Librarians collaborating to teach evidence-based practice: exploring partnerships with professional organizations
Bibliographic record
Abstract
OBJECTIVE: The study sought to determine if librarians are collaborating with nurses and professional nursing organizations to teach evidence-based practice (EBP) continuing education courses, workshop, classes, or other training activities. METHODS: A 15-question survey was sent to 1,845 members of the Medical Library Association through email. RESULTS: The survey was completed by 201 consenting respondents. Some respondents (37) reported having experience teaching continuing education in collaboration with professional health care organizations and 8 respondents, more specifically, reported having experience teaching EBP continuing education courses, workshops, classes, or other training activities in collaboration with professional nursing organizations. CONCLUSIONS: The survey results demonstrate that librarians are teaching continuing education classes or workshops in collaboration with professional health care organizations and reveal that there are a small number of librarians collaborating with professional nursing organizations to teach EBP continuing education courses, workshops, classes, or other training activities.
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 | 0.051 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".