Inuit mental health service utilisation in Manitoba: results from the qanuinngitsiarutiksait study
Bibliographic record
Abstract
Despite decades of Inuit accessing services in Manitoba, Inuit-centric services remain scant and have only begun to emerge. This article reports on Inuit utilisation of mental health services in Manitoba. In this study, we focused on two interrelated cohorts: Inuit living in Manitoba and Inuit from the Kivalliq region who come to Winnipeg to access specialised services. We used administrative data routinely collected by Manitoban agencies. The study was conducted in partnership with the Manitoba Inuit Association, and Inuit Elders from Nunavut and Manitoba. Our results show that mental health-related consults represent between 1 in 5 and 1 in 3 of all consults made by Inuit in Manitoba. Rates of hospitalisation for mental health conditions are considerably lower than those of residents from the Manitoba northern health authority. Given that Nunavut has the highest rate of suicide in the world, our results suggest underserved needs rather than lower needs. Kivalliq and Manitoba Inuit utilise mental health services in Manitoba extensively, yet these services for the most part remain western-centric. Epistemological accommodations in the provision of mental health services have yet to be implemented. This is now the focus of our work.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".