Cause Celebre: Georgetown University Hospital’s Journey to Magnet
Bibliographic record
Abstract
Designation as a magnet organization by the American Nurses Credentialing Center is a coveted distinction for health care organizations. These organizations experience fewer problems with nurse recruitment and retention because they have been found to be good places to practice professional nursing. Better patient outcomes have also been documented in these organizations. In this article, the authors recount their 3-year experience leading an organization successfully to become the first magnet organization in the nation’s capitol. The magnet application and review process is linked to the core principles of organization development. The authors conclude with policy recommendations for other organizations that are just beginning their journey to achieving magnet status and with reflections on leadership and the value created by participating in the magnet program.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.028 | 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".