Deceased Organ Donation Registration and Familial Consent among Chinese and South Asians in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: For various reasons, people of Chinese (China, Hong Kong or Taiwan) and South Asian (Indian subcontinent) ancestry (the two largest ethnic minority groups in Ontario, Canada) may be less likely to register for deceased organ donation than the general public, and their families may be less likely to consent for deceased organ donation at the time of death. METHODS: We conducted two population-based studies: (1) a cross-sectional study of deceased organ donor registration as of May 2013, and (2) a cohort study of the steps in proceeding with deceased organ donation for patients who died in hospital from October 2008 to December 2012. RESULTS: A total of 49 938 of 559 714 Chinese individuals (8.9%) and 47 774 of 374 291 South Asians (12.8%) were registered for deceased organ donation, proportions lower than the general public (2 676 260 of 10 548 249 (25.4%). Among the 168 703 Ontarians who died in a hospital, the families of 33 of 81 Chinese (40.1%; 95% CI: 30.7%-51.6%) and 39 of 72 South Asian individuals (54.2%; 95% CI: 42.7-65.2%) consented for deceased organ donation, proportions lower than the general public (68.3%; 95% CI: 66.4%-70.0%). CONCLUSIONS: In Ontario, Canada Chinese and South Asian individuals are less likely to register and their families are less likely to consent to deceased organ donation compared to the remaining general public. There is an opportunity to build support for organ and tissue donation in these two large ethnic communities in Canada.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".