Rural surgical services in two Canadian provinces.
Bibliographic record
Abstract
OBJECTIVE: Contrast alternative health delivery systems and the use of differently trained physician providers in the supply of surgical services to rural residents in 2 Canadian provinces. METHODS: Four surgical procedures (carpal tunnel release, inguinal herniorrhaphy, appendectomy and cholecystectomy) provided to rural residents of Alberta and Northern Ontario were identified between 1997/98 and 2001/02. Surgical staff were identified as specialists or non-specialists. Rural populations were mapped into the catchment areas of rural acute care facilities. Rural surgical programs were characterized by the level of surgical service available locally. RESULTS: Alberta and Northern Ontario have a similar number of rural surgical programs staffed by Canadian-certified general surgeons (10 and 12, respectively). However, Alberta has 27 smaller rural surgical programs staffed by non-specialist surgeons and Northern Ontario has only 4. These non-specialist surgeons play a significant role in Alberta, often in collaboration with specialist surgeons. In Northern Ontario the non-specialist surgeons play a minor role. The small rural surgical programs in Northern Ontario that are staffed by specialist surgeons are significantly more successful in retaining the local surgical caseload compared with similar programs in Alberta. CONCLUSIONS: The principal differences between Alberta and Northern Ontario in the delivery of rural surgical services are the greater number of small rural surgical programs in Alberta, and the substantial role of non-specialist surgical staff in these programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".