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GOFinder-AI: Rapid and Explainable Gene Ontology Term Assignment Using Large Language Models
(Université d'Ottawa / University of Ottawa, 2026-05-13) Almir Ahmad, Aws; Mer, Arvind
Gene Ontology (GO) provides a structured vocabulary for describing the function of gene products. However, the rapid growth of biomedical literature makes manual GO curation increasingly difficult to sustain. Here, we present GOFinder-AI, a computational framework that supports literature-grounded GO annotation through pre-query text mining and large language model (LLM) inference. Given a biomedical text, the system identifies candidate GO annotations and produces supporting citations, explanatory reasoning, and linked biological entities. To improve task-specific performance, we fine-tuned multiple general-purpose LLMs (Llama-3.1-8B and Qwen3-8B) on a large, annotated dataset with more than 23,000 examples. Model performance was assessed using grouped 4-fold cross-validation, followed by evaluation on an independent test set containing >7000 gene-GO associations. Fine-tuning markedly improved performance compared to zero-shot prompting. The fine-tuned Qwen3-8B-based system reported higher predictive accuracy than GPT-5 mini, Llama-3.1-8B, and its own zero-shot counterpart. Overall, when tested on over 3,500 annotations, GOFinder-AI achieved a cumulative accuracy of 95.32%. It completed document-level GO curation in under one minute on average. GOFinder-AI offers a scalable, interpretable, and transparent approach to automated GO curation.
Context-Aware and Adaptive Multi-Scale Interest Modeling for Sequential Recommendation
(Université d'Ottawa / University of Ottawa, 2026-05-13) Wang, Xiaowen; Tran, Thomas
Sequential recommendation aims to predict a user's next interaction by modeling ordered user-item behavior sequences and plays a critical role in modern recommender systems. In real-world scenarios, user behavior is influenced by multiple contextual factors, among which temporal dynamics and item popularity are particularly important. Time intervals between interactions reflect the evolution and decay of user interests, while item popularity introduces frequency bias that may cause recommender systems to overemphasize popular items and underrepresent long-tail preferences. Moreover, user interests naturally exist at different temporal scales: long-term behaviors capture stable and persistent preferences, while recent interactions often reflect short-term, context-dependent intents. Effectively modeling these signals and integrating long-term and short-term interests remains a central challenge in sequential recommendation. To address these challenges, this thesis presents two sequential recommendation models with increasing modeling capability. The first model, Dual-Gated Time Frequency Co-Modeling for Sequential Recommendation (TiIfSRec), is designed to explicitly incorporate temporal intervals and item-frequency information into long-term and short-term interest modeling. TiIfSRec employs a dual-gated recurrent architecture in which time-interval signals control the decay of historical preferences, while item-frequency signals regulate the direction of state updates to mitigate popularity bias and preserve long-tail information. An attention mechanism is further introduced to highlight informative historical interactions and improve long-range dependency modeling. Experiments on multiple Amazon benchmark datasets demonstrate that TiIfSRec consistently outperforms representative time-aware and popularity-aware baselines, validating the effectiveness of jointly modeling temporal and frequency signals for sequential recommendation. While TiIfSRec improves long-term and short-term interest modeling, its fusion strategy relies on deterministic mechanisms, which limits flexibility when balancing stable preferences and rapidly changing intents. Motivated by this limitation, the second model, Diffusion-based Long-Short Interest Fusion for Sequential Recommendation (DiffLSRec), formulates long-short interest integration as a generative process. DiffLSRec introduces a diffusion-based framework in which the long-term interest representation serves as a generative prior, and the short-term interest representation is incorporated as conditional guidance during a multi-step denoising process. This progressive fusion strategy enables the model to adaptively adjust the contribution of long-term and short-term interests at different stages, rather than relying on a single static fusion operation. To further enhance contextual modeling and stability, DiffLSRec incorporates token-level contextual enhancement to capture fine-grained recent behavioral patterns, as well as a monotonic signal-to-noise ratio-adaptive guidance mechanism to regulate the influence of short-term signals throughout the diffusion trajectory. Extensive experiments show that DiffLSRec consistently outperforms strong sequential recommendation baselines, including diffusion-based models, across multiple evaluation metrics. Overall, this thesis demonstrates that explicitly modeling contextual behavioral signals and progressively integrating user interests across different temporal scales can substantially improve the accuracy, robustness, and adaptability of sequential recommender systems. The proposed models provide complementary contributions, with TiIfSRec offering effective context-aware interest encoding and DiffLSRec introducing a flexible generative paradigm for long-short interest fusion.
Préjugés en milieu de travail : impact sur les femmes racialisées
(Université d'Ottawa | University of Ottawa, 2026-05-13) Roswell, Valérie-Clara; Sula-Raxhimi, Enkelejda
De nombreux employeurs ont mis en place des mesures visant à prévenir la discrimination en milieu de travail. Néanmoins, plusieurs travailleurs sont victimes de discrimination raciale et de sexisme. Les femmes racialisées sont particulièrement affectées par ces pratiques discriminatoires. L’objectif de cette recherche est de comprendre les conséquences des préjugés sur les femmes racialisées en milieu de travail au Canada, à la fois dans le secteur public et privé. Dans cette étude, nous privilégions la théorie de la discrimination raciale avancée par les auteurs Shalla et Clement (2007) et de l’intersectionnalité conceptualisée par Kimberley Crenshaw (1989) afin de pouvoir construire notre objet de recherche. Les entretiens approfondis avec 30 femmes racialisées, employées dans le secteur public et privé, des sources secondaires et une revue de la littérature ont permis une analyse fine des pratiques discriminatoires et préjugés qui produisent de la discrimination raciale au milieu du travail, affectent l’estime de soi des femmes racialisées. À son tour, le manque de confiance peut les conduire à nier leur identité dans divers aspects de leur vie incluant leur culture afin d’être socialement acceptées au sein de l’environnement de travail.
