Cuerpo, alma y carne de la lengua maya. Vitalidad lingüística: desde la lengua maya, a lo maya y con lo maya
Bibliographic record
Abstract
En este artículo describimos en coautoría con la comunidad lingüística de Naranjal Poniente la estrategia de recuperación subjetiva que empleamos para enfrentar los escollos que relatamos sobre la vitalidad lingüística de la lengua maya. Mediante el uso de metáforas mitológicas desarrollamos la existencia del wíinklal (cuerpo), pixan (alma) y bak’el (carne) de la maaya t’aan: las tres piedras que sostienen el comal del t’aan (habla) en el k’óoben (fogón maya). A partir de un análisis desde adentro retratamos y explicamos de manera detallada los elementos básicos que permiten la prevención y fortalecimiento de la vitalidad de la lengua maya que se encuentra en contacto con las lenguas hegemónicas o mayoritarias, en condiciones socioculturales desequilibradas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".