Code poverty: An adaptation of the social‐ecological model to inform a more strategic direction toward nursing advocacy
Bibliographic record
Abstract
The purpose of this discussion paper is to explore how nurses can be strategically poised to advocate for needed policy change in support of greater income equality and other social determinants of health. We adapted Bronfenbrenner's social-ecological model to highlight how four broad pervasive subsystems shape the opportunities that nurses have to engage in advocacy at the policy level. These subsystems include organizations (the microsystem), professional bodies (the mesosystem), public policies (the exosystem), and societal values (the macrosystem). On the basis of this adapted model, we recommend changes among modifiable elements of the microsystem and mesosystem that can help position nurses (ecologically and collectively) to advocate for public policy change and use examples from a Canadian context to illustrate these points. We believe that the ideas arising from this model can be widely used where policy action on the social determinants of health is needed to inform, guide, and frame change efforts and advocacy work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".