Protective Effects of Language Learning, Use and Culture on the Health and Well-being of Indigenous People in Canada
Bibliographic record
Abstract
Traditional language and culture have an important role to play in Indigenous communities. Many communities assert that their language and culture is at the heart of what makes them unique and what has kept them alive in the face of more than 150 years of colonial rule. Studies have shown that although the health of Indigenous communities has improved over time, Indigenous people are still not faring as well as the general population (Health Canada, 2001; Young, 2003). But what role does the use of traditional language and culture play in maintaining health and reducing risk factors for health crises in Indigenous communities? This paper explores the literature discussing the protective effects of traditional language and culture on health outcomes for Indigenous people. Indigenous people continue to assert that language is the foundation for culture and without our languages, our cultures cannot survive (Battiste, 1998; Kirkness, 1998; Kirkness, 2002). This paper argues the time for action is now – to revive and hold high the indigenous cultures of this land, if for no other reason than for the tremendous potential they hold for the renewed and continued holistic health of Indigenous people. \n----- \nLa langue et la culture traditionnelle ont un rôle important à jouer dans les communautés autochtones. De nombreuses communautés affirment que leur langue et leur culture se trouvent au coeur de leur identité et de leur survie à plus de 150 ans de domination coloniale. Des études ont montré que, bien que la santé des communautés autochtones s’est améliorée au fil du temps, les peuples autochtones ne se portent toujours pas aussi bien que la population en général (Santé Canada, 2001; Young, 2003). Mais quel rôle est-ce que l’usage de la langue et de la culture traditionnelle jouent dans le maintien de la santé et la réduction des facteurs de risque pour les crises de santé dans les communautés autochtones? Cet article explore la littérature au sujet des effets protecteurs de la langue et la culture traditionnelle sur la santé des populations autochtones. Les peuples autochtones continuent d’affirmer que leur langue est le fondement de leur culture et de sa survie (Battiste, 1998; Kirkness, 1998; Kirkness, 2002). Cet article plaide en faveur de l’action: relancer et valoriser les cultures indigènes de ce pays, si ce n’est que pour leur énorme potentiel en santé holistique pour les peuples autochtones.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".