YorkSpace

YorkSpace is York University's Institutional Repository. It supports York University's Senate Policy on Open Access by providing York community members with a place to preserve their research online in an institutional context.

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Recent Submissions

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    The Black Box is Orange
    (2025-11-13) Benivolski, Yuula; Greyson, John R.
    The Black Box is Orange is a multimodal thesis project composed of three interconnected parts: a 51-minute film, a written text, and a 70-page field guide. Together, they provide the geographic, visual, and historical contexts that piece together the fragmented timeline of my childhood. The project examines how personal and collective memory are shaped by the absence of archives. It begins with my family’s abrupt emigration from the USSR to Israel, which resulted in the loss of our family’s entire photographic record, and our subsequent settlement in a small Israeli border town called Shlomi, built on the remains of a thriving Palestinian village destroyed in 1948 for which visual records no longer exist. The film reconstructs childhood memories through a combination of 16mm footage, voiceover, and 35mm slide presentations. It traces how settler-colonial policies structure daily life in an apartheid state focusing on everyday events to avoid sensationalism. The written component situates these memories within macro- and micro-histories of land dispossession, bureaucratic erasure, and a deliberately buried archive, while the field guide maps memory through meaningful encounters with plants and flowers.
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    Changing Nature of Cataloguing Librarians in Academic Libraries
    (International Federation of Library Associations and Institutions (IFLA), 2022-11-22) Cao, Haiyun; Salmon, Marcia
    The shifting research and scholarly landscape, the transformation in higher education, and advances in technology have been reshaping the profession of cataloguing librarianship in academic settings. There has been a trend in the cataloguing community that cataloguers are transforming their roles from traditional cataloguing into metadata creation. The authors of this research study conducted a survey to cataloguers in Canadian and American academic libraries who experienced this change in roles. The survey addresses changes of position description, acquisition of new skills, challenges and opportunities during the transition, and their extent of confidence and satisfaction to perform the new roles. The Survey result shows transition in the job roles of cataloguers is a big challenge to cataloguers who lack metadata knowledge and computer technologies. However, they are able to acquire the needed skills to perform their new responsibility, as well as develop certain confidence and satisfaction in their new role.
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    Performing geographies of disappearance: migration and the case of the Saharan knowledge claim
    (Taylor & Francis, 2025-05-29) Stierl, Maurice
    This article explores the performativity of data practices and knowledge claims regarding migratory death and disappearance. Engaging with Science and Technology Studies inspired migration research, it assesses the political contestedness and the performative effects of knowledge practices on migration. Data practices do not simply measure, reflect or represent a self-evident reality ‘out there’ but are deeply entangled in the making of migration realities that are acted upon, including by states and international organizations. In the article, based on document analysis and semi-structured interviews, a specific knowledge claim is analysed. Namely, the claim that more ‘people on the move’ die when seeking to transit the Saharan desert than when trying to cross the Mediterranean Sea. By tracing the emergence and circulation of this claim in the epistemic community of international organizations and in the context of heightened post-2015 migration anxiety in Europe, the article shows how the claim helped perform the Sahara as a geography of disappearance where a messy, dangerous and deadly migration reality required governmental intervention and taming. Echoing colonial imaginaries of the desert as a space of emptiness, unknowingness and danger, the claim underwrote justifications for humanitarian deterrence where, in the name of saving lives, cross-desert movements needed to be prevented by further securitizing and bordering the Sahara. Este artículo explora la performatividad de las prácticas de datos y las reivindicaciones de conocimiento en torno a la muerte y la desaparición migratoria. A partir de la investigación sobre migración inspirada en los Estudios de Ciencia y Tecnología, evalúa la controversia política y los efectos performativos de las prácticas de conocimiento en la migración. Las prácticas de datos no se limitan a medir, reflejar o representar una realidad evidente, sino que están profundamente