Evolving trends in nurse regulation: what are the policy impacts for nursing's social mandate?
Bibliographic record
Abstract
We recognize a paradox of power and promise in the context of legislative and organizational changes in nurse regulation which poses constraints on nursing's capacity to bring voice and influence to pressing matters of healthcare and public policy. The profession is at an important crossroads wherein leaders must be well informed in political, economic and legislative trends to harness the profession's power while also navigating forces that may put at risk its central mission to serve society. We present a critical policy analysis of the impact of recent regulatory trends on what the International Council of Nurses considers nursing's three 'pillars' - the profession of nursing, socioeconomic welfare of nurses and nurse regulation. Themes surfacing from this analysis include regulatory discontinuity, a tightening of regulatory control, and an increasingly managerial governance culture. These themes illuminate insights and strategies required to renew and revitalize the social mandate of our profession amidst a climate of urgency in the questioning of nurse scholars with respect to the future of the profession. At this historic juncture, nurses must clearly understand the implications of legislative and organizational regulatory changes to ensure the profession contributes to full capacity in achieving health and health equity globally.
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 | 0.025 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".