Supporting Indigenous Child Suicide Prevention Within Classrooms in Canada: Implications for School Psychologists and Educators
Bibliographic record
Abstract
Indigenous young people in Canada are disproportionately overrepresented in suicide rates and alarmingly, young children are accounted for in these disparities. Since children spend much of their day at school, schools are a vital context for suicide prevention, identification, and intervention. However, research indicates that educators often report that they feel unprepared to address mental health challenges within the classroom. Indigenous communities are developing community driven responses to suicide that are culturally relevant and strengths based. It is critical that these models are considered when developing such suicide prevention within schools as they diverge from medicalized focused approaches and attend to broader social dimensions. It is imperative that educators and the education system are properly equipped with the training and resources to provide suicide prevention within schools and communities servicing Indigenous children. School psychologists can play an important role in providing this prevention leadership. Through interviews with educators, we learned about the types of supports that are needed within schools to address Indigenous child suicide, and in what ways school psychologists could enhance prevention efforts. Using a reflexive approach to thematic analysis, we identified four main themes related to support needed. Findings are discussed in conversation with the current state of child specific suicide and suicide prevention literature. Applied implications for suicide prevention within schools for Indigenous children, as well as future research and community-based recommendations are considered.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".