Integrating Ecofeminism Into Canadian Nursing to Tackle Climate Change and Health Issues
Bibliographic record
Abstract
This paper presents an overview of the health impacts associated with anthropogenic climate change and examines the interconnection between human health and the environment. It highlights the nursing profession's stance on environmental issues, drawing attention to the disengagement of nurses from advocacy initiatives related to climate change and how this relates to the nursing metaparadigm. Moreover, this paper supports a multidirectional approach to address climate change solutions, with a particular emphasis on both adaptation and mitigation strategies. Ecofeminism is proposed as a critical framework to address the shortcomings of the metaparadigm and the approaches to climate change solutions. It examines the potential for integrating ecofeminism into nursing research and practice by reconceptualizing the concept of the environment, adopting an ethic of the environment, and critiquing oppressive social structures. The benefits of ecofeminism for nursing include enhancing nurses' responsiveness to the health consequences of climate change, facilitated by using a critical voice that promotes inclusion and collective action.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".