Nurses Day: sharing care stories to combat fatigue
Bibliographic record
Abstract
Last month was International Nurses Day. On the 12th of May, the birthday of British nursing pioneer Florence Nightingale, nurses from the UK, and from as far as Canada, the USA and Hong Kong shared personal nursing care experiences as part of an initiative to combat compassion fatigue. Compassion fatigue is a particular problem in the nursing profession because of the amount of emotional energy required to care for patients, in addition to the many physical and mental demands. The initiative featured a series of stories from nurses in an effort to promote the importance of sharing care experiences with fellow health professionals and reflecting on those experiences in order to top up emotional reserves and continue providing the highest quality compassionate nursing care possible. Contributions from three cardiac nurses are featured here. The first is a short editorial with a nurse's thoughts about compassion fatigue in nursing. The following two are nursing care experiences, and the rest of the series can be seen at http://www.ayshamendes.com
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".