The Power of Community: A Leisure-Based Approach to Postvention
Bibliographic record
Abstract
Losing a loved one to suicide is often traumatizing. Those left behind to bear the loss do so under a shroud of stigma, shame, blame, and regret, alongside other complex emotions. Due to the misconceptions surrounding suicide, individuals closest to the bereft often do not know how to respond to the loss, leaving the survivor to grapple with arguably one of the most challenging events of their life alone. Yet, evidence suggests that suicide survivors may find meaningful group support and ways to integrate the loss into their lives through postvention resources. Drawing inspiration from Pieper’s contemplative leisure, and in collaboration with suicide survivors, we explore leisure’s potential in a co-created suicide bereavement support group. Our findings indicate that leisure as a contemplative act helped facilitate healing within a participatory action research postvention.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".