The relational mediation approach through the lens of intersubjectivity: The promises and limits
(2026-05-13) Dupuis, Natalie; Tessier, Helene
This thesis endeavours to make a critical assessment of the relational mediation approach and discerns gaps that remain insufficiently accounted for in the models selected. Accounting for these gaps and how they impact relational mediation processes creates opportunities to improve and further develop relational mediation theories. Further development in the theory may thus equip mediators with additional aptitudes for assessing how they can best assist parties with unique needs and help to determine if the conditions for mediation are propitious for success. Using an interdisciplinary approach to understanding relational mediation practice, this thesis develops a view of relational mediation models as distinctly phenomenological in orientation with the ultimate goal being the emergence of a new intersubjective understanding between parties in conflict. However, in addition to enriching the description of relational mediation practices, theories of intersubjectivity also offer an analysis that includes dimensions of conflict that may prove to be resistant to developing new intersubjective understanding between parties in conflict and thus, may resist resolution when certain approaches are used. This thesis employs a three-part structure. The first part of this thesis lays the foundation for the development of the argument, namely that conflict is experienced through the lens of subjectivity and that relational mediation tends to work in this realm. Working under the assumption that conflict is created in the subjective experiences of parties, mediation presumes that addressing conflict through the subjective experiences of the parties offers a suitable path to resolution. Furthermore, this thesis offers a review of how the conflict studies field views success in mediation and the various mediation models developed in various contexts and narrows the field of inquiry to a particular mediation approach, the relational mediation approach. The relational mediation approach, consisting of a series of mediation models, describes an approach to conflict resolution that presumes that while people are concerned with their own interests, they also are simultaneously concerned with the interests of others. This mutual-concern approach stands in contrast to individualist interpretations of conflict resolution as a problem-solving approach that prioritizes having one's own needs met with minimal concern for the interests of the other party. In this thesis, the scope for examination is narrowed to the transformative, insight, narrative, and nonviolent communication models of mediation as they share the relational orientation to their respective theories and practices. Having narrowed and clearly defined the goals of relational mediation models, the second part of this thesis situates relational mediation practices within the phenomenological approach to conflict resolution. This approach explores conflict through the lens of first-person experience using methods familiar to phenomenologists. Using a phenomenological approach, relational mediators seek to guide mutual understanding between parties about how the conflict has presented itself to each party. Thus, this thesis further contends that relational mediators are unknowingly working with theories of intersubjectivity to guide parties toward new shared understandings of self, other, and the conflict as they promote mutual cognitive and empathic understanding. Indeed, the mediator is equally participatory in this intersubjective understanding as it is often considered as an integral part of the mediation process. Having established that relational mediation models employ their own version of theories of intersubjectivity, the final part of this thesis uses literature from theories of intersubjectivity to discern likely blocks to intersubjective understanding. With the definition of these blocks established through the lens of intersubjectivity, this thesis contends that some conflicts are inherently resistant to resolution through mediation because of individual dispositions or structural influences on the parties and their conflicts. This thesis contends that applying the lens of theories of intersubjectivity to relational mediation theories and practices provides new paths in mediation’s theoretical and practical maturation and adds to the tools mediators may already be applying. Specifically, theories of intersubjectivity shed light on the quality of dynamics mediators seek to prompt during a mediation process. However, theories of intersubjectivity also point toward explanations about party dispositions and contexts that are likely to contribute to mediation failure. Exploring these dimensions of relational mediation approaches offers paths for mediator development to help them address these challenges in mediation or to help to guide them in determining whether a conflict should be referred to another dispute resolution mechanism.
Where Participation and Tokenism Meet: An Analysis of “Meaningful Participation” in Peace and Security
(Université Saint-Paul / Saint Paul University, 2026-05-13) Leclerc, Katrina; Eaton, Heather
This dissertation examines the gap between the policy commitment to participation in peace and security and the lived realities of those most frequently positioned as its subjects. Focusing on young women peacebuilders operating at the intersection of the United Nations’ Women, Peace and Security (WPS) and Youth, Peace and Security (YPS) policies, the study asks how meaningful participation is understood, experienced, and negotiated in practice. While participation is repeatedly invoked as a normative good within global peace and security frameworks, it is rarely theorized beyond procedural inclusion or measured in ways that capture influence, accountability, or power. Drawing on in-depth qualitative interviews and sustained practitioner-researcher engagement across multiple regions, this research centres young women as analysts of participation rather than merely its beneficiaries. The findings reveal that participation is frequently experienced as conditional, extractive, and uneven, shaped by intersecting hierarchies of age, gender, language, education, sexuality, and institutional legitimacy. The dissertation demonstrates how participatory processes often prioritize visibility over authority, consultation over co-creation, and access over influence, reproducing exclusion even within inclusion-focused frameworks. The study advances a relational understanding of participation, arguing that meaningful participation cannot be reduced to presence or representation alone. It introduces the “Triangle of Meaningful Participation” as an analytical model identifying three enabling conditions: co-creation, influence over outcomes, and a feedback loop. By reframing participation as a relational and political practice rather than a technical procedure, the dissertation contributes to feminist, decolonial, and critical peacebuilding scholarship and offers policy-relevant insights for rethinking participation within WPS and YPS agendas.