Developing Palliative Care Competencies for the Education of Entry Level Baccalaureate Prepared Canadian Nurses
Bibliographic record
Abstract
Educational preparation of health professionals for Palliative and End of Life Care (PEOLC) is inadequate, and nurses are no exception. In 2004, the Canadian Association of Schools of Nursing struck a Task Force to develop PEOLC competencies to address this issue. The development of national PEOLC nursing competencies involved a multi-step, emergent, interactive, and iterative process. An overarching principle guiding this process was building national consensus about the essential PEOLC specific competencies for nurses among experts in this field while simultaneously generating, revising, and refining them. There have been three stages in this iterative, multi-step process: 1) Generating a preliminary set of competencies, 2) Building a national consensus among educators and experts in the field on PEOLC specific competencies for nurses, and 3) Refining the consensus based competencies for curriculum development. Ongoing follow up work for this project is focusing on the integration of these competencies into nursing curricula.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".