The evolution of freestanding children's hospitals in Canada
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present article is to examine the evolution of freestanding children's hospitals in Canada over the past century. The results include documentation of the number of freestanding children's hospitals in Canada that have since closed, merged with other institutions or remained freestanding. Similar data are presented for the United States (US). Also included is an analysis of factors in the internal and external environment that contributed to the changing structure of children's hospitals. METHODS: Sources of information included a review of the literature, publicly available data and statistics on children's hospitals in Canada and the US. RESULTS: Nine of the 16 children's hospitals in Canada were freestanding at one time. Today, only two remain freestanding. Three formerly freestanding children's hospitals have merged with maternal health facilities and four formerly freestanding children's hospitals have merged with adult institutions. Similar trends are seen in the US. CONCLUSIONS: The structure of children's hospitals in North America has changed significantly over the past century. This can be attributed to a number of factors, including the evolution of the health status of children due to medical advances, as well as external forces such as demographics and the rising cost of health care. The impact on the health of children and the mission of children's hospitals in terms of patient care, teaching and research remains to be seen.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 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".