Bibliographic record
Abstract
N umerous high-profile events in several provinces related to quality of care have illustrated that governing bodies are ultimately accountable for the safety and quality of care in our organizations.These events have served as wake-up calls to many boards, which are seeking guidance to better understand and live up to their responsibilities.This issue of Healthcare Quarterly addresses the need to clarify and support the board's role for quality and safety.Many boards have traditionally relied upon management or medical staff to look after quality and focused on financial resources and relationships with key stakeholders.Today there is increasing awareness that healthcare boards cannot abdicate their responsibilities for ensuring quality and safety and need to take specific actions to address these duties.This need is recognized by the Canadian Patient Safety Institute (CPSI), which is sponsoring development of a tool kit to assist boards in carrying out their roles related to quality and safety.I am honoured to co-lead this work with Jim Nininger, former president of the Conference Board of Canada.The governance tool kit involves a rich set of resources and related training, and it will be available by spring 2010.In this issue, Ross Baker and his colleagues summarize their research regarding effective governance for quality and safety in the Canadian healthcare system.They confirm that many boards are unclear and poorly equipped to fulfill their roles.Baker and his co-authors suggest reasons for this situation and propose a framework to assist boards in providing effective governance.The CPSI tool kit is based on this framework.
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 | 0.026 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.035 | 0.026 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".