Bibliographic record
Abstract
Purpose This article aims to overview research undertaken through the Canadian Association of Research Libraries (CARL) to identify themes and issues of interest to library leaders in Canadian research libraries. Design/methodology/approach This paper discusses the context of the research, including moves by the Canadian Association of Research Libraries (CARL) to develop closer collaborative projects with Canadian Masters of Library and Information Sciences (MLIS) programs and to develop a National Research Agenda (NRA), inclusive of National Research Priorities (NRP). It overviews the specific research undertaken to develop the NRP, including the methodology and research outcomes. Findings The research resulted in the NRP, which identified key themes/issues of interest to directors in CARL member institutions. As such, it provides a snapshot of current issues and trends in research library management and leadership within Canada. CARL is now promoting its NRP and encouraging researchers (individuals and teams) to undertake applied research on the identified themes/issues, as part of its strategy to encourage research collaborations; increase research intensiveness within academic librarianship; and, use of evidence‐based decision making and applied research to solve management challenges. Originality/value The article identifies the context for the research, the research approach (including methodology) and research outcomes which point to issues of concern for library leaders in Canadian research libraries. It is a snapshot of current issues of concern to library managers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.035 | 0.016 |
| Scholarly communication | 0.028 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".