Precipitating Circumstances of Suicide and Alcohol Intoxication Among U.S. Ethnic Groups
Bibliographic record
Abstract
BACKGROUND: Our goal was to assess the prevalence of 9 different types of precipitating circumstances among suicide decedents, and examine the association between circumstances and postmortem blood alcohol concentration (BAC ≥ 0.08 g/dl) across U.S. ethnic groups. METHODS: Data come from the restricted 2003 to 2011 National Violent Death Reporting System, with postmortem information on 59,384 male and female suicide decedents for 17 U.S. states. RESULTS: Among men, precipitating circumstances statistically associated with a BAC ≥ 0.08 g/dl were physical health and job problems for Blacks, and experiencing a crisis, physical health problems, and intimate partner problem for Hispanics. Among women, the only precipitating circumstance associated with a BAC ≥ 0.08 g/dl was substance abuse problems other than alcohol for Blacks. The number of precipitating circumstances present before the suicide was negatively associated with a BAC ≥ 0.08 g/dl for Whites, Blacks, and Hispanics. CONCLUSIONS: Selected precipitating circumstances were associated with a BAC ≥ 0.08 g/dl, and the strongest determinant of this level of alcohol intoxication prior to suicide among all ethnic groups was the presence of an alcohol problem.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".