Bibliographic record
Abstract
Innovation is essential for advancing and sustaining healthcare systems, particularly in hospitals. While innovation offers solutions to challenges such as chronic disease management, access to care, and patient safety, it also introduces significant ethical dilemmas for health leaders. This column explores the broad ethical issues associated with healthcare innovation, focusing on resource allocation, support for diverse healthcare professions, equitable access to care, and the emphasis on technology-based innovations. It highlights the complexities of funding innovation through government, private sector, universities, donors, and the unpaid work of healthcare providers. The column also addresses the disparities in innovation support across different professions and the potential for innovation to exacerbate healthcare inequities. Potential solutions are proposed, including the establishment of interdisciplinary councils, dedicated innovation funds, and public-private partnerships. By prioritizing ethical leadership and balanced innovation strategies, health leaders can ensure that advancements benefit all stakeholders, fostering a more equitable and sustainable healthcare system in 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 | 0.057 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.077 |
| Scholarly communication | 0.029 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.019 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".