Evolution of hospital clinical ethics committees in Canada
Bibliographic record
Abstract
To investigate the current status of hospital clinical ethics committees (CEC) and how they have evolved in Canada over the past 20 years, this paper presents an overview of the findings from a 2008 survey and compares these findings with two previous Canadian surveys conducted in 1989 and 1984. All Canadian hospitals over 100 beds, of which at least some were acute care, were surveyed to determine the structure of CEC, how they function, the perceived achievements of these committees and opinions about areas with which CEC should be involved. The percentage of hospitals with CEC in our sample was found to be 85% compared with 58% and 18% in 1989 and 1984, respectively. The wide variation in the size of committees and the composition of their membership has continued. Meetings of CEC have become more regularised and formalised over time. CEC continue to be predominately advisory in their nature, and by 2008 there was a shift in the priority of the activities of CEC to meeting ethics education needs and providing counselling and support with less emphasis on advising about policy and procedures. More research is needed on how best to define what the scope of activities of CEC should be in order to meet the needs of hospitals in Canada and elsewhere. More research also is needed on the actual outcomes to patients, families, health professionals and organisations from the work of these committees in order to support the considerable time committee members devote to this endeavour.
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 | 0.022 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".