Addressing Barriers to Mental Health Care for Indigenous Peoples in Canada
Bibliographic record
Abstract
Indigenous populations in Canada, including First Nations, Métis, and Inuit communities, face significant mental health challenges and experience higher rates of mental health disorders compared to the general population. For instance, suicide rates among Indigenous youth aged 15 to 24 are five to six times higher than those of their non-Indigenous peers, with Inuit youth facing rates up to 11 times the national average (Centre for Suicide Prevention, n.d.; Kirmayer et al., 2019). This striking disparity highlights the prevalence of conditions such as depression, anxiety, post-traumatic stress disorder (PTSD), and substance use disorders within these communities. Historical factors, particularly the intergenerational trauma from the residential school system, have contributed to these elevated mental health issues (Truth and Reconciliation Commission of Canada [TRC], 2015). The suppression of Indigenous languages and cultures in these institutions has led to a loss of cultural identity and community cohesion, further worsening mental health struggles (Gone, 2013). Addressing these challenges requires culturally sensitive approaches that recognize and integrate Indigenous perspectives on healing and well-being.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".