9-8-8: Suicide Crisis Helpline – Implementing a Pan-Canadian Program to Prevent Suicide
Bibliographic record
Abstract
The 9-8-8: Suicide Crisis Helpline was launched in Canada in November 2023, aligned with an international movement to ensure access to crisis supports as part of a public health approach to suicide prevention. We describe the planning and implementation of 9-8-8 in Canada using the RE-AIM framework, considering the Reach, Effectiveness, Adoption, Implementation and Maintenance of 9-8-8 within the first six months of service (Glasgow et al. 2019). There is evidence of reach and adoption of 9-8-8 across Canada, and we discuss evidence-based strategies to evaluate and enhance effectiveness, implementation and maintenance. We also consider the importance of evaluating 9-8-8 within the larger socio-ecological and health system contexts. 9-8-8 must cultivate a learning health system approach and be part of a larger learning health system focused on reducing suicide in Canada.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".