Incidence of suicide among teenagers and young adults in Transkei, South Africa
Bibliographic record
Abstract
Background: Transkei is the least developed of the former black homelands in South Africa and has a population of about 4 million. People in this area are poor and depend mainly on the income from migratory workers to the gold mines. Suicide is a complex problem, with no definitive causative agent that has been identified as yet. Suicide among teenagers and young adults is now emerging as an important mental health issue. Suicidal behaviour in the population is under- researched, and therefore under-reported.Method: This is a retrospective record review from 1993 to 2003, carried out in the Umtata General Hospital mortuary. About 1 000 medico-legal autopsies are conducted annually, and the mortuary caters for a population of about 400 000.Results: Of the 10 340 medico-legal autopsies, 398 (3.84%) suicide cases were due to hanging. The number has increased from 5.2 per 100 000 of the population in 1993 to 16.2 in 2003. More than a half (55%) of the hangings were of people less than 30 years of age, and less than one-quarter (23%) of these victims were younger than 20 years. The rate in males has increased from 4.5 (1993) to 14 per 100 000, and in females from 0.7 to 2.2 per 100 000. The male/female ratio is recorded highest (9 : 1) in the 20- and 29-year age group.Conclusion: There is an increasing incidence of suicides among young adults. Suicidal tendency among teenagers and young adults is emerging as an important health issue that needs to be addressed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".