Leadership for Ethical Policy and Practice (LEPP): Participatory Action Project
Bibliographic record
Abstract
Within Canada's fast-paced, ever-changing healthcare environment, providers are experiencing difficulty practising according to their professional ethical standards, leading many to experience moral or ethical distress. Limited attention has been paid to improvements in the ethical climate in healthcare settings in research focusing on nurses' workplaces. In this three-year study, we focused on how the ethical climate in healthcare delivery can be improved and how the use of participatory action research methods can lead to continued enhancements and lasting changes in services delivery. Together, we developed strategies for taking action, aimed at improving the quality of the work environment. This action involved both nurses in direct care and those in key leadership positions (CNOs or their equivalents). Through the active participation of those for whom the research-based change was intended, these strategies were tested in various sites across British Columbia and can be used as templates or designs for use in other settings. A key component of the success of the projects and action plans that were created was the integral involvement of nurse leaders through all phases.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.140 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.010 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".