<i>How Can We Teach Our Children if We Cannot Access the Forest?</i> Generational Change in Mapuche Knowledge of Wild Edible Plants in Andean Temperate Ecosystems of Chile
Bibliographic record
Abstract
For many indigenous peoples, the contributions of wild edible plants go well beyond nourishment; they are often also used as dye and medicines, as well as markers of identity. However, historical and contemporary processes of land grabbing, forest loss, acculturation, and lifestyle changes may erode the transmission of plant knowledge to new generations. In this paper, we document 1) the botanical knowledge of wild edible plants and 2) perceived influences on the transmission of this knowledge to younger generations in a Mapuche community in Andean temperate forests, Chile. Thirty-seven people participated in this study. We conducted participant observation, freelists, and informal, photo-elicitation, and semi-structured interviews. A total of 47 wild edibles were recorded (42 plants were determined to species level by participants). Digee (Cyttaria espinosae; Smith's Index of Saliency, S 5 0.82) was the most salient wild edible, followed by changle (Ramaria flava, S 5 0.68), maqui (Aristotelia chilensis, S 5 0.67), murra (Rubus ulmifolius, S 5 0.59), and pin (Araucaria araucana, S 5 0.56). Participants provided detailed information on species seasonality, ecology, and changes in availability over time. Most adult women and elders had a comprehensive knowledge of wild edibles. However, younger generations were not learning what the elders had once learned. The lack of access to forests and the formal school regime were reported as the main factors interrupting the transmission of knowledge. Because Mapuche pedagogy is oral and in situ, land loss and the school regime have left younger generations with few opportunities to engage in these forms of indigenous pedagogy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".