of them. Moreover, we give a formula for the local dimension of some special points in the support of the convolution. We study the local dimension of the addition of two measures. We give an exact formula for the lower local dimension of the addition based on the local dimension of the two added measures. We give an upper bound to the upper local dimension of the addition of two measures. We explore the special case where the two measures satisfy the convex additive finite-type condition that we introduce. We introduce the notion of graph iterated function system. We show that we can always associate a self-similar measure to the graph iterated function system.
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    Between Here and There: Architecture, Becoming, and the Search for Home After Displacement
    (University of Waterloo, 2026-02-20) Correa, Samuel
    This thesis investigates the persistent cycles of displacement and strategies of place-making among communities affected by forced migration, focusing on Colombia’s history of conflict as case study and situating its findings within a broader discourse on displacement. Drawing on social history, and analysis of theory, literature, and architecture, the work explores how the trauma of uprooting disrupts social ties, erodes a sense of belonging, and fragments cultural identity for those forced to leave their places of origin. At the heart of the thesis is the concept of “architectural design containers for counter-displacement offerings”, spatial interventions conceived not merely as shelters, but as active agents in fostering identity, resilience, and community. The proposed containers are analyzed through mixed methods, including, architectural precedent studies, cartographic analysis and site research, and theoretical synthesis, to understand how they may resist cultural erasure, support the rebuilding of networks, and nurture agency among displaced peoples. Central Northwest Toronto, an area shaped by both Colombian newcomers and a highly diverse immigrant population, becomes the setting for a network of architectural design proposals, chosen for its diverse urban forms and histories of migration. Through detailed site analysis and reference to international case studies, the thesis demonstrates how architectural design and intervention can meaningfully respond to the shifting needs of displaced communities, serving as a platform for reconnection, storytelling, and agency. By integrating theoretical frameworks, participatory research, and design praxis, the work asserts the important role architects and urbanists can play in reconciliation, restoration of dignity, and the creation of genuine belonging for those affected by displacement. The thesis advances the conceptualization of design containers as adaptable spatial frameworks that can be tailored to diverse displacement contexts, supporting resilience, healing, and the formation of lasting communities.
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    Use of Large Language Models (LLMs) in Qualitative Analysis: Evaluating LLMs as Assistive Coding Agents
    (University of Waterloo, 2026-02-19) Neeb, Mikayla
    Introduction: Large language models (LLMs) are increasingly used to support qualitative research, yet robust methods to evaluate the quality of LLM-generated codes remain underdeveloped. Existing approaches often rely on comparisons to human ground truth or custom evaluative methods, limiting cross-study comparisons. This study examines whether LLMs can function as assistive qualitative coding agents and introduces the CReDS framework as a structured approach to evaluating LLM-generated codes without the need for a comparative codebase. Methods: Two social media datasets were employed as validation sets to systematically develop and test approaches for evaluating LLM-generated inductive codes. Codes were generated using GPT-4o-mini and assessed through an iterative evaluation process. Initial assessment relied on conventional quantitative similarity metrics (e.g., cosine similarity); however, limitations in capturing qualitative distinctions prompted the incorporation of structured human evaluation. This process led to the development of the CReDS framework, comprising Consistency, Relevance, Distinction and Specificity, as a more comprehensive evaluative method. Targeted exploratory analyses further examined evaluative performance under specific conditions, further investigating the evaluative methods explored in this study. Results: LLM-generated codes aligned closely with human codes across both datasets, with overall semantic match rates ranging from 74-83%. At the text level, 65-95% of inputs had at least one LLM-generated code judged appropriate by human reviewers. CReDS scores revealed strong alignment to human-generated codes, with strong overlap across all dimensions. However, LLM-generated codes showed reduced specificity, and the CReDS framework observed conservative scoring behaviour. Despite these limitations, CReDS effectively surfaced systematic strengths and weaknesses in LLM outputs. Conclusions: These findings indicate that LLMs can reliably support early state qualitative coding when used as assistive tools under human oversight. The CReDS framework offers a transparent and scalable method for evaluating LLM-generated codes that align with qualitative principles while supporting iterative model development. This study contributes to a measurable and scalable platform for responsible human-AI collaboration in qualitative analysis and highlights directions for refining evaluation frameworks in future work.