The Use of a Clinical Resource Nurse for Newly Graduated Nurses in a Pediatric Oncology Setting
Bibliographic record
Abstract
The pediatric oncology nursing unit at the Alberta Children's Hospital experienced a large influx of new staff nurses between May 2008 and November 2008. There were 16 in total, and only a few had previous experience, whereas the majority was newly graduated nurses. As a solution to the high numbers of new staff nurses, the role of a Resource Nurse was developed as a temporary position to assist new staff nurses with their patient assignment, prioritize their day, and deal with complex patient procedures/treatments. Also, the Resource Nurse assisted all staff on the unit in dealing with increased patient acuity, chemotherapy administration, acuity issues, family teaching, and complicated family situations. A total of 55 prebooked shifts were scheduled from November 2008 to January 2009. A questionnaire was handed out to the staff nurses as a means to determine the effectiveness of having a Resource Nurse work on the unit. Twenty-three nurses responded by filling out the confidential questionnaire. Overall, respondents reported that the Resource Nurse was beneficial to their practice on the unit.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".