An Ecologic Study of Parasuicide in Edmonton and Calgary
Bibliographic record
Abstract
OBJECTIVE: From 1986 to 1999, the suicide rate in the Edmonton Regional Health Authority (RHA) was greater than that in the Calgary RHA (mean rate ratio 1.4). We conducted a study to determine whether a similar relation holds for parasuicide, and if so, whether the pattern can be explained at the ecologic level by sociodemographic factors. METHODS: The Edmonton and Calgary RHAs provided data on emergency department visits for nonfatal intentional self-injury for 1997. We obtained sociodemographic data from the 1996 national census for the Edmonton and Calgary census metropolitan areas (CMAs) from Statistics Canada's public-use files. In each CMA, which is nearly coterminous with the corresponding RHA, we created 10 geographic areas based on average income. We analyzed the data at the ecologic level, using linear regression and multilevel Poisson regression. RESULTS: The parasuicide rate in the Edmonton CMA was greater than that in the Calgary CMA (rate ratio 1.3). In both CMAs, the parasuicide rate decreased as average income increased. In the final regression models, the only independent variables were average income, CMA, and their interaction term (linear regression model R2 = 0.82). CONCLUSIONS: The parasuicide rate in the Edmonton CMA is elevated, compared with that in the Calgary CMA. At the ecologic level, much of the variation in rates can be explained by average income and CMA. The high degree of correlation among the sociodemographic variables suggests that it may not be low income per se that is affecting the parasuicide rate but, rather, the consequences of belonging to a socially disadvantaged stratum of society.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".