El Merito Forestal no Evita Migracion: San Juan Bautista Jayacatlan
Bibliographic record
Abstract
"A lo mejor es pura coincidencia, a lo mejor no, pero apenas hace cuatro anos cuando el gobierno del presidente Fox inicio su politica de Cambio, tambien empezo el exodo de San Juan Bautista Jayacatlan hacia los Estados Unidos. Este ano, el municipio, ubicado en los limites entre la Sierra Norte y la Canada de Oaxaca, recibio la certificacion por su desarrollo forestal sustentable, y ademas, como parte de la union forestal IXETO, fue reconocido por el gobierno federal con el merito forestal, junto con los otros tres socios: Nuevo Zoquiapam, San Miguel Aloapam y San Miguel Maninaltepec. Comenta el presidente municipal, Adrian Perez, sin rencor en su voz: 'A lo mejor apoya el gobierno, pero sin el trabajo comunitario del pueblo este apoyo no alcanza para nada. Lo que hemos logrado es gracias a los tequios de los comuneros. Sin embargo, las autoridades nos sentimos en aprietos, porque todos los jovenes se van, hombres y mujeres. Es cada vez mas dificil cumplir con los cargos y tequios.'"
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 | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".