entrelazadas en la creación de realidades migratorias sobre las que se realiza, incluso por parte de Estados y organizaciones internacionales. En el artículo, basado en análisis documental y entrevistas semiestructuradas, se analiza una reivindicación de conocimiento específica: la afirmación de que mueren más personas en movimiento al intentar cruzar el desierto sahariano que al intentar cruzar el mar Mediterráneo. Al rastrear el surgimiento y la circulación de esta afirmación en la comunidad epistémica de organizaciones internacionales y en el contexto de la creciente ansiedad migratoria posterior a 2015 en Europa, el artículo muestra cómo esta afirmación contribuyó a presentar el Sáhara como una geografía de la desaparición, donde una realidad migratoria caótica, peligrosa y mortal requería la intervención y el control gubernamental. Haciendo eco de los imaginarios coloniales del desierto como un espacio de vacío, desconocimiento y peligro, esta afirmación justificó la disuasión humanitaria donde, en nombre de salvar vidas, era necesario prevenir los movimientos a través del desierto mediante una mayor seguridad y la delimitación de las fronteras del Sáhara.
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    An IRT Model-Based Reliable Change Index With Empirical Priors: An Extension Using A Multiple Group Approach With Finite Sample Sizes
    (2025-11-11) Campbell, Sarah Grace; Robert Philip Chalmers
    The reliable change index (RCI; Jacobson & Truax, 1991) is a popular tool for assessing whether individuals have changed between treatments. Recently, an Item Response Theory (IRT)-based RCI that incorporates group mean information through the use of expected a posteriori (EAP) estimation has been adopted, showing promising results (Chalmers & Campbell, 2025). This paper extends the previous RCI-IRT work by (1) using finite sample sizes for model calibration and parameter estimation and (2) adopting a multiple group (MG) approach to modelling sample data. Results showed that even with slight methodological changes, the results are similar to the previous studies, in that incorporating empirical priors improves rates of detecting individual change when true change is present. Larger calibration sample size has an impact on model parameter recovery, but not person parameter recovery. Finally, results favour the use of the MG approach with EAP group-informed priors when underlying group heterogeneity is expected.
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    Quantum Chemistry, Machine Learning and Atomistic Monte Carlo to Study Melting-Like Transitions in Small Clusters
    (2025-11-11) Krishnadas, Anirudh; Fournier, Rene Andre
    This thesis develops computational methods for efficiently predicting melting-like transitions in clusters. Four criteria are introduced to characterize these transitions: (i) the width of the potential energy distribution (W_U), which broadens near the melting point; (ii) a dissimilarity measure relative to the ground-state configuration, defined from the ordered interatomic distances r_ij; (iii) the effective count of r_ij values near the mean of the first two peaks of the pair distribution function; and (iv) the degree of non-uniformity in the r_ij distribution. Together with an artificial neural network classifier for estimating solid fractions, these measures identify melting transitions with two- to threefold reductions in computational effort compared to conventional heat-capacity-based (C(T)) analyses. Parallel Tempering Monte Carlo (PTMC) was combined with an E(3)-equivariant neural network potential (Allegro) trained to reproduce density functional theory (DFT) energies. The framework was validated on sodium clusters and applied to aluminum clusters containing up to 16 atoms in both neutral and charged states. Predicted melting temperatures ranged from 305 K to above 1200 K, exhibiting size- and charge-dependent nonmonotonic variations consistent with experimental and theoretical data. The methodology was further extended to global optimization, where tens of millions of candidate geometries were screened using the neural network, refined through local optimization, and classified by topological fingerprints and bond-orientational order. This reduced computational cost by three to four orders of magnitude compared to DFT-based sampling while maintaining near-DFT accuracy. The same approach was applied to heteroatomic icosahedral clusters AB_2C_10 chosen for their superatomic potential. Among them, ZrRb_2Au_10 and Sn_3Y_10 were prioritized based on atomization energies and electronic simplicity. Estimated melting temperatures 1263 K and 2061 K, respectively, exceeded the weighted average of their elemental melting points. Overall, this work provides new insights into cluster melting, revealing size-dependent trends, enhanced thermal stability in superatomic systems, and non-melting behaviour in certain aluminum clusters. By integrating multiple indicators and scalable algorithms, it advances the understanding of phase-like transitions at the nanoscale.