Library involvement in academic program review: an exploratory survey of the Canadian perspective
Bibliographic record
Abstract
Purpose This research explores how Canadian university libraries participate in program review, a key component of quality assurance in post-secondary institutions and an important way for libraries to show their value. To become aware of how libraries provide impact, it is necessary to understand what other libraries are doing with processes occurring at a university-wide level. Design/methodology/approach The researcher sent an exploratory survey to university librarians across Canada asking who played a main role in program review tasks, how coordination worked and what was going well and could use improvement in the overall process. Findings Themes emerged on workflow, visibility, schedule, feedback and effects on library work. Although there are different ways of reaching the same goal, academic libraries are involved in helping reach the university’s mission. Originality/value Very little is written about this in the literature (library or otherwise). Most research is not current or only looks at specific components of library involvement (i.e. collection assessment). Not only is this helpful strategically for libraries but getting a sense of how other libraries engage with university and library colleagues will benefit those operationally tasked with supporting academic program review.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.044 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.018 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".