The Work of Preparing Canadian Nurses for A Licensure Exam Originating from the USA: A Nurse Educator’s Journey into the Institutional Organization of the NCLEX-RN
Bibliographic record
Abstract
The licensing exam for registered nurses in Canada has recently been changed from a Canadian developed, owned and delivered exam to the National Council Licensure Examination for Registered Nurses (NCLEX-RN) which originates from the United States. Rationale for this exam change focused on transitioning to a computer-based exam that has increased writing dates, with increased security, validated psychometrics, increased exam result delivery, and an anticipated decrease in expense to students. Concerns have arisen around the acceptance, implementation and delivery of this exam to Canadian nursing students that reflects the broad Canadian landscape of education and nursing practice. The experience of a Canadian nurse educator in working to facilitate students' transition to this exam is addressed using an institutional ethnographic lens. Finally, we come to conclusions about the importance of countries utilizing licensing exams that reflect their nursing education and practice.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.012 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".