There Is Never Really Just a Simple Choice: Nurse Advocacy for Gender‐Transformative Cardiovascular Disease Prevention
Bibliographic record
Abstract
Cardiovascular disease remains the leading cause of mortality for women globally and presents a considerable health burden despite decades of awareness campaigns. Messaging in these campaigns includes a significant focus on individual lifestyle behaviour modification for the prevention of cardiovascular disease, with health promotion campaigns and clinical organizations stating that 80%-90% of cardiovascular disease is preventable. Public messaging campaigns on prevention strategies have historically lacked differentiation for gender. As a result, they can overlook the complex factors that may hinder women from achieving the suggested lifestyle modifications, including the long-promoted trio of diet, exercise and tobacco. The non-coherence between the logics guiding cardiovascular disease prevention messaging and the competing logics of everyday life for women deserves attention. In this paper, we explore the assumptions evident in common cardiovascular disease prevention narratives and propose that nurses are well-positioned to advocate for gender-transformative health promotion.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.011 |
| 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".