Re-visioning library support for undergraduate educational programmes in an academic health sciences library
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
McMaster University’s Health Sciences Library (HSL) began to transition to a new liaison service model in early 2018. One of its librarians sought to understand how an academic health sciences library can optimise its support for academic undergraduate programmes. This scoping review of the literature was pursued with the aim to submit an informed recommendation to HSL’s new Education and Lifelong Learning team, so the library could shift its approach to information literacy instruction in a manner that would optimise its outcomes for students and improve relationships with faculty staff. The author searched seven databases: Library, Information Science & Technology Abstracts (LISTA), ProQuest ERIC, OVID Embase, EBSCO CINAHL, OVID Medline, Web of Science and PapersFirst. She developed a robust and comprehensive search strategy that used a combination of subject headings and keywords to describe information literacy, metaliteracy, libraries and health sciences education. The author also hand-searched bibliographies of seminal publications to broaden her search for relevant literature. The findings in this review indicate that metaliteracy as a concept has not been intentionally implemented into information literacy training at academic health sciences libraries. The review finds that it is preferable to integrate information literacy skills directly into course or programme curricula and align those skills with the evidence-based practice skills undergraduates are already learning. Further, establishing a programme that builds on these skills gradually throughout the duration of the academic programme, rather than one-shot library instruction, is also preferred. To achieve success, libraries must build strong collaborative relationships with faculty staff. The author provides recommendations for practice that reflect the findings of this review. Other academic health libraries may benefit from this review by taking into consideration its findings and subsequent recommendations.
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.
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 | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.226 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it