Community-led Digital Exhibits Service at the Edmonton Public Library: Research and Consultation
Bibliographic record
Abstract
This paper presents the findings of the community consultation and research conducted as part of the Digital Exhibits Intern Librarian Project at the Edmonton Public Library in 2016. The research project aimed to understand the local context for a new technology service in Edmonton, including the capacity for content creation and partnership among community organizations aligned with the Library’s mission. The study consisted of a survey and a series of semi-structured interviews. Findings include identification of various audiences and topics for digital projects, prioritization of Library and community partner roles in digital project collaborations, and identification of major components of digital exhibits as areas of project management workflows. Cet article présente les résultats d'une recherche et d'une consultation communautaire menées dans le cadre du Digital Exhibits Intern Librarian Project de la bibliothèque publique d'Edmonton en 2016. Ce projet de recherche visait à mieux comprendre le contexte local pour un nouveau service technologique à Edmonton qui comprend la capacité de créer du contenu et d'établir des partenariats avec des organismes communautaires alignés à la mission de la bibliothèque. Un sondage et une série d'entrevues semi-dirigées ont été utilisés lors de cette étude. Les résultats incluent l'identification de divers auditoires et sujets pour des projets numériques, la priorisation des rôles de la bibliothèques et des partenaires communautaires au sein des projets numériques collaboratifs, et l'identification de principales composantes des expositions numériques en tant que déroulement de projet.
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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 | 0.029 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".