«Dar comida obligando a repartirla» : un modelo de don maya-ch'orti' en proceso de transformación
Bibliographic record
Abstract
Se analiza la importancia de los regalos de comida para el mantenimiento de la cohesión comunitaria entre los mayas-ch'orti' del oriente de Guatemala. Eso se percibe en los regalos cotidianos de comida pero, sobre todo, en aquéllos que se producen como consecuencia de actos rituales trascendentes como el recubal (regalo de comida de padres a compadres). En el recubal, se regala tal cantidad de comida y de una cualidad tan particular que el receptor se ve obligado a repartir la ofrenda. Ese modelo de don lo he llamado «dar obligando a repartir». En la actualidad, el modelo comienza a resquebrajarse como consecuencia de la irrupción desde el mundo ladino de dos tipos de discurso que lo cuestionan, uno sobre la pobreza y otro sobre la superstición. Analizo finalmente las implicaciones sociales que sobre las comunidades ch'orti' puede tener el triunfo de ese tipo de discursos.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".