Portage: A cultural safety intervention co-developed with three Atikamekw communities in Québec
Bibliographic record
Abstract
Context and objectives First defined by a Maori nurse, cultural safety is a concept encompassing environments and therapeutic relationships that are spiritually, socially, emotionally and physically safe for Indigenous peoples; free from aggression and racism or denial of their identities or needs (23). Culturally safe care is envisioned as health care that recognizes, respects and nurtures the needs, rights and identities of Indigenous peoples. Objectives: This presentation looks back on 4 years of working in full partnership with three Atikamekw communities (Manawan, Wemotaci et Opitciwan) in Quebec to better understand, define and co-develop an intervention model to ensure cultural safety in care. Methods This project is based on a sequential design with successive stages of research and intervention development, led with an advisory committee composed of seven representatives from the three Atikamekw communities and from the Atikamekw Nation Council. The research stages of the project included a rapid review of cultural safety interventions involving the creation or transformation of professional roles, an environmental scan of existing interventions related to cultural safety on the regional territories of the communities, and three talking circles with community members. The project is based on a two-eyed seeing approach (Etuaptmumk), allowing for the respectful integration of Indigenous and Western knowledge. Results In line with the two-eyed seeing approach, the ultimate result of this project is an interventional model represented in a graphic format incorporating Atikamekw symbolism. The model, which involves co-governance between Atikamekw and organizational players, is deployed through three pillars of action at clinical, staff and organizational levels. It involves accompanying practices and patients at the clinical level, mentoring at the team level, and organizational policies and practices in favor of cultural safety. The model, illustrated by the canoe portage metaphor, includes elements symbolizing the three levels, such as the oar, the bark baskets and the canoe frame. Conclusion This research project, carried out with and by the Atikamekw Nation, exemplifies how a decolonizing approach centered on the expertise of Indigenous communities can be used to develop culturally safe interventions that respect their needs, values and cultural 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".