The Home-School-Community Interface in Language Revitalization in Latin America and the Caribbean
Bibliographic record
Abstract
Linguistic human rights (LHRs), especially in education, are one of the most necessary (but not sufficient) prerequisites for the maintenance of the world’s Indigenous/tribal, minority and minoritized (ITM) languages and communities. An unconditional right to mother tongue-based bi/multilingual education in non-fee state schools is the most important LHR if ITM languages and communities are not to remain seriously endangered. This chapter describes and analyses educational linguistic rights in international law, in the USA and in Canada. All Indigenous/tribal/First Nations languages in North America, with the possible exception of Inuit in Kalaallit Nunaat/Greenland, are seriously endangered and in need of revitalization. For them, education using the ITM children’s ancestors’ mother tongues in Indigenous mother tongue–based multilingual and revitalization immersion programs should be a linguistic human right. This right does not exist today, either in law or in practice—linguistic and cultural genocide continues. Attempts to counteract this genocide are presented.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".