ADVANCED PRACTICE NURSING IN CANADA: REFLECTIONS ON THE IMPLEMENTATION PROCESS IN THE BRAZILIAN CONTEXT
Bibliographic record
Abstract
ABSTRACT Objective: to reflect on the implementation of the role of Nurse Practitioner (NP) in Brazil, based on aspects considered important in the perspective of implementing this role in the country, based on previous experiences in the province of Quebec, Canada. Method: this is a theoretical-reflective study based on information obtained from technical-scientific literature and documents, laws, draft bills or historical records of governmental organizations or nursing councils, considering Canada/Quebec and Brazil as the context of analysis. Based on this, the study is structured around three main axes: historical aspects of the implementation and regulation of the NP role in Quebec; aspects of NP training; and possible challenges and paths in the perspective of implementing this role in the Brazilian context. Results: it is possible to observe similarities between the current situation in Brazil and what nursing experienced in Canada around 60 years ago, particularly in relation to the search for health care for people, especially in remote areas. The Quebec experience shows that the implementation of the NP role has been procedural, with the incorporation of different documents and actions over the years to ensure both guidelines aimed at training and regulating this role, as well as contributing to the inclusion of these professionals in the health system. Final considerations: bringing together experiences from the implementation of the APN in other places, in this case with the context of Quebec in particular, is important in defining the best paths for the health care of the Brazilian population.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.035 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| 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".