Depredadores o aliados, los insectos y arácnidos (okuiltsitsin) en los saberes y en las prácticas de los masehualmej (nahuas) de la Sierra Nororiental de Puebla (México). Primera parte: El campo de la depredación.
Bibliographic record
Abstract
Insects and arachnids have been the subject of relatively few comprehensive studies by ethnobiologists, compared with more ‘noble’ animals, such as birds or mammals. This article, based on a long-term study, carried on by a Canadian anthropologist and a maseual (nahua) collective devoted to research on their indigenous culture, included 173 interviews carried on in the nahuat language (maseualtajtol). It reveals a vast and detailed knowledge of 141 classes of ‘little animals’ (okuiltsitsin), that is, the most numerous category within the 314 animals identified and studied. Maseualmej classify them in terms of their morphological characteristics (grasshoppers, ants…) but also in function of their relationships with humans. On the one side are the predators that bite or sting (such as scorpions and mosquitoes) or prey on harvests (such as many caterpillars). This we shall call the domain of predation. Others are of bad omen (nexikolokuilimej); they give advice about bad luck and may as well provoke it. On the other side are the ‘good’ ones (den kuali), those which provide food or medicine (such as bees, or edible larvae). This we shall call the domain of reciprocity: it will be dealt with in a subsequent article. In this first paper, we shall present insects and arachnids which belong to the domain of depredation. A second paper will deal with those that belong to the domain of reciprocity. As for other animals, these two types of relationships with humans also have a supernatural dimension: some ‘little animals’ are wise (tamatini) and give good advice or good luck, others are a bad omen (nexikolokuilimej)]. Both articles will give the reader an accurate view of the intricate world of ‘little animals’ in the knowledge and practices, in San Miguel Tzinacapan, an indigenous community in Northeastern Sierra de Puebla (Mexico).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".