Extending “Helping Babies Breathe” to an Academic Setting in Fiji: A Project Involving American Nursing Faculty and Graduate and Undergraduate Nursing Students
Bibliographic record
Abstract
ABSTRACT: Approximately 2.5 million neonates died worldwide in 2018. Over one quarter of neonatal deaths are caused by birth asphyxia. Helping Babies Breathe (HBB) was created to teach basic neonatal resuscitation steps in limited-resource settings. Fifteen Fijian faculty members attended a master teacher class. Nine undergraduate nursing students from the western United States assisted in teaching two HBB classes for Fijian nursing students. Fijian faculty and student knowledge increased significantly posteducation. Educational settings provide ideal locations for future nurses to learn and practice evidence-based neonatal resuscitation skills. Implementing HBB in an academic setting, though novel, may ensure educators are familiar with current guidelines.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".