Choosing to enter the darkness - <i>a researcher’s reflection on working with suicide survivors</i>: A collage of words and images
Bibliographic record
Abstract
It is important to find constructive avenues for breaking the silence and taboo around suicide on both a personal and societal level. This collage of words and images is an iteration based on the extensive research that resulted in the award winning documentary film, The Hidden Face of Suicide. The film enters the world of survivors, those who lost family to suicide, and tells their remarkable stories through the use of mask making and interviews. The survivors expressed that the process of creating masks, telling their stories, and witnessing the positive audience response, gave them a sense of meaning and hope and decreased their feelings of being isolated and stigmatized. After screening the film to diverse audiences internationally, and upon further reflection on the making of the film and the audience responses, the author expresses the findings in another creative medium adding another layer to the tapestry of this process.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.023 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".