Perioperative Nurse Recruitment: An <scp>OR</scp> Placement Program for Fourth‐Year Nursing Students in Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nursing associations have predicted a worldwide shortage of perioperative RNs as more nurses reach retirement age. Additionally, the lack of perioperative exposure during undergraduate nursing programs is contributing to the failure to attract recently graduated nurses to this field. In 2019, multiple hospital sites within the St. Lawrence College network in Ontario, Canada, expressed difficulty recruiting perioperative RNs and expressed an interest in collaborating with the college to increase exposure to the perioperative specialty and recruit students to their ORs after graduation. The college has run a successful preceptor-supported OR placement program for fourth-year baccalaureate nursing students since 2019. Eleven out of thirteen students were hired into the OR after their 2020-2021 placement program. This article outlines the steps taken to initiate this program as well as results of a formal program evaluation conducted in 2021, including detailed feedback from participating students, preceptors, and leaders at the involved hospitals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it