Assessing the training needs f First Nations mental health workers in Manitoba
Bibliographic record
Abstract
Through open-ended interviews, people in three Manitoba reserve communities are asked the following questions: what does mental health mean; what are the problems, the causes, and the solutions to mental health problems in their communities; what training and skills do First Nations mental health workers need; what are the attributes of a good helper; and what supports do helpers require? The priority mental health problems of depression and anxiety, suicide, and substance abuse are symptoms of imbalance and disharmony, and the consequences of the losses and abuses suffered. Healing means returning individuals, families, communities and the nations to states of balance and harmony. The solutions to mental health problems must include rebuilding community resources through political self-determination and rebuilding positive cultural identity. Mental health systems are being constructed by First Nations blending western health and social service models with native traditional approaches. First Nations mentalhealth systems place emphasis upon public education and community development as well as upon treatment. First Nations community mental health workers need strong working ties with mainstream mental health specialists for ongoing training, supervision, and consultation; they need to be members of the community team (including elders and the general public), but must also connect communities to mental health resources available in the rest of the province. There are six areas of training required by mental health workers in First Nations: counselling skills; mental health theory and practise; writing and agency skills; public education skills; community development skills; and spiritual/traditional training. The crucial attributes of a First Nations helper are self-healing/self-awareness, caring, and a First Nations background. Mental health is part of an attitude of healing and harmonious connection with all of creation; this attitude includes traditional values of respect and caring which must form the foundation of First Nations mental health systems. (Abstract shortened by UMI.)
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".