Bridging communities and universities through language engagement: A vision for university engagement in the maintenance, revitalization, and strengthening of Indigenous languages
Bibliographic record
Abstract
Universities have had a direct impact on the vitality of Indigenous languages, and now have a corresponding responsibility to support them. Since their emergence on Indigenous territories, universities have beencomplicit in state-led activities designed to suppress Indigenous languages and cultures. Until 1961, Indigenous graduates of university programs would lose their Indian Status as recognized by the Canadian government.Historically, universities have contributed to Indigenous language loss by devaluing Indigenous languages as languages of learning and knowledge production, contributing to false narratives of the death or dying ofIndigenous languages and cultures, and drawing on assimilationist curricula and pedagogies that erase the diversity of Indigenous knowledges. Until today, Canada’s two colonial languages, French and English, remainthe languages of educational opportunity and advancement. For these and other reasons, universities must actively work with Indigenous communities to repair past and ongoing colonial policies and practices.
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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 | 0.021 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.059 |
| Scholarly communication | 0.031 | 0.027 |
| Open science | 0.004 | 0.055 |
| Research integrity | 0.014 | 0.011 |
| 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".