Rol de la evidencia científica en las políticas publicas relacionadas con los sistemas de salud.
Bibliographic record
Abstract
Existen diferentes modelos para explicar cómo la evidencia de la investigación se utiliza en los procesos de formulación de políticas sobre los sistemas de salud. En este artículo argumentamos que los modelos que se desarrollaron desde el contexto clínico, como el de políticas basadas en la evidencia, pueden ser útiles en algunas decisiones políticas. Sin embargo, debido a su “silencio” sobre el contexto político, estos modelos son incompatibles con las decisiones relacionadas con la modificación de los arreglos de los sistemas de salud. Otros modelos, generados desde las ciencias políticas, son más útiles para entender que la investigación es uno solo de los factores que afecta la toma de decisiones y que diferentes tipos de evidencia científica pueden ser utilizados de manera instrumental, conceptual o estratégica en diferentes etapas del proceso de formulación de políticas.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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 teacher head, 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".