Academic Dental Librarianship in Canada: Taking Stock, Planning the Future
Bibliographic record
Abstract
The Oral Health Interest Group/Groupe d’intérêt en santé buccale of CHLA/ABSC, established in 2016, aims to act as a source of networking for dental librarians in Canada, conduct research, and advocate for the specialty. In the present article, the first produced by OHIG, the authors describe the current landscape of academic dental librarianship in Canada using data resulting from an informal consultation of all OHIG members. Examples of distinctive practice are highlighted through a series of vignettes, and the overview is set in context through a literature review of dental librarianship, focussing on Canadian contributions to the speciality. The article concludes with the authors’ reflections into possible directions the specialty may take over the next few years, noting the importance of increased embedded collaboration with faculty and the need to develop new skills, for example, to support research data management and new trends in scholarly communications.
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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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.016 |
| Science and technology studies | 0.044 | 0.015 |
| Scholarly communication | 0.034 | 0.014 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".