Providing after-hours on-call clinical coverage in academic health sciences centres: the Hospital for Sick Children experience.
Bibliographic record
Abstract
An increasing number of admissions of patients requiring complex and acute care coupled with a decreasing number of pediatric postgraduate trainees has caused a shortage of house staff available to provide after-hours on-call coverage in the Department of Pediatrics at Toronto's Hospital for Sick Children. The Clinical Assistant program created to deal with this problem was short on staff, did not provide adequate continuity of care and was becoming increasingly unaffordable. The Clinical Departmental Fellowship program was created to address the problem of after-hours clinical coverage. The program is aimed at qualified pediatricians seeking additional clinical or research training in one of the subspecialty divisions in the Department of Pediatrics. We describe the hiring process, job description and evolution of the program since its inception in 1996. This program has been mutually advantageous for the individual fellows and their sponsoring divisions as well as the Department of Pediatrics and the Hospital for Sick Children. We recommend the introduction of similar programs to other academic medical departments facing staff shortages.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".