Bibliographic record
Abstract
<div> Canadian nursing regulators have implemented various innovations to reform regulatory approaches to address workforce challenges, system demands, governance reforms, and a drive for efficiency. Given the significant role that regulators play in influencing patient safety, workforce, and health system outcomes, decision-making must be evidence-informed. This review examined the nature, extent, and range of literature related to nursing regulation in Canada and how the existing scholarship aligns with emerging regulatory and health system trends to inform the development of a research agenda. The review was conducted following the JBI methodology for scoping reviews and with the support of a medical research librarian. A total of 195 sources, including scholarly (n = 156, 80%) and grey literature sources (n = 39, 20%), were included and reviewed. Just over half of the included scholarly sources were empirical studies (n = 80, 51.3%). The number of publications has steadily increased over the last few decades, and the majority of sources were situated in a provincial/territorial context (n = 104, 53.3%), followed by the national (n = 67, 34.4%) and global context (n = 24, 12.3%). The majority of the literature was led by scholars or professional groups unaffiliated with nursing regulators (n = 129, 66.2%). In contrast, nursing regulators led, commissioned, or were involved in a smaller portion of sources (n = 66, 33.8%). The largest category of literature focused on regulatory models, governance structures, and reforms (n = 59, 30.3%); followed by registration and licensure (n = 57, 29.2%); nursing roles and standards (n = 53, 27.2%); conduct, complaints, and discipline (n = 13, 6.7%); continuing competence programs (n = 11, 5.7%); and education program approval/accreditation (n = 2, 1%). The current literature base related to nursing regulation in Canada is largely descriptive and non-empirical and may not provide sufficient evidence to inform regulatory decision-making. This highlights opportunities for regulators and researchers to enhance collaboration to co-create research agendas that can maximize knowledge development and mobilization efforts. </div>
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.710 | 0.062 |
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; both teacher heads agree on what is shown here.
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".