Promoción de la salud ambiental: acercamiento de dos campos. El caso de México
Bibliographic record
Abstract
En México, al igual que en otras regiones del mundo, se presentan desafíos complejos en salud ambiental que requieren de nuevos enfoques integradores, participativos e interdisciplinarios. El propósito de este artículo es mostrar las ventajas que puede aportar el campo de la promoción de la salud al de la salud ambiental para afrontar estos desafíos. Se abordan de manera general y particularmente para el caso de México las principales características de los dos campos. Además se discuten algunas de las diferencias epistemológicas y metodológicas que dificultan el acercamiento de las dos áreas y la utilidad de un concepto o campo de promoción de la salud ambiental. Finalmente se propone un modelo conceptual que permite visualizar los principales elementos a tomar en cuenta para investigaciones o intervenciones en promoción de la salud ambiental. Y se dan ejemplos de acciones en promoción de la salud ambiental en México, usando el modelo planteado.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".