‘ <i>Resilience is action taken together</i> ’ results of a dialogue-based study on community factors shaping resilience in the context of youth suicide prevention
Bibliographic record
Abstract
Suicide is a leading cause of death among children and youth around the world, and is centred within the Sustainable Development Goals. While research consistently shows the importance of external, intersecting factors that shape youth resilience, much work in this field remains vague and focused downstream. Situated within a community-based partnership and grounded in critical pedagogies, this research invited young people and caring adults into deliberative dialogues about how resilience-promoting communities look and feel. Our goal was to centre youth voices, illuminating their ideas about wellness and suicide prevention. The study brought 31 people into four dialogues: four school aged youth (15–18); nine emerging adults (19–24); nine caring adults; and nine community service providers. Contributors described resilience as a set of collective actions involving three mutually-reinforcing actions: cultivating belonging; cultivating connection; and promoting a positive social climate. These concepts were the essence of how resilience-promotion looks and feels. People in all four dialogues explored this idea of resilience as action taken together, reinforcing these three conditions as points of intervention to promote collective thriving and invest in upstream prevention of suicidality. This relational and upstream conceptualization of resilience-as-action serves to shift the ways communities organize around youth suicide prevention. Shifting conceptualizations of resilience upstream and toward resilience-promoting communities opens new ways of conceptualizing interventions to promote youth mental health. Doing so requires us to embrace solidarity, collective and population-level strategies, and place-based interventions that disentangle knots of social and structural determinants of health.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 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".