Alcohol and Other Contextual Factors of Suicide in Four Aboriginal Communities of Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: Aboriginal populations worldwide face increasing rates of suicide. Despite this recurring observation, little research has emerged from Aboriginal settings. AIMS: This paper describes the psychosocial and behavioral characteristics of 30 consecutive adult suicides from four First-Nations communities in Quebec, Canada. METHOD: Psychological autopsies guided by the LEDS with family members of the deceased. RESULTS: Suicide among this group is overrepresented by young single men. Alcohol intoxication at the time of death was reported for 22 cases in association with rapid acting out after the precipitating event for 20. All but two cases had a history of alcohol abuse, and drug use was also present in 23 cases. In 16 cases there had been a previous suicide attempt, 14 of which occurred during the previous year. The main socio-demographic characteristics of the communities were overcrowded living arrangements and no job status (90%). Seven cases were incarcerated or locked up at the time of death. Clustering of suicide was observed within seven nuclear families including 16 suicides. CONCLUSION: This study shows that Aboriginal suicide is the result of a complex interweaving of individual, familial, and socio-historical variables. The impact of contemporary social stressors on individual well-being must be addressed to prevent suicide in this community.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".