Are Health Sciences Librarians Taking the Evidence-Based Medicine Challenge?
Bibliographic record
Abstract
This study sought to find out whether and how health sciences librarians’ roles have been changing to support the evidence-based medicine (EBM) practice. Both content analysis of job advertisements and literature review were employed. Results revealed that there exist some disconnects between what are expected of health sciences librarians in…Cette étude visait à déterminer si le rôle des bibliothécaires du domaine des sciences de la santé a évolué et de quelle manière ce rôle est en mesure de subvenir aux besoins de la médecine fondée sur les preuves (MFP). L’analyse de contenu des offres d’emploi et la revue de la littérature a été employée. Les résultats ont révélé qu’il existe un fossé entre ce que l’on attend des bibliothécaires des sciences de la santé en…
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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 | 0.063 | 0.222 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.039 | 0.028 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".