We’re Open: Caring for the Walking Well in a Rural Emergency Department
Bibliographic record
Abstract
Emergency departments (EDs) are increasingly unable to cope with patient volume, leading staff to question the arrival of those seeking non-urgent care. However, these patients ideally should be afforded appropriate management and treatment. In 2014, the Carbonear General Hospital ED in Newfoundland and Labrador took decisive action, engaging front-line staff and shifting the focus of care away from why patients were visiting to prioritize how best to treat those who did. By 2019, the ED had not needed to resort to hallway medicine, despite a visit volume that increased to 30,000 patients over five years, and staff grew into a close-knit, quality improvement and community force. From this experience, it is evident that small investments in education and system redesign can shift attitudes toward ED care for patients, and provide support for primary care in the community. It has already started in one hospital — we’re open for assistance with primary and non-urgent care.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".