A Comparative-Legal Study of the Regulation of Independent Nurses in the USA, Canada, and France
Bibliographic record
Abstract
Introduction: The ever-increasing societal needs for quality and efficient healthcare, both nationally and globally, highlight the importance of independent practice nurses. Achieving clarity and legal certainty in their activities is essential for providing effective healthcare. In this regard, a comparative-legal study of the experience of other countries in the normative regulation of independent nursing practices holds significant scientific and practical importance. Aim: The purpose of the current study is to conduct a comparative-legal analysis of the regulatory framework governing independent practice nurses in the USA, Canada, and France. Materials and Methods: A documentary method was applied, involving a comparative-legal analysis of the legislation of the USA, Canada, and France on the researched problem. Results and Discussion: The comparative-legal analysis of the legislation in the USA, Canada, and France regarding the regulatory framework for independent practicing nurses revealed that the establishment of independent nursing practices and their activities is clearly and systematically organized by the legislatures of these countries. Although different methods are employed, a unified approach to addressing the problem emerges. According to the legal definitions analyzed, registered nurses assist individuals, families, groups, and communities in achieving optimal physical, emotional, mental, and spiritual health and well-being. Conclusion: Societies face similar challenges, and while they may employ different means, they often achieve comparable solutions. Foreign legal systems may use different terms, organizational structures, and institutional logic, yet they provide analogous legal frameworks. The applied comparative-legal approach highlights opportunities for regulating or improving the relevant institute within Bulgarian legislation.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".