REPRESENTACIONES DE LAS MEDIDAS GUBERNAMENTALES EN EL CONTEXTO DEL COVID-19
Bibliographic record
Abstract
Se considera determinante para detener la rápida propagación del COVID-19, lograr adherencia de lapoblación a las políticas públicas preventivas indicativas de comportamiento. Las recomendaciones han sidodiferentes en los distintos países y han arrojado resultados variados en términos de prevalencia del COVID-19(Montreal Behavioural Medicine Centre, 2020). El Estudio International COVID- 19 Awareness and ResponsesEvaluation Study (ICARE) asociado a las políticas de salud pública busca conocer si es loable optimizar lasestrategias aplanando la curva de infección por COVID-19. Entre los hallazgos se relevó una preocupación centralen el 80 % de los participantes de que un miembro de la familia no conviviente o allegados se infectará de COVID19. Las respuestas exhibían mayor desazón por los impactos potenciales del COVID-19 en otras personas cercanasque en sí mismos. Estos hallazgos podrían dar cuenta de conductas de solidaridad y prosociales muy relevantes ala hora de diseñar campañas de prevención y desarrollo estratégico de políticas públicas, fomentando y haciendofoco en el cuidado del otro.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".