Death and work: recognition of occupational association and coroner's investigation
Bibliographic record
Abstract
BACKGROUND: The degree of recognition of occupation as a contributory factor at the time of death certification is not known and there are few data describing the frequency with which a link to work is confirmed by the coroner. The medical examiner (ME) in England and Wales has a remit to scrutinize the circumstances of death and ensure accurate certificate completion with a requirement to pay specific attention to occupational factors. AIMS: To examine work assessment in the death certification process. METHODS: Deaths between March 2011 and December 2012 scrutinized by the Sheffield ME were assessed to identify the number of cases in which occupation was recorded and considered, the proportion of deaths referred to the coroner on the grounds of occupational history and the subsequent action taken by the coroner. RESULTS: A total of 5018 deaths were included in the study. Occupation was recorded in medical documentation used to complete the medical certificate of cause of death (MCCD) in 32% (1581) of cases. Of 1775 cases referred to the coroner by the ME, 8% (142) were on the grounds of occupation with 102 of these requiring autopsy, inquest or both. A total of 50 deaths were confirmed by the coroner as due to industrial disease. CONCLUSIONS: Our study describes an important step towards improving the validity of data on occupational mortality, using trained independent review prior to medical certification. Wider implementation of the ME scheme can improve the accuracy of MCCD completion and improve judgement of the contribution of occupation to an individual's death.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".