New graduate registered nurses' perceptions of transitioning to professional practice after completion of the new graduate guarantee orientation program
Bibliographic record
Abstract
In Canada, the projected shortage of Registered Nurses (RNs) by 2022 is 60,000. This shortage is accentuated as Canadian New Graduate Registered Nurses (NGRNs) experience difficulties transitioning to professional practice. This study sought to explore NGRNs’ transition experiences in the 12 months post New Graduate Guarantee (NGG) orientation informed by Charmaz’s grounded theory methodology. Semi-structured interviews were conducted with ten NGRNs working in one urban, academic hospital in Ontario. The theory’s overarching category Discovering Professional Self highlights the NGRNs’ transition experiences as a progressive process with transitory setbacks. The early part of the process, described as Surviving without a Safety Net, involved Experiencing Fear, Figuring it Out, and Learning on the Job. In the later part of the process, the NGRNs’ experienced a Turning of the Tables as they described Being Trusted, Gaining Confidence, and Feeling Comfortable in their professional role. Recommendations focus on strategies to enhance NGRNs’ transition experienc
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".