<u>A</u> m <u>x</u> same’ su sa ‘Nawalakw (the supernatural spirit wraps around us): impacts of Kwakw <u>a</u> k <u>a</u> ’wakw regalia making on identity, wellness and belonging in ‘Y <u>a</u> lis, British Columbia
Bibliographic record
Abstract
In this article, we share findings from a community-based Participatory Action Research project, titled Sanala, which means to be whole in Kwak’wala—the language of the Kwakwaka’wakw (Kwak̓wala-speaking people; a First Nation from what is now called Canada). In response to community priorities, the Sanala team initiated regalia as a weekly programme where people from the ‘Namgis tribe and other surrounding Kwakwaka’wakw Nations on the northwest coast of British Columbia, Canada, come together to create regalia. Participants learn about family crests, design and sew button blankets and dance aprons, and learn oral histories belonging to individuals and families, all within the context of Kwak’wala language revitalization and regalia making. We outline the impacts of this programme on identity, belonging, wholistic health and collective wellbeing, as well as implications for Participatory Action Research and community-led research aimed at strengthening individual and collective health and wellness through Indigenous languages and cultural continuity.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".