Opening Minds: The Mental Health Commission of Canada’s Anti-Stigma Initiative: Opening Minds in Canada: Background and Rationale
Bibliographic record
Abstract
In 2006, Canada’s Senate Committee on Social Affairs, Science and Technology completed a national review of mental health and addiction services in Canada1—the first national review since the report of the Royal Commission on Psychiatric Services published almost half a century earlier.2 The Committee recommended that a mental health commission be created, which was subsequently established in 2007 with the full support of all federal parties. The MHCC was funded through Health Canada, with a 10-year mandate to act as a catalyst for improving the mental health system and changing the attitudes and behaviours of Canadians regarding mental health issues. The OM Anti-Stigma Initiative of the MHCC was launched on October 2, 2009. Our paper will provide the rationale for the approach taken and summarize the way in which programs were identified and engaged in this initiative.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.033 | 0.031 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.013 | 0.014 |
| 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".