Indigenizing the Structural Syllabus: The Challenge of Revitalizing Mi'gmaq in Listuguj
Bibliographic record
Abstract
Mi'gmaq, an Algonkian language of northeastern North America, is one of nearly 50 surviving Indigenous languages in Canada that are usually not considered to be viable into the next century. Only Inuktitut, Cree, and Ojibwe presently have enough younger speakers to provide a critical mass for long-term survival. In one Mi'gmaq community, however, a new way of passing on the language to adults who do not already speak it is rekindling new hope for the language. Building on a kernel provided by Arapaho scholar and Indigenous language revival activist Stephen Greymorning, teachers in Listuguj have created a structural syllabus that expands on the basic categories found in Mi'gmaq grammar rather than borrowing from methods devised to teach English or French as a second language. Learners have responded enthusiastically. This article reports on a participatory action research project involving Listuguj teachers and researchers from McGill University who are documenting this approach as it evolves.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 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".