Women, kinship and language resurgence in Kahnawà:ke - Advanced pedagogies within a peer group model
Bibliographic record
Abstract
Indigenous language movements, rooted in the recognition of language's intrinsic ties to identity and land, have gained global momentum over decades.Despite the enduring impact of colonization, Indigenous communities are forging pathways to reclaiming and fortifying their languages.This study contributes to the field by emphasizing culturally grounded pedagogies that support adult second language (L2) learners in the revitalization of Kanien'kéha [Mohawk language] in Kahnawà:ke.The research provides a peer group model of advanced language learning that strategically returns language to the home, amongst families, and within an intergenerational setting.Collaborating with Kanien'kehá:ka women, four units of study were piloted and analyzed that featured advanced-level L2 pedagogies grounded in Rotinonhsión:ni ways of knowing.This study illuminates the important role of women in language and cultural continuity as well as the collaborative interaction between advanced learners and elder first language speakers.It also illustrates how L2 learners in Kahnawà:ke are part of a grand undertaking to revitalize Kanien'kéha in their families and community while simultaneously learning it.Positioned as Indigenous-led community research, this study underscores the importance of revitalizing Onkwehón:we [languages through methods that center Onkwehón:we ways of thinking that guide the resurgence and development of culturally aligned pedagogy.This research has led to the understanding that by reconnecting language with land, culture, and identity, we are ensuring the continuity of our diverse knowledge systems and spiritual connections embedded in Indigenous languages.Thus, Indigenous language revitalization through Indigenous pedagogy becomes a pathway to nurturing, centering and celebrating Indigeneity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".