Las Comunas costeras del Ecuador frente al COVID-19 : alianzas sociales, territorio, autonomía y dependencia
Bibliographic record
Abstract
Desde marzo hasta mayo de 2020, el número de fallecidos por causa del COVID-19 creció drásticamente en las Comunas de Santa Elena. Surgiendo así un panorama de desesperación, inseguridad y precariedad monetaria, que dura hasta el momento. A pesar del descenso turístico, el desempleo y la hambruna, surgió también un escenario caracterizado por las acciones comunitarias y las alianzas sociales, y con ello, se produjo una reconexión con el territorio como espacio sociocultural, pilar central que sostiene el proyecto comunitario. La información aquí expuesta es el resultado de una base de datos recopilada durante estos meses, con el objetivo de visibilizar la situación de las 70 Comunas de Santa Elena durante el estado de emergencia. Además, la metodología usada para compartir los datos con los dirigentes comunales invita a pensar en nuevos métodos dentro del contexto académico.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".