Development and Impact of Helping Babies Breathe Educational Methodology
Bibliographic record
Abstract
The educational pedagogy surrounding Helping Babies Breathe (HBB) has been transformative in going beyond a curriculum focused only on basic neonatal resuscitation; indeed, it created the framework for an educational program that has served as a model for replication for other impactful programs, such as the Helping Mothers Survive and other Helping Babies Survive curricula. The tenets of HBB include incorporation of innovative learning strategies such as small group discussion, skills-based learning, simulation and debriefing, and peer-to-peer learning, all of which begin the hard work of changing behaviors that may eventually affect health care systems. Allowing for adaptation for local resources and culture, HBB has catalyzed innovation in the development of simplified, pictorial educational materials, in addition to low-tech yet realistic simulators and adjunct devices that have played an important role in empowering health care professionals in their care of newborns, thereby improving outcomes. In this review, we describe the development of HBB as an educational program, the importance of field testing and input from multiple stakeholders including frontline workers, the strategies behind the components of educational materials, and the impact of its pedagogy on learning.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".