Educación Ambiental y su estado actual como factor primordial para la conservación de la Biodiversidad
Bibliographic record
Abstract
Se inicia este trabajo con las siguientes palabras, de la filósofa y escritora hindú Vandana Shiva, que encierran, en gran manera, el objetivo de nuestra investigación: Madre Tierra debe ser tratada con cariño. Ella nos da la vida, no la riegues con veneno porque, si ella muere, muero, aquí moriremos todos. Aún no se dieron cuenta, somos lo que comemos. Vaya panda de alelados, que bajo su sombrero son tan pobres que sólo tienen dinero. (Guatemala) \nLa Educación Ambiental ha sido un tema bastante abordado por diferentes actores, tanto nacional como internacional, sin embargo continúa en el tapete porque, irónicamente, los índices de destrucción ambiental sigue en aumento. Así, la contaminación de las aguas, la contaminación del aire por efecto invernadero, la degradación y erosión de los suelos, resultan palabras familiares entre la ciudadanía
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".