Leadership, Education and Awareness: A Compassionate Care Nursing Initiative
Bibliographic record
Abstract
The Canadian Nurses' Association Code of Ethics (2008) and the College of Registered Nurses of Nova Scotia (CRNNS) Standards of Practice for Registered Nurses (CRNNS 2011) identify the provision of safe, compassionate, competent and ethical care as one of nursing's primary values and ethical responsibilities. While compassion has historically been viewed as the essence of nursing, there is concern that this has become an abstract ideal, rather than a true reflection of nursing practice. This paper describes a compassionate care initiative undertaken by the CRNNS and the initial outcomes of these educational workshops. This work is informed by an exploration of the multiplicity of factors that have brought this issue to the fore for nursing regulators, educators, administrators, the public as well as front-line staff. The two most significant areas of learning reported by workshop participants included understanding the connection between mindfulness, non-judgmental care and compassion/self-compassion and recognizing possibilities for action related to compassionate care, even in the face of personal and environmental constraints. Implications for nursing regulators and leaders include consideration of their roles and responsibilities in supporting nurses to meet professional practice standards, such as provision of compassionate care.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| 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".