Las personas mayores frente al COVID-19: tendencias demográficas y acciones políticas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
El impacto de la pandemia de COVID-19 en la población de los países de América Latina (AL) depende en gran medida de las acciones de política pública (en general) y de salud (en particular) que los gobiernos hayan adoptado para frenar su avance y efectos. Especial atención merecen las personas mayores como grupo demográfico de más vulnerabilidad frente a esta enfermedad infecciosa. Así, este trabajo tiene dos objetivos: primero, examinar la tendencia de COVID-19 a partir de los casos confirmados y la mortalidad por esa causa entre personas adultas mayores de una selección de países de AL (Argentina, Brasil, Chile, Colombia, Ecuador, México y Uruguay) junto con España; para luego destacar las acciones y políticas dirigidas a la atención de la población mayor en cada país durante la primera ola de la pandemia.
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.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it