Bibliographic record
Abstract
BACKGROUND: An outcome of globalization and internationalization in higher education in the health professions has been increasing global health placements. There is, however, a lack of literature on debriefing and support following these placements. The authors undertook a participatory project to develop peer support and debriefing in a global health nursing elective, during which this gap in literature was addressed. AIMS: The purpose of the project was to develop a peer support component of the course and revise the debriefing component based on results of a previous course evaluation. METHODS: The methods were guided by a participatory approach involving course alumni and included a scoping review and focus groups. RESULTS: The project resulted in development of: (1) a peer support statement and (2) a debriefing framework. CONCLUSIONS: Key lessons about the obligation of appropriate debriefing for students returning from global health placements include importance of affective learning, a pedagogy of discomfort, and global health ethics.
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 | 0.270 | 0.447 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".