Death and International Travel—The Canadian Experience: 1996 to 2004
Bibliographic record
Abstract
BACKGROUND: Death during international travel concerns several levels of the travel industry. In addition to the immediate effects for the traveler, their family and friends, the nature of travel-related mortality has important implications for pretravel health advisors and providers of medical care services. METHODS: The Consular Affairs Bureau, Foreign Affairs Canada provides information and assistance to Canadian civilians abroad. Beginning in 1995, the Consular Management and Operations System tracked Canadian deaths abroad notifications. The annual data for 1996 to 2004 was extracted for sex, age, and cause of death by location for all reports received. RESULTS: There were 2,410 reported deaths in Canadians abroad; reported sex was 32% female and 68% male, average age of 61.7 and 60.4 years, respectively. Recorded causes of death: natural (1,762), accidental (450), suicide (92), and murder (106). Country of death reflected the pattern of Canadian international travel for recreation, business, and ancestral linkages. Average age of natural death (66 years) distinguished it from all other causes of death: accidental (45), suicide (41), and murder (43). CONCLUSION: Natural causes and suicide deaths may be anticipated or planned to occur abroad. The risk of death may be mitigated through personal knowledge and medical assessment and prevention strategies. Deaths due to vaccine-preventable diseases, exotic and infectious diseases were rare in this population. Consular services may be able to provide various types of support. Local laws and customs, as well as international regulations in health and quarantine govern other responsibilities such as funeral services and repatriation of the deceased to Canada.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".