Las dos caras del Xoloitzcuintle, revalorización de un perro diferente: 'Escuincles y Xoloitzcuintles', divulgación entre el público infantil
Bibliographic record
Abstract
l perro pelón mexicano ha compartido la existencia con el ser humano desde la época precolonial. Haciendo una revisión de las fuentes etnohistóricas, arqueológicas e históricas se manifiesta una necesaria puesta en valor que ayude a desterrar mitos sobre un animal de apariencia dual, existiendo ejemplares con y sin pelo. Sobre bases empíricas, a través de un sondeo realizado en el Colegio Pier Faure (La Piedad, Michoacán), hemos desarrollado una propuesta preliminar de divulgación para el público infantil. Mediante una actividad lúdico-formativa se persigue establecer lazos de empatía hacia este patrimonio vivo, entre niños y niñas de 5 a 12 años. The Mexican hairless dog has shared its existence with humans since precolonial times. Making a review of data from historical records, archaeology and history, we have seen the need to enhancing the value of this animal which has a dual appearance. We can find dogs with or without hair. This characteristic makes them a prey of myths and misinterpretations. We have developed a divulgation strategy for children's audience (5-12 years old), upon the empiric bases offered by a survey in Colegio Pier Faure Faure (La Piedad, Michoacán). Through ludic-formative activities we would like to support our main objective: to establish empathy ties with this living heritage.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".