Policy Advocacy and Nursing Organizations: A Scoping Review
Bibliographic record
Abstract
Policy advocacy is a fundamental component of nursing's social mandate. While it has become a core function of nursing organizations across the globe, the discourse around advocacy has focused largely on the responsibilities and accountabilities of individual nurses, with little attention to the policy advocacy work undertaken by nursing organizations. To strengthen this critical function, an understanding of the extant literature is needed to identify areas that require further research. We conducted a scoping review to examine the nature, extent, and range of scholarly work focused on nursing organizations and policy advocacy. A systematic search of six databases produced 4,731 papers and 68 were included for analysis and synthesis. Findings suggest that the literature has been increasing over the years, is largely non-empirical, and covers a broad range of topics ranging from the role and purpose of nursing organizations in policy advocacy, the identity of nursing organizations, the development and process of policy advocacy initiatives, the policy advocacy products of nursing organizations, and the impact and evaluation of organizations' policy advocacy work. Based on the review, we identify several research gaps and propose areas for further research to strengthen the influence and impact of this critical function undertaken by nursing organizations.
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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 | 0.022 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.033 | 0.037 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".