Explorando la currícula oculta sobre salud global / Commentary: Exploring the hidden curriculum of global health
Bibliographic record
Abstract
Estamos experimentando una apresurada expansion de programas de salud global en las universidades para dar cabida a estudiantes interesados. Un cuerpo creciente de literatura elabora acerca de las consideraciones eticas y practicas de experiencias singulares en la salud global y otros articulos comienzan a dar cuenta de las competencias necesarias para construir una curricula global para la salud. Sin embargo, hay una ausencia marcada de estrategias estandarizadas para la ensenanza de la salud global que orilla a los estudiantes a la construccion de su conocimiento a partir de fuentes disimiles: cursos formales, lecturas, conferencias, investigacion, mentores y materias electivas. - - - - - - - - Universities are experiencing a hurried expansion of global health programs to accommodate interested trainees . A growing body of literature has addressed the practical and ethical considerations for singular global health experiences, and other articles have begun to tackle competencies for building global health curricula . However, standardized approaches to teaching global health are frequently absent, leaving learners to build their knowledge through a variety of avenues: formal coursework, informal reading, conferences, research, mentorship, and electives.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".