Death and Dying Abroad: The Canadian Experience
Bibliographic record
Abstract
BACKGROUND: The objective was to examine the characteristics of international travelers from Canada, who have died while abroad, and to review the health protection and promotion strategies for prevention of adverse health outcomes associated with travel, which may have prevented these deaths. METHOD: An EpiInfo 6 program was created to analyse all of the Consular reports received in 1995 via the Secure Integrated Global Network, which provides communications and computerization services to the Department of Foreign Affairs and International Trade, Canada. The Consular Management and Operations System was designed to support the delivery of consular services by the Department, and to link Headquarters in Ottawa with missions in other countries, through case management files, including a "Death Abroad" file. The type of data collected included personal demographics (age, gender), date, country, and cause of death. RESULTS: In 1995, consular services received 309 reports of Canadians dying abroad. Two hundred and twenty deaths were males (71.2%), and 69 were females (22.3%). The average age (56 years) and median age (43 years) were similar for males and females (age range 0.3-86 years). Recorded causes of death were: natural (62.1%), accidents (24.9%), murder (7.8%), and suicide (5.2%). Cardiovascular disease and trauma were the two most commonly specified causes of death. CONCLUSIONS: At least 36% of the deaths occurring in Canadian travelers would be considered preventable. Pretravel medical interventions for travelers with known preexisting medical problems, may have prevented many more deaths. International travelers need to be aware of the health risks associated with travel. Access to appropriate health risk assessment, prior to exposure, in many cases, would have prevented death abroad.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".