A Critique of the Undergraduate Nursing Preceptorship Model
Bibliographic record
Abstract
The preceptorship model is a cornerstone of clinical undergraduate nursing education in Canadian nursing programs. Their extensive use means that nursing programs depend heavily on the availability and willingness of Registered Nurses to take on the preceptor role. However, both the health service and education industries are faced with challenges that seem to undermine the effectiveness of the preceptorship clinical model. Indeed, the unstable nature of the clinical setting as a learning environment in conjunction with faculty shortages and inadequate preparation for preceptors and supervising faculty calls us to question if the preceptorship model is able to meet student learning needs and program outcomes. In a critical analysis of preceptorship, we offer a deconstruction of the model to advance clinical nursing education discourse.
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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 | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.053 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".