© 2007 Canadian Medical Association or its licensors Commentary D
Bibliographic record
Abstract
All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association. Public funds can be used to pay for health care servicesthat are delivered either by for-profit or not-for profitagencies. A systematic review of patient outcomes in US hospitals by ownership status showed that not-for-profit hospitals tended to produce better results.1 Although there are no Canadian acute care hospitals in the for-profit sector, the issue of interest here is whether the same trend in out-comes applies to for-profit and not-for-profit ownership of long-term care facilities. About 60 % and 30 % of all publicly funded long-term care beds in Ontario and British Columbia, respectively, are in for-profit institutions.2,3 The co-existence of for-profit and not-for-profit providers in the same province creates a “natural laboratory ” for examining their differences. This is particu-larly true because the funding paid by the province to these fa-cilities is tied to resident care requirements and thus the same
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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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.031 | 0.016 |
| Insufficient payload (model declined to judge) | 0.105 | 0.043 |
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".