Advancing Excellence in Community Health Nursing Through Evidence-Based National Standards of Practice
Bibliographic record
Abstract
Background: Current standards of practice are necessary to ensure safe nursing practice in Canada and across the world. This article aimed to describe and present findings from the rigorous review process undertaken to update the 2011 Canadian Community Health Nursing Standards of Practice. Method: A revision process included a scoping review of the literature, focus groups, and a modified Delphi method. Results: Through the inclusive consultation process, 495 community health nurses enhanced the content of the standards with respect to cultural safety, cultural humility, Indigenous health and ways of knowing, health equity, and evidence-informed practice. Conclusion: This comprehensive revision process can guide other nursing specialty groups developing or revising specialized practice standards in Canada and across the world. [ J Contin Educ Nurs . 2021;52(4):168–175.]
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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 | 0.238 | 0.353 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.007 | 0.010 |
| 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".