Bibliographic record
Abstract
As a society, we react badly to suicide, especially by the young. We seek understanding of why youth do it, and we are determined on prevention. To date we have looked mainly to the Western medical/mental health model, one which approaches the treatment and prevention of suicide as if this behaviour was solely a 'mental illness'. But this particular model has failed to alleviate, let alone prevent, escalating rates of youth suicide among Aborigines, Maori and Inuit in Australia, New Zealand and the Canadian territory of Nunavut, respectively. An alternative approach is to look at external social, political and cultural factors, such as 'Westernisation', the legacies of colonialism, chronic unemployment, and the impoverishment of body and soul; and at internal factors such as parenting problems, sexual abuse, alcohol and drug overuse, grief cycles, an absence of mentors, illiteracy and deafness. To generate discussion about the need for the separation of this growing problem from the mainstream medical approach to suicide, a case is made for the development of entirely different pathways to suicide alleviation (a less ambitious and less grandiose aim than prevention) in these three societies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".