Collaborating with GLAM Institutions
Bibliographic record
Abstract
This essay cluster features three essays by students which reflect on their experiences developing digital scholarly resources in collaboration with the GLAM sector (the acronym for galleries, libraries, archives, and museums). Each essay focuses on a particular project: a digital exhibit of Redpath Museum’s precious seahorse collection, a digital collection of Renaissance books published by the printer-publisher Aldus Manutius held at Simon Fraser University Library Special Collections, and a digital exhibit of Victorian-era Pre-Raphaelite books hosted by the University of Victoria Library. In describing these projects, these essays reveal emerging models of digital pedagogy involving collaboration among students, faculty, and librarians. Lisa Goddard and Rebecca Dowson, academic librarians specialized in digital scholarship from the University of Victoria and Simon Fraser University, respond to these essays, offering their perspective on what student–GLAM collaborations add to the mission of academic libraries. RésuméCe regroupement de dissertation se compose de trois dissertations écrites par des étudiants qui réfléchissent à leurs expériences acquises en développant des ressources universitaires numériques en collaboration avec le secteur GLAM (l’acronyme anglais pour Galleries, Libraries, Archives and Museums, ou Galeries, Bibliothèques, Archives et Musées). Chaque dissertation se focalise sur un projet particulier : sur une exposition numérique de la collection précieuse d’hippocampes du Musée Redpath ; sur une collection numérique de livres de la Renaissance publiés par l’imprimeur-éditeur Aldus Manutius, ce qui se trouve dans les Collections Spéciales de la Bibliothèque de l’Université Simon Fraser ; et sur une exposition numérique de livres Pré-Raphaelite venant de l’époque victorienne qui a eu lieu à la Bibliothèque de l’Université de Victoria. En décrivant ces projets, ces dissertations révèlent des modèles émergents de pédagogie numérique qui nécessitent la collaboration entre des étudiants, des membres de faculté et des bibliothécaires. Lisa Goddard et Rebecca Dowson, des bibliothécaires académiques qui se spécialisent dans l’érudition numérique de l’Université de Victoria et de l’Université Simon Fraser, répondent à ces dissertations, en donnant leur perspective sur ce que les collaborations étudiant-GLAM contribuent à la mission des bibliothèques académiques. Mots-clés: institutions GLAM; humanités numériques (DH); exposition numérique; curation numérique; métadonnées descriptives; pédagogie numérique
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.023 | 0.012 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.003 | 0.046 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".