Suicide in Newfoundland and Labrador: A Linkage Study Using Medical Examiner and Vital Statistics Data
Bibliographic record
Abstract
OBJECTIVE: To examine suicide epidemiology in Newfoundland and Labrador from 1997 to 2001. METHOD: Data from the Office of the Chief Medical Examiner (CME) were linked with data derived from the Canadian Vital Statistics Death Database. Ninety-five percent confidence intervals (CI) were calculated to assess variation of rates. We used the chi-square test to compare categorical data. RESULTS: The CME recorded 225 suicide deaths, compared with 187 in the Canadian Vital Statistics Death Database. Most deaths not coded as suicide in the national database were coded as accidental. Using the CME data, the overall suicide rate was 9.5/100000, aged 10 years and older. The rate among males (15.8/100 000, 95% CI, 10.7 to 20.8) was almost 5 times that of females (3.3/100000; 95% CI, 1.0 to 5.5). Age-standardized rates decreased over the study period, from 10.9 to 8.0/100000; however, the difference was not significant. The proportionate mortality ratio for suicide deaths was highest among those aged 10 to 19 years (20.0%) and decreased with age. The suicide rate was highest among those aged 50 to 59 years. The rate for unpartnered individuals (17.0/100000, 95% CI, 10.7 to 23.0) was significantly higher, compared with partnered individuals (5.1/100000; 95%CI, 2.5 to 7.8). Males used more violent methods than females. Suicide was significantly higher in Labrador (27.7/100000, 95% CI, 18.4 to 37.0), an area with a higher Aboriginal population, compared with the island of Newfoundland (8.5/100000, 95% CI, 7.3 to 9.7). Psychiatric illness was the most common predisposing factor. CONCLUSIONS: Suicide deaths are highest among males, unpartnered individuals, and individuals with psychiatric disorders.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".