The Awakening of Mapuzugun (the Mapuche Language): Challenges, Reflections, and Effects of this Struggle in Northern Patagonia, Argentina
Bibliographic record
Abstract
The purpose of this article is to share and reflect on the Mapuche and Mapuche-Tehuelche struggle to transmit and strengthen Mapuzugun (the Mapuche language) in recent decades. The military campaigns that invaded the indigenous lands now known as Patagonia (Argentina and Chile) are considered critical events 1 that provide clues to understanding not only the genocide but also the years that followed. 2 For this purpose, this article will first contextualize the genocide on the Mapuche people, focusing specifically on the Mapuche language and how elders supressed its transmission to younger generations. The various examples employed come from on-going doctoral research in the field of memory studies in anthropology and collaborative research that began in 2019, since this author is also part of a Mapuche organization that is oriented towards Mapuzugun's learning and teaching. The questions, demands, and projects that are considered herein come from different Mapuche organizations and communities that are working toward Mapuzugun revitalization and other political-spiritual projects that have language reclamation, use, and transmission as their main concerns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".