The Triple Planetary Health Crisis: Nursing Leadership in Championing the Integration of Planetary Health in Canadian Nursing Education
Bibliographic record
Abstract
During the past decade, planetary health has emerged as a scientific field of practice and global movement in response to the major disruptions to our world, such as catastrophic floods, droughts, wildfires, heat domes, and extreme heat, affecting the health and well-being of humans and the planet. The concept of planetary health has been increasingly acknowledged by Canadian nurse educators, and globally, about the importance for integration in baccalaureate and graduate nursing curricula. In 2022, the Canadian Association of Schools of Nursing updated its National Nursing Education Framework to include planetary health. There is, however, a gap in the Canadian literature of the process for integrating planetary health content in an already-full nursing curriculum. This paper highlights the pivotal historical timeline of the planetary health movement alongside the emergence educational initiatives, such the Call to Action in 2019 in the Canadian context and the global movement to address the planetary health crisis. The author describes how a nurse educator champions and leads the integration of planetary health content in a Canadian baccalaureate nursing program, while addressing the barriers to and facilitators of curricular change. It is important that nurse educators receive further professional development in equipping them with an understanding of planetary health and how to integrate and actualize this content in the nursing curricula. Planetary health knowledge is essential in preparing the next generation of nursing students so they can better address and mitigate the catastrophic impact of the planetary health crisis so all can flourish.
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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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.055 | 0.018 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".