Bibliographic record
Abstract
The manner of death in hangings is virtually always suicide. Uncommonly, accidental hangings do also occur. Homicidal hangings, however, are generally thought to be highly unusual. Despite some case reports of homicidal hangings, retrospective studies have demonstrated that homicidal hangings are virtually non-existent. The present study was undertaken retrospectively to evaluate the incidence of true and simulated homicidal hangings in the forensic population of Quebec (Canada) during a six-year study period. In a total of 251 cases of hanging, suicide was the leading manner of death (239 cases); the remaining cases were accidents (eight cases) and homicides (four cases). This unusually high homicidal hanging rate in Quebec (1.6%) is hard to explain. It could be attributed to an intrinsic particularity of the population and culture. It could also be that our forensic team shares a strong interest in asphyxial deaths as a research topic and, therefore, is particularly alert in detecting such homicides. Nevertheless, this relatively higher homicidal rate may be a reminder that homicidal hangings do sometimes occur. This study emphasises the importance of not disregarding this manner of death in hangings